Machine Learning and Soft Computing最新文献

Research on Construction of RDF with HBase 基于HBase的RDF构建研究

Machine Learning and Soft Computing Pub Date : 2023-01-28 DOI: 10.5121/csit.2023.130213

Hui Hu

引用次数: 0

A Novel System for Regional Twitter Hate Speech Analysis and Detection using Deep Learning Models and Web Scraping 基于深度学习模型和网络抓取的区域性推特仇恨言论分析与检测新系统

Machine Learning and Soft Computing Pub Date : 2023-01-28 DOI: 10.5121/csit.2023.130207

Nicole Ma, Yu Sun

引用次数: 0

Implementation of a New E-voting System based on Blockchain using ECDSA with Blind Signatures 基于区块链的ECDSA盲签名电子投票系统的实现

Machine Learning and Soft Computing Pub Date : 2023-01-28 DOI: 10.5121/csit.2023.130211

Lina Lumburovska, V. Dimitrova, Aleksandra Popovska Mitrovikj, Ss. Cyril

引用次数: 0

Comparative Study of Anxiety Symptom’s Predictions From Discord Chat Messages using Automl 使用Automl对不和谐聊天信息预测焦虑症状的比较研究

Machine Learning and Soft Computing Pub Date : 2023-01-28 DOI: 10.5121/csit.2023.130202

Anishka Duvvuri, Navya Kovvuri, Sneka Kumar, Rebecca Victor, Tanush Kaushik

{"title":"Comparative Study of Anxiety Symptom’s Predictions From Discord Chat Messages using Automl","authors":"Anishka Duvvuri, Navya Kovvuri, Sneka Kumar, Rebecca Victor, Tanush Kaushik","doi":"10.5121/csit.2023.130202","DOIUrl":"https://doi.org/10.5121/csit.2023.130202","url":null,"abstract":"Anxiety is a chronic illness especially during the Covid and post-pandemic era. It’s important to diagnose anxiety in its early stages. Traditional Machine learning (ML) methods have been developmental intense procedures to detect mental health issues, but Automated machine learning (AutoML) is a method whereby the novice user can build a model to detect a phenomenon such as Generalized Anxiety Disorder (GAD) fairly easily. In this study we evaluate a popular AutoML technique with recent chat engine (Discord) conversation dataset using anxiety hashtags. This multi-symptom AutoML Random Forest predictive model is at least 75+% accurate with the most prevalent symptom, namely restlessness. This could be a very useful first step in diagnosing GAD by medical professionals and their less skilled hospital’s IT area using pre diagnostic textual conversations. But it lacks high quality in predicting GAD in most symptoms as found by a low 50% precision on most symptoms (except 5). The AutoML technology is quicker for IT professionals and gives a decent performance, but it can be improved upon by more sophisticated ANN methods like Convolution neural networks that plug AutoML’s symptom’s deficiencies with at least 80+% precision and 0.4+% in F1 score, namely in detecting poorly predicted symptoms of concentration and irritability.","PeriodicalId":132577,"journal":{"name":"Machine Learning and Soft Computing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123928798","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

A First-Person Shooter Game Designed to Educate and Aid the Player Movement Implementation 这是一款第一人称射击游戏，旨在教育和帮助玩家执行移动

Machine Learning and Soft Computing Pub Date : 2023-01-28 DOI: 10.5121/csit.2023.130203

Chunhei Zhu, Yujia Zhang

{"title":"A First-Person Shooter Game Designed to Educate and Aid the Player Movement Implementation","authors":"Chunhei Zhu, Yujia Zhang","doi":"10.5121/csit.2023.130203","DOIUrl":"https://doi.org/10.5121/csit.2023.130203","url":null,"abstract":"The issue of finding a clean and simple player movement implementation that the general public will find intuitive and easy to use has been tackled over the years in various ways. With FPS (first-person shooter) games, the need fora simple and fun style of movement is monumentally crucial, as that will be a core aspect of the gameplay [4]. To address this issue, an FPS game was created with the ability to maintain momentum while crouching with intention of providing a smoother and more intuitive gaming experience for players. This movement implementation was tested by having participants play the game for a sufficient amount of time, then asking the participants to rate the experience of movement in the game and the overall enjoyment of playing the game. The results indicate that the implemented movement would be well-received by the general public, as the vast majority of the participants viewedthe new form of movement as a welcome feature based on the optional feedback and the quantitative ratings. However, the other aspects of the gameplay were not as polished and therefore lowered the overall enjoyment of the game for the participants, particularly the shooting in the game that does not yet have proper audio or visual cues tolet the player know that the weapon has been fired.","PeriodicalId":132577,"journal":{"name":"Machine Learning and Soft Computing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121373078","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

A NLP-learning Powered Customizable Approach Towards Auto-blocking Distracting Websites 一种基于nlp学习的自定义方法，用于自动阻止分散注意力的网站

Machine Learning and Soft Computing Pub Date : 2023-01-28 DOI: 10.5121/csit.2023.130209

Yulin Zhang, Yu Sun

{"title":"A NLP-learning Powered Customizable Approach Towards Auto-blocking Distracting Websites","authors":"Yulin Zhang, Yu Sun","doi":"10.5121/csit.2023.130209","DOIUrl":"https://doi.org/10.5121/csit.2023.130209","url":null,"abstract":"Over the past few decades, the problem of distraction and its accompanying side effects has taken its root deeply in all parts of our daily life and extended its ever-increasing influences among young generations [2]. In addition to its alarming prevalence, another characteristic of distraction that raises most concerns is how easily we can get distracted from our tasks at hand while using the electronic devices as a means of solving problems [3]. This paper attempts to address this society-wide problem thoroughly and universally through a technical approach of detecting, analyzing, and blocking the websites intelligently. Our design highlights the applications of machine learning and natural language processing, and is implemented purely in Python, Javascript, and several other web development languages. After retrieving the web content from the target websites through the web scraping process, summarizing the data to a number of short paragraphs via the use of NLP, we were able to perform data analysis on the result and finally block the websites accordingly [4]. With the help of this extension, students and those who wish to improve their concentration in work will be able to put more focus on the tasks at hand and thus boost their work efficiency under any working conditions.","PeriodicalId":132577,"journal":{"name":"Machine Learning and Soft Computing","volume":"01 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127332067","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

A Cryptocurrency Analysis Tool based on Social Metrics 基于社交指标的加密货币分析工具

Machine Learning and Soft Computing Pub Date : 2023-01-28 DOI: 10.5121/csit.2023.130206

Bill Xu, Yu Sun

引用次数: 0

Ethical Algorithms in Human-Robot-Interaction. A Proposal 人机交互中的伦理算法。一个提议

Machine Learning and Soft Computing Pub Date : 2023-01-28 DOI: 10.5121/csit.2023.130214

Joerg H. Hardy

引用次数: 0

Micam: Visualizing Feature Extraction of Nonnatural Data Micam:非自然数据的可视化特征提取

Machine Learning and Soft Computing Pub Date : 2023-01-28 DOI: 10.5121/csit.2023.130201

Randy Klepetko, R. Krishnan

{"title":"Micam: Visualizing Feature Extraction of Nonnatural Data","authors":"Randy Klepetko, R. Krishnan","doi":"10.5121/csit.2023.130201","DOIUrl":"https://doi.org/10.5121/csit.2023.130201","url":null,"abstract":"Convolutional Neural Networks (CNN) continue to revolutionize image recognition technology and are being used in non-image related fields such as cybersecurity. They are known to work as feature extractors, identifying patterns within large data sets, but when dealing with nonnatural data, what these features represent is not understood. Several class activation map (CAM) visualization tools are available that assist with understanding the CNN decisions when used with images, but they are not intuitively comprehended when dealing with nonnatural security data. Understanding what the extracted features represent should enable the data analyst and model architect tailor a model to maximize the extracted features while minimizing the computational parameters. In this paper we offer a new tool Model integrated Class Activation Maps, (MiCAM) which allows the analyst the ability to visually compare extracted feature intensities at the individual layer detail. We explore using this new tool to analyse several datasets. First the MNIST handwriting data set to gain a baseline understanding. We then analyse two security data sets: computers process metrics from cloud based application servers that are infected with malware and the CIC-IDS-2017 IP data traffic set and identify how re-ordering nonnatural security related data affects feature extraction performance and identify how reordering the data affect feature extraction performance.","PeriodicalId":132577,"journal":{"name":"Machine Learning and Soft Computing","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127160173","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

A Smart Mobile Application Designed to Educate and Aid the Public in Combating Climate Change 一个旨在教育和帮助公众应对气候变化的智能移动应用程序

Machine Learning and Soft Computing Pub Date : 2023-01-28 DOI: 10.5121/csit.2023.130208

Ke Zhang

{"title":"A Smart Mobile Application Designed to Educate and Aid the Public in Combating Climate Change","authors":"Ke Zhang","doi":"10.5121/csit.2023.130208","DOIUrl":"https://doi.org/10.5121/csit.2023.130208","url":null,"abstract":"We aim to tackle the issue of improving the global situation regarding climate change by creating a mobile application named Climerry, which educates its users on recent news related to climate on the home screen. Climerry also features a second tab that allows users to view opportunities to improve the climate change situation in the vicinity by typing in a ZIP code or city name. Some examples of opportunities include beach cleanups and tree-planting sessions. By informing and encouraging the general public to become more involved in the effort to preserve our planet, the negative effects of climate change may be much less significant in the future. To prove the effectiveness of this application in encouraging the general public to take action against climate change, one experiment was performed to gauge how much knowledge regarding climate change the participants had gained by using the application. Another experiment tested the reliability of the news API used in the application by testing the accuracy of information in each of the selected articles in the featured news section of the application. The result of the experiments indicated that the application is useful when it comes to providing accurate news and educating its users on the topic of climate change.","PeriodicalId":132577,"journal":{"name":"Machine Learning and Soft Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131115331","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