{"title":"TokenLink: a secure loyalty point exchange system powered by smart contracts","authors":"Hartik Suhagiya, Hrithik Mistry, Aryan Trivedi, Ramchandra Mangrulkar, Pallavi Chavan","doi":"10.1080/1206212x.2023.2293592","DOIUrl":"https://doi.org/10.1080/1206212x.2023.2293592","url":null,"abstract":"","PeriodicalId":39673,"journal":{"name":"International Journal of Computers and Applications","volume":"120 28","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138953727","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 : 2023-12-18DOI: 10.1080/1206212x.2023.2286032
S. R. Deepti, P. C. Karthik
{"title":"Survey on age-related macular degeneration detection in OCT image","authors":"S. R. Deepti, P. C. Karthik","doi":"10.1080/1206212x.2023.2286032","DOIUrl":"https://doi.org/10.1080/1206212x.2023.2286032","url":null,"abstract":"","PeriodicalId":39673,"journal":{"name":"International Journal of Computers and Applications","volume":"13 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139172825","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 : 2023-12-15DOI: 10.1080/1206212x.2023.2289706
Nail Adeeb Ali Abdu, K. O. Basulaim
{"title":"Machine learning in concept drift detection using statistical measures","authors":"Nail Adeeb Ali Abdu, K. O. Basulaim","doi":"10.1080/1206212x.2023.2289706","DOIUrl":"https://doi.org/10.1080/1206212x.2023.2289706","url":null,"abstract":"","PeriodicalId":39673,"journal":{"name":"International Journal of Computers and Applications","volume":"5 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138999812","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 : 2023-12-08DOI: 10.1080/1206212x.2023.2289708
Yang Cao, Junhai Zhai, Wei Zhang, Xuesong Zhou, Feng Zhang
{"title":"MTTF: a multimodal transformer for temperature forecasting","authors":"Yang Cao, Junhai Zhai, Wei Zhang, Xuesong Zhou, Feng Zhang","doi":"10.1080/1206212x.2023.2289708","DOIUrl":"https://doi.org/10.1080/1206212x.2023.2289708","url":null,"abstract":"","PeriodicalId":39673,"journal":{"name":"International Journal of Computers and Applications","volume":"55 47","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138587939","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 : 2023-12-06DOI: 10.1080/1206212x.2023.2283647
Amrithkala M. Shetty, Mohammed Fadhel Aljunid, D. H. Manjaiah
{"title":"Unleashing the power of 2D CNN with attention and pre-trained embeddings for enhanced online review analysis","authors":"Amrithkala M. Shetty, Mohammed Fadhel Aljunid, D. H. Manjaiah","doi":"10.1080/1206212x.2023.2283647","DOIUrl":"https://doi.org/10.1080/1206212x.2023.2283647","url":null,"abstract":"","PeriodicalId":39673,"journal":{"name":"International Journal of Computers and Applications","volume":"67 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138595986","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 : 2023-11-28DOI: 10.1080/1206212x.2023.2284443
Ahmed Aljabri, F. Jemili, O. Korbaa
{"title":"Convolutional neural network for intrusion detection using blockchain technology","authors":"Ahmed Aljabri, F. Jemili, O. Korbaa","doi":"10.1080/1206212x.2023.2284443","DOIUrl":"https://doi.org/10.1080/1206212x.2023.2284443","url":null,"abstract":"","PeriodicalId":39673,"journal":{"name":"International Journal of Computers and Applications","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139216176","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 : 2023-11-25DOI: 10.1080/1206212X.2023.2283648
Yuanhan Du, Ling Wang, Yebo Tao
ABSTRACT The complex and diverse server video data leads to the problem of effective retrieval of these data. The current shot edge detection algorithm and key frame extraction algorithm in server node video processing have problems such as poor extraction performance and poor adaptability. Therefore, the research combined the feature depth analysis to improve the two, and the performance was verified by experiments. The shot detection algorithm is verified by modifying the secondary detection model. This method can detect lens mutation, gradual change and other phenomena well, and the accuracy rate can reach 99.7%. The precision under the gradient lens is 92.08%, far higher than 63.50% and 85.39% of ISIFT and CS-DFS. In the verification experiment using Convolution Neural Networks (CNNs) key frame extraction algorithm, the number of key frame extractions of the proposed algorithm can reach up to 88 frames. Compared with other methods, the accuracy of the algorithm studied can reach 99.67%, which is higher than the comparison algorithm. In general, the improved algorithm proposed in the study has high adaptability to edge detection and the ability to express key frame video, and has high practicability in actual server node video processing.
{"title":"Server node video processing based on feature depth analysis algorithm","authors":"Yuanhan Du, Ling Wang, Yebo Tao","doi":"10.1080/1206212X.2023.2283648","DOIUrl":"https://doi.org/10.1080/1206212X.2023.2283648","url":null,"abstract":"ABSTRACT The complex and diverse server video data leads to the problem of effective retrieval of these data. The current shot edge detection algorithm and key frame extraction algorithm in server node video processing have problems such as poor extraction performance and poor adaptability. Therefore, the research combined the feature depth analysis to improve the two, and the performance was verified by experiments. The shot detection algorithm is verified by modifying the secondary detection model. This method can detect lens mutation, gradual change and other phenomena well, and the accuracy rate can reach 99.7%. The precision under the gradient lens is 92.08%, far higher than 63.50% and 85.39% of ISIFT and CS-DFS. In the verification experiment using Convolution Neural Networks (CNNs) key frame extraction algorithm, the number of key frame extractions of the proposed algorithm can reach up to 88 frames. Compared with other methods, the accuracy of the algorithm studied can reach 99.67%, which is higher than the comparison algorithm. In general, the improved algorithm proposed in the study has high adaptability to edge detection and the ability to express key frame video, and has high practicability in actual server node video processing.","PeriodicalId":39673,"journal":{"name":"International Journal of Computers and Applications","volume":"117 11","pages":"58 - 65"},"PeriodicalIF":0.0,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139237218","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 : 2023-11-24DOI: 10.1080/1206212x.2023.2284446
K. Sakkaravarthy Iyyappan, S. Balasundaram
{"title":"A novel multi document summarization with document-elements augmentation for learning materials using concept based ILP and clustering methods","authors":"K. Sakkaravarthy Iyyappan, S. Balasundaram","doi":"10.1080/1206212x.2023.2284446","DOIUrl":"https://doi.org/10.1080/1206212x.2023.2284446","url":null,"abstract":"","PeriodicalId":39673,"journal":{"name":"International Journal of Computers and Applications","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139238768","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 : 2023-11-24DOI: 10.1080/1206212x.2023.2285533
S. Kinger, Vrushali Kulkarni
{"title":"Demystifying the black box: an overview of explainability methods in machine learning","authors":"S. Kinger, Vrushali Kulkarni","doi":"10.1080/1206212x.2023.2285533","DOIUrl":"https://doi.org/10.1080/1206212x.2023.2285533","url":null,"abstract":"","PeriodicalId":39673,"journal":{"name":"International Journal of Computers and Applications","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139240931","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 : 2023-11-21DOI: 10.1080/1206212X.2023.2277553
Vishal Kumar, Sumit Kushwaha
Because of the rapid rise in the count of corporations using cloud-dependent infrastructure as the foundation for big data storing and analysis. The fundamental difficulty in scheduling big data services in cloud-dependent systems is ensuring the shortest possible makespan while simultaneously reducing the number of resources being used. We have created a new, secure map reduce scheduling method that functions as follows. Initially, the cloud architecture is designed and the tasks are generated. In the pre-processing phase, the huge set of tasks was processed by the map-reduce scheduling framework. Afterward, the optimal task scheduling task is conducted which utilizes a hybrid algorithm named Tunicate Combined Moth Flame Algorithm (TCMFA), which provides better task scheduling via providing optimal makespan, execution time, and security. This proposed TCMFA is the hybridization of both Moth Flame Optimization (MFO) and Tunicate Swarm Algorithm (TSA). The error rate of the TCMFA gets reduced to 320 approximately over other conventional methods such as RSA, ACO, GHO, BTS, OWPSO, BES, PRO, SOA, COOT, TSA & MFO which proves the accuracy of our TCMFA and makes it more efficient and secure for optimal map-reduce scheduling.
{"title":"Hybrid metaheuristic model based performance-aware optimization for map reduce scheduling","authors":"Vishal Kumar, Sumit Kushwaha","doi":"10.1080/1206212X.2023.2277553","DOIUrl":"https://doi.org/10.1080/1206212X.2023.2277553","url":null,"abstract":"Because of the rapid rise in the count of corporations using cloud-dependent infrastructure as the foundation for big data storing and analysis. The fundamental difficulty in scheduling big data services in cloud-dependent systems is ensuring the shortest possible makespan while simultaneously reducing the number of resources being used. We have created a new, secure map reduce scheduling method that functions as follows. Initially, the cloud architecture is designed and the tasks are generated. In the pre-processing phase, the huge set of tasks was processed by the map-reduce scheduling framework. Afterward, the optimal task scheduling task is conducted which utilizes a hybrid algorithm named Tunicate Combined Moth Flame Algorithm (TCMFA), which provides better task scheduling via providing optimal makespan, execution time, and security. This proposed TCMFA is the hybridization of both Moth Flame Optimization (MFO) and Tunicate Swarm Algorithm (TSA). The error rate of the TCMFA gets reduced to 320 approximately over other conventional methods such as RSA, ACO, GHO, BTS, OWPSO, BES, PRO, SOA, COOT, TSA & MFO which proves the accuracy of our TCMFA and makes it more efficient and secure for optimal map-reduce scheduling.","PeriodicalId":39673,"journal":{"name":"International Journal of Computers and Applications","volume":"7 1","pages":"776 - 788"},"PeriodicalIF":0.0,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139253980","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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