Artificial Intelligence and Machine Learning最新文献

Detecting Depression in Social Media using Machine Learning 使用机器学习检测社交媒体中的抑郁症

Artificial Intelligence and Machine Learning Pub Date : 2022-07-23 DOI: 10.5121/csit.2022.121223

Ruoxi Ding, Yu Sun

{"title":"Detecting Depression in Social Media using Machine Learning","authors":"Ruoxi Ding, Yu Sun","doi":"10.5121/csit.2022.121223","DOIUrl":"https://doi.org/10.5121/csit.2022.121223","url":null,"abstract":"Social Media Depression Detection is an Intelligent System to automate the detection of Youth Depression with social media (Instagram) using AI and Deep Learning. The student is the targeted group because most students with depression express themselves on social media rather than seeking help from doctors. This app gathers captions and images from the user's personal Instagram profile through web scraping using Instagram private API to check whether or not the posts are depressive. The google cloud dataset supports the captions and pictures analysis performed by the app [6]. Caption sentiment analysis depends on sentiment analysis, and the pictures analysis depends on classifying images by custom labels. The app reports the image and the caption analysis results back to the user. Python is used for the back-end functionality, while Dart and Flutter are used for the front-end. It was tested by 2 experiments, the first experiments returned the feedback of 15 students demonstrates that the program has the capability of detecting depression through the captions with relatively high accuracy. The second experiment of testing the app functionality on the same account demonstrates that the program is stable and consistent. The purpose of the app is to detect depression at an early stage to prevent the condition from worsening.","PeriodicalId":174755,"journal":{"name":"Artificial Intelligence and Machine Learning","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124826090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Online Graphical User Interface Application to Remove Barriers in the Process of Learning Neural Networks and Deep Learning Concepts Using Tensorflow 一个在线图形用户界面应用程序，以消除使用Tensorflow学习神经网络和深度学习概念过程中的障碍

Artificial Intelligence and Machine Learning Pub Date : 2022-07-23 DOI: 10.5121/csit.2022.121215

Justin D. Li, Yu Sun

引用次数: 0

ChatForSenior: An Intelligent ChatBot Communication System for Depression Relief using Artificial Intelligence and Natural Language Processing ChatForSenior:一种基于人工智能和自然语言处理的抑郁症智能聊天机器人通信系统

Artificial Intelligence and Machine Learning Pub Date : 2022-07-23 DOI: 10.5121/csit.2022.121221

Hanwen Mai, Yu Sun

引用次数: 0

Survey of Secure Network Protocols: United States Related Domains 安全网络协议调查:美国相关领域

Artificial Intelligence and Machine Learning Pub Date : 2022-07-23 DOI: 10.5121/csit.2022.121207

DeJean Dunbar

{"title":"Survey of Secure Network Protocols: United States Related Domains","authors":"DeJean Dunbar","doi":"10.5121/csit.2022.121207","DOIUrl":"https://doi.org/10.5121/csit.2022.121207","url":null,"abstract":"Over time, the HTTP Protocol has undergone significant evolution. HTTP was the internet's foundation for data communication. When network security threats became prevalent, HTTPS became a widely accepted technology for assisting in a domain’s defense. HTTPS supported two security protocols: secure socket layer (SSL) and transport layer security (TLS). Additionally, the HTTP Strict Transport Security (HSTS) protocol was included to strengthen the HTTPS protocol. Numerous cyber-attacks occurred in the United States, and many of these attacks could have been avoided simply by implementing domains with the most up-to-date HTTP security mechanisms. This study seeks to accomplish two objectives: 1. Determine the degree to which US-related domains are configured optimally for HTTP security protocol setup; 2. Create a generic scoring system for a domain's network security based on the following factors: SSL version, TLS version, and presence of HSTS to easily determine where a domain stands. We found through our analysis and scoring system incorporation that US-related domains showed a positive trend for secure network protocol setup, but there is still room for improvement. In order to safeguard unwanted cyber-attacks, current HTTP domains need to be extensively investigated to identify if they possess security-related components. Due to the infrequent occurrence of HSTS in the evaluated domains, the computer science community necessitates further HSTS education.","PeriodicalId":174755,"journal":{"name":"Artificial Intelligence and Machine Learning","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128448985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-View Human Tracking and 3D Localization in Retail 零售业中的多视角人体跟踪和3D定位

Artificial Intelligence and Machine Learning Pub Date : 2022-07-23 DOI: 10.5121/csit.2022.121214

Akash Jadhav

引用次数: 0

Learning Structured Information from Small Datasets of Heterogeneous Unstructured Multipage Invoices 从异构非结构化多页发票的小数据集中学习结构化信息

Artificial Intelligence and Machine Learning Pub Date : 2022-07-23 DOI: 10.5121/csit.2022.121220

David Emmanuel Katz, C. Guyeux, A. Haimovici, Bastian Silva, Lionel Chamorro, Raul Barriga Rubio, Mahuna Akplogan

引用次数: 0

Crypto your Belongings by Two Pin Authentication using Ant Algorithm based Technique 使用基于蚂蚁算法的技术对您的物品进行双Pin认证

Artificial Intelligence and Machine Learning Pub Date : 2022-07-23 DOI: 10.5121/csit.2022.121210

Janaki Raman Palaniappan

{"title":"Crypto your Belongings by Two Pin Authentication using Ant Algorithm based Technique","authors":"Janaki Raman Palaniappan","doi":"10.5121/csit.2022.121210","DOIUrl":"https://doi.org/10.5121/csit.2022.121210","url":null,"abstract":"Everyone realize data is one of the important strategic for any company to run and win the business. Let it be a mobile apps, websites and so on, there are more chances that our personal data like images, videos, texts get expose while we share across for different purposes. Even though the company says app, website forms are encrypted, the said company itself uses the data internally for their business development. This research presents how one can secure own’s data themselves before sending. There are many cryptography methods that has evolved from time to time. Upon researching and analyzing, I present a unique method to encrypt and decrypt the data, using combination of techniques such as Cryptographic technique, ANT Algorithm based formula and logic gates that would provide stronger protection to the data. Secure your images, videos with a 2-pin authentication and protection to encrypt and decrypt the data. A user must provide 2 different symmetric pins to encrypt and decrypt, where first pin shall be up to 4-digit secret pin and a second pin is a single digit pin. Single digit pin acts on how many stages the encryption takes place. The proposed method had been experimented on several images and videos. This study reveals, A combination of secret keys, ANT algorithm and Logic gates makes difficult for anyone to hack the data. This unique methodology helps us to protect our data more safely at source device itself.","PeriodicalId":174755,"journal":{"name":"Artificial Intelligence and Machine Learning","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131084092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Data-Driven Mobile Community Application for Book Recommendation and Personalization using AI and Machine Learning 一个数据驱动的移动社区应用程序，使用人工智能和机器学习进行图书推荐和个性化

Artificial Intelligence and Machine Learning Pub Date : 2022-07-23 DOI: 10.5121/csit.2022.121218

Lulu Zha

引用次数: 0

Are your Sensitive Inputs Secure in Android Applications? 你的敏感输入在Android应用程序中安全吗?

Artificial Intelligence and Machine Learning Pub Date : 2022-07-23 DOI: 10.5121/csit.2022.121206

Trishla Shah, Raghav V. Sampangi, Angela Siegel

{"title":"Are your Sensitive Inputs Secure in Android Applications?","authors":"Trishla Shah, Raghav V. Sampangi, Angela Siegel","doi":"10.5121/csit.2022.121206","DOIUrl":"https://doi.org/10.5121/csit.2022.121206","url":null,"abstract":"Android applications may request for users’ sensitive information through the GUI. Developer guidelines for designing applications mandate that information must be masked/encrypted before storing or leaving the system. However not all applications adhere to the guidelines. As a prerequisite to tracking sensitive input data, it is essential to identify the widgets that request it. Previous research has focused on identifying the sensitive input widgets, but the extraction of all layouts, including images and unused layouts, is fundamental. In this paper, we propose an automated framework that finds sensitive user input widgets from Android application layouts and validates the masking of these inputs. Our design includes novel techniques for resolving the user semantics, extraction of resources, identification of potential data leaks and helping users to prioritize the sharing of sensitive information, resulting in significant improvement over prior work. We also train track the obtained sensitive input widgets and check for unencrypted transmission or storage of sensitive data. Based on a preliminary evaluation of our framework with some applications from the Google Play store, we observe notable improvement over prior work in this domain.","PeriodicalId":174755,"journal":{"name":"Artificial Intelligence and Machine Learning","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121231660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Intelligent Lock System to Improve Learning Efficiency using Artificial Intelligence and Internet of Things 利用人工智能和物联网提高学习效率的智能锁系统

Artificial Intelligence and Machine Learning Pub Date : 2022-07-23 DOI: 10.5121/csit.2022.121204

Ivy Chen, Ang Li

{"title":"An Intelligent Lock System to Improve Learning Efficiency using Artificial Intelligence and Internet of Things","authors":"Ivy Chen, Ang Li","doi":"10.5121/csit.2022.121204","DOIUrl":"https://doi.org/10.5121/csit.2022.121204","url":null,"abstract":"According to recent statistics, 75.4% of people with access to the internet are addicted to their phones. 78 percent of teenagers check their mobile devices at least hourly [2]. The purpose of this paper is to propose a tool that lowers users’ dependence on their electronic devices. The tool named Phone Cage is created with the aim of locking electronic device for a set period of time. The application involves the user setting a specific mobile application for a specified amount of time. The phone cage provides the user a display countdown of the remaining time frame through which the locked application is inaccessible. The app provides access only when the set timer reaches the zero mark. This tool is created using Tinker cad, 3D- printer, Thunkable, Firebase console, and Raspberry Pi Zero. This will act as perfect remedy for individuals with addiction to their phones. It will also be a way for parents to control their children’s use of mobile phones. Therefore, noting that a significant number of people lack selfcontrol when it comes to cell phone usage, the cage will be of great help. The project will therefore have great impact to the community by allowing families to spend more time together and not on their phones. It will also help adults place more focus on their jobs and not on their phones.","PeriodicalId":174755,"journal":{"name":"Artificial Intelligence and Machine Learning","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126006611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0