Khadidja Benchaira, Salim Bitam, Zineb Djihane Agli
{"title":"Mitigating Data Variability and Overfitting in Deep Learning\u0000Models for Atrial Fibrillation Detection Using Single-Lead\u0000ECGs","authors":"Khadidja Benchaira, Salim Bitam, Zineb Djihane Agli","doi":"10.12785/ijcds/1501120","DOIUrl":"https://doi.org/10.12785/ijcds/1501120","url":null,"abstract":"","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141230441","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}
{"title":"Efficient Heuristics for Timetabling Scheduling in Blended Learning","authors":"Mohamed Jarraya","doi":"10.12785/ijcds/1501124","DOIUrl":"https://doi.org/10.12785/ijcds/1501124","url":null,"abstract":"","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"3 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141230273","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}
Atiya Khan, Chandrashekhar H. Patil, Amol D. Vibhute, Shankar Mali
{"title":"Mapping Crop Types At a 10 m Scale Using Sentinel-2 Data and Machine Learning Methods","authors":"Atiya Khan, Chandrashekhar H. Patil, Amol D. Vibhute, Shankar Mali","doi":"10.12785/ijcds/1501123","DOIUrl":"https://doi.org/10.12785/ijcds/1501123","url":null,"abstract":"","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"59 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141231705","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}
{"title":"Analytical Comparison On Detection Of Sarcasm Using\u0000Machine Learning And Deep Learning Techniques","authors":"Ameya Parkar, Rajni Bhalla","doi":"10.12785/ijcds/1501114","DOIUrl":"https://doi.org/10.12785/ijcds/1501114","url":null,"abstract":"","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"18 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141053844","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}
{"title":"Phishing Website Classification using Machine Learning with\u0000Different Datasets","authors":"Habiba Bouijij, A. Berqia","doi":"10.12785/ijcds/1501115","DOIUrl":"https://doi.org/10.12785/ijcds/1501115","url":null,"abstract":"","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"25 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141030890","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}
Raed Ibrahim Khaleel Almsari, Abbas Hussein Miry, Tariq M. Salman
{"title":"Performance Evaluation of Deep Learning Models for Face\u0000Expression Recognition","authors":"Raed Ibrahim Khaleel Almsari, Abbas Hussein Miry, Tariq M. Salman","doi":"10.12785/ijcds/1501117","DOIUrl":"https://doi.org/10.12785/ijcds/1501117","url":null,"abstract":"","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"30 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141041622","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}
{"title":"Human Detection in Clear and Hazy Weather Based on\u0000Transfer Learning With Improved INRIA Dataset Annotation","authors":"Yassine Bouafia, Larbi Guezouli, Hicham Lakhlef","doi":"10.12785/ijcds/1501119","DOIUrl":"https://doi.org/10.12785/ijcds/1501119","url":null,"abstract":"","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"13 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141022791","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}
: Alcohol consumption can lead to vocal health risks and long-term health issues for individuals. The paper introduces a novel dataset that analyzes vowel vocalizations to detect early alcohol consumption. This study examines hidden parameters in vowel sounds, such as frequency, jitters, shimmer, and harmonic ratio, which can identify individuals who consume alcohol. It aims to identify subtle vocal patterns that serve as markers for alcohol consumption. This study analyzed 509 vowel vocalizations from 290 records of 46 alcohol-consuming individuals and 219 non-drinkers aged 22–34. The study used intelligent machine learning models and Incremental Hidden Layer Neurons Artificial Neural Networks (IHLN-ANNs) with Back-propagation to identify patterns indicative of alcohol consumption. The Random Forest (RF) model achieved 95.3% accuracy, while the BP-ANNs model showed 99.4% accuracy with five neurons in a hidden layer. The findings could be applied to developing smartphone applications to provide timely alerts and cautionary measures for alcohol consumption, reducing accident risks. The study highlights voice analysis’s potential as a non-invasive and cost-e ff ective tool for identifying alcohol consumers, o ff ering potential avenues for future public health initiatives.
{"title":"Real-time Speech-based Intoxication Detection System: Vowel\u0000Biomarker Analysis with Artificial Neural Networks","authors":"Panduranga Vital Terlapu, Ram Prasad Reddy Sadi","doi":"10.12785/ijcds/1501116","DOIUrl":"https://doi.org/10.12785/ijcds/1501116","url":null,"abstract":": Alcohol consumption can lead to vocal health risks and long-term health issues for individuals. The paper introduces a novel dataset that analyzes vowel vocalizations to detect early alcohol consumption. This study examines hidden parameters in vowel sounds, such as frequency, jitters, shimmer, and harmonic ratio, which can identify individuals who consume alcohol. It aims to identify subtle vocal patterns that serve as markers for alcohol consumption. This study analyzed 509 vowel vocalizations from 290 records of 46 alcohol-consuming individuals and 219 non-drinkers aged 22–34. The study used intelligent machine learning models and Incremental Hidden Layer Neurons Artificial Neural Networks (IHLN-ANNs) with Back-propagation to identify patterns indicative of alcohol consumption. The Random Forest (RF) model achieved 95.3% accuracy, while the BP-ANNs model showed 99.4% accuracy with five neurons in a hidden layer. The findings could be applied to developing smartphone applications to provide timely alerts and cautionary measures for alcohol consumption, reducing accident risks. The study highlights voice analysis’s potential as a non-invasive and cost-e ff ective tool for identifying alcohol consumers, o ff ering potential avenues for future public health initiatives.","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"99 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141052341","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}
Ahmad AL-Hawamleh, Marwan Altarawneh, Heba Hikal, Alya Elfedawy
: This research focuses on the metaverse’s evolving trend and the potential application of blockchain technology in the accounting of virtual assets in this digital domain. The metaverse introduces a new economy in which users may earn real-world revenue through virtual activities, necessitating the need for e ffi cient and dependable virtual asset accounting. Blockchain technology, with its decentralized and immutable record, appears to be a viable answer to these problems. This paper discusses the present status of blockchain technology for accounting for virtual assets in the metaverse as well as its potential role for businesses and the economy. It also determines the technology’s issues and limits and makes recommendations for further development. The approach of this study is based on a comprehensive review of the existing literature on the interactions between blockchain technology, virtual asset accounting, and the metaverse. The findings indicate that blockchain technology has the potential to transform virtual asset accounting in the metaverse by improving security, transparency, and consistency. However, scalability and legal / regulatory issues must be overcome before it can completely achieve its promise. Accounting experts, developers, and stakeholders interested in the convergence of blockchain technology and the metaverse economy will find this paper useful.
{"title":"Blockchain Technology and Virtual Asset Accounting in the\u0000Metaverse: A Comprehensive Review of Future Directions","authors":"Ahmad AL-Hawamleh, Marwan Altarawneh, Heba Hikal, Alya Elfedawy","doi":"10.12785/ijcds/1501113","DOIUrl":"https://doi.org/10.12785/ijcds/1501113","url":null,"abstract":": This research focuses on the metaverse’s evolving trend and the potential application of blockchain technology in the accounting of virtual assets in this digital domain. The metaverse introduces a new economy in which users may earn real-world revenue through virtual activities, necessitating the need for e ffi cient and dependable virtual asset accounting. Blockchain technology, with its decentralized and immutable record, appears to be a viable answer to these problems. This paper discusses the present status of blockchain technology for accounting for virtual assets in the metaverse as well as its potential role for businesses and the economy. It also determines the technology’s issues and limits and makes recommendations for further development. The approach of this study is based on a comprehensive review of the existing literature on the interactions between blockchain technology, virtual asset accounting, and the metaverse. The findings indicate that blockchain technology has the potential to transform virtual asset accounting in the metaverse by improving security, transparency, and consistency. However, scalability and legal / regulatory issues must be overcome before it can completely achieve its promise. Accounting experts, developers, and stakeholders interested in the convergence of blockchain technology and the metaverse economy will find this paper useful.","PeriodicalId":37180,"journal":{"name":"International Journal of Computing and Digital Systems","volume":"42 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140733845","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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