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| import { Component } from "react"; | |
| import logo from "./logo.svg"; | |
| import "./App.css"; | |
| class App extends Component { | |
| constructor() { | |
| super(); | |
| this.state = { |
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| server { | |
| listen 80; | |
| server_name www.travens-ai.my.id; | |
| location /static { | |
| alias /root/flask-vm/static; | |
| } | |
| location / { | |
| proxy_pass http://127.0.0.1:5000; |
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| sudo apt-get update | |
| sudo apt-get install software-properties-common | |
| sudo add-apt-repository universe | |
| sudo add-apt-repository ppa:certbot/certbot | |
| sudo apt-get update | |
| sudo apt-get install python3-certbot-nginx | |
| sudo certbot --nginx |
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| function ClickConnect() { | |
| console.log('Working') | |
| document | |
| .querySelector('#top-toolbar > colab-connect-button') | |
| .shadowRoot.querySelector('#connect') | |
| .click() | |
| } | |
| setInterval(ClickConnect, 60000) |
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| alay_dict = pd.read_csv('new_kamusalay.csv', names=['original', 'replacement'], encoding='latin-1') | |
| alay_dict_map = dict(zip(alay_dict['original'], alay_dict['replacement'])) | |
| def normalize_alay(text): | |
| return ' '.join([alay_dict_map[word] if word in alay_dict_map else word for word in text.split(' ')]) | |
| print("normalize_alay: ", normalize_alay("aamiin adek abis")) | |
| # normalize_alay: amin adik habis |
| Asset Name | Asset Type | IP Address | Operating System | Software Version | Threat Type | Vulnerability | Impact | Likelihood | Mitigation Strategy | Last Patch Date | Number of Users | Number of Admins | Number of Connections | Location | Backup Frequency | Backup Type | Backup Location | Encryption Type | Compliance | Logging | Auditing | Incident Response | Business Continuity | Risk Label |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Server 1 | Physical | 192.168.0.1 | Windows Server 2019 | 10.0.177 |
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| import os | |
| from keras.models import load_model | |
| from PIL import Image, ImageOps | |
| import numpy as np | |
| # Load the model | |
| model = load_model("keras_Model.h5", compile=False) | |
| # Load the labels | |
| class_names = open("labels.txt", "r").readlines() |
