diff --git a/LSTM_GRU_Suara_Hati.ipynb b/LSTM_GRU_Suara_Hati.ipynb
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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/mhmmdluthfi/data-structurce-classroom-2020/blob/master/LSTM_GRU_Suara_Hati.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Re3rS6KaiD37"
+      },
+      "source": [
+        "# Klasifikasi Suara Jantung"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "JGzm_jLliD4C"
+      },
+      "source": [
+        "## A. Mengimpor Library yang diperlukan"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "FTkwtmJgiIpr",
+        "outputId": "1ce9dd3e-7f58-4d9d-877c-69665e52185b"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Mounted at /content/gdrive/\n"
+          ]
+        }
+      ],
+      "source": [
+        "from google.colab import drive\n",
+        "drive.mount('/content/gdrive/')\n",
+        "DATA_DIR = '/content/gdrive/MyDrive/heart_sound'"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "YkuzV-hMiD4D"
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np # linear algebra\n",
+        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
+        "import os # to use operating system dependent functionality\n",
+        "import librosa # to extract sound features\n",
+        "import wave # read and write WAV files\n",
+        "import matplotlib.pyplot as plt # to generate the visualizations\n",
+        "from sklearn.model_selection import train_test_split\n",
+        "from sklearn.metrics import classification_report\n",
+        "from sklearn.metrics import confusion_matrix\n",
+        "from sklearn.metrics import roc_curve, auc, roc_auc_score\n",
+        "import seaborn as sns\n",
+        "import IPython.display as ipd\n",
+        "import tensorflow as tf\n",
+        "\n",
+        "from PIL import Image\n",
+        "import matplotlib.pyplot as plt\n",
+        "import matplotlib.image as mpimg\n",
+        "import seaborn as sns\n",
+        "from scipy import interp\n",
+        "from itertools import cycle\n",
+        "\n",
+        "import keras\n",
+        "import tensorflow\n",
+        "from tensorflow.keras.utils import to_categorical\n",
+        "from tensorflow.keras.models import Sequential\n",
+        "from tensorflow.keras.layers import *\n",
+        "from tensorflow.keras.optimizers import RMSprop"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "W2DyBzwtiD4G"
+      },
+      "source": [
+        "## B. Membaca Dataset & Ekstraksi Fitur"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "p8oi9npb7UjH"
+      },
+      "source": [
+        "Suara Jantung Sehat"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "sSqv5Tdb5BOW",
+        "outputId": "23b2ded2-fe76-468b-a1b4-bf038db82e23",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 76
+        }
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<IPython.lib.display.Audio object>"
+            ],
+            "text/html": [
+              "\n",
+              "                <audio  controls=\"controls\" >\n",
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\" type=\"audio/x-wav\" />\n",
+              "                    Your browser does not support the audio element.\n",
+              "                </audio>\n",
+              "              "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 3
+        }
+      ],
+      "source": [
+        "# heart it\n",
+        "healthy_file=DATA_DIR+\"/train/healthy/a0009.wav\"\n",
+        "ipd.Audio(healthy_file)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "fT5FGyL65vcN",
+        "outputId": "4a09e819-6aa9-4df7-84d1-2c09084e3eb4",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Sampling (frame) rate =  2000\n",
+            "Total samples (frames) =  (71611,)\n",
+            "[-134 -225 -278 ...  211  291  194]\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Load use scipy\n",
+        "from scipy.io import wavfile\n",
+        "rate, data = wavfile.read(healthy_file)\n",
+        "print(\"Sampling (frame) rate = \", rate)\n",
+        "print(\"Total samples (frames) = \", data.shape)\n",
+        "print(data)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "kln3MxIf6FsX",
+        "outputId": "5ddf1d21-ab55-4443-9773-12e87e8f1919",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 211
+        }
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1152x216 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "# plot wave by audio frames\n",
+        "plt.figure(figsize=(16, 3))\n",
+        "plt.plot(data, '-', );"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "l2Kai3XQ7bTp"
+      },
+      "source": [
+        "\n",
+        "Suara Jantung Tidak Sehat"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "UCIaAv-z7HEF",
+        "outputId": "5913ae3d-d869-4512-ba62-9a1632eb68e6",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 76
+        }
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<IPython.lib.display.Audio object>"
+            ],
+            "text/html": [
+              "\n",
+              "                <audio  controls=\"controls\" >\n",
+              "                    <source 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+              "                </audio>\n",
+              "              "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 6
+        }
+      ],
+      "source": [
+        "unhealthy_file=DATA_DIR+\"/train/unhealthy/a0001.wav\"\n",
+        "ipd.Audio(unhealthy_file) "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Arv8yz7u7Ir2",
+        "outputId": "2bae1527-5f55-43bc-ce03-a96bf54e46bf",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Sampling (frame) rate =  2000\n",
+            "Total samples (frames) =  (71332,)\n",
+            "[ -69 -135 -104 ... -285 -257 -187]\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Load use scipy\n",
+        "from scipy.io import wavfile\n",
+        "rate, data = wavfile.read(unhealthy_file)\n",
+        "print(\"Sampling (frame) rate = \", rate)\n",
+        "print(\"Total samples (frames) = \", data.shape)\n",
+        "print(data)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "f8kp7Vp47K0H",
+        "outputId": "6298e0fe-6813-4a2f-ad7f-de5972dee252",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 211
+        }
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1152x216 with 1 Axes>"
+            ],
+            "image/png": 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bC3f7hElu0kQwCOQ9Ef/WySyohP24RUh2KyXvAyHgRqWnG+tMuBsaM5yFhFnCUdz1Ajs/w9Fa072UdoGOFnjBw+6e5KQFlbCP/MJiXMorVPwuGM+OugdBBBd654IDCbOEo5ClQIobW6OsP0I3CrFurHNZoqy/U0DZVJ7c/MVatJu4IOjXdTIBVLiy6egFnL+Up3kOrU8IonRAwmwZJhiZGd04VTjrdu2eFimDa80yjVLXpO2ZCMCd47gTlAiF1lpk6/GL9lXGBMFQHISbAu2GKWsx6tN/FL+jUY0gShckzBKO4iLZrUxaCgh93NSHBUpLrPrJizl49a/dKC4ObgU+XXoACePmIjtf2SU0UOxe+JdFyxsRHoSzwuvExRzN7+l1IZyGxuTgQMIs4Sjhpq0NNW5sDXqGHsJhUtp/JhNfrTrsSNnhqMx58tetmLb6CDYfSwvqdX9YdxQAkJ5T4Ej54dCXjBAUi55L2sJpgjPOUmMTZY+ComLsSEl3pGzOORLGzcWb8/bonOjI5S1z8OwlLNt7NtTVsA0SZglX4faFj5vqH47CTSgJh0d30+dr8drcPUG3VIaKwhDdZzhbm7Rwk+LJjeOLW7MZB6M/u2luIwLnp/VHMWX5oVBXwxCT5uzC1Z+uxvEL2baXLfT7L1Y6o2R2iiHvr8Dd324MdTVsg4RZwlHcOME5WmcXtkc4Mejd5ej62qKgXjOcHllmrsdSqCfk2dWHwyVLbjg9g3DEacHQTbH+zuJCCVwEPUYPzI2aFIt8ssQTMmH3O/zC/3birb/32lqmU2xL8cSqp2Xn655rtp2Mnm229XPyi3BSx02eKIGEWYIWil6CMb25yXIiEE4LoMPns3D+kv6EVFqJ8C7CCouLHbuGG/uoGQ6evYQ+k5fiXKZ2plPAub7vlnLdaqF2I+E0zrodUr6U8P7i/QCAvELn5oyyjF5fszqfjvlmA3pPXmrpt3o4lQsilJAwW4ZxYzxUaV9oE+GH0wsjM+WXCLP2TKD93l6KH73xoXYILk9M34Lmz88LuBw5dg5VX/9zBCcu5mDBrtPq13Pa0unQOObG0dGNY3q4yUrvLtiHhHFzsfOEM3GBWgTier3/TCb+3qn+HlqljERh6LJ07xlfXw1VyEY4cY8Bt1qz77ZTrbrhyAWHSgbu/TbJsbJDBQmzhKOYXaiczcjF2cxch2pjFOcG/XBbBBEmCANrWoR3xC4sssfN+PiFHLw4a6fnNwo3aFamm7X1pCOLJjtLNLO9ilte13C1oC7fdxY5+UWhroZthKt36qfLDgIARn6yWvF7J8MFAmmSoR+sxEM/brKtLgLFBm+0tM/H7y3c7/tM1moY8uoqC6209nBqqKtgOwELs4yxhoyxZYyx3YyxXYyxx73HqzHGFjHGDnj/r+o9zhhjHzPGDjLGtjPGOovKGuM9/wBjbEygdSNCj9nxs/sbS9D99SVISnZOK6WGkwsVNyYO8e1DHOJ6hAvhYE0ThJYiB7XsSoJRqKxnTrySgnVbqwmt7CeamVuAF/63A1l5+i5czrkZ27zlTwAPYO/pDNz1zUZMmrPLvgoRlghTGdwx9ITZkvm4dM9u4mZwy52mZxcgPduZLPKA/WOkXnGBXq6sJHsMFDsss4UAnuactwHQE8AjjLE2AMYBWMI5bwFgifdvABgBoIX33wMApgAe4RfARAA9AHQHMFEQgAlncVJjZ7XkGz9fq1yeS99rK4tjIjyw+sSEZE265VvoE3qLMCMlql1XXHa4WqICQbg/u+9t6srD+Gn9MXy7JtlAHZwhnEaXC14ryNELWYrfh6s12Qjh1M6EPw6mFADn3JXzuFuqPODdZej4ykLHytdTBJtPAGXUC8DaA8gwuI4o6wQszHLOT3HON3s/ZwLYA6A+gFEAvvOe9h2Aa72fRwH4nntYB6AKY6wugGEAFnHOL3DO0wAsAjA80PoR6gQnXX/4jKB5hUVYb8C9wskqh09rEE4yf8cptJ+0ENuOX9Q911KfsKEjyed0NwsXVrD7bktzTJqVMTGvyCNRlIuKtLk2ocPXZ8JoXjODFUvktZ/9gyemb9EvO4zaxKibsRWajJ+HJuPtzwvgBFz1j8DILXAudCDNQassYCTfhDmc7vadXgnu7g1uxdaYWcZYAoDLAawHUJtzfsr71WkAtb2f6wM4LvpZiveY2nHCApxzzEg6jksGXN7KCm/O24vRU9dh98mMoF/b57JrcuDbciwNwz9c6UiSDD1KrMnmf5tbUGQoW6wbsHL/Kw+cBwDssDkhi7AY1ZObjCwsxQs+vbjGMFqn2saE2btU+6iV99XcuQ65rNudzTgAif9chqdtI8qWjiQsCeQ5bj1+EbO2nnSmcIfQdTMOUj1CjXicsdOl+vk/dthWVjAQdwcnFR2K1w7q1coutgmzjLFKAH4H8ATnXCItcM8bZdszZYw9wBhLYowlnTt3zq5iSxWbj13E2JnbMcGb3CVU2P0iB1LewbOXAACpWfYKWZxz7DrpTBbJ6/67BntPZzqSJMNJOry8EN1eX2xrmV+scGaD9szcAkNJaszMgWbWd1YEJjvcjMWT+uT5e1TOKt3LvsPnLoXkumbHseJijpS0bNXvS/pbeCydMnMLMPb37YbOLY2KEisEox3KSltn5pISX46djiPbQ5A12y70FcHmyisr71S4Y4swyxiLhkeQ/Ylz/of38Bmv+zC8/5/1Hj8BoKHo5w28x9SO+8E5n8o578o571qzZk07bqHUISzOz2SoZwYORKG6+sB5fGckNiyMXvSICO1tTQQ3S7NV/mHdUSR+vBprDp7XPbe0J5wAPH0v34E97d5ftF//JAu0n7QQrV/6G4d0BBvn4hwtxMzaUBlxGeez8hWP+44FfrmAuEklht4K4vtzIpGWE94wL8zagb5vLcO+05m2l73paJruli5m+6i4DcJpDjDCZS/Ox7Wf/aP4nVuT4gUlpMjxKxjHqf05ncKpOFxJAii3vYgOYbdl1nDMrK1XJeTYkc2YAZgGYA/n/H3RV3MACBmJxwCYLTp+pzercU8A6V535AUAhjLGqnoTPw31HiMs4GQqfgC4fdp6TDSSpTKM3uAIX5vYW6k9pzyOCOs19gULM8OJMSxmfHzQISuy0003+L0VKte1fmVjiZjMl6s3IRspU1xGYZGy8sHpcSTUFDggzE5ZfggnL+ZonmO2PX/Z4InA0YvBtvKcbpiyRn1LF4tCUEQYup4aJa+wGFtV2tmuuyLBIjwIl8fw5K9bHYnDFc9ddt6qm/sv19Gzm53v9bMZO99WavN3WcIOy2wfAHcAGMQY2+r9dxWAyQCuZIwdADDE+zcAzANwGMBBAF8CeBgAOOcXALwKYKP33yveY4QFhLVEkZG9FB1NeOTeQc84nsb+aMkBpF5Si8Hz/F8WWmPlfmdc/900gTqVKEYozY5ixXJcgWjfWrEcYnXxbsRLIVSIm87OPiUe645dUHcJ9quEAQZe5vFAql6pnOL3vvh2c8U6hhFZtiyNiXJCNZQFctmzCl5eh89dcudCOsyULUJMcnqOvcmPxGO8nX3Oqe4rhILZjfhx26EIFrN8X+hDHd+YtzfUVQg5dmQzXs05Z5zzDpzzTt5/8zjnqZzzwZzzFpzzIYJg6s1i/AjnvBnnvD3nPElU1tec8+bef98EWreyjKBR1xqy7RjO9fbAsnvSdlKgsWqFEg+UF1UmI58Lc1lcuZUSzPQ9p2JmjReqf4p4Utd3vTJXydu+Wm/q/GBipL0DtUjrbv9gsj1ZiBffgcSR2d298wuLMW31kZAKUVb6hcT1WqlMJ8V6G7rP9VPWSP4+m5GLQe+twC5vQsVAxjE3KSqdpOPLC3ExO1//RIM4lQDKKYa8r+wdZSd2uxk/8vNmQ+c52cXXGtilo7RjazZjwjybjl7ABw7FAgIe11cn4sIE9Cy/4Th82h0/xFQ+K+GGCUUg3LZqCdl6x3vdYg7Tm7kbcjO20Cd0tcsGylRztxIXHWohSkwwF7yB3rbu9g8O3Uq4yATiOcfu5zZt9RG8+tdu/LT+mK3lGiGQO/m3KPzCjcJbSprUdV5NcWsFN1qqneKaT5Xjta3AVf+ws2B3UYp3UCvTkDAbYm6YshYfLTlge7nixezvm1NsLXvOtpI0/XZvQB0M7BYoxfFhqov/8JEJfHy3JhnHUnXcIRE+C+Rgp9RX4uiFLFPn2/nYM3ILfIm17HEzFgsc2gJcGDR9SPZxtTpW6FkN7b4Tq0qH//yivX+o1fs3okC1+m5czPFYrlYdOIdPl9o/dzrF5qNpvs+hWlCHw3usRLDH9jCcjn3ohiiYwSEPCSeelp0WaS301qT2exMGXsbe09rbSQayzg7HNboVSJgtA2TpZNc0u2D55p8jvs+lac8uq9YYMzGG4TJuZOcXYuKcXRg9VT1LrLw9svMLkZlr0jJpa0xiaBBf16yXw9bj+lsYGGmigqJivLdgn2KdrJZpxM04nGIxnfAwsbVElRhkxVNNvhdGzzc7losVk1ocOHvJVJZmM/OC2bYQQlsW7zmLdxc659WkhRUhX6z0VPq9k3ODHcJbuUjpctFOgTBkY3s4DGwmKTDhXi9WANq5VnNCADrgULysHDdaZod/uMqxst34DihBwmyYoJf9MhDUXl47PAj1Y8PCDyfdjPUIl/YQBrCLJtxmu7++BO0nLbR0HTswU9b+M/ZvYQKYF6h+35yCC1naGme9ErccS0OLF+Zjyd6zvmN2LEzktyIovcRjURh5GdtomXX+LVRb7Dmd9MhJq8IyUf/Tw9HQlhDmGwpkES9+l0LnVmvfhe0cG9yyoD5y3pxnjhNMnm8t2U+4t/H2FOf2rhXfux0hOpbqEDarPynhWSvzkDAbJji5L5qTbgTFemnOXfimBJKcRc/LOFxcOoQB3ci9fr7iEABr+2eGyjX4mk+VtxoJFKOLdPFt63pG6LSRsOWTOGZNdzsA7a/9rlvMOc5f8gjdHyz2t3aFqt9KBYAgxsx639icgiJLv1erqXA74eAybxYz2+2YkWXNtoS87fSSEDqB2x5fMGLfVwSQxd4t78ONsiRYocCqojbc3YyrV5Rmal9zyJmM+E4q2txIuKxJA4WE2dKKGU1UAH1ZPwGUvS+Ks65Y1iZ88Tqh/zvLkauwAA63/Tpz8j11zC0oxuLdZxTPEW4rM9e8ECsQqtvNLbDPfCPV6pr//bYU7b1Bz2Yqb+dUck2liwbuxqq2bYM0AZRuMY4SaNtbJdv7fjwxfavv2J1fb0Dz59X3ghRXT635mY2m2YRxc/H8/3ZI6+BgGzWsVt7wuY4qUGVlhyKWOlD05uTD55xxuVxz0Lmspx8vOYDNx9L0T/SycNdpx+oi5pBCW5aMa+b6jt1b5ziNZJ9ZW92MbSvKx2GZ1fu2L7Uz4suVWEXFHGO+3oC1hwLr48Feo13KK9T13nIS942eypAwGyJ2nUzH3O2ngnItJ7PS6mq5SsubooG8fdOClMggEK77b4mG+b7vk3AqPXA390W7zyBh3FzJsdPp/nsTOsX7C/fpnyQiYdxcv/rqYVQ5IxYCH/1ZO8nOKJ3slUqT64ykFKw+oK651ovZBKQL6jWiBYB50dka437frikcytG6XzNI2lPlxnLyPQqcvadLrCAr958zLDjp9RO72vNnWUZfJ5WH8rE+t6AICePm+tVh3eFU7D5VkrBEb3GYHKDrZjAtLbY5uisUJD602qF9mk9n5CoKd0Yw0rfMJPF5esY232cnLbO/b1JPgPnLhuOGyykoKg4LxYmRtkpJy0a/t5fi5MWS+dfefWaNF3ZOR1kr0KF+vKk6vL1AOt9fyMrHiv3n8Ngv2lvl6LXfjhPOuDvLL8s5x+LdZ3DF28vQ+dVFtpYdrN+GEyTMhojEj1cb3p/KLPtOZ1p2jzOLfvyB+whkn1kAiFQwZ4XbNjcnZDHaeq6wci3o75v8Y0Hv/z4Jcvq9vUyzXCOuywfPZuJbUdIxNT5eelD3nEDRc6sXECx7RtBrAyWN+tSVh3H7NKnmeoPXHRkArnhHu90B9XdXfNzM/sjnLxlbtAhM33hcd3EofpWcGi+V0PM40UPttgTB65t/kgMrX3aBYFjQ5f1F8Nh4T6ZEumXqOjwusriAeEoAACAASURBVGir4q30UyKhRiD1Uh66vrYI2477ezXIH02h0ZfSRgJdAOr93Mz4YQRx98jOs6vswOa5TPG+uw4uFIQM8IEyduZ2yd9FxRwzko4H3W3VSHefsfE4jl/IkdTtnQXayt6pKw8FWjVFXvB6j5zLzMPyfepx92YVBQtklv3ICGaoHL2+dsvUdabqoYdwvTxZP/x98wnc932S3zoqLSsf7we4XeeEWTtxxzRje72HayyvWUiYLWVk5BZg2Icrce93/oKFHMHlLZCurL81j/Gy5JOOotXMZGUnzdmFhHFzUVhUjOX7PDE9S/aeUdbW2rQg1BpMnZy0J83Zpfn9zZ+vxVerDit+p5dURby435GSjqd/2xawNhEA2k1cgL93arubDXl/JSb9udvyNdYcPI+EcXP9BHijiAd7oxaEPzafkJZh8HfTVh/B7pPSNPxG+8zNX5RkpjaygFMrV9J9TbwTD/2wSfeccI3Pmb31BFIv5eHZ37Zh0pxdht3UOecYO3Mb1h9Oldyb3n3O3npC83sxD/6QhGXesUsQWvNVXtjEj43HisvrqGdVk19SeC/U6iI/zwzL9p3D+Uv5+G5Nsu65dgoTZzOse5LsP5OpqZgS17LdxAVYpBLeAQAFAQhgettC2YWSAiUiwtiAIY+HLOYcG5MvqL43SvN1v7eXGvKs0eufRvnfFuk7+9P6oxg7czu+X5tsS/lqFBdz/G9Lyf1vOpaGp2ds0/QsUoqRnrPtpGZ8+Rvz9hoel0yt67ztP/qLtbjrm42qdTBrnZcrsQQjQpGOV5LZ6+w5lWEpX4gSSckXMGPjcWxMvqAa3vXi7J342MB2nTs1LMg/rDuKVQY9mcJ0SjYNCbMOcyEr3+/lfetva9nojqVm45U/d2sulNYfvqD6nRbpOQW47ct1OG5yjzP9bMbG35T3FvlrDgNd/H7rXQyJrTo/rjuGp38rsQak5xTg6RnbkG4is68Y+fxdqDGYKrVHZm4BJszaiez8wAbMb2ULv7xCqRvghuQLeG3uHsXf6g3w4udstp65BUV4c/4e1b4SSOIQAa1++Jt3IbTOQCyN3mQut9j9lnQcE2fvlBxTsnIXFXP8ue2kz51bfo7Qz1/9azeu+liahl+c+EnOmQAW36rPXOG4Wutm5Bb4Fs9G9kcM1IXrjXl7sDHZ2hinxN3fbkRaVj4en74Vwz5chd82pfi9R2czciWxqQnj5mLXSc995BcVY0ZSCm79UqrN1xu2Tqm4309ZfghXfSR9/gt2lSx6OPcs7FtN+Fvv1nSRu6Lf+Ln/Nl3i8Up4zucy88A5LxnndO71n4OpinkEtNASieTrdCMu9Ubp/sYS3+dZW/zHAuG57j6VgR/XHRUd5xj6wUrc/c0Gw9eavkHmIi5JyGa4GD96TV6K275cp9rmVl165T8TlMNilLySlNh7SprE6I15e3HT52vxW5JnrJ6+4RjOZpa8I8sULHrHL/iPi0oCnlL/sOIp1a9FDcnfqd6EeUbdaNXQezdmbk7Bk7+WrFfyC4vx+2Z112lA/ZUs0DHrGvKogDkBSJibhZjYHSfS8c4C/zWwWcus2q3oedUUc4+CYOamFOQVard9cTHHiI9Wod3EBYbqpOfhNnfHKYz9fTtu+nwtUi4qz5dGc5SM/MSeJJeB5EQJJ0iYdZC0rHx0fnUR7vp2o+9YcTHHlOXW3DmueGcZvv7niCSOS05C9Qqmy508fy86vrwQaw6lYsoK/bodFO0HpjcxCgO+ETYl+yeP0BrglLRlqZfyJPUTEC8IxUzfcAyjv1iL3zenWI5TkmtBtdze5Av+4mKOz5Ydwg/rjuL7tUdVflXCrC0nMGvLCd+kLRdmEsbNxX9+8cRoHkv1XEueJEYJuTDIOZekyhe7yBz3ClfNalbULRfwuO18seKwr15y/tCZmI2gtfdebHQkACDbwIL67b+1XbHkypVnZ27Hd6LnlnopD20VJr6cgiI89ssW9HrTk7X8FZmlue9by1QtKjXiyikeB4AebyxR1XQfPCsdJ7LyCtH3raVYf9gj1Ku9WuLjeku+DpMW4jHvc5WPBUqLNLmrFQB8uvQAmo73tzDM33EKl2QukVNXHsZNCkIXYFzxJT9NWGSpuUm/8tduv7jQDUcu4EJWPj5f7vF0kLdlMeeW3Bvf+nuvJN5USUkjVsQFgnycUho3xRQUc2w6egHdXl+MkZ+sRoZ3z+nMvEK/vibntbme/r73dAa2KCQJkj87rTxZ8ufX7fXFeH2uvudGZm6BKVf4J37VXti/OKtEiSU8p40Kc5gakRpWTKNu7jtPpOOv7dK9gs9l5mHNoVSJ5UY8RW1VcN2WIzwPrVwKG474Kwdvn7bekFK4eiXpmPaLV7A/kpqFs5m5GPfHDtz/fYmnh1buhWOp2ZoCoXx85Jz7zYlHU/Xjtq/tVF/y90de69l/lx9Cwri52HMqA2kil9E93vf4aGoWFu8+g/ScAvy57SQ2HZUq49Yf0VbOWRGW1eYELUW7VeTv7oEzmRKlsHwMG/XZP/hs2SG/OmpZjbenXMSqA1LlibjcY6nZuORVsusZWI6cz8KXqw7jmd+2aYZ7zN56Ap1e0d6KUP5+PPTjJqw7nCrx8BArBDs1rOL7nKMSSlBkIWzCiIKqyCt7yAXubq8vNn29cISEWQcRNoFeKbI82ZFAYLsoO+qi3Wd8i0lAebF49EKWzy1FPPAoTaXyjdHlLNh1WqLJ0RuIBe3RrpPpqi+vQNJR/4WA/H7ErqKrD5zDm/P2SO5/4LvLMeT9Fb6/a8bFaF5z3B87/JQDHB4rxCaF+ighb8d7vt3ol2RDiGG+Y9oGbE+56Bu4mz4/z7f1zeT5e7Fkj7rrGeBZYIkXWUquxXO2nURBUTEqxkQBAKIjmeS591HYBko+GH6x8rBEuM8TLRae8S6mj5zP8k3YWggp92OiPX3rSdkiUf6MOefYdDRNUzgRT1gZuQWK9UjPLkBuQRFioiIk93AuMw8fKmw/AygrIiQZdXXmGbXMxFkyoSw1S3reiYs5qu5wURHa76Ta74a8v9InuHLOseNEOlLScnyxU2oToJL3wH7RO5KUfEGysJjvdROXj21K1kOlS767cL9EGDx/KQ+Hz13Cv3/abKh/Cfy2KQWXv7LQgreI9vlKQmlhEccD3ydJtjES39u7C/ah5YvzJYtseX8e9O5yzesC/kqaAwoCZ8K4uZLzntIRwkrKNjcXFRUXY8sxz9yz62QGhn9YYkEe8v5Kzd/+uM4jrAz/cBWu++8a9HhjsSQe9rnfpfGIJdnfOeZuP4Vx3u9Pp+cqCt1frjqieF3xXNl+0kJ0fW0xZm5KQWauMS+chHFzVTONMgZsOpqG5PNZqvP6qfQcJIybq5hhNVpjrjW6oB35yWrVBHNq1v+JOuEoT0zfgibjPYnZtCx1av1n+X79/YirV1Selzkved/E/UNpbSBwxTvLcJeGRbzQp2i4gJ/XH/NTOEyYtRP931mumxBQT2AY8dEqXC4KvRnh9bDo/85y3Pd9Ejq+7FH83TBFqozTK9fK1lNqZc7feVo32aMRwV5sNS8s5rjty3VY410vXPnBSkm/UXs38gqLcUmkCDupUa9rPv0Hd0yTPuPTGbn4deMxnM3IxRXvLPOta5TWwGLu/z4Jb3r36k1Jy8a8HacU1xqPT9+KDNFaVx6Dmp5TgOd+lypFVh04j1umrpN4eIgRx8IfOqfcznqv/ndrkv3mDmHO23c6EztU9uudv/MU3vp7L24Ig+2lnICEWQepUiEagFRA1FpoCQJQQVExflibrGqpuaxOZd/n+79Pwp/bPJrZVQfOKboe/LjumM8t5bzIUqpk2dRLPf/GPKmb6tiZ23UtIrkFRUj8eDVav/Q3EsbNxecrDuETAzEBgFSIAiBxwXzox834YuVh3/0D8A0+6dkF2Hr8ImpU0hZmlXh6xlb8Z/oW3DBlDbYcS8Md09b7JrmComKfa8rF7Hzc/PlanJQtGpJTszH4vRV+5Qpc8+k/eGy68gJEiHXefTJDN5YUkO6D2VRkKW3xwnyfFrZ6xRhJv1OKHb2UVyiJmZNvzK6UUKyYl0zYWtSr4tnSo1WdOAD+sUdy/rflBG6YsgZ/aWT7Ft/P6C/WSbIzC3R8ZSGu/ewfv/0xu72+GB8uVu5/ZzLykDBurkR7OXVlSZyx3sJDEJzl+L9X/qokq4lKtKzSR72eAJ1fXeRLbCFYhNTe250nMpDqtWAJXgenM3J9IQg3fr4Wd0zb4DeWKcUqHb+QLXHl0lNQLNh1Gl1fW4x/dFzCb/58rZ9L54uzdiLNq8BQY/+ZTD+BWr64lKNU47k7TmkusIUxIa+gGJxznM3M9fN6OXw+S9eKJV8Iyt9LAXGM7x9bTiAp+YLqWD7m6w24+Yu1hmIrxW3157ZTaFJD3RsjI7fA8ML7TIZUmTMjKQU5+Z6wiPOX8lBQ6CmnoJjjkZ83Y/pGT9bZnm8uwdrDyn3j/KU8v5jXaxQyhT/z2za0n7RQEmOuhdo2OZwDN0xZgwHvLld9B4W4NSW3UE3LrA1hnrHRkUjPKcB/lx/0a28hVET+PuYXFmPW1pOSvwUKi7lEEFITlo1YidS8lzi4ovWwSoVorNx/Do9P34LEj1f5CZ3rNMKrhLa/6fO1eP5/O/ys8z+s8/eIOpORK+nLM5KO41lZAqhAEIdzBbpP8pvz9yBh3FxJ+I9akc/8tg1Xf6KdPb//O8slhocTF3N8wmtaVj5unLJGosgY/uFKrDmUiv+orGkKi4oVDRmX8gpxzzcbfYowJev7zhPpmtnOn/t9B04HEGrz47pjePinzXhUxWtMzKoD55GeU+Czvnd9bZHEUCVH8IwTG3/G/6HuJffH5hQUF3PV0LyEcXPx6M+bMXHOLr9tjIR5YtiHK3H1p1IZ4GJ2Pj5afMCn9FLy7Nx5It10KEi4ERXqCpRmhEG5VuUYnLiYg/pVymu6oA5+bwV+uq8HZm05gd82paCgiOOevk1837euWxl7TmUgSmESzMor9NNcKXHiYg6mrjyEfw5Kt08QqCWyZHLO8cHiA/hXj0aoFReDLccvolKMf5fJKyz2uXIqIbfQCAuyxwa38B1Tcj0DPBp7zoFpd3XTvjEZd369HttS0tGomrrb9UcqAk1BEce8HR5B8mxmnm9BkldYhOv/uwa7vAl6Hh7QDBs04vcSxs3Frw/0RI+m1f2+m7v9FD67Tfl3xcXcL24S8LhjyhHHLeXJktaIM9rqeQQIe7olT05EbkERYqMjJAtkvYQ4E2btVP1O6K5alohfNx7D6G6NAHgsvgBwWEVzCXiE61lbT/hlmJSz93Qm+jT3xDqZifP5atURPD7E0z/FMZQP/LAJG14YjFpxsZLzO0xagI0vDlG1ksoXxEqhZaM+K1lkFBdzvL1gH+pXidXNVNt+0kJMvLqN4ndL9pzBzV0bIk0kNEUwhsW7z2hq6Lu8thjJkxMlIvecbSfxyMDmvr+bibbV+XjJAUl2UgEhm/Xnt3dGg6raIRBXfbQKcbGe8UWrPwHwvXfiRDLCwnvZvrOIYAxXta8r+c3k+Xt9XhBmUBLAlVw1lbpXYXExBr+/QrUvZ+UXIrZcBGKipONnn8lL8eb17dGxQRXF38mRL0Ru/HwtqlUshzXjBvmNzUKMutKYkDBuLtaNH4w68bFYdeCcZE7535YTmvHt//lli2IcpVFav+SZJ7q+VuL2Zmb7OuF3e18dbuj8DUc8CYeUkuWIkSor9d03tx2/iI5ed0JB4aM0Z0dFMvy+KQVP/7YN68YPRoWYkuekJRB+teowWtSOw5ivted7pezyAm1eWoBXRrXFS7N3oXuTapjxYC9k5hag/SSpW6W8Fr3eXIpXR7XFd2uPqrqlP/vbdrw0axd2vDwMmbkFGPfHDrx+bTtUqVDiWqym1D96PhvrFdyXL2YX4E6d+zWK3nZx01Yfwat/7cZ/BjXH40Naophz3XnGLP3eXobkyYkAjOQd0eaLFR5l67wdp3FNx3r4e9dppKSp5y8w4mqflp2PyIgYpGbl+SyeyZMTMf6PHX5KPMHCmJ1fhEd+8s84v/nYRd+7LYaD+8bxTUfTUDfefx9rI3GhSgorsxgdZzq+7Hk/kicn6nq2XPHOMnRtXFVT6SnmqRnbUFjENePl1RT8aorJdxfsw74zmZrJ5gBPO1/TsR4+vvVyQ3UNR0iYdRBhYZuSloM+k5di9iN9JAtWJf71VYkrw8xNKRJh9oR3gPpoyQE8f1VrieZdKUGCEqfTc1VdsgDgx3VHUVjMMWFkG+w9nYmPlxzQzaymJ8yqsWTPGURHRuBUeo6fu4bA4j2e+/pg0X7dF1LMNq+rhVZSmg9UXE3VyCss9gmygCdWRo/RU9dhzqN9TF0nSyXB0rsLteurlpjpdEauZE8/LVLSstH3rWV+x/W2elLSbgusMhCL/NzvO/Dyn7ux+5XhvsXlB4v3qz6jF/63Q9NyK0ZYRxZzbnhf2U6NquBoahZqV471++6Z37bj+3u6S45l5BYi9VI+3ld5Rv8WTfIr959T7MtHU0v6alORoPjEkBZ+58qRe0wILNh1RpIJEwAiIjx7C+txKa8QX4qyX7+zYJ9EmBWjt5XAQz967v/XB3qqnrPvjHbcpRKCEkaMoIEWFouAx2vFiiALlIxBenyjsH3U6KnrNJUyIz9ZjQtZ+Vg7fpBkPD9xMcfU4l3Jte5CVj5aTfgba8cPwvrDF9C0ZkV0EAnHatbEz1cc8kuCJS5TDT1B1ohbtRZG31258nTd4VT0VFAoAsbmrpoGvHuGf1TiZj3qs3/w9o0dcHWHer5FpmBZFhMdEeGLf5699QRu7dHI993UlYdxTcd6SE7NwsgO9TBpzi4cOncJP9zbQzWJn1lmJHnqtOHIBRxLzVZMhqNkNZwwW9tNubCYIzOvEMM/XOmzAs3dfgpbX7oS21LS0b9lTVXl6t+7TuPvXfoeSWYR951X/tKOr37V+/3HSw9ixf5zvrWEU9iVjPuZ37b5QoCMsGL/OdSL95/fAKC3QijS/d8naa7BsvOLMHeHceVT99dLXHGNur4azVz+985TSEnLwd19mmBG0nHJuk2JhtXKKyYUU8Oo8GtUkBUY+/t2dGlc1dRvAM87J88QDgCfLjO+XeGcbSdJmCWUkbvIGkm3LWZkx7qSDiq40C7afcZvUFGLm5Gjl/00K78I01YfwR09Gxu2ZN3+1XrsOJGOBlXL49lhl2GULFGCGka2DxL4SKftEsbNxQ/3dtc8J1CsumEoaQ6jIhieVZl4tLLXaqElcBqdZN5SSYCkF++shdZiXkx2fhHumLYenRvpD+brVFwNlbCyBdWCXaf9kv4IrNx/DmNnbsPbN3aUHI9gDAsNKFz0YtbkCBk+tdDSEoszYZpBKYNjoNt+jLZ5Dz8tBr27HA9c0RQj2tU15LUSKErrLL2kSoJwKCQGc4LHft7iW1R9fVdX33G1ZDBqgmygyF3j5Iwf0coXy2Ynt0xdh20Thyp+l1dQjMV7zuCpGdtQo6JyorUHfkjCQ/2bIa+wWHlLN/i7TY+duR1jZ27Hc8Nbqdbr16QSAbdDgyp++78KVqlODav4noleTgUziJ3ErnhnGf4lEqYBj+LbSIZyNeTujHdM24AdJ9JxZ6/G6N6kmuVy1ZBnAbeDQAXZY6nq7ddn8lLc3rOx6u4Wy/ad1d1mJhD0LPtyzBgTnOIBA0pYoER5+suGY6qxqWLkgqzenuZO7nluNFeLmEt5hYqK3bIEC9d9/4zStWtXnpRkXCgKJnI3LbO0qVtZ0RU4EO7v10TTMmsHteJiVBPhuI3Pb++Ch370ZFV896aOpjSfZYVlzwzAQANWl7t6J6BJjYq6wtzjg1voKi+iI5npBDbXd67vt/+rGtd2qieJHVNi5bMDJa7cbqFv8xqWM3cvebq/Zjw44R4+uqWT4a04gsFtPRqpKpCc4pu7u+Hubzbqn+gw397dDXO3n/JtIxYKBLdjgZioCN1kOlYZ3raOIxZYwhjh0u+J8ELszRSuMMY2cc67+h0PN2GWMTYcwEcAIgF8xTmfrHV+OAuzS/acMWV9JMKPHk2q6WZsJsomVStES2JR3UK/FjUMb6hOEETZINyUGwRBBBc3C7Nhlc2YMRYJ4DMAIwC0AXArY0w5s4kLsJqdlAgfSJAl1HCjIAuABFmCIPwgQZYgCLcSVsIsgO4ADnLOD3PO8wFMBzAqxHWyjFsXuwRBEARBEARBlA3CzVPXDOEmzNYHIE77l+I95kqsBHITBEEQBEEQBEEEi2SNhGXhTrgJs4ZgjD3AGEtijCWdO2d9XzunWXkgfOtGEARBEARBEATx0A+bQl0Fy4SbMHsCQEPR3w28xyRwzqdyzrtyzrvWrFkzaJUzy+BWtUJdBYIgCIIgCIIgCFWs7PUeLoSbMLsRQAvGWBPGWDkAtwCYE+I6WebVa9sFXEbNOP0N2wmCIAiCIAiCIMoaYSXMcs4LATwKYAGAPQBmcM61N6UMY6IjA2/eMb0a21CT4HFbj0Z476aOoa6GbSx68opQV4EIMVe2qR3qKoSEyAgW6ioQBOEQNSo5qygfWkbHTbtIbF831FUICvXiY0NdBaIUEFbCLABwzudxzltyzptxzl8PdX1CzY4T6aGugineuK49ejevHupq2EJkBEOzmpUCLkdpsI6LicKzwy5T/c2hN64K+LpWGdLauHv8g/2bmiq7Q4N4ze/fvrEDVj47ULecW7s3xEe3dDJ1bQCoX6W86d/ERIXdMBkQnRtVMXTe9Zcbz733rx6NrFbHMT6/vUuoq2CYUZ3qYeZDvUJdDQDA+ucHh7oKtlIzLgbx5aP9jndvUg0/3Ns9BDWS0rh6BcXx3spYZYaMnJLdFr65q5vp3+uFUcXF+rc5AFxnYlwJNTFREUienIhZj/Sx9Pv//quz5WvP3XHK8m+1YMzafqJv39jB8jXjYqJUv3t/dCc8MaSF5bIJbWpXLhvenaVrlRaGBDIhLX6qv6Z195ZuDVW/02LrS1darZLqILjy2YE48PoIAEC1iuUMlXVr94a2bNL8wBX+AtW1neoFXG5i+7qIEFmntkzwb7cv7/Tbu1nCjAd7Yc14/8XhjpeH4aH+zVR/Z9QqFuWA9WyKCSGgXnx5fDjauFA5+5E+uL6z/2Lmusvr49cHeuLmrg3RqHoF1Kik3ociGPDm9R0wqpO5RVHy5ET8ZkFgiIv1n4jHDvdXRPRxiRLnj4f7YP7j/XTPG9M7QfJ3i1qVMPFq5W2/mYFu+PI1bXF3nwTd84zSt3kNtK5bWfG7J4a0wLC2tTGyQ12MH9HKtmuaZZDBvAlxsVGSkJKf7+9h+Zo3dmmA92+27h1Tu3KsrtLJSV6/LvDwHDHloyOx9aUr8eO90jaNi4lCvxb6OTf+fsLzrnww2libviYKL9r76nDd8wdeVktxvO/bvIbm7yorjEtGub1nI+QXFfv+7qNyLbl1dfL17X2fezStpvib6t75X21u+kBnvogvH41JKuNMIFhZEwjrL6uzrNrv3r6hA3ZMGqr52zeu87T1rd0b2WpFN6qclc8RnRtVtXzN7ZOGYunT/VW/f2JIS8tlq6ElQAeLDWGgGFz+jMc4UK6UKeXllO67CwPM7NskttR1T6iG5rUqoZyCMNu8lsdaeHefJkienIgPR3cyJTTHl482ZFHbPOFK1DXoAtKoegXfwK9UZyVyCzyT6eKnrsA9fZpontuxQTz+eqyv3/F3b+qI569qjal3dMGWCVf6JgAOIKF6BUP1UOLFxNY+y9/ip/pj84QrUbViOSx+Sup2rOeC2r2J8oQPeATWzQoCcoOq6s9ynUwwTuxQ4ookdu9e/FR/vHVDe8jRWiANalULLya2NuUeP3f7KZQvF2n4fMYY+jTzrwNjQI+mxoTBqADc96MitZclHRtWQYtaUmu8vD16N6uOO3slIHlyItaMG+Q7/tN9PVXLTahewbdgXTNukK77+sInrzAkIFolv7BY8/vy0ZFoV18q0Cx6qj/u7tNEUZCP0KjshucHI3lyIsb0TsDjg+3TwP94Xw9Vi/ATQ1qCMYZPb+uMB/s3MzyOGUXrHRWY82gfXKXjKli1Qon1qnH1igA842dvhXfEKE1qVMT1nRv4CVJii5jaePvwAI+CTe15Jk9ORNt6ygqEQDjyZoll8l89/ENrbgvA8t+ydiUwxpBfVCQ5zrz3OOnqNpJxVMxltePQqk5lJE9OxHWXN5B8t33SULSqE+f3m6s7lAhNsdHaY+PyZwbgxcTWAID/DGou+S46imH8iFaYNkZZYfrB6E749QH1MUeN5MmJeO3akrmBMc9Cd+MLQzDwMo9w/+SQlvjl/p5+yphhbev4lOgVVYSFrgkeoefXpOOS448Nao5/ROOlGvHlo1Fk83aXD/Vv5ltvyKmoMX8J6zcrY3HXxlXRoKryGqRn0+qIi43GoTeukvR9Mbf1aITNE67Em9e39z0XOxD6pJ6FvLFo/bTvteG+daecQa1qaSpHZz3SB4wxNFXxcivWWSM3rGbeIPTz/T2wbaK2skCMkX5phioVovH9Pd0Ro/P+y9n76nBLXhI9m1ZT7SMxURFoWqMi3lUJ/2tf37O2vrdvE3x9l7ZxJpwhYdZhimXvqeDCWaWCsguOoAm9p28CAO24Ww5P4ddeXh/XmNA6MsYwfkRr3fOqVSyHZc8MwK6Xh+HQG1cpukLFRkf4WVeZwZFfmBSb14rDVe3r6Na5Xf149G9Z8sJe1b4ObuziWWAMbVsHVSuWQ8UYz+BRVMwD0kTd16+p7z6a16rkszY3rxVnyJq84fnB2P3KMN3z5HXs0rgqVj+nPrDWkS3Ktx2/qHhedCTD6G6N/BZbk65pq1p2y9pxuK+fR8lxdUdpf1J7Pnf0amxoYQ+UWCkilB6L33xW0vZ+pxpUEP1wb3e/AV5P3xTV4wAAIABJREFU0TIhsTWm3O5xDWtWsyJu6dbQb2H/8/09Ucm7kKuuYUEWM/2BXr5FU9UK5VBPR/kUFcGw9aWhmPcffQuqHkpuxTkFRQpnlrDqOXVXbyVho1A+0KnALNs4lJEnyIuOZLi5awO/89YqeEcYRe4l0LJ2Jcw18Fw6NKiie7dfexcugpLpnRs7YPFT6hYMIxR6JYHY6EgkT05E8uRE/P1EP3wwuhOSJyci6cUheEnB8tWganmMHe6xYmt5hrSvb81qe01H5TmqTuVY1Tlj76vDcUfPxnhuWCvMeqSPT/DTQuz5cXvPRj5LYGZuoeQ8wYJ4V58muLyh/ztyf78m+OE+dTfkyrHRaFRNKqz8fH8PREcZ7+MJNSr6lHNtRe3aqk4cHh7QHA/2b4bBrf0Vpn2b18Dg1rXRo2l1P0u2kmAuV9CJESxYNeNi8M3d3bHr5WH4z+Dm6NXMX7kYwRjeuK69IYuz3KOlXf14XaX76K4N8cUdXfzG+B4ypXDd+Fg/t/z5j/dDJ4Xn+PP9PTBuRCt0VPgOAHa9on8vVnhuRCu0qhuHEe38505BgIuMYJrrJWHdYVaYVvJWE4iN8sxDk29orxmqI54rY7y/YQxoWrOi5LyqFcpJBF85SkNJYoe66J7geaZ60/mLiW0QXz4ab17vr5wHPJ4QH996ueRY72Y1EBHh6atyRWbzWpVw0OtFCADTxnRFtKySN3dtIOlzsx7pg7+f6OfzTNr04hDcJfNcErP1paG4omVNlDcpzMZGR2KghjfPymcHYtkzA/yOjx/RGl/f1U3iUfPVnV2x+rmBiIhgWPrMANXxt0WtSmhXPx4TRrbBoFbujXMnYdZh5FqnT2/rjOkP9FR0Wc0vLMat3T0a6Lb1PJ3yQna+5Jzhbevg4NlLAIDzmSXfOZXMITY6EhVjohAZwRQXOJEmRtmkF4fg0BtX4T+DW2DD84Mlljg1wVNwERQuLbZ0vneT/0As1JFz4Is7umoOOAJWNH/9WtTAhJHqrlCx5SJRoZy/5rpl7UoSd7doDUuhXOuudC9Z+cpCSYF3QXtnL89vhIWblleyWM77RDY5vH+z8qQXXz4abevFY8nT/RWVHeKJRNAIKwk08vns3r4ey9FjMmsFoD/5CXRLqIZv7pYuRvWsuowxNK8Vh6/u7IrZj/bF5Bs6SBYScsFQ3v+VtPwxURGoEx+LXx7oiccHt0BsdISqsCAoBiIjGOLLR6ONQStYjybVMONBZRfqIpGgKfQDLQXEm9e31xxP4stH48ibV0k0yFru7pXF8Yqy02Y82Au//9uc63f56EifIkzsBjmsbW3sf20E3rpBObZLEOzMkvSidKxuUSsO8eWjkTw5EQO8yhL5olBQwigqbrx0b1INlzeqim0Th2J4O48AcpPXzT4QlGKkWtUp6UfCs5UrVD+6peSdFx6T0vD+8qi2fkLch6M74bnhrbDpxSGq9bq+c31f3N2qsSXKEuEaSteKjY7Eq9e2Q3yFaHRqWMWnbJNTwfve/XBvd9zWvcSKO6BlLV/splyYfXFkiWBcpKCMGXBZLdSK07boy5U4vZvVMOyZpMVP9/WQKLyERJCJHeoieXIifryvZA65UibsXtupvk9QAIAXrlJWAFzuHcuEOUKgYkyUT8CSP5OICCAigiE2OlJ1HK4b76m34IXRvFYlPD64hSGX+7du7IDWdSv7rZueurIl2tStjJ/v64G9rw7H2vGD0TWhGpInJ+LjWy/H/f2aoHXdyooeGMK7OKZ3Y10PDbEirEeTavjURMzr4qeukCgfIxhDdGSEYtxsJZMu4kZdfDe9OASbJ1yJ51WeOQC0qutRcMdERfrWmUoozZVH3kzE0qcHSI4xpq2kVPLyuKNnY2xIvgAAOH4hGwDwyihlRfuwtnWwbeJQ3Nq9EQ4rrDFu79kY13Ssp/j723o08lNkRjImubeacTF+8/HbN3bErw/28nnOdGwQj1Z1Kvu8IatXisHEq9sork/EqK3v5GP07Ef6GJoHG1WvgCY1KvodZ8yzdpn5UG8AnjwtQ9rU9vMMUIx7LiV5HkPvVF7Kkc+RsdGR6KnhTjmwVS3JgmvLsRLL23s3dcQNXRpgzaHzuO3L9egpilkZ06sxykUyTJjtSf5cLjJCEhOjx1d3dsV93ycBAP56rC8W7j5j6HdmMp4Ki6inrvSPj1AqZ9fLw7DTmwBL+F48Liq5twoDZzHnaFKjIiaMbINv1yT7nVelQjReTGyDZ37bhj8f7YtOrywyfB8A8MO92jFtakJ+n+Y10LdFiQuh1sJH7nbbuq6/S9uNXRpgyvJDfsdreQfL23o0wm09GmHoByuQmuVRflx3eX38b4vf9s2I1Fh5K7nLTRjZBv2896KWKKtjgypYO14ag8v9zbB+i5d/D2iGfw9ohoW7Tvuda0SWHTv8MsU6aykPgJJ+NkQkJIkn6j8e7qN4vsCvD/bCyE9WS44JXaFtvXjf4kE8wd/WoxF+Xn8MQInrvVEL5vWd6+OlkW1QpUI57D2doXjOthTPO/RiYmvc1NUjBDaoWgGt6sRh72lr+8oxxjCwVS3senkYjpzPwuyt/v1JQM3VUjzORUUwXevusLa1Mematr7FslAPgZu6NDTsFWKUSjJXyua1KuFR0QKmpndMk1uIf/MqFrSeo/DuKyUnAjxxdWN/3266zlou32LmP94P/d9e7psnxF35of7NcN/3SWhbrzJ2npD2q5ioSKwcOxBp3vGkqixHQuu6lbHnlPQ3a8cP8j23m7sq53o48maiIa+LCSPb4NW/dkuO/fVYX1zMKUDnRlWx+Via77h4SDsg2kPRiFJDqRmval8H83aUjEm5Ch4OUZERmDCyjc+L6LYejZCeU4C5240n9JH344Ze5YGSVVx+bgTz5HLYdTId3ZpUQ1QEw8xNKX6/++PfvbFg12kMa6vuFSV/HOK+pfakbu/ZGHN3nMLIDvVUlQ/rnx+MHm8s8f09pHVtfCVyp5YPBRERDPNUXFmv6VjPZ3Wav9N/vhDewQrlorD82QEYO3M7Zm89qVjWm9d3wIwkT1v9KlIOVlZJZiWmea047Bf1MeF9Ep5PzbgYLH26P7Ycu6ipLHxySEvcKdvFQmwl//m+HogtF4l68eXR880lkvOq6yghK5ePkribypddE69ug5f/3A0zMHjWYm/f0AE142Jw97cbpd+LrrF90lAs2HkaPZpUw3s3dcTTv23DgMs8So47eyWgVlwsHvpxk+q1IkysN1Xr6y1iyr86498/bfZ7p8SeDVteUndVZoyhS2NtJQNjDA8PaIb/etdo/VrUwKoD5/HdPd3BObAx+QIGtaql6o5uFKGPl4uKwNQ7uqh6IdzctSHGzjQ/p7gBssyGkD2vDJe86PKEKwBwQ5cSlynh3N7NaiB5cqJEuxQVGYE7ZBpWJZSS2QDSxXu7+vGKAqcSdm3fEaUgSFWMiUKeN7ZPWBDrLdSEbwXhSK16P9/XEzd2aYDkyYmoUsGYq6gZ1NpFvriVL0QqaMTvyH97fef6GC1aGNaIi8G2l4bij4d7+02+n9zaGXf2aoyE6hXx/s0dFa2oZpNJ3du3iW3Cg5oco7e0XTt+EEa0q+O3jUG3BOVY5WhRP1PaB1pJCaF1i/L7b1c/3t/tXkGgEfcPwcrVsFp5n5uQ4C6vR5u6lX39V+kdElO5fLREcJK7rFuhYkwU2tWPx+Zj/u7u40a0UghBUC7nkYHaGm7A045iQdYuBK8QpXdvgSy2efFT/SVJpyZd0xavX9cOvWSKp6oG3AP19hC/uVtDTL3DQkZmg69k3fjy6CTyNBCPrUPa1Eby5ERUq6hex6oVy/kJsoByOxp9bkbGE8FrQ0ztyrE+65X4HRaXN/6q1mhSoyLWjvcP4xASQYkXtkpzjfwdu9/rzvn8Va3ws8haem/fJj6L4BvXtcdnt5nLaiu/8pjeCRg/opViAjX5sB3BGOIrRKN38xqIjowAY0yxHzLGMLxdXVNjuKRNVBQPzWtVwsYXhmiOL7UrS7+TV2HgZVIrbiCzjLh9YqIiJR4IctTm7YQaFU1nvhaXlTw5ERtfGIK42Ghc0VI7/rViTKTfeyWeQyrGRKFzo6qS9k3sUFcxl4GYGpXKYdXYQRJBWv7s75bF0j88oBm+u0f7voU+cXO3horJP8V1rxwbjZu6epSON3jXX+L7CGQ5adRjS7jnEe09Xg6e96PkwnpZuvWoJRvXxZ5Jn9/eBd/c1Q2t6lRG67qVcWevhIAFWTlD29bxe7/EyONi7Q79CRVkmXWY7+7phpmbUvDNP8l+mTfLl4vEl3d4LKKDWtVSHAiMatnlFClYuoa1rWM4vtEoRoTZr+/q6ufiJUfNOnF5oypIqF7BlxxL73KCa9bl3oWN0kQdGx1h2H3TKmrPTckqKfDYoOa4o6f6vsLyIt+7qSPOZeb5/u7UoAriK0QruiRdVicOr4wqEd6UDJRD2wYeL/H2jR0kmj+lZlCadNQsMkr3Ij63bnx5TLm9C3ILinBXnwTc9Plaz3VF5w9tUxsXsz3bUIg1uyPb18WHi/aDMeD8pXzv9/51cGK7VXGZ0ZERmP5AT7SuUxmVYqNw/EK2poYd8MQ092teQxIfqGblXzNuECbO2eVnEVNyrQSsLRyv7lAXm46mSY6ZKefJK1viyStbYv+ZTKRl5WP01HX+9XJozt3njf9jjCFh3FzJd0KM34uJrZFQ3d+9q2JMlGIMsRFeVnGrEzO0bR2fNl9MzbgYNKpWAZuOpiE2OkKS3MbMnCHuh0q/E8eSGU381KFBvF9f0OJUeq7fsaY1KuLw+SzDZYjrrvY5NjpSMd4MANrU8yR5mjRnl287PCPtOPCyWrZk5Aek74v80tGREXhQJfu9Xz1tfE/8ihbLsgGWLfYMkVf5sjpxWPDEFRj24UrFeqixdvwg9HpzqeSY1TWUHK3M10rvhl3XBaT3XyDyuPvl/p6oVrEcLlNIROZfhn99lOa2vx7r61tHCTH0Ruu2T8HTR0fHqlrHCuUiNUO5rOLk9umLnrwCtWVKHPHlKpTTjok1ypKn++OX9cfw1eojnmuYuCc3x8VqQZZZh2lbLx4Tr26LBU9cgV8fNJ95UPzi1dHQtsiRW6qeG94KnRpW0XRvWfjkFVjx7ACT9dN/iwa1qq27jUqd+FiJNViIM4mLjcbyZweiQ4Mqhq7XsWEVLHjiCjyg4t4EmIvztYpZi3V8+Wg8PfQy1NJ4xsK9PzLQs6jxm5wCuK3kyYmSuDo9lJJaAP4uhEpNreQqp7b4rRkX41ssasU2x0ZHorEojk/cNlPv7IoZClvyVK1YDpsmXKlrjTFiuTAbJycvs2fT6oivEI3ICIYEhZgYOdERDDd3ayjxzoiUaSjKRUagR5NqqFelvOIWUgUqYQjiqulZDwXG9E7wi7NWtAbplNOydhx6NK2OzROu9MtGqfcYrC6u5Zp5JcXaff2aSrxXzJStxGODmhtyXQQgcb8EPPFbU+/ogq/v6obKsVH4VhYXrhSOoFo/0RNRqqo4+7eRpFcADCUX1GP+E/0MJdADPIra2OiS90B8H4EsXIMwTWhc26K11GHE11Ia8+TZ/rV4T7R9lNItSJ+dsXusG18ezwyVepUFo3l2nfS41Ysv5dRzaVG75P3u1ay6IUEWUG5BJatcu/rxhrdXlCNPHAlYV67d1TvBl0NGDXGmb6OXsfOxyN/TxtUrao7rdnmyNatZCS/aJOiHcpyzExJmg8RldeIML17EVClfMqio+cEroZaGW4uWteN820MYxc4BW5yJUE04MHK9y+rEacZWKJUx9z99Rd/rXkIXM2X8+WhfLFJZBIgzqQoazmeHidw3RdcJ1qB0V+8ETbe5nir7DwoopehXi60SSJ6ciK/u1ElZb7AtHhnYDD+JXALFE4ySEkKvWT+59XIs1NlqRwuj2ZnF27hc39k/Y29GToHk7z8e7q3pIqZm6RHTRyGjqRKMMT8lhdJCyehkXq1iOT+hUu+3RttxusZ2JiufHYjlKtY7K/RtXgMdG8Sjjcwrx8SObb5MogKzH+2LyxtVRXz5aGyfNMwvB4NWUhc5UsFP363WCOWiItBVJ5ZMj5go5QR6cuLLR+O54a1U32Gz85OeIGzXGFspJko5GYuV6zhnmPVD3LY3dGmAR2XhAc1rGVek6Cl8xc80kHY3MuaIt37q0riq4aSQguvxvwf4j6V2hWDJsbPYjNySOUNt6x0zlC8XiYOvj8DLol0TzFTXSEy2QJfGVRUzfetxLDXb9G/UkIft6eXkMMqG5wfjSQf23i3NkDAbYvTG2VGXm9voe8q/OuPJIS0l2YHlSUzsxKkBWw07LqfU5uIFoB0CuhkNXPsG8apZMz+WZBgNDxXabT0aaSoLXr9OOYW+gPiXk69vj+TJiYpxcHL0jJ8SK5PGec8Oa4U+ov129bTpes/y6o71DFlTA0WclVGcRExAvj1C5dhozX0u5XFpAlJrnfE+Jx8L7Fau6BVntK5aCfgaVa+gGAdqlWoVy2H2o33RsaG17WycRuKSq/B+6e3LrIZSBtdgERFEIcgq/VvWVPBiMTZ+yXFyCvZLxCS6VnRkBJ4Zph2nqYXkOSncsfhagdyikfZ547r2PgXx7//ujVVjje072q9FTex8eRjGKrSDUnIwNUaq7HMsIO6KRvulfPskpZ+Jrbrv32zeAAL4K+aiIiMkW0qaeY/MvHLy2Hy1UDU5GTohb2bqIA+DUrpXK8NIrcqx6NvCmCLZ6jUEgryEdwwSZsMENauC2Yl5RPu6eHxIC8mxWY/0DqhuWtgpzBoxVtiRzU6vjEDXMFa2+lGDSRabSlZDawsgMeK4Sy2+ubsb+jSvjpa1tbXveosUcfvqJcOQ/s7zQ7V+Ii43OdV4vJ0T1pgk0RYlgfanPx7ujT8f7atbjnxPajvW4qYMRLKTxfHcVsorTfRq5q98CAecsMwC0AyXsBOlPi5+DQJRTDrqvqtTtN1uxlYFc3lcvZ0CvkRYVRx3rSnVtDIwO0Elja2MjHKtThiWGKOX0FJkCkiEToujs1IeELESzMySzcyzekK2zr26Qz28fWMH7H9thMovPDS1WfE8xIJ12AjyPq8V8hOIoSNcjCSBQsJsiNF7d5nks7VOZ8b1xyx6wqzSBu5qFOtszQFYm0x/uV/qVqibETnAyU9Lq2vGvRCQTgRKmaitaGzlqO0hK2fgZbXw0336cd+BCECBlCt+rhk52tpXtZKtuBkrIY5N13Pf0ntunRtVRfsG8br9Vp6NWr6PqBUCscyKXdjsQK8u4TwlX9OxHra+5L+3uFHEMaFOoTSUm81wHg5IFIABCbN21EYZpaKZzveqZTlYz6s7mPMMM4Oeot4uy6xS2fKMs0YxmgTNbuzo03rrR63klJq/U/iZOEzMTH3Fp+qtlcpHS9dDEREMN3dtKPFKVMJqPLBVrK7bxe32yMBm2PiC+h7eBAmzYYO6tSm8FxN6E34LE3EYYi2wWntYWWD0alZdEuMpjkO16xpOIX7+A0xYMUOJZPLS07ibGOiNbssE+O9bq/k7HetUoJr9b+7SifU1iBklzAtXtUachRh9T0HiMo3/TJ5YrYWCEi0gt0/rPw0K4rh7JcRbgJnpnwCwZtxg/ZMsoNen7PCEcRKl2kXqCElaiB+LkxYL/XfZeFlO1jO+QjQu0/HEsYq+m3HJsfQc44ox+Zul1NYVLYZevWQi6Y6tiYZsKNeppaTSSCa2zJq5rjRmVnuMtCp8K2VPF2P2fRKqfFMX/zwWgWAmUWlg4RTWfxtOkDDrIsKx0+lZZk0lOjFgfbAqWIgtxN/f00PjzOBmh9RDaN7LG1VRjsdQ+RxKdGRZy5hZABow8itfQ8kyG+BN6G2zYzRxkRm5IlZjv2I9rN6uvO3u7OW/ZU1A7lDh0sFVMJN4ySyVVfYHDxRpm9rf90OBZEEcwP4xFj2sDaHXrnbPQeH4GCN1TK/iJjhxMcdwua1k2X3tbEp95Y41Ra0p5YVDD9Pq2KykmBOHJ1i1zDqFmb5kBKHKVpJRaZYbBn3CTZAwG2L0BpBw7KNidzmxtSFQ+jbXjyuzw1CgtZk7EF5t7sYBzak6C+eqLVDF75JRAdHzuxKUtKFh0qwh8dIw876J265VnTjJtkF2EC7PwQ7Mto1zmVGtWzHDgUgFiVN8KCXNeuZSxWRwlksDhrQOfH9JJYxkUA3HZ6un9GQWlRJD20q3jVPM22C8OAlOOSrohptJ2sqZSli1dCpRLipwy6xTjJYlXpNjvQr2tR8gHfOd9L4Ix7HBCiTMhgmBaJCDjViA/fS2yzXONAdjDIN1NpQOxoI+vFy7jbuWhgtOTUi6xYq+11NYqJWrZI0Jxza2G3kyDQFTbuCiyXfv6Uzl8gJyhyo9z+Gh/tpbUclx6t7NuO6HI0oxveJ7MqsEGNM7QbEcO5h4tfHtSsxcOioyAv8SbS3jlvdEslhXDO8o+WxW0GoiSvKj2AUsN5HxH1Yy4U1hLtzG8Kl4SLT9mmP9QuHRdGpYkuXXqT2TrQp4b1yvvduCWZxqVicFe72QGDdCwmyYI03wE7p6qKG2pYxVgu1+ZaUOoUDdGin+HB4VN5OUykyNzbgZ99LYfkWrXKXsreHYH+xmTK8E32erix7x4vSajvYnjilNj8HIHqrBQGwgVraOBa0qlvhqTFe/Y4HsM9ukRkVfnge77z1CR3gLxPpW1UYPqWChG69t0wOw08JupkpNbMyaa3W7tMcHKysp9a4RKOJtc8xlMy75XKW8M31aT8Fltd+prtEsNquT6Qqk9xjmg7xBAhJmGWPvMMb2Msa2M8b+xxirIvpuPGPsIGNsH2NsmOj4cO+xg4yxcaLjTRhj673Hf2WMuW90toIZN8tS0umMoL5VkfPXNnuJUZ2cy/joc601cW6oMTUZ2OiSLNkz02KcTnmF7QzKwnun1l5m4gbFbsYfjDaWIVuPaWJhRecxdEuoZrp8YW9Jt9CxYRX9k0wgVt64xaInpl19/zjlQBXAWmNtIG2kl53XLsW1W5QSEo8YhfqJDwXiueZUIqbHBjW371om3IzNrIHM5K8wY/2+v18T3+eG1Sr4fS+tr7W5+D7RNYKJWWFWON9u50onk++Fu5HMCoFaZhcBaMc57wBgP4DxAMAYawPgFgBtAQwH8F/GWCRjLBLAZwBGAGgD4FbvuQDwFoAPOOfNAaQBuDfAurkK1WzGZWAhLSU42lrNGpi8xke32OdqLcdXE5XZPBwHIqd0fmZcIq22i9IWKGGe0FURs1VmKjNBHwNx7L4yRBdV036bfS7ipBp6Y2G8DVsRhTNLn+6Pn+7TTl5X0WTiL/GCSTle3PnOX9Xm5ya+DzMZQeXYfed6Wd7turZ8v2lPeeE3iEmyTiudIDpYv6q5vdulc4GSFdxae4h/9+SQln7fWxW6zdTGTN2dElru6lMiaCoK9RJLsvFyhXtrXbeyYj8OBmbbSS+Xh1WcXOtG6L17LiSg3sI5X8g5FzZ0XAdAyE09CsB0znke5/wIgIMAunv/HeScH+ac5wOYDmAU8/TgQQBmen//HYBrA6lbaSQcBRc9zL/f2r8IpA0eHtAM9/bV1/YFcg27N9DWd9P9f3v3Hh3HVd8B/PvblVaS9ZafsiVbkh+S5fi9tqWQurEdW7bjxCmPOOFhE0JNHpw2pTiYGBJCQg/0tEADFJoGh6aF5gmNDw1NkxIOp7R5OCROnLcDCbaPQ4DEMSWAiX37x9yVRvLuzs7uXM29q+/nnD1azc7evTt39s7cuXd+176dYvhk9wHrhon4GPi5xaWbsWOgO3D4X7nJfLdcJ5abQswzaSpIkSlB8//apmtiHeoCphRZHbL+8d9zGjSPtSlzIp76xdagVmHqp7Ansv5etaB5Nov19iXTIk0vzDDjxRGPSCh1t1jQ1hhpz5mpObRN/RYyX702lcwazK7YY/FgL2eMQWSKLdYoA2gBpV2ICzJslIhFdWQporxx5wMAbtPPp8Fr3GYc0ssA4OCI5SsAjAdw1Ncw9q9f1jL7Uc4fb4hhImNBKVerrlzfU9B6xX5CQ3UFvvIec720QWyplMxFfAxzibfwVTM/vY7x2e9xcnH4ZaFZbqqpxOtv/iGSE+BCDr62TM2z9xNnDbuva6zKzO19+aqZaK4tjzt7Sr0fzNSJdJiGRSn7+rSmcL2YQTIn6dtX5g9aFvb3FHgP8bDn0dbBxW7fofM1M+kWv0Kkbysg3cKH1hZ7z2xcwh7vB7dFxNWG2dMOCzZ0xAIbsyJyP4ApWV7apZS6W6+zC8BbAL4ZbfZy5mk7gO0AMH369IC13WbreXRDdcWwyI+5HHg1e1TT3OIfZlzMZzzxqXVIJROoqsh/QC82+znrSQv3D//BIKiBE24IUsDrRQ5tyhyEcr3H1t9gFO689HT88PlfRDKkK3NyGvWwURMmBMz966qwu2qt7uld3pk9YNpo7PrRB1ry/1f8GWbk+QoY2ldskB9gqA7b1j8jayT30ajD5k1tCLV+8D3EJVzJj3BE0LD3ZYaURtwLZ6p8TJ0vBTU6/S+HycNQz2wRmcrjkV1nYdln7g+Vh4KZKjuDLfvhv73yOMEJbMwqpc7K97qIvB/AJgBr1NAlzcMA/JM5tellyLH8VwCaRKRC987618+WpxsB3AgA6XTaoUltSmNTD9ETnxoIXgnA37xrYVHp5yrUqA8i2RSzmRuqCzuBD1txhFnblkrJX1EGVchhchwmmnGYdDP7VK732LJdTZg5sQ4zJw4fbltKNfP58xciPSN3IKaoA9sAwO73p7NGoaZgOzf0oGdKPVbOzn5vtE3HnEL564mTRRwuTB1hhg3lN7RZJzVEO7sAYK7+Swa0Zof1zEacBdd261Ib36WkkT3d/I3OMLcaZVPIeV6YdFtCjDpZ3hk+kCAQfb1hchd1sV4PUmo04/UArgRwrlJd1MedAAAVlUlEQVTKPzv5HgAXiEiViHQCmA3gYQCPAJitIxen4AWJ2qMbwQ8AeKd+/zYAd5eSt3JR2oCp+NkyBUU49m3pQoY12Vg/LetoDl6pQOGiOBa+ctw9s7bNMZ2vMRrk7UvaMH38qdEtM4rZlJ97R/55AVf3TMbKOROLSDl61547DzsGuuPORsEaayqx7fSOsjq5ia43Kv/Q11KSG+0LZKPxaWHrMX85VWa5GFWOQWpyCdofih6+bOgCSvAoqex5CBKmZzbM/hbmqzfWhBtZNDT03I3eeoD3zGbzZQBVAO7TO+yDSqlLlFJPicjtAJ6GN/z4cqXUCQAQkQ8DuBdAEsBupdRTOq2PAbhVRK4H8BiAr5eYNyeU00nEaBiNkwCT920saDt1Kol8goY12X6x4/x0e97XQ0VmjDBYlN/Qls3+Lhvu4xlN+RqjcQi62GCTQm69MMmFbTSaskUnD2To4pLJesSG62Fh971hjdmKoMZcyMQNbRA374/UnxFhWkPT0QTPshDqntnEqe+Pgsnta+oc3uS5brHTGNqspMasnkYn12ufAfCZLMvvAXBPluU/gRfteExZPL0Jk+qrcEWWMO9AaVfWLl81Ey//6s3gFS1iw+/KZB7OWxwurpnJCi2VTOD4iZORp5s50DeNq4y0os81fczg60VebaxMeivnisZrurI3kbytQ6OL2R8yp0u2fieyi38XW9U9KZJ0hhYWnRzqqipQm0riN8dPWHGcCyvqBpy/vl3Xmy0syxAHN1fRsh2HIvn+UR6LB/9mT3P4eauhC9aGRmrZYrRG3bk2C0EuLo4BLSsN1ZV4eFfe25IHhf1B7hgoLHovDWfTSXPQvSPFHjQA4Ac7zsSRN35XVL7yOany34PqFybHQesOC6ASIuVPbz4NrY01WNVtx1BVGs6lnlmyh0hpF0/Cv5ifiOCqs+di13f2j/6+XMIHDsYUCBxaGu4zkgnBjoFu/PGciThtWpYRSyWczJvuqTY7BNT+ii5MHk19G1tuzxkaZmwmXdPKpTHLqBmWK4/dLLygimHj/PxXckth02978ES+gD0hbLanNtVg6Yzc97QWe0zNREjd2t8RuG6Yzwh1AA2R7oS6KnxyU2/W+fK8tLzE+ruyR3wtlS0H5dFQyk/LgXM88rnr0v64s1CUbj3vba2BeA9Dv3X3dmYTF3kvXzUre0O2xM+Oc57SYgwblputZ9a2yi9Ur6ihLFiyScx9v8ITLmV3t2U7loo9s2OYiH0n0jb8rmw6cGSKJ1cD22ROBcVd4a6uTOKlz5496gERzE1v4P3tnlJv5gMMKGZbvGtpG+549FD0mfExFdmSPPbUXMDSEgKJBdn9/jQm1UcfuRcA/vb8hdh2qCPrFDelGhwyH/EQZpNsGBlhyyE5cKRUkem2Nw/FKch2rI/i60d7z2yYzw3RKAtR19t27mpyuqYty/LHHikl7feumBFp2nFhz6zlTFbi37jIu0U5FcEck9HLXjHYOjWPKScDziRM3ldRaqO+kPeHOdAFTs0z7LMLTjbQ0DAiM/vehPrCpw0w6bPvWIBnr1t/yvIvXbgY377s9Eg/6319hR9AMz1lJhtH5cKmC3GFKqbHb3XP5Jw9eqVugtqqCvTPNDMKAyFuwSgiWSPHrqF71gNYtOsF1dQlH9si/rLtLePwpQsXAwD6DI0ACvrKoaIDGxolNfieAravLRc5A29/KnJfaxmXwtreybhtex/amvMHZQw9DF9vuqmN1WhvsSvgY7HYMzuGrdDzadl0/hNnXu64pB/v+tr/WrU9Mgq6/9TGjAcp5kBXwHuMzKkXWYrDnbcoXFCwQmw4Lfww/GRCkEwkT1l+zsKpUWQJgLctn79+AypCXNpPd7TgRztXY6qBnjLKz8UqxWaZeW+jvi9SDTaSc1z0jCDtOEW9H9rwnUY6Z+HUnHVtKd+/t7UBTx85FlvPbFVF+M4SWxqqhTCV00RC8I9b04ZS9zh5zpiDjV1y5GMyGJGF9Xkgk9tjYl2V8c8Ia1pTDYDc9wibzOtobIVi7pnN9RZTc+plDtwnDf1gTBxQmsbZ0dubTaoikfW+sHymNdWU1YHXFNu20LXnzsOujXNH9TNtqr9HyvS6bZzfGmm6eYcvl2j7yi4AMDLsOp+aylMvrBXK1Pz2cZ0zlfK5V5/TCwCoyDKX77DPCJFmuKjD9v4eoxAmroktbLh1IGrsmbXcqMw/ZuEOHcdBI9NYsSm62+SGauy/dgC1qewHdhvLzpTMd811cJQcz6P6YBcv/pBd7rr0dLzx2+PG0t8a8zy3I8Ux767JOrHUKqB7Sj1e+uzZkeTFTxkavgwAW5ZNx5Zl0wPXi/qzU74evbANhZu2pTHwhR+it7Uh4ly556QeDlCd4xyiGJnfWHtLTWRpAoWV89zWBjxz5Jh1x2OXzsUKjVDuEjZmySpxXt1q1r1ZZ0d81bxUdVXx/Extq+gy2WktoIcg0vlt9d+wx85lHc2YNzV3pM7bP9SPEyctOyKTUfmih0dhUXuTkXQ/uanXSLomWVZ9GaUChi/bVpeHFTb/05pqsP/agcjzMWtSHRprKrFjoDvytPMppfxWdI3HxWd0DvawR6G6Mom/f88SpDuirc8KGV5s265swxE8bMO+qsK7sNExvtZAbuLBxixZGQAqjgqiuTaFfdesQ31MjUfbSNHxjM2oSCZww4WLkc7RIBgWDCvCz00M9syG2xZ3XJI/aNLyTgY0omgsam/C4wePGkvfxnsMc7HtZHc0TKz3bpEZX2fv7QXloLaqAvuuWRd3NkJJJqSgi1Fhf+NRD5X3c6i6sULYix1TGqvxD+9bir5OQ4HuYsCz9jGsJpXER9bOwfoigsWYEvcV5MaayngzYBMLzwrPzROMyNQ9s5m0eIAlW30n4mjTGS7dBzaWXXxGJ6Y0VuetH025+aJluOjmR3DJmTONfQb3QvNMHN7CjirLnH/1Ts09PNy247FLF/r8BubZc94fBTZmx7g/WzM77ixQCUw2/k2eQNRXVeDXv3/LWPpGhhm7ecyiMcBUkJV0RzN2/+ineYfL28ZkwBmTdWIpaVckE9icJyq6yXyv6p5k5D5gv3IPIhSn2lQSvzl+IvLj243vW4q5Ie9Zbm2swV2X9qO3NXd9Y9uuMBR8Lb6M8aIjG7NkKTYcCsNKzLzMMGNT0YzJPv/9sVU48sbv4s5G7DbOb8XDV63BpAZOiwTYdNMFUTTmTKnHYz+L/haFdUX2/AXNJ97XOR77Dx9DiyVD6ifUevmoq4ouwFZYtjXw48DGLBlRXZnA7/5wMvT7zuyeiO/tfwWzJtUZyBWFkakg1/RMijcjcRucmifebABAX1cL5k9zp5fMVW3N4wInqh8rXG3IZoKckPt4rm7O8o4WPPazo4NTE9pu54YevHvF9MFpC+O2c8NcdE9pwKruMX6eFDM2ZsmIRz+xFieK6Mk6P92OgXlTrJ4nc6z5/JZFcWehYO/tm45NC8zcN2bD1c9bt/fHnQWiSKRnNGPvy69Hnm4yIbhyfTfW9EyOPO2Mj66bYyxtE1wfputK9hscjLmxY6AbW5a1Y/p4Ny7eVSQT6JpoT2dHTSqJd6/IPXWVf4opModb2XKuVOIj1VZVoKE6fMUuImzIWqYyGf1OeMHydgBAVcQV/fXnzUdfV7QR+jLRk8+JIbgKUbn6i7XmGoSXnTkL3VPqjaU/1ZJeobAuNRikiYAJhns3k4noj8W2NQ5N6uvKPYQ5IWbKb0u6PfI06VTsmSWiUffxDXPx0YFuJ4YCdk2sMx7gJCr11RWcWoqIslrt6C0jrvcslyoTG6M2Zf/x0lbPXrceFXkuBjx73QYjnUej0TM7c4xcjMiHZz2WyzUJ+li1qmci/mj2BHxsfU/cWbGCq7tHIiGoSvDAHLV9V7s1ByKRq3WYS7iJ3aYYeqxk1ZX5zzdcHg5sosfeNZGUnoj8pYgoEZmg/xcRuUFEDojIEyKyxLfuNhF5QT+2+ZYvFZEn9XtukLF+KU6rTCbwxS2LcNPWdNxZscK4VAX++eIVmDG+Nu6sWCFpdBoK/gRdk0gIEjywETmHpzxERMUpuWdWRNoBrAPwM9/iDQBm68cKAF8FsEJEWgBcAyANL8r9oyKyRyn1ul7nTwE8BOAeAOsBfK/U/JWD8xbnnj+O3HDVxh4cfO23kafLhgsRucjFma4+vHoWnjlyzGhwKZNc3OY01PM22dHI4mPdB8/oRKXDPb8uiGKY8RcAXAngbt+yzQBuUUopAA+KSJOItAI4E8B9SqnXAEBE7gOwXkR+AKBBKfWgXn4LgPPAxiyVie0r3Qu8cdO2NG7+0U9REzA8h4gorMzQSZc6JGdOrMN/XLHSSNotBgMfzp5ch70vv45GB6PtElBfXYkvbFmI/q4JcWeFivCJTb1xZ6HsldSYFZHNAA4rpfaNGCIzDcBB3/+H9LJ8yw9lWU5EMXnbrAl42ywePIkoepleQt7O4JnfZm7+6GvOmYdNC6YajfBMZv3J4ra4s0BkrcDGrIjcD2BKlpd2AbgK3hDjUSUi2wFsB4Dp03PP70RERET2yYx4daln1lXVlUknL0wubG/CvoNHI0/3rLmT8ewrv448XQC4/UP9eO7nZtImGmnWJEYyBgpozCqlzsq2XETmA+gEkOmVbQPwYxFZDuAwAP/kSm162WF4Q439y3+gl7dlWT9Xnm4EcCMApNNp3gVCRETkkIVtjahICOc+pZz+5eLlOHw0+lgTH1k7B19+4EDk6QLA8s4WLO/MPZ8pUVQev3ptYJTmsaLoO5KVUk8qpSYppTqUUh3whgYvUUq9AmAPgK06qnEfgDeUUkcA3AtgnYg0i0gzvF7de/Vrx0SkT0cx3orh9+ASERFRmWgal8KBv9qI02e612NIo6O+uhI9UxoiT5eBE6kcNI1LsTGrmZpn9h4AGwEcAPAmgIsAQCn1mohcB+ARvd6nM8GgAFwG4BsAauAFfmLwJyIiIiKK3LgUGwJE5SCyxqzunc08VwAuz7HebgC7syzfC+C0qPJDRERERDTStz64Ah0TOF89UTkw1TNLRERERAUal0rizeMn4s7GmHC6gwGxiCg7NmaJHHf2glb8+xNH4s4GERGV4H92rmZjlogoJFHK7WDA6XRa7d27N+5sEMXm5EmFt04qpCqKjudGRERERGQtEXlUKZUeuZw9s0SOSyQEKUZnJCIiIqIxhl05RERERERE5Bw2ZomIiIiIiMg5bMwSERERERGRc9iYJSIiIiIiIuewMUtERERERETOcX5qHhH5BYCX485HHhMA/DLuTFDJWI7lgeVYHliO7mMZlgeWY3lgOZaHci7HXwKAUmr9yBecb8zaTkT2ZpsTidzCciwPLMfywHJ0H8uwPLAcywPLsTyM1XLkMGMiIiIiIiJyDhuzRERERERE5Bw2Zs27Me4MUCRYjuWB5VgeWI7uYxmWB5ZjeWA5locxWY68Z5aIiIiIiIicw55ZIiIiIiIicg4bswaJyHoReU5EDojIzrjzQ4CI7BaRV0Vkv29Zi4jcJyIv6L/NermIyA26/J4QkSW+92zT678gItt8y5eKyJP6PTeIiIzuNyx/ItIuIg+IyNMi8pSI/LleznJ0iIhUi8jDIrJPl+O1enmniDykt/1tIpLSy6v0/wf06x2+tD6ulz8nIgO+5ayDR4GIJEXkMRH5rv6fZegYEXlJ13mPi8hevYx1qmNEpElE7hSRZ0XkGRHpZzm6RUS69e8w8zgmIlewHPNQSvFh4AEgCeBFAF0AUgD2AeiNO19j/QFgJYAlAPb7lv01gJ36+U4An9PPNwL4HgAB0AfgIb28BcBP9N9m/bxZv/awXlf0ezfE/Z3L7QGgFcAS/bwewPMAelmObj30tq3TzysBPKS3+e0ALtDLvwbgUv38MgBf088vAHCbft6r69cqAJ263k2yDh7VsvwIgG8B+K7+n2Xo2APASwAmjFjGOtWxB4B/AvBB/TwFoInl6O5D14GvAJjBcsz9YM+sOcsBHFBK/UQpdRzArQA2x5ynMU8p9UMAr41YvBneAQD673m+5bcoz4MAmkSkFcAAgPuUUq8ppV4HcB+A9fq1BqXUg8qrLW7xpUURUUodUUr9WD//NYBnAEwDy9Epujz+T/9bqR8KwGoAd+rlI8sxU753AlijryZvBnCrUur3SqmfAjgAr/5lHTwKRKQNwNkAbtL/C1iG5YJ1qkNEpBHeBfuvA4BS6rhS6ihYji5bA+BFpdTLYDnmxMasOdMAHPT9f0gvI/tMVkod0c9fATBZP89VhvmWH8qynAzRwxQXw+vVYzk6Rg9PfRzAq/AOtC8COKqUekuv4t/2g+WlX38DwHiEL1+K1hcBXAngpP5/PFiGLlIA/lNEHhWR7XoZ61S3dAL4BYCb9bD/m0SkFixHl10A4F/1c5ZjDmzMEvnoq1QM8e0AEakDcBeAK5RSx/yvsRzdoJQ6oZRaBKANXi9cT8xZohBEZBOAV5VSj8adFyrZGUqpJQA2ALhcRFb6X2Sd6oQKeLdRfVUptRjAb+ANRx3EcnSHjjVwLoA7Rr7GchyOjVlzDgNo9/3fppeRfX6uh11A/31VL89VhvmWt2VZThETkUp4DdlvKqW+rRezHB2lh8I9AKAf3hCpCv2Sf9sPlpd+vRHArxC+fCk6bwNwroi8BG8I8GoAfweWoXOUUof131cBfAfexSXWqW45BOCQUuoh/f+d8Bq3LEc3bQDwY6XUz/X/LMcc2Jg15xEAs8WL6piCN1RgT8x5ouz2AMhEedsG4G7f8q06UlwfgDf0EI97AawTkWYdTW4dgHv1a8dEpE/fB7bVlxZFRG/brwN4Rin1ed9LLEeHiMhEEWnSz2sArIV3//MDAN6pVxtZjpnyfSeA7+ur03sAXCBepNxOALPhBbdgHWyYUurjSqk2pVQHvO37faXUe8AydIqI1IpIfeY5vLpwP1inOkUp9QqAgyLSrRetAfA0WI6uuhBDQ4wBlmNu2aJC8RHNA16Esefh3Qe2K+788KEAr2I4AuAP8K5iXgzvnq3/AvACgPsBtOh1BcBXdPk9CSDtS+cD8IKUHABwkW95Gt5JwIsAvgxA4v7O5fYAcAa84TVPAHhcPzayHN16AFgA4DFdjvsBXK2Xd8FryByAN7yqSi+v1v8f0K93+dLapcvqOfiiMrIOHtXyPBND0YxZhg49dHnt04+nMtuZdap7DwCLAOzV9eq/wYtiy3J07AGgFt6olUbfMpZjjofoL0VERERERETkDA4zJiIiIiIiIuewMUtERERERETOYWOWiIiIiIiInMPGLBERERERETmHjVkiIiIiIiJyDhuzRERERERE5Bw2ZomIiIiIiMg5bMwSERERERGRc/4fm2rr9+HMvNcAAAAASUVORK5CYII=\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "# plot wave by audio frames\n",
+        "plt.figure(figsize=(16, 3))\n",
+        "plt.plot(data, '-', );"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "lzEiKmwg7fXz"
+      },
+      "source": [
+        "Ekstraksi menggunakan MFCC\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "EYQh2ECaiD4I"
+      },
+      "outputs": [],
+      "source": [
+        "def extract_mfcc(wav_file_name):\n",
+        "    #This function extracts mfcc features and obtain the mean of each dimension\n",
+        "    #Input : path_to_wav_file\n",
+        "    #Output: mfcc_features'''\n",
+        "    y, sr = librosa.load(wav_file_name)\n",
+        "    mfccs = np.mean(librosa.feature.mfcc(y=y, sr=sr, n_mfcc=40).T,axis=0)\n",
+        "    \n",
+        "    return mfccs"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ZEhSE-r9zRL1",
+        "outputId": "8b32ce30-33e7-40c6-bd88-e7e4741fd352"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
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+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0017.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0048.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0307.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0319.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0257.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0378.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0014.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0010.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0267.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0390.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0159.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0033.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0356.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0362 (1).wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0197.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0273.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0031.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0384.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0010.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0428.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0284.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0003.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0021.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0372.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0397.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0427.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0008.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0292.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0402.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0032.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0012.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0008.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0365 (1).wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0408.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0005.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0364.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0380.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0360.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0398.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0436.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0385.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0369.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0373.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0444.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0299.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0009.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0465.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0471.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0389.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0390.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0377.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0013.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0004.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0388.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0367 (1).wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0368.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0357 (1).wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0358 (1).wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0025.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0369.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0468.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0327.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0399.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0467.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0176.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0020.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0015.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0384.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0279.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0012.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0335.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0409.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0232.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0422.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0349.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0024.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0018.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0120.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0371.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0029.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0026.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0164.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0037.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0155.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0233.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0295.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0365.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0263.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0017.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0023.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0484.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0341.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0361.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0357.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0040.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0140.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0383.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0063.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0397.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0362.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0022.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0046.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0404.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0041.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0018.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0400.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0106.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0354.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0054.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0028.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0002.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0243.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0394.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0395.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0148.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0239.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0403.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0190.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0450.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0381.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0057.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0117.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0096.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0376.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0001.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0136.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0391.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0023.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0418.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0375.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0358.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0392.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0474.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0251.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0334.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0077.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0396.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0387.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0366.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0130.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0265.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0344.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0002.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0221.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0318.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0446.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0248.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0342.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0224.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0208.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0013.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0382.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0365.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0043.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0011.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/c0027.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0455.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0363.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0137.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0374.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0262.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0370.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0367.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0018.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0030.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0068.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0016.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0171.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0278.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/b0413.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/a0395.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0035.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e00048.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01013.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e00526.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e00847.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01856.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/f0003.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01084.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0028.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e02101.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01382.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01623.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e02030.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01365.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e00551.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01226.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0034.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01602.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01016.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e00142.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/d0022.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e02135.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01581.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01375.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e00998.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01272.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01668.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01756.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e00619.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e01787.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e00792.wav\n",
+            "/content/gdrive/MyDrive/heart_sound/train/unhealthy/e00305.wav\n"
+          ]
+        }
+      ],
+      "source": [
+        "##### load heart sound dataset #####\n",
+        "heart_sound_labels = [] # to save extracted label/file\n",
+        "heart_sound_data = [] # to save extracted features/file\n",
+        "subset_dirs_list = ['healthy', 'unhealthy']\n",
+        "\n",
+        "for dirname, dirs, filenames in os.walk(DATA_DIR+'/train/'):\n",
+        "    dirs[:] = [d for d in dirs if d in subset_dirs_list] # you can remove it to train the model over the entire dataset\n",
+        "    for filename in filenames[:500]:\n",
+        "        print(os.path.join(dirname, filename))\n",
+        "        heart_sound_labels.append(dirname)\n",
+        "        wav_file_name = os.path.join(dirname, filename)\n",
+        "        heart_sound_data.append(extract_mfcc(wav_file_name))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "print(heart_sound_data[0])"
+      ],
+      "metadata": {
+        "id": "6BN3idPFzvAX",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "7ad6a126-a1bc-4bdb-ac48-30074143c12e"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[-3.8871002e+02  1.3892465e+02  9.8952888e+01  5.1492561e+01\n",
+            "  1.4615340e+01 -1.0892975e+00  3.4092684e+00  1.7839680e+01\n",
+            "  2.9493780e+01  3.0431330e+01  2.0918722e+01  7.6602278e+00\n",
+            " -1.4322722e+00 -2.3407214e+00  3.1740789e+00  9.5958424e+00\n",
+            "  1.1760442e+01  8.1640263e+00  1.4404843e+00 -3.9433441e+00\n",
+            " -4.9063611e+00 -1.6533734e+00  2.8479555e+00  5.1911964e+00\n",
+            "  3.8888910e+00  1.6465628e-01 -3.1876323e+00 -3.8951457e+00\n",
+            " -1.7150207e+00  1.6135643e+00  3.7762253e+00  3.5384398e+00\n",
+            "  1.4726839e+00 -6.6054112e-01 -1.3057116e+00 -2.1532640e-01\n",
+            "  1.4971294e+00  2.3042653e+00  1.4483467e+00 -5.1705819e-01]\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "M1g0Yj2ViD4M",
+        "outputId": "c1e11d0c-6541-4d01-f729-5d4ef7cfa2a6"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
+            " 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
+            " 1]\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(1000,)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 12
+        }
+      ],
+      "source": [
+        "from sklearn.preprocessing import LabelEncoder\n",
+        "#### convert data and label to array\n",
+        "heart_sound_data_array = np.asarray(heart_sound_data) # convert the input to an array\n",
+        "heart_sound_label_array = np.array(heart_sound_labels)\n",
+        "\n",
+        "encoder = LabelEncoder()\n",
+        "heart_sound_label_array = encoder.fit_transform(heart_sound_label_array)\n",
+        "\n",
+        "# print(heart_sound_data_array)\n",
+        "print(heart_sound_label_array)\n",
+        "#### make categorical labels\n",
+        "labels_categorical = heart_sound_label_array # converts a class vector (integers) to binary class matrix\n",
+        "heart_sound_data_array.shape\n",
+        "labels_categorical.shape"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ava0maKTfH7R",
+        "outputId": "1cb9be3d-ef8a-46ce-e5c4-68ce81a39dd5"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "[[1. 0.]\n",
+            " [1. 0.]\n",
+            " [1. 0.]\n",
+            " ...\n",
+            " [0. 1.]\n",
+            " [0. 1.]\n",
+            " [0. 1.]]\n"
+          ]
+        }
+      ],
+      "source": [
+        "from numpy import array\n",
+        "from sklearn.preprocessing import OneHotEncoder\n",
+        "\n",
+        "onehot_encoder = OneHotEncoder(sparse=False)\n",
+        "integer_encoded = labels_categorical.reshape(len(labels_categorical), 1)\n",
+        "onehot_encoded = onehot_encoder.fit_transform(integer_encoded)\n",
+        "print(onehot_encoded)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "AeD_Gq8QiD4N"
+      },
+      "source": [
+        "## C. Split Train dan Test"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "oltO79lMiD4O"
+      },
+      "source": [
+        "*  Split the dataset into training and testing sets: (training set) a subset to train a model, (test set) a subset to test the trained model.\n",
+        "*  **Note:**(train_test_split) function will split arrays or matrices into random train and test subsets, in our example, training set 80% and testing set 20% "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "zTVc0YaKgEt3",
+        "outputId": "908d82f3-9cb3-45fe-9b82-360e66696854"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "(800, 200)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 14
+        }
+      ],
+      "source": [
+        "x_train,x_test,y_train,y_test= train_test_split(np.array(heart_sound_data_array), onehot_encoded, test_size=0.20, random_state=9)\n",
+        "len(y_train), len(y_test)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "rbKryB-2iD4V"
+      },
+      "source": [
+        "## D. Train and Test LSTM Classifier\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "FYQTBNNdiD4W"
+      },
+      "source": [
+        "* **What is Long short-term memory (LSTM)?**\n",
+        "\n",
+        "Recurrent neural networks, of which LSTMs are the most powerful and well known subset, are a type of artificial neural network designed to recognize patterns in sequences of data, such as text, genomes, handwriting and the spoken word. **More Details:** (https://keras.io/layers/recurrent/#lstm) "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "uOTvEB5KiD4X"
+      },
+      "outputs": [],
+      "source": [
+        "# Define the LSTM model\n",
+        "def create_model_BiLSTM():\n",
+        "    model = Sequential()\n",
+        "    model.add(Bidirectional(LSTM(128, return_sequences=False, input_shape=(40, 1))))\n",
+        "    model.add(Dense(64))\n",
+        "    model.add(Dropout(0.4))\n",
+        "    model.add(Activation('relu'))\n",
+        "    model.add(Dense(32))\n",
+        "    model.add(Dropout(0.4))\n",
+        "    model.add(Activation('relu'))\n",
+        "    model.add(Dense(2))\n",
+        "    model.add(Activation('softmax'))\n",
+        "    \n",
+        "    # Configures the model for training\n",
+        "    model.compile(loss='categorical_crossentropy', optimizer='Adam', metrics=['accuracy'])\n",
+        "    return model"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "NUpH4QYyHV25"
+      },
+      "outputs": [],
+      "source": [
+        "model_BiLSTM = create_model_BiLSTM()\n",
+        "model_BiLSTM.build(input_shape=(None ,40, 1))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "n6xzAQ3C_3il",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "outputId": "f475ed9f-572d-4ede-d9df-9baed2b45581"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<IPython.core.display.Image object>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 17
+        }
+      ],
+      "source": [
+        "# plot the model including the sizes of the model\n",
+        "tf.keras.utils.plot_model(model_BiLSTM, show_shapes=True)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "tjCU19lsiD4Y",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "6b242a0f-ba92-45ab-db16-1ba6909a109e"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Epoch 1/100\n",
+            "25/25 [==============================] - 8s 168ms/step - loss: 0.6291 - accuracy: 0.6388 - val_loss: 0.4833 - val_accuracy: 0.8000\n",
+            "Epoch 2/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.4343 - accuracy: 0.8225 - val_loss: 0.3450 - val_accuracy: 0.8450\n",
+            "Epoch 3/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.3494 - accuracy: 0.8575 - val_loss: 0.3260 - val_accuracy: 0.8600\n",
+            "Epoch 4/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.3276 - accuracy: 0.8750 - val_loss: 0.2926 - val_accuracy: 0.8700\n",
+            "Epoch 5/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.3100 - accuracy: 0.8925 - val_loss: 0.3700 - val_accuracy: 0.8450\n",
+            "Epoch 6/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.2601 - accuracy: 0.9050 - val_loss: 0.2797 - val_accuracy: 0.8700\n",
+            "Epoch 7/100\n",
+            "25/25 [==============================] - 2s 87ms/step - loss: 0.2869 - accuracy: 0.9000 - val_loss: 0.2741 - val_accuracy: 0.8800\n",
+            "Epoch 8/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.2473 - accuracy: 0.9087 - val_loss: 0.3185 - val_accuracy: 0.8600\n",
+            "Epoch 9/100\n",
+            "25/25 [==============================] - 2s 91ms/step - loss: 0.2128 - accuracy: 0.9175 - val_loss: 0.3493 - val_accuracy: 0.8600\n",
+            "Epoch 10/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.2303 - accuracy: 0.9125 - val_loss: 0.2227 - val_accuracy: 0.9050\n",
+            "Epoch 11/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.2216 - accuracy: 0.9175 - val_loss: 0.2173 - val_accuracy: 0.8950\n",
+            "Epoch 12/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.1592 - accuracy: 0.9463 - val_loss: 0.2092 - val_accuracy: 0.9300\n",
+            "Epoch 13/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.1677 - accuracy: 0.9362 - val_loss: 0.1654 - val_accuracy: 0.9400\n",
+            "Epoch 14/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.1464 - accuracy: 0.9513 - val_loss: 0.1535 - val_accuracy: 0.9300\n",
+            "Epoch 15/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.1628 - accuracy: 0.9425 - val_loss: 0.3349 - val_accuracy: 0.8550\n",
+            "Epoch 16/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.2275 - accuracy: 0.9150 - val_loss: 0.2829 - val_accuracy: 0.8950\n",
+            "Epoch 17/100\n",
+            "25/25 [==============================] - 2s 92ms/step - loss: 0.1802 - accuracy: 0.9350 - val_loss: 0.1506 - val_accuracy: 0.9450\n",
+            "Epoch 18/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.1475 - accuracy: 0.9475 - val_loss: 0.1787 - val_accuracy: 0.9400\n",
+            "Epoch 19/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.1144 - accuracy: 0.9563 - val_loss: 0.1205 - val_accuracy: 0.9600\n",
+            "Epoch 20/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0976 - accuracy: 0.9650 - val_loss: 0.1506 - val_accuracy: 0.9550\n",
+            "Epoch 21/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.1381 - accuracy: 0.9600 - val_loss: 0.1371 - val_accuracy: 0.9700\n",
+            "Epoch 22/100\n",
+            "25/25 [==============================] - 2s 87ms/step - loss: 0.1167 - accuracy: 0.9575 - val_loss: 0.1565 - val_accuracy: 0.9600\n",
+            "Epoch 23/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.1089 - accuracy: 0.9650 - val_loss: 0.1596 - val_accuracy: 0.9450\n",
+            "Epoch 24/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.1029 - accuracy: 0.9663 - val_loss: 0.1023 - val_accuracy: 0.9700\n",
+            "Epoch 25/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.1010 - accuracy: 0.9613 - val_loss: 0.1222 - val_accuracy: 0.9700\n",
+            "Epoch 26/100\n",
+            "25/25 [==============================] - 2s 87ms/step - loss: 0.0928 - accuracy: 0.9725 - val_loss: 0.1641 - val_accuracy: 0.9350\n",
+            "Epoch 27/100\n",
+            "25/25 [==============================] - 2s 87ms/step - loss: 0.0988 - accuracy: 0.9638 - val_loss: 0.1406 - val_accuracy: 0.9600\n",
+            "Epoch 28/100\n",
+            "25/25 [==============================] - 2s 87ms/step - loss: 0.0801 - accuracy: 0.9712 - val_loss: 0.1353 - val_accuracy: 0.9450\n",
+            "Epoch 29/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0638 - accuracy: 0.9800 - val_loss: 0.1126 - val_accuracy: 0.9650\n",
+            "Epoch 30/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0902 - accuracy: 0.9688 - val_loss: 0.1852 - val_accuracy: 0.9400\n",
+            "Epoch 31/100\n",
+            "25/25 [==============================] - 2s 87ms/step - loss: 0.0955 - accuracy: 0.9613 - val_loss: 0.1377 - val_accuracy: 0.9550\n",
+            "Epoch 32/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0691 - accuracy: 0.9712 - val_loss: 0.0987 - val_accuracy: 0.9550\n",
+            "Epoch 33/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0931 - accuracy: 0.9600 - val_loss: 0.1278 - val_accuracy: 0.9600\n",
+            "Epoch 34/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0820 - accuracy: 0.9737 - val_loss: 0.1700 - val_accuracy: 0.9400\n",
+            "Epoch 35/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0774 - accuracy: 0.9712 - val_loss: 0.1389 - val_accuracy: 0.9650\n",
+            "Epoch 36/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0809 - accuracy: 0.9725 - val_loss: 0.2939 - val_accuracy: 0.9150\n",
+            "Epoch 37/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.1397 - accuracy: 0.9513 - val_loss: 0.1654 - val_accuracy: 0.9350\n",
+            "Epoch 38/100\n",
+            "25/25 [==============================] - 2s 87ms/step - loss: 0.1039 - accuracy: 0.9663 - val_loss: 0.1673 - val_accuracy: 0.9400\n",
+            "Epoch 39/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0733 - accuracy: 0.9750 - val_loss: 0.1252 - val_accuracy: 0.9550\n",
+            "Epoch 40/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0524 - accuracy: 0.9862 - val_loss: 0.1008 - val_accuracy: 0.9600\n",
+            "Epoch 41/100\n",
+            "25/25 [==============================] - 2s 87ms/step - loss: 0.0497 - accuracy: 0.9825 - val_loss: 0.1046 - val_accuracy: 0.9550\n",
+            "Epoch 42/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0887 - accuracy: 0.9638 - val_loss: 0.0976 - val_accuracy: 0.9500\n",
+            "Epoch 43/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0875 - accuracy: 0.9762 - val_loss: 0.1026 - val_accuracy: 0.9700\n",
+            "Epoch 44/100\n",
+            "25/25 [==============================] - 2s 87ms/step - loss: 0.0651 - accuracy: 0.9787 - val_loss: 0.1525 - val_accuracy: 0.9450\n",
+            "Epoch 45/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0581 - accuracy: 0.9850 - val_loss: 0.1343 - val_accuracy: 0.9600\n",
+            "Epoch 46/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0663 - accuracy: 0.9800 - val_loss: 0.0957 - val_accuracy: 0.9750\n",
+            "Epoch 47/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0538 - accuracy: 0.9825 - val_loss: 0.0894 - val_accuracy: 0.9750\n",
+            "Epoch 48/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0383 - accuracy: 0.9862 - val_loss: 0.1272 - val_accuracy: 0.9550\n",
+            "Epoch 49/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0516 - accuracy: 0.9825 - val_loss: 0.1103 - val_accuracy: 0.9600\n",
+            "Epoch 50/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0692 - accuracy: 0.9787 - val_loss: 0.0982 - val_accuracy: 0.9700\n",
+            "Epoch 51/100\n",
+            "25/25 [==============================] - 2s 91ms/step - loss: 0.0460 - accuracy: 0.9875 - val_loss: 0.0480 - val_accuracy: 0.9850\n",
+            "Epoch 52/100\n",
+            "25/25 [==============================] - 4s 165ms/step - loss: 0.0418 - accuracy: 0.9825 - val_loss: 0.1093 - val_accuracy: 0.9650\n",
+            "Epoch 53/100\n",
+            "25/25 [==============================] - 3s 109ms/step - loss: 0.0513 - accuracy: 0.9825 - val_loss: 0.1102 - val_accuracy: 0.9700\n",
+            "Epoch 54/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0648 - accuracy: 0.9812 - val_loss: 0.1103 - val_accuracy: 0.9600\n",
+            "Epoch 55/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0881 - accuracy: 0.9825 - val_loss: 0.0966 - val_accuracy: 0.9650\n",
+            "Epoch 56/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0538 - accuracy: 0.9825 - val_loss: 0.0458 - val_accuracy: 0.9800\n",
+            "Epoch 57/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0822 - accuracy: 0.9700 - val_loss: 0.1196 - val_accuracy: 0.9600\n",
+            "Epoch 58/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0414 - accuracy: 0.9850 - val_loss: 0.0572 - val_accuracy: 0.9750\n",
+            "Epoch 59/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0288 - accuracy: 0.9887 - val_loss: 0.0665 - val_accuracy: 0.9700\n",
+            "Epoch 60/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0873 - accuracy: 0.9688 - val_loss: 0.1118 - val_accuracy: 0.9500\n",
+            "Epoch 61/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0639 - accuracy: 0.9787 - val_loss: 0.0885 - val_accuracy: 0.9600\n",
+            "Epoch 62/100\n",
+            "25/25 [==============================] - 2s 91ms/step - loss: 0.0520 - accuracy: 0.9825 - val_loss: 0.0785 - val_accuracy: 0.9550\n",
+            "Epoch 63/100\n",
+            "25/25 [==============================] - 2s 93ms/step - loss: 0.0379 - accuracy: 0.9837 - val_loss: 0.1181 - val_accuracy: 0.9500\n",
+            "Epoch 64/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0667 - accuracy: 0.9837 - val_loss: 0.1728 - val_accuracy: 0.9350\n",
+            "Epoch 65/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0319 - accuracy: 0.9900 - val_loss: 0.1088 - val_accuracy: 0.9700\n",
+            "Epoch 66/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0655 - accuracy: 0.9775 - val_loss: 0.0603 - val_accuracy: 0.9650\n",
+            "Epoch 67/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0450 - accuracy: 0.9862 - val_loss: 0.0924 - val_accuracy: 0.9700\n",
+            "Epoch 68/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0482 - accuracy: 0.9787 - val_loss: 0.1343 - val_accuracy: 0.9500\n",
+            "Epoch 69/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0689 - accuracy: 0.9725 - val_loss: 0.1440 - val_accuracy: 0.9500\n",
+            "Epoch 70/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0676 - accuracy: 0.9850 - val_loss: 0.0673 - val_accuracy: 0.9800\n",
+            "Epoch 71/100\n",
+            "25/25 [==============================] - 2s 91ms/step - loss: 0.0474 - accuracy: 0.9837 - val_loss: 0.1076 - val_accuracy: 0.9750\n",
+            "Epoch 72/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0543 - accuracy: 0.9787 - val_loss: 0.0667 - val_accuracy: 0.9800\n",
+            "Epoch 73/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0493 - accuracy: 0.9800 - val_loss: 0.0861 - val_accuracy: 0.9650\n",
+            "Epoch 74/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0413 - accuracy: 0.9850 - val_loss: 0.0781 - val_accuracy: 0.9700\n",
+            "Epoch 75/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0338 - accuracy: 0.9900 - val_loss: 0.0853 - val_accuracy: 0.9800\n",
+            "Epoch 76/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0426 - accuracy: 0.9875 - val_loss: 0.0966 - val_accuracy: 0.9700\n",
+            "Epoch 77/100\n",
+            "25/25 [==============================] - 2s 91ms/step - loss: 0.0284 - accuracy: 0.9887 - val_loss: 0.0959 - val_accuracy: 0.9800\n",
+            "Epoch 78/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0479 - accuracy: 0.9825 - val_loss: 0.0830 - val_accuracy: 0.9700\n",
+            "Epoch 79/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0245 - accuracy: 0.9925 - val_loss: 0.1022 - val_accuracy: 0.9800\n",
+            "Epoch 80/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0190 - accuracy: 0.9925 - val_loss: 0.0917 - val_accuracy: 0.9850\n",
+            "Epoch 81/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0324 - accuracy: 0.9887 - val_loss: 0.1564 - val_accuracy: 0.9550\n",
+            "Epoch 82/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0954 - accuracy: 0.9725 - val_loss: 0.1226 - val_accuracy: 0.9600\n",
+            "Epoch 83/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0370 - accuracy: 0.9912 - val_loss: 0.0977 - val_accuracy: 0.9750\n",
+            "Epoch 84/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0274 - accuracy: 0.9900 - val_loss: 0.1122 - val_accuracy: 0.9750\n",
+            "Epoch 85/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0301 - accuracy: 0.9887 - val_loss: 0.1226 - val_accuracy: 0.9650\n",
+            "Epoch 86/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0645 - accuracy: 0.9750 - val_loss: 0.2129 - val_accuracy: 0.9500\n",
+            "Epoch 87/100\n",
+            "25/25 [==============================] - 2s 91ms/step - loss: 0.0265 - accuracy: 0.9925 - val_loss: 0.1686 - val_accuracy: 0.9700\n",
+            "Epoch 88/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0650 - accuracy: 0.9850 - val_loss: 0.1250 - val_accuracy: 0.9750\n",
+            "Epoch 89/100\n",
+            "25/25 [==============================] - 2s 91ms/step - loss: 0.0260 - accuracy: 0.9925 - val_loss: 0.1120 - val_accuracy: 0.9900\n",
+            "Epoch 90/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0418 - accuracy: 0.9887 - val_loss: 0.0957 - val_accuracy: 0.9650\n",
+            "Epoch 91/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0427 - accuracy: 0.9812 - val_loss: 0.0805 - val_accuracy: 0.9750\n",
+            "Epoch 92/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0209 - accuracy: 0.9950 - val_loss: 0.1224 - val_accuracy: 0.9600\n",
+            "Epoch 93/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0277 - accuracy: 0.9887 - val_loss: 0.1321 - val_accuracy: 0.9700\n",
+            "Epoch 94/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0355 - accuracy: 0.9875 - val_loss: 0.0981 - val_accuracy: 0.9600\n",
+            "Epoch 95/100\n",
+            "25/25 [==============================] - 2s 91ms/step - loss: 0.0483 - accuracy: 0.9850 - val_loss: 0.0999 - val_accuracy: 0.9750\n",
+            "Epoch 96/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0214 - accuracy: 0.9925 - val_loss: 0.0909 - val_accuracy: 0.9750\n",
+            "Epoch 97/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0265 - accuracy: 0.9900 - val_loss: 0.1707 - val_accuracy: 0.9700\n",
+            "Epoch 98/100\n",
+            "25/25 [==============================] - 2s 88ms/step - loss: 0.0601 - accuracy: 0.9850 - val_loss: 0.0736 - val_accuracy: 0.9800\n",
+            "Epoch 99/100\n",
+            "25/25 [==============================] - 2s 89ms/step - loss: 0.0350 - accuracy: 0.9887 - val_loss: 0.1197 - val_accuracy: 0.9800\n",
+            "Epoch 100/100\n",
+            "25/25 [==============================] - 2s 90ms/step - loss: 0.0394 - accuracy: 0.9875 - val_loss: 0.0835 - val_accuracy: 0.9800\n"
+          ]
+        }
+      ],
+      "source": [
+        "### train using LSTM model\n",
+        "model_A = create_model_BiLSTM()\n",
+        "# history = model_A.fit(np.expand_dims(heart_sound_data_array[:training_samples],-1), labels_categorical[:training_samples], validation_data=(np.expand_dims(heart_sound_data_array[training_samples:training_samples+validation_samples], -1), labels_categorical[training_samples:training_samples+validation_samples]), epochs=50, shuffle=True)\n",
+        "history = model_A.fit(np.expand_dims(x_train,-1),\n",
+        "                    y = y_train,\n",
+        "                    validation_data = (np.expand_dims(x_test,-1), y_test),\n",
+        "                    epochs=100,\n",
+        "                    shuffle = True)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "hbe0iRz-YAYn",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "92a83fca-dcc3-4b93-e606-60e8476422c3"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Model: \"sequential_1\"\n",
+            "_________________________________________________________________\n",
+            " Layer (type)                Output Shape              Param #   \n",
+            "=================================================================\n",
+            " bidirectional_1 (Bidirectio  (None, 256)              133120    \n",
+            " nal)                                                            \n",
+            "                                                                 \n",
+            " dense_3 (Dense)             (None, 64)                16448     \n",
+            "                                                                 \n",
+            " dropout_2 (Dropout)         (None, 64)                0         \n",
+            "                                                                 \n",
+            " activation_3 (Activation)   (None, 64)                0         \n",
+            "                                                                 \n",
+            " dense_4 (Dense)             (None, 32)                2080      \n",
+            "                                                                 \n",
+            " dropout_3 (Dropout)         (None, 32)                0         \n",
+            "                                                                 \n",
+            " activation_4 (Activation)   (None, 32)                0         \n",
+            "                                                                 \n",
+            " dense_5 (Dense)             (None, 2)                 66        \n",
+            "                                                                 \n",
+            " activation_5 (Activation)   (None, 2)                 0         \n",
+            "                                                                 \n",
+            "=================================================================\n",
+            "Total params: 151,714\n",
+            "Trainable params: 151,714\n",
+            "Non-trainable params: 0\n",
+            "_________________________________________________________________\n"
+          ]
+        }
+      ],
+      "source": [
+        "model_A.summary()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "F8u8JqttiD4Y",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 295
+        },
+        "outputId": "8ced4c9c-721e-4563-fa26-5e058216e3fb"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "### loss plots using LSTM model\n",
+        "loss = history.history['loss']\n",
+        "val_loss = history.history['val_loss']\n",
+        "\n",
+        "epochs = range(1, len(loss) + 1)\n",
+        "\n",
+        "plt.plot(epochs, loss, 'ro', label='Training loss')\n",
+        "plt.plot(epochs, val_loss, 'b', label='Validation loss')\n",
+        "plt.title('Training and validation loss')\n",
+        "plt.xlabel('Epochs')\n",
+        "plt.ylabel('Loss')\n",
+        "plt.legend()\n",
+        "\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "G7yEDALLiD4Z",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 295
+        },
+        "outputId": "04216f45-74a5-4e73-d0de-e077e508babf"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "### accuracy plots using LSTM model\n",
+        "plt.clf()                                                \n",
+        "\n",
+        "acc = history.history['accuracy']\n",
+        "val_acc = history.history['val_accuracy']\n",
+        "\n",
+        "plt.plot(epochs, acc, 'ro', label='Training acc')\n",
+        "plt.plot(epochs, val_acc, 'b', label='Validation acc')\n",
+        "plt.title('Training and validation accuracy')\n",
+        "plt.xlabel('Epochs')\n",
+        "plt.ylabel('Loss')\n",
+        "plt.legend()\n",
+        "\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "_tnxWVX7iD4a"
+      },
+      "source": [
+        "*  **(evaluate function): Returns the loss value & metrics values for the model in test mode.**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "uRx7vcyfiD4b",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "6df2edc9-9a19-4fe2-f687-41eef87d8aaa"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "7/7 [==============================] - 0s 28ms/step - loss: 0.0835 - accuracy: 0.9800\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[0.08349721133708954, 0.9800000190734863]"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 22
+        }
+      ],
+      "source": [
+        "### evaluate using model A\n",
+        "model_A.evaluate(np.expand_dims(x_test, -1), y_test)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "dAV_0JrZiD4b"
+      },
+      "source": [
+        "* **Save the weights of the model as a HDF5 file**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "6lYFPCH6iD4c"
+      },
+      "outputs": [],
+      "source": [
+        "model_A.save_weights(\"Model_LSTM.h5\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "d4ZHczoH23Yr",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "3ab467a6-baa9-4449-f876-2ba5d550caf6"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "7/7 [==============================] - 1s 28ms/step\n"
+          ]
+        }
+      ],
+      "source": [
+        "y_pred = model_A.predict(np.expand_dims(x_test,-1))\n",
+        "y_pred = np.argmax(y_pred, axis=1)\n",
+        "# y_test = np.expand_dims(y_test,-1)\n",
+        "y_true = np.argmax(y_test, axis=1)\n",
+        "y_true\n",
+        "\n",
+        "conf_heart_sound = confusion_matrix(y_true=y_true, y_pred=y_pred)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "K87a-Nds3kLC",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 312
+        },
+        "outputId": "d846665d-a0f2-47b3-bf53-4968baefc20b"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[Text(0, 0.5, 'healthy'), Text(0, 1.5, 'unhealthy')]"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 25
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 2 Axes>"
+            ],
+            "image/png": "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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "ax = plt.subplot()\n",
+        "sns.heatmap(conf_heart_sound, annot= True, ax = ax)\n",
+        "\n",
+        "ax.set_xlabel('Predict labels')\n",
+        "ax.set_title('Confusion Matrix')\n",
+        "ax.xaxis.set_ticklabels(['healthy','unhealthy'])\n",
+        "ax.yaxis.set_ticklabels(['healthy','unhealthy'])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "5EcXK-yJ7U0-",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "ed59fa4b-1eb9-459c-f058-d4666e211b45"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "7/7 [==============================] - 0s 31ms/step\n",
+            "              precision    recall  f1-score   support\n",
+            "\n",
+            "     Healthy       0.96      1.00      0.98        98\n",
+            "   Unhealthy       1.00      0.96      0.98       102\n",
+            "\n",
+            "    accuracy                           0.98       200\n",
+            "   macro avg       0.98      0.98      0.98       200\n",
+            "weighted avg       0.98      0.98      0.98       200\n",
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Menampilkan nilai presisi, recall, dan F1-score\n",
+        "pred_A = model_A.predict(np.expand_dims(x_test, -1))\n",
+        "modelA_predicted = np.argmax(pred_A, axis = 1)\n",
+        "\n",
+        "File=[\"Healthy\", \"Unhealthy\"]\n",
+        "print(classification_report(y_test.argmax(axis=1), modelA_predicted, target_names=File))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Grv7G3xrIUOW",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "373b6fb7-2a0c-4d70-a0d5-5bae84db2768"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "7/7 [==============================] - 0s 28ms/step\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Menampilkan kurva AUC-ROC\n",
+        "Y_pred = model_A.predict(np.expand_dims(x_test, -1))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "2J5rYwa5JK-7"
+      },
+      "outputs": [],
+      "source": [
+        "n_classes = 2\n",
+        "lw = 1\n",
+        "Y_val = y_test\n",
+        "fpr = dict()\n",
+        "tpr = dict()\n",
+        "roc_auc = dict()\n",
+        "for i in range(n_classes):\n",
+        "    fpr[i], tpr[i], _ = roc_curve(Y_val[:, i], Y_pred[:, i])\n",
+        "    roc_auc[i] = auc(fpr[i], tpr[i])\n",
+        "\n",
+        "# Compute micro-average ROC curve and ROC area\n",
+        "fpr[\"micro\"], tpr[\"micro\"], _ = roc_curve(Y_val.ravel(), Y_pred.ravel())\n",
+        "roc_auc[\"micro\"] = auc(fpr[\"micro\"], tpr[\"micro\"])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "L0lSe1mqJWEC",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 548
+        },
+        "outputId": "42c6fe2f-edb4-45c4-b4fd-e8bad4f2434f"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "<ipython-input-29-c858286738c8>:7: DeprecationWarning: scipy.interp is deprecated and will be removed in SciPy 2.0.0, use numpy.interp instead\n",
+            "  mean_tpr += interp(all_fpr, fpr[i], tpr[i])\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 576x576 with 1 Axes>"
+            ],
+            "image/png": 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1cxW6It+gQQO+++67oGOIiIgUCjP7Le+5sqfuehERkQSlIi8iIpKgVORFREQSlIq8iIhIglKRFxERSVAq8iIiIglKRV5ERCRBqciLiIgkKBV5ERGRBKUiLyIikqBU5EVERBKUiryIiEiCUpEXERFJUCryIiIiCUpFXkREJEHFrMib2XtmttHMluQw3czsNTNbaWaLzOzcWGUREREpikrEcNnDgDeA4TlM7wSc5v9dAAz2/0tI7dx5gM8+W0FqahoAxYoZN97YLNt5f/xxE99+uzZjuHHjalxwQZ1s5/3005/Yvn1/xvBVVzWicuUyR823ceMeJk78OWO4evVydO58WrbLnDNnNatWbc0YbtWqHqeeWuWo+dLS0hk5clHGsLZJ26Rt0jYFsU35Zc65415Ijgs3awB85pw7K5tpbwMznXOj/eHlQLJzbn1uy2zRooX77rvvYpBWcjJ8+A/Mn7+WzZv3sXnzXp5+un22L8zffttOgwavZgyXKlWcAwf6Z7vM11//hvvum5Qx3KfPebz+euds5z377MEsWbIxY3jRojs5++yaR8339ddraNXqvYzhli3r8PXXt2a7zF69PuGf//whY/gf/7iaXr3OOWq+AwcOkZT0TDi26fL3+efklZnbVL4cvc6vC9O6575NwIFqVWFgMtx05Fv1qG1KSuL18uVgU5+8t6nSCZx9S1N4+eLct6lECb6udAJ80Q2a1Thym7I+T9ombVOR3KYBC5xzLY6aKQqxbMnnpTawJmI4xR+Xa5HPy2+/bWfevJSM4Xr1TqBly7rZzjtjxn/ZuHFPxnBycgNq1ix/1Hy7dh3g888zv/2VL1+KK644PdtlLlz4O8uXb84YbtbsRBo3rpbtvP/+9zIOHUrPGP5//+8MSpYsXijb9J//rKdfv+ls3ryXLVv20qJFLcaMuS7bZY4bt5x///vHjOHbbmuebZGvXr1ctveXQvLd70EnEJECd3wN8SBb8p8Bzzvn5vjD04BHnXNHNdPN7A7gDoB69er94bfffsuc+K8qcHBbLOJLPlVZBdvS855PRERy8V9gDrCKULbk1wKRzdE6/rijOOfeAd4Br7v+iIkHt8H1maNGj17M9dd/nDHco8dZjB59bbYB2rf/JzNn/poxPL1iRdqXKukN3Ngko6tnxYotNGr0RsZ8p5UpyYpyFTMXFNHV07fvFAYOnJsx6aWyZelb1t831LT6EV09FSs+x65dBzOGd1SpTMVi/rGQEV09R21TqVKMrlghc/0RXT353aaGSSVZVT77berffzrPPDM7Y9KAsmX4v7Jls92mu+76jG0nduGmX8ZSYsHvDN1wKHOZEds0deoqRo5cnDGpw8eruDGpdLbb1K/fNFJSdnkDq7bx9LKd1C1e/Kht+vnnLTz9dGbOU2ev5S+7Il4uEds0ZMgC5szxO5K27uO22b/TpmTJo7YpNTWN224bn7GIUGzTkk2wdAu3JZWmzR9qHdW9mLFN89fDLzsoAQytUD7b7sWMbfrwJ2+bSpb0timb7sV+/aaR8uVq+G4DAE+XLUPdXmcf1WWasU1T/gvbDnBq8WL8pWzZbLtMhwxZwJxxK2Cq98Ve26RtKirb1LXrU0wY9zfa0oMpDDlqerSCbMlfAfQBOuMdcPeac+78vJZ51D75URZdka/+BkfY1KdIF/mtW/dRteqLmVmKF2NH5crZbtNXX63m22/XUq1aWartPMgZf/maBocLUpZtArAnDfd/Dh6aDiOWZU7I5kWfIZvnJ1vDl8DDMzOHI7bpKJd8CIs2ZbtNR/hhI3QYkzmczTZlCMs2iUhorV69mosuuohPP/2UP/zhD5hZ/LXkzWw0kAxUM7MU4P+AkgDOubeAz/EK/EpgL3DLsSx/8+a9VKhQitJZxterdwLdup2ZMXzhhbVzXEZycn1q1PD3I/+6gxordmU7X/nypY5Y5klfr4McDnps1qxm5rzb99No7sbsZ8TbB79vn98qXLiBEluy7+M+apsm/DfHZUa7TZUqJTFuXA+vcFcrS9VbJ8OPW7Odt1WrerRqVc8b+GEjFP8mx/WLiEj+/fDDDzRr1owff/yRChUq5H2HPMS0JR8LJeqUcGm3pwUdQ3JROakyWx/N/guDiIgczTnHX/7yFz7++GO+//57SpfObMLGZUs+VtLS03D/5zjxxL+xYcMe3PsDsBsGsHr1A9SdsebImSO7UaPtOhURESlE6enp9OnTh2+++YYvv/zyiAJ/vEJX5MG7+MCmTXuPGFejRrkj92vCkUVeRV1EROLQ3r17KV68ODNmzKBixYp53+EYhPLa9Tt3HqB69bIUK2aAt3+5dOlQfl8REZEiau/evdx3332kpqby+uuvF3iBh5AW+cqVy/D77305eNC78ti8ef4VwG5skjlT/YJ/sERERArC9u3b6dixI9u3b6d8+aMvWFZQQlnkDyte3IvfqFGWK8rVrwh/Sy78QCIiInk4dOgQHTp0oEWLFgwbNoySh6/REQOhO7reaplz6yIyZzlPXkREJF7t3r2b8uXLs3DhQpo1a4aZ5Xmf4zm6PtQteRERkbBYunQpTZo04aeffuKcc86JqsAfr3AX+Us+zPx/+LaIiEic+eabb7jkkkt47rnnaNy4caGtN9yHpB++vGfkZT5FRETizHPPPce7777LlVdeWajrDWWRf/vt79i2bT819+/nFmB7ejqVioW7U0JERBLPhAkTOO+88xg7dmyhdM9nFcrK+NZbC3j88Wn03u39bvqKNF3mVkRE4st7773H7bffzoYNGwIp8BDSlvyGDbuPGK45+iqodfwX8hcRESkIr7zyCq+++iozZ87k9NNPDyxHKIv8xo17jhiu2b4+JIVyU0REJIE45zAzTjnlFObMmUOdOnUCzRPKyvjss5ewYcNuNmzwin2SCryIiAQsLS2Ne+65h+TkZHr06BF0HCCkRf7Pl52WObA0uBwiIiIABw8e5MYbb2Tz5s289NJLQcfJEMoiT4cxmbdfDS6GiIgIwJNPPsnBgweZMGECSUlJQcfJEM4iLyIiEge2bdvG/v37efzxx0lKSqJEifgqq6E8hU5ERCRo69evp127dowePZry5cvHXYGHsLbkm1YPOoGIiBRhv/zyCx07dqR37948+OCDQcfJkX6FTkRE5BiNHz+elJQU7rrrrpiv63h+hS6ULfkaNV6iRo1y1KxZnmm3Bp1GRESKirlz5/Kf//yHe+65J+goUQnlPvlNm/aydOkmpk//b9BRRESkiJgyZQpXXXUVJ598ctBRohbKlryIiEhhmjlzJjfeeCNjx46ldevWQceJmoq8iIhILvbu3ct5553HjBkzaNKkSdBxjkkoi/zatQ+xYcNu7xr2WwYEHUdERBLUCy+8wIwZM5g0aVLoCjyEtMjX+tt8ah0eyNfxhiIiIjlzzvHoo48yYcIEpkyZEnScfAtlkWfEsszbKvIiIlLAFi9ezNdff82sWbOoWrVq0HHyLZRH14uIiMTCgQMH+Pjjj2natCmzZ88OdYEHFXkREREAdu/eTZcuXXj//fdJT0/HzIKOdNzC2V0/MDnoBCIikkC2bdtGp06dOPPMM3n77bcpViwx2sChLPJTTixDzZrlOOWUKpQfF3QaEREJu6SkJHr16sWf/vSnhGjBHxbKryqXXTaSc855mylTVgUdRUREQmzVqlVceumlpKenc+eddyZUgYeQFvnDatYsF3QEEREJqUWLFtG2bVu6du1KuXKJWU9C2V1/WI0a5eC3oFOIiEjY7N27lyuvvJKXX36Z7t27Bx0nZkJZ5JOTG7Bhw25q1iwfdBQREQmZn3/+mdNOO43vv/8+9KfI5SWU3fUzZtzMsmX3ULFi6aCjiIhIiHz44Ye0bt2a9evXJ3yBh5C25Kn+RubtV4OLISIi4fH222/z1FNPMXXqVE466aSg4xSKcBZ5ERGRY5Cens53333Hl19+yamnnhp0nEITyu56ERGRaDjneOaZZ0hJSWHIkCFFqsCDiryIiCSoQ4cOcdttt/HZZ59RvnzRPFA7nN31m/pk3h51b3A5REQkbt1yyy1s3LiRL774ImHPg89LKFvyN9/8CV9/vSboGCIiEof279+Pc4777ruPcePGFdkCDyEt8sOH/8DatTuDjiEiInFmy5YttG3bls8//5zzzjuP0qWL9qnWoSzygC6EIyIiR0hJSaFNmzZcfPHFdO7cOeg4cSGc++TRdetFRORIzzzzDLfccguPPPJI0FHiRiiL/JAhXahb94SgY4iISBxYuHAhFSpU4M0330yY34EvKKF8NG4rVYqy/1oOw5cEHUVERAI0e/ZsOnbsyLJly1TgsxHKljwPz8y8rcvaiogUSZ9//jk333wzo0aN4tJLLw06TlwKZ5EXEZEiLykpifHjx3PhhRcGHSVuqciLiEioDBo0iD179ugAuyiEs8jf2CToBCIiUsgOX4d+2LBhTJ06Neg4oRDOIv/yxZm3RwUXQ0RECs+IESP46KOPmDNnDieeeGLQcULBnHNBZzgmVsucWxeReZTB9eHaBhERid6hQ4dYv349NWrUYN++fVSqVCnoSIXKzBY451rk577hbMmLiEiRsH//fnr06EHVqlUZOnRokb9M7bHSSYUiIhKXdu7cSefOnUlKSmLw4MFBxwklFXkREYlLP/30E02bNuX999+nVKlSQccJJXXXi4hIXElJSeGDDz6gb9++nH/++UHHCbVwtuQv+TDzT0REEsaKFSto3bo1ZhZ0lIQQzpb8ok1BJxARkQK2atUqkpOTefrpp+ndu3fQcRJCOIu8iIgklIMHD1KvXj0+/PBD2rRpE3SchBHO7noREUkY48eP57zzzsPMVOALWDhb8l90y7y99N7gcoiIyHEZOXIkffv2Zdy4cZQoEc6SFM/C+Yg2q5F5e2lwMUREJP82b97Ms88+y/Tp02nSRL9JEgvqrhcRkULlnGPChAlUrVqVxYsXq8DHkIq8iIgUmvT0dB544AH69evHrl27KF68eNCRElo4u+tFRCR0UlNT6d27N//973+ZOXMmFStWDDpSwlNLXkRECkWxYsU4++yzmTJlSpH7JbmghLPI/7Ax809EROLajh076Nq1K+vWrePPf/4zZcuWDTpSkRHO7voOYzJvvxpcDBERyd3GjRu5/PLLadmyJbVr1w46TpETzpa8iIjEPeccXbp04YorruCNN96gWDGVnMIWzpa8iIjEtbVr11KrVi3Gjh1LrVq1go5TZIXza1XT6pl/IiISVxYsWECLFi2YP3++CnzAwtmSn9Y98/aoHsHlEBGRI8ycOZNu3boxZMgQ/RZ8HAhnkRcRkbj0ySef8OGHH9K+ffugowgx7q43s8vNbLmZrTSzx7KZXs/MZpjZ92a2yMw6xzKPiIjExvvvv8/ixYv5+9//rgIfR2JW5M2sOPAm0AloAvQ0s6wXKO4PjHHONQd6AINilUdERGLj1Vdf5fHHH9evyMWhWD4j5wMrnXO/AJjZB8DVwLKIeRxw+LqGJwDrYphHREQK2Isvvsi7777L7NmzqV+/ftBxJItYdtfXBtZEDKf44yINAP5oZinA50C2Pw5vZneY2Xdm9l0sgoqIyLFJT08nPT2dDh06MGfOHBX4OBV030pPYJhzbqCZtQRGmNlZzrn0yJmcc+8A7wBYLXM8ND1zYotCTCsiIqSmptKrVy/OP/987r///qDjSC5iWeTXAnUjhuv44yLdClwO4Jyba2ZJQDUg94vSj4jo8VeRFxEpNHv37qVbt26YGXfccUfQcSQPseyunw+cZmYnm1kpvAPrxmWZZzVwCYCZnQEkAZtimElERI7DoEGDqFy5Mh9//DFlypQJOo7kIWYteefcITPrA0wGigPvOeeWmtlTwHfOuXHAw8AQM3sQ7yC8Xs45F6tMIiKSPxs2bOD333/nwQcfxMx0HfqQiOk+eefc53gH1EWO+9+I28uAVse84IHJxxtNRESi9Ouvv9KxY0fuuOMOmjVrFnQcOQZBH3iXPzedlXl7VHAxREQS3bJly7j88svp27cv9913X9Bx5BiFs8iLiEihOHDgAM8//zzXX3990FEkH1TkRUTkKNOmTWPixIn87W9/o3nz5kHHkXzSkRMiIu1aZPwAACAASURBVHKEsWPH0rNnT7p06RJ0FDlOasmLiEiGuXPncvfddzNp0iTOPffcoOPIcVKRFxERAH7//XcuuOAC5s+fT506dYKOIwUgnEW++huZt18NLoaISCJwztG/f39mzJjBV199pQKfQMJZ5EVEpECkpaXRp08fvv32WyZNmoSZBR1JCpCKvIhIEbZmzRo2btzIjBkzqFixYt53kFCxsF1F1mqZc3+LGFGqMnTdGlgeEZEw2rt3L4MHD+bBBx/UJWrjnJktcM7l6+fYwtmSvz5cX0xEROLJtm3buPLKKznllFNIT09XkU9gemZFRIqQHTt2kJyczHnnncewYcMoUSKcbT2JTji769eFK7OISDxIS0ujWLFifPbZZ1x55ZU6yC4kjqe7Xi15EZEiYOnSpTRr1oxt27bRpUsXFfgiQkVeRCTBffPNN1xyySU88cQTVKlSJeg4Uoi0M0ZEJIGlpqZy6623MnToUK644oqg40ghC2eRH74k83bkb8uLiEiGr776igsuuIAFCxZQunTpoONIAMLZXf/wzMw/ERE5ytChQ7nuuutYvXq1CnwRFs6WvIiI5Oill15i0KBBfPnllzRs2DDoOBIgFXkRkQTinCMtLY3Zs2frh2YkpEX+xiZBJxARiStpaWk89NBD3HzzzTz22GNBx5E4Ec4i//LFQScQEYkbBw8e5I9//CNbtmzhtNNOCzqOxJFwFnkREclwxx13kJqayoQJE0hKSgo6jsQRXdZWRCSktm/fTrly5Vi3bh21a9fWdegTlC5rKyJSxKxfv542bdrw0UcfUb9+fRV4yZaKvIhIyKxatYrWrVvTs2dPevbsGXQciWPqrhcRCZlnn32WypUrc9dddwUdRQrB8XTXh7PIn/FB5ohp3YMLIyJSiObOnUtqaipt27YNOooUoqK3T37Rpsw/EZEiYMqUKVx99dXs3bs36CgSIjpSQ0Qkzn366afccccdjB07llatWgUdR0JERV5EJI6lp6dzxhlnMGXKFJo1axZ0HAmZcBb5L7oFnUBEJOZeeOEF1q5dy2uvvRZ0FAmpcBb5ZjWCTiAiEjPOOR599FEmTJjAlClTgo4jIRbOIi8iksDGjRvHl19+yaxZs6hatWrQcSTEwnkKnc6TF5EEdODAAZYuXUrz5s05cOCArkMvQFE8hU5EJMHs3r2bK6+8ktdeew0zU4GXAqEiLyISsK1bt9KhQwfq16/P0KFDg44jCSSc++R/2Jh5WwfhiUjI7dixgyuvvJJ+/fphZkHHkQQSzn3yqa9njtjUJ7gwIiLHYeXKlQwcOJA333yTYsXUsSrZ0z55EZGQ+eGHH2jXrh3NmzdXgZeYCWd3vYhIiKWkpNCxY0feeOMNrrvuuqDjSAILZ5FvWj3oBCIi+bJ161Zq167NrFmzaNSoUdBxJMGFc5+8zpMXkRD64IMPeOyxx/jxxx8pU6ZM0HEkJLRPXkQkzr311lv07duX8ePHq8BLoQlnd72ISIjs3r2bMWPGMGvWLBo2bBh0HClC1JIXEYkR5xxvv/02JUuWZPr06SrwUuhU5EVEYuDQoUPceuutDBs2jH379gUdR4ooddeLiBSwtLQ0unXrxp49e/jiiy8oV65c0JGkiApnkX9oeubtly8OLoeISBbOOYoXL06PHj24+uqrKV26dNCRpAgLZ3f9iGWZfyIicWLz5s20bduWpUuX0q1bNxV4CVw4i7yISJxJSUmhbdu2tG7dmiZNmgQdRwQIa3e9iEic6dWrF7169eLPf/5z0FFEMoSzyA9MDjqBiAgAy5Yt4+STT+bTTz/VAXYSd8LZXX/TWZl/IiIBmT17NsnJycyfP18FXuJSOIu8iEjAJkyYwLXXXsuoUaNo27Zt0HFEshXO7noRkYCtXLmScePGceGFFwYdRSRHKvIiIsdg8ODBNGjQgPvvvz/oKCJ5Une9iEgUnHP89a9/ZeDAgTRu3DjoOCJRUUteRCQKL730Ev/617+YM2cOJ554YtBxRKJizrmgMxwTq2XOpb6eOWJTn+DCiEjCO3ToEAcOHGDbtm2UK1eOypUrBx1JihgzW+Cca5Gf+6q7XkQkB/v37+faa6/lxRdfpE6dOirwEjoq8iIi2di5cyedOnWiTJky9OvXL+g4IvmiIi8iko1x48bRuHFj3n//fUqVKhV0HJF8Cec++XXhyiwi4bFmzRqWLFlCp06dcM5hZkFHkiJO++RFRArA8uXLad26NStWrABQgZfQi/oUOjMr65zbG8swIiJBWbRoEZdffjnPPPMMt9xyS9BxRApEni15M7vIzJYBP/nDzcxsUMyTiYgUEucc1atXZ8iQISrwklCi6a5/BbgM2ALgnPsB0K8xiEhCGD9+PNdddx0nnXQSV1xxRdBxRApUVN31zrk1WfZNpcUmjohI4RkxYgSPPPII48aNCzqKSExEU+TXmNlFgDOzksD9wI+xjZWH4Usyb+s35UUkH5YsWUK/fv2YPn06TZo0CTqOSEzkeQqdmVUDXgU6AAZMAe5zzm2Nfbxs8uiytiJyHJxzLFmyhLPPPpudO3dSsWLFoCOJ5Op4TqGLpiXfyDl3Q5YVtgK+ys8KRUSCkp6ezgMPPMDcuXOZN2+eCrwkvGgOvHs9ynEiInErNTWVm2++me+//56pU6dSvHjxoCOJxFyOLXkzawlcBFQ3s4ciJlUEgn133Kj9ZyJybHbt2sUJJ5zA5MmTKVu2bNBxRApFbi35UkB5vC8CFSL+dgJdo1m4mV1uZsvNbKWZPZbDPN3MbJmZLTWzUVGlfvnizD8RkVzs2LGD+++/n6SkJN544w0VeClScmzJO+e+BL40s2HOud+OdcFmVhx4E7gUSAHmm9k459yyiHlOAx4HWjnntplZjWPeAhGRHGzcuJHLL7+cVq1akZSUFHQckUIXzYF3e83sJeBMIONd4pzLqxl9PrDSOfcLgJl9AFwNLIuY53bgTefcNn+ZG48hu4hIjvbt20fbtm3p3r07AwYM0HXopUiKpsi/D3wIXAncCdwMbIrifrWBNRHDKcAFWeY5HcDMvsLbzz/AOTcp64LM7A7gDgBOimLNIlKk7d69m/LlyzN69GiaN28edByRwERzdH1V59xQINU596VzrjdQUDvDSwCnAclAT2CImVXKOpNz7h3nXIv8nicoIkXHd999R+PGjUlJSVGBlyIvmiKf6v9fb2ZXmFlzoEoU91sL1I0YruOPi5QCjHPOpTrn/guswCv6IiLHbMaMGXTu3JlBgwZRp06doOOIBC6a7vqnzewE4GG88+MrAg9Ecb/5wGlmdjJece8BXJ9lnk/wWvD/8K+sdzrwS55LvuTDzNvTukcRRUQSXXp6Os888wxjxowhOTk56DgicSHPIu+c+8y/uQNoDxlXvMvrfofMrA8wGW9/+3vOuaVm9hTwnXNunD+to/9TtmnAI865LXmmXhTNIQEiUlR88skntG/fnqlTp+oAO5EIOV673j8FrhveAXSTnHNLzOxK4AmgjHMukJ1duna9iET6+9//ziuvvMK0adM49dRTg44jUuBide36oXj71L8FXjOzdUAL4DHn3Cf5WZmISEEaMGAAH3zwAbNnz6ZevXpBxxGJO7kV+RZAU+dcupklAb8Dp0TVnR5rX3QLOoGIxIEmTZowa9YsatTQdbREspNbkT/onEsHcM7tN7Nf4qLAAzTTG1qkqEpNTeWWW27hj3/8I9266Qu/SG5yK/KNzWyRf9uAU/xhA5xzrmnM04mIRNi7dy/XXXcdxYoVo127dkHHEYl7uRX5MwothYhIFPr27UuVKlV47733KFmyZNBxROJejkfXxyurZc6tC1dmETk+GzZsoGTJkhQvXpwKFSpQrFg01/ESSQzHc3S93ikiEtd+/fVX2rRpwyeffMIJJ5ygAi9yDKK54l38+SHix+p0EJ5Iwlq2bBmXXXYZjzzyCL179w46jkjoRNVdb2ZlgHrOueWxj5RHFl0MR6TIGDlyJM45brzxxqCjiAQmVhfDObzwLsDfgFLAyWZ2DvCUc+6q/KxQRCQv06ZNY926dSruIscpmp1bA4Dzge0AzrmFwMkxzCQiRdjYsWPp2bOnrmAnUgCi2Sef6pzbkeVHH4I9vL1p9UBXLyKxMW7cOO6++24mTZrEueeeG3QckdDLc5+8mQ0FpgGPAdcC9wElnXN3xj5eNnl0Cp1IQtq3bx/79u1j8+bNnH766UHHEYkbsT6F7l7gTOAAMArvJ2ej+T15EZE8Oefo378/vXv3pkqVKirwIgUomu76xs65fkC/WIcRkaIlLS2NPn36MH/+fCZOnBh0HJGEE01LfqCZ/WhmfzWzs2KeSESKjK+//poVK1Ywffp0qlfXsTYiBS3PIu+caw+0BzYBb5vZYjPrH/NkuXloeqCrF5Hjs3fvXsaPH0+bNm2YOnUqFStWDDqSSEKK6vqQzrnfnXOvAXcCC4H/jWmqvIxYFujqRST/tm3bxqWXXsrYsWNxzukytSIxlOe7y8zOMLMBZrYYeB34GqgT82QiknA2bNhAcnIy559/Pu+++y5ZTs0VkQIWzYF37wEfApc559bFOI+IJLAyZcrQp08fbrvtNhV4kUIQzT75ls65v8dVgR+YHHQCETkGS5YsoVOnTpQpU4bbb79dBV6kkOTYkjezMc65bn43feTVZwxwzrmmMU+Xk5t0kL9IWMybN49rrrmGV155hZIlSwYdR6RIyfGKd2Z2knNuvZnVz266c+63mCbLga54JxIeW7du5cwzz2To0KF07tw56DgioRSTK94559b7N+92zv0W+QfcnZ+ViUjRsXLlSqpUqcLixYtV4EUCEs25K5dmM65TQQcRkcTx7rvv0q5dO7Zv3061atWCjiNSZOW2T/4uvBZ7QzNbFDGpAvBVrIOJSDi9+OKLDB48mJkzZ1KpUqWg44gUabmdQjcKmAg8h/cLdIftcs5tjWkqEQmlgwcPsmzZMubMmUPt2rWDjiNS5OXWXe+cc78C9wC7Iv4wsyqxj5aL6m8EunoROVJaWhoDBgxgx44dDBs2TAVeJE7kVuRH+f8XAN/5/xdEDIuIcODAAXr27Mns2bNJSkoKOo6IRMixu945d6X//+TCiyMiYeKc49prr6VUqVJMmDBBRV4kzkRz7fpWZlbOv/1HM3vZzOrFPpqIxLMDBw5gZvTr148xY8aowIvEoWhOoRsM7DWzZsDDwCpgRExT5WVTn0BXL1LUrVu3jhYtWvD111/TsmVLSpSI5mcwRKSwRVPkDznvsnhXA284597EO41ORIqgVatW0aZNG66//npatmwZdBwRyUU0X793mdnjwI1AGzMrBugC1CJFVP/+/XnkkUe48847g44iInnI8dr1GTOYnQhcD8x3zs3298cnO+eGF0bAo/Lo2vUigfjmm2+oW7cuNWvWpHjx4kHHESkyYnLt+sOcc78D7wMnmNmVwP6gCryIBGPy5Ml06dKFFStWqMCLhEg0R9d3A74FrgO6Ad+YWddYBxOR+DBmzBhuuukmxo4dS3JyctBxROQYRLNPvh9wnnNuI4CZVQe+AP4Vy2C5Gr5EvykvUkiSkpKYOnUqTZs2DTqKiByjaIp8scMF3reF6I7Kj52HZ6rIi8SQc44XXniBqlWrcvvttwcdR0TyKZoiP8nMJgOj/eHuwOexiyQiQXLO8eijj/L5558zZcqUoOOIyHHIs8g75x4xs/8HtPZHveOcGxvbWCISlNdff53Zs2cza9YsqlQJ9reoROT45HgKnZmdBvwNOAVYDPR1zq0txGzZslrmXI9p8PLFQUcRSSgHDhxg69atVKjgXeuqfPnyAScSEYjdKXTvAZ8B1+L98tzr+VlBTKjAixSoXbt2ccUVVzBw4EDKly+vAi+SIHLrrq/gnBvi315uZv8pjEAiUri2bNlC586dOfvss3nhhReCjiMiBSi3Ip9kZs0B84fLRA4751T0RRLAwoULufjii3n22Wcxs7zvICKhkds++Rm53M855wLpM9dlbUUKxs8//8zUqVO5++67g44iIrk4nn3yObbknXPt8x9JROLZwoUL6dy5M08++WTQUUQkhvQj0CJFzA8//EDHjh158803ue6664KOIyIxlOev0MUbq2XOnfEBTOsedBSR0ElNTeXQoUN8//33XHTRRUHHEZEoxPRX6OLSok1BJxAJndGjR9OuXTuSkpJU4EWKiDy768073PYGoKFz7in/9+RPdM59G/N0IlIgBg8ezDPPPMPEiRN1BL1IERJNS34Q0BLo6Q/vAt6MWSIRKVC//fYbr7/+OrNmzeLss88OOo6IFKJoivwFzrl7gP0AzrltQKmYpsrLF90CXb1IGDjnmDRpEvXr12fRokU0bNgw6EgiUsiiObo+1cyKAw4yfk8+Paap8tKsRqCrF4l3hw4d4vbbb2f58uW0b9+e0qVLBx1JRAIQTZF/DRgL1DCzZ4CuQP+YphKRfNu/fz89e/Zk7969TJ06VQVepAiL5qdm3zezBcAleJe0vcY592PMk4lIvpgZF1xwAQ899BClSgW7Z01EgpXnPnn/aPq9wHhgHLDHHycicWTz5s1ce+217Nq1i8cee0wFXkSi6q6fgLc/3oAk4GRgOXBmDHOJyDFISUmhY8eOXHPNNVStWjXoOCISJ6Lprj/inBszOxcI9hctftiog+9EfIcOHaJjx47ccsstPPLII0HHEZE4kq/L2prZ4qzFv7BYLXMu9XXY1CeI1YvElZSUFGrXrs26deuoXbt20HFEJAZi8it0EQt/KGKwGHAusC4/KxORgjNr1iy6du3K7NmzadSoUdBxRCQORXMxnAoRf6Xx9tFfHctQIpK7CRMm0LVrV0aNGqUCLyI5yrUl718Ep4Jzrm8h5YlO0+pBJxAJ1NixYxk/fjwXXHBB0FFEJI7luE/ezEo45w6Z2VznXMtCzpUjq2XOrQvXz+OKFJR3332Xiy++WJeoFSlCYrVP/lu8/e8LzWwc8BGw5/BE59zH+VmhiBw75xx//etfGT58OJdccknQcUQkJKI5Tz4J2AJcTOb58g5QkRcpJE888QQTJ05kzpw5nHjiiUHHEZGQyK27PgV4mcyiHvkj1M4593Ls42WTS931UoQcOnSI4sWLM2/ePM444wwqVaoUdCQRKWSx6q4vDpTnyOJ+mKqsSIzt27eP7t2707VrV2666aag44hICOVW5Nc7554qtCQikmHnzp1cddVVnHTSSfTo0SPoOCISUrmdJ59dCz4+PDQ96AQiMfXCCy/QpEkTRo4cqR+aEZF8y22ffBXn3NZCzpMnXdZWEtnq1avZv38/J598MiVKlMAsfr9ri0jhOJ598jm25OOxwIsksuXLl9OmTRtmzZpFyZIlVeBF5LhFc1lbEYmx//znPyQnJ/Pkk09y2223BR1HRBJETIu8mV1uZsvNbKWZPZbLfNeamTOz6LojBiYXVESRuLBnzx4GDRpEr169go4iIgkkmovh5It/3fs3gUuBFGC+mY1zzi3LMl8F4H7gm6gXftNZBZhUJDjjx4/n+++/53//93+DjiIiCSiWLfnzgZXOuV+ccweBD8j+1+v+CrwA7I9hFpG4M2LECG6//XY6deoUdBQRSVCxLPK1gTURwyn+uAxmdi5Q1zk3IYY5ROLOpEmT6NevHzNmzOC8884LOo6IJKiYddfnxcyK4V02t1cU894B3AHASTGNJRJTzjk2btzIJZdcwty5c6ldu3bedxIRyadYtuTXAnUjhuv44w6rAJwFzDSzX4ELgXHZHXznnHvHOdciv+cJisSD9PR07r//fm699VZKliypAi8iMRfLlvx84DQzOxmvuPcArj880Tm3A6h2eNjMZgJ9nXPfxTCTSCBSU1Pp3bs3v/32G+PHjw86jogUETFryTvnDgF9gMnAj8AY59xSM3vKzK46roVXf6MAEooUnhUrVpCamsrkyZM54YQTgo4jIkVEjpe1jVe6rK2EyY4dO/jnP//JvffeqyvYiUi+xOSytiJyfDZu3EhycjIrVqwgbF+mRSQxqMiLxMCGDRto06YNV111Fa+//jrFiumtJiKFL5zd9evClVmKlrS0NJxzTJw4kS5dugQdR0RCTt31InFi/vz5nHvuuRw8eFAFXkQCF9jFcEQSzfTp0+nevTtDhw6lbNmyQccREVGRFykIe/bs4U9/+hMfffQRycnJQccREQFU5EWO25w5c2jVqhVLliyhdOnSQccREcmgffIix+GVV17hhhtuYMOGDSrwIhJ3wlnkhy8JOoEUcc45+vfvz1tvvcXs2bM58cQTg44kInKUcBb5h2cGnUCKOOccJUqUYPbs2dSrVy/oOCIi2QpnkRcJSGpqKnfddRcrV65kwIAB1KhRI+hIIiI50oF3IlHau3cvXbt2pUSJEtStWzfvO4iIBCycLfkbmwSdQIqgnj17Uq1aNf79739TpkyZoOOIiORJl7UVycPWrVupVKkSv/76Kw0aNNB16EWkUOmytiIx8uuvv3LBBRcwefJkGjZsqAIvIqGiTyyRHCxbtow2bdpw//3306lTp6DjiIgcMx14J5KDYcOG8fzzz3PDDTcEHUVEJF+0T14ki2nTplGlShWaN28edBQREe2TFykoH3/8MT179mT37t1BRxEROW7hLPKXfBh0AklAI0eOpE+fPkyePJk2bdoEHUdE5LiFc5/8ok1BJ5AEk56ezplnnsnMmTM5/fTTg44jIlIgwlnkRQqIc45+/fpRsmRJnnzyyaDjiIgUKBV5KbLS0tK45557WLBgARMnTgw6johIgQtnkf+iW9AJJAEMHz6cn3/+menTp1OhQoWg44iIFDidQidFzp49e/jll18488wzSU1NpXTp0kFHEhHJkU6hE4nStm3buPTSS3n33XcpVqyYCryIJDQVeSky1q9fT7t27bjwwgt55ZVXgo4jIhJz4dwnL5IPW7du5aabbuLhhx/GzIKOIyIScyrykvAWL17MsGHDGDhwIGeeeWbQcURECk04u+t/2Bh0AgmJefPm0aFDB1q0yNcxKyIioRbOIt9hTNAJJAR++uknrrrqKv7xj3/Qs2fPoOOIiBQ6dddLQtq2bRuNGjVi9uzZNGrUKOg4IiKBCGdLXiQXQ4YMoVWrVqSlpanAi0iRFs6WfNPqQSeQOPXCCy/w9ttvM2XKFEqUCOfLW0SkoITzU3Ba96ATSBzatGkTkyZNYvbs2dSuXTvoOCIigVN3vYReWloa77zzDlWqVGHGjBkq8CIiPhV5CbUDBw7Qs2dPxowZw/79+4OOIyISV1TkJbQOHDhAly5dSEtLY8KECZQrVy7oSCIicSWc++SlyHPOUapUKW6++Wa6d++ug+xERLKhlryEzrp162jZsiWrV6/mhhtuUIEXEclBOIv8Q9ODTiABWbVqFa1bt+aaa66hXr16QccREYlr4SzyI5YFnUAC4JyjR48ePProozz22GP6JTkRkTyon1NCYfHixTRu3JgZM2ZQvnz5oOOIiIRCOFvyUqRMmjSJiy++mCVLlqjAi4gcg3AW+YHJQSeQQvLhhx9y880388knn9C8efOg44iIhEo4u+tvOivoBFJIVq5cydSpU2natGnQUUREQsecc0FnOCZWy5xbF67Mcmycc7z00ku0bt2aiy66KOg4IiKBMrMFzrkW+blvOLvrJWE553jkkUcYPnw4DRo0CDqOiEiohbO7XhLWE088wVdffcWsWbOoUqVK0HFEREJN3fUSFw4cOADA2rVrqVGjho6iFxHxqbteQm3Xrl1cccUVDB48mIYNG6rAi4gUkHAW+epvBJ1ACsiWLVvo0KEDJ598Mvfee2/QcUREEko4i7wkjPfff5/27dvzzjvvULx48aDjiIgkFB14J4H4+eefWbt2Lffee6+uQS8iEiNqyUuhW7hwIe3ateOXX35RgRcRiaFwtuQ39Qk6geTT3Llzufrqqxk0aBBdu3YNOo6ISEILZ5GXUHLOUbNmTUaNGkWHDh2CjiMikvBU5KVQjB49mi+++IKhQ4fSsGHDoOOIiBQJKvISc4MGDeLZZ59l0qRJQUcRESlSVOQlpr766isGDhzIrFmz1IIXESlkKvISE+np6SxbtoyLLrqI77//nooVKwYdSUSkyAnnKXTDlwSdQHJx6NAhevfuzQMPPACgAi8iEpBwFvmHZwadQHKwf/9+unbtyoYNG/j00091HryISIDCWeQlbm3ZsoX69evz6aefUq5cuaDjiIgUaSryUiA2bdrEgw8+SI0aNXj11VcpVapU0JFERIq8cBb5G5sEnUAirFmzhrZt21K2bFlKlNCxnCIi8cKcc0FnOCZWy5xbF67MiWz79u2cc8453HvvvTz88MNBxxERSThmtsA51yI/91WzS/Jtz549VKpUiY8//phzzz036DgiIpJFOLvrJXCzZs2icePGbN26VQVeRCROqcjLMfvss8+49tpr+cc//kGVKlWCjiMiIjlQd70ck9TUVJ577jkmTJjA+eefH3QcERHJhVryErV//etfHDp0iDlz5qjAi4iEQDiL/CUfBp2gSHHO8eSTT/L444+zZcsWXcVORCQkwtldv2hT0AmKDOccDzzwAF9++SVz5syhZs2aQUcSEZEoxbQlb2aXm9lyM1tpZo9lM/0hM1tmZovMbJqZ1Y9lHjl2ZsYf/vAHZs6cqQIvIhIyMSvyZlYceBPoBDQBeppZ1kvVfQ+0cM41Bf4FvBirPHJs9u3bR9euXZk7dy433XQTlSpVCjqSiIgco1i25M8HVjrnfnHOHQQ+AK6OnME5N8M5t9cfnAfUiWrJX3QryJySxc6dO+nUqROlSpWiRYt8XWRJRETiQCyLfG1gTcRwij8uJ7cCE6NacrMa+U8lefrTn/5EkyZNGDlyJCVLlgw6joiI5FNcHHhnZn8EWgDtcph+B3AHACcVXq6iJiUlhcqVKzNoa9Cw8QAAIABJREFU0CAqVaqko+hFREIuli35tUDdiOE6/rgjmFkHoB9wlXPuQHYLcs6945xrkd8L9EvefvrpJ1q1asWkSZOoXLmyCryISAKIZZGfD5xmZiebWSmgBzAucgYzaw68jVfgN8Ywi+RiwYIFtG/fnqeeeoprr7026DgiIlJAYtZd75w7ZGZ9gMlAceA959xSM3sK+M45Nw54CSgPfOS3HFc7566KVSbJ3rx58xg8eDDXXHNN0FFERKQAhfP35Cdu0MF3BWDcuHGkpaXxP//zP0FHERGRHBzP78mH87K2HcYEnSD0hg8fzh133EHdunXznllEREIpLo6ul8I1YsQI+vfvz4wZMzjjjDOCjiMiIjGiIl+EOOfYv38/HTp0oG3bttSvr6sIi4gksnAW+abVg04QOunp6dx3332kp6czaNCgoOOIiEghCGeRn9Y96AShkpqaSq9evVizZg3jx48POo6IiBSScBZ5OSaTJ09m586dTJ48mTJlygQdR0RECkk4T6FbF67MQdmxYwfz5s3jsssuIz09nWLFwnkyhYhIUVb0TqGTPG3YsIHk5GQmTZoEoAIvIlIE6ZM/Aa1evZo2bdpw9dVX8/LLLwcdR0REAqJ98gkoKSmJJ554gl69egUdRUREAhTOffI9psHLFwcdJe7Mnz+f5557jn//+9/6FTkBvDMrUlJS2L9/f9BRRCQPSUlJ1KlTh5IlSx4x/nj2yYezJT9imYp8FtOnT6d79+4MHTpUBV4ypKSkUKFCBRo0aKDXhUgcc86xZcsWUlJSOPnkkwtsudonnwBSUlLo2bMnH330EVddpR/xk0z79++natWqKvAicc7MqFq1aoH3uoWzJS8ZfvnlFxo2bMiSJUuoXl1XApSjqcCLhEMs3qvhbMkPTA46QVx4+eWXufTSS9m/f78KvITauHHjeP7554OOEbhhw4ZRvXp1zjnnHBo3bswrr7xyxPR33nmHxo0b07hxY84//3zmzJmTMS01NZXHHnuM0047jXPPPZeWLVsyceLEwt6EPD3wwAPMmjUr6Bg56tevH3Xr1qV8+fK5zvfcc89x6qmn0qhRIyZPnpwxftKkSTRq1IhTTz31iNd0jx49+Pnnn2OWO0fOuVD9cRKuqEtPT3f9+vVzjRo1cqtXrw46jsSxZcuWBR2hwKWnp7v/396dx0VZ9f8ff51wwRW3MlNzQ0XZEURzIcDtm4a7aN2paVq5dafh1uatbS7lV9O+pbdmpgapPzUrLSnNtUQNTMzExCVERUwQFGX5/P6Y4YqRVQQG8Dwfj3nIwJnr+swZ5My5rmvOOz093Wr7T01NLbZtf/rppzJ+/HgREbly5YrUrVvX+D++detW8fDwkLi4OBEROXz4sDRu3FhiY2NFRGTatGkyfPhwSUlJERGRixcvSkhISJHWl5aWdk+Pv3Llinh7e9/VY4qzv3Ny4MABuXDhglSrVi3XNpGRkeLi4iIpKSly+vRpad68uaSlpUlaWpo0b95c/vzzT7l165a4uLhIZGSkiIjs2rVLnnvuuXz3n9P/WeCQFHLMLJsz+ftccnIyZ8+eZc+ePToPXrs7Dy6xvOVm9THLdpN/LNTuzpw5g4ODAyNHjqRVq1Y8/fTThIaG0qlTJ1q2bMnBgwcB0wx2woQJgGkhp/79++Pq6oqrqyv79+/nzJkztG7dmuHDh+Pk5MT58+cJCgrCyckJZ2dnQkJCctz/wYMH6dixI+7u7jz22GP88ccfAHTo0IHIyEij3eOPP86hQ4dITk5m1KhRtG/fHnd3d7Zs2WLUFxAQgJ+fH/7+/iQlJeHv74+HhwfOzs5GO4A5c+bQunVrOnfuzLBhw1iwYAEAf/75J7169aJdu3Z06dKFEydO5Nl3devWxd7entjYWADmzp3L/PnzqVevHgAeHh6MGDGCpUuXcuPGDZYvX86HH35I5cqVAahfvz5DhgzJtt2wsDAee+wxXF1dad++PdevX7fof4A+ffqwa9cuAKpXr86UKVNwdXXl3XffZfDgwUa7Xbt20adPHwC+//57OnbsiIeHB4MHDyYpKSnbvjdu3EivXr2M+7Nnz8bLywsnJyfGjh1rmsiZX49///vfeHp6smjRIg4fPoyPjw/t2rWjZ8+eRp8sX74cLy8vXF1dGThwIDdu3MizTwuiQ4cONGjQIM82W7ZsYejQoVSuXJlmzZphb2/PwYMHOXjwIPb29jRv3pxKlSoxdOhQ43ejS5cuhIaGkpaWds813g09yJcht2/f5o033iAjI4PPP/9cH6LXyoRTp04xZcoUTpw4wYkTJ1i3bh179+5lwYIFvPPOO9naT5o0CR8fHyIiIjhy5AiOjo4AREVFMW7cOCIjIzl06BDh4eFEREQQGhpKUFCQ8Yc/KwcHB/bs2cOvv/7K7NmzmTlzJgCBgYF8+eWXAMTGxhIbG4unpydvv/02fn5+HDx4kJ07dxIUFERycjIAR44cYcOGDfz000/Y2tqyadMmjhw5ws6dO5kyZQoiQlhYGBs3biQiIoJt27Zx6NAho5axY8fy4YcfcvjwYRYsWMC4cePy7Ldz586RkpKCi4sLAJGRkbRr186ijaenJ5GRkZw6dYpHH32UmjVr5rnN27dvExgYyKJFi4y+yy/PIjk5GW9vbyIiIpg+fTq//PKL0SchISEMHTqUK1eu8NZbbxEaGsqRI0fw9PTMcSGuffv2WTyHCRMmEBYWxrFjx7h58yZff/21Ra2HDh1i0qRJTJw4kQ0bNnD48GFGjRrFq6++CsCAAQMICwsjIiKCNm3asGLFimz73LlzJ25ubtlujz32WJ7POy8xMTEWE6xGjRoRExOT6/fBtOqovb09ERERhd5vYegL78qIGzduMGjQICpWrJjtM5SaVpo1a9YMZ2dnABwdHfH390cphbOzM2fOnMnW/scff2T16tUA2NjYYGdnx99//02TJk3o0KEDAHv37mXYsGHY2NhQv359fHx8CAsLy/bpkoSEBEaMGEFUVBRKKVJTUwEYMmQIPXr04D//+Q9ffvklgwYNAkyz0a+++sqYfaekpHDu3DkAunfvTp06dQDTac6ZM2eye/duHnjgAWJiYrh06RL79u2jb9++2NraYmtry5NPPglAUlIS+/fvt5gF37p1K8f+CgkJYffu3Zw4cYIlS5Zga2t7952eiz/++IMGDRrg5eUFkO+bAjC9BgMHDgSgQoUK9OrVi61btzJo0CC++eYb5s2bx08//cTx48fp1KkTYBqgO3bsmG1bsbGxFpOTnTt3Mm/ePG7cuMHVq1dxdHQ0+iwwMNCo+dixY3Tv3h2A9PR0Y6Z97NgxXnvtNa5du0ZSUhI9e/bMtk9fX1/Cw8ML3EfF6aGHHuLChQvZ3qwVJz3IlwHp6en06tWLZs2asWLFCipU0C+bVnZkHj4G02wm8/4DDzxwV4cuq1Wrlm+bpUuXsnz5cgC+/fZbXn/9dXx9fdm0aRNnzpzh8ccfB6Bhw4bUrVuXo0ePEhISwscffwyYBu+NGzfSunVri+3+8ssvFvtfu3YtcXFxHD58mIoVK9K0adM8P/qUkZFBrVq1CjTYBAYGsmTJEg4dOkSPHj0ICAjg4Ycfpm3bthw+fBg/v3/WCDl8+DCOjo7Y29tz7tw5EhMTCzRw36lChQpkZGQY97M+F1tbW2xsbIz7Q4cOZcmSJdSpUwdPT09q1KiBiNC9e3e++OKLPPdTpUoVY9spKSmMGzeOQ4cO0bhxY2bNmmWx38z+FhEcHR05cOBAtu2NHDmSzZs34+rqyqpVq4xTDFnt3LmTl19+Odv3q1atyv79+/OsNzcNGzbk/Pnzxv2//vqLhg0bAuT6fTA955JOAtWH60u5W7duYWNjwzvvvMOnn36qB3jt3sRNsLzlZriTZbsSXHzK39+f//u//wNMb3ATEhKytenSpQshISGkp6cTFxfH7t27ad++PePHjyc8PJzw8HAeeeQREhISjD+yq1atsthGYGAg8+bNIyEhwTgk3rNnTz788EPj3PCvv/6aY40JCQk89NBDVKxYkZ07d3L27FkAOnXqxNatW0lJSSEpKck4/FyzZk2aNWvG+vXrAdPAld9hW09PT5555hkWLVoEwNSpU5k2bRrx8fEAhIeHs2rVKsaNG0fVqlUZPXo0L730Erdv3wYgLi7O2F+m1q1bExsbS1hYGADXr18nLS2Npk2bEh4eTkZGBufPnzeulciJj48PR44cYfny5QwdOhQwncfet28fp06dAkyH+E+ePJntsW3atDHaZA7o9erVIykpiQ0bNuS4v9atWxMXF2cM8qmpqcb1FNevX6dBgwakpqaydu3aHB+fOZO/81bYAR4gICCA4OBgbt26RXR0NFFRUbRv3x4vLy+ioqKIjo7m9u3bBAcHWxxdOnnyJE5OToXeb2GUzUE+rwuGypHo6GhcXFyIjIykc+fOOklOuy8sWrSInTt34uzsTLt27Th+/Hi2Nv3798fFxQVXV1f8/PyYN28eDz/8cLZ2U6dOZcaMGbi7u2c7ajBo0CCCg4MtLk57/fXXSU1NxcXFBUdHR15//fUca3z66ac5dOgQzs7OrF69GgcHBwC8vLwICAjAxcWF//mf/8HZ2Rk7OzvANPtfsWIFrq6uODo6Wlysl5tp06bx6aefcv36dQICAhg1ahSPPfYYDg4OjBkzhjVr1hiHrt966y0efPBB2rZti5OTE3369Mk2q69UqRIhISFMnDgRV1dX4yO4nTp1olmzZrRt25ZJkybh4eGRa002Njb06dOHbdu2GRfdPfjgg6xatYphw4bh4uJCx44dc7ywsHfv3sZsu1atWowZMwYnJyd69uxpnEK4U6VKldiwYQPTpk3D1dUVNzc3Y4CeM2cO3t7edOrUyXgN7tXUqVNp1KgRN27coFGjRsyaNQswfczzjTfeAEynnYYMGULbtm3p1asXS5cuxcbGhgoVKrBkyRJ69uxJmzZtGDJkiHFNyaVLl6hSpUqOv6fFqWyuXZ/6Yd6zkHIgMjKSXr16MX36dMaPH2/tcrQy6vfff6dNmzbWLuO+kpSURPXq1blx4wZdu3Zl2bJleQ6a95vOnTvz9ddfU6tWLWuXUqIWLlxIzZo1GT16dJ7tcvo/e/+tXX8fmDp1KnPnzuWpp56ydimapt2FsWPHcvz4cVJSUhgxYoQe4O/w/vvvc+7cuftukK9VqxbPPPNMie9Xz+RLmT179uDo6IidnZ3FxS6aVhh6Jq9pZUtRz+TL5knecjrAb9y4kYEDB/Lnn3/qAV7TNE27Z2VzkC+HVqxYwcSJE/nuu+9yvQBF0zRN0+6GPidfSlSrVo1du3bRqlUra5eiaZqmlRN6kLciEeHVV1/F3d3d+LyppmmaphUVfbjeStLT03nhhRfYsWMHvr6+1i5H07RS5syZM1SpUgU3Nzfatm3L8OHDjWV5wbS0b/v27Y3o2WXLllk8fvXq1UaAj7u7u7FUb2myefNmZs+ebe0ycrV+/XocHR154IEHLHII7pRbvGx0dDTe3t7Y29sTGBhoLFS0ZMkSVq5cWez1Azpq1lrefPNN8fX1lcTERGuXopVj5TFq9k73Gn96L4oz9jY6OlocHR1FxPQcfX19Zc2aNSIiEhsbK40bN5bDhw+LiEhcXJx4eHjI119/LSIi3377rbi7u0tMTIyIiKSkpMiyZcuKtL6iiIDt2LGjEZ1bUvu8G8ePH5cTJ06Ij4+PhIWF5dgmr3jZwYMHyxdffCEiIs8//7x89NFHIiKSnJwsbm5uue7zTtx3UbOrj1m7gkJLTk7mypUrvPTSS3z77bfUqFHD2iVp9xGl/mNxy82yZYct2o0du7VQ+yto1GxukbDp6em88sorODk54eLiwocffghA06ZNmTZtGh4eHqxfv54vvvgCZ2dnnJycmDZtWo615BYPO336dJYuXWq0mzVrljHrnT9/Pl5eXri4uPDmm28az+nO2NsXX3wRT09PHB0djXZgWj/fwcGBdu3aMWnSJGOFuNwibXNjY2ND+/btjUSzpUuXMnLkSOMz+PXq1WPevHnGLPLdd99lwYIFPPLII4ApP2DMmDHZtptbrG/WpVcXLFhgrPqWNQL27bffpkmTJsaa98nJyTRu3JjU1NQCxeqePHmSypUrG9G5W7duxdvbG3d3d7p168alS5eM1+OZZ56hU6dOPPPMM8TFxTFw4EC8vLzw8vJi3759QO6/Q/eiTZs22XIM7pRbvKyI8OOPPxrhRyNGjGDz5s2Aad38pk2b5rl8cJEp7LsDa91ogEi9D3N8B1TaXb16VTp27ChvvfWWtUvR7hN3zgpglsUtN598csii3ZgxXxVq/9HR0WJjYyNHjx6V9PR08fDwkGeffVYyMjJk8+bN0rdvXxERSUhIMGZpO3bskAEDBoiIyEcffSQDBw40fhYfHy8iIk2aNJG5c+eKiEhMTIw0btxYLl++LKmpqeLr6yubNm3KVktqaqokJCSIiGnm26JFC8nIyJAjR45I165djXZt2rSRc+fOyXfffSdjxowxZuu9e/eWn376SaKjo0UpJQcOHDAek1lXWlqa+Pj4SEREhNy8eVMaNWokp0+fFhGRoUOHSu/evUVEZMaMGfL555+LiMjff/8tLVu2lKSkpGx9lzmTv3nzpjz++OMSEREhIiL9+/eXzZs3W7S/du2a1K5dW0REateuLdeuXcv39RkyZIgsXLjQqP3atWsW+xURmT9/vrz55psiIuLj4yMvvvii8bOAgAD58ccfRUQkODhYRo8eLSIifn5+cvLkSRER+fnnn8XX1zfbvleuXCmTJ0827l+9elUyMjJERGT58uXGz958803x8PCQGzduiIjIsGHDZM+ePSIicvbsWXFwcBCR3H+HskpMTBRXV9ccb5mz75zkNZNfv3698bxFRFavXi3jx483fscynTt3zqJf33rrLVmwYEG27RX1TF5feFdCYmNj6dmzJ927d2fGjBnWLkfTSkxBomZzi4QNDQ3lhRdeMIKZMqNe4Z8o0rCwMB5//HEjwvTpp59m9+7d9OvXz6IOkZzjYd3d3bl8+TIXLlwgLi6O2rVr07hxYxYtWsT333+Pu7s7YDoSEBUVxaOPPmoRewvw5ZdfsmzZMtLS0oiNjeX48eNkZGTQvHlzmjVrBsCwYcOM8+a5RdreuQjKn3/+iZubG9HR0fTu3dsI0ikqucX65iWz3zO/DgkJwdfXl+DgYMaNG1fgWN07Y2f/+usvAgMDiY2N5fbt20a/gSkQJjO9LTQ01CLPIDExkaSkpFx/h7KqUaNGqYqdzekIR1HTg3wJOXDgAIGBgcycOROllLXL0bQSU5Co2dwiYfOSX/TsL7/8wvPPPw/A7NmzuXr1aq7xsIMHD2bDhg1cvHjRGMREhBkzZhjbyHTmzBmLfUdHR7NgwQLCwsKoXbs2I0eOzDN2NnPbOUXa3qlFixaEh4dz5coVOnXqxFdffUVAQIARO9u3b1+jbWbsLJjeTN0ZS1tQecXOgmW/BwQEMHPmTK5evWrsLzk5uUCxulWqVLFIGJw4cSKTJ08mICCAXbt2GacI7txnRkYGP//8M7a2thbbmzBhQr6/Q9evX6dLly451rNu3Tratm2bZ805yS12tm7duly7do20tDQqVKhgtdjZsnlO/pm7fyGs5bfffmPVqlUMGDCAV199VQ/wmlWJvGlxy83Yse0s2i1b9mSx1pVbJGz37t355JNPjDcDV69ezfbY9u3b89NPP3HlyhXS09P54osv8PHxwdvb24gVDQgIyDUeFkwz0uDgYDZs2GDMQHv27MnKlStJSkoCICYmhsuXL2fbf2JiItWqVcPOzo5Lly6xbds2wBSRevr0aeNoRUhIiPGYgkbaZqpXrx7vvfce7777LgDjx49n1apVxkAaHx/PtGnTmDp1KgAzZswgKCiIixcvAnD79m3++9//ZttuTrG+9evX5/Lly8THx3Pr1i0jLjcn1atXx8vLi5deeok+ffpgY2NT4FjdrLGzYPk78Nlnn+W6zx49ehjXZgBGH+QVK5wpcyaf060wAzyQa7ysUgpfX18jQvezzz6zeFNWUrGzZXOQL8Fs63tx4MABunXrlu0dp6ZplnKLhH3uued49NFHjVjZdevWZXtsgwYNeO+99/D19cXV1ZV27dpZ/DHNlFs8LJhmvtevX6dhw4ZGdGuPHj146qmn6NixI87OzgwaNIjr169n266rqyvu7u44ODjw1FNP0alTJ8A0U/3oo4+MC9Bq1KhhxM4WNNI2q379+nHjxg327NlDgwYNWLNmDWPGjMHBwYHHHnuMUaNG8eSTpjdjTzzxBBMmTKBbt244Ojri4eFBYmJitm3mFOtbsWJF3njjDdq3b0/37t3zjXANDAxkzZo1FofxCxKr27VrV3799Vfjjc6sWbMYPHgw7dq1My7Gy8nixYs5dOgQLi4utG3blo8//hjIO1a4sDZt2kSjRo04cOAAvXv3pmfPngBcuHCBJ554AiDPeNm5c+fywQcfYG9vT3x8vEUC3b59++jevXuR1JmXshlQc6H017x//3769u3LZ599ZvwyaFpJ0wE11pUZOysijB8/npYtW/Lyyy9bu6xS46WXXuLJJ5+kW7du1i6lRP3666988MEHfP7559l+pgNqyoDU1FQcHR355ptv9ACvafex5cuX4+bmhqOjIwkJCdnO79/vZs6cyY0bN6xdRom7cuUKc+bMKZF96Zl8EVu+fDkbN25k+/bt1i5F0/RMXtPKmKKeyeur64vQ3Llz+fjjj9mxY4e1S9E0TdM0PcgXlWPHjrFu3Tr27t1r8TEJTdM0TbOWsnlO3j8k/zYlJD09nR07duDk5MThw4f1AK9pmqaVGmVzJn80ztoVAKZVnJ5++mkSExPx8/MzVuXSNE3TtNKgbM7kS4GkpCSefPJJRIStW7diY2Nj7ZI0TdM0zYIe5O+Bn58fISEhFst2appmycbGBjc3N5ycnHjyySe5du2a8bPIyEj8/Pxo3bo1LVu2ZM6cOWT9xM+2bdvw9PSkbdu2uLu7M2XKFGs8hUIZNmwYLi4uLFy4sEDtq1evXix1iAiTJk3C3t4eFxcXjhw5kmO7mzdv4uPjQ3p6erHUca/i4+Px9fWlevXqTJgwIdd2V69epXv37rRs2ZLu3bsba/Hn1g9xcXH06tWrRJ6DNZTNQT50iNV2feHCBQYOHAiYIir1IXpNy1uVKlUIDw/n2LFj1KlTx4h1vXnzJgEBAUyfPp0//viDiIgI9u/fz0cffQSYLmadMGECa9as4fjx4xw6dAh7e/sira2oVka708WLFwkLC+Po0aNWX/xm27ZtREVFERUVxbJly3jxxRdzbLdy5UoGDBhQ4KOSImKxxn1xs7W1Zc6cOUaoT27ee+89/P39iYqKwt/f34jfza0fHnzwQRo0aGBE1pY3ZXOQd33IKrs9deoUnTt3xsvLK99wDE3TsuvYsaORib5u3To6depEjx49AFPG9pIlS4w/yvPmzePVV181llW1sbHJcYBKSkri2WefxdnZGRcXFzZu3AhYzow3bNjAyJEjARg5ciQvvPAC3t7eTJ06laZNm1ocXWjZsiWXLl3KNbc8q5SUFGPf7u7u7Ny5EzAtiRsTE4Obmxt79uyxeExOGe53Pp+ccu+Tk5Pp3bs3rq6uODk5GWvhT58+nbZt2+Li4sIrr7ySrcYtW7YwfPhwlFJ06NCBa9euERsbm63d2rVrjeWAc6vhzJkztG7dmuHDh+Pk5MT58+eZP38+Xl5euLi48Oab/+Qh9OvXj3bt2uHo6Gik792LatWq0blz53yXCd+yZQsjRowALDPc8+qHfv36sXbt2nuusTTS09ACunnzJt26dWPmzJmMHTvW2uVoWuGsK4aApKcKtjhVeno6P/zwg7F+d2RkJO3atbNo06JFC5KSkkhMTOTYsWMFOjw/Z84c7Ozs+O233wDyjUoFU1LY/v37sbGxIT09nU2bNvHss8/yyy+/0KRJE+rXr89TTz3Fyy+/TOfOnTl37hw9e/bk999/t9jO0qVLUUrx22+/ceLECXr06MHJkyf56quv6NOnT45JbJMmTcLHx4dNmzaRnp5uBOBksrW1ZdOmTdSsWZMrV67QoUMHAgIC2L59O4888gjffPMNYApkiY+PZ9OmTZw4cQKllMWblUwxMTE0btzYuN+oUSNiYmKMNfrBFGBz+vRpmjZtmmcNAFFRUXz22Wd06NCB77//nqioKA4ePIiIEBAQwO7du+natSsrV66kTp063Lx5Ey8vLwYOHEjdunUtanv55ZeNN0ZZDR06lOnTp+f1Eubq0qVLxnN7+OGHuXTpUr794OnpyWuvvVao/ZV2epAvgAsXLvDII4+wd+9eGjVqZO1yNK3wCjggF6WbN2/i5uZGTEwMbdq0KfJQjtDQUIKDg437tWvXzvcxgwcPNg5LBwYGMnv2bJ599lmCg4ONoJXccsuzHiHYu3cvEydOBMDBwYEmTZpw8uRJatasmeu+c8pwzyq33HtnZ2emTJnCtGnT6NOnD126dCEtLQ1bW1tGjx5Nnz596NOnT77PPSdXrlyhVq1a+dYA0KRJEzp06ADA999/z/fff4+7uztgOgIQFRVF165dWbx4MZs2bQLg/PnzREVFZRvkC3q9QmEppQqU/PnQQw9x4cKFYq3FWsrm4foStH37duMPlB7gNe3uZZ6TP3v2LCJinJPPzETP6vTp01SvXp2aNWsameiFlfWPe16Z6B07duTUqVPExcWxefNmBgwYAPyTW54ZRRoTE1NsF8dltXbtWiP3Pjw8nPr165OSkkKrVq04cuQIzs7OvPbaa8yePZsKFSpw8OBBBg0axNdff53jBWS55Z1nVaVKFYs+yq0GsOw7EWHGjBlGH506dYrRo0eza9cuQkNDOXDgABEREbi7u2d7DcA0k3dzc8s+LpEcAAASdklEQVR2yzxlUxj169c3DsPHxsby0EMP5dsPJZXtbg16kM9DcHCwcU5HL3KjafematWqLF68mPfff5+0tDSefvpp9u7dS2hoKGCa8U+aNMnIRA8KCuKdd97h5MmTgGnQzYwVzap79+7GGwf453B9/fr1+f3338nIyDBmlDlRStG/f38mT55MmzZtjNlmbrnlWXXp0sU4l3vy5EnOnTtH69at8+yHnDLcs8ot9/7ChQtUrVqVf/3rXwQFBXHkyBGSkpJISEjgiSeeYOHChTnmtgcEBLB69WpEhJ9//hk7OzuLQ/VgOvqRnp5uDMS51XCnnj17snLlSuOUQ0xMDJcvXyYhIYHatWtTtWpVTpw4wc8//5zj4xcuXJhjtnthD9VnPt/MPPqsGe559UNJZbtbhYiUqRsNEAm/JMUtPT1dhg4dKhEREcW+L00rLsePH7d2CVKtWjWL+3369JHVq1eLiMjRo0fFx8dHWrVqJS1atJBZs2ZJRkaG0Xbr1q3i4eEhDg4O0qZNGwkKCsq2/evXr8vw4cPF0dFRXFxcZOPGjSIisn79emnevLl4e3vL+PHjZcSIESIiMmLECFm/fr3FNsLCwgSQVatWGd+Li4uTIUOGiLOzs7Rp00aef/75bPu+efOmjBw5UpycnMTNzU1+/PFHERGJjo4WR0fHHPvj4sWLEhAQIE5OTuLq6ir79++36Ke4uDjp0KGDODk5yciRI8XBwUGio6Nl+/bt4uzsLK6uruLp6SlhYWFy4cIF8fLyEmdnZ3FycrKoP1NGRoaMGzdOmjdvLk5OThIWFpZjXaNGjZIdO3bkWUNOz+t///d/xcnJSZycnKRDhw5y6tQpSUlJkV69eomDg4P07dtXfHx8ZOfOnTnu9240adJEateuLdWqVZOGDRtKZGSkiIiMHj3aeF5XrlwRPz8/sbe3F39/f4mPj8+3H+bPny+LFy++5/qKQk7/Z4FDUsgxs2ym0KV+CHG5f07yXogIH330EQMGDMj2blfTyhqdQqcV1JEjR1i4cGGOGeflXdeuXdmyZUuBrucobjpPvhiJCK+88kqOhwQ1TdPKMw8PD3x9fUvtYjjFJS4ujsmTJ5eKAb446Kvrsxg3bhzh4eH89NNP1KlTx9rlaJqmlahRo0ZZu4QS9+CDD9KvXz9rl1FsyuZM3uXBIt1c5jvXwMBAQkND9QCvaZqmlQtlc5D/IbDINnX9+nV69OjB1q1befzxx/VKdpqmaVq5UTYH+SISHx+Pv78/LVq04IknnrB2OZqmaZpWpO7rQf61117D39+fTz75REfFapqmaeXOfTnIR0VFcf78eRYtWsS7775boGUPNU0rHB01a92o2RMnTtCxY0cqV66cZ4KbiODn50diYmKx1FEUevXqRa1atfJcvvfWrVsEBgZib2+Pt7c3Z86cMX727rvvYm9vT+vWrfnuu+8A07r9Xbt2LbZEQmu77wb58PBwfHx8OHDgAJUqVbJ2OZpW7umoWetGzdapU4fFixfnmFCX1bfffourq2ue6+7fqaQ/bhcUFJTv5/hXrFhB7dq1OXXqFC+//DLTpk0D4Pjx4wQHBxMZGcn27dsZN24c6enpVKpUCX9/fyPVr7y5rwb5vXv3GktVDhlivUx6Tbtf6ajZko+afeihh/Dy8qJixYo5viaZskbNQu5RsdWrV2fKlCm4urpy4MAB1qxZQ/v27XFzc+P55583Bv4XX3wRT09PHB0dLSJo74W/vz81atTIs03WqNlBgwbxww8/ICJs2bKFoUOHUrlyZZo1a4a9vT0HDx40nquOmi1NJv8IH/jd9cMSEhJYu3ZtkadgaVpZof5T9Kem5E0dNVuao2YLat++fXzyySfG/dyiYpOTk/H29ub999/n999/Z+7cuezbt4+KFSsybtw41q5dy/Dhw3n77bepU6cO6enp+Pv7c/ToUVxcXCz2OX/+/BwH18wUu8LIGilboUIF7OzsiI+PJyYmxkjPg3+iZgGcnJwICwsr1P5Ku7I5yH9+/K4G+XXr1nH58mX+/e9/F2NRmlb6FXRALko6atZSaYyaBbh69arFLDm3qFgbGxsGDhwIwA8//MDhw4fx8vICTK91Zurbl19+ybJly0hLSyM2Npbjx49nG+SDgoIICgoqdM1FxcbGhkqVKnH9+vV8jxSUNeX+cP3SpUuZOnUq3bp1s3YpmnZf0lGzd6eoo2YLqkKFCmRkZADkGRVra2trvEESEUaMGGH00R9//MGsWbOIjo5mwYIF/PDDDxw9epTevXvnGDU7f/78HKNmJ02aVOjnkTVSNi0tjYSEBOrWrZtv5O6tW7ewtbUt9H5Lq3I9yIeEhLBw4UL27NlTfmMENa2M0FGzJiUdNVtQrVu35vTp00YNBYmK9ff3Z8OGDVy+fBkwHQ04e/YsiYmJVKtWDTs7Oy5dusS2bdtyfHxQUFCOUbOFPVQPllGzGzZswM/PD6UUAQEBBAcHc+vWLaKjo4mKiqJ9+/aAac2UevXq5XvdQplU2Pg6a91ogMhnv+UZ1Zeeni6XL1+W5ORkuXjxYp5tNa0801GzOmo2NjZWGjZsKDVq1BA7Oztp2LChJCQkZGs3e/ZsWb58uYhInlGxd76ewcHB4urqKs7OzuLh4SEHDhww+rlly5bi5+cn/fv3l08//TTH/rgbnTt3lnr16omtra00bNhQtm/fLiIir7/+umzZskVETK/JoEGDpEWLFuLl5SV//vmn8fi33npLmjdvLq1atZJvv/3W+P769etl8uTJ91xfUdBRs48okQu515yWlsZzzz1HWloaa9asKcHKNK300VGzWkHFxsYyfPhwduzYYe1SStyAAQN47733aNWqlbVLKfKo2bJ54V0uUlJSCAwM5Pbt22zYsMHa5WiappUZDRo0YMyYMSQmJt7VZ+XLutu3b9OvX79SMcAXh3J1Tj48PBw7Ozu2bNmig2Y0TdPu0pAhQ+6rAR6gUqVKDB8+3NplFJtyMZOPi4tj06ZNjB071uJzkJqmma670Us3a1rpVxynz8v8TP78+fN07drV+HiOpmn/sLW1JT4+Xv/f0LRSTkSIj48v8o/xlemZ/NmzZ/Hx8WHixIllKrhC00pKo0aN+Ouvv4iLi7N2KZqm5cPW1pZGjRoV6TaL9ep6pVQvYBFgA/xXRN674+eVgdVAOyAeCBSRM3lu8xElkvohGZfGkZqaSmhoKL179y6eJ6BpmqZpVnYvV9cX2+F6pZQNsBT4H6AtMEwp1faOZqOBv0XEHlgIzC3ItnennsLb25sHHnhAD/CapmmaloviPCffHjglIqdF5DYQDPS9o01f4DPz1xsAf5XfFUK3YFDiCt57773yuTqRpmmaphWR4hzkGwLns9z/y/y9HNuISBqQANTNc6sJ8HXN5/H39y+6SjVN0zStHCoTF94ppcYCY813b3knvH8M9b41Syrv6gFXrF3EfUD3c/HTfVz8dB8Xv7wDEfJQnIN8DNA4y/1G5u/l1OYvpVQFwA7TBXgWRGQZsAxAKXWosBcgaAWj+7hk6H4ufrqPi5/u4+KnlDpU2McW5+H6MKClUqqZUqoSMBT46o42XwEjzF8PAn4U/YFeTdM0TSsSxTaTF5E0pdQE4DtMH6FbKSKRSqnZmBJ1vgJWAJ8rpU4BVzG9EdA0TdM0rQgU6zl5EfkW+PaO772R5esUYPBdbnZZEZSm5U33ccnQ/Vz8dB8XP93Hxa/QfVzmomY1TdM0TSuYMr92vaZpmqZpOSu1g7xSqpdS6g+l1Cml1PQcfl5ZKRVi/vkvSqmmJV9l2VaAPp6slDqulDqqlPpBKdXEGnWWZfn1cZZ2A5VSopTSVykXQkH6WSk1xPz7HKmUWlfSNZZ1Bfh78ahSaqdS6lfz34wnrFFnWaaUWqmUuqyUOpbLz5VSarH5NTiqlPLId6MiUupumC7U+xNoDlQCIoC2d7QZB3xs/nooEGLtusvSrYB97AtUNX/9ou7jou9jc7sawG7gZ8DT2nWXtVsBf5dbAr8Ctc33H7J23WXpVsA+Xga8aP66LXDG2nWXtRvQFfAAjuXy8yeAbYACOgC/5LfN0jqTL54lcbWs8u1jEdkpIjfMd3/GtNaBVnAF+T0GmIMptyGlJIsrRwrSz2OApSLyN4CIXC7hGsu6gvSxADXNX9sBF0qwvnJBRHZj+qRZbvoCq8XkZ6CWUqpBXtssrYN88SyJq2VVkD7OajSmd5BaweXbx+bDbY1F5JuSLKycKcjvciuglVJqn1LqZ3NCplZwBenjWcC/lFJ/YfpU1cSSKe2+crd/t8vGsraadSml/gV4Aj7WrqU8UUo9AHwAjLRyKfeDCpgO2T+O6YjUbqWUs4hcs2pV5cswYJWIvK+U6ohpDRQnEcmwdmH3s9I6k7+bJXHJa0lcLVcF6WOUUt2AV4EAEblVQrWVF/n1cQ3ACdillDqD6RzbV/riu7tWkN/lv4CvRCRVRKKBk5gGfa1gCtLHo4EvAUTkAGCLaV17regU6O92VqV1kNdL4ha/fPtYKeUOfIJpgNfnMO9enn0sIgkiUk9EmopIU0zXPQSISKHXqb5PFeTvxWZMs3iUUvUwHb4/XZJFlnEF6eNzgD+AUqoNpkE+rkSrLP++Aoabr7LvACSISGxeDyiVh+tFL4lb7ArYx/OB6sB68zWN50QkwGpFlzEF7GPtHhWwn78DeiiljgPpQJCI6CN/BVTAPp4CLFdKvYzpIryReuJ1d5RSX2B6M1rPfG3Dm0BFABH5GNO1Dk8Ap4AbwLP5blO/BpqmaZpWPpXWw/Wapmmapt0jPchrmqZpWjmlB3lN0zRNK6f0IK9pmqZp5ZQe5DVN0zStnNKDvKZZgVIqXSkVnuXWNI+2SUWwv1VKqWjzvo6YVyS72238VynV1vz1zDt+tv9eazRvJ7NfjimltiqlauXT3k2nnWla7vRH6DTNCpRSSSJSvajb5rGNVcDXIrJBKdUDWCAiLvewvXuuKb/tKqU+A06KyNt5tB+JKblvQlHXomnlgZ7Ja1opoJSqrpT6wTzL/k0plS2tTinVQCm1O8tMt4v5+z2UUgfMj12vlMpv8N0N2JsfO9m8rWNKqX+bv1dNKfWNUirC/P1A8/d3KaU8lVLvAVXMdaw1/yzJ/G+wUqp3lppXKaUGKaVslFLzlVJh5hzs5wvQLQcwh28opdqbn+OvSqn9SqnW5pXXZgOB5loCzbWvVEodNLfNKfVP0+4bpXLFO027D1RRSoWbv44GBgP9RSTRvOzqz0qpr+5YMewp4DsReVspZQNUNbd9DegmIslKqWnAZEyDX26eBH5TSrXDtGKWN6Z86l+UUj9hygy/ICK9AZRSdlkfLCLTlVITRMQth22HAEOAb8yDsD/wIqZ1zRNExEspVRnYp5T63ryOfDbm5+ePaWVLgBNAF/PKa92Ad0RkoFLqDbLM5JVS72Ba4nqU+VD/QaVUqIgk59EfmlZu6UFe06zjZtZBUilVEXhHKdUVyMA0g60PXMzymDBgpbntZhEJV0r5AG0xDZoAlTDNgHMyXyn1Gqb1xEdjGkQ3ZQ6ASqn/B3QBtgPvK6XmYjrEv+cuntc2YJF5IO8F7BaRm+ZTBC5KqUHmdnaYAmLuHOQz3/w0BH4HdmRp/5lSqiWmJVMr5rL/HkCAUuoV831b4FHztjTtvqMHeU0rHZ4GHgTaiUiqMqXS2WZtICK7zW8CegOrlFIfAH8DO0RkWAH2ESQiGzLvKKX8c2okIieVKef+CeAtpdQPIpLXkYGsj01RSu0CegKBQHDm7oCJIvJdPpu4KSJuSqmqmNZJHw8sBuYAO0Wkv/kixV25PF4BA0Xkj4LUq2nlnT4nr2mlgx1w2TzA+wJN7myglGoCXBKR5cB/AQ9MyXWdlFKZ59irKaVaFXCfe4B+SqmqSqlqQH9gj1LqEeCGiKzBFFLkkcNjU81HFHISguk0QOZRATAN2C9mPkYp1cq8zxyJyA1gEjBF/RMlnRmpOTJL0+uYInszfQdMVObDGsqUpKhp9y09yGta6bAW8FRK/QYMx3QO+k6PAxFKqV8xzZIXiUgcpkHvC6XUUUyH6h0KskMROQKsAg4CvwD/FZFfAWdM57LDMaVgvZXDw5cBRzMvvLvD94APECoit83f+y9wHDiilDqGKcI4zyOJ5lqOAsOAecC75uee9XE7gbaZF95hmvFXNNcWab6vafct/RE6TdM0TSun9Exe0zRN08opPchrmqZpWjmlB3lN0zRNK6f0IK9pmqZp5ZQe5DVN0zStnNKDvKZpmqaVU3qQ1zRN07RySg/ymqZpmlZO/X/F0ENuYeHmjwAAAABJRU5ErkJggg==\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "# Pertama-tama, gabungkan semua False Positive Rates\n",
+        "all_fpr = np.unique(np.concatenate([fpr[i] for i in range(n_classes)]))\n",
+        "\n",
+        "# Kemudian interpolasi semua kurva ROC pada titik ini\n",
+        "mean_tpr = np.zeros_like(all_fpr)\n",
+        "for i in range(n_classes):\n",
+        "    mean_tpr += interp(all_fpr, fpr[i], tpr[i])\n",
+        "\n",
+        "# Terakhir, rata-rata dan hitung AUC\n",
+        "mean_tpr /= n_classes\n",
+        "\n",
+        "fpr[\"macro\"] = all_fpr\n",
+        "tpr[\"macro\"] = mean_tpr\n",
+        "roc_auc[\"macro\"] = auc(fpr[\"macro\"], tpr[\"macro\"])\n",
+        "\n",
+        "# Plot semua kurva ROC\n",
+        "plt.figure(figsize=(8, 8))\n",
+        "plt.plot(fpr[\"micro\"], tpr[\"micro\"],\n",
+        "         label='micro-average ROC curve (area = {0:0.2f})'\n",
+        "               ''.format(roc_auc[\"micro\"]),\n",
+        "         color='deeppink', linestyle=':', linewidth=4)\n",
+        "\n",
+        "plt.plot(fpr[\"macro\"], tpr[\"macro\"],\n",
+        "         label='macro-average ROC curve (area = {0:0.2f})'\n",
+        "               ''.format(roc_auc[\"macro\"]),\n",
+        "         color='navy', linestyle=':', linewidth=4)\n",
+        "\n",
+        "colors = cycle(['orange', 'green', 'blue'])\n",
+        "for i, color in zip(range(n_classes), colors):\n",
+        "    plt.plot(fpr[i], tpr[i], color=color, lw=lw,\n",
+        "             label='ROC curve of class {0} (area = {1:0.2f})'\n",
+        "             ''.format(i, roc_auc[i]))\n",
+        "\n",
+        "plt.plot([0, 1], [0, 1], 'k--', lw=lw)\n",
+        "plt.xlim([0.0, 1.0])\n",
+        "plt.ylim([0.0, 1.05])\n",
+        "plt.xlabel('False Positive Rate')\n",
+        "plt.ylabel('True Positive Rate')\n",
+        "plt.title('Some extension of Receiver operating characteristic to multi-class')\n",
+        "plt.legend(loc=\"lower right\")\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "lKkrHktRoM4f"
+      },
+      "source": [
+        "## E. GRU"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "NyU-50cMoTsb"
+      },
+      "outputs": [],
+      "source": [
+        "# Define the GRU model\n",
+        "def create_model_BiGRU():\n",
+        "    model = Sequential()\n",
+        "    model.add(Bidirectional(GRU(128, return_sequences=False, input_shape=(40, 1))))\n",
+        "    model.add(Dense(64))\n",
+        "    model.add(Dropout(0.4))\n",
+        "    model.add(Activation('relu'))\n",
+        "    model.add(Dense(32))\n",
+        "    model.add(Dropout(0.4))\n",
+        "    model.add(Activation('relu'))\n",
+        "    model.add(Dense(2))\n",
+        "    model.add(Activation('softmax'))\n",
+        "    \n",
+        "    # Configures the model for training\n",
+        "    model.compile(loss='categorical_crossentropy', optimizer='Adam', metrics=['accuracy'])\n",
+        "    return model"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "IsMVZx4pIpsh"
+      },
+      "outputs": [],
+      "source": [
+        "model_BiGRU = create_model_BiGRU()\n",
+        "model_BiGRU.build(input_shape=(None ,40, 1))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "Y62TmloKDe7D",
+        "outputId": "d52a3899-0e26-4423-fc89-c9f10d969112"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<IPython.core.display.Image object>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 32
+        }
+      ],
+      "source": [
+        "tf.keras.utils.plot_model(model_BiGRU, show_shapes=True)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "DZC76D2KopLR",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "c2b7db27-4d57-4f5a-fc0a-95667a53c12b"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Epoch 1/100\n",
+            "25/25 [==============================] - 7s 118ms/step - loss: 0.7162 - accuracy: 0.5525 - val_loss: 0.6273 - val_accuracy: 0.7350\n",
+            "Epoch 2/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.5519 - accuracy: 0.7362 - val_loss: 0.5160 - val_accuracy: 0.7700\n",
+            "Epoch 3/100\n",
+            "25/25 [==============================] - 1s 58ms/step - loss: 0.4719 - accuracy: 0.7987 - val_loss: 0.4638 - val_accuracy: 0.7900\n",
+            "Epoch 4/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.4491 - accuracy: 0.8100 - val_loss: 0.5022 - val_accuracy: 0.8200\n",
+            "Epoch 5/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.4031 - accuracy: 0.8475 - val_loss: 0.4076 - val_accuracy: 0.8250\n",
+            "Epoch 6/100\n",
+            "25/25 [==============================] - 1s 57ms/step - loss: 0.3765 - accuracy: 0.8575 - val_loss: 0.3962 - val_accuracy: 0.8400\n",
+            "Epoch 7/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.3501 - accuracy: 0.8737 - val_loss: 0.3714 - val_accuracy: 0.8500\n",
+            "Epoch 8/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.3400 - accuracy: 0.8825 - val_loss: 0.4636 - val_accuracy: 0.8400\n",
+            "Epoch 9/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.3583 - accuracy: 0.8813 - val_loss: 0.3804 - val_accuracy: 0.8750\n",
+            "Epoch 10/100\n",
+            "25/25 [==============================] - 1s 58ms/step - loss: 0.2930 - accuracy: 0.9062 - val_loss: 0.2661 - val_accuracy: 0.9000\n",
+            "Epoch 11/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.2774 - accuracy: 0.9150 - val_loss: 0.2322 - val_accuracy: 0.9250\n",
+            "Epoch 12/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.2482 - accuracy: 0.9225 - val_loss: 0.1905 - val_accuracy: 0.9300\n",
+            "Epoch 13/100\n",
+            "25/25 [==============================] - 1s 58ms/step - loss: 0.2354 - accuracy: 0.9250 - val_loss: 0.1434 - val_accuracy: 0.9450\n",
+            "Epoch 14/100\n",
+            "25/25 [==============================] - 1s 58ms/step - loss: 0.1966 - accuracy: 0.9375 - val_loss: 0.1184 - val_accuracy: 0.9550\n",
+            "Epoch 15/100\n",
+            "25/25 [==============================] - 2s 63ms/step - loss: 0.1737 - accuracy: 0.9438 - val_loss: 0.1303 - val_accuracy: 0.9550\n",
+            "Epoch 16/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.1584 - accuracy: 0.9538 - val_loss: 0.1612 - val_accuracy: 0.9300\n",
+            "Epoch 17/100\n",
+            "25/25 [==============================] - 1s 58ms/step - loss: 0.1678 - accuracy: 0.9475 - val_loss: 0.1233 - val_accuracy: 0.9600\n",
+            "Epoch 18/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.1497 - accuracy: 0.9513 - val_loss: 0.1085 - val_accuracy: 0.9600\n",
+            "Epoch 19/100\n",
+            "25/25 [==============================] - 1s 58ms/step - loss: 0.1465 - accuracy: 0.9538 - val_loss: 0.2445 - val_accuracy: 0.8900\n",
+            "Epoch 20/100\n",
+            "25/25 [==============================] - 1s 58ms/step - loss: 0.1884 - accuracy: 0.9450 - val_loss: 0.1884 - val_accuracy: 0.9300\n",
+            "Epoch 21/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.1411 - accuracy: 0.9613 - val_loss: 0.1124 - val_accuracy: 0.9550\n",
+            "Epoch 22/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.1247 - accuracy: 0.9625 - val_loss: 0.0845 - val_accuracy: 0.9700\n",
+            "Epoch 23/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.1300 - accuracy: 0.9525 - val_loss: 0.1638 - val_accuracy: 0.9400\n",
+            "Epoch 24/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.1332 - accuracy: 0.9613 - val_loss: 0.1487 - val_accuracy: 0.9450\n",
+            "Epoch 25/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.1125 - accuracy: 0.9700 - val_loss: 0.0699 - val_accuracy: 0.9750\n",
+            "Epoch 26/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0964 - accuracy: 0.9712 - val_loss: 0.0546 - val_accuracy: 0.9750\n",
+            "Epoch 27/100\n",
+            "25/25 [==============================] - 2s 60ms/step - loss: 0.1295 - accuracy: 0.9563 - val_loss: 0.0975 - val_accuracy: 0.9600\n",
+            "Epoch 28/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.1223 - accuracy: 0.9625 - val_loss: 0.0972 - val_accuracy: 0.9550\n",
+            "Epoch 29/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.1215 - accuracy: 0.9613 - val_loss: 0.0825 - val_accuracy: 0.9600\n",
+            "Epoch 30/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0901 - accuracy: 0.9725 - val_loss: 0.0486 - val_accuracy: 0.9850\n",
+            "Epoch 31/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0981 - accuracy: 0.9638 - val_loss: 0.1641 - val_accuracy: 0.9200\n",
+            "Epoch 32/100\n",
+            "25/25 [==============================] - 2s 60ms/step - loss: 0.1131 - accuracy: 0.9563 - val_loss: 0.0882 - val_accuracy: 0.9650\n",
+            "Epoch 33/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0744 - accuracy: 0.9737 - val_loss: 0.0814 - val_accuracy: 0.9550\n",
+            "Epoch 34/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0833 - accuracy: 0.9787 - val_loss: 0.1329 - val_accuracy: 0.9650\n",
+            "Epoch 35/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.1251 - accuracy: 0.9575 - val_loss: 0.1001 - val_accuracy: 0.9450\n",
+            "Epoch 36/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0963 - accuracy: 0.9750 - val_loss: 0.0545 - val_accuracy: 0.9800\n",
+            "Epoch 37/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0757 - accuracy: 0.9737 - val_loss: 0.0577 - val_accuracy: 0.9850\n",
+            "Epoch 38/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0633 - accuracy: 0.9800 - val_loss: 0.0986 - val_accuracy: 0.9650\n",
+            "Epoch 39/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0702 - accuracy: 0.9787 - val_loss: 0.1083 - val_accuracy: 0.9600\n",
+            "Epoch 40/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0934 - accuracy: 0.9762 - val_loss: 0.0567 - val_accuracy: 0.9850\n",
+            "Epoch 41/100\n",
+            "25/25 [==============================] - 1s 58ms/step - loss: 0.0766 - accuracy: 0.9750 - val_loss: 0.0457 - val_accuracy: 0.9800\n",
+            "Epoch 42/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0764 - accuracy: 0.9750 - val_loss: 0.1203 - val_accuracy: 0.9650\n",
+            "Epoch 43/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.0641 - accuracy: 0.9787 - val_loss: 0.0335 - val_accuracy: 0.9850\n",
+            "Epoch 44/100\n",
+            "25/25 [==============================] - 2s 64ms/step - loss: 0.0673 - accuracy: 0.9800 - val_loss: 0.0599 - val_accuracy: 0.9750\n",
+            "Epoch 45/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0460 - accuracy: 0.9862 - val_loss: 0.0293 - val_accuracy: 0.9850\n",
+            "Epoch 46/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0522 - accuracy: 0.9812 - val_loss: 0.0317 - val_accuracy: 0.9850\n",
+            "Epoch 47/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0444 - accuracy: 0.9825 - val_loss: 0.0245 - val_accuracy: 0.9900\n",
+            "Epoch 48/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0430 - accuracy: 0.9850 - val_loss: 0.0203 - val_accuracy: 0.9950\n",
+            "Epoch 49/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0671 - accuracy: 0.9750 - val_loss: 0.1684 - val_accuracy: 0.9600\n",
+            "Epoch 50/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0560 - accuracy: 0.9750 - val_loss: 0.0633 - val_accuracy: 0.9750\n",
+            "Epoch 51/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0388 - accuracy: 0.9887 - val_loss: 0.0257 - val_accuracy: 0.9950\n",
+            "Epoch 52/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0317 - accuracy: 0.9912 - val_loss: 0.0489 - val_accuracy: 0.9850\n",
+            "Epoch 53/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0254 - accuracy: 0.9912 - val_loss: 0.0399 - val_accuracy: 0.9850\n",
+            "Epoch 54/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0627 - accuracy: 0.9825 - val_loss: 0.2258 - val_accuracy: 0.9500\n",
+            "Epoch 55/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0522 - accuracy: 0.9850 - val_loss: 0.0482 - val_accuracy: 0.9850\n",
+            "Epoch 56/100\n",
+            "25/25 [==============================] - 2s 60ms/step - loss: 0.0344 - accuracy: 0.9925 - val_loss: 0.1025 - val_accuracy: 0.9700\n",
+            "Epoch 57/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0527 - accuracy: 0.9825 - val_loss: 0.0224 - val_accuracy: 0.9900\n",
+            "Epoch 58/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0526 - accuracy: 0.9775 - val_loss: 0.1285 - val_accuracy: 0.9700\n",
+            "Epoch 59/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0475 - accuracy: 0.9825 - val_loss: 0.0840 - val_accuracy: 0.9850\n",
+            "Epoch 60/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0445 - accuracy: 0.9837 - val_loss: 0.1239 - val_accuracy: 0.9550\n",
+            "Epoch 61/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0355 - accuracy: 0.9900 - val_loss: 0.1234 - val_accuracy: 0.9700\n",
+            "Epoch 62/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0445 - accuracy: 0.9812 - val_loss: 0.1124 - val_accuracy: 0.9700\n",
+            "Epoch 63/100\n",
+            "25/25 [==============================] - 1s 58ms/step - loss: 0.0383 - accuracy: 0.9900 - val_loss: 0.0753 - val_accuracy: 0.9650\n",
+            "Epoch 64/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0365 - accuracy: 0.9862 - val_loss: 0.0772 - val_accuracy: 0.9750\n",
+            "Epoch 65/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0345 - accuracy: 0.9862 - val_loss: 0.1063 - val_accuracy: 0.9700\n",
+            "Epoch 66/100\n",
+            "25/25 [==============================] - 2s 60ms/step - loss: 0.0266 - accuracy: 0.9925 - val_loss: 0.0663 - val_accuracy: 0.9700\n",
+            "Epoch 67/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.0274 - accuracy: 0.9937 - val_loss: 0.0642 - val_accuracy: 0.9800\n",
+            "Epoch 68/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0248 - accuracy: 0.9900 - val_loss: 0.0289 - val_accuracy: 0.9900\n",
+            "Epoch 69/100\n",
+            "25/25 [==============================] - 2s 60ms/step - loss: 0.0214 - accuracy: 0.9950 - val_loss: 0.0804 - val_accuracy: 0.9750\n",
+            "Epoch 70/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0158 - accuracy: 0.9950 - val_loss: 0.1147 - val_accuracy: 0.9700\n",
+            "Epoch 71/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0136 - accuracy: 0.9962 - val_loss: 0.1413 - val_accuracy: 0.9750\n",
+            "Epoch 72/100\n",
+            "25/25 [==============================] - 3s 113ms/step - loss: 0.0228 - accuracy: 0.9900 - val_loss: 0.1420 - val_accuracy: 0.9650\n",
+            "Epoch 73/100\n",
+            "25/25 [==============================] - 3s 103ms/step - loss: 0.0231 - accuracy: 0.9937 - val_loss: 0.1359 - val_accuracy: 0.9700\n",
+            "Epoch 74/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.0149 - accuracy: 0.9962 - val_loss: 0.0673 - val_accuracy: 0.9800\n",
+            "Epoch 75/100\n",
+            "25/25 [==============================] - 2s 60ms/step - loss: 0.0247 - accuracy: 0.9950 - val_loss: 0.0931 - val_accuracy: 0.9650\n",
+            "Epoch 76/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 0.0614 - val_accuracy: 0.9850\n",
+            "Epoch 77/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 0.0785 - val_accuracy: 0.9650\n",
+            "Epoch 78/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0038 - accuracy: 0.9987 - val_loss: 0.0788 - val_accuracy: 0.9700\n",
+            "Epoch 79/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0039 - accuracy: 0.9987 - val_loss: 0.0824 - val_accuracy: 0.9700\n",
+            "Epoch 80/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0054 - accuracy: 0.9975 - val_loss: 0.0733 - val_accuracy: 0.9750\n",
+            "Epoch 81/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0042 - accuracy: 0.9987 - val_loss: 0.0457 - val_accuracy: 0.9800\n",
+            "Epoch 82/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0022 - accuracy: 1.0000 - val_loss: 0.0631 - val_accuracy: 0.9800\n",
+            "Epoch 83/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.0032 - accuracy: 0.9987 - val_loss: 0.1135 - val_accuracy: 0.9700\n",
+            "Epoch 84/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0104 - accuracy: 0.9950 - val_loss: 0.1972 - val_accuracy: 0.9600\n",
+            "Epoch 85/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.0648 - accuracy: 0.9825 - val_loss: 0.0586 - val_accuracy: 0.9700\n",
+            "Epoch 86/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0610 - accuracy: 0.9712 - val_loss: 0.0622 - val_accuracy: 0.9700\n",
+            "Epoch 87/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.0438 - accuracy: 0.9850 - val_loss: 0.0597 - val_accuracy: 0.9750\n",
+            "Epoch 88/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.0233 - accuracy: 0.9912 - val_loss: 0.0535 - val_accuracy: 0.9750\n",
+            "Epoch 89/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0244 - accuracy: 0.9887 - val_loss: 0.2603 - val_accuracy: 0.9400\n",
+            "Epoch 90/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.1068 - accuracy: 0.9663 - val_loss: 0.1615 - val_accuracy: 0.9500\n",
+            "Epoch 91/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0773 - accuracy: 0.9787 - val_loss: 0.1007 - val_accuracy: 0.9550\n",
+            "Epoch 92/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0293 - accuracy: 0.9875 - val_loss: 0.0903 - val_accuracy: 0.9600\n",
+            "Epoch 93/100\n",
+            "25/25 [==============================] - 1s 59ms/step - loss: 0.0494 - accuracy: 0.9850 - val_loss: 0.0950 - val_accuracy: 0.9600\n",
+            "Epoch 94/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0390 - accuracy: 0.9825 - val_loss: 0.1126 - val_accuracy: 0.9650\n",
+            "Epoch 95/100\n",
+            "25/25 [==============================] - 2s 60ms/step - loss: 0.0131 - accuracy: 0.9962 - val_loss: 0.0764 - val_accuracy: 0.9750\n",
+            "Epoch 96/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0207 - accuracy: 0.9925 - val_loss: 0.0938 - val_accuracy: 0.9750\n",
+            "Epoch 97/100\n",
+            "25/25 [==============================] - 1s 60ms/step - loss: 0.0571 - accuracy: 0.9850 - val_loss: 0.0605 - val_accuracy: 0.9800\n",
+            "Epoch 98/100\n",
+            "25/25 [==============================] - 2s 61ms/step - loss: 0.0346 - accuracy: 0.9887 - val_loss: 0.0920 - val_accuracy: 0.9650\n",
+            "Epoch 99/100\n",
+            "25/25 [==============================] - 2s 60ms/step - loss: 0.0207 - accuracy: 0.9925 - val_loss: 0.0486 - val_accuracy: 0.9800\n",
+            "Epoch 100/100\n",
+            "25/25 [==============================] - 2s 62ms/step - loss: 0.0135 - accuracy: 0.9937 - val_loss: 0.0432 - val_accuracy: 0.9800\n"
+          ]
+        }
+      ],
+      "source": [
+        "### train using GRU model\n",
+        "model_B = create_model_BiGRU()\n",
+        "# history = model_B.fit(np.expand_dims(heart_sound_data_array[:training_samples],-1), labels_categorical[:training_samples], validation_data=(np.expand_dims(heart_sound_data_array[training_samples:training_samples+validation_samples], -1), labels_categorical[training_samples:training_samples+validation_samples]), epochs=50, shuffle=True)\n",
+        "history = model_B.fit(np.expand_dims(x_train, -1),\n",
+        "                      y = y_train,\n",
+        "                      validation_data = (np.expand_dims(x_test, -1), y_test), \n",
+        "                      epochs = 100, \n",
+        "                      shuffle=True)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "2_l2sgmXYHbA",
+        "outputId": "afa8376d-04d0-493a-9d9e-1bc1d8404522"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Model: \"sequential_3\"\n",
+            "_________________________________________________________________\n",
+            " Layer (type)                Output Shape              Param #   \n",
+            "=================================================================\n",
+            " bidirectional_3 (Bidirectio  (None, 256)              100608    \n",
+            " nal)                                                            \n",
+            "                                                                 \n",
+            " dense_9 (Dense)             (None, 64)                16448     \n",
+            "                                                                 \n",
+            " dropout_6 (Dropout)         (None, 64)                0         \n",
+            "                                                                 \n",
+            " activation_9 (Activation)   (None, 64)                0         \n",
+            "                                                                 \n",
+            " dense_10 (Dense)            (None, 32)                2080      \n",
+            "                                                                 \n",
+            " dropout_7 (Dropout)         (None, 32)                0         \n",
+            "                                                                 \n",
+            " activation_10 (Activation)  (None, 32)                0         \n",
+            "                                                                 \n",
+            " dense_11 (Dense)            (None, 2)                 66        \n",
+            "                                                                 \n",
+            " activation_11 (Activation)  (None, 2)                 0         \n",
+            "                                                                 \n",
+            "=================================================================\n",
+            "Total params: 119,202\n",
+            "Trainable params: 119,202\n",
+            "Non-trainable params: 0\n",
+            "_________________________________________________________________\n"
+          ]
+        }
+      ],
+      "source": [
+        "model_B.summary()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 295
+        },
+        "id": "ttjhitGtoaib",
+        "outputId": "644db387-d6f5-4fba-fc83-e4b357153e20"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "### loss plots using GRU model\n",
+        "loss = history.history['loss']\n",
+        "val_loss = history.history['val_loss']\n",
+        "\n",
+        "epochs = range(1, len(loss) + 1)\n",
+        "\n",
+        "plt.plot(epochs, loss, 'ro', label='Training loss')\n",
+        "plt.plot(epochs, val_loss, 'b', label='Validation loss')\n",
+        "plt.title('Training and validation loss')\n",
+        "plt.xlabel('Epochs')\n",
+        "plt.ylabel('Loss')\n",
+        "plt.legend()\n",
+        "\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 295
+        },
+        "id": "AvIklWv8ocSL",
+        "outputId": "75d2d95f-caf2-4fce-80a7-a52709f62aec"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "### accuracy plots using GRU model\n",
+        "plt.clf()                                                \n",
+        "\n",
+        "acc = history.history['accuracy']\n",
+        "val_acc = history.history['val_accuracy']\n",
+        "\n",
+        "plt.plot(epochs, acc, 'ro', label='Training acc')\n",
+        "plt.plot(epochs, val_acc, 'b', label='Validation acc')\n",
+        "plt.title('Training and validation accuracy')\n",
+        "plt.xlabel('Epochs')\n",
+        "plt.ylabel('Loss')\n",
+        "plt.legend()\n",
+        "\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "OzLmvhozoeL_",
+        "outputId": "e91f5a8c-05fb-446b-c670-be04f28e30cc"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "7/7 [==============================] - 0s 12ms/step - loss: 0.0432 - accuracy: 0.9800\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[0.04317435622215271, 0.9800000190734863]"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 37
+        }
+      ],
+      "source": [
+        "### evaluate using model B\n",
+        "model_B.evaluate(np.expand_dims(x_test, -1), y_test)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "xjyJWCInogII"
+      },
+      "outputs": [],
+      "source": [
+        "model_B.save_weights(\"Model_GRU.h5\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Gpfco1KHpKjH",
+        "outputId": "a468ae78-563f-4fb0-df2c-a8e46447aa77"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "7/7 [==============================] - 1s 16ms/step\n"
+          ]
+        }
+      ],
+      "source": [
+        "y_pred = model_B.predict(np.expand_dims(x_test,-1))\n",
+        "y_pred = np.argmax(y_pred, axis=1)\n",
+        "# y_test = np.expand_dims(y_test,-1)\n",
+        "y_true = np.argmax(y_test, axis=1)\n",
+        "y_true\n",
+        "\n",
+        "conf_heart_sound = confusion_matrix(y_true=y_true, y_pred=y_pred)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 312
+        },
+        "id": "mLmBllC_pPLe",
+        "outputId": "9ee0aeec-3cd1-4ea5-c4d3-f4f910584e40"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "[Text(0, 0.5, 'healthy'), Text(0, 1.5, 'unhealthy')]"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 40
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 2 Axes>"
+            ],
+            "image/png": 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rE7CZVZW6WmVemhIRHwEfSlo/XbU78CYwBjgmXXcMMLrYWF2CMLOq0tzJtRYaCtwqaRngPWAwScf1LknHAe8DhxTbuBOwmVWVUibgiHgZ2LqBTbuXon0nYDOrKlE50wE7AZtZdSlxCaKsnIDNrKq0ZBha3pyAzayq1GaY46G9cAI2s6riHrCZWU5cAzYzy4lHQZiZ5cQ9YDOznNTWVc4MC07AZlZVXIIwM8tJnUdBmJnlw8PQzMxy4hJEgeW3P6nch7AKNH/auLxDsCrlEoSZWU48CsLMLCcVVIFwAjaz6uIShJlZTjwKwswsJ83f7Lj9cAI2s6oSuAdsZpaLGpcgzMzy4R6wmVlOXAM2M8uJe8BmZjlxD9jMLCe17gGbmeWjgu5I5ARsZtWlzj1gM7N8eDIeM7Oc+CScmVlO6uQShJlZLmrzDqAFnIDNrKpU0iiIyrl3h5lZBnUo85KFpI6SXpJ0f/p6TUnjJb0r6U5JyxQbqxOwmVWVaMGS0anAWwWvLwZ+FxHrAJ8BxxUbqxOwmVWVOmVfmiNpALAPcG36WsC3gHvSXUYBBxQbq2vAZlZVSjwM7ffA2UD39PVKwKyIqElfTwH6F9u4e8BmVlVqlX2RNETSiwXLkPp2JO0LfBwRE8sVq3vAZlZVWtIDjogRwIhGNu8E7C/pO0AXoAdwBbCCpE5pL3gAMLXYWN0DNrOqUteCpSkR8bOIGBARawCHAY9HxJHAE8BB6W7HAKOLjdUJ2MyqSij7UqSfAqdLepekJnxdsQ25BGFmVaUcc0FExJPAk+nz94BtS9GuE7CZVRVfimxmlpNKuhQ5UwKW1DEiKukPi5ktpSppOsqsJ+HekXSppI3KGo2ZWSuVahREW8iagDcD3gaulfR8Oni5RxnjMjMrShnmgiibTAk4IuZGxMiI2JFkCMZ5wHRJoyStU9YIzcxaoJRzQZRb5howyYQUg4E1gN8CtwI7Aw8C65UpPjOzFqmkk1VZR0G8Q3L1x6UR8WzB+nsk7VL6sMzMilPXLooL2WRNwJtGxLyGNkTEKSWMx8ysVdrDybWssibgrpJOISk/LHxPRPygHEGZmRWrcvq/2RPwaGAc8Hcqq8RiZkuZauwBLxcRPy1rJGZmJVCjyukDZx0HfH86J6aZWbtWSeOAm+wBS5pLEqeAcyV9CSxIX0dE+GIMM2tXqqYEERHdm9puZtbeVNIwtEwlCEmPZVlnZpa3aipBdAG6Ab0lrUhSeoDk3khF3wnUzKxcqqYEAZwA/AToB0wqWD8HuLpcQZmZFau2XfRts2muBnwFcIWkoRFxVRvFZGZWtKrpAUv6bvp0asHzhSLi3rJEZWZWpKiWHjCwXxPbAnACNrN2pWp6wBExuK0CqXbf3nNXLr/8fDp26MD1N9zOJZf+Ie+QrESGXXQ5Tz3zAr1WXIH7brmm1e2NfnAsfx51BwAnHHMYg76zB/P/+19OH3YRU6ZOp0OHDuz6je047SRPxdKQqhuGBiBpH0lnS/pF/VLOwKpJhw4duPKKC9l3v++zyWa7ceihB7DhhuvmHZaVyAHf2YNrLr+gxe879sdnM3X6jMXWzZ4zlz/dcBu3j/w9t4/8PX+64TZmz5kLwODDv8ffbh/JPTdezUuvvsm45yaUJP5qU0nD0LKOA74GOBQYSjIU7WBg9TLGVVW23WYL/v3v/8fkyR+wYMEC7rprNPvv9+28w7IS2XrzTejZY/Frlj6YMo0TTh/GIT8YytEnncl773+Yqa1nxk9kh222oGeP7vTs0Z0dttmCZ8ZPpGuXLmy71WYAdO7cmQ3XX4cZMz8p+WepBjVE5iVvWXvAO0bE0cBnEfFLYAd8F4zM+vVflQ+nTFv4esrU6fTrt2qOEVm5/fKSKzn3tJO46/qrOPPHx3PBZdlKTjNmfsKqq6y88HWflXt/LdHOmTuPfzwznu222rykMVeLaMF/ecs6G9r89PELSf2AT4G+je0saQgwBEAde9KhQ7dWBWlWSb74Yj4vv/YWpw+7aOG6rxYsAOCvDzzKLXeNBuCDqdM46cz/o3OnzvTv14crf918Va+mppazh1/MkQftz8D+jf4vuFSrmpNwBe6XtAJwKckFGQFc29jOETECGAHQaZn++f+Zydm0qR8xcEC/ha8H9O/LtGkf5RiRlVNd1NG9ezf+Murrvd4D99mTA/fZE0hqwBf+/Az69+2zcHuflXsz4aVXF76eMfMTttli04Wvh19yBasN6MdRhx5Yxk9Q2dpDzzarrHdF/lVEzIqIv5DUfjeIiP8rb2jVY8KLL7POOmuyxhoD6dy5M4ccMoi/3f9o3mFZmSzfrRv9+67KI4+PAyAi+Oc772V6707bbcWzL0xi9py5zJ4zl2dfmMRO220FwJUjRjFv3hecc+oJZYu9GtS1YMlb1rsiLwecAawWET+UtJqknSPi/vKGVx1qa2s59SfDePCB2+jYoQM3jrqTN998O++wrETOOu83THjpVWbNmsPuB3yfk487iovPO5tfXXY1fx51OzU1Ney9+zfZYN21mm2rZ4/unHDs4Rx2/KkAnDj4CHr26M5HH89kxKg7WHP1gRw8eCgAh39vPw7af6+yfrZKVBuV0wNWZAhW0p3ARODoiNg4TcjPRkSzZwFcgrCGzJ82Lu8QrB3q3HstNb9X045Y/cDMOee29//a6uO1RtZREGtHxCUkk7ETEV+waGY0M7N2oxpHQXwlqSvp2GVJawNfli0qM7MitYfablZZE/B5wMPAQEm3AjsBx5YrKDOzYlXSpciZEnBEjJU0CdiepPRwakT4Mhwza3faQ2khq8xzQQBdgM9IJmPfSNIu5QnJzKx4tRGZl6ZIGijpCUlvSnpD0qnp+l6Sxkp6J31csdhYsw5Du5hkLog3WFRiCeCpYg9sZlYOJSxB1ABnRMQkSd2BiZLGkpRfH4uI30g6BzgH+GkxB8haAz4AWD8ifOLNzNq1Up2Ei4jpwPT0+VxJb5HcC3MQsGu62yjgSYpMwFlLEO8BnYs5gJlZW2rJMDRJQyS9WLAMaahNSWsAWwDjgT5pcgb4COjT0HuyaO6WRFeRlBq+AF5Ob0W/sBccEacUe2Azs3JoSQmicN6axkhaHvgL8JOImCMtugQiIkJS0TWP5koQL6aPE4ExxR7EzKytZLm6NytJnUmS760F98CcIalvREyX1Bf4uNj2m7sl0ahiGzYzy0OpbkuvpKt7HfBWRFxesGkMcAzwm/RxdLHHyDoKYidgOMlMaJ1IxgJHRDQ/u4iZWRsq4SiInYCjgNckvZyuO5ck8d4l6TjgfeCQYg+QdRTEdcBpJKWI2mIPZmZWbqUqQUTE0zQ+583upThG1gQ8OyIeKsUBzczKqeouRQaekHQpcC+Lj4KYVJaozMyKVEmXImdNwNulj1uljyIZnvatkkdkZtYKlTQhe9YE/GQD6yrnU5rZUqMaSxDzCp53AfYF3ip9OGZmrVN1CTgiflv4WtJlwCNlicjMrBVKeSFGuWXtAS9pOWBAKQMxMyuFqusBS3qNRTXfjsDKwPnlCsrMrFjVOApi34LnNcCMiKgpQzxmZq1SG5VzV7isNeD3yx2ImVkpLA01YDOzdqnqasBmZpWiGmvAZmYVoc4lCDOzfLgHbGaWk6obBWFmVilcgjAzy4lLEGZmOXEP2MwsJ+4Bm5nlpDYq57aVTsBmVlV8KbKZWU58KbKZWU7cAzYzy4lHQZiZ5cSjIMzMcuJLkc3McuIasJlZTlwDNjPLiXvAZmY58ThgM7OcuAdsZpYTj4IwM8uJT8KZmeWkkkoQHfIOwMyslKIF/zVH0l6S/iXpXUnnlDpW94DNrKqUqgcsqSPwB2APYAowQdKYiHizJAfACdjMqkwJa8DbAu9GxHsAku4ABgGVk4Brvpqqch+jUkgaEhEj8o7D2hf/XpRWS3KOpCHAkIJVIwp+Fv2BDwu2TQG2a32Ei7gG3LaGNL+LLYX8e5GTiBgREVsXLG36h9AJ2MysYVOBgQWvB6TrSsYJ2MysYROAdSWtKWkZ4DBgTCkP4JNwbct1PmuIfy/aoYiokfRj4BGgI3B9RLxRymOokgYtm5lVE5cgzMxy4gRsZpYTJ+AMJK0h6fUStHOspKvT5wdI2qhg25OStm7tMSx/hT/nErR1o6SD0uc/kbRcwbZ5pTiG5ccJOD8HABs1u5fZIj8Blmt2L6sYTsDZdZQ0UtIbkh6V1FXS2pIeljRR0jhJGwBI2k/SeEkvSfq7pD6FDUnaEdgfuFTSy5LWTjcdLOkFSW9L2jnd9ylJmxe892lJm7XRZza+/g1I0pmShqffWi5e8meW6pf+brwj6ZKC9+4p6TlJkyTdLWn5dP0vJE2Q9LqkEZIWu5pL0ilAP+AJSU8UrL9Q0iuSnpfUR1J3SZMldU639yh8be2LE3B26wJ/iIj/AWYB3yMZPjQ0IrYCzgT+mO77NLB9RGwB3AGcXdhQRDxLMp7wrIjYPCL+nW7qFBHbkvR0zkvXXQccCyBpPaBLRLxSno9oRWjoZwawOXAosAlwqKSBknoDw4D/jYgtgReB09P9r46IbSJiY6ArsG/hQSLiSmAasFtE7Jau7gY8HxGbAU8BP4yIucCTwD7pPocB90bEglJ+aCsNjwPObnJEvJw+nwisAewI3F3QWVk2fRwA3CmpL7AMMDnjMe5don2Au4H/k3QW8APgxuLCtzJp6GcG8FhEzAaQ9CawOrACSdnpmfR3ZhnguXT/3SSdTVJi6AW8AfytmWN/BdxfcPw90ufXkvzRvw8YDPywiM9lbcAJOLsvC57XAn2AWRGxeQP7XgVcHhFjJO0KDG/hMWpJfzYR8YWksSSzMB0CbNXy0K2Valj822KXgudf+5ktsb5wm4CxEXF4YeOSupB8e9o6Ij6UNHyJYzRmQSwayF/4O/NMWjbZFegYEa0+gWzl4RJE8eYAkyUdDKBEfW22J4uuGT+mkffPBbpnPNa1wJXAhIj4rMh4rXgzgFUkrSRpWZYoD7TA88BOktYBkNStvqyUbv8krQkf1Mj7W/I7cxNwG3BDkbFaG3ACbp0jgeMkvULylXFQun44SWliIvBJI++9AzgrPVG3diP7ABARE0kSvv9nykFaPz0feAEYC/yzyHZmktTzb5f0Kkn5YYOImAWMBF4nuex1QiNNjAAeLjwJ14RbgRWB24uJ1dqGL0WuAJL6kZxY2SCigm75arlJxw4Pioij8o7FGucacDsn6WjgQuB0J1/LQtJVwN7Ad/KOxZrmHrCZWU5cAzYzy4kTsJlZTpyAzcxy4gS8lJJUm85D8Xo6J0HRk7wsMWPXtYWzvDWw767pXBgNbWt2FrF0DoYzWxifZw2zdskJeOk1P52HYmOSS1pPLNwoqagRMhFxfES82cQuu5Jcwm221HMCNoBxwDpp73ScpDHAm5I6Sro0naXrVUknwMKr/q6W9C9JfwdWqW9IBfMaS9ornfXrFUmPSVqDJNGflva+d/5aJIvaaWpGuc3SGcXekfTDgvecVRDrLxtos6+S2eXqe/6NHt+sLXgc8FIu7enuDTycrtoS2DgiJksaAsyOiG3SS3CfkfQosAWwPsnEMn2AN4Hrl2h3ZZKru3ZJ2+oVEf+RdA0wLyIuaya0+hnlQtLxJJPLnJFu2xTYnmQ2sJckPQBsTDJj3bYkcy6MkbRLRDxV0OYRwCMRcaGkjnhuXcuZE/DSq6uk+tndxpFMe7kj8EJE1M/etiewaX19l2SOi3WBXYDbI6IWmCbp8Qba3x54qr6tiPhPC+Nraka50RExH5ifXpa7LfCNNN6X0n2WT2MtTMATgOvTuXHvK5jdziwXTsBLr/lLzuSWTpH4eeEqkvmOH1liv7a4wqqpGeWWvHooSGL9dUT8ubEGI+IpSbuQzJV7o6TLI+Km0oZtlp1rwNaUR4CTCu6usJ6kbiS9ykPTGnFfYLcG3vs8sIukNdP39krXZ53Rq6kZ5QZJ6iJpJZKTehPSWH+gRXeY6C9plcI3SVodmBERI0lmmNsyQxxmZeMesDXlWpJJxicp6R7PJLmX3V+Bb5HUfj9g0aTiC0XEzLSGfK+kDsDHJBOG/w24R9Igkt71uEaOPZxkRrnPgMeBNQu2vQo8AfQGfhUR040BFdgAAABQSURBVEhKIRsCz6U9+XnA99Pj1tuVZAa6Ben2o1vyj2FWap4LwswsJy5BmJnlxAnYzCwnTsBmZjlxAjYzy4kTsJlZTpyAzcxy4gRsZpaT/w/9X9KTYElAxQAAAABJRU5ErkJggg==\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "ax = plt.subplot()\n",
+        "sns.heatmap(conf_heart_sound, annot= True, ax = ax)\n",
+        "\n",
+        "ax.set_xlabel('Predict labels')\n",
+        "ax.set_title('Confusion Matrix')\n",
+        "ax.xaxis.set_ticklabels(['healthy','unhealthy'])\n",
+        "ax.yaxis.set_ticklabels(['healthy','unhealthy'])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "-OZG_ZtKFM9V",
+        "outputId": "254b51a6-d74e-4b02-8169-8089c19d4a95"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "7/7 [==============================] - 0s 13ms/step\n",
+            "              precision    recall  f1-score   support\n",
+            "\n",
+            "     Healthy       1.00      0.96      0.98        98\n",
+            "   Unhealthy       0.96      1.00      0.98       102\n",
+            "\n",
+            "    accuracy                           0.98       200\n",
+            "   macro avg       0.98      0.98      0.98       200\n",
+            "weighted avg       0.98      0.98      0.98       200\n",
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Menampilkan nilai presisi, recall, dan F1-score\n",
+        "pred_B = model_B.predict(np.expand_dims(x_test, -1))\n",
+        "modelB_predicted = np.argmax(pred_B, axis = 1)\n",
+        "\n",
+        "File=[\"Healthy\", \"Unhealthy\"]\n",
+        "print(classification_report(y_test.argmax(axis=1), modelB_predicted, target_names=File))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "19gCQYX5KoJw",
+        "outputId": "b71071ad-44c5-416c-a6d8-8398b2ad5fd0"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "7/7 [==============================] - 0s 13ms/step\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Menampilkan kurva AUC-ROC\n",
+        "Y_pred = model_B.predict(np.expand_dims(x_test, -1))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "6zV-aZPrLEqu"
+      },
+      "outputs": [],
+      "source": [
+        "n_classes = 2\n",
+        "lw = 2\n",
+        "Y_val = y_test\n",
+        "fpr = dict()\n",
+        "tpr = dict()\n",
+        "roc_auc = dict()\n",
+        "for i in range(n_classes):\n",
+        "    fpr[i], tpr[i], _ = roc_curve(Y_val[:, i], Y_pred[:, i])\n",
+        "    roc_auc[i] = auc(fpr[i], tpr[i])\n",
+        "\n",
+        "# Compute micro-average ROC curve and ROC area\n",
+        "fpr[\"micro\"], tpr[\"micro\"], _ = roc_curve(Y_val.ravel(), Y_pred.ravel())\n",
+        "roc_auc[\"micro\"] = auc(fpr[\"micro\"], tpr[\"micro\"])"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "hAbZB7SPLMbc",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 548
+        },
+        "outputId": "46df7a42-fee6-4a1e-aefb-55fc9072f02c"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "<ipython-input-44-c858286738c8>:7: DeprecationWarning: scipy.interp is deprecated and will be removed in SciPy 2.0.0, use numpy.interp instead\n",
+            "  mean_tpr += interp(all_fpr, fpr[i], tpr[i])\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 576x576 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "# Pertama-tama, gabungkan semua False Positive Rates\n",
+        "all_fpr = np.unique(np.concatenate([fpr[i] for i in range(n_classes)]))\n",
+        "\n",
+        "# Kemudian interpolasi semua kurva ROC pada titik ini\n",
+        "mean_tpr = np.zeros_like(all_fpr)\n",
+        "for i in range(n_classes):\n",
+        "    mean_tpr += interp(all_fpr, fpr[i], tpr[i])\n",
+        "\n",
+        "# Terakhir, rata-rata dan hitung AUC\n",
+        "mean_tpr /= n_classes\n",
+        "\n",
+        "fpr[\"macro\"] = all_fpr\n",
+        "tpr[\"macro\"] = mean_tpr\n",
+        "roc_auc[\"macro\"] = auc(fpr[\"macro\"], tpr[\"macro\"])\n",
+        "\n",
+        "# Plot semua kurva ROC\n",
+        "plt.figure(figsize=(8, 8))\n",
+        "plt.plot(fpr[\"micro\"], tpr[\"micro\"],\n",
+        "         label='micro-average ROC curve (area = {0:0.2f})'\n",
+        "               ''.format(roc_auc[\"micro\"]),\n",
+        "         color='deeppink', linestyle=':', linewidth=4)\n",
+        "\n",
+        "plt.plot(fpr[\"macro\"], tpr[\"macro\"],\n",
+        "         label='macro-average ROC curve (area = {0:0.2f})'\n",
+        "               ''.format(roc_auc[\"macro\"]),\n",
+        "         color='navy', linestyle=':', linewidth=4)\n",
+        "\n",
+        "colors = cycle(['orange', 'green', 'blue'])\n",
+        "for i, color in zip(range(n_classes), colors):\n",
+        "    plt.plot(fpr[i], tpr[i], color=color, lw=lw,\n",
+        "             label='ROC curve of class {0} (area = {1:0.2f})'\n",
+        "             ''.format(i, roc_auc[i]))\n",
+        "\n",
+        "plt.plot([0, 1], [0, 1], 'k--', lw=lw)\n",
+        "plt.xlim([0.0, 1.0])\n",
+        "plt.ylim([0.0, 1.05])\n",
+        "plt.xlabel('False Positive Rate')\n",
+        "plt.ylabel('True Positive Rate')\n",
+        "plt.title('Some extension of Receiver operating characteristic to multi-class')\n",
+        "plt.legend(loc=\"lower right\")\n",
+        "plt.show()"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "collapsed_sections": [
+        "rbKryB-2iD4V"
+      ],
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.6.4"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
\ No newline at end of file
diff --git a/assignment-01/H071181301/Main.java b/assignment-01/H071181301/Main.java
new file mode 100644
index 0000000..350a26a
--- /dev/null
+++ b/assignment-01/H071181301/Main.java
@@ -0,0 +1,22 @@
+public class Main {
+    public static void main(String[] args) {
+        SingleLinkedList<String> str = new SingleLinkedList<>();
+        SingleLinkedList<String> str2 = new SingleLinkedList<>();
+
+        str.isEmpty();
+        str.traverse();
+        str.append("1");
+        str.append("2");
+        str.append("3");
+        str.append("4");
+        str.append("5");
+        str2.append("satu");
+        str.mergeAppend(str2);
+        str.traverse();
+        str.indexOf("satu");
+        str.prependBeforeIndex("6", 0);
+        str.traverse();
+
+    }
+
+}
\ No newline at end of file
diff --git a/assignment-01/H071181301/Node.java b/assignment-01/H071181301/Node.java
new file mode 100644
index 0000000..d2b443f
--- /dev/null
+++ b/assignment-01/H071181301/Node.java
@@ -0,0 +1,24 @@
+public class Node<T> {
+    private T data;
+    private Node<T> pointer;
+
+    public Node(T data) {
+        this.data = data;
+    }
+
+    public Node<T> getPointer() {
+        return pointer;
+    }
+
+    public void setPointer(Node<T> pointer) {
+        this.pointer = pointer;
+    }
+
+    public T getData() {
+        return data;
+    }
+
+    public boolean hasPointer() {
+        return pointer != null;
+    }
+}
diff --git a/assignment-01/H071181301/SingleLinkedList.java b/assignment-01/H071181301/SingleLinkedList.java
new file mode 100644
index 0000000..c0bbc28
--- /dev/null
+++ b/assignment-01/H071181301/SingleLinkedList.java
@@ -0,0 +1,650 @@
+import java.util.NoSuchElementException;
+
+public class SingleLinkedList<T> {
+    private Node<T> head;
+    private Node<T> tail;
+    private int size;
+
+    public void append(T data) {
+        if (head == null) {
+            head = new Node<T>(data);
+            size++;
+            return;
+        }
+        if (tail == null) {
+            tail = new Node<T>(data);
+            head.setPointer(tail);
+            size++;
+            return;
+        }
+        Node<T> newNode = new Node<T>(data);
+        tail.setPointer(newNode);
+        tail = newNode;
+        size++;
+    }
+
+    public void appendAfterData(T data, T after) {
+        if (head == null) {
+            head = new Node<T>(data);
+            size++;
+            return;
+        }
+        if (tail == null) {
+            tail = new Node<T>(data);
+            head.setPointer(tail);
+            size++;
+            return;
+        }
+
+        Node<T> node = head;
+        Node<T> newNode = new Node<T>(data);
+
+        while (node.getPointer() != null) {
+            if (node.getData() == after) {
+                newNode.setPointer(node.getPointer());
+                node.setPointer(newNode);
+                size++;
+                return;
+            }
+            if (tail.getData() == after || node.getData() != after) {
+                append(data);
+                size++;
+                return;
+            }
+            node = node.getPointer();
+        }
+    }
+
+    public void appendAfterIndex(T data, int index) {
+        if (head == null) {
+            head = new Node<T>(data);
+            size++;
+            return;
+        }
+        if (tail == null) {
+            tail = new Node<T>(data);
+            head.setPointer(tail);
+            size++;
+            return;
+        }
+
+        int pos = 0;
+        Node<T> node = head;
+        Node<T> newNode = new Node<T>(data);
+
+        while (node.getPointer() != null) {
+            if (pos == index) {
+                newNode.setPointer(node.getPointer());
+                node.setPointer(newNode);
+                size++;
+                return;
+            }
+            pos++;
+            node = node.getPointer();
+        }
+        if ((size - 1) == index || pos != index) {
+            append(data);
+            size++;
+            return;
+        }
+    }
+
+    public void appendVarargs(T... datas) {
+        for (T data : datas) {
+            append(data);
+            size++;
+        }
+    }
+
+    public void prependVarargs(T... datas) {
+        for (T data : datas) {
+            prepend(data);
+            size++;
+        }
+    }
+
+    public void mergeAppend(SingleLinkedList<T> list) {
+        tail.setPointer(list.head);
+        tail = list.tail;
+        size += list.size;
+        return;
+    }
+
+    public void mergePrepend(SingleLinkedList<T> list) {
+        head = list.head;
+        list.tail.setPointer(list.head);
+        size += list.size;
+        return;
+    }
+
+    public void prepend(T data) {
+        if (head == null) {
+            head = new Node<T>(data);
+            size++;
+            return;
+        }
+
+        if (tail == null) {
+            tail = head;
+            Node<T> newNode = new Node<T>(data);
+            newNode.setPointer(tail);
+            head = newNode;
+            size++;
+            return;
+        }
+        Node<T> newNode = new Node<T>(data);
+        newNode.setPointer(head);
+        head = newNode;
+        size++;
+    }
+
+    public void prependBeforeData(T data, T before) {
+        Node<T> newNode = new Node<T>(data);
+
+        if (head == null) {
+            head = new Node<T>(data);
+            size++;
+            return;
+        }
+        if (tail == null) {
+            tail = head;
+            newNode.setPointer(tail);
+            head = newNode;
+            size++;
+            return;
+        }
+
+        Node<T> node = head;
+
+        while (node.getPointer().getPointer() != null) {
+            if (node.getPointer().getData() == before) {
+                newNode.setPointer(node.getPointer());
+                node.setPointer(newNode);
+                size++;
+                return;
+            }
+            if (node.getData() == before || node.getData() != before) {
+                prepend(data);
+                size++;
+                return;
+            }
+            node = node.getPointer();
+        }
+    }
+
+    public void prependBeforeIndex(T data, int index) {
+        if (head == null) {
+            head = new Node<T>(data);
+            size++;
+            return;
+        }
+        if (tail == null) {
+            tail = new Node<T>(data);
+            head.setPointer(tail);
+            size++;
+            return;
+        }
+
+        int pos = 0;
+        Node<T> node = head;
+        Node<T> newNode = new Node<T>(data);
+
+        while (node.getPointer().getPointer() != null) {
+            if ((pos + 1) == index) {
+                newNode.setPointer(node.getPointer());
+                node.setPointer(newNode);
+                size++;
+                return;
+            }
+            if (0 == index || pos != index) {
+                prepend(data);
+                size++;
+                return;
+            }
+            node = node.getPointer();
+            pos++;
+        }
+    }
+
+    public void removeByData(T data) {
+        Node<T> node = head;
+        while (node.getPointer().getPointer() != null) {
+            if (node.getPointer().getData() == data) {
+                node.setPointer(node.getPointer().getPointer());
+                size--;
+                return;
+            }
+            if (node.getData() == data) {
+                removeHead();
+            }
+            node = node.getPointer();
+        }
+        if (tail.getData() == data) {
+            removeTail();
+        }
+    }
+
+    public void removeByIndex(int index) {
+        int pos = 0;
+        Node<T> node = head;
+        while (node.getPointer().getPointer() != null) {
+            if (index - pos == 1) {
+                node.setPointer(node.getPointer().getPointer());
+                size--;
+                return;
+            }
+            pos++;
+            node = node.getPointer();
+        }
+        if (0 == index) {
+            removeHead();
+        }
+        if (size == index) {
+            removeTail();
+        }
+        if ((size - 1) < index) {
+            throw new IndexOutOfBoundsException("Index Out Of Bounds");
+        }
+    }
+
+    public void removeAfterData(T data) {
+        Node<T> node = head;
+        while (node.getPointer() != null) {
+            if (node.getData() == data) {
+                node.setPointer(node.getPointer().getPointer());
+                size--;
+                return;
+            }
+            node = node.getPointer();
+        }
+        if (node.getPointer() == tail) {
+            node.setPointer(null);
+            tail = node;
+        }
+    }
+
+    public void removeAfterIndex(int index) {
+        int pos = 0;
+        Node<T> node = head;
+        while (node.getPointer().getPointer() != null) {
+            if (pos == index) {
+                node.setPointer(node.getPointer().getPointer());
+                size--;
+                return;
+            }
+            pos++;
+            node = node.getPointer();
+        }
+        if (size - index == 2) {
+            removeTail();
+        }
+        if ((size - 1) < index) {
+            throw new IndexOutOfBoundsException("Index Out Of Bounds");
+        }
+    }
+
+    public void removeBeforeData(T data) {
+        Node<T> node = head;
+        while (node.getPointer().getPointer() != null) {
+            if (node.getData() == data) {
+                node.setPointer(node.getPointer().getPointer());
+                size--;
+                return;
+            }
+            node = node.getPointer();
+        }
+        if (head.getData() == data) {
+            removeHead();
+        }
+    }
+
+    public void removeBeforeIndex(int index) {
+        Node<T> node = head;
+        int pos = 0;
+
+        if ((pos + 1) == index) {
+            head = head.getPointer();
+            size--;
+            return;
+        }
+        while (node.getPointer() != null) {
+            if ((index) - pos == 2) {
+                node.setPointer(node.getPointer().getPointer());
+                size--;
+                return;
+            }
+            node = node.getPointer();
+            pos++;
+        }
+        throw new IndexOutOfBoundsException("Index Out Of Bounds");
+    }
+
+    public void removeHead() {
+        if (head == null) {
+            throw new NoSuchElementException("Empty List");
+        }
+        head = head.getPointer();
+        size--;
+    }
+
+    public void removeTail() {
+        if (head == null) {
+            throw new NoSuchElementException("Empty List");
+        } else if (tail == null) {
+            throw new NoSuchElementException("Head");
+        } else if (tail == head) {
+            throw new NoSuchElementException("Head is Tail");
+        }
+        Node<T> node = head;
+        while (node.getPointer().getPointer() != null) {
+            node = node.getPointer();
+        }
+        node.setPointer(null);
+        tail = node;
+        size--;
+    }
+
+    public void removeForwardData(T data) {
+        Node<T> node = head;
+        int count = 0;
+        try {
+            while (node.getData() != data) {
+                node = node.getPointer();
+                count++;
+            }
+            node.setPointer(null);
+            size = count + 1;
+        } catch (Exception e) {
+            throw new NoSuchElementException("No Such Element");
+        }
+    }
+
+    public void removeForwardIndex(int index) {
+        Node<T> node = head;
+        int pos = 0;
+        int count = 0;
+        try {
+            while (pos != index) {
+                node = node.getPointer();
+                count++;
+                pos++;
+            }
+            node.setPointer(null);
+            size = count + 1;
+        } catch (Exception e) {
+            throw new IndexOutOfBoundsException("Index Out Of Bounds");
+        }
+    }
+
+    public void removeBackwardData(T data) {
+        Node<T> node = head;
+        int count = 0;
+        try {
+            while (node.getData() != data) {
+                node = node.getPointer();
+                count++;
+            }
+            head = node;
+            size -= count;
+        } catch (Exception e) {
+            throw new NoSuchElementException("No Such Element");
+        }
+    }
+
+    public void removeBackwardIndex(int index) {
+        int pos = 0;
+        int count = 0;
+        Node<T> node = head;
+        try {
+            while (pos != index) {
+                node = node.getPointer();
+                count++;
+                pos++;
+            }
+            head = node;
+            size -= count;
+        } catch (Exception e) {
+            throw new IndexOutOfBoundsException("Index Out Of Bounds");
+        }
+    }
+
+    public void describeNodeData(T data) {
+        if (head == null) {
+            throw new NoSuchElementException("Empty List");
+        }
+        if (head.getData() == data) {
+            System.out.printf("{\n  data\t: %s\n  index\t: %d\n}\n", head.getData(), 0);
+            return;
+        }
+        if (tail.getData() == data) {
+            System.out.printf("{\n  data\t: %s\n  index\t: %d\n}\n", tail.getData(), size - 1);
+            return;
+        }
+        Node<T> node = head;
+        int index = 0;
+        while (node.hasPointer()) {
+            if (node.getData() == data) {
+                System.out.printf("{\n  data\t: %s\n  index\t: %d\n}\n", node.getData(), index);
+                return;
+            }
+            node = node.getPointer();
+            index++;
+        }
+        throw new NoSuchElementException("No Such Element");
+    }
+
+    public void describeNodeIndex(int index) {
+        if (head == null) {
+            throw new NoSuchElementException("Empty List");
+        }
+        if (0 == index) {
+            System.out.printf("{\n  data\t: %s\n  index\t: %d\n}\n", head.getData(), 0);
+            return;
+        }
+        if ((size - 1) == index) {
+            System.out.printf("{\n  data\t: %s\n  index\t: %d\n}\n", tail.getData(), size - 1);
+            return;
+        }
+        Node<T> node = head;
+        int pos = 0;
+        while (node.hasPointer()) {
+            if (pos == index) {
+                System.out.printf("{\n  data\t: %s\n  index\t: %d\n}\n", node.getData(), pos);
+                return;
+            }
+            node = node.getPointer();
+            pos++;
+        }
+        throw new NoSuchElementException("No Such Element");
+    }
+
+    public int indexOf(T data) {
+        int pos = 0;
+        Node<T> node = head;
+
+        while (node.getPointer() != null) {
+            pos++;
+            node = node.getPointer();
+            if (node.getData() == data) {
+                System.out.printf("indeks => %s\n", pos);
+                return pos;
+            }
+        }
+        throw new NoSuchElementException("No Such Element");
+    }
+
+    public boolean isEmpty() {
+        if (size == 0) {
+            System.out.println("List is Empty");
+            return true;
+        }
+        System.out.println("List is filled");
+        return false;
+    }
+
+    public void unique() {
+    }
+
+    public void sort() {
+    }
+
+    public void updateByData(T data, T newData) {
+        if (head == null)
+            throw new NoSuchElementException("Empty List");
+
+        Node<T> node = head;
+        Node<T> newNode = new Node<T>(newData);
+
+        if (node.getData() == data) {
+            head = newNode;
+            newNode.setPointer(node.getPointer());
+            node.setPointer(null);
+            return;
+        }
+        while (node.getPointer().getPointer() != null) {
+            if (node.getPointer().getData() == data) {
+                newNode.setPointer(node.getPointer().getPointer());
+                node.setPointer(newNode);
+                return;
+            }
+            node = node.getPointer();
+        }
+        if (tail.getData() == data) {
+            newNode.setPointer(null);
+            node.setPointer(newNode);
+            tail = newNode;
+            return;
+        }
+        if (node.getPointer().getData() != data) {
+            throw new NoSuchElementException("No Such Element");
+        }
+    }
+
+    public void updateByIndex(int index, T newData) {
+        if (head == null)
+            throw new NoSuchElementException("Empty List");
+
+        int pos = 0;
+        Node<T> node = head;
+        Node<T> newNode = new Node<T>(newData);
+
+        if (0 == index) {
+            head = newNode;
+            newNode.setPointer(node.getPointer());
+            node.setPointer(null);
+            return;
+        }
+        while (node.getPointer().getPointer() != null) {
+            if (index - pos == 1) {
+                newNode.setPointer(node.getPointer().getPointer());
+                node.setPointer(newNode);
+                return;
+            }
+            pos++;
+            node = node.getPointer();
+        }
+        if ((size - 1) == index) {
+            newNode.setPointer(null);
+            node.setPointer(newNode);
+            tail = newNode;
+            return;
+        }
+        if ((size - 1) < index)
+            throw new IndexOutOfBoundsException("Index Out Of Bounds");
+    }
+
+    public void clear() {
+        head = null;
+        size = 0;
+    }
+
+    public void traverse() {
+        if (head == null) {
+            System.out.println("Empty Linked List");
+            return;
+        }
+        Node<T> node = head;
+        while (node.hasPointer()) {
+            System.out.printf("[%s] -> ", node.getData());
+            node = node.getPointer();
+        }
+        System.out.printf("[%s] -> null\n", node.getData());
+    }
+
+    public boolean contain(T data) {
+        Node<T> node = head;
+        while (node.getPointer() != null) {
+            node = node.getPointer();
+        }
+        if (node.getData() == data) {
+            System.out.println("Data is true");
+            return true;
+        } else {
+            throw new NoSuchElementException("No Such Element");
+        }
+    }
+
+    public T get(int index) {
+        Node<T> node = head;
+        int pos = 0;
+        while (node.getPointer() != null) {
+            if (pos == index) {
+                System.out.printf("data => [%s]\n", node.getData());
+                return node.getData();
+            }
+            node = node.getPointer();
+            pos++;
+        }
+        if (size - 1 == index) {
+            System.out.printf("data => [%s]\n", node.getData());
+            return node.getData();
+        }
+        throw new IndexOutOfBoundsException("Index Out Of Bounds");
+    }
+
+    public int size() {
+        System.out.println("Size ::> " + size);
+        return size;
+    }
+
+    public void traverseFromData(T data) {
+        try {
+            if (head == null) {
+                System.out.println("Empty Linked List");
+                return;
+            }
+            Node<T> node = head;
+            while (node.getData() != data) {
+                node = node.getPointer();
+            }
+            while (node.getPointer() != null) {
+                System.out.printf("[%s] -> ", node.getData());
+                node = node.getPointer();
+            }
+            System.out.printf("[%s] -> null\n", node.getData());
+        } catch (Exception E) {
+            throw new NoSuchElementException("No Such Element");
+        }
+    }
+
+    public void traverseFromIndex(int index) {
+        Node<T> node = head;
+        int pos = 0;
+        while (node.getPointer().getPointer() != null) {
+            pos++;
+            node = node.getPointer();
+        }
+        if (pos == index) {
+            while (node.getPointer() != null) {
+                System.out.printf("[%s] -> ", node.getData());
+                node = node.getPointer();
+            }
+            System.out.printf("[%s] -> null\n", node.getData());
+            return;
+        }
+        if (pos != index) {
+            throw new IndexOutOfBoundsException("Index Out Of Bounds");
+        }
+    }
+
+}