Pub Date : 2023-01-01DOI: 10.33545/2707661x.2023.v4.i1a.58
Saksham Shankar
{"title":"Insurance fraud detection: Pre-emptive analysis and prevention","authors":"Saksham Shankar","doi":"10.33545/2707661x.2023.v4.i1a.58","DOIUrl":"https://doi.org/10.33545/2707661x.2023.v4.i1a.58","url":null,"abstract":"","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":"14 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86868944","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}
Pub Date : 2023-01-01DOI: 10.33545/2707661x.2023.v4.i1a.57
J. Devi, Sandeep Kumar, Sunil Kumar
{"title":"Evaluation of water resources: A case study of Rohtak district, Haryana","authors":"J. Devi, Sandeep Kumar, Sunil Kumar","doi":"10.33545/2707661x.2023.v4.i1a.57","DOIUrl":"https://doi.org/10.33545/2707661x.2023.v4.i1a.57","url":null,"abstract":"","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":"10 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80485159","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}
Pub Date : 2023-01-01DOI: 10.33545/2707661x.2023.v4.i1a.61
Dev Goyal, Hardik Sharma
{"title":"Brain tumor detection system using neural networks","authors":"Dev Goyal, Hardik Sharma","doi":"10.33545/2707661x.2023.v4.i1a.61","DOIUrl":"https://doi.org/10.33545/2707661x.2023.v4.i1a.61","url":null,"abstract":"","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75716845","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}
Pub Date : 2023-01-01DOI: 10.33545/2707661x.2023.v4.i1a.60
Y. Yaswanth, Samala Rohan, Neerudu Anusha, Gali Mohith
Machine learning and deep learning are rapidly evolving paradigms that are being used to solve a wide range of problems in various application areas. This literature review summary highlights the different types of neural networks and tools used in machine learning, as well as the use cases for deep learning, such as image identification, natural language processing, audio recognition, anomaly detection, and recommender systems. The existing system of machine learning is constantly expanding, with new techniques and architectures being developed to address real world problems. A proposed system for machine learning involves identifying the problem, collecting and preparing data, selecting and training appropriate models, evaluating performance, deploying and monitoring the model, and continuously updating it to improve its accuracy and effectiveness.
{"title":"Machine learning paradigm and application area of deep learning and types of neural network","authors":"Y. Yaswanth, Samala Rohan, Neerudu Anusha, Gali Mohith","doi":"10.33545/2707661x.2023.v4.i1a.60","DOIUrl":"https://doi.org/10.33545/2707661x.2023.v4.i1a.60","url":null,"abstract":"Machine learning and deep learning are rapidly evolving paradigms that are being used to solve a wide range of problems in various application areas. This literature review summary highlights the different types of neural networks and tools used in machine learning, as well as the use cases for deep learning, such as image identification, natural language processing, audio recognition, anomaly detection, and recommender systems. The existing system of machine learning is constantly expanding, with new techniques and architectures being developed to address real world problems. A proposed system for machine learning involves identifying the problem, collecting and preparing data, selecting and training appropriate models, evaluating performance, deploying and monitoring the model, and continuously updating it to improve its accuracy and effectiveness.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":"19 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85289347","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}
Pub Date : 2023-01-01DOI: 10.33545/2707661x.2023.v4.i1a.63
Richa Dhanta, Hardwik Sharma, Vivek Kumar, Hari Om Singh
This research paper aims to explore the effectiveness of machine learning algorithms in analyzing sentiment on Twitter. The study utilizes a dataset of tweets collected from various sources, which were then preprocessed to remove noise and irrelevant data [4, 5] . To categorize the tweets as positive, negative, or neutral, a number of machine learning techniques were used, such as logistic regression and Naive Bayesian [1] . The efficiency of these algorithms is also assessed in the study using a number of criteria, including accuracy, precision, recall, and F1 score. The results indicate that machine learning algorithms are effective in analyzing sentiment on Twitter, with Naive Bayes providing the best performance [18] . The results of this study have significant ramifications for companies and organizations looking to track consumer opinion of their goods or services [7] . This paper examines the problem of analyzing sentiment in Twitter by examining the tweets' expressed sentiments—whether they be favourable, negative, or neutral. Natural language processing methods will be used to analyze the messages that
{"title":"Twitter sentimental analysis using machine learning","authors":"Richa Dhanta, Hardwik Sharma, Vivek Kumar, Hari Om Singh","doi":"10.33545/2707661x.2023.v4.i1a.63","DOIUrl":"https://doi.org/10.33545/2707661x.2023.v4.i1a.63","url":null,"abstract":"This research paper aims to explore the effectiveness of machine learning algorithms in analyzing sentiment on Twitter. The study utilizes a dataset of tweets collected from various sources, which were then preprocessed to remove noise and irrelevant data [4, 5] . To categorize the tweets as positive, negative, or neutral, a number of machine learning techniques were used, such as logistic regression and Naive Bayesian [1] . The efficiency of these algorithms is also assessed in the study using a number of criteria, including accuracy, precision, recall, and F1 score. The results indicate that machine learning algorithms are effective in analyzing sentiment on Twitter, with Naive Bayes providing the best performance [18] . The results of this study have significant ramifications for companies and organizations looking to track consumer opinion of their goods or services [7] . This paper examines the problem of analyzing sentiment in Twitter by examining the tweets' expressed sentiments—whether they be favourable, negative, or neutral. Natural language processing methods will be used to analyze the messages that","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":"60 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80692202","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}
Pub Date : 2023-01-01DOI: 10.33545/2707661x.2023.v4.i1a.64
Sujay Singh, Suhasi Sethi, Raghav Sharma, R. ., Dr. Priyanka Kaushik
{"title":"AI based approach for 6G wireless communication","authors":"Sujay Singh, Suhasi Sethi, Raghav Sharma, R. ., Dr. Priyanka Kaushik","doi":"10.33545/2707661x.2023.v4.i1a.64","DOIUrl":"https://doi.org/10.33545/2707661x.2023.v4.i1a.64","url":null,"abstract":"","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":"44 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76588647","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}
Pub Date : 2022-12-01DOI: 10.57237/j.jeit.2022.01.005
Xiaohui Zou, Shunpeng Zou
{"title":"The Seven-Times-Pass Method: Beneficial to the Optimization of Computer-Aided Teaching System","authors":"Xiaohui Zou, Shunpeng Zou","doi":"10.57237/j.jeit.2022.01.005","DOIUrl":"https://doi.org/10.57237/j.jeit.2022.01.005","url":null,"abstract":"","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":"22 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90633883","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}
Pub Date : 2022-11-01DOI: 10.57237/j.jeit.2022.01.002
陈 桂映, 孔 艺权
{"title":"Design and Development of Educational Intervention System for Learning Disabilities of Autistic Children","authors":"陈 桂映, 孔 艺权","doi":"10.57237/j.jeit.2022.01.002","DOIUrl":"https://doi.org/10.57237/j.jeit.2022.01.002","url":null,"abstract":"","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":"45 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84942488","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}
Pub Date : 2022-11-01DOI: 10.57237/j.jeit.2022.01.004
刘 超群, 杨 志杰, 蔡 兰兰, 魏 翼鹰
{"title":"Exploration of Open Experimental Teaching Mode Based on \"Robot Platform\"","authors":"刘 超群, 杨 志杰, 蔡 兰兰, 魏 翼鹰","doi":"10.57237/j.jeit.2022.01.004","DOIUrl":"https://doi.org/10.57237/j.jeit.2022.01.004","url":null,"abstract":"","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":"24 3 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88678210","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}
Pub Date : 2022-11-01DOI: 10.57237/j.jeit.2022.01.001
冯 富生, 蒋 东云
{"title":"On the Teaching Reform of Badminton Courses in Colleges and Universities Under the Background of \"Internet+\"","authors":"冯 富生, 蒋 东云","doi":"10.57237/j.jeit.2022.01.001","DOIUrl":"https://doi.org/10.57237/j.jeit.2022.01.001","url":null,"abstract":"","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":"31 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81039691","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}
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