Pub Date : 2024-03-01DOI: 10.3844/jcssp.2024.276.290
Stanley Limonthy, E. D. Madyatmadja
{"title":"Factors Influencing Student Individual Performance of University XYZ Through the Use of Mobile Learning Management System","authors":"Stanley Limonthy, E. D. Madyatmadja","doi":"10.3844/jcssp.2024.276.290","DOIUrl":"https://doi.org/10.3844/jcssp.2024.276.290","url":null,"abstract":"","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140086961","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 : 2024-03-01DOI: 10.3844/jcssp.2024.303.309
Saad Ahmed, Sidrah Khurshid, Muhammad Imran, Muhammad Shoaib Siddiqui, Saman Hina, Munad Ahmed
{"title":"Analysis of Mental Health Counseling Conversation Using Natural Language Processing","authors":"Saad Ahmed, Sidrah Khurshid, Muhammad Imran, Muhammad Shoaib Siddiqui, Saman Hina, Munad Ahmed","doi":"10.3844/jcssp.2024.303.309","DOIUrl":"https://doi.org/10.3844/jcssp.2024.303.309","url":null,"abstract":"","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140090269","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":"Securing Mobile Devices from Malware: A Faceoff Between Federated Learning and Deep Learning Models for Android Malware Classification","authors":"Narayan Subramanian, Logesh Ravi, Mithin Jain Shaan, Malathi Devarajan, Tanupriya Choudhury, K. Kotecha, Subramaniyaswamy Vairavasundaram","doi":"10.3844/jcssp.2024.254.264","DOIUrl":"https://doi.org/10.3844/jcssp.2024.254.264","url":null,"abstract":"","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140083497","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 : 2024-03-01DOI: 10.3844/jcssp.2024.333.343
Joachim Notcker, E. Adetiba, Kennedy K. Ronoh, A. Abayomi, O. A. Akinola
{"title":"A Spectrum Sensing and Allocation Model for Primary User Detection and Interference Mitigation in Television Whitespaces","authors":"Joachim Notcker, E. Adetiba, Kennedy K. Ronoh, A. Abayomi, O. A. Akinola","doi":"10.3844/jcssp.2024.333.343","DOIUrl":"https://doi.org/10.3844/jcssp.2024.333.343","url":null,"abstract":"","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140083656","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":"A Comprehensive Survey on Applications, Challenges, Threats and Solutions in IoT Environment and Architecture","authors":"Sadia Waheed, Savera Hanif, Rubab Hafeez, Muhammad Imran Sharif, Kamran Siddique, Zahid Akhtar","doi":"10.3844/jcssp.2024.310.332","DOIUrl":"https://doi.org/10.3844/jcssp.2024.310.332","url":null,"abstract":"","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140088267","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 : 2024-03-01DOI: 10.3844/jcssp.2024.291.302
Manjunath Tk, A. Ps
{"title":"Fuel Prediction Model for Driving Patterns Using Machine Learning Techniques","authors":"Manjunath Tk, A. Ps","doi":"10.3844/jcssp.2024.291.302","DOIUrl":"https://doi.org/10.3844/jcssp.2024.291.302","url":null,"abstract":"","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140083201","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 : 2024-03-01DOI: 10.3844/jcssp.2024.229.238
Slimane Ennajar, Walid Bouarifi
{"title":"Deep Transfer Learning Approach for Student Attendance System During the COVID-19 Pandemic","authors":"Slimane Ennajar, Walid Bouarifi","doi":"10.3844/jcssp.2024.229.238","DOIUrl":"https://doi.org/10.3844/jcssp.2024.229.238","url":null,"abstract":"","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140085241","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}
: Cloud droplet dynamics is an important part of cloud physics. This element of cloud physics analyses the features of each droplet, including its size distribution, probability density and mean saturation. The cloud's structure is significantly important for the Earth's atmosphere and this structure is affected by changes in the droplet's micro-physical properties. In order to investigate and understand the dynamics of cloud droplets in both the high and low vortex areas, data obtained from Direct Numeric Simulations (DNS) are utilized. Data generated from simulations of cumulus clouds, which are defined as low-level clouds located between 800 and 1200 m above the surface of the earth. DNS data reveals complex droplet dynamics on a scale that is three-dimensional. When employing conventional machine learning methods, the processing of data relating to dynamic droplets requires a substantial amount of CPU resources. In this study, we discussed the advantages of using quantum mechanisms in cloud physics in order to investigate the complicated nature of cloud droplets. The use of quantum computing in the study of droplet dynamics using the quantum k-mean approach was further investigated in the discussion. Quantum machine learning is used to study the micro-physical characteristics of cloud droplets in order to investigate the effect that droplet dynamics have on the overall structure of clouds. The current topic of discussion delves more into the specifics of how data relating to DNS can be processed by an analog quantum computer in order to deal with enormous amounts of data in this specific area of research.
:云液滴动力学是云物理学的重要组成部分。云物理学的这一要素分析每个液滴的特征，包括其大小分布、概率密度和平均饱和度。云的结构对地球大气层非常重要，而这种结构会受到液滴微观物理特性变化的影响。为了研究和了解高涡和低涡区域的云滴动态，我们利用了直接数值模拟（DNS）获得的数据。积云是指距地球表面 800 至 1200 米的低空云层。DNS 数据揭示了三维尺度上复杂的液滴动态。如果采用传统的机器学习方法，处理与动态液滴相关的数据需要大量的 CPU 资源。在本研究中，我们讨论了在云物理学中使用量子机制的优势，以便研究云液滴的复杂性质。在讨论中，我们还进一步研究了利用量子 k-mean 方法研究液滴动力学时如何使用量子计算。量子机器学习用于研究云滴的微观物理特性，以研究云滴动力学对云的整体结构的影响。当前的讨论主题更深入地探讨了模拟量子计算机如何处理 DNS 相关数据的具体细节，以便处理这一特定研究领域的海量数据。
{"title":"Investigation and Statistical Analysis of Cloud Droplet Dynamics Using Quantum Computing","authors":"Mukta Nivelkar, Sunil Bhirud, Rahul Ranjan, Bipin Kumar","doi":"10.3844/jcssp.2024.344.356","DOIUrl":"https://doi.org/10.3844/jcssp.2024.344.356","url":null,"abstract":": Cloud droplet dynamics is an important part of cloud physics. This element of cloud physics analyses the features of each droplet, including its size distribution, probability density and mean saturation. The cloud's structure is significantly important for the Earth's atmosphere and this structure is affected by changes in the droplet's micro-physical properties. In order to investigate and understand the dynamics of cloud droplets in both the high and low vortex areas, data obtained from Direct Numeric Simulations (DNS) are utilized. Data generated from simulations of cumulus clouds, which are defined as low-level clouds located between 800 and 1200 m above the surface of the earth. DNS data reveals complex droplet dynamics on a scale that is three-dimensional. When employing conventional machine learning methods, the processing of data relating to dynamic droplets requires a substantial amount of CPU resources. In this study, we discussed the advantages of using quantum mechanisms in cloud physics in order to investigate the complicated nature of cloud droplets. The use of quantum computing in the study of droplet dynamics using the quantum k-mean approach was further investigated in the discussion. Quantum machine learning is used to study the micro-physical characteristics of cloud droplets in order to investigate the effect that droplet dynamics have on the overall structure of clouds. The current topic of discussion delves more into the specifics of how data relating to DNS can be processed by an analog quantum computer in order to deal with enormous amounts of data in this specific area of research.","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140088218","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 : 2024-03-01DOI: 10.3844/jcssp.2024.265.275
Mostafa Al Uahabi, Hicham Attariuas, Mohammed Saleh, Mohamed Chentouf
{"title":"An Adaptive Data Preprocessing Framework for Improved Learning: A Case Study of Tangier Container Terminal","authors":"Mostafa Al Uahabi, Hicham Attariuas, Mohammed Saleh, Mohamed Chentouf","doi":"10.3844/jcssp.2024.265.275","DOIUrl":"https://doi.org/10.3844/jcssp.2024.265.275","url":null,"abstract":"","PeriodicalId":40005,"journal":{"name":"Journal of Computer Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140092228","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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