system6.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experiments 6:\n",
    "### generating byte frequency distributions derived from file last blocks to train and evaluate our models - FFNN, CNN, GRU, LSTM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from toolkit.utils import get_file_types, get_last_block_bytes, convert_cat2num, byte_frequency_histogram\n",
    "from toolkit.models import Ffnn, Ffnn2, Cnn, Cnn2, Lstm, Gru\n",
    "from toolkit.metrics import evaluate_performance, plot_confusion_matrix\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import confusion_matrix, classification_report"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Data Preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dir_path = 'govdocs1/'\n",
    "files_data = get_file_types(dir_path)\n",
    "df = pd.DataFrame(files_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The average file size is: 519.8767892054933\n"
     ]
    }
   ],
   "source": [
    "df['size KB'] = df['file'].apply(\n",
    "    lambda x: float(os.path.getsize(\n",
    "        os.path.join(os.getcwd(), f\"govdocs1/{x}\")\n",
    "    ) / 1024.0) if os.path.isfile(\n",
    "        os.path.join(os.getcwd(), f\"govdocs1/{x}\")\n",
    "    ) else None\n",
    ")\n",
    "\n",
    "print(f\"The average file size is: {df['size KB'].mean()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "CLASS_NAMES = [\n",
    "    \"doc\",\n",
    "    \"pdf\",\n",
    "    \"ps\",\n",
    "    \"xls\",\n",
    "    \"ppt\",\n",
    "    \"swf\",\n",
    "    \"gif\",\n",
    "    \"jpg\",\n",
    "    \"png\",\n",
    "    \"html\",\n",
    "    \"txt\",\n",
    "    \"xml\"\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['type'].isin(CLASS_NAMES)]\n",
    "df = df[df['size KB'] > 8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\User\\AppData\\Local\\Temp\\ipykernel_28184\\603527055.py:2: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
      "  df = df.groupby('type').apply(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "type\n",
       "doc     2000\n",
       "gif     2000\n",
       "html    2000\n",
       "jpg     2000\n",
       "pdf     2000\n",
       "ppt     2000\n",
       "ps      2000\n",
       "swf     2000\n",
       "txt     2000\n",
       "xls     2000\n",
       "xml     2000\n",
       "png     1650\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.groupby('type').apply(\n",
    "    lambda x: x if x.name == \"png\" else x.sample(n=min(len(x), 2000), random_state=42)\n",
    ").reset_index(drop=True)\n",
    "\n",
    "df[\"type\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_dir = os.path.join(os.getcwd(), \"govdocs1\")\n",
    "df[\"last_block_bytes\"] = df.apply(\n",
    "    lambda row: get_last_block_bytes(\n",
    "        path=os.path.join(base_dir, row[\"file\"]), \n",
    "        file_size_kb=row[\"size KB\"]\n",
    "    ), \n",
    "    axis=1\n",
    ")\n",
    "df[\"byte_bfh\"] = df[\"last_block_bytes\"].apply(\n",
    "    lambda byte_sequence: byte_frequency_histogram(np.array([byte for byte in byte_sequence]))\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "byte lengths of each sequence:\n",
      " 0        256\n",
      "1        256\n",
      "2        256\n",
      "3        256\n",
      "4        256\n",
      "        ... \n",
      "23645    256\n",
      "23646    256\n",
      "23647    256\n",
      "23648    256\n",
      "23649    256\n",
      "Name: byte_bfh, Length: 23650, dtype: int64\n",
      "all byte sequences of the same length: True\n"
     ]
    }
   ],
   "source": [
    "byte_lengths = df[\"byte_bfh\"].apply(len)\n",
    "all_same_length = byte_lengths.nunique() == 1\n",
    "\n",
    "print(\"byte lengths of each sequence:\\n\", byte_lengths)\n",
    "print(\"all byte sequences of the same length:\", all_same_length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"class\"] = df[\"type\"].apply(lambda file_type: convert_cat2num(file_type))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>file</th>\n",
       "      <th>type</th>\n",
       "      <th>size KB</th>\n",
       "      <th>last_block_bytes</th>\n",
       "      <th>byte_bfh</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2173</th>\n",
       "      <td>591957.gif</td>\n",
       "      <td>gif</td>\n",
       "      <td>29.300781</td>\n",
       "      <td>b'U\\x8d\\x9a\\xe3\\xc4\\xbe\\xae0\\xea^\\xcf\\xbd\\t\\xd...</td>\n",
       "      <td>[3, 3, 2, 2, 2, 2, 6, 5, 2, 6, 3, 3, 3, 5, 3, ...</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16098</th>\n",
       "      <td>642777.swf</td>\n",
       "      <td>swf</td>\n",
       "      <td>501.567383</td>\n",
       "      <td>b'\\x07\\x06\\x00@\\x00\\x00\\x00\\xbf\\x06\\x1a\\x00\\x0...</td>\n",
       "      <td>[388, 39, 75, 15, 19, 14, 28, 28, 97, 6, 4, 5,...</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20464</th>\n",
       "      <td>169274.xls</td>\n",
       "      <td>xls</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...</td>\n",
       "      <td>[2542, 7, 6, 2, 1, 4, 1, 1, 2, 1, 1, 1, 1, 1, ...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4286</th>\n",
       "      <td>026680.html</td>\n",
       "      <td>html</td>\n",
       "      <td>27.201172</td>\n",
       "      <td>b'istration\\n&lt;br&gt;&lt;b&gt;Latest Major Action:&lt;/b&gt; 9...</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 22, 0, 0, 0, 0,...</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21295</th>\n",
       "      <td>738351.xls</td>\n",
       "      <td>xls</td>\n",
       "      <td>16.500000</td>\n",
       "      <td>b'R\\x00o\\x00o\\x00t\\x00 \\x00E\\x00n\\x00t\\x00r\\x0...</td>\n",
       "      <td>[382, 5, 5, 1, 0, 3, 0, 0, 1, 0, 0, 0, 0, 0, 1...</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              file  type     size KB  \\\n",
       "2173    591957.gif   gif   29.300781   \n",
       "16098   642777.swf   swf  501.567383   \n",
       "20464   169274.xls   xls   23.000000   \n",
       "4286   026680.html  html   27.201172   \n",
       "21295   738351.xls   xls   16.500000   \n",
       "\n",
       "                                        last_block_bytes  \\\n",
       "2173   b'U\\x8d\\x9a\\xe3\\xc4\\xbe\\xae0\\xea^\\xcf\\xbd\\t\\xd...   \n",
       "16098  b'\\x07\\x06\\x00@\\x00\\x00\\x00\\xbf\\x06\\x1a\\x00\\x0...   \n",
       "20464  b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00...   \n",
       "4286   b'istration\\n<br><b>Latest Major Action:</b> 9...   \n",
       "21295  b'R\\x00o\\x00o\\x00t\\x00 \\x00E\\x00n\\x00t\\x00r\\x0...   \n",
       "\n",
       "                                                byte_bfh  class  \n",
       "2173   [3, 3, 2, 2, 2, 2, 6, 5, 2, 6, 3, 3, 3, 5, 3, ...      7  \n",
       "16098  [388, 39, 75, 15, 19, 14, 28, 28, 97, 6, 4, 5,...      6  \n",
       "20464  [2542, 7, 6, 2, 1, 4, 1, 1, 2, 1, 1, 1, 1, 1, ...      4  \n",
       "4286   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 22, 0, 0, 0, 0,...     10  \n",
       "21295  [382, 5, 5, 1, 0, 3, 0, 0, 1, 0, 0, 0, 0, 0, 1...      4  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(n=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = np.array([x for x in df[\"byte_bfh\"]])\n",
    "y = np.array([y for y in df[\"class\"]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X shape:  (23650, 256)\n",
      "y shape:  (23650,)\n"
     ]
    }
   ],
   "source": [
    "print(\"X shape: \", X.shape)\n",
    "print(\"y shape: \", y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_temp, y_train, y_temp = train_test_split(X, y, test_size=0.3, random_state=42)\n",
    "X_val, X_test, y_val, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X training shape:  (16555, 256)\n",
      "X validation shape:  (3547, 256)\n",
      "X testing shape:  (3548, 256) \n",
      "\n",
      "y training shape:  (16555,)\n",
      "y validation shape:  (3547,)\n",
      "y testing shape:  (3548,)\n"
     ]
    }
   ],
   "source": [
    "print(\"X training shape: \", X_train.shape)\n",
    "print(\"X validation shape: \", X_val.shape)\n",
    "print(\"X testing shape: \", X_test.shape, \"\\n\")\n",
    "print(\"y training shape: \", y_train.shape)\n",
    "print(\"y validation shape: \", y_val.shape)\n",
    "print(\"y testing shape: \", y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Models Training and Evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feed Forward Neural Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### a. Base FFNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ dense (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)       │           <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)       │        <span style=\"color: #00af00; text-decoration-color: #00af00\">32,896</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32768</span>)          │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │       <span style=\"color: #00af00; text-decoration-color: #00af00\">425,997</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ dense (\u001b[38;5;33mDense\u001b[0m)                   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m256\u001b[0m)       │           \u001b[38;5;34m512\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_1 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m128\u001b[0m)       │        \u001b[38;5;34m32,896\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten (\u001b[38;5;33mFlatten\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32768\u001b[0m)          │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_2 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │       \u001b[38;5;34m425,997\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">459,405</span> (1.75 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m459,405\u001b[0m (1.75 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">459,405</span> (1.75 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m459,405\u001b[0m (1.75 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn = Ffnn(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 20ms/step - accuracy: 0.6515 - loss: 1.1267 - val_accuracy: 0.8131 - val_loss: 0.5042\n",
      "Epoch 2/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 19ms/step - accuracy: 0.8411 - loss: 0.4555 - val_accuracy: 0.8469 - val_loss: 0.4247\n",
      "Epoch 3/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 19ms/step - accuracy: 0.8676 - loss: 0.3931 - val_accuracy: 0.8692 - val_loss: 0.3837\n",
      "Epoch 4/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 19ms/step - accuracy: 0.8936 - loss: 0.3130 - val_accuracy: 0.8421 - val_loss: 0.4409\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x217e7060800>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ffnn.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=4,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VHRd/f3/4+Phgy5YtmDRpEgDVkJSdnZ36szg1NRXp6elYt24d1q1bV+Fz1+Z3V58x3JB6EuumTZvg5ORU7v6SD9WSdjNnzlSPBz+pqh8mDa3sX6Bl9ejRA0VFRTh79qz6L3MA6r/Oo6OjkZqaqt4OqP6Cf+GFF9CrVy989913cHZ2hqGhITZs2IBffvml3D4a4iymXr16oU+fPvjiiy8q7AlQKpVwcHBQ93w96ckvnoo8OfmzREWvb9q0adiwYQOmT5+O4OBgWFlZQSKRYNSoUXUyqdzT0xOvvfYa1q1bV+FaTUqlEhKJBAcOHCjXqwSgSgvkGRoaomvXrvjjjz9w8+ZNJCUloWfPnnB0dERRURH+/vtvnDp1Cj4+PlU6fpWp7P1hZGSEwYMHY/fu3Th48GCdrVtUnd/jTz/9FPPmzcPrr7+OJUuWwNbWFlKpFNOnT6/w37Gy11LRv0F1VPZ4oZI5StXl4+ODiIgIxMXFwc3N7antK/ojBlD9jlRUa2XHZeTIkfjkk0+QlpYGCwsL7NmzB6NHjy73mfvaa6+Vm5tTokOHDk+ttyliuCG0atUKAODg4ID+/ftX2s7T0xOA6kNfWzsAcHd3V/cIlRUTE1OLSjWfv+T5nuxxiomJUd//NF26dIFcLsepU6dw6tQp/N///R8AVVj44YcfcOzYMfXPJXbs2AFjY2McOnRIY5hgw4YN1aq/ro/PwoUL0adPH3z//ffl7mvVqhWOHj2K7t27PzVs2djYaJwNBACFhYWVDgFVZPv27Rg/fjy+/vpr9bb8/Pxyz1sbc+fOxc8//1zhKbqtWrWCIAho2bIl2rRpo/V5KvuiAlQh9/PPP8fRo0dhZ2cHHx8fSCQStG3bVv2eKRs6yr4vnxQdHQ07O7sqn+otkUiwefNmDBs2DK+88goOHDigcSZOTVXn93j79u3o27cv1q9fr7E9PT29XpZoqCl3d3colUrcuXNHo7fu5s2bVXr80KFD8b///Q8///wzZs+e/dT2Ff2OAKqeu5LjWxUjR47EokWLsGPHDjg6OiIzMxOjRo1S329vbw8LCwsoFIqn/luRJs65IYSEhMDS0hKffvopioqKyt2fmpoKQBV+Sr48K/qiK2kHAIMHD8Zff/2Fc+fOadxfWc9BdXXq1AkODg5Yu3atxrDQgQMHEBUVVeWzJIyNjdG5c2f873//w7179zR6bvLy8vDtt9+iVatWcHZ2Vj9GJpNBIpFo9GTcvXsXYWFhVa6/Po5P79690adPH3z++efIz8/XuG/EiBFQKBRYsmRJuccVFxdrfFC3atVK4ywhAFi3bl2lPTcVkclk5f6qXrlyZbWe42latWqF1157Dd9//z2SkpI07nvxxRchk8mwaNGicnUIgoAHDx6ofzYzM6t0qKxnz54oKCjA8uXL0aNHD3UQ6tmzJzZt2oSEhASNXj1nZ2cEBATgp59+0jimV65cweHDhzF48OBqvUa5XI6dO3eic+fOGDp0qMb7paaq83tc0b/jtm3bKlwlWkwlPVDfffedxvaqLvb48ssvo3379vjkk0/Uc+3KysrKwpw5c9Q/t2rVCn/99RcKCwvV2/bu3auxzEBV+Pr6on379tiyZQu2bNkCZ2dnjT+kZDIZXnrpJezYsQNXrlwp9/iy/1akiT03BEtLS6xZswZjx45Fx44dMWrUKNjb2+PevXvYt28funfvjlWrVgFQTUru0aMH2rdvjzfffBOenp5ITk7G2bNncf/+ffX6Fx9++CE2bdqEgQMH4v3331ef6uzu7o5Lly7VumZDQ0N8/vnnmDhxInr37o3Ro0erTwX38PCocN5JZXr27InPPvsMVlZWaN++PQDVF4C3tzdiYmLKrWcxZMgQLFu2DAMHDsSrr76KlJQUrF69Gq1bt67ya6uv47NgwQL07du33PbevXvj7bffxtKlSxEZGYnnnnsOhoaGuHHjBrZt24YVK1bg5ZdfBgC88cYbeOedd/DSSy9hwIABuHjxIg4dOlStv9Sff/55bNq0CVZWVvDz88PZs2dx9OjRCudp1MacOXOwadMmxMTEoG3bturtrVq1wscff4zZs2fj7t27CA0NhYWFBe7cuYNdu3bhrbfewsyZMwEAQUFB2LJlC2bMmIHOnTvD3NwcQ4cOBQAEBwfDwMAAMTExeOutt9TP36tXL/XaQmXDDQB8+eWXGDRoEIKDgzFp0iT1qeBWVlY1um6SiYkJ9u7di379+mHQoEE4efJklVYWX7ZsWblT7qVSKf79739X+ff4+eefx+LFizFx4kR069YNly9fxubNm6vVO9EQgoKC8NJLL2H58uV48OCB+lTwkhWFtfXOAarPk507d6J///7o1asXRowYge7du8PQ0BBXr17FL7/8AhsbG/VaN2+88Qa2b9+OgQMHYsSIEbh16xZ+/vlndS94dYwcORLz58+HsbExJk2aVG74/LPPPsPx48fRtWtXvPnmm/Dz88PDhw8RHh6Oo0ePllsugx4T5RwtalBlT6PV5vjx40JISIhgZWUlGBsbC61atRImTJggnD9/XqPdrVu3hHHjxglOTk6CoaGh4OrqKjz//PPC9u3bNdpdunRJ6N27t2BsbCy4uroKS5YsEdavX1/tU5212bJlixAYGCgYGRkJtra2wpgxY4T79+9rtCl7Wm1F9u3bJwAQBg0apLH9jTfeEAAI69evL/eY9evXC15eXoKRkZHg4+MjbNiwQV1zWQCEKVOmVLjf+jo+vXv3FgBonApeYt26dUJQUJBgYmIiWFhYCO3btxc+/PBDISEhQd1GoVAIH330kWBnZyeYmpoKISEhws2bNys9Fbyi99WjR4+EiRMnCnZ2doK5ubkQEhIiREdHl3uOmpwK/qSSU43LngpeYseOHUKPHj0EMzMzwczMTPDx8RGmTJkixMTEqNtkZ2cLr776qmBtba2x3ECJzp07lztt//79+wIAwc3NrcJ6jx49KnTv3l0wMTERLC0thaFDhwrXrl3TaKPt37Ci92xaWprg5+cnODk5CTdu3Khwv2Wft6KbTCZTt6vK73F+fr7wr3/9S3B2dhZMTEyE7t27C2fPnq30lOdt27ZV6bWUrbMsVHIq+JPHqOT9UPb3JCcnR5gyZYpga2srmJubC6GhoUJMTIwAQPjss88qPV5lPXr0SJg/f77Qvn17wdTUVDA2NhbatWsnzJ49W0hMTNRo+/XXXwuurq6CkZGR0L17d+H8+fPVOi4lbty4of73OX36dIVtkpOThSlTpghubm6CoaGh4OTkJDz77LPCunXrqvS6miKJINTRjCwiIiIdEhkZicDAQPz88881WmaBGi/OuSEiokavojWeli9fDqlUqjGPhZoGzrkhIqJG74svvsCFCxfQt29fGBgY4MCBAzhw4ADeeuutKp3eTfqFw1JERNToHTlyBIsWLcK1a9eQnZ2NFi1aYOzYsZgzZ06dLYBIjQfDDREREekVzrkhIiIivcJwQ0RERHqlyQ1EKpVKJCQkwMLC4qkLOxEREZFuEAQBWVlZcHFxqfBagWU1uXCTkJDAmfNERESNVFxcHJo3b661TZMLNxYWFgBUB8fS0lLkaoiIiKgqMjMz4ebmpv4e16bJhZuSoShLS0uGGyIiokamKlNKOKGYiIiI9ArDDREREekVhhsiIiLSK01uzg0REekPpVKJwsJCscugOiKXy596mndVMNwQEVGjVFhYiDt37kCpVIpdCtURqVSKli1bQi6X1+p5GG6IiKjREQQBiYmJkMlkcHNzq5O/9klcJYvsJiYmokWLFrVaaJfhhoiIGp3i4mLk5ubCxcUFpqamYpdDdcTe3h4JCQkoLi6GoaFhjZ+HUZeIiBodhUIBALUeviDdUvLvWfLvW1MMN0RE1GjxGoH6pa7+PRluiIiISK8w3BARETVCHh4eWL58eZXbnzhxAhKJBOnp6fVWk67ghGIiIqIG0qdPHwQEBFQrlFTmn3/+gZmZWZXbd+vWDYmJibCysqr1vnUdw00din2QgyKFEq0dnn7FUiIioicJggCFQgEDg6d/Pdvb21frueVyOZycnGpaWqPCYak6cvBKIgZ88wdmbrsEpVIQuxwiItIxEyZMwMmTJ7FixQpIJBJIJBJs3LgREokEBw4cQFBQEIyMjHD69GncunULw4YNg6OjI8zNzdG5c2ccPXpU4/meHJaSSCT4z3/+g+HDh8PU1BReXl7Ys2eP+v4nh6U2btwIa2trHDp0CL6+vjA3N8fAgQORmJiofkxxcTHee+89WFtbo1mzZvjoo48wfvx4hIaG1uehqjWGmzoS4GYDQ6kEkXHp2Ho+TuxyiIiaFEEQkFtYLMpNEKr2B+2KFSsQHByMN998E4mJiUhMTISbmxsAYNasWfjss88QFRWFDh06IDs7G4MHD8axY8cQERGBgQMHYujQobh3757WfSxatAgjRozApUuXMHjwYIwZMwYPHz6stH1ubi6++uorbNq0CX/88Qfu3buHmTNnqu///PPPsXnzZmzYsAFnzpxBZmYmwsLCqvR6xcRhqTriZGWMDwa0wcf7ovDZwWg819YJtmZcf4GIqCHkFSngN/+QKPu+tjgEpvKnf51aWVlBLpfD1NRUPTwUHR0NAFi8eDEGDBigbmtrawt/f3/1z0uWLMGuXbuwZ88eTJ06tdJ9TJgwAaNHjwYAfPrpp/j2229x7tw5DBw4sML2RUVFWLt2LVq1agUAmDp1KhYvXqy+f+XKlZg9ezaGDx8OAFi1ahX279//1NcqNvbc1KEJ3Tzg42SB9NwifH4gWuxyiIiokejUqZPGz9nZ2Zg5cyZ8fX1hbW0Nc3NzREVFPbXnpkOHDur/NzMzg6WlJVJSUiptb2pqqg42AODs7Kxun5GRgeTkZHTp0kV9v0wmQ1BQULVemxjYc1OHDGRSfBzaDi+vPYst5+MworMbgtxtxC6LiEjvmRjKcG1xiGj7rq0nz3qaOXMmjhw5gq+++gqtW7eGiYkJXn755adeAf3JSxZIJBKtFxatqH1Vh9l0GcNNHevkYYtXgppj24X7mBt2Bb9N7Q4DGTvIiIjqk0QiqdLQkNjkcnmVLi1w5swZTJgwQT0clJ2djbt379ZzdZqsrKzg6OiIf/75B7169QKguixCeHg4AgICGrSW6uK3bj2YNcgHViaGiErMxKa/YsUuh4iIdISHhwf+/vtv3L17F2lpaZX2qnh5eWHnzp2IjIzExYsX8eqrr2rtgakv06ZNw9KlS7F7927ExMTg/fffx6NHj3T+shcMN/WgmbkRPhzoDQD4+vB1pGTmi1wRERHpgpkzZ0Imk8HPzw/29vaVzqFZtmwZbGxs0K1bNwwdOhQhISHo2LFjA1cLfPTRRxg9ejTGjRuH4OBgmJubIyQkBMbGxg1eS3VIBH0YXKuGzMxMWFlZISMjA5aWlvW2H4VSwItr/sTFuHS84O+Cb0cH1tu+iIiamvz8fNy5cwctW7bU+S9afaJUKuHr64sRI0ZgyZIldf782v5dq/P9zZ6beiKTSvDxsHaQSoA9FxPw5800sUsiIiKqltjYWPzwww+4fv06Ll++jHfffRd37tzBq6++KnZpWjHc1KP2za3w2jPuAIC5u6+gsLjhx0uJiIhqSiqVYuPGjejcuTO6d++Oy5cv4+jRo/D19RW7NK10f2p5I/ev57yx/3Iibqfm4IdTtzGlb2uxSyIiIqoSNzc3nDlzRuwyqo09N/XMysQQc4aoEu7K32/g/qNckSsiIiLSbww3DSA0wBVdW9oiv0iJRb9dE7scIiIivcZw0wAkEgmWhLaDgVSCI9eScSwqWeySiIiI9BbDTQNp42iBST1bAgAW7LmKvMKnr1BJRERE1cdw04De6+cFZytj3H+Uh+9O3BS7HCIiIr3EcNOAzIwMsGCoHwDg+5O3cTs1W+SKiIiI9A/DTQMLaeuEPt72KFQoMX/3Vb24+ioRETUMDw8PLF++XP2zRCJBWFhYpe3v3r0LiUSCyMjIWu23rp6noTDcNDCJRIJFL7SF3ECK0zfTsO9yotglERFRI5WYmIhBgwbV6XNOmDABoaGhGtvc3NyQmJiIdu3a1em+6gvDjQjcm5lhcp9WAIAle68hu6BY5IqIiKgxcnJygpGRUb3vRyaTwcnJCQYGjWPtX4YbkbzTuxXcm5kiObMAy49cF7scIiKqZ+vWrYOLiwuUSs1L8QwbNgyvv/46bt26hWHDhsHR0RHm5ubo3Lkzjh49qvU5nxyWOnfuHAIDA2FsbIxOnTohIiJCo71CocCkSZPQsmVLmJiYwNvbGytWrFDfv3DhQvz000/YvXs3JBIJJBIJTpw4UeGw1MmTJ9GlSxcYGRnB2dkZs2bNQnFx6R/rffr0wXvvvYcPP/wQtra2cHJywsKFC6t/4GqA4UYkxoYyLHqhLQBgw593EZWYKXJFRESNmCAAhTni3Ko4d/KVV17BgwcPcPz4cfW2hw8f4uDBgxgzZgyys7MxePBgHDt2DBERERg4cCCGDh2Ke/fuVen5s7Oz8fzzz8PPzw8XLlzAwoULMXPmTI02SqUSzZs3x7Zt23Dt2jXMnz8f//73v7F161YAwMyZMzFixAgMHDgQiYmJSExMRLdu3crtKz4+HoMHD0bnzp1x8eJFrFmzBuvXr8fHH3+s0e6nn36CmZkZ/v77b3zxxRdYvHgxjhw5UqXXUxuNo39JT/XxdsCgdk44cCUJ88KuYOvbwZBKJWKXRUTU+BTlAp+6iLPvfycAcrOnNrOxscGgQYPwyy+/4NlnnwUAbN++HXZ2dujbty+kUin8/f3V7ZcsWYJdu3Zhz549mDp16lOf/5dffoFSqcT69ethbGyMtm3b4v79+3j33XfVbQwNDbFo0SL1zy1btsTZs2exdetWjBgxAubm5jAxMUFBQQGcnJwq3dd3330HNzc3rFq1ChKJBD4+PkhISMBHH32E+fPnQypV9Z106NABCxYsAAB4eXlh1apVOHbsGAYMGPDU11Mb7LkR2bzn/WAql+F87CPsCL8vdjlERFSPxowZgx07dqCgoAAAsHnzZowaNQpSqRTZ2dmYOXMmfH19YW1tDXNzc0RFRVW55yYqKgodOnSAsbGxeltwcHC5dqtXr0ZQUBDs7e1hbm6OdevWVXkfZfcVHBwMiaT0D/Lu3bsjOzsb9++Xfpd16NBB43HOzs5ISUmp1r5qgj03InOxNsH7z3ph6YFoLD0QjQF+jrA2lYtdFhFR42JoqupBEWvfVTR06FAIgoB9+/ahc+fOOHXqFL755hsAqiGhI0eO4KuvvkLr1q1hYmKCl19+GYWFhXVW6q+//oqZM2fi66+/RnBwMCwsLPDll1/i77//rrN9lGVoaKjxs0QiKTfnqD4w3OiA13u0xPYL93EjJRtfHIrBp8Pbi10SEVHjIpFUaWhIbMbGxnjxxRexefNm3Lx5E97e3ujYsSMA4MyZM5gwYQKGDx8OQDWH5u7du1V+bl9fX2zatAn5+fnq3pu//vpLo82ZM2fQrVs3TJ48Wb3t1q1bGm3kcjkUCu2XCPL19cWOHTsgCIK69+bMmTOwsLBA8+bNq1xzfeGwlA4wlEmxJFS1dsD/zt1DZFy6uAUREVG9GTNmDPbt24cff/wRY8aMUW/38vLCzp07ERkZiYsXL+LVV1+tVi/Hq6++ColEgjfffBPXrl3D/v378dVXX2m08fLywvnz53Ho0CFcv34d8+bNwz///KPRxsPDA5cuXUJMTAzS0tJQVFRUbl+TJ09GXFwcpk2bhujoaOzevRsLFizAjBkz1PNtxCR+BQQAeMazGV4MdIUgAHPDLkOh5MrFRET6qF+/frC1tUVMTAxeffVV9fZly5bBxsYG3bp1w9ChQxESEqLu1akKc3Nz/Pbbb7h8+TICAwMxZ84cfP755xpt3n77bbz44osYOXIkunbtigcPHmj04gDAm2++CW9vb3Tq1An29vY4c+ZMuX25urpi//79OHfuHPz9/fHOO+9g0qRJmDt3bjWPRv2QCE1s/f/MzExYWVkhIyMDlpaWYpejITWrAP2+PoGs/GIsHtYW44I9xC6JiEgn5efn486dO2jZsqXGBFpq3LT9u1bn+5s9NzrE3sII/xfiDQD48lAMUrMKRK6IiIio8WG40TFjurqjnaslsvKLsXR/lNjlEBERNToMNzpGJpXg49D2kEiAnRHx+Ov2A7FLIiIialQYbnRQgJs1RndpAQCYF3YFRYr6XxOAiIhIXzDc6KgPQ7xhaybHjZRs/Hj6jtjlEBHppCZ2Tozeq6t/T4YbHWVtKsfsQT4AgOVHbyAhPU/kioiIdIdMJgOAOl29l8RX8u9Z8u9bU1yhWIe91LE5tvwTh/Oxj7Bk7zWseS1I7JKIiHSCgYEBTE1NkZqaCkNDQ51YOI5qR6lUIjU1FaampjAwqF08YbjRYVKpBEtC2+H5ladx4EoSjsekoK+3g9hlERGJTiKRwNnZGXfu3EFsbKzY5VAdkUqlaNGihcYFOWuC4UbH+TpbYmI3D/zn9B0s3HMVwdObwdiwdt11RET6QC6Xw8vLi0NTekQul9dJLxzDTSMwfUAb/HYpAbEPcrH25C1M799G7JKIiHSCVCrlCsVUDgcpGwFzIwPMe94PAPDdiVuIfZAjckVERES6i+GmkRjS3hk9vexQWKzE/N1XefojERFRJRhuGgmJRIJFL7SFXCbFyeupOHQ1SeySiIiIdBLDTSPiaW+Ot3t7AgAW/XYNOQXFIldERESkexhuGpkpfVvDzdYEiRn5+Pb3G2KXQ0REpHMYbhoZY0MZFg5tCwBYf+oOridniVwRERGRbmG4aYSe9XXEAD9HFCsFzA27wsnFREREZehEuFm9ejU8PDxgbGyMrl274ty5c5W27dOnDyQSSbnbkCFDGrBi8S0Y6gdjQynO3XmIsMh4scshIiLSGaKHmy1btmDGjBlYsGABwsPD4e/vj5CQEKSkpFTYfufOnUhMTFTfrly5AplMhldeeaWBKxdXcxtTTOvnBQD4ZF8UMvKKRK6IiIhIN4gebpYtW4Y333wTEydOhJ+fH9auXQtTU1P8+OOPFba3tbWFk5OT+nbkyBGYmpo2uXADAG/29EQrezOkZRfi68MxYpdDRESkE0QNN4WFhbhw4QL69++v3iaVStG/f3+cPXu2Ss+xfv16jBo1CmZmZhXeX1BQgMzMTI2bvpAbSLFkWDsAwM9/xeLy/QyRKyIiIhKfqOEmLS0NCoUCjo6OGtsdHR2RlPT0RerOnTuHK1eu4I033qi0zdKlS2FlZaW+ubm51bpuXdKttR1e8HeBUgDmhl2GQsnJxURE1LSJPixVG+vXr0f79u3RpUuXStvMnj0bGRkZ6ltcXFwDVtgw5g7xhbmRAS7ez8Cv/9wTuxwiIiJRiRpu7OzsIJPJkJycrLE9OTkZTk5OWh+bk5ODX3/9FZMmTdLazsjICJaWlho3feNgaYx/Pae6UvgXB2PwILtA5IqIiIjEI2q4kcvlCAoKwrFjx9TblEoljh07huDgYK2P3bZtGwoKCvDaa6/Vd5mNwthn3OHnbImMvCJ8diBa7HKIiIhEI/qw1IwZM/DDDz/gp59+QlRUFN59913k5ORg4sSJAIBx48Zh9uzZ5R63fv16hIaGolmzZg1dsk4ykEmxJFQ1uXjbhfs4f/ehyBURERGJw0DsAkaOHInU1FTMnz8fSUlJCAgIwMGDB9WTjO/duwepVDODxcTE4PTp0zh8+LAYJeusIHcbjOzkhi3n4zA37Ar2TusBA5no+ZWIiKhBSYQmtnZ/ZmYmrKyskJGRoZfzbx7mFKLf1yeQnluEuUN88UZPT7FLIiIiqrXqfH/zz3o9Y2smx6yBPgCAb45cR1JGvsgVERERNSyGGz00opMbAltYI6dQgY/3XRO7HCIiogbFcKOHpFIJlgxrB6kE2HspEadupIpdEhERUYNhuNFT7VytMC7YAwAwf/dVFBQrxC2IiIiogTDc6LEZz7WBvYUR7qTl4Ic/botdDhERUYNguNFjlsaGmDvEFwCw8vebiHuYK3JFRERE9Y/hRs+94O+CYM9mKChWYuGeq2KXQ0REVO8YbvScRCLBktC2MJRJcCw6BUeuJT/9QURERI0Yw00T0NrBQr2Y38I9V5FbWCxyRURERPWH4aaJmNavNVytTRCfnodVv98UuxwiIqJ6w3DTRJjKDTB/qB8A4IdTt3EzJVvkioiIiOoHw00T8pyfI/r5OKBIIWD+7itoYpcVIyKiJoLhpgmRSCRYOLQtjAyk+PPWA+y5mCB2SURERHWO4aaJadHMFFP6tgYAfLwvCpn5RSJXREREVLcYbpqgt3p5oqWdGVKzCvDNketil0NERFSnGG6aIGNDGRa90BYA8NOfd3E1IUPkioiIiOoOw00T1auNPYa0d4ZSAOaFXYFSycnFRESkHxhumrB5z/vBTC5D+L10bLsQJ3Y5REREdYLhpglzsjLGBwPaAAA+OxCNRzmFIldERERUeww3Tdz4bh7wdrTAo9wifHEoWuxyiIiIao3hpokzlEnx8fB2AID/nYtD+L1HIldERERUOww3hM4etng5qDkA1eTiYoVS5IqIiIhqjuGGAACzBvnA0tgAVxMy8fNfsWKXQ0REVGMMNwQAsDM3wocDfQAAXx++jpTMfJErIiIiqhmGG1Ib3aUF/JtbIaugGJ/ujxK7HCIiohphuCE1mVSCJaHtIJEAYZEJ+PNWmtglERERVRvDDWno0Nwar3V1B6CaXFxYzMnFRETUuDDcUDkzn/OGnbkct1JzsP70HbHLISIiqhaGGyrHytQQswf5AgC+PXYD9x/lilwRERFR1THcUIVe7OiKLh62yCtSYPFv18Quh4iIqMoYbqhCEolqcrFMKsHha8n4PTpZ7JKIiIiqhOGGKuXtZIFJPVoCABbsuYr8IoXIFRERET0dww1p9f6zXnCyNEbcwzx8d/ym2OUQERE9FcMNaWVmZID5Q/0AAGtP3sadtByRKyIiItKO4YaealA7J/RqY49ChRLzd1+BIAhil0RERFQphht6KolEgsUvtIXcQIpTN9Kw/3KS2CURERFViuGGqsTDzgzv9G4FAFiy9xqyC4pFroiIiKhiDDdUZZP7tEILW1MkZeZjxdHrYpdDRERUIYYbqjJjQxkWDWsLAPjxzF1EJ2WKXBEREVF5DDdULX29HRDS1hEKpYB5YZxcTEREuofhhqpt/tC2MDGU4Z+7j7AjPF7scoiIiDQw3FC1uVqb4P3+XgCApfujkJFbJHJFREREpRhuqEZe794SrR3M8SCnEF8ejha7HCIiIjWGG6oRuYEUS4a1AwBs/vseLsali1sQERHRYww3VGPBrZpheKArBAGYG3YFCiUnFxMRkfgYbqhWZg/2gYWRAS7HZ+CXc/fELoeIiIjhhmrHwcIYM0O8AQBfHIxGalaByBUREVFTx3BDtfbaM+5o62KJrPxiLD0QJXY5RETUxDHcUK3JpBJ8HNoOEgmwMzwef99+IHZJRETUhDHcUJ0IbGGDUZ1bAADm7b6CIoVS5IqIiKipYrihOvNhiDdszeS4npyNjWfuil0OERE1UQw3VGdszOSYNdAHAPDN0etIzMgTuSIiImqKGG6oTr0c1BxB7jbILVRgyd5rYpdDRERNEMMN1Snp48nFMqkE+y8n4eT1VLFLIiKiJobhhuqcr7Mlxgd7AAAW7L6C/CKFuAUREVGTwnBD9eKDAV5wsDDC3Qe5+P7kbbHLISKiJoThhuqFhbEh5j3vBwBYfeImYh/kiFwRERE1FQw3VG+e7+CMHq3tUFisxMI9VyEIvLAmERHVP4YbqjcSiQSLhrWFoUyC4zGpOHQ1WeySiIioCWC4oXrVyt4cb/XyBAAs/u0qcguLRa6IiIj0HcMN1bupfb3gam2ChIx8fHvsptjlEBGRnmO4oXpnIpdh0QttAQD/OXUbN5KzRK6IiIj0GcMNNYj+fo7o7+uAYqWAebuvcHIxERHVG4YbajALhraFsaEUf91+iN2RCWKXQ0REekr0cLN69Wp4eHjA2NgYXbt2xblz57S2T09Px5QpU+Ds7AwjIyO0adMG+/fvb6BqqTbcbE0xrZ8XAODjfVHIyCsSuSIiItJHooabLVu2YMaMGViwYAHCw8Ph7++PkJAQpKSkVNi+sLAQAwYMwN27d7F9+3bExMTghx9+gKurawNXTjX1Rs+W8LQzQ1p2Ab45cl3scoiISA9JBBEnP3Tt2hWdO3fGqlWrAABKpRJubm6YNm0aZs2aVa792rVr8eWXXyI6OhqGhoY12mdmZiasrKyQkZEBS0vLWtVPNXP6RhpeW/83pBJgz9QeaOdqJXZJRESk46rz/S1az01hYSEuXLiA/v37lxYjlaJ///44e/ZshY/Zs2cPgoODMWXKFDg6OqJdu3b49NNPoVBUfmHGgoICZGZmatxIXD287DDU3wVKAZgbdgVKJScXExFR3REt3KSlpUGhUMDR0VFju6OjI5KSkip8zO3bt7F9+3YoFArs378f8+bNw9dff42PP/640v0sXboUVlZW6pubm1udvg6qmblDfGFuZIDIuHRsOR8ndjlERKRHRJ9QXB1KpRIODg5Yt24dgoKCMHLkSMyZMwdr166t9DGzZ89GRkaG+hYXxy9SXeBoaYwPBrQBAHx2IBoPsgtEroiIiPSFaOHGzs4OMpkMycma1xtKTk6Gk5NThY9xdnZGmzZtIJPJ1Nt8fX2RlJSEwsLCCh9jZGQES0tLjRvphvHB7vBxskBGXhE+PxgtdjlERKQnRAs3crkcQUFBOHbsmHqbUqnEsWPHEBwcXOFjunfvjps3b0KpVKq3Xb9+Hc7OzpDL5fVeM9UtA5kUnwxvBwDYev4+LsQ+FLkiIiLSB6IOS82YMQM//PADfvrpJ0RFReHdd99FTk4OJk6cCAAYN24cZs+erW7/7rvv4uHDh3j//fdx/fp17Nu3D59++immTJki1kugWgpyt8WITs0BAHN2XUGxQvmURxAREWlnIObOR44cidTUVMyfPx9JSUkICAjAwYMH1ZOM7927B6m0NH+5ubnh0KFD+OCDD9ChQwe4urri/fffx0cffSTWS6A6MGuQLw5fS0Z0UhZ+OhuLST1ail0SERE1YqKucyMGrnOjm375+x7+vesyzI0McOxfveFoaSx2SUREpEMaxTo3RGWN6uwGfzdrZBcU4+N9UWKXQ0REjRjDDekEqVSCT0LbQSoBfruYgDM308QuiYiIGimGG9IZ7VytMPYZdwDAvN1XUFBc+crTRERElWG4IZ0y4zlv2Jkb4XZqDv5z6o7Y5RARUSPEcEM6xcrEEHOH+AIAVv5+A3EPc0WuiIiIGhuGG9I5wwJc8IynLfKLlFj02zWxyyEiokaG4YZ0jkQiwZJh7WAgleBoVDKOXkt++oOIiIgeY7ghneTlaIE3enoCABb+dhV5hZxcTEREVcNwQzrrvWdbw8XKGPcf5WH18Ztil0NERI0Eww3pLFO5AeYPbQsA+P6PW7iVmi1yRURE1Bgw3JBOC2nriL7e9ihSCFiw+yqa2NVCiIioBhhuSKdJJBIsfKEt5AZSnL6Zhr2XEsUuiYiIdBzDDek892ZmmNKnNQBgyd5ryMovErkiIiLSZQw31Ci83dsTHs1MkZJVgOVHb4hdDhER6TCGG2oUjA1lWDSsHQBg4593cS0hU+SKiIhIVzHcUKPRu409Brd3gkIpYN7uK1AqObmYiIjKY7ihRmXe834wlctwIfYRtoffF7scIiLSQQw31Kg4W5lgen8vAMDS/VF4lFMockVERKRrGG6o0ZnYvSXaOJrjUW4RvjgUI3Y5RESkYxhuqNExlEmx5PHk4l//uYeIe49EroiIiHQJww01Sl09m+HFjq4QBGBu2BUoOLmYiIgeY7ihRmv2IF9YGhvgakImfv4rVuxyiIhIRzDcUKNlb2GE/wvxBgB8dTgGKVn5IldERES6gOGGGrVXu7qjvasVsvKLsXR/tNjlEBGRDqhRuImLi8P9+6VrjJw7dw7Tp0/HunXr6qwwoqqQSSX4OLQdJBJgV0Q8zt56IHZJREQkshqFm1dffRXHjx8HACQlJWHAgAE4d+4c5syZg8WLF9dpgURP4+9mjVe7tAAAzN99BYXFSpErIiIiMdUo3Fy5cgVdunQBAGzduhXt2rXDn3/+ic2bN2Pjxo11WR9RlXwY4oNmZnLcSMnGj2fuiF0OERGJqEbhpqioCEZGRgCAo0eP4oUXXgAA+Pj4IDExse6qI6oiK1NDzB7sCwBYcfQG4tPzRK6IiIjEUqNw07ZtW6xduxanTp3CkSNHMHDgQABAQkICmjVrVqcFElXVSx1d0dnDBnlFCiz57ZrY5RARkUhqFG4+//xzfP/99+jTpw9Gjx4Nf39/AMCePXvUw1VEDU0ikWBJaDvIpBIcvJqE49EpYpdEREQikAiCUKOlXRUKBTIzM2FjY6PedvfuXZiamsLBwaHOCqxrmZmZsLKyQkZGBiwtLcUuh+rBJ/uu4YdTd9DC1hSHP+gFY0OZ2CUREVEtVef7u0Y9N3l5eSgoKFAHm9jYWCxfvhwxMTE6HWyoaXi/fxs4Whrh3sNcrDlxS+xyiIiogdUo3AwbNgz//e9/AQDp6eno2rUrvv76a4SGhmLNmjV1WiBRdZkbGWD+820BAGtO3sKdtByRKyIiooZUo3ATHh6Onj17AgC2b98OR0dHxMbG4r///S++/fbbOi2QqCYGt3dCTy87FBYrsWDPVdRw9JWIiBqhGoWb3NxcWFhYAAAOHz6MF198EVKpFM888wxiY3kBQxKfRCLB4mHtIJdJ8cf1VBy8kiR2SURE1EBqFG5at26NsLAwxMXF4dChQ3juuecAACkpKZykSzqjpZ0Z3untCQBY9Ns1ZBcUi1wRERE1hBqFm/nz52PmzJnw8PBAly5dEBwcDEDVixMYGFinBRLVxuS+reFma4KkzHx8e+yG2OUQEVEDqPGp4ElJSUhMTIS/vz+kUlVGOnfuHCwtLeHj41OnRdYlngre9PwenYzXN56HgVSCfe/1hLeThdglERFRNdX7qeAA4OTkhMDAQCQkJKivEN6lSxedDjbUNPXzccRzfo4oVgqYF3aFk4uJiPRcjcKNUqnE4sWLYWVlBXd3d7i7u8Pa2hpLliyBUskrMpPumT/UDyaGMpy7+xA7w+PFLoeIiOpRjcLNnDlzsGrVKnz22WeIiIhAREQEPv30U6xcuRLz5s2r6xqJaq25jSmmPdsaALD0QBQycotEroiIiOpLjebcuLi4YO3ateqrgZfYvXs3Jk+ejPh43f3LmHNumq7CYiUGrfgDt1JzMPYZdywJbSd2SUREVEX1Pufm4cOHFc6t8fHxwcOHD2vylET1Tm4gVQean/+OxeX7GSJXRERE9aFG4cbf3x+rVq0qt33VqlXo0KFDrYsiqi/dWtlhWIALBAGYG3YZCiUnFxMR6RuDmjzoiy++wJAhQ3D06FH1Gjdnz55FXFwc9u/fX6cFEtW1OYN98XtUCi7ez8D/zt3Da8+4i10SERHVoRr13PTu3RvXr1/H8OHDkZ6ejvT0dLz44ou4evUqNm3aVNc1EtUpB0tjzHiuDQDgy0MxSMsuELkiIiKqSzVexK8iFy9eRMeOHaFQKOrqKescJxQTABQrlHhh1RlcS8zEy0HN8dUr/mKXREREWjTIIn5EjZmBTIqPh6smF2+/cB//3OVEeCIifcFwQ01WxxY2GNXZDQAwd9cVFCm4ACURkT5guKEm7aOBPrAxNURMchZ++vOu2OUQEVEdqNbZUi+++KLW+9PT02tTC1GDszGTY9YgH3y04zK+OXIdz3dwgZOVsdhlERFRLVSr58bKykrrzd3dHePGjauvWonqxStBbujYwho5hQos2XdN7HKIiKiW6vRsqcaAZ0tRRa4mZGDoytNQCsB/X++CXm3sxS6JiIjK4NlSRNXU1sUK47t5AAAW7LmKgmLdXc6AiIi0Y7gheuyDAW1gb2GEO2k5WHfyttjlEBFRDTHcED1maWyIuUN8AQCrjt/EvQe5IldEREQ1wXBDVMYL/i7o1qoZCoqVWPjbVTSxKWlERHqB4YaoDIlEgsXD2sFQJsHv0Sk4ci1Z7JKIiKiaGG6IntDawRxv9vQEACz67RpyC4tFroiIiKqD4YaoAtP6ecHV2gTx6XlY+ftNscshIqJqYLghqoCJXIYFQ/0AAP85dRs3U7JEroiIiKqK4YaoEgP8HPGsjwOKFALmhXFyMRFRY8FwQ1QJiUSChS+0hZGBFGdvP8Ceiwlil0RERFXAcFOXlFzVVt+42Zpiat/WAICP90UhM79I5IqIiOhpdCLcrF69Gh4eHjA2NkbXrl1x7ty5Sttu3LgREolE42ZsrANXcS7IBpZ3APb/H5B0RexqqA691dsTLe3MkJpVgGWHr4tdDhERPYXo4WbLli2YMWMGFixYgPDwcPj7+yMkJAQpKSmVPsbS0hKJiYnqW2xsbANWXInovUDmfeDcOmBtd+CHZ4HwTUBhjtiVUS0ZGciweFhbAMB/z97FlfgMkSsiIiJtRA83y5Ytw5tvvomJEyfCz88Pa9euhampKX788cdKHyORSODk5KS+OTo6NmDFlWg/AnhtJ+A3DJAaAPHngT1Tga+8gb0zgMSLYldItdDTyx5DOjhDKQDzdl+BUsnJxUREukrUcFNYWIgLFy6gf//+6m1SqRT9+/fH2bNnK31cdnY23N3d4ebmhmHDhuHq1auVti0oKEBmZqbGrV5IpUDrZ4ER/wVmRAH9FwI2LYHCLOD8euD7XsC6PsCFjUABTytujOYN8YOZXIaIe+nYej5O7HKIiKgSooabtLQ0KBSKcj0vjo6OSEpKqvAx3t7e+PHHH7F79278/PPPUCqV6NatG+7fv19h+6VLl8LKykp9c3Nzq/PXUY65A9DjA2BaODBuD9D2RUBqCCREAL+9D3ztA+x5D4gPB3h6caPhZGWMDwa0AQB8djAaD3MKRa6IiIgqIvqwVHUFBwdj3LhxCAgIQO/evbFz507Y29vj+++/r7D97NmzkZGRob7FxTXgX9xSKeDZG3hlA/CvaGDAEqBZa6AwGwj/Cfihr6pH55//APmcx9EYTOjmAR8nC6TnFuGLg9Fil0NERBUQNdzY2dlBJpMhOVnz4oTJyclwcnKq0nMYGhoiMDAQN29WvES+kZERLC0tNW6iMLMDur8HTD0PTNgHtH8FkBkBSZeAff9S9ebsngLcP8/eHB1mIJNiSWg7AMCv/8ThQuwjkSsiIqIniRpu5HI5goKCcOzYMfU2pVKJY8eOITg4uErPoVAocPnyZTg7O9dXmXVLIgE8egAv/UfVmxOyFLDzBopygYifgf88C6zpDvy9DshLF7taqkBnD1u8EtQcADA37AqKFUqRKyIiorJEH5aaMWMGfvjhB/z000+IiorCu+++i5ycHEycOBEAMG7cOMyePVvdfvHixTh8+DBu376N8PBwvPbaa4iNjcUbb7wh1kuoOVNbIHgyMOVvYOJBwH80YGAMpFwFDvyfqjdn17vAvb/Ym6NjZg3ygZWJIaISM7HpLx1YioCIiNQMxC5g5MiRSE1Nxfz585GUlISAgAAcPHhQPcn43r17kEpLM9ijR4/w5ptvIikpCTY2NggKCsKff/4JPz8/sV5C7UkkgHuw6jZwKXBpq+qsqpRrwMVfVDd7HyBoAtBhpCoUkaiamRvhw4HemLPrCr4+fB1D2jvDwVIHFpMkIiJIhCZ2NcDMzExYWVkhIyNDvPk3VSEIqvk3FzYCV3YAxXmq7TIj1Vo6QRMA926qYESiUCgFvLjmT1yMS8ewABesGBUodklERHqrOt/fDDeNQX4GcHkbcH4jkHy5dHszLyBoPOD/KmDWTLTymrLL9zPwwurTEATglze6oltrO7FLIiLSSww3WjTKcFNCEICEcFVvzuUdQNHjSzvI5IDvUFVvjkdP9uY0sPm7r+C/Z2PRyt4MB97vBbmB6FPZiIj0DsONFo063JRVkAVc3q4KOomRpdttPYGO44GAMYC5vVjVNSkZeUV49usTSMsuxIcDvTG5T2uxSyIi0jsMN1roTbgpKyFStSjgpW2qyz0Aqutb+QxR9ea07KNaUJDqzc7w+5ix9SKMDaU4OqM3mtuYil0SEZFeYbjRQi/DTYmCbODqTuDCT6oLd5awdlfNzQkYA1hUbXFEqh5BEDBy3V84d+chBvg54odxncQuiYhIrzDcaKHX4aaspMuqkHNpC1Dw+GKhEhngPQgImgi06gtIZeLWqGeuJ2dh8IpTKFYKWD++E5711YGr1RMR6QmGGy2aTLgpUZgLXAtTzc2J+7t0u1ULoONYIPA1wNJFrOr0ztL9Ufj+j9tobmOCIx/0homcAZKIqC4w3GjR5MJNWSlRqt6ci/8D8tNV2yRSoM1A1SRkrwHszamlnIJi9F92EokZ+ZjWrzX+9Zy32CUREekFhhstmnS4KVGUB1zbo+rNufdn6XZLVyDwcW+OtZto5TV2By4n4t3N4ZDLpDg4vSc87c3FLomIqNFjuNGC4eYJqTFA+H+ByF+AvIeqbRIp0Lq/6kwrrxBAJvpVOhoVQRAwYcM/OHk9FT1a22HTpC6QcO0hIqJaYbjRguGmEsUFQNRvqt6cu6dKt1s4q3pyAscCNu6ildfY3E3LwXPL/0BhsRKrXg3E8x04r4mIqDYYbrRguKmCtJuqdXMifwFy0x5vlACt+ql6c7wHATJDMStsFL45ch0rjt2Ao6URjv2rD8yN2ANGRFRTDDdaMNxUQ3EhELNP1Ztz+0TpdjMHIHAM0HGcakVkqlB+kQIhy/9A7INcvNGjJeY+34ivXE9EJDKGGy0Ybmro4W0gfBMQ8TOQk1K63bOP6kwrn+cBA7lo5emq4zEpmLjhH8ikEux7rwd8nPieIyKqCYYbLRhuaklRBMQcUA1b3TwG4PHbx9QOCHhVFXTseG2lst7ZdAEHryahk7sNtr4dDKmUk4uJiKqL4UYLhps69CgWiNik6tHJTird7tFTNTfHdyhgYCRaeboiIT0P/ZedRG6hAl++3AGvdOJp9kRE1cVwowXDTT1QFAM3Dqvm5tw8AghK1XYTW8B/tOq6VvZNezG770/ewtID0bA1k+P3f/WGtSmH8IiIqoPhRguGm3qWcV81Lyf8v0BmfOn2Ft1UvTl+LwCGJqKVJ5YihRKDV5zCjZRsjOnaAp8Mby92SUREjQrDjRYMNw1EqQBuHlX15lw/BAgK1XZjK1VvTsfxgGPTOnvor9sPMGrdX5BIgF2TuyPAzVrskoiIGg2GGy0YbkSQmQBEbFb15mTcK93u1lUVctoOB+Sm4tXXgGZsicTOiHi0c7XE7ik9IOPkYiKiKmG40YLhRkRKBXDrOBC+EYjeX9qbY2QFdBihmpvjpN/DNalZBej39Qlk5RdjybC2GBvsIXZJRESNAsONFgw3OiIrCYh83Jvz6G7pdtcg1dycti8CRvp5wcn/nr2L+buvwsLYAL//qw/sLXhGGRHR0zDcaMFwo2OUSuDOSdXcnOh9gLJItV1uAbR/WRV0XAJELLDuKZQChq0+jSvxmXgx0BXLRgaIXRIRkc5juNGC4UaHZacCF39RBZ2Ht0u3OweoQk77lwEjC5GKq1uRcekY/t0ZCALw61vP4BnPZmKXRESk0xhutGC4aQQEQXVl8gsbVVcqVxSqthuaAe1fetyb0xGQNO7JuP/edRm//H0PXg7m2P9+TxjKpGKXRESksxhutGC4aWRyHgAX/6cKOg9ulG53bK+agNxhhOr08kYoPbcQ/b4+iYc5hZg9yAdv924ldklERDqL4UYLhptGShCAe2dVIedqGKAoUG03MAHavaQKOs07N7renK3n4/Dh9kswlctwdEZvuFg3vQUOiYiqguFGC4YbPZD7ELi0RRV0UqNLtzv4qYasOowATGzEqq5alEoBI74/i/OxjzConRPWvBYkdklERDqJ4UYLhhs9IghA3LnHvTk7geJ81XYDY8AvVBV0Wjyj8705UYmZeH7laSiUAjZO7Iw+3g5il0REpHMYbrRguNFTeenA5W2qoJN8pXS7nbdqyMp/NGBqK1Z1T7Vk7zWsP30H7s1McWh6LxgbysQuiYhIpzDcaMFwo+cEAYgPBy5sAK7sAIpyVdtlcsBvmKo3x727zvXmZOUXof+yk0jOLMD0/l6Y3r+N2CUREekUhhstGG6akPzM0t6cpEul25u1Vl3TKuBVwMxOtPKe9NvFBEz7XwTkBlIc+aAX3JuZiV0SEZHOYLjRguGmiUqIUIWcy9uBwmzVNqkh4DtUNWzl0QuQirvOjCAIGLv+HE7fTEPvNvbYOLEzJDrWw0REJBaGGy0Ybpq4gizVcNWFn4CE8NLtNi1VISdgDGAu3oTe26nZGLj8FAoVSqx9rSMGtnMWrRYiIl3CcKMFww2pJV4Cwn8CLm0FCjJV26QGgPdg1dwcz76i9OZ8dSgGq47fhIuVMY7M6A0zI4MGr4GISNcw3GjBcEPlFOYAV3ephq3u/1O63boF0HEcEPAaYNlwPSh5hQoM+OYk7j/Kw9u9PTF7kG+D7ZuISFcx3GjBcENaJV9VDVld/BUoyFBtk8gA70Gq3pxW/QBp/Z+mfSwqGZN+Og8DqQT73++JNo76ccFQItJzgqA6gUNRDDSv20VJGW60YLihKinMBa7tVg1b3Ttbut3KDQgcCwS+Bli51msJb/x0HkejktG1pS1+fesZTi4mIt2U9wi4dRy4eVR1y05W/SE4dled7obhRguGG6q2lGhVyLn4P9UvMQBIpIDXc6renNYDAFndz4uJe5iLAd+cRH6REt+M9MfwwOZ1vg8iomor6Z25cUQVZuLOAYKi9H5DM6DNc8DLG+p0TTGGGy0YbqjGivKBqN9Uc3NiT5dut3ABOo5V9ehYu9XpLlcfv4kvD8XAysQQE7t7IDTAFR52XP+GiBpYRb0zZdl5A14DVLcWwYCBUZ2XwHCjBcMN1Ym0G6renMhfgNwHjzdKgNb9Vb05bUIAmWGtd1NYrMTw787gakKmeltgC2u8GOiKIR1cYGsmr/U+iIjKqUrvjGdv1Wee1wDVCRj1jOFGC4YbqlPFBUD0XtUk5DsnS7ebOwGBY1RnW9l41GoXeYUKHLyaiF0RCTh9IxXKx7+xBlIJ+njbIzTQFf19HXk9KiKqnbx04PZx4EZJ70yS5v0lvTOt+wPu3eqld0YbhhstGG6o3jy4BYT/F4jcDOSkPt4oAVr1VV3uwXswYFC7npaUrHzsiUxAWGQ8rsSX9uZYGBlgUHsnhAa64pmWzSCVcvIxET2FIABJl4EbhyvpnTEFWvYGvPqr5hbauItXKxhutGK4oXpXXAhcP6Cam3Pr99LtZvaqFZA7jgOatar1bm4kZyEsMh5hEQmIT89Tb3e2MsYLAS54MbA5vJ14CjkRlaHjvTPaMNxowXBDDerhHSBiExDxs+YEvJa9VHNzfJ6v9YeHUingn7sPERYZj72XEpGVX6y+z9fZEsMDXfCCvyucrIxrtR8iaoRKemduHlEFmri/dbp3RhuGGy0YbkgUiiLg+iFVb87NowAe/9qZNlNdnbzjBMCuda13k1+kwImYFOwMj8fxmBQUKVT7kUiA7q3sEBroioHtnGDOSzoQ6a+8dOD2idJAU653po0qyHj1B9y761TvjDYMN1ow3JDo0u+penLCNwFZCaXb3XuoenN8hwKGte9lSc8txL7LiQiLiMc/dx+ptxsbSjHAzwnDA13Q08sehjJxr4ZORLVUpd6ZXqXDTbU8yUEsDDdaMNyQzlAUqz6MLmxUTegTlKrtJjaA/2jVJGQHnzrZVdzDXIRFxGNXRDxup+Wotzczk2OovwtCA13h39yKqyATNRb5GY/XnTkC3DwGZCVq3l+2d6ZFtzr5g0lsDDdaMNyQTsqIf9yb818g837p9hbBqpDTNhQwNKn1bgRBwOX4DOyKiMdvFxOQll2ovs/Tzgyhga4IDXBFi2amtd4XEdUhQQCSr5SuO3Pvr4p7Z0rWnWmkvTPaMNxowXBDOk2pUJ1hdWEjEHOg9MPLwBhwag+4BAIuHVX/tfOq1UU8ixVKnLqZhrCIeBy6moT8IqX6viB3G4QGuuL59s6w4UKBROJ4Wu9MM68yqwLrR++MNgw3WjDcUKORmahaMyf8J9U8nSfJzQFn/8eB5/HN1rNG13LJLijG4atJ2BURjzM309QLBRrKJOjj7YDhga7o5+PAhQKJ6tOTvTNxfwPK0rMfm0LvjDYMN1ow3FCjIwjAw9tAQoTqFh8OJF4EinLKtzW20uzdce0IWLpWK/AkZ+bjt4sJ2BURr3HZBwtjAwxp74zQQFd08bDlQoFEdSE/Q3Vm042S3pkEzftLemdaPz6zSc97Z7RhuNGC4Yb0glIBpF0vDTsJEaqzJRQF5dua2WuGHZdAwNyhSru5npyFXRHx2B0Rj4SMfPV2FytjDAt0xfBAV7Rx5EKBRFUmCEDy1cdnNh0p3ztjYKJ5ZpNtS/Fq1TEMN1ow3JDeKi4EUqNKw05COJASpfnBWcLStXQoy7Uj4BwAmNpW+tRKpYBzdx8iLCIe+y5rLhTo52yJFzu64gV/FzhYNt2/Kokq9dTemdaA13PsnXkKhhstGG6oSSnKU/2VWDbwpMZAvYhgWTYtNXt3nP0Bo/K9MvlFCvwenYJdEfE4UWahQKkE6N7aDsMDXRHS1glmXCiQmiqN3pmjQNxf7J2pAww3WjDcUJNXkK2as1MSdhIiVHN6ypGo1sooCTsuHQGndhqnpD/KKcTexwsFXogtXSjQxFCG59o6IjTQFT1b28GACwWSvsvP1FwVuKLeGfWqwD3YO1MDDDdaMNwQVSDvEZAQWSbwRAIZceXbSWSAgx/gGlgaeBz8AAM5Yh/kYHekaiLynTILBdqZqxYKHB7oivauXCiQ9ESVemd6lg43sXem1hhutGC4Iaqi7JTHgSe8dOJyTkr5djIjVY/O47AjuATgYr4Twi4m4beLCXiQU2ahQHszDA9wRWigK9xsuVAgNTLV6p3pXicLb1IphhstGG6IakgQgMwEzbCTEAHkp5dva2gKOPtD4RyAaElr7Eh2wC83ZCgzDxmdPVQLBQ5p7wxrUy4USDpIEICUa2VWBT5bce9MSaCx9RSv1iaA4UYLhhuiOiQIwKM7ZcJOJJAYCRRml29qZIlUC1/8XeCBAw+dcFHhiXjYQS6Toa+PPYYHuqKvjwOMDLhQIIkoPxO4c1J1vbebx4DMeM37bVuVrgrM3pkGxXCjBcMNUT1TKoEHN55Yg+cSUJxfrmm6xAoRxR64JHjistITt+Vt0LWDH0IDXNGZCwVSQ3hq74wx4PF47gx7Z0TFcKMFww2RCBRFQGq05inpyVcrXIMnSbDBJaUn7hp5w8arK4KC+8GzRQsRiia9pe6deRxoKuudaT0A8GDvjK5guNGC4YZIRxTlqwLO4zk8QkIEkBoNiaAs1zRJ6ohcuw5w8AmGecvOqkUHjfn7S1UkCKoFLUtWBa60d+bxujPNWolXK1WK4UYLhhsiHVaQDSRdRtH9C0iJPgtZUiSciu5X2FRp2xrS5kGlKy07dQDkPAOLHivIKrMqcEW9M56PT9Nm70xj0ejCzerVq/Hll18iKSkJ/v7+WLlyJbp06fLUx/36668YPXo0hg0bhrCwsCrti+GGqHF59CAV58/+jqSos7DNvAp/6W00l6SVbyiRAva+mmvwOLYFDIwavmhqeOV6Z/4ClEWl97N3ptFrVOFmy5YtGDduHNauXYuuXbti+fLl2LZtG2JiYuDgUPnF/e7evYsePXrA09MTtra2DDdETcDdtByERcbjePg12KRfRXvJbXSQ3kag7DbskF7+AVLDMmvwPA489j6AjJeG0AsFWcDtk6XrzmQ+0ctn6/n4NO0BgEcP9s40co0q3HTt2hWdO3fGqlWrAABKpRJubm6YNm0aZs2aVeFjFAoFevXqhddffx2nTp1Ceno6ww1REyIIAiLj0rErIh6/XUzAo9wiOOIhOkhvo4/5ffQwi0PzvGjI8h+Vf7CBCeDcoTTsuASqFl+T8hIROk8QVBPTbxzW0jvTo3RVYPbO6JXqfH+L+udLYWEhLly4gNmzZ6u3SaVS9O/fH2fPnq30cYsXL4aDgwMmTZqEU6dONUSpRKRDJBIJAlvYILCFDeY974c/rqdiV0Q8jlyzw5HMTkAmAAgY0rwIo93S0NnwLoxSLqrW4SnMAuL+Vt1KyC0AlwDNK6VbuwO8VIT4ntY7Y9Py8Wna7J2hUqKGm7S0NCgUCjg6Ompsd3R0RHR0dIWPOX36NNavX4/IyMgq7aOgoAAFBQXqnzMzM2tcLxHpHkOZFM/6OuJZX0dk5hfh4JUkhEXE4+ztB9h3X459910glzVHP58XETrUGf0cMiFPKnPh0MRLqsBz95TqVsLEtsxw1uPAY+HMwFPf1L0zR1SBJvZsxb0zJcNN7J2hCjSqgeesrCyMHTsWP/zwA+zs7Kr0mKVLl2LRokX1XBkR6QJLY0OM6OSGEZ3ckJiRhz2PL+QZnZSFg1eTcPBqEqxMDDGkgx+GBw5Ap4E2kCgVqi/TsldJT7oC5D0Ebh1T3UqYO5YOZZVcLd2sap9FpEVBtua6M09etNWmZZl1Z3rwrDh6KlHn3BQWFsLU1BTbt29HaGioevv48eORnp6O3bt3a7SPjIxEYGAgZLLS5dmVStWaGFKpFDExMWjVSjPFV9Rz4+bmxjk3RE1IVGImwiLiERYZj+TM0s+D5jYmGB7oimEBrmjtYF76gOKCx2vwlLlKekoUICjKP7lVC9WQVknYcQ4ATKzr+RU1ck/rnZEZlc6dYe8MPdboJhR36dIFK1euBKAKKy1atMDUqVPLTSjOz8/HzZs3NbbNnTsXWVlZWLFiBdq0aQO5XPsF+DihmKjpUigF/HX7AXZFxOPglSRkF5Qu5NahuRVCA1wx1N8F9hYVnD5emAskXda8cOiDGxXvyLaVZu+Osz8gN6unV9VIPLV3xqPMujPsnaHyGlW42bJlC8aPH4/vv/8eXbp0wfLly7F161ZER0fD0dER48aNg6urK5YuXVrh4ydMmMCzpYio2vIKFTgalYxdEfE4eT0VCqXqo1AmlaCnlx2GB7pigJ8jTOVaRu/zM1UXCk2IKA086bHl20mkgJ13adgpWYPH0Lh+XpwuEAQgNebxRODDWnpnHg83NWvF+UykVaM5WwoARo4cidTUVMyfPx9JSUkICAjAwYMH1ZOM7927BylP0SSiOmYil2GovwuG+rvgQXYB9l5KxK6IeETGpeNETCpOxKTCVC7DwLZOGN7RFd1a2UH25IU8jS2Blr1UtxK5D8v07jwOPVkJQGqU6ha5WdVOaqAKOGXX4HHwBWSGDXcQ6hp7Z0hHiN5z09DYc0NE2txJy1HPz4l9kKve7mBhhBf8XRAa6Iq2LpaQVKeXIStJ8yrpCeFA7oPy7QyMAaf2mmvw2HkBUln5trpAo3fm8TWbFIWl97N3hupQoxqWamgMN0RUFYIgIPxeOsIi4vHbpQSk55YOqbRxNEfo44nIrtY1WFdFEFS9GmXDTsJFoCCjfFu5uWrOTtlT0m1aihcSCrKBO3+UrjuTcU/zfhuPMqsC92TvDNUZhhstGG6IqLoKi5U4eT0VYRHxOBKVjMLi0iuXd21pi+GBrhjU3hlWJrUYUlIqgUd3NANP4kWgKLd8W2Pr8mvwWLrWT+ARBCDtuqpn5sbhSnpnupdZd6Y1e2eoXjDcaMFwQ0S1kZlfhIOXk7Az4j7+uv1QvV1uIEV/XweEBriij7cD5AZ1MFdQqVAN+2iswXNZM1yUMLMvvwaPeeXX59Pqab0z1u6aqwI39TPBqEEw3GjBcENEdSU+vWShwPu4npyt3m5taojnOzhjeKArOrawqd78nKcpLgRSrmlOWk65VvEaPJbNy6/BY2pbvl3Z3pmbR4DYP9k7QzqH4UYLhhsiqmuCICAqMQu7Iu5jd2QCUrJKFwpsYWuK0ADVRGRPe3Mtz1ILRXmP1+Apc0p62nUAFXy827TUHMq6e1oVairsnXk8EbhlT/bOkOgYbrRguCGi+qRQCjh7q2ShwETkFJb2qPi7WWN4gAue93eBnXkFCwXWpYIs1ZydsmdpPbpTeXuZHHDvrgo0Xs+xd4Z0DsONFgw3RNRQcguLceRaMsIi4vHHjTSNhQJ7edlheMfmGODrCBN5A53qnftQtehgSdhJvwe4dWHvDDUKDDdaMNwQkRjSsgvw28UEhEXE4+L90lO+zeQyDGynmp8T3KpZ+YUCiQgAw41WDDdEJLZbqdnYHRGPXZHxiHuYp97uaGmEYQGuCA1wha+zRd1ORCZq5BhutGC4ISJdIQgCLsQ+wq6IeOy9lIiMvNKFAr0dLRAa6IrQQBc4W9VgoUAiPcNwowXDDRHposJiJU7EpGBXRDyORaWgUKFaKFAiAZ5p2QzDA10xsL0TLI0b8bWniGqB4UYLhhsi0nUZeUU4cFl1Ic+/75QuFGhkIEV/P0cMD3BFrzb2dbNQIFEjwXCjBcMNETUm9x/lYndkAnZFxONmSulCgTamhni+gwuGd3RFoJs15+eQ3mO40YLhhogaI0EQcDUhE2ER8dh9MQGpZRYKdG9mitAAV4QGuqKlHU/nJv3EcKMFww0RNXbFCiX+vPUAYRHxOHg1CbllFgoMbGGN4YGuGNLeGc3qe6FAogbEcKMFww0R6ZPcwmIcvpqMXRHxOHUjFY/XCYSBVILebewRGuiKAX6OMDZsoIUCieoJw40WDDdEpK9SsvKx92IiwiLjcanMQoHmRgYY1M4JwwNd0dWTCwVS48RwowXDDRE1BTdTshAWoZqIHJ9eulCgk6UxhgW6YHigK3yc+BlIjQfDjRYMN0TUlCiVAi7ce4Sd4fHYdykBmfnF6vt8nCzQrZUdOnnYoJO7DRwsjUWslEg7hhstGG6IqKkqKFbgeHQqwiLi8Xt06UKBJdxsTdDJ3RZB7jbo5GGDNg4WkHIIi3QEw40WDDdEREBGbhFOXE/B+buPcD72EaKTMvHkt4GFsQE6tlD16gR52CDAzRqmcgNxCqYmj+FGC4YbIqLysvKLEHEvHedjH+FC7ENE3EvXOMUcUJ2B5ediqerZcbdFJw8bOHIoixoIw40WDDdERE9XrFAiOikL5+8+fBx4HiExI79cu+Y2Jo97dmzRmUNZVI8YbrRguCEiqpn49DxV2Hk8lBWTlKleV6cEh7KovjDcaMFwQ0RUN6oylCWTStCWQ1lUBxhutGC4ISKqHzUZyurkboM2jhZcWJCeiuFGC4YbIqKGUzKUdSH2Ec7fVZ2VVW4oy8gAge6qoaxO7jYIaMGhLCqP4UYLhhsiIvFk5RchMi4d5++qenYi7j1CTgVDWX7Olur1djq528LJikNZTR3DjRYMN0REuqNkKOtCrGqS8oW7D5FQwVCWq7WJeiXlIHdbeDtxKKupYbjRguGGiEi3JaTnqYPO+dhHiEqseCgroIW1epJygJs1zIw4lKXPGG60YLghImpcsguKEXkvHedjVXN3wmMrHsrydbbQuHyEs5WJSBVTfWC40YLhhoiocVMoBUQnZaonKZ/XMpRVEnSC3G3g42TJoaxGjOFGC4YbIiL9U5WhLHMjAwRyKKvRYrjRguGGiEj/PTmUFXEvHdkFxRptOJTVuDDcaMFwQ0TU9Dw5lHUh9hHi0/PKteNQlu5iuNGC4YaIiAAgMSNPHXTOxz7EtYTKh7JKLh8R0MIa5hzKEgXDjRYMN0REVJGcgmL1AoPnH18r68mhLKkE8HW21Lh8hIs1h7IaAsONFgw3RERUFQqlgJikLFyIVU1SPn+34qEsFytjddAJcreBrzOHsuoDw40WDDdERFRTSRn5OB/7UD2cdS0xE4onxrLM5DIEtrBRz90JbGHDoaw6wHCjBcMNERHVlZyCYlyMS1f17DxeYLCioSwfJ0v1JOVOHrZw5VBWtTHcaMFwQ0RE9aWqQ1nOVsaPJymrwo6PkwUMZFIRKm48GG60YLghIqKGVNWhrIAW1ghyt0VnDmVViOFGC4YbIiIS05NDWRGxj5DFoaynYrjRguGGiIh0iUIp4HpylsblI+4/4lDWkxhutGC4ISIiXZecma9eb+dC7CNcTSg/lGUqlz1eYFB1GnpgC2tYGBuKVHH9Y7jRguGGiIgam9xC1QKDF+4+Pivr3iNk5ZcfyvJ2snzcs6MaznK1NoFEoh9r7jDcaMFwQ0REjZ1SKeB6SpbG5SPiHpYfynKyNEaQx+OhLHdb+Do33qEshhstGG6IiEgfJWfml7kw6ENcqWQoK8DNWn35iMAW1rBsJENZDDdaMNwQEVFTUJWhLIkE8Ha0QCcPVc9OkLsNmtvo5lAWw40WDDdERNQUVXUoy9HSSB10OnvozlAWw40WDDdEREQqKZn56pWUL8Q+xNWETBRrGcrq+PgmxlAWw40WDDdEREQVyytUqIayHl8+4kKs7gxlMdxowXBDRERUNUqlgBsp2ar1dh7P3bn3MLdcu7JDWZ08bODrbAnDOh7KYrjRguGGiIio5lJKzsp6fLsan1FuKMujmSlO/F/fOt1vdb6/eVUuIiIiqjIHS2MMau+MQe2dAaiGsi7eT398GrpqRWU/F3E7DxhuiIiIqMZM5DI849kMz3g2A6AaynryQqANTfxzu4iIiEhvSKUSWJmIuzAgww0RERHpFYYbIiIi0isMN0RERKRXGG6IiIhIrzDcEBERkV5huCEiIiK9wnBDREREekUnws3q1avh4eEBY2NjdO3aFefOnau07c6dO9GpUydYW1vDzMwMAQEB2LRpUwNWS0RERLpM9HCzZcsWzJgxAwsWLEB4eDj8/f0REhKClJSUCtvb2tpizpw5OHv2LC5duoSJEydi4sSJOHToUANXTkRERLpI9Atndu3aFZ07d8aqVasAAEqlEm5ubpg2bRpmzZpVpefo2LEjhgwZgiVLljy1LS+cSURE1PhU5/tb1J6bwsJCXLhwAf3791dvk0ql6N+/P86ePfvUxwuCgGPHjiEmJga9evWqz1KJiIiokRD1wplpaWlQKBRwdHTU2O7o6Ijo6OhKH5eRkQFXV1cUFBRAJpPhu+++w4ABAypsW1BQgIKCAvXPmZmZdVM8ERER6aRGeVVwCwsLREZGIjs7G8eOHcOMGTPg6emJPn36lGu7dOlSLFq0qOGLJCIiIlGIGm7s7Owgk8mQnJyssT05ORlOTk6VPk4qlaJ169YAgICAAERFRWHp0qUVhpvZs2djxowZ6p8zMjLQokUL9uAQERE1IiXf21WZKixquJHL5QgKCsKxY8cQGhoKQDWh+NixY5g6dWqVn0epVGoMPZVlZGQEIyMj9c8lB8fNza3mhRMREZEosrKyYGVlpbWN6MNSM2bMwPjx49GpUyd06dIFy5cvR05ODiZOnAgAGDduHFxdXbF06VIAqmGmTp06oVWrVigoKMD+/fuxadMmrFmzpkr7c3FxQVxcHCwsLCCRSOr0tWRmZsLNzQ1xcXE8E+speKyqjseq6nisqo7Hqnp4vKquvo6VIAjIysqCi4vLU9uKHm5GjhyJ1NRUzJ8/H0lJSQgICMDBgwfVk4zv3bsHqbT0pK6cnBxMnjwZ9+/fh4mJCXx8fPDzzz9j5MiRVdqfVCpF8+bN6+W1lLC0tOSbv4p4rKqOx6rqeKyqjseqeni8qq4+jtXTemxKiL7OjT7hGjpVx2NVdTxWVcdjVXU8VtXD41V1unCsRF+hmIiIiKguMdzUISMjIyxYsEBjAjNVjMeq6nisqo7Hqup4rKqHx6vqdOFYcViKiIiI9Ap7boiIiEivMNwQERGRXmG4ISIiIr3CcENERER6heGmmlavXg0PDw8YGxuja9euOHfunNb227Ztg4+PD4yNjdG+fXvs37+/gSoVX3WO1caNGyGRSDRuxsbGDViteP744w8MHToULi4ukEgkCAsLe+pjTpw4gY4dO8LIyAitW7fGxo0b671OXVDdY3XixIly7yuJRIKkpKSGKVgkS5cuRefOnWFhYQEHBweEhoYiJibmqY9rqp9XNTleTfUza82aNejQoYN6gb7g4GAcOHBA62PEeF8x3FTDli1bMGPGDCxYsADh4eHw9/dHSEgIUlJSKmz/559/YvTo0Zg0aRIiIiIQGhqK0NBQXLlypYErb3jVPVaAajXLxMRE9S02NrYBKxZPTk4O/P39sXr16iq1v3PnDoYMGYK+ffsiMjIS06dPxxtvvIFDhw7Vc6Xiq+6xKhETE6Px3nJwcKinCnXDyZMnMWXKFPz11184cuQIioqK8NxzzyEnJ6fSxzTlz6uaHC+gaX5mNW/eHJ999hkuXLiA8+fPo1+/fhg2bBiuXr1aYXvR3lcCVVmXLl2EKVOmqH9WKBSCi4uLsHTp0grbjxgxQhgyZIjGtq5duwpvv/12vdapC6p7rDZs2CBYWVk1UHW6C4Cwa9curW0+/PBDoW3bthrbRo4cKYSEhNRjZbqnKsfq+PHjAgDh0aNHDVKTrkpJSREACCdPnqy0TVP+vHpSVY4XP7NK2djYCP/5z38qvE+s9xV7bqqosLAQFy5cQP/+/dXbpFIp+vfvj7Nnz1b4mLNnz2q0B4CQkJBK2+uLmhwrAMjOzoa7uzvc3Ny0/iXQ1DXV91VtBAQEwNnZGQMGDMCZM2fELqfBZWRkAABsbW0rbcP3VamqHC+An1kKhQK//vorcnJyEBwcXGEbsd5XDDdVlJaWBoVCob6gZwlHR8dKx++TkpKq1V5f1ORYeXt748cff8Tu3bvx888/Q6lUolu3brh//35DlNyoVPa+yszMRF5enkhV6SZnZ2esXbsWO3bswI4dO+Dm5oY+ffogPDxc7NIajFKpxPTp09G9e3e0a9eu0nZN9fPqSVU9Xk35M+vy5cswNzeHkZER3nnnHezatQt+fn4VthXrfSX6VcGJACA4OFgj+Xfr1g2+vr74/vvvsWTJEhEro8bM29sb3t7e6p+7deuGW7du4ZtvvsGmTZtErKzhTJkyBVeuXMHp06fFLqVRqOrxasqfWd7e3oiMjERGRga2b9+O8ePH4+TJk5UGHDGw56aK7OzsIJPJkJycrLE9OTkZTk5OFT7GycmpWu31RU2O1ZMMDQ0RGBiImzdv1keJjVpl7ytLS0uYmJiIVFXj0aVLlybzvpo6dSr27t2L48ePo3nz5lrbNtXPq7Kqc7ye1JQ+s+RyOVq3bo2goCAsXboU/v7+WLFiRYVtxXpfMdxUkVwuR1BQEI4dO6beplQqcezYsUrHGoODgzXaA8CRI0cqba8vanKsnqRQKHD58mU4OzvXV5mNVlN9X9WVyMhIvX9fCYKAqVOnYteuXfj999/RsmXLpz6mKb+vanK8ntSUP7OUSiUKCgoqvE+091W9TlfWM7/++qtgZGQkbNy4Ubh27Zrw1ltvCdbW1kJSUpIgCIIwduxYYdasWer2Z86cEQwMDISvvvpKiIqKEhYsWCAYGhoKly9fFuslNJjqHqtFixYJhw4dEm7duiVcuHBBGDVqlGBsbCxcvXpVrJfQYLKysoSIiAghIiJCACAsW7ZMiIiIEGJjYwVBEIRZs2YJY8eOVbe/ffu2YGpqKvzf//2fEBUVJaxevVqQyWTCwYMHxXoJDaa6x+qbb74RwsLChBs3bgiXL18W3n//fUEqlQpHjx4V6yU0iHfffVewsrISTpw4ISQmJqpvubm56jb8vCpVk+PVVD+zZs2aJZw8eVK4c+eOcOnSJWHWrFmCRCIRDh8+LAiC7ryvGG6qaeXKlUKLFi0EuVwudOnSRfjrr7/U9/Xu3VsYP368RvutW7cKbdq0EeRyudC2bVth3759DVyxeKpzrKZPn65u6+joKAwePFgIDw8XoeqGV3K68pO3kuMzfvx4oXfv3uUeExAQIMjlcsHT01PYsGFDg9cthuoeq88//1xo1aqVYGxsLNja2gp9+vQRfv/9d3GKb0AVHSMAGu8Tfl6VqsnxaqqfWa+//rrg7u4uyOVywd7eXnj22WfVwUYQdOd9JREEQajfviEiIiKihsM5N0RERKRXGG6IiIhIrzDcEBERkV5huCEiIiK9wnBDREREeoXhhoiIiPQKww0RERHpFYYbImryJBIJwsLCxC6DiOoIww0RiWrChAmQSCTlbgMHDhS7NCJqpAzELoCIaODAgdiwYYPGNiMjI5GqIaLGjj03RCQ6IyMjODk5adxsbGwAqIaM1qxZg0GDBsHExASenp7Yvn27xuMvX76Mfv36wcTEBM2aNcNbb72F7OxsjTY//vgj2rZtCyMjIzg7O2Pq1Kka96elpWH48OEwNTWFl5cX9uzZU78vmojqDcMNEem8efPm4aWXXsLFixcxZswYjBo1ClFRUQCAnJwchISEwMbGBv/88w+2bduGo0ePaoSXNWvWYMqUKXjrrbdw+fJl7NmzB61bt9bYx6JFizBixAhcunQJgwcPxpgxY/Dw4cMGfZ1EVEfq/dKcRERajB8/XpDJZIKZmZnG7ZNPPhEEQXXF5nfeeUfjMV27dhXeffddQRAEYd26dYKNjY2QnZ2tvn/fvn2CVCoVkpKSBEEQBBcXF2HOnDmV1gBAmDt3rvrn7OxsAYBw4MCBOnudRNRwOOeGiETXt29frFmzRmObra2t+v+Dg4M17gsODkZkZCQAICoqCv7+/jAzM1Pf3717dyiVSsTExEAikSAhIQHPPvus1ho6dOig/n8zMzNYWloiJSWlpi+JiETEcENEojMzMys3TFRXTExMqtTO0NBQ42eJRAKlUlkfJRFRPeOcGyLSeX/99Ve5n319fQEAvr6+uHjxInJyctT3nzlzBlKpFN7e3rCwsICHhweOHTvWoDUTkXjYc0NEoisoKEBSUpLGNgMDA9jZ2QEAtm3bhk6dOqFHjx7YvHkzzp07h/Xr1wMAxowZgwULFmD8+PFYuHAhUlNTMW3aNIwdOxaOjo4AgIULF+Kdd96Bg4MDBg0ahKysLJw5cwbTpk1r2BdKRA2C4YaIRHfw4EE4OztrbPP29kZ0dDQA1ZlMv/76KyZPngxnZ2f873//g5+fHwDA1NQUhw4dwvvvv4/OnTvD1NQUL730EpYtW6Z+rvHjxyM/Px/ffPMNZs6cCTs7O7z88ssN9wKJqEFJBEEQxC6CiKgyEokEu3btQmhoqNilEFEjwTk3REREpFcYboiIiEivcM4NEek0jpwTUXWx54aIiIj0CsMNERER6RWGGyIiItIrDDdERESkVxhuiIiISK8w3BAREZFeYbghIiIivcJwQ0RERHqF4YaIiIj0yv8DZFii86PKX7EAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m111/111\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 8ms/step\n"
     ]
    }
   ],
   "source": [
    "ffnn_pred = ffnn.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feed Forward Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.8480834272829764.\n",
      "precision\t0.8673922771060257.\n",
      "recall\t\t0.8438908078654238.\n",
      "f1-score\t0.8463243082810062.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, ffnn_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{ffnn.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.96      0.91      0.94       280\n",
      "         pdf       0.99      0.99      0.99       335\n",
      "          ps       1.00      0.94      0.97       311\n",
      "         xls       0.87      0.97      0.91       288\n",
      "         ppt       0.99      0.86      0.92       337\n",
      "         swf       0.48      0.83      0.61       283\n",
      "         gif       0.79      0.54      0.64       301\n",
      "         jpg       0.89      0.70      0.78       276\n",
      "         png       0.73      0.66      0.69       260\n",
      "        html       0.85      0.97      0.90       292\n",
      "         txt       0.88      0.99      0.93       301\n",
      "         xml       0.99      0.77      0.87       284\n",
      "\n",
      "    accuracy                           0.85      3548\n",
      "   macro avg       0.87      0.84      0.85      3548\n",
      "weighted avg       0.87      0.85      0.85      3548\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ffnn_report = classification_report(y_test, ffnn_pred, target_names=CLASS_NAMES)\n",
    "print(ffnn_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn_cm = confusion_matrix(y_test, ffnn_pred)\n",
    "plot_confusion_matrix(ffnn_cm, CLASS_NAMES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### b. Fine-tuned FFNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_1\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_1\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ dense_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">352</span>)       │           <span style=\"color: #00af00; text-decoration-color: #00af00\">704</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)        │        <span style=\"color: #00af00; text-decoration-color: #00af00\">11,296</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8192</span>)           │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_5 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │       <span style=\"color: #00af00; text-decoration-color: #00af00\">106,509</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ dense_3 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m352\u001b[0m)       │           \u001b[38;5;34m704\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_4 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m32\u001b[0m)        │        \u001b[38;5;34m11,296\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_1 (\u001b[38;5;33mFlatten\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8192\u001b[0m)           │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_5 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │       \u001b[38;5;34m106,509\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">118,509</span> (462.93 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m118,509\u001b[0m (462.93 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">118,509</span> (462.93 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m118,509\u001b[0m (462.93 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn2 = Ffnn2(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 16ms/step - accuracy: 0.6297 - loss: 1.3120 - val_accuracy: 0.8227 - val_loss: 0.5127\n",
      "Epoch 2/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 16ms/step - accuracy: 0.8345 - loss: 0.4593 - val_accuracy: 0.8472 - val_loss: 0.4413\n",
      "Epoch 3/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 16ms/step - accuracy: 0.8655 - loss: 0.3941 - val_accuracy: 0.8359 - val_loss: 0.4646\n",
      "Epoch 4/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 16ms/step - accuracy: 0.8767 - loss: 0.3500 - val_accuracy: 0.8514 - val_loss: 0.4343\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x217f77d9a00>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ffnn2.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=4,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn2.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m111/111\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 8ms/step\n"
     ]
    }
   ],
   "source": [
    "ffnn2_pred = ffnn2.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feed Forward Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.8644306651634723.\n",
      "precision\t0.8682207101710177.\n",
      "recall\t\t0.8582412850315753.\n",
      "f1-score\t0.8581979298411325.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, ffnn2_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{ffnn2.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.89      0.96      0.92       280\n",
      "         pdf       0.99      0.99      0.99       335\n",
      "          ps       1.00      0.98      0.99       311\n",
      "         xls       0.92      0.93      0.93       288\n",
      "         ppt       0.95      0.89      0.92       337\n",
      "         swf       0.61      0.63      0.62       283\n",
      "         gif       0.60      0.78      0.68       301\n",
      "         jpg       0.78      0.80      0.79       276\n",
      "         png       0.84      0.49      0.62       260\n",
      "        html       0.91      0.96      0.93       292\n",
      "         txt       0.96      0.93      0.95       301\n",
      "         xml       0.97      0.96      0.96       284\n",
      "\n",
      "    accuracy                           0.86      3548\n",
      "   macro avg       0.87      0.86      0.86      3548\n",
      "weighted avg       0.87      0.86      0.86      3548\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ffnn2_report = classification_report(y_test, ffnn2_pred, target_names=CLASS_NAMES)\n",
    "print(ffnn2_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn2_cm = confusion_matrix(y_test, ffnn2_pred)\n",
    "plot_confusion_matrix(ffnn2_cm, CLASS_NAMES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convolutional Neural Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### a. Base CNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_2\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_2\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv1d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">254</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)        │           <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling1D</span>)    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">127</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)        │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv1d_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">125</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)       │        <span style=\"color: #00af00; text-decoration-color: #00af00\">24,704</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling1D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">62</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)        │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">7936</span>)           │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │       <span style=\"color: #00af00; text-decoration-color: #00af00\">103,181</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv1d (\u001b[38;5;33mConv1D\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m254\u001b[0m, \u001b[38;5;34m64\u001b[0m)        │           \u001b[38;5;34m256\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d (\u001b[38;5;33mMaxPooling1D\u001b[0m)    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m127\u001b[0m, \u001b[38;5;34m64\u001b[0m)        │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv1d_1 (\u001b[38;5;33mConv1D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m125\u001b[0m, \u001b[38;5;34m128\u001b[0m)       │        \u001b[38;5;34m24,704\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_1 (\u001b[38;5;33mMaxPooling1D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m62\u001b[0m, \u001b[38;5;34m128\u001b[0m)        │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_2 (\u001b[38;5;33mFlatten\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7936\u001b[0m)           │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_6 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │       \u001b[38;5;34m103,181\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">128,141</span> (500.55 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m128,141\u001b[0m (500.55 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">128,141</span> (500.55 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m128,141\u001b[0m (500.55 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn = Cnn(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 11ms/step - accuracy: 0.6124 - loss: 1.6019 - val_accuracy: 0.7869 - val_loss: 0.6371\n",
      "Epoch 2/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 9ms/step - accuracy: 0.8283 - loss: 0.5126 - val_accuracy: 0.8215 - val_loss: 0.5368\n",
      "Epoch 3/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 10ms/step - accuracy: 0.8558 - loss: 0.4187 - val_accuracy: 0.8385 - val_loss: 0.4734\n",
      "Epoch 4/4\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 11ms/step - accuracy: 0.8905 - loss: 0.3334 - val_accuracy: 0.8497 - val_loss: 0.4479\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x217f794f290>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cnn.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=4,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m111/111\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 6ms/step\n"
     ]
    }
   ],
   "source": [
    "cnn_pred = cnn.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Convolutional Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.8754227733934611.\n",
      "precision\t0.8738413117874467.\n",
      "recall\t\t0.8714395430020092.\n",
      "f1-score\t0.8715057305690518.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, cnn_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{cnn.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.95      0.94      0.95       280\n",
      "         pdf       0.99      0.99      0.99       335\n",
      "          ps       0.99      0.98      0.99       311\n",
      "         xls       0.91      0.94      0.93       288\n",
      "         ppt       0.96      0.92      0.94       337\n",
      "         swf       0.65      0.67      0.66       283\n",
      "         gif       0.78      0.68      0.72       301\n",
      "         jpg       0.82      0.78      0.80       276\n",
      "         png       0.60      0.74      0.66       260\n",
      "        html       0.96      0.90      0.93       292\n",
      "         txt       0.96      0.95      0.96       301\n",
      "         xml       0.90      0.96      0.93       284\n",
      "\n",
      "    accuracy                           0.88      3548\n",
      "   macro avg       0.87      0.87      0.87      3548\n",
      "weighted avg       0.88      0.88      0.88      3548\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cnn_report = classification_report(y_test, cnn_pred, target_names=CLASS_NAMES)\n",
    "print(cnn_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn_cm = confusion_matrix(y_test, cnn_pred)\n",
    "plot_confusion_matrix(cnn_cm, CLASS_NAMES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### b. Fine-tuned CNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_3\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_3\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv1d_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">254</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)        │           <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling1D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">127</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)        │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv1d_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">125</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">192</span>)       │        <span style=\"color: #00af00; text-decoration-color: #00af00\">37,056</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling1D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">62</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">192</span>)        │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">11904</span>)          │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">11904</span>)          │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_7 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)            │     <span style=\"color: #00af00; text-decoration-color: #00af00\">3,047,680</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_8 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">3,341</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv1d_2 (\u001b[38;5;33mConv1D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m254\u001b[0m, \u001b[38;5;34m64\u001b[0m)        │           \u001b[38;5;34m256\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_2 (\u001b[38;5;33mMaxPooling1D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m127\u001b[0m, \u001b[38;5;34m64\u001b[0m)        │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv1d_3 (\u001b[38;5;33mConv1D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m125\u001b[0m, \u001b[38;5;34m192\u001b[0m)       │        \u001b[38;5;34m37,056\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_3 (\u001b[38;5;33mMaxPooling1D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m62\u001b[0m, \u001b[38;5;34m192\u001b[0m)        │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_3 (\u001b[38;5;33mFlatten\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m11904\u001b[0m)          │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout (\u001b[38;5;33mDropout\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m11904\u001b[0m)          │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_7 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m)            │     \u001b[38;5;34m3,047,680\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_8 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │         \u001b[38;5;34m3,341\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">3,088,333</span> (11.78 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m3,088,333\u001b[0m (11.78 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">3,088,333</span> (11.78 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m3,088,333\u001b[0m (11.78 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn2 =  Cnn2(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/6\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m22s\u001b[0m 39ms/step - accuracy: 0.5837 - loss: 2.2163 - val_accuracy: 0.7668 - val_loss: 0.6433\n",
      "Epoch 2/6\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m20s\u001b[0m 38ms/step - accuracy: 0.8063 - loss: 0.5435 - val_accuracy: 0.8080 - val_loss: 0.5138\n",
      "Epoch 3/6\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m20s\u001b[0m 38ms/step - accuracy: 0.8532 - loss: 0.4038 - val_accuracy: 0.8458 - val_loss: 0.4513\n",
      "Epoch 4/6\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m20s\u001b[0m 39ms/step - accuracy: 0.8787 - loss: 0.3439 - val_accuracy: 0.8063 - val_loss: 0.5261\n",
      "Epoch 5/6\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m23s\u001b[0m 44ms/step - accuracy: 0.8895 - loss: 0.3111 - val_accuracy: 0.8664 - val_loss: 0.4279\n",
      "Epoch 6/6\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m23s\u001b[0m 45ms/step - accuracy: 0.9140 - loss: 0.2461 - val_accuracy: 0.8703 - val_loss: 0.3917\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x2178d7137a0>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cnn2.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=6,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn2.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m111/111\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 8ms/step\n"
     ]
    }
   ],
   "source": [
    "cnn2_pred = cnn2.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Convolutional Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.8883878241262683.\n",
      "precision\t0.8848494413508083.\n",
      "recall\t\t0.8843013419486064.\n",
      "f1-score\t0.8837675458460037.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, cnn2_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{cnn2.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.95      0.96      0.96       280\n",
      "         pdf       0.99      1.00      1.00       335\n",
      "          ps       0.99      0.98      0.98       311\n",
      "         xls       0.94      0.95      0.95       288\n",
      "         ppt       0.96      0.93      0.95       337\n",
      "         swf       0.71      0.68      0.70       283\n",
      "         gif       0.82      0.71      0.76       301\n",
      "         jpg       0.73      0.83      0.78       276\n",
      "         png       0.64      0.70      0.67       260\n",
      "        html       0.97      0.93      0.95       292\n",
      "         txt       0.96      0.96      0.96       301\n",
      "         xml       0.94      0.97      0.96       284\n",
      "\n",
      "    accuracy                           0.89      3548\n",
      "   macro avg       0.88      0.88      0.88      3548\n",
      "weighted avg       0.89      0.89      0.89      3548\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cnn2_report = classification_report(y_test, cnn2_pred, target_names=CLASS_NAMES)\n",
    "print(cnn2_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn2_cm = confusion_matrix(y_test, cnn2_pred)\n",
    "plot_confusion_matrix(cnn2_cm, CLASS_NAMES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gated Reccurent Unit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_4\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_4\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ bidirectional (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Bidirectional</span>)   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">136</span>)            │        <span style=\"color: #00af00; text-decoration-color: #00af00\">28,968</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_9 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,781</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ bidirectional (\u001b[38;5;33mBidirectional\u001b[0m)   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m136\u001b[0m)            │        \u001b[38;5;34m28,968\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_9 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │         \u001b[38;5;34m1,781\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">30,749</span> (120.11 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m30,749\u001b[0m (120.11 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">30,749</span> (120.11 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m30,749\u001b[0m (120.11 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gru = Gru(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m89s\u001b[0m 164ms/step - accuracy: 0.3217 - loss: 1.6921 - val_accuracy: 0.5540 - val_loss: 1.1215\n",
      "Epoch 2/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m82s\u001b[0m 158ms/step - accuracy: 0.5828 - loss: 1.0647 - val_accuracy: 0.6552 - val_loss: 0.8867\n",
      "Epoch 3/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m81s\u001b[0m 156ms/step - accuracy: 0.6327 - loss: 0.9151 - val_accuracy: 0.6761 - val_loss: 0.8119\n",
      "Epoch 4/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m81s\u001b[0m 156ms/step - accuracy: 0.6861 - loss: 0.7986 - val_accuracy: 0.7090 - val_loss: 0.7534\n",
      "Epoch 5/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m84s\u001b[0m 163ms/step - accuracy: 0.7124 - loss: 0.7449 - val_accuracy: 0.7223 - val_loss: 0.7175\n",
      "Epoch 6/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m84s\u001b[0m 162ms/step - accuracy: 0.7468 - loss: 0.6629 - val_accuracy: 0.7403 - val_loss: 0.6587\n",
      "Epoch 7/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 168ms/step - accuracy: 0.7588 - loss: 0.6400 - val_accuracy: 0.7626 - val_loss: 0.6315\n",
      "Epoch 8/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m88s\u001b[0m 169ms/step - accuracy: 0.7792 - loss: 0.5803 - val_accuracy: 0.7623 - val_loss: 0.6018\n",
      "Epoch 9/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 168ms/step - accuracy: 0.7881 - loss: 0.5592 - val_accuracy: 0.7793 - val_loss: 0.5820\n",
      "Epoch 10/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 168ms/step - accuracy: 0.8092 - loss: 0.5205 - val_accuracy: 0.7962 - val_loss: 0.5466\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x2178e116ff0>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gru.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=10,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gru.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m111/111\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 46ms/step\n"
     ]
    }
   ],
   "source": [
    "gru_pred = gru.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gated Reccurent Unit performance evaluation:\n",
      "\n",
      "accuracy\t0.8091882750845547.\n",
      "precision\t0.804715164211164.\n",
      "recall\t\t0.8031156746829468.\n",
      "f1-score\t0.8026471812128637.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, gru_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{gru.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.85      0.85      0.85       280\n",
      "         pdf       0.94      0.98      0.96       335\n",
      "          ps       0.91      0.90      0.91       311\n",
      "         xls       0.86      0.83      0.85       288\n",
      "         ppt       0.87      0.83      0.85       337\n",
      "         swf       0.64      0.65      0.65       283\n",
      "         gif       0.73      0.88      0.80       301\n",
      "         jpg       0.70      0.60      0.65       276\n",
      "         png       0.59      0.59      0.59       260\n",
      "        html       0.90      0.80      0.85       292\n",
      "         txt       0.84      0.83      0.84       301\n",
      "         xml       0.83      0.88      0.85       284\n",
      "\n",
      "    accuracy                           0.81      3548\n",
      "   macro avg       0.80      0.80      0.80      3548\n",
      "weighted avg       0.81      0.81      0.81      3548\n",
      "\n"
     ]
    }
   ],
   "source": [
    "gru_report = classification_report(y_test, gru_pred, target_names=CLASS_NAMES)\n",
    "print(gru_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gru_cm = confusion_matrix(y_test, gru_pred)\n",
    "plot_confusion_matrix(gru_cm, CLASS_NAMES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Long Short-Term Memory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_5\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_5\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ bidirectional_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Bidirectional</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">136</span>)            │        <span style=\"color: #00af00; text-decoration-color: #00af00\">38,080</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_10 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,781</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ bidirectional_1 (\u001b[38;5;33mBidirectional\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m136\u001b[0m)            │        \u001b[38;5;34m38,080\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_10 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │         \u001b[38;5;34m1,781\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">39,861</span> (155.71 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m39,861\u001b[0m (155.71 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">39,861</span> (155.71 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m39,861\u001b[0m (155.71 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lstm = Lstm(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m75s\u001b[0m 138ms/step - accuracy: 0.3195 - loss: 1.6494 - val_accuracy: 0.4934 - val_loss: 1.2346\n",
      "Epoch 2/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m69s\u001b[0m 133ms/step - accuracy: 0.4997 - loss: 1.2113 - val_accuracy: 0.5579 - val_loss: 1.0838\n",
      "Epoch 3/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m72s\u001b[0m 139ms/step - accuracy: 0.5845 - loss: 1.0121 - val_accuracy: 0.6456 - val_loss: 0.9149\n",
      "Epoch 4/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m72s\u001b[0m 139ms/step - accuracy: 0.6198 - loss: 0.9339 - val_accuracy: 0.5266 - val_loss: 1.1825\n",
      "Epoch 5/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m70s\u001b[0m 136ms/step - accuracy: 0.6277 - loss: 0.9476 - val_accuracy: 0.6685 - val_loss: 0.8442\n",
      "Epoch 6/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m72s\u001b[0m 138ms/step - accuracy: 0.6985 - loss: 0.7967 - val_accuracy: 0.7037 - val_loss: 0.7532\n",
      "Epoch 7/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m70s\u001b[0m 136ms/step - accuracy: 0.7213 - loss: 0.7372 - val_accuracy: 0.7195 - val_loss: 0.7071\n",
      "Epoch 8/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m73s\u001b[0m 140ms/step - accuracy: 0.7376 - loss: 0.6850 - val_accuracy: 0.7333 - val_loss: 0.6791\n",
      "Epoch 9/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m74s\u001b[0m 142ms/step - accuracy: 0.7539 - loss: 0.6369 - val_accuracy: 0.7581 - val_loss: 0.6468\n",
      "Epoch 10/10\n",
      "\u001b[1m518/518\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m74s\u001b[0m 142ms/step - accuracy: 0.7748 - loss: 0.5920 - val_accuracy: 0.7621 - val_loss: 0.6252\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x2178b13adb0>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lstm.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=10,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+Pd1IVj53ef0zXaVKFQC2bdtG8+bNb3m8yWS64bX/O0ggzc0+L7179+aBBx5g8+bN1KlTh9mzZ9O6dWtKlCiRfozZbKZt27a88MILNzxHpUqVblmv5I7CjdhcUFAQXl5e7NmzJ8Nzu3fvxsnJKcNf07eS1iF43759Vn9RnTlzJlt3Dv4rMDCQ8uXLs3379my/Njw8nEWLFnH+/Hmrv8x3795tVXNmbtaxuV27dlajim6lfPnyAAQHB9OmTZssv84eunbtyiOPPMI///xjdXv/v8qXL8+iRYto2rRptoJhdqV9nW72/VqiRIksD/Xu378/H3zwAf/73//4/fffCQoKol27drmuMSgoCF9fX1JTU2/59Z07dy7lypXjhx9+sPr++m8nWHvL7c90586dGTNmDN9//32Wwk1gYOANm1D/e4f1Vrp06cIjjzyS/r27d+9eRowYYXVM+fLlSUxMLPA/i45MfW7E5pydnbnzzjv5+eefrYYKnzhxIn0St1vd0v6v1q1b4+LiwoQJE6z2Xz/0MjNbtmy54Twqhw4dYufOnTdskriVjh07kpqamqGGjz76CJPJlD4iKDNpo5Ti4uKs9oeGhtKmTRurR2batWuHn58fb7/9tlUzRJr/DsG1Jx8fHyZMmMDo0aPp3LnzTY/r1asXqamp6bf/r5eSkpLhc5ZToaGh1KlTh2+++cbqnNu3b+fPP/+kY8eOWT5XrVq1qFWrFpMnT2bevHn07t07w12znHB2dqZ79+7MmzfvhkH8+q9v2h2T6+9SrFmzhtWrV+e6DlvK7c9048aNad++PZMnT+ann37K8HxycjLDhg1L/7h8+fLs3r3b6nO1ZcsWVq5cma26AwICaNeuHbNnz2bmzJm4ubnRpUsXq2N69erF6tWrWbBgQYbXx8XFkZKSkq1rSvbpzo3k2FdffcUff/yRYf/TTz/Nm2++ycKFC2nWrBmPP/44Li4ufPHFFyQlJfHee+9l+1ohISE8/fTTfPDBB9x99920b9+eLVu28Pvvv1OiRIlbDu1euHAho0aN4u677+a2227Dx8eHAwcO8NVXX5GUlJSjuWU6d+7M7bffzssvv8zBgwepXbs2f/75Jz///DPPPPNM+t2UzHh6elKtWjVmzZpFpUqVKFasGDVq1KBGjRrZqsXPz48JEyZw//33U7duXXr37k1QUBCHDx/m119/pWnTpln+pZEfbta0cr2WLVvyyCOPMGbMGDZv3sydd96Jq6sr//77L3PmzOHjjz++aX+d7Hr//ffp0KEDjRs3ZtCgQelDwf39/bP9vdG/f//0X6rZbZLK7GfqnXfe4a+//qJRo0YMHjyYatWqcfbsWTZu3MiiRYs4e/YsAJ06deKHH36ga9eu3HXXXURHRzNx4kSqVatGYmJiturJS7n9mQZjaoc777yTbt260blzZ1q3bo23tzf//vsvM2fO5Pjx4+lz3Tz44IN8+OGHtGvXjkGDBnHy5EkmTpxI9erVs9RB+nr33nsv9913H59//jnt2rXL0LT6/PPPM3/+fDp16sTAgQOpV68eFy5cYNu2bcydO5eDBw9aNWOJ7SncSI799y+uNAMHDqR69eosX76cESNGMGbMGMxmM40aNeL777/PMMdNVr377rt4eXnx5ZdfsmjRIho3bsyff/5Js2bN8PDwyPS13bt35/z58/z5558sWbKEs2fPEhgYSMOGDXnuuee4/fbbs12Pk5MT8+fPZ+TIkcyaNYuvv/6aiIgI3n//fZ577rksn2fy5Mk8+eSTPPvssyQnJ6evf5Vdffv2pVSpUrzzzju8//77JCUlUbp0aZo3b56h/05hMXHiROrVq8cXX3zBSy+9hIuLCxEREdx33303nJAxp9q0acMff/zBqFGjGDlyJK6urrRs2ZJ33303Wx3BAfr168eLL75I+fLladiwYbZem9nPVJkyZVi7di2vv/46P/zwA59//jnFixenevXqVvPODBw4kNjYWL744gsWLFhAtWrV+P7775kzZ84t1zDLb7n5mQajuW7VqlV8/vnnzJo1i5dffpnk5GTCw8O5++67efrpp9OPrVq1Kt9++y0jR45k6NChVKtWje+++47p06dn+/Ny99134+npyfnz561GSaXx8vJi6dKlvP3228yZM4dvv/0WPz8/KlWqxGuvvZbeqV3yjsmSVz02RfJBXFwcgYGBvPnmmzabal0kN06fPk1oaCgjR47k1VdftXc5hY5+psUW1OdGCo1Lly5l2Jc206ct1lcSsYWpU6eSmpqaZzPnOhL9TEteUbOUFBqzZs1i6tSpdOzYER8fH1asWMGMGTO48847bdpEIZITS5YsYefOnbz11lt06dIlw5INkpF+piWvKNxIoVGrVi1cXFx47733SEhISO+QeP38NCL28vrrr7Nq1SqaNm3Kp59+au9yCgX9TEteUZ8bERERcSjqcyMiIiIOReFGREREHEqR63NjNps5duwYvr6+WZokSkREROzPYrFw/vx5SpUqddO18dIUuXBz7NixbK9rJCIiIgVDTEwMZcqUyfSYIhdu0hY4jImJyfb6RiIiImIfCQkJhIWFWS1UfDNFLtykNUX5+fkp3IiIiBQyWelSog7FIiIi4lAUbkRERMShKNyIiIiIQylyfW5ERMRxmM1mkpOT7V2G2Iibm9sth3lnhcKNiIgUSsnJyURHR2M2m+1ditiIk5MTkZGRuLm55eo8CjciIlLoWCwWjh8/jrOzM2FhYTb5a1/sK22S3ePHj1O2bNlcTbSrcCMiIoVOSkoKFy9epFSpUnh5edm7HLGRoKAgjh07RkpKCq6urjk+j6KuiIgUOqmpqQC5br6QgiXt65n29c0phRsRESm0tEagY7HV11PhRkRERByKwo2IiEghFBERwbhx47J8/N9//43JZCIuLi7Paioo1KFYREQkn7Rq1Yo6depkK5TczLp16/D29s7y8U2aNOH48eP4+/vn+toFne7c2NCJhMvsOp5g7zJERKSQslgspKSkZOnYoKCgbI0Uc3Nzo2TJkkWin5LCjY38sf04zd5dwss/brN3KSIiUgANHDiQpUuX8vHHH2MymTCZTEydOhWTycTvv/9OvXr1cHd3Z8WKFezfv5977rmHkJAQfHx8aNCgAYsWLbI633+bpUwmE5MnT6Zr1654eXlRsWJF5s+fn/78f5ulpk6dSkBAAAsWLKBq1ar4+PjQvn17jh8/nv6alJQUnnrqKQICAihevDgvvvgiAwYMoEuXLnn5qco1hRsbqRdeDBMmNh6OY/3Bs/YuR0SkSLFYLFxMTrHLw2KxZKnGjz/+mMaNGzN48GCOHz/O8ePHCQsLA2D48OG888477Nq1i1q1apGYmEjHjh1ZvHgxmzZton379nTu3JnDhw9neo3XXnuNXr16sXXrVjp27Ei/fv04e/bmv5MuXrzI2LFj+e6771i2bBmHDx9m2LBh6c+/++67TJs2ja+//pqVK1eSkJDATz/9lKX3a0/qc2MjQb7udKtbmpnrYpi07AD1I4rZuyQRkSLj0pVUqo1cYJdr73y9HV5ut/516u/vj5ubG15eXpQsWRKA3bt3A/D666/Ttm3b9GOLFStG7dq10z9+4403+PHHH5k/fz5Dhgy56TUGDhxInz59AHj77bf55JNPWLt2Le3bt7/h8VeuXGHixImUL18egCFDhvD666+nP//pp58yYsQIunbtCsD48eP57bffbvle7U13bmzooeaRACzcdYIDpxLtXI2IiBQW9evXt/o4MTGRYcOGUbVqVQICAvDx8WHXrl23vHNTq1at9G1vb2/8/Pw4efLkTY/38vJKDzYAoaGh6cfHx8dz4sQJGjZsmP68s7Mz9erVy9Z7swfdubGhCsG+tKkazKJdJ5m8Ipq3u9a0d0kiIkWCp6szO19vZ7dr59Z/Rz0NGzaMhQsXMnbsWCpUqICnpyc9evS45Qro/12ywGQyZbqw6I2Oz2ozW0GmcGNjg5uXY9Guk8zbcIShbStRwsfd3iWJiDg8k8mUpaYhe3Nzc8vS0gIrV65k4MCB6c1BiYmJHDx4MI+rs+bv709ISAjr1q2jRYsWgLEswsaNG6lTp06+1pJdapaysYaRxagdFkBSiplvVx+ydzkiIlKAREREsGbNGg4ePMjp06dvelelYsWK/PDDD2zevJktW7bQt2/fTO/A5JUnn3ySMWPG8PPPP7Nnzx6efvppzp07V+CHkyvc2JjJZOLh5uUA+G71QS4l527xLxERcRzDhg3D2dmZatWqERQUdNM+NB9++CGBgYE0adKEzp07065dO+rWrZvP1cKLL75Inz596N+/P40bN8bHx4d27drh4eGR77Vkh8niCI1r2ZCQkIC/vz/x8fH4+fnlyTVSzRZajf2LmLOXeOOe6tzfOCJPriMiUlRdvnyZ6OhoIiMjC/wvWkdiNpupWrUqvXr14o033rD5+TP7umbn97fu3OQBZycTDzUz7t5MXhFNqrlI5UcREXEQhw4d4ssvv2Tv3r1s27aNxx57jOjoaPr27Wvv0jKlcJNHetYvQ4CXK4fOXGThzlh7lyMiIpJtTk5OTJ06lQYNGtC0aVO2bdvGokWLqFq1qr1Ly1TB71peSHm5uXD/beF8umQfXyw7QLvqRWM9DxERcRxhYWGsXLnS3mVkm13v3CxbtozOnTtTqlQpTCZTtqZ0XrlyJS4uLgV6OFr/xhG4uTix6XAcGw6ds3c5IiIiRYJdw82FCxeoXbs2n332WbZeFxcXR//+/WndunUeVWYbQb7udK9bGoAvlh2wczUiIiJFg12bpTp06ECHDh2y/bpHH32Uvn374uzsXOAX8BrUrBwz1sawaNcJ9p9KpHyQj71LEhERcWiFrkPx119/zYEDBxg1alSWjk9KSiIhIcHqkZ8qBPvQpmoIFgtMXh6dr9cWEREpigpVuPn3338ZPnw433//PS4uWbvpNGbMGPz9/dMfacvL56eHWxjDwudtPMLpxKR8v76IiEhRUmjCTWpqKn379uW1116jUqVKWX7diBEjiI+PT3/ExMTkYZU31iAikNphASRrSQYREZE8V2jCzfnz51m/fj1DhgzBxcUFFxcXXn/9dbZs2YKLiwtLliy54evc3d3x8/OzeuQ3k8nEIy20JIOIiOROREQE48aNS//4ViONDx48iMlkYvPmzbm6rq3Ok18KzTw3fn5+bNu2zWrf559/zpIlS5g7dy6RkZF2qixr2lUvSdliXhw+e5G5G2K0JIOIiOTa8ePHCQwMtOk5Bw4cSFxcnFVoCgsL4/jx45QoUcKm18ordg03iYmJ7Nu3L/3j6OhoNm/eTLFixShbtiwjRozg6NGjfPvttzg5OVGjRg2r1wcHB+Ph4ZFhf0Hk7GTioeaRjPx5B5NXRNO3UTjOTprUT0REcq5kyZL5ch1nZ+d8u5Yt2LVZav369URFRREVFQXA0KFDiYqKYuTIkYCRSG+2Ymph1KPetSUZ/tyhJRlERIqSSZMmUapUKcxms9X+e+65hwcffJD9+/dzzz33EBISgo+PDw0aNGDRokWZnvO/zVJr164lKioKDw8P6tevz6ZNm6yOT01NZdCgQURGRuLp6UnlypX5+OOP058fPXo033zzDT///DMmkwmTycTff/99w2appUuX0rBhQ9zd3QkNDWX48OGkpKSkP9+qVSueeuopXnjhBYoVK0bJkiUZPXp09j9xOWDXcNOqVSssFkuGx9SpUwGYOnUqf//9901fP3r06ELT/gfGkgz9bwsHjEn9itiC7CIiecdigeQL9nlk8f/ynj17cubMGf7666/0fWfPnuWPP/6gX79+JCYm0rFjRxYvXsymTZto3749nTt3zvIf+YmJiXTq1Ilq1aqxYcMGRo8ezbBhw6yOMZvNlClThjlz5rBz505GjhzJSy+9xOzZswEYNmwYvXr1on379hw/fpzjx4/TpEmTDNc6evQoHTt2pEGDBmzZsoUJEyYwZcoU3nzzTavjvvnmG7y9vVmzZg3vvfcer7/+OgsXLszS+8mNQtPnxlHc3ziCicsOsDkmjvWHztEgopi9SxIRKfyuXIS3S9nn2i8dAzfvWx4WGBhIhw4dmD59evoM+3PnzqVEiRLcfvvtODk5Ubt27fTj33jjDX788Ufmz5/PkCFDbnn+6dOnYzabmTJlCh4eHlSvXp0jR47w2GOPpR/j6urKa6+9lv5xZGQkq1evZvbs2fTq1QsfHx88PT1JSkrKtBnq888/JywsjPHjx2MymahSpQrHjh3jxRdfZOTIkTg5GfdOatWqlT4vXcWKFRk/fjyLFy+mbdu2t3w/uVFoRks5iuuXZJikJRlERIqUfv36MW/ePJKSjDnPpk2bRu/evXFyciIxMZFhw4ZRtWpVAgIC8PHxYdeuXVm+c7Nr1y5q1aqFh4dH+r7GjRtnOO6zzz6jXr16BAUF4ePjw6RJk7LdBWTXrl00btzYakHopk2bkpiYyJEjR9L31apVy+p1oaGhnDx5MlvXygndubGDh5prSQYREZty9TLuoNjr2lnUuXNnLBYLv/76Kw0aNGD58uV89NFHgNEktHDhQsaOHUuFChXw9PSkR48eJCcn26zUmTNnMmzYMD744AMaN26Mr68v77//PmvWrLHZNa7n6upq9bHJZMrQ5ygvKNzYQfkgY0mGRbtOMHl5NGO61bR3SSIihZvJlKWmIXvz8PCgW7duTJs2jX379lG5cmXq1q0LwMqVKxk4cCBdu3YFjD40Bw8ezPK5q1atynfffcfly5fT7978888/VsesXLmSJk2a8Pjjj6fv279/v9Uxbm5upKZmPh9b1apVmTdvHhaLJf3uzcqVK/H19aVMmTJZrjmvqFnKTh5peW1JhlPntSSDiEhR0a9fP3799Ve++uor+vXrl76/YsWK/PDDD2zevJktW7bQt2/fbN3l6Nu3LyaTicGDB7Nz505+++03xo4da3VMxYoVWb9+PQsWLGDv3r28+uqrrFu3zuqYiIgItm7dyp49ezh9+jRXrlzJcK3HH3+cmJgYnnzySXbv3s3PP//MqFGjGDp0aHp/G3uyfwVFVP3wQOpcXZLhu9UH7V2OiIjkkzvuuINixYqxZ88e+vbtm77/ww8/JDAwkCZNmtC5c2fatWuXflcnK3x8fPjf//7Htm3biIqK4uWXX+bdd9+1OuaRRx6hW7du3HvvvTRq1IgzZ85Y3cUBGDx4MJUrV6Z+/foEBQWxcuXKDNcqXbo0v/32G2vXrqV27do8+uijDBo0iFdeeSWbn428YbIUsfHICQkJ+Pv7Ex8fb5elGK73+7bjPDZtIwFerqwafgdebmolFBHJisuXLxMdHU1kZKRVB1op3DL7umbn97fu3NjRnVeXZIi7eIW5G47c+gUiIiJySwo3dpS2JAPA5OXRpJqL1E00ERGRPKFwY2c964UR6OXK4bMXWaAlGURERHJN4cbOPN2cuV9LMoiIiNiMwk0B0L9JBG4uTmyJiWPdwXP2LkdEpNDQH4SOxVZfT4WbAqCEjzvd6xqTHmlJBhGRW3N2dgaw6ey9Yn9pX8+0r29OaexxAfFQ80hmrjusJRlERLLAxcUFLy8vTp06haura4GYOE5yx2w2c+rUKby8vHBxyV08UbgpINKWZFi48wSTlx9gTLdat36RiEgRZTKZCA0NJTo6mkOHDtm7HLERJycnypYta7UgZ04o3BQgD7cox8KdJ5i38ShD21YmyNfd3iWJiBRYbm5uVKxYUU1TDsTNzc0md+EUbgqQ+uGBRJUNYNPhOL5dfZDn7qxs75JERAo0JycnzVAsGaiRsgAxmUw83NxYUPO7fw5xMTnFzhWJiIgUPgo3Bcyd1UsSXtxYkmHOei3JICIikl0KNwWMs5OJh5pdXZJhxQEtySAiIpJNCjcFUI+rSzLEnL2kJRlERESySeGmAPJ0c+b+xhGAlmQQERHJLoWbAqp/43DctSSDiIhItincFFAlfNzpXi9tSYb9dq5GRESk8FC4KcAeahaJyQSLdp1k38lEe5cjIiJSKCjcFGDlgnxoWzUEgMnLtaCmiIhIVijcFHAPtzAm9fth41FOnr9s52pEREQKPoWbAq7e1SUZklPNfLdai8OJiIjcisJNAWcymXikhZZkEBERySqFm0KgbbWSRGhJBhERkSxRuCkEnJ1MDLq6oObkFQdISTXbuSIREZGCS+GmkOhRtwzFvN2uLslwwt7liIiIFFgKN4WEp5sz998WDhiT+mlJBhERkRtTuClE7k9bkuFIPGujz9q7HBERkQJJ4aYQuX5Jhi81qZ+IiMgNKdwUMtZLMpy3dzkiIiIFjsJNIWO9JEO0nasREREpeBRuCqFHWmpJBhERkZtRuCmE6oUXo+7VJRm+XaUlGURERK6ncFNIPdyiPGAsyXAhSUsyiIiIpFG4KaTaVgshorgX8ZeuMGd9jL3LERERKTAUbgqp65dkmLIyWksyiIiIXKVwU4hdvyTDHzti7V2OiIhIgaBwU4hdvyTDl8sOaEkGERERFG4Kvf7XLcmwRksyiIiIKNwUdsV93OmRtiTDMi3JICIionDjAB5qXg6TCRbvPsm/J7Qkg4iIFG0KNw4gsoQ3d1bTkgwiIiKgcOMwHm5hDAv/cZOWZBARkaJN4cZB1AsvRr3wQJJTzXyz6qC9yxEREbEbhRsHMvjqpH7f/3NYSzKIiEiRpXDjQNpWCyGyhDfxl64wW0syiIhIEaVw40CcnUwMahYJwJQVWpJBRESKJoUbB9OjnrEkw5Fzl/h9u5ZkEBGRokfhxsF4uDrTv7GxJMMkLckgIiJFkMKNA7r/NmNJhm1HtSSDiIgUPQo3Dqi4jzs96xtLMkzSkgwiIlLEKNw4qEHNjCUZlmhJBhERKWIUbmwlJQl+egI2TbN3JYCxJEO7aiUB+HK57t6IiEjRoXBjK1tmwObv4Zdn4PA/9q4GgMFXl2T4adMxTiZoSQYRESkaFG5sJao/VO0Mqckwsx/EHbZ3RdQLD6T+1SUZpmpJBhERKSIUbmzFyQm6fgEla8LF0zCjDyQl2ruq9Ls33/9zSEsyiIhIkaBwY0tu3tB7BngHw4nt8MPDYLbvLMFtqhpLMiRcTtGSDCIiUiQo3NhaQBj0ngbObrDnV/jrTbuW4+xk4qHmWpJBRESKDoWbvBDWEO7+1Nhe/gFsnW3XcrrXLUNxLckgIiJFhMJNXqndG5o+Y2z/PASOrLdbKcaSDBGAlmQQERHHp3CTl1qPhEodIDUJZvaF+CN2K+X+xuF4uBpLMvxzQEsyiIiI41K4yUtOztD9SwiuBoknjBFUyRfsUkoxbzd61gsDYNKy/XapQUREJD8o3OQ1d1/oMxO8ikPsVvjpMbuNoBrULBKTCf7ac4q9WpJBREQclF3DzbJly+jcuTOlSpXCZDLx008/ZXr8Dz/8QNu2bQkKCsLPz4/GjRuzYMGC/Ck2NwLD4d7vwckVdv4MS9+1SxkR1y3JMFlLMoiIiIOya7i5cOECtWvX5rPPPsvS8cuWLaNt27b89ttvbNiwgdtvv53OnTuzadOmPK7UBsKbQKePjO2l78D2H+xSxsMttSSDiIg4NpOlgAydMZlM/Pjjj3Tp0iVbr6tevTr33nsvI0eOzNLxCQkJ+Pv7Ex8fj5+fXw4qzaUFL8Pq8eDiAQ/8DqXr5nsJPSasYv2hczzeqjwvtK+S79cXERHJruz8/i7UfW7MZjPnz5+nWLFiNz0mKSmJhIQEq4ddtX0dKrSFlMvGCKqE4/lewsPXLcmQqCUZRETEwRTqcDN27FgSExPp1avXTY8ZM2YM/v7+6Y+wsLB8rPAGnJyhxxQoURnOHzcCzpVL+VpCm6ohlEtbkmGdlmQQERHHUmjDzfTp03nttdeYPXs2wcHBNz1uxIgRxMfHpz9iYgrAL3MPf+g7EzwD4dhG+PkJyMfWQScnEw81N+7eaEkGERFxNIUy3MycOZOHHnqI2bNn06ZNm0yPdXd3x8/Pz+pRIBQrB72+BScX2D4Plo/N18t3q1ua4t5uHI27xG9akkFERBxIoQs3M2bM4IEHHmDGjBncdddd9i4ndyJbQMf3je0lb8Ku/+Xbpa2XZNivJRlERMRh2DXcJCYmsnnzZjZv3gxAdHQ0mzdv5vDhw4DRpNS/f//046dPn07//v354IMPaNSoEbGxscTGxhIfH2+P8m2j/oPQ8BFj+4eH4fjWfLt02pIM248msPrAmXy7roiISF6ya7hZv349UVFRREVFATB06FCioqLSh3UfP348PegATJo0iZSUFJ544glCQ0PTH08//bRd6reZdm9DudvhykVjiYbEk/ly2euXZPhymSb1ExERx1Bg5rnJL3af5+ZmLp2DyW3gzD4o0xAG/A9cPfL8sofOXKDV2L+xWODPZ1tQKcQ3z68p2bR1DpzdDy1eAKdC15IsImITRWaeG4fiGQh9ZhkjqY6shV+eyZcRVOHFvWlf3ViSQXdvCqC4GPjpUfh7DOxbZO9qREQKBYWbgqREBeg5FUzOsGUGrPw4Xy47+Oqkfj9tPsoJLclQsKz+DMxXJ1rcMsO+tYiIFBIKNwVN+Tug/TvG9qLRsOf3PL9k3bKBNIgI5EqqhamrDub59SSLLp6Fjd9c+3j3r3Apzm7liIgUFgo3BVHDwcYoKiww7yE4sSPPLzn46qR+07QkQ8GxdpLRybxkLQiuBqlJsONHe1clIlLgKdwURCYTdHgPIppDciLM6A0XTufpJa9fkmGWlmSwv+QLsGaisd3sGajdx9hW05SIyC0p3BRUzq7GDMaBkRB3GGbdDynJeXa565dk+EpLMtjfxm+NEXSBkVD1HqjVC0xOELMGzuy3d3UiIgWawk1B5lUM+s4Cdz84vAp+fTZPR1B1q1uaEj7Gkgy/bsv/1crlqtQrsGq8sd30KXB2Ad+SUL61sW/LTPvVJiJSCCjcFHRBlaHHV8Zf7Zu+h38+z7NLXb8kw8SlB0g1F6kpkAqObXMh4Qh4B0Ptvtf21+5t/LtlJph1Z01E5GYUbgqDim3hzjeN7T9fgX8X5tml7r8tHF93F3YdT2DKCs17k+/MZlg5zthu/Lj1RI5V7gJ3f4g/DIdW2qU8EZHCQOGmsLjtcYi6HyxmmPsgnNqTJ5cJ9HbjlU5VARj75172nUzMk+vITez9A07tNpoi6z9o/ZyrJ1TvYmyraUpE5KYUbgoLkwnu+hDKNoGkBJh+rzEPSh7oVT+MlpWCSE4x8/zcLWqeyi8WC6z4yNiu/6AxW/V/pY2a2vmTMaJKREQyULgpTFzc4N7vIKAsnIuG2f2Nzqc2ZjKZeKd7TXzdXdh0OI7Jy9U8lS8OrzaW3nB2h9seu/ExZW8zRlAlJ8KuX/K3PhGRQkLhprDxLgF9ZoKbDxxcDr+/kCcjqEL9PXm1UzUAPli4l30nz9v8GvIfaXdt6vQ1RkfdiMmkOW9ERG5B4aYwCqkO3ScDJlj/FaybnCeX6Vm/DK0qG81Tz83Zqrlv8lLsdvj3T2NUXJMnMz+29r3Gvwf+hvijeV6aiEhho3BTWFXuAG1GG9u/vwj7l9j8EiaTiTHdauLr4cKWmDi+XB5t82vIVWmLpFa7B4qXz/zYwAgIbwpYYOusvK5MRKTQUbgpzJo+bTRRWFJhzkA4vc/ml7i+eeqjhXv594Sap2zu3EHYPs/YbvpM1l5zfdNUHk7sKCJSGCncFGYmE3QaB2UawuV4mHGvMWW/jfWsV4bbKweRnGpm2Jwtap6ytVXjjYBa/g4oVSdrr6l2D7h4wum9cGxjnpYnIlLYKNwUdq4e0Hsa+JWBM/tgzgOQattVvY3mqVpG89SReCZp9JTtJJ6CTd8Z21m9awPg4QdVOxvbm9WxWETkego3jsAnGPrMAFcvOPAXLHjJ5pco6e/ByKvNU+MW/steNU/ZxpqJkHIZStWFyBbZe23acgzb50JKku1rExEppBRuHEVoLej6hbG99gtjFJWN9ahXhjuqBKt5ylaSzsO6L43tZs8azYzZUa4V+JYymiL3LrB5eSIihZXCjSOpdjfc8Yqx/dvzEL3Mpqc3mUy83dUYPbX1SDxfLFPzVK5smGr0lSpeEap0yv7rnZyhVi9jW8sxiIikU7hxNM2HQY0eYE4xZjA+a9sAUtLfg1GdqwPw8aJ/2ROr5qkcSUmC1Z8Z202fAqcc/iimjZr6dwFcOG2b2kRECjmFG0djMsE9440+HJfOwfTecDnBppfoXrc0ra82Tz0/V81TObJ1Fpw/Dr6hUOvenJ8nuAqUijLC7La5tqtPRKQQU7hxRK6e0Hu60R/j9B6YNwjMqTY7vclk4u1uNfFT81TOmFNh5SfGduMnwMU9d+er3df4d8v03J1HRMRBKNw4Kr9Q6DPdmAvl3z9h4Uibnj7Ez4PRdxvNU+MW7VXzVHbs/hXO/Gus+l1vYO7PV7MHOLnC8S1wYmfuzyciUsgp3DiyUlHQ5XNje/V42PS9TU/fNao0baoGcyXVwrA5W7ii5qlbs1iuLZDZ8GFw9839Ob2KQaV2xrYW0xQRUbhxeDW6Qcvhxvb/noFDq2126rTRU/6ermw7Gs8XS/fb7NwOK3qZMaOwiwc0fMR2503rWLx1ts0ncRQRKWwUboqCli8a0/Wbr8CsfnDukM1OHeznwei7jcn9Pl78L7tjbdt52eGsHGf8G3U/+ATZ7rwV7wTPYpAYa6wWLiJShCncFAVOTtBlIoTWhotnYEYfYwI5G+lSpzRtqoaoeepWjm02Vm83OUOTIbY9t4sb1OxpbKtpSkSKOIWbosLNC3rPAJ8QOLkDfngYzLYJIUbzVA38PV3ZfjSBiX+reeqG0u7a1OgOgRG2P3/acgy7fzEmBxQRKaIUbooS/9LGEHFnd9jzGyx53WanDvbz4LWro6c+WfIvu46recrKmf2w82dju+nTeXONUlEQVMVYq2rHT3lzDRGRQkDhpqgpUx/uuToz7oqPbDpt/z11StG2mpqnbmjVp2AxG31jStbIm2uYTNc6FqtpSkSKMIWboqhWT2j+nLE9/0mIWWeT05pMJt7qWoMAL1d2HEtggpqnDOdjYfM0Y7vZs3l7rVr3gskJDq+2+dIbIiKFhcJNUXX7K8ZijanJMLMvxMXY5LTBvteapz5V85ThnwnG5zmsEZRtnLfX8gs1VgsH2DIrb68lIlJAKdwUVU5O0PULCKkBF07CzD6QfMEmp767dinuVPOU4XI8rP/K2G76jNF0lNfSl2OYYbNO4yIihYnCTVHm7gN9ZoBXCYjdBj8+apNfhiaTiTeva576/K8i3Dy1bgokJRgdfSu1z59rVrkL3Hwh7hDE/JM/1xQRKUAUboq6gLLQexo4u8Gu+fD3GJuc9r/NUzuPFcHmqSuXjSYpMO7aOOXTj5ubF1TvYmxv1mKaIlL0KNwIlL0NOo0ztpe9B9vn2eS0d9cuRbvqIaSYi2jz1JbpRpOfXxljccv8lDZqasdPkHwxf68tImJnCjdiiOoHTZ40tn96HI5uyPUpTSYTb3apSaCXKzuPJ/DZX/tyfc5CIzUFVn5sbDcZAs6u+Xv9so0hIBySzxurkIuIFCEKN3JNm9egYjtjEriZ98GF07k+ZZCvO6/dY8zrMn7JPnYcKyIz5+76Gc4dBM9AqNs//6/v5KQ5b0SkyFK4kWucnKH7ZChRCc4fs1kH4861QmlfveTV5qmtJKc4ePOUxQIrxhnbjR4FN2/71JG2HMOBvyDhuH1qEBGxA4UbsebhBz2+BhcP2LcQVo/P9SlNJhNvdKlBoJcru4pC89T+JRC7FVy9oOHD9qujWKTRPGUxw1bNeSMiRYfCjWRUsga0vzpqavFrcGR9rk8Z5OvO61ebpz77y8Gbp1Z8ZPxbdwB4FbNvLdc3TVks9q1FRCSfKNzIjdV7AKp3BXMKzHkALp3L9Sk71QqlQw2jeeq52Vscs3nqyAY4uBycXKDxE/auxhgS7uIBp3bD8c32rkZEJF8o3MiNmUzQ+WMIjID4w8YaVLn8yz+teaqYtxu7Y88zfsm/tqm1IFl59a5NzV4QEGbfWgA8/I1lNgA2q2OxiBQNCjdycx7+Rv8bJ1fY9T9YNznXpyzh487r9xiT+3329362H3Wg5qlTe2HXL8Z206ftW8v10pqmts2BlGT71iIikg8UbiRzpetC29eN7QUvwfGtuT5lp1ql6FizJKlXJ/dzmOapVR8DFqh8FwRXsXc115S/HXxKwqWz8O+f9q5GRCTPKdzIrd32GFTuaKxsPWcgJJ3P9SnfuKcGxa82T33qCM1T8UevrcLd7Bm7lpKBkzPU6mVsa84bESkCFG7k1kwmuOcz8CsNZ/fDL0Nz3f+muI87b3QxRk99/vd+th0p5M1T/3wO5isQ3hTCGtq7mozSmqb2LoCLZ+1bi4hIHlO4kazxKgbdp4DJGbbNhs3Tcn3KjjVDuatWaHrzVFJKqg0KtYOLZ2HDVGO72bN2LeWmQqpBaG0jgG2ba+9qRETylMKNZF14Y7jjZWP712FwcneuT/n63dUp7u3GnhPn+XRxIZ3cb90USE6EkBpQoY29q7m52n2Nf7dopXARcWwKN5I9TZ+FcrdDyiWY+0CuV5wu7uPOm1ebpyYs3c/WI3E2KDIfJV+ENROM7abPGE14BVXNHsb8O8c22SSYiogUVAo3kj1OTtBtEngHw8md8MfwXJ+yQ81QOhXW5qlN38PFMxBQ1pj0sCDzLgEV7zS21bFYRByYwo1kn08wdP8SMMHGb2zSh+P1e2pQwseNvScS+WRxIRk9lXoFVn1qbDd5Cpxd7FtPVqR1LN46C8yFKESKiGRDjsJNTEwMR44cSf947dq1PPPMM0yaNMlmhUkBV64VtHje2P7fM3Bmf65OV8zbLb15auLSA4WjeWrHj8bszV4lIOo+e1eTNZXagWcgnD8OB/62dzUiInkiR+Gmb9++/PXXXwDExsbStm1b1q5dy8svv8zrr79u0wKlAGv5IpRtAsnnjf43KUm5Ol37GqF0rl2qcDRPWSzXFsi87VFw9bRvPVnl4g41ehjbW2batxYRkTySo3Czfft2GjY05vKYPXs2NWrUYNWqVUybNo2pU6fasj4pyJxdoPtk8CwGx7fAwpG5PuVrd1dPb576eFEBbp7690+jz5GbDzR4yN7VZE9a09Su/8HlBPvWIiKSB3IUbq5cuYK7uzsAixYt4u677wagSpUqHD9+3HbVScHnXxq6TjS210y8trZSDhnNUzUBmLh0P1ti4nJZYB5ZMc74t/4DRjNPYVK6LpSoZIx42/mzvasREbG5HIWb6tWrM3HiRJYvX87ChQtp3749AMeOHaN48eI2LVAKgUrtoPEQY/vnxyHucK5O175GSe6uXQqzBYbN2cLlKwWseerwP3B4FTi7wW1P2Lua7DOZrt290agpEXFAOQo37777Ll988QWtWrWiT58+1K5dG4D58+enN1dJEdN6FJSuB5fjYe4gYyRRLhjNU+78ezKRjwva6Km0uza17gW/ULuWkmO17gVMcGglnDto72pERGwqR+GmVatWnD59mtOnT/PVV1+l73/44YeZOHGizYqTQsTFDXp8Be7+cGQt/PVWrk4X6O3GW12N0VNfLN3P5oLSPHViJ+z9HTBB06ftXU3O+ZeGci2N7bQFP0VEHESOws2lS5dISkoiMNDoa3Do0CHGjRvHnj17CA4OtmmBUogERsA9V+d9WfER7FuUq9O1q16Se+oUsOapVZ8Y/1btDCUq2reW3EpfjmFGrhdCFREpSHIUbu655x6+/fZbAOLi4mjUqBEffPABXbp0YcKECTYtUAqZavdcGz30wyOQkLsO5qM7G81T+04mMs7eo6fiDsO2OcZ2s2fsWopNVO1kjPY6Fw0xa+xdjYiIzeQo3GzcuJHmzZsDMHfuXEJCQjh06BDffvstn3zyiU0LlELozrcgpCZcPA0/DM7VTLiB3m68fbV5atKy/Ww6fM5WVWbf6s/AnAKRLY3+RYWdm7cRRgE2azFNEXEcOQo3Fy9exNfXF4A///yTbt264eTkxG233cahQ4dsWqAUQq4e0HMquHrDweWwbGyuTndn9ZJ0sXfz1IUzsOEbY9sR7tqkSRs1teNHuHLJvrWIiNhIjsJNhQoV+Omnn4iJiWHBggXceaexGN/Jkyfx8/OzaYFSSJWoAJ2uzuC79B2IXp6r042+uzpBvu7sP3WBjxbttUGB2bR2kjEvTGhtY1V0RxHeFPzLQlIC7P7V3tWIiNhEjsLNyJEjGTZsGBERETRs2JDGjRsDxl2cqKgomxYohVjte6HOfWAxw7yH4MLpHJ8qwMuNt7sak/t9uewAG/OzeSopEdZ+YWw3e9aYJ8ZRODlB7d7GtpZjEBEHkaNw06NHDw4fPsz69etZsGBB+v7WrVvz0Ucf2aw4cQAd34MSlSExFn58FMzmHJ+qbbUQukaVxmyB5/OzeWrjt3DpHBQrB1Xvzp9r5qe0cLN/MZyPtW8tIiI2kKNwA1CyZEmioqI4duxY+grhDRs2pEqVKjYrThyAmzf0/BpcPGDfQlj9aa5ON6pztWvNUwvzoXkqJRlWjze2mzwFTs55f838Vrw8hDUy7rBtnW3vakREci1H4cZsNvP666/j7+9PeHg44eHhBAQE8MYbb2DOxl/my5Yto3PnzpQqVQqTycRPP/10y9f8/fff1K1bF3d3dypUqKCFOguDkOrQ4V1je/HrELMux6cK8HJjTFrz1PJ8aJ7aNgcSjoJPyLXOt47o+uUYNOeNiBRyOQo3L7/8MuPHj+edd95h06ZNbNq0ibfffptPP/2UV199NcvnuXDhArVr1+azzz7L0vHR0dHcdddd3H777WzevJlnnnmGhx56yKppTAqougOgejdjKPXcB41mnhxqUy2Eblebp/J09JTZDCs/NrZve9wYBeaoqncFZ3djpfPYrfauRkQkV0wWS/b/TCtVqhQTJ05MXw08zc8//8zjjz/O0aNHs1+IycSPP/5Ily5dbnrMiy++yK+//sr27dvT9/Xu3Zu4uDj++OOPLF0nISEBf39/4uPjNbIrv11OgC9aGJPGVekE936f48658Rev0PajpZw8n8TDLcrxUseqNi4WY/TQzL7GkhLPbgcPB/9+mTPQGBLe6DHo8I69qxERsZKd3985unNz9uzZG/atqVKlCmfPns3JKbNk9erVtGnTxmpfu3btWL169U1fk5SUREJCgtVD7MTDz+h/4+QKu3+BtV/m+FT+Xq6M6XateWrDIRs3T1kssPxDY7vBg44fbODacgzb5uR64VMREXvKUbipXbs248ePz7B//Pjx1KpVK9dF3UxsbCwhISFW+0JCQkhISODSpRtPQDZmzBj8/f3TH2FhYXlWn2RBqSi48w1j+8+X4fiWHJ+qddUQutctgyUvRk8dWglH1xtNNY0es915C7Lydxh9iy6ehn8X2rsaEZEcy1G4ee+99/jqq6+oVq0agwYNYtCgQVSrVo2pU6cydmzuZqO1tREjRhAfH5/+iImJsXdJ0uhRqNwRUpONppCk8zk+1cjO1Qjxc+fA6QuMXbDHdjWuGGf8G9UPfEMyPdRhOLtAzZ7G9pYZ9q1FRCQXchRuWrZsyd69e+natStxcXHExcXRrVs3duzYwXfffWfrGtOVLFmSEydOWO07ceIEfn5+eHp63vA17u7u+Pn5WT3EzkwmuOcz8CsDZw/AL8/meISOv6cr73Qz7hZOWRnN+oM2aBaN3WYMWzc5QZMnc3++wiRt1NTeP+Bi3jUxi4jkpRzPc1OqVCneeust5s2bx7x583jzzTc5d+4cU6ZMsWV9Vho3bszixYut9i1cuDB9hmQpRLyKQY+vwORs9PHY9H2OT3V7lWB61LvaPDV3K5eSc9k8lXbXploXY+K+oqRkDShZ07irtn2evasREcmRHIcbW0hMTGTz5s1s3rwZMIZ6b968mcOHDwNGk1L//v3Tj3/00Uc5cOAAL7zwArt37+bzzz9n9uzZPPvss/YoX3KrbCO44xVj+7fn4eSuHJ/q1U7VKOnnQfTpC4z9MxfNU2ejYccPxrYjLZCZHWkdi9U0JSKFlF3Dzfr164mKikpfj2ro0KFERUUxcuRIAI4fP54edAAiIyP59ddfWbhwIbVr1+aDDz5g8uTJtGvXzi71iw00fcboyJpyyeh/k3wxR6fx93RlTHdj9NRXK6NZl9PmqdXjjZl6y7c2Fsksimr2NO6oHd0Ap+ywSKmISC7laJ6bm9myZQt169YlNTWf1vzJAc1zUwAlnoKJTSHxBNTtD3fnfImG5+dsYc6GI0QU9+L3p1vg6ZaN5RIST8K4mpByGQb8ApHNc1xHoTf9XqPfTbOh0GaUvasREcnW72+X7Jy4W7dumT4fFxeXndOJGHyCoNuX8O09xiKVES2gVs8cneqVTtVY/u9pDp65yPsL9jCyc7Wsv3jNRCPYlK4PEc1ydH2HUbuPEW62zjKaDh1xTS0RcVjZapa6fr6YGz3Cw8Ot+siIZFm5ltDyBWP7l2fgzP4cneb65qmvV0WzNjqLzVOXE2DtZGO72TM5njnZYVTuAB7+xrpa0cvsXY2ISLbYtFmqMFCzVAGWmgLf3m1MoFeyFjy0CFzcc3SqF+ZuYfb6I/h7utKqchANIorRKLIYFYJ9MN0ouKz8BBa+CsUrwhNrwcmu3dEKhl+ehfVfQa3e0O0Le1cjIkVcdn5/K9xIwZJwDCY0hUtnoeEj0PG9nJ3m8hW6fraS/acuWO0v5u1G/fBAGkYWo2FkMaqF+uFiuQLjakFirDH/TtR9tngnhV/MOpjSBly9YNhecPe1d0UiUoQp3GRC4aYQ2PsnTL/a5+be76Fq5xyd5vKVVDYeOsea6LOsO3iWjYfPcfmK2eoYbzdnni3+Dw+d+4hkr5KYn9qMh8eNJ4QsciwWGF8fzuyDez43ZmsWEbEThZtMKNwUEn++Cqs+Mfp9PLoCAsrm+pTJKWa2H4tnbfRZ1kWfZe3Bs1y4nMwit2GUc4rljSv9+I7O1AkLoEFkIA0ji1MvPBAf92z1u3csy8bCkjcgojkM/MXe1YhIEaZwkwmFm0Ii9Qp81d5YvLJMA3jgd3B2te0lzBaOrZpJ2KJHueDkS0enCRxKtO5r42SC6qX8aRBhNGM1iAikuE/O+gEVSnExxvB4LPDMNpuETBGRnFC4yYTCTSFy7hBMbA5J8dD0aWj7um3Pb7HAl7fDsU3Q4gUst7/EwTMXWRd9ljXRZ1l78AwxZzOuNl8h2Mfos3M18JQKcPBmrG86GyOmbn8FWj5v72pEpIhSuMmEwk0hs3M+zL7f2O43Dyq2sd25D/xtzK3j4gnPbgfvEhkOOR5/yWjGOniWtdFn2XsiMcMxpQM8aRRZjAZXOymXK+F94xFZhdXmGfDTo1CsPDy5QcPkRcQuFG4yoXBTCP06DNZ9CV7F4dGV4Bdqm/N+e48RcBo+DB3fz9JLzl1IZt3Ba2Fn+7EEUs3WP0IlfNyua8YqRtVQP5ydCnEgSEqEsZXgygUYtBDCGtq7IhEpghRuMqFwUwhduWwMSY7dZnRs7f9z7mfMPbYJJrUy1lB6ahMEhufoNBeSUth4+Bxro42wsykmjuQU6xFZvu4u1Iswhp83iixGzdIBuLkUsnl0fnzUWEiz3gPQeZy9qxGRIkjhJhMKN4XU6X0wqSUkJ0KrEdBqeO7ON3sA7PwJat0L3SbZpESApJRUth2JN/rsRJ9lw6FzJCalWB3j7uJEVNmAq312ihNVNgDvgj4i68BSY4JFD394bi+4eti7IhEpYhRuMqFwU4htnQ0/DAZMMGA+RLbI2XnO7IdP6wEWeGwVhFS3ZZVWUs0Wdh1PSL+zs+7gWc5cSLY6xtnJRI3S/jSMMIafN4gIJMDLLc9qyhGzGT6uBfEx0ONrqJH5OnMiIramcJMJhZtC7ucnYNP34FPSmP/GJyj755j/FGz8Biq2g36zbV9jJiwWC/tPXUjvs7M2+ixH4zKOyKoc4mv02bk6KqukfwG4U7L4DVg+1i6fNxERhZtMKNwUcskX4Ms74NRuKN8a+s3N3jpQ52ONeVtSk+GBPyC8cd7VmkVHzl28GnbOsTb6TIYlIwAqhfgwqFkkXaPK2K+/zul/jRmLTc7w3G7wCbZPHSJSJCncZELhxgGc2GnMT5NyGdq8ZqzinVULR8LKjyHsNhi0IM9KzI3TiUmsP3g2fdmInccSSBuQVdLPg4eaR9KnYVn79NOZ3AaOrIM734ImQ/L/+iJSZCncZELhxkFs+Ab+95RxF+GB36Fso1u/5lIcfFQDks9Dn1lQuX2el2kL8ZeuMHtdDJNXHOBEQhIA/p6uDGgSwcAmERTzzsf+OeumwK9DIaQGPLYy/64rIkVedn5/F7LxqCJX1e0PNXqAJRXmDYKLZ2/9mvVTjGATVBUq3pn3NdqIv6crg1uUY9kLt/NOt5pElvAm/tIVPln8L03fWcJr/9txw347eaJGN3B2gxPbjaH5IiIFkMKNFE4mE3T6CAIjjRE88580llO4mSuX4J8JxnazZ7LXT6eAcHdxpnfDsiwa2pLP+9WlRmk/Ll1J5euVB2n53l8Mm7OFfSfP520RnoFQuYOxvXlG3l5LRCSHCt//8CJpPPyg51TjTsLuX2BtJvPVbJ4OF06BfxjU6J5vJeYFZycTHWuG8r8hzfhuUEMalytOitnC3A1HaPvRMh75bj2bY+LyroDafY1/t802FjgVESlgFG6kcCtVB+5809j+8xU4tjnjMakpsOoTY7vJkzZfXdxeTCYTzSsGMePh2/jx8SbcWS0EiwUW7DhBl89W0mfSPyz/9xQ271ZXoTV4Bxlhcd9i255bRMQGFG6k8Gv4MFTpZAzvnvsAXE6wfn7nT3DuoLE2VdT99qgwz0WVDWRS//osGtqCHvXK4OJkYvWBM9w/ZS13j1/Jb9uOZ1gDK8ecXaFmT2N7i5qmRKTgUbiRws9kgrs/NZqczh6AX5651v/GYoEV44ztho+Am5e9qswXFYJ9GduzNktfuJ0Hmkbg6erMtqPxPD5tI20+XMrMtYdJSknN/YVq9zH+3fMbXDqX+/OJiNiQwo04Bq9i0OMrY2j49nmw8Vtj/77FcGIbuHpDw8H2rTEflQ7wZFTn6qwcfgdPta6Iv6cr0acvMPyHbbR47y++XHYgw5pX2RJayxgOnpoM23+wXeEiIjagcCOOI6whtH7V2P79RWOyv5XjjI/rDTQCUBFTzNuNoW0rsXL4HbxyV1VC/Nw5kZDEW7/touk7S/jwzz2cSUzK2cnT7t6oaUpEChhN4ieOxWyGaT1g/2LwLQXnj4GTKzy9BfxL27s6u0tKSeWnTUf5YukBDpw2lnnwcHWid4OyDG5RjtIBnlk/2fkT8GFVY66hIRugRIU8qlpERJP4SVHm5ARdvzAW1jx/zNhXq5eCzVXuLs7c26AsC6/OlVOztD+Xr5iZusqYK2fo7M38eyKLc+X4hhgjp0B3b0SkQFG4EcfjEwTdvwRMxqPp0/auqMBJmytn/pCmfD+oEU3KG3Pl/LDxKG0/Wsbgb9ez6XAWOgqnNU1tnWXcNRMRKQDULCWOa/9fRpNJhTb2rqRQ2BwTx8S/97NgZ2z6YLPbyhXjsVYVaFGxBCaTKeOLrlyGsZUgKR4G/A8iW+Rv0SJSZGjhzEwo3Ihkbt/J83yx9AA/bjpKytW5caqX8uOxVuXpUCMUZ6f/hJz/PQ0bphozF3edkP8Fi0iRoHCTCYUbkaw5FneJycujmbH2MJeuGHPjRBT34pGW5elWtzTuLs7GgYfXwFd3GsPth+0Fdx87Vi0ijkrhJhMKNyLZc/ZCMt+sOsjUVQeJv2SsJRXs685DzSPp2ygcHzdn+LQenN0PXSZCnT52rlhEHJHCTSYUbkRy5kJSCjPWHmby8mhiEy4D4OfhQv/GETzu9ANeK9+ByJYwYL6dKxURR6RwkwmFG5HcSU4x89Omo0xcuj99rpzyrqdZ7PwUFkyYnt0O/mXsXKWIOBrNcyMiecbNxYleDcJYOLQlE67OlbP/SglWp1bDhIVfv/+IvVmdK0dEJA8o3IhIjjg7mehwda6caQ81YmuJDgBUOfErd360lIe+Wc+GQ1pUU0Tyn5qlRMQ2ks6T+n5FnFMu0TX5dTaZjeUYGkUW47FW5WlZKejGc+WIiGSBmqVEJP+5++Jc7W4Apkbto1f9Mrg6m1gTfZaBX6/jrk9W8Nu24xSxv6dExA4UbkTEdq4ux+C/fz7vdanC0udvZ1CzSDxdndl5PIHHp23ktf/txGxWwBGRvKNwIyK2E9kC/ErD5TjY8zulAjx5tVM1Vg2/g8dalQdg6qqDPD1rM8kpWotKRPKGwo2I2I6Ts7EKO8CWmem7A73deLF9FT7uXQcXJxP/23KMQd+sIzEpxU6FiogjU7gREduq3df4d99CSDxl9dQ9dUozZWADvNycWf7vafp++Q9nEpPsUKSIODKFGxGxraBKULoemFNg25wMT7esFMT0wbcR6OXK1iPx9Jy4mpizF+1QqIg4KoUbEbG9qx2L2TL9hk/XCQtgzqNNKB3gyYHTF+g+YRW7YxPysUARcWQKNyJiezW6g5MrxG6D2O03PKRCsA/zHmtCpRAfTp5PoufE1ayNPpvPhYqII1K4ERHb8yoGldsb21tm3PSwkv4ezH6kMfXCAzl/OYX7p6xh4c4T+VSkiDgqhRsRyRtpHYu3zobUm4+KCvBy4/tBjWhdJZikFDOPfLeeWesO51ORIuKIFG5EJG9UbAtexeHCSdi/JNNDPd2c+eL+evSoVwazBV6ct43P/tqn2YxFJEcUbkQkbzi7Qs2exnYmTVNpXJydeL9HLR5taUz29/6CPbz+i2YzFpHsU7gRkbyTNmpq969wKe6Wh5tMJoZ3qMIrd1UF4OuVB3l2tmYzFpHsUbgRkbwTWhuCq0FqEuz4Mcsve6h5OT66tzYuTiZ+3mzMZnxBsxmLSBYp3IhI3jGZrpvz5tZNU9frGlWGyQPq4+mq2YxFJHsUbkQkb9XqBSYniFkDZ/Zn66WtKgczfXAjAr1c2XJ1NuMj5zSbsYhkTuFGRPKWb0kof4exfd1imlkVVTaQOY82oZS/R/psxntiz9u4SBFxJAo3IpL30pumZoI5+52DKwT7MO/xJlQM9uFEQhI9J65i3UHNZiwiN6ZwIyJ5r8pd4O4H8Yfh58chKTHbpwj192TOo8ZsxgmXU7hv8hoWaTZjEbkBhRsRyXuuntBmtNH3ZssM+KIFHNuc7dOkzWZ8R9psxt9vYPb6GJuXKyKFm8KNiOSPBoNgwC/gVxrO7ofJbWD1Z9lupkqbzbh73TKkmi28MHcrE/7er9mMRSSdwo2I5J+IpvDoCqjSCcxXYMFLML0XJJ7K1mlcnZ0Y27MWj7QsB8C7f+zmzV93aTZjEQEUbkQkv3kVg3u/h7s+BBcP2LcQJjS55fpT/2UymRjRoWr6bMZTVkQzVLMZiwgKNyJiDyaT0Uw1+C8IqmosrvldV1g4ElKvZOtU189m/NPmYzz07XrNZixSxCnciIj9hFSDwUug/oPGxys/hq/awdkD2TpN16gyfHl1NuNle0/Rd/Iazl5IzoOCRaQwULgREfty84JOH0Gv78DDH45ugIktYOvsbJ3m9srBTBvciAAvV7bExNFj4iqOxl3Ko6JFpCBTuBGRgqHa3fDoSijbGJLPww+D4cdHISnrsxHXLRvI3EcbG7MZn7pA989XsfeEZjMWKWoUbkSk4AgIM4aLtxpx3Zw4LeHYpiyfokKwL3Mfa0KFYB9iEy7Tc+JqNhzSbMYiRYnCjYgULM4u0Go4DPwV/MpcnROnLawan+U5cUoFeDL30cbULRtA/KUr9Ju8hsW7NJuxSFGhcCMiBVN4E3h0+bU5cf58Gab3hMSTWXp5gJcb0x66jdsrB3H5ipmHv9vAHM1mLFIkKNyISMGVYU6cRTChaZbnxPF0c2ZS//p0q1uaVLOF5+duZeJSzWYs4ugUbkSkYMtsTpyUWw/3dnV24oOetXmkhTGb8Tu/7+YtzWYs4tDsHm4+++wzIiIi8PDwoFGjRqxduzbT48eNG0flypXx9PQkLCyMZ599lsuXL+dTtSJiNyHV4OG/oP4g4+NszIljMpkY0bEqL3WsAsDkFdE8N2cLV1I1m7GII7JruJk1axZDhw5l1KhRbNy4kdq1a9OuXTtOnrxxm/r06dMZPnw4o0aNYteuXUyZMoVZs2bx0ksv5XPlImIXrp7Q6UOjqcojAI5tzNacOA+3KM8HPWvj7GTix01HGfztei4mazZjEUdjstix8blRo0Y0aNCA8ePHA2A2mwkLC+PJJ59k+PDhGY4fMmQIu3btYvHixen7nnvuOdasWcOKFSuydM2EhAT8/f2Jj4/Hz8/PNm9ERPJfXAz88DAcXmV8XLsPdHwf3H1v+dK/dp/ksWkbuHzFTJ2wAL4e2IBAb7c8LlhEciM7v7/tducmOTmZDRs20KZNm2vFODnRpk0bVq9efcPXNGnShA0bNqQ3XR04cIDffvuNjh073vQ6SUlJJCQkWD1ExAEEhMGA//1nTpwWWZoT5/YqwUx76Db8PV3ZrNmMRRyO3cLN6dOnSU1NJSQkxGp/SEgIsbGxN3xN3759ef3112nWrBmurq6UL1+eVq1aZdosNWbMGPz9/dMfYWFhNn0fImJHGebEOXB1TpxPbzknTr1wYzbjUH8P9p+6QI8Jq/hXsxmLOAS7dyjOjr///pu3336bzz//nI0bN/LDDz/w66+/8sYbb9z0NSNGjCA+Pj79EROjeS5EHE7anDhVO1+dE+eVLM2JUzHEl3lXZzM+Hn+ZHhNXs+HQuXwqWkTyit3CTYkSJXB2dubECetZQ0+cOEHJkiVv+JpXX32V+++/n4ceeoiaNWvStWtX3n77bcaMGYP5Jn+lubu74+fnZ/UQEQfkVcxYfLPTR9Zz4uxbnOnLSgV4MueRxkSlz2b8D0t2azZjkcLMbuHGzc2NevXqWXUONpvNLF68mMaNG9/wNRcvXsTJybpkZ2dnAE3KJSLGnDj1H4SH/4bgasacON93gz9fzXROnEBvN6Y91IhWV2czHvztBuZtOJJ/dYuITdm1WWro0KF8+eWXfPPNN+zatYvHHnuMCxcu8MADDwDQv39/RowYkX58586dmTBhAjNnziQ6OpqFCxfy6quv0rlz5/SQIyJCcFUYvAQaPGR8vOoT+OpOOLP/pi/xcnPhy/716RZlzGb83JwtTFp28+NFpOBysefF7733Xk6dOsXIkSOJjY2lTp06/PHHH+mdjA8fPmx1p+aVV17BZDLxyiuvcPToUYKCgujcuTNvvfWWvd6CiBRUrp5w1wdQrhX8PMQYRfVFC6PZqlavG7/E2YmxPWtTwtedScsO8PZvuzmdmMzw9lVwcjLlb/0ikmN2nefGHjTPjUgRFH8E5g3O1pw4Xyzdz5jfdwPQrW5p3u1eC1fnQjUGQ8ShFIp5bkRE8o1/GRj4C7R6Kctz4jzSsjxjr85m/MPGozys2YxFCg2FGxEpGpycodWLMPC3LM+J06NeGb7sXw8PVyf+2nOKfpPXcO7CrRfrFBH7UrgRkaIlvDE8tgKq3n1tTpxpPW46J84dVUKY9lAj/D1d2XQ4jp5frOaYZjMWKdAUbkSk6PEMhF7fQqdxxpw4+xfDhCbG3Dg3UC+8GHMebUxJPw/2nUyk+4RVzNtwhKSU1PytW0SyRB2KRaRoO7kL5j4IJ3caHzd5Eu4YCS4ZF9I8GneJ/lPWsP/UBQCCfN25/7Zw+jUqS3Ef9/ysWqTIyc7vb4UbEZErl4zmqXWTjY9LRUH3KVC8fIZDEy5f4bvVh/h29UFOJCQB4O7iRNeo0jzYLJJKIbdelVxEsk/hJhMKNyJyU7t+gZ+fgMtx4OYDd30Ite+94aHJKWZ+23acKSui2XY0Pn1/84olGNQskpaVgjCZNDeOiK0o3GRC4UZEMhV/BH54GA6tND6u1RvuGnvTOXEsFgvrDp5jyooD/LnzBGn/o1YI9uHBppF0q1saD1fNoC6SWwo3mVC4EZFbMqfC8g/g7zFgMUOxckYzVem6mb7s8JmLTF11kNnrY0hMMubECfRypV+jcPo3DifYzyM/qhdxSAo3mVC4EZEsO7Qa5j0ECUfAyRXajILbngCnzAeaJly+wux1MUxddZAj54xh467OJjrVKsWgZpHUKO2fH9WLOBSFm0wo3IhItlw6B/Ofgl3zjY/L3wFdJoJvyC1fmpJqZuHOE0xZEc36Q+fS9zeMLMagZpG0qRqCs9asEskShZtMKNyISLZZLLDxG/h9OKRcAq8SUG+gsUZViQpZOsWWmDimrIjmt23HSTEb/+2GF/diYJMIetYPw8fdrusYixR4CjeZULgRkRw7ufvqnDg7ru0r0wBq94bq3cCr2C1PcTz+Et+uPsT0NYeJv3QFAF8PF3o3CGNAkwjKBHrlVfUihZrCTSYUbkQkV1KSYfcvsGWmMaOx5eosxc5uUKm9cTenYltwds30NBeTU5i38Shfr4jmwGljUkBnJxPtq5fkwWaR1AsPzOt3IlKoKNxkQuFGRGzm/AnYPtdYZTx227X9XsWhZk/jjk5oHchkvhuz2cLfe08yZUU0K/edSd9fJyyAB5tF0qFGSVydtVKOiMJNJhRuRCRPxG43Qs62OZB44tr+oKpGyKnVC/xKZXqKXccT+GpFND9vPkZyqrFSeSl/D/o3iaBPg7L4e2V+N0jEkSncZELhRkTyVGoKHPjLCDq7f4WUy1efMEG5VlCnL1S5C9y8b3qKU+eTmLbmEN//c4jTickAeLk506NeGR5oGklkiZu/VsRRKdxkQuFGRPLN5XjY+TNsngGHV13b7+YD1e4x+ueEN73pvDmXr6Qyf8sxvloRze7Y84DRwtW6SjAPNoukcbniWuJBigyFm0wo3IiIXZyNhq2zjDs65w5e2+8fBrXuzXRYucViYdX+M0xZEc2S3SfT91cN9WNQs0g61w7F3UVLPIhjU7jJhMKNiNiVxQIxa2DzdNjxEyRdW3QzK8PK959K5OuV0czbcJRLV4yRWiV83OnfOJx+jcpS3Mc9H96ESP5TuMmEwo2IFBhXLsGe3427OfsWZ2tYedzFZGasjeGbVQeJTTD69bi5ONG1TmkebBZJ5ZI3XuhTpLBSuMmEwo2IFEg5HFZ+JdXMb9uO89WKaLYcuXYXqHnFEjzYLJKWFYNw0hIP4gAUbjKhcCMiBV7asPKts+HCtT42BFW5Oqz83gzDyi0WCxsOnWPKimgW7Ijl6goPlA/y5sFmkXSLKoOnm/rlSOGlcJMJhRsRKTRyOKw85uxFvll1kFnrYjiflAJAgJcr/RqVpX/jCEL8PPL3fYjYgMJNJhRuRKRQuhxvdEDeMjPLw8rPX77CnPVH+HpVNDFnLwHg6myiU61SPNg0kppl/PP5TYjknMJNJhRuRKTQy+aw8lSzhYU7T/DVimjWHjybvr9hRDH6NwnnzmolcXPREg9SsCncZELhRkQchtWw8h8hKeHaczcZVr7tSDxTVhzgl63HSbnaMSfI153eDcLo07AspQI88/tdiGSJwk0mFG5ExCFduQR7fru6Wvmth5WfSLjMtH8OMWNdDKfOJwHgZII7qoRwf+NwmlcooVFWUqAo3GRC4UZEHF7asPLNM+BE5sPKr6SaWbjzBN+tPsTqA9dWJQ8v7kXfhmXpWT+MYt5u+f8eRP5D4SYTCjciUqTEbjPu5txoWHmte6FcSwipCS5u7DuZyLQ1h5i74QjnLxujrNxcnOhUM5R+t4VTt2yA1rISu1G4yYTCjYgUSTcdVg64eECpKKOfTlgjLobU5X/7U/j+n8NsO3ptYsCqoX7cf1s499Qphbe7ix3ehBRlCjeZULgRkSIvbVj57l/gyDq4dC7jMQHhENaQIz41mHOiFF/u9eJiinHXxsfdhW51S3PfbeFUCtEyD5I/FG4yoXAjInIdiwXO7DNGXcWsNcLOyV2A9a8Gi6sXsd5VWXIhgr8uRLDRXJGz+NEwshj33RZO++oaTi55S+EmEwo3IiK3cDkejm4wwk7MWjiy3nr18qsOWkqywVyBTeaKHPCoRt0GTejdqBxlAr3sULQ4OoWbTCjciIhkk9kMp/fCkbVX7/Csg9N7MhyWaPFgq6U8ZwNrU7Z2K6o3bIOzT3E7FCyOSOEmEwo3IiI2cOkcHNkAR9ZijlmL+fBaXFIuZDjsnGcEnuVuwyPyNghraIzSctICnpJ9CjeZULgREckD5lQ4tZtTu5ZzdNsy/M9sIpJjGQ6zuPliKlPfCDplGkKZ+uAZkP/1SqGjcJMJhRsRkbx3KTmVBet3svWfhQSe3UJd07/UdtqPj+lyxoNLVDbCTlrgKVHJagFQEVC4yZTCjYhI/tp6JI7v/znEL1uOEJ5yiHpOe2ngso+m7tGUSD6S8QUe/lC6PoQ1grAGxraH/r8u6hRuMqFwIyJiH/EXrzBv4xG+X3OIA6eM/jnFSKBXyeN0CzpKhaRdOB3fBFcu/ueVJgiuenWSwYZG6CleATRbcpGicJMJhRsREfuyWCys3n+G79cc4s8dJ9JXJy/u7ca99UPpH5lIyYRt1+beiTuU8SSegUbYKZPWnNUA3DQE3ZEp3GRC4UZEpOA4kXCZmWtjmLH2MLEJRn8ckwlaVQrivtvCaVU5GOcLJ43JBY+sNYahH9tovXwEGKufl2kIkS2MR+l64KIFPx2Jwk0mFG5ERAqelFQzi3ef5Pt/DrH839Pp+0sHeNK3UVnubRBGCR/3qwcnG6udx1wNPIf/gYSj1id09YKyja+FndDaGoJeyCncZELhRkSkYIs+fYHpaw4xe/0R4i9dAcDV2UT7GqHcf1s4DSICrVcnt1jg7AGIXnbtcfG09Und/SGi2bWwE1xVfXYKGYWbTCjciIgUDpevpPLL1uN8/88hNsfEpe+vFOLDfbeF0zWqNL4erhlfaLEY62OlBZ2DKzIuH+EdBBHNr4WdYuUUdgo4hZtMKNyIiBQ+24/G8/0/h/h58zEuXUkFwMvNmS5RpbmvUThVQ32t7+Zcz5wKx7dcCzuHV2cckeVX5lrQiWwB/qXz+B1JdincZELhRkSk8Iq/dIUfNh7h+38Osf/UteUegn3diSobQN2ygUSVDaRmaX883W7SxyYl2VgYNHqpEXZi1oL5ivUxxcpbhx3vEnn4riQrFG4yoXAjIlL4WSwW/jlw9upw8liupFr/KnN2MlE11JeosECiygYQVTaQiOJeN767k3wRYv65dmfn2CawmK2PCa4O5VoaQSe8iTHRoOQrhZtMKNyIiDiWS8mpbD8Wz8ZD59h0OI6Nh89x8nxShuMCvVypE2YEnaiyAdQOC8DvRn12LsfDoVXXws6J7dbPm5ygVNS1uzpht2mOnXygcJMJhRsREcdmsVg4Hn+ZTYfj2HT4HJti4th2NJ7kFOu7MSYTVAz2sbq7UyHYB2en/9zduXAaDi6/FnbO7LN+3snVmEgwfY6d+ppjJw8o3GRC4UZEpOhJTjGz63gCGw8bd3c2xZwj5uylDMf5uLtQO8w/PfDUCQugeNr8Omnij14LOweWQsJ/1sdy9YKyt103x04dzbFjAwo3mVC4ERERgFPnk9gcc/XuzuE4thyJ42Jyaobjwot7EXW1Oatu2UCqhPri6nx11XKLBc5FXws6N51jp+m1sBNUVaue54DCTSYUbkRE5EZSUs38ezIxvd/OpsPnrEZkpXF3caJWGX+j787V0FPS38N4Mitz7HiVgMi0OXZaao6dLFK4yYTCjYiIZFX8xStsPnLt7s6mw+dIuJyS4bhQfw+j387V5qwapf3xcHXO4hw7pa/d1SkVZax47nyDjs5FnMJNJhRuREQkp8xmC9FnLqQHnY2H49gTm4D5P79JXZ1NVAv1Sx+ZFRUWSFgxT0ypV67OsXM17BxZC6nJ1i92coUSFSG4mrFMRNq/AeFFujlL4SYTCjciImJLF5JS2Hoknk0x1+7unE5MznBccW+39FFZUWEB1AoLwMeUDDFrjKBzaCWc2AnJ5298IVcvCKpyXeipCiHVwSekSDRrKdxkQuFGRETyksVi4ci5S2yKuXZ3Z+ex+AwTDTqZoFKIb/qdnbrhAZQv4Y0p4YjRb+fkzmv/ntoLqRnn7gHAM9A68KRtewbmw7vNPwo3mVC4ERGR/Hb5Sio7jiWkz7uz+XAcR+MyDkUvHeDJndVDaF+9JPUjil2bcyc1xVj5/PrAc3IXnN2fcTblNL6lMgaeoMrg5p2H7zTvKNxkQuFGREQKghMJl9Pn3Nl0OI4tMXEkXTfRYHFvN9pWC6FdjZI0KV8cd5cbzJVz5TKc3ntd4LkaeuJjbnJVEwRGXAs7IdWM7ULQiVnhJhMKNyIiUhBdvpLKsr2n+GNHLIt3nST+0rXFPH3dXbi9SjDta5SkZaUgvN1dbnGyeDi1x/pOz4mdGefgSZPeifk/d3oCIgpMJ2aFm0wo3IiISEF3JdXMmgNn+WPHcf7cccJqrSx3FyeaVwyifY2StKkaTIBXNpZ6SDyVsWnr5K7sdWIOrga+JfO9E7PCTSYUbkREpDAxmy1sioljwY5Y/tgey+Gz1+bJcXYycVu5YrSvXpI7q5ckxM8j+xewWCD+iHWz1q06MXsEZGzaCqoCXsVy9iazQOEmEwo3IiJSWFksFnbHnueP7bEs2BHL7ljrOy5RZQNoX70k7aqXJKJELjsOp6YYS0ukBZ4TO7LQiTnUCDxlGsDtL+Xu+v+hcJMJhRsREXEUB09fYMEOI+hsPBxn9VyVkr60q16S9jVKUqWkLyZbNSNl6MR89d/rOzGHNYJBf9rmelcp3GRC4UZERBzRiYTL/LkjlgU7TrD6wBlSr5s2uWwxL9rXMO7oRIUF4OSUB/1lLifAqd1G0HH3hRrdbXp6hZtMKNyIiIiji7uYzKJdJ1mwI5Zle09ZDTEP9nW/OpdOKI3KFbu2wnkBp3CTCYUbEREpSi4kpbB07ykW7Ihlya6TnE+6tvCnv6crrasG0756SVpUCjIW+yygFG4yoXAjIiJFVVJKKqv2n+HPHbH8ueMEZy5cWwPL09WZVpWNIea3VwnGz6NgTeqncJMJhRsRERFINVtYf/AsC3acYMGOWKvlIFydTTQpX4L2NUrStloIJXzc7VipITu/v+3e0PbZZ58RERGBh4cHjRo1Yu3atZkeHxcXxxNPPEFoaCju7u5UqlSJ3377LZ+qFRERcQzOTiYalSvOyM7VWPHi7fxvSDOG3F6BCsE+XEm1sHTvKUb8sI0Gby2i18TVTFkRzZFzF2994gLArnduZs2aRf/+/Zk4cSKNGjVi3LhxzJkzhz179hAcHJzh+OTkZJo2bUpwcDAvvfQSpUuX5tChQwQEBFC7du0sXVN3bkRERDK372Ri+hDzrUfirZ6rUdqP9leHmFcI9s23mgpNs1SjRo1o0KAB48ePB8BsNhMWFsaTTz7J8OHDMxw/ceJE3n//fXbv3o2ra87aAhVuREREsu5o3CX+vDo78rqDZ7luhDnlgrzTJw2sVcbfdnPp3EChCDfJycl4eXkxd+5cunTpkr5/wIABxMXF8fPPP2d4TceOHSlWrBheXl78/PPPBAUF0bdvX1588UWcnW/cwzspKYmkpGvTRyckJBAWFqZwIyIikk1nEpNYtOsEf2yPZeW+MySnXhtiXsrfgzuvBp0GEYG42HiIeXbCzS2WFc07p0+fJjU1lZCQEKv9ISEh7N69+4avOXDgAEuWLKFfv3789ttv7Nu3j8cff5wrV64watSoG75mzJgxvPbaazavX0REpKgp7uPOvQ3Kcm+Dspy/fIW/9pxiwfZY/tpzkmPxl5m66iBTVx0korgXfw1rlad3cjJjt3CTE2azmeDgYCZNmoSzszP16tXj6NGjvP/++zcNNyNGjGDo0KHpH6fduREREZGc8/Vw5e7apbi7dikuX0llxb+n+WNHLIt2naBOWIDdgg3YMdyUKFECZ2dnTpw4YbX/xIkTlCxZ8oavCQ0NxdXV1aoJqmrVqsTGxpKcnIybW8Zl393d3XF3t/8QNhEREUfl4epMm2ohtKkWQkqqmYTLKbd+UR6y21BwNzc36tWrx+LFi9P3mc1mFi9eTOPGjW/4mqZNm7Jv3z7M5mttfHv37iU0NPSGwUZERETyl4uzE8W87fs72a7z3AwdOpQvv/ySb775hl27dvHYY49x4cIFHnjgAQD69+/PiBEj0o9/7LHHOHv2LE8//TR79+7l119/5e233+aJJ56w11sQERGRAsaufW7uvfdeTp06xciRI4mNjaVOnTr88ccf6Z2MDx8+jJPTtfwVFhbGggULePbZZ6lVqxalS5fm6aef5sUXX7TXWxAREZECRssviIiISIFXqJZfEBEREbElhRsRERFxKAo3IiIi4lAUbkRERMShKNyIiIiIQ1G4EREREYeicCMiIiIOReFGREREHIrCjYiIiDgUhRsRERFxKHZdW8oe0labSEhIsHMlIiIiklVpv7ezsmpUkQs358+fB4xFOEVERKRwOX/+PP7+/pkeU+QWzjSbzRw7dgxfX19MJpNNz52QkEBYWBgxMTFalLMA0NejYNHXo2DR16Pg0dckcxaLhfPnz1OqVCmcnDLvVVPk7tw4OTlRpkyZPL2Gn5+fvjELEH09ChZ9PQoWfT0KHn1Nbu5Wd2zSqEOxiIiIOBSFGxEREXEoCjc25O7uzqhRo3B3d7d3KYK+HgWNvh4Fi74eBY++JrZT5DoUi4iIiGPTnRsRERFxKAo3IiIi4lAUbkRERMShKNyIiIiIQ1G4sZHPPvuMiIgIPDw8aNSoEWvXrrV3SUXWmDFjaNCgAb6+vgQHB9OlSxf27Nlj77LkqnfeeQeTycQzzzxj71KKrKNHj3LfffdRvHhxPD09qVmzJuvXr7d3WUVSamoqr776KpGRkXh6elK+fHneeOONLK2fJDencGMDs2bNYujQoYwaNYqNGzdSu3Zt2rVrx8mTJ+1dWpG0dOlSnnjiCf755x8WLlzIlStXuPPOO7lw4YK9Syvy1q1bxxdffEGtWrXsXUqRde7cOZo2bYqrqyu///47O3fu5IMPPiAwMNDepRVJ7777LhMmTGD8+PHs2rWLd999l/fee49PP/3U3qUVahoKbgONGjWiQYMGjB8/HjDWrwoLC+PJJ59k+PDhdq5OTp06RXBwMEuXLqVFixb2LqfISkxMpG7dunz++ee8+eab1KlTh3Hjxtm7rCJn+PDhrFy5kuXLl9u7FAE6depESEgIU6ZMSd/XvXt3PD09+f777+1YWeGmOze5lJyczIYNG2jTpk36PicnJ9q0acPq1avtWJmkiY+PB6BYsWJ2rqRoe+KJJ7jrrrusflYk/82fP5/69evTs2dPgoODiYqK4ssvv7R3WUVWkyZNWLx4MXv37gVgy5YtrFixgg4dOti5ssKtyC2caWunT58mNTWVkJAQq/0hISHs3r3bTlVJGrPZzDPPPEPTpk2pUaOGvcspsmbOnMnGjRtZt26dvUsp8g4cOMCECRMYOnQoL730EuvWreOpp57Czc2NAQMG2Lu8Imf48OEkJCRQpUoVnJ2dSU1N5a233qJfv372Lq1QU7gRh/bEE0+wfft2VqxYYe9SiqyYmBiefvppFi5ciIeHh73LKfLMZjP169fn7bffBiAqKort27czceJEhRs7mD17NtOmTWP69OlUr16dzZs388wzz1CqVCl9PXJB4SaXSpQogbOzMydOnLDaf+LECUqWLGmnqgRgyJAh/PLLLyxbtowyZcrYu5wia8OGDZw8eZK6deum70tNTWXZsmWMHz+epKQknJ2d7Vhh0RIaGkq1atWs9lWtWpV58+bZqaKi7fnnn2f48OH07t0bgJo1a3Lo0CHGjBmjcJML6nOTS25ubtSrV4/Fixen7zObzSxevJjGjRvbsbKiy2KxMGTIEH788UeWLFlCZGSkvUsq0lq3bs22bdvYvHlz+qN+/fr069ePzZs3K9jks6ZNm2aYGmHv3r2Eh4fbqaKi7eLFizg5Wf8qdnZ2xmw226kix6A7NzYwdOhQBgwYQP369WnYsCHjxo3jwoULPPDAA/YurUh64oknmD59Oj///DO+vr7ExsYC4O/vj6enp52rK3p8fX0z9Hfy9vamePHi6gdlB88++yxNmjTh7bffplevXqxdu5ZJkyYxadIke5dWJHXu3Jm33nqLsmXLUr16dTZt2sSHH37Igw8+aO/SCjUNBbeR8ePH8/777xMbG0udOnX45JNPaNSokb3LKpJMJtMN93/99dcMHDgwf4uRG2rVqpWGgtvRL7/8wogRI/j333+JjIxk6NChDB482N5lFUnnz5/n1Vdf5ccff+TkyZOUKlWKPn36MHLkSNzc3OxdXqGlcCMiIiIORX1uRERExKEo3IiIiIhDUbgRERERh6JwIyIiIg5F4UZEREQcisKNiIiIOBSFGxEREXEoCjciUuSZTCZ++ukne5chIjaicCMidjVw4EBMJlOGR/v27e1dmogUUlpbSkTsrn379nz99ddW+9zd3e1UjYgUdrpzIyJ25+7uTsmSJa0egYGBgNFkNGHCBDp06ICnpyflypVj7ty5Vq/ftm0bd9xxB56enhQvXpyHH36YxMREq2O++uorqlevjru7O6GhoQwZMsTq+dOnT9O1a1e8vLyoWLEi8+fPz9s3LSJ5RuFGRAq8V199le7du7Nlyxb69etH79692bVrFwAXLlygXbt2BAYGsm7dOubMmcOiRYuswsuECRN44oknePjhh9m2bRvz58+nQoUKVtd47bXX6NWrF1u3bqVjx47069ePs2fP5uv7FBEbsYiI2NGAAQMszs7OFm9vb6vHW2+9ZbFYLBbA8uijj1q9plGjRpbHHnvMYrFYLJMmTbIEBgZaEhMT05//9ddfLU5OTpbY2FiLxWKxlCpVyvLyyy/ftAbA8sorr6R/nJiYaAEsv//+u83ep4jkH/W5ERG7u/3225kwYYLVvmLFiqVvN27c2Oq5xo0bs3nzZgB27dpF7dq18fb2Tn++adOmmM1m9uzZg8lk4tixY7Ru3TrTGmrVqpW+7e3tjZ+fHydPnszpWxIRO1K4ERG78/b2ztBMZCuenp5ZOs7V1dXqY5PJhNlszouSRCSPqc+NiBR4//zzT4aPq1atCkDVqlXZsmULFy5cSH9+5cqVODk5UblyZXx9fYmIiGDx4sX5WrOI2I/u3IiI3SUlJREbG2u1z8XFhRIlSgAwZ84c6tevT7NmzZg2bRpr165lypQpAPTr149Ro0YxYMAARo8ezalTp3jyySe5//77CQkJAWD06NE8+uijBAcH06FDB86fP8/KlSt58skn8/eNiki+ULgREbv7448/CA0NtdpXuXJldu/eDRgjmWbOnMnjjz9OaGgoM2bMoFq1agB4eXmxYMECnn76aRo0aICXlxfdu3fnww8/TD/XgAEDuHz5Mh999BHDhg2jRIkS9OjRI//eoIjkK5PFYrHYuwgRkZsxmUz8+OOPdOnSxd6liEghoT43IiIi4lAUbkRERMShqM+NiBRoajkXkezSnRsRERFxKAo3IiIi4lAUbkRERMShKNyIiIiIQ1G4EREREYeicCMiIiIOReFGREREHIrCjYiIiDgUhRsRERFxKP8H+tm+FpKgfW4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lstm.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m111/111\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 53ms/step\n"
     ]
    }
   ],
   "source": [
    "lstm_pred = lstm.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Long Short-Term Memory performance evaluation:\n",
      "\n",
      "accuracy\t0.7736753100338218.\n",
      "precision\t0.7718249779434169.\n",
      "recall\t\t0.7659803961995385.\n",
      "f1-score\t0.7649413266332744.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, lstm_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{lstm.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.85      0.79      0.82       280\n",
      "         pdf       0.96      0.96      0.96       335\n",
      "          ps       0.92      0.89      0.90       311\n",
      "         xls       0.78      0.80      0.79       288\n",
      "         ppt       0.78      0.80      0.79       337\n",
      "         swf       0.55      0.71      0.62       283\n",
      "         gif       0.75      0.76      0.76       301\n",
      "         jpg       0.63      0.67      0.65       276\n",
      "         png       0.56      0.37      0.45       260\n",
      "        html       0.89      0.73      0.80       292\n",
      "         txt       0.74      0.91      0.81       301\n",
      "         xml       0.84      0.81      0.82       284\n",
      "\n",
      "    accuracy                           0.77      3548\n",
      "   macro avg       0.77      0.77      0.76      3548\n",
      "weighted avg       0.78      0.77      0.77      3548\n",
      "\n"
     ]
    }
   ],
   "source": [
    "lstm_report = classification_report(y_test, lstm_pred, target_names=CLASS_NAMES)\n",
    "print(lstm_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lstm_cm = confusion_matrix(y_test, lstm_pred)\n",
    "plot_confusion_matrix(lstm_cm, CLASS_NAMES)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv",
   "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": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}