Pub Date : 2024-04-17DOI: 10.51594/csitrj.v5i4.1047
Excel G Chukwurah
As data privacy concerns become increasingly prevalent, especially in the U.S. where regulations like the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR) are setting new standards, technology companies must adopt advanced risk management strategies to ensure compliance and protect consumer data. This review explores the concept of proactive privacy and outlines key strategies for integrating privacy considerations into product development processes. The review begins by highlighting the growing importance of data privacy in the U.S. tech industry, emphasizing the need for proactive approaches to privacy management. It then introduces the concept of proactive privacy, which involves identifying and mitigating privacy risks early in the product development lifecycle. The review emphasizes the importance of adopting a privacy-by-design approach, where privacy considerations are integrated into every stage of product development. The review then outlines several advanced risk management strategies for proactive privacy. This includes conducting thorough privacy impact assessments (PIAs) to identify potential privacy risks associated with new products or services. It also emphasizes the importance of implementing privacy-enhancing technologies, such as encryption and anonymization, to protect consumer data. Furthermore, the review discusses the importance of establishing a culture of privacy within tech companies, where privacy is viewed as a fundamental value and employees are educated about privacy best practices. It also highlights the benefits of engaging with privacy experts and regulators to stay informed about evolving privacy regulations and industry standards. In conclusion, the review emphasizes the importance of proactive privacy in product development and highlights key strategies for integrating privacy considerations into the development process. By adopting advanced risk management strategies and prioritizing privacy throughout the product lifecycle, U.S. technology companies can enhance consumer trust, ensure compliance with regulations, and mitigate privacy risks. Keywords: Proactive Privacy, Risk Management, Strategies, Product Development, Advanced
{"title":"PROACTIVE PRIVACY: ADVANCED RISK MANAGEMENT STRATEGIES FOR PRODUCT DEVELOPMENT IN THE U.S","authors":"Excel G Chukwurah","doi":"10.51594/csitrj.v5i4.1047","DOIUrl":"https://doi.org/10.51594/csitrj.v5i4.1047","url":null,"abstract":"As data privacy concerns become increasingly prevalent, especially in the U.S. where regulations like the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR) are setting new standards, technology companies must adopt advanced risk management strategies to ensure compliance and protect consumer data. This review explores the concept of proactive privacy and outlines key strategies for integrating privacy considerations into product development processes. The review begins by highlighting the growing importance of data privacy in the U.S. tech industry, emphasizing the need for proactive approaches to privacy management. It then introduces the concept of proactive privacy, which involves identifying and mitigating privacy risks early in the product development lifecycle. The review emphasizes the importance of adopting a privacy-by-design approach, where privacy considerations are integrated into every stage of product development. The review then outlines several advanced risk management strategies for proactive privacy. This includes conducting thorough privacy impact assessments (PIAs) to identify potential privacy risks associated with new products or services. It also emphasizes the importance of implementing privacy-enhancing technologies, such as encryption and anonymization, to protect consumer data. Furthermore, the review discusses the importance of establishing a culture of privacy within tech companies, where privacy is viewed as a fundamental value and employees are educated about privacy best practices. It also highlights the benefits of engaging with privacy experts and regulators to stay informed about evolving privacy regulations and industry standards. In conclusion, the review emphasizes the importance of proactive privacy in product development and highlights key strategies for integrating privacy considerations into the development process. By adopting advanced risk management strategies and prioritizing privacy throughout the product lifecycle, U.S. technology companies can enhance consumer trust, ensure compliance with regulations, and mitigate privacy risks. \u0000Keywords: Proactive Privacy, Risk Management, Strategies, Product Development, Advanced","PeriodicalId":282796,"journal":{"name":"Computer Science & IT Research Journal","volume":" 38","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140691878","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 : 2024-04-17DOI: 10.51594/csitrj.v5i4.1045
Kevin Namiiro Kuteesa, Chidiogo Uzoamaka Akpuokwe, Chioma Ann Udeh
This review paper examines the digital divide and Information and Communication Technology (ICT) access in rural communities across Africa and the United States, employing a comparative analysis to understand the multifaceted nature of digital disparities. Through an exploration of theoretical frameworks, including Technology Acceptance Models, Socio-Economic Models, and Cultural and Policy Analysis, the paper highlights the complex interplay of factors influencing ICT access. It delves into the current state of ICT infrastructure, digital literacy, and the impact of ICT on socio-economic development in these communities. The analysis further assesses policy and regulatory environments, identifying challenges and opportunities for bridging the digital divide. The paper concludes by offering insights into future directions for research, policy reforms, and innovative solutions aimed at enhancing digital inclusion. Keywords: Digital Divide, ICT Access, Rural Communities, Technology Acceptance Models, Digital Literacy, Policy Analysis.
{"title":"THEORETICAL PERSPECTIVES ON DIGITAL DIVIDE AND ICT ACCESS: COMPARATIVE STUDY OF RURAL COMMUNITIES IN AFRICA AND THE UNITED STATES","authors":"Kevin Namiiro Kuteesa, Chidiogo Uzoamaka Akpuokwe, Chioma Ann Udeh","doi":"10.51594/csitrj.v5i4.1045","DOIUrl":"https://doi.org/10.51594/csitrj.v5i4.1045","url":null,"abstract":"This review paper examines the digital divide and Information and Communication Technology (ICT) access in rural communities across Africa and the United States, employing a comparative analysis to understand the multifaceted nature of digital disparities. Through an exploration of theoretical frameworks, including Technology Acceptance Models, Socio-Economic Models, and Cultural and Policy Analysis, the paper highlights the complex interplay of factors influencing ICT access. It delves into the current state of ICT infrastructure, digital literacy, and the impact of ICT on socio-economic development in these communities. The analysis further assesses policy and regulatory environments, identifying challenges and opportunities for bridging the digital divide. The paper concludes by offering insights into future directions for research, policy reforms, and innovative solutions aimed at enhancing digital inclusion. \u0000Keywords: Digital Divide, ICT Access, Rural Communities, Technology Acceptance Models, Digital Literacy, Policy Analysis.","PeriodicalId":282796,"journal":{"name":"Computer Science & IT Research Journal","volume":"92 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140693662","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 : 2024-04-17DOI: 10.51594/csitrj.v5i4.1046
Babajide Tolulope Familoni, Philip Olaseni Shoetan
This paper provides a comprehensive review and comparative analysis of cybersecurity challenges and strategies within the financial sectors of the United States of America (USA) and Nigeria. It aims to elucidate the complexities and variances in cybersecurity practices, focusing on the different approaches taken by these nations to safeguard their financial data against increasing cyber threats. Through a detailed examination of existing literature, including academic journals, industry reports, and cybersecurity incident databases, this study identifies the unique and common cybersecurity vulnerabilities, regulatory environments, and defense mechanisms employed by the financial sectors in both countries. The review reveals that the USA's financial sector benefits from advanced cybersecurity technologies and a strong regulatory framework, yet faces challenges related to sophisticated cyber-attacks and the management of insider threats. Conversely, Nigeria's financial sector grapples with issues such as limited cybersecurity awareness, technological constraints, and evolving regulatory frameworks. Despite these disparities, both countries share the necessity of enhancing their cybersecurity posture to combat the evolving nature of cyber threats effectively. Conclusively, the paper argues that addressing cybersecurity in the financial sector necessitates a comprehensive approach that includes not only technological solutions but also the strengthening of regulatory policies, enhancement of cybersecurity awareness, and fostering international collaboration. The comparative analysis underscores the importance of adopting best practices from each country's experience, aiming to bolster the resilience of financial institutions against cyber threats in an increasingly interconnected world. Keywords: Cybersecurity, Financial Sector, United States, Nigeria, Digital Infrastructure, Technological Vulnerabilities, Regulatory Complexities, Human Factors, Advanced Detection, Prevention Technologies, Machine Learning, Anomaly Detection, Cybersecurity Frameworks, Awareness, Training, Culture, Public-Private Partnerships, Threat Intelligence, Best Practices, Innovation, Regulatory Foresight, Human Capital Development, Stability, Integrity, Collaboration
{"title":"CYBERSECURITY IN THE FINANCIAL SECTOR: A COMPARATIVE ANALYSIS OF THE USA AND NIGERIA","authors":"Babajide Tolulope Familoni, Philip Olaseni Shoetan","doi":"10.51594/csitrj.v5i4.1046","DOIUrl":"https://doi.org/10.51594/csitrj.v5i4.1046","url":null,"abstract":"This paper provides a comprehensive review and comparative analysis of cybersecurity challenges and strategies within the financial sectors of the United States of America (USA) and Nigeria. It aims to elucidate the complexities and variances in cybersecurity practices, focusing on the different approaches taken by these nations to safeguard their financial data against increasing cyber threats. Through a detailed examination of existing literature, including academic journals, industry reports, and cybersecurity incident databases, this study identifies the unique and common cybersecurity vulnerabilities, regulatory environments, and defense mechanisms employed by the financial sectors in both countries. \u0000The review reveals that the USA's financial sector benefits from advanced cybersecurity technologies and a strong regulatory framework, yet faces challenges related to sophisticated cyber-attacks and the management of insider threats. Conversely, Nigeria's financial sector grapples with issues such as limited cybersecurity awareness, technological constraints, and evolving regulatory frameworks. Despite these disparities, both countries share the necessity of enhancing their cybersecurity posture to combat the evolving nature of cyber threats effectively. \u0000Conclusively, the paper argues that addressing cybersecurity in the financial sector necessitates a comprehensive approach that includes not only technological solutions but also the strengthening of regulatory policies, enhancement of cybersecurity awareness, and fostering international collaboration. The comparative analysis underscores the importance of adopting best practices from each country's experience, aiming to bolster the resilience of financial institutions against cyber threats in an increasingly interconnected world. \u0000Keywords: Cybersecurity, Financial Sector, United States, Nigeria, Digital Infrastructure, Technological Vulnerabilities, Regulatory Complexities, Human Factors, Advanced Detection, Prevention Technologies, Machine Learning, Anomaly Detection, Cybersecurity Frameworks, Awareness, Training, Culture, Public-Private Partnerships, Threat Intelligence, Best Practices, Innovation, Regulatory Foresight, Human Capital Development, Stability, Integrity, Collaboration","PeriodicalId":282796,"journal":{"name":"Computer Science & IT Research Journal","volume":" 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140690898","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 : 2024-04-17DOI: 10.51594/csitrj.v5i4.1044
Excel G Chukwurah, Samuel Aderemi
Data protection compliance is a critical issue for U.S. technology companies, especially in light of increasingly stringent regulations such as the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR). Achieving compliance requires a harmonized approach that aligns internal teams and processes with regulatory requirements. This review explores strategies for U.S. technology companies to harmonize teams and regulations to ensure data protection compliance. The first key strategy is to establish a cross-functional team dedicated to data protection compliance. This team should include representatives from legal, IT, security, and other relevant departments. By bringing together experts from different areas, companies can ensure a comprehensive approach to compliance that takes into account legal requirements, technical capabilities, and organizational policies. Secondly, companies should invest in training and education for all employees on data protection principles and compliance requirements. This includes raising awareness about the importance of data protection, as well as providing specific training on how to handle personal data in accordance with regulations. By ensuring that all employees are informed and knowledgeable about data protection, companies can reduce the risk of non-compliance. Another important strategy is to implement privacy by design and by default principles in product development and business processes. This means building privacy considerations into products and services from the outset, rather than trying to retrofit them later. By incorporating privacy into the design process, companies can ensure that their products and services are compliant with regulations and protect user data. Finally, companies should establish a culture of continuous improvement and accountability when it comes to data protection compliance. This includes regularly reviewing and updating data protection policies and procedures, as well as conducting regular audits and assessments to identify and address compliance gaps. By making data protection a priority at all levels of the organization, companies can reduce the risk of data breaches and non-compliance with regulations. Keywords: Data Protection, Compliance, Strategies, Technology, Regulations.
{"title":"HARMONIZING TEAMS AND REGULATIONS: STRATEGIES FOR DATA PROTECTION COMPLIANCE IN U.S. TECHNOLOGY COMPANIES","authors":"Excel G Chukwurah, Samuel Aderemi","doi":"10.51594/csitrj.v5i4.1044","DOIUrl":"https://doi.org/10.51594/csitrj.v5i4.1044","url":null,"abstract":"Data protection compliance is a critical issue for U.S. technology companies, especially in light of increasingly stringent regulations such as the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR). Achieving compliance requires a harmonized approach that aligns internal teams and processes with regulatory requirements. This review explores strategies for U.S. technology companies to harmonize teams and regulations to ensure data protection compliance. The first key strategy is to establish a cross-functional team dedicated to data protection compliance. This team should include representatives from legal, IT, security, and other relevant departments. By bringing together experts from different areas, companies can ensure a comprehensive approach to compliance that takes into account legal requirements, technical capabilities, and organizational policies. Secondly, companies should invest in training and education for all employees on data protection principles and compliance requirements. This includes raising awareness about the importance of data protection, as well as providing specific training on how to handle personal data in accordance with regulations. By ensuring that all employees are informed and knowledgeable about data protection, companies can reduce the risk of non-compliance. Another important strategy is to implement privacy by design and by default principles in product development and business processes. This means building privacy considerations into products and services from the outset, rather than trying to retrofit them later. By incorporating privacy into the design process, companies can ensure that their products and services are compliant with regulations and protect user data. Finally, companies should establish a culture of continuous improvement and accountability when it comes to data protection compliance. This includes regularly reviewing and updating data protection policies and procedures, as well as conducting regular audits and assessments to identify and address compliance gaps. By making data protection a priority at all levels of the organization, companies can reduce the risk of data breaches and non-compliance with regulations. \u0000Keywords: Data Protection, Compliance, Strategies, Technology, Regulations.","PeriodicalId":282796,"journal":{"name":"Computer Science & IT Research Journal","volume":" 35","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140692522","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 : 2024-04-17DOI: 10.51594/csitrj.v5i4.1049
Lawrence Damilare Oyeniyi, Chinonye Esther Ugochukwu, Noluthando Zamanjomane Mhlongo
In the digital epoch, where the financial sector stands as the cornerstone of global economic stability, the escalating sophistication of cyber threats poses an unprecedented challenge. This scholarly pursuit aimed to dissect the intricate web of cybersecurity within the financial domain, elucidating the evolving threat landscape, scrutinizing the efficacy of existing cybersecurity frameworks, and delineating strategic pathways for fortification against digital adversaries. Anchored in a qualitative methodology, the study embarked on a systematic literature review, meticulously sifting through contemporary academic discourse to unveil the nuances of cybersecurity challenges besieging financial institutions. The scope of this inquiry spanned the assessment of regulatory landscapes, the exploration of technological innovations in cybersecurity, and the critical examination of human factors influencing cybersecurity efficacy. The findings illuminate a stark reality—the existing cybersecurity frameworks, though foundational, are increasingly inadequate in the face of sophisticated cyber threats. The study advocates for a paradigmatic shift towards more adaptable, robust, and technology-driven cybersecurity frameworks, underscored by the imperative for regulatory agility and international collaboration. Conclusively, the paper posits that the future of cybersecurity in the financial sector hinges on a tripartite alliance among financial institutions, regulatory bodies, and technology providers, urging a unified front to navigate the cyber tempest. Recommendations call for an integrated approach that marries regulatory compliance with cutting-edge technological solutions, fostering a cybersecurity ecosystem that is both resilient and responsive to the digital zeitgeist. This scholarly endeavor not only contributes to the academic discourse on financial cybersecurity but also serves as a beacon for policymakers, practitioners, and stakeholders in charting a secure course in the digital financial frontier. Keywords: Cybersecurity, Financial Sector, Systematic Literature Review, Regulatory Compliance, Technological Innovation, Strategic Recommendations.
{"title":"DEVELOPING CYBERSECURITY FRAMEWORKS FOR FINANCIAL INSTITUTIONS: A COMPREHENSIVE REVIEW AND BEST PRACTICES","authors":"Lawrence Damilare Oyeniyi, Chinonye Esther Ugochukwu, Noluthando Zamanjomane Mhlongo","doi":"10.51594/csitrj.v5i4.1049","DOIUrl":"https://doi.org/10.51594/csitrj.v5i4.1049","url":null,"abstract":"In the digital epoch, where the financial sector stands as the cornerstone of global economic stability, the escalating sophistication of cyber threats poses an unprecedented challenge. This scholarly pursuit aimed to dissect the intricate web of cybersecurity within the financial domain, elucidating the evolving threat landscape, scrutinizing the efficacy of existing cybersecurity frameworks, and delineating strategic pathways for fortification against digital adversaries. Anchored in a qualitative methodology, the study embarked on a systematic literature review, meticulously sifting through contemporary academic discourse to unveil the nuances of cybersecurity challenges besieging financial institutions. The scope of this inquiry spanned the assessment of regulatory landscapes, the exploration of technological innovations in cybersecurity, and the critical examination of human factors influencing cybersecurity efficacy. The findings illuminate a stark reality—the existing cybersecurity frameworks, though foundational, are increasingly inadequate in the face of sophisticated cyber threats. The study advocates for a paradigmatic shift towards more adaptable, robust, and technology-driven cybersecurity frameworks, underscored by the imperative for regulatory agility and international collaboration. Conclusively, the paper posits that the future of cybersecurity in the financial sector hinges on a tripartite alliance among financial institutions, regulatory bodies, and technology providers, urging a unified front to navigate the cyber tempest. Recommendations call for an integrated approach that marries regulatory compliance with cutting-edge technological solutions, fostering a cybersecurity ecosystem that is both resilient and responsive to the digital zeitgeist. This scholarly endeavor not only contributes to the academic discourse on financial cybersecurity but also serves as a beacon for policymakers, practitioners, and stakeholders in charting a secure course in the digital financial frontier. \u0000Keywords: Cybersecurity, Financial Sector, Systematic Literature Review, Regulatory Compliance, Technological Innovation, Strategic Recommendations.","PeriodicalId":282796,"journal":{"name":"Computer Science & IT Research Journal","volume":"223 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140693198","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}
This review critically examines the integration of Machine Learning (ML) in drug discovery, highlighting its applications across target identification, hit discovery, lead optimization, and predictive toxicology. Despite ML's potential to revolutionize drug discovery through enhanced efficiency, predictive accuracy, and novel insights, significant challenges persist. These include issues related to data quality, model interpretability, integration into existing workflows, and regulatory and ethical considerations. The review advocates for advancements in algorithmic approaches, interdisciplinary collaboration, improved data-sharing practices, and evolving regulatory frameworks as potential solutions to these challenges. By addressing these hurdles and leveraging the capabilities of ML, the drug discovery process can be significantly accelerated, paving the way for the development of new therapeutics. This review calls for continued research, collaboration, and dialogue among stakeholders to realize the transformative potential of ML in drug discovery fully. Keywords: Machine Learning, Drug Discovery, Predictive Toxicology, Data Quality, Interdisciplinary Collaboration.
这篇综述认真研究了机器学习（ML）在药物发现中的应用，重点介绍了它在靶点识别、新药发现、先导物优化和预测性毒理学方面的应用。尽管机器学习有可能通过提高效率、预测准确性和新颖见解彻底改变药物发现，但重大挑战依然存在。这些挑战包括与数据质量、模型可解释性、与现有工作流程的整合以及监管和伦理考虑有关的问题。本综述主张将算法方法的进步、跨学科合作、数据共享实践的改进以及不断发展的监管框架作为应对这些挑战的潜在解决方案。通过解决这些障碍并利用 ML 的能力，可以大大加快药物发现过程，为开发新的治疗方法铺平道路。本综述呼吁利益相关者继续开展研究、合作和对话，以充分发挥 ML 在药物发现中的变革潜力。关键词机器学习 药物发现 预测毒理学 数据质量 跨学科合作
{"title":"MACHINE LEARNING IN DRUG DISCOVERY: A CRITICAL REVIEW OF APPLICATIONS AND CHALLENGES","authors":"Francisca Chibugo Udegbe, Ogochukwu Roseline Ebulue, Charles Chukwudalu Ebulue, Chukwunonso Sylvester Ekesiobi","doi":"10.51594/csitrj.v5i4.1048","DOIUrl":"https://doi.org/10.51594/csitrj.v5i4.1048","url":null,"abstract":"This review critically examines the integration of Machine Learning (ML) in drug discovery, highlighting its applications across target identification, hit discovery, lead optimization, and predictive toxicology. Despite ML's potential to revolutionize drug discovery through enhanced efficiency, predictive accuracy, and novel insights, significant challenges persist. These include issues related to data quality, model interpretability, integration into existing workflows, and regulatory and ethical considerations. The review advocates for advancements in algorithmic approaches, interdisciplinary collaboration, improved data-sharing practices, and evolving regulatory frameworks as potential solutions to these challenges. By addressing these hurdles and leveraging the capabilities of ML, the drug discovery process can be significantly accelerated, paving the way for the development of new therapeutics. This review calls for continued research, collaboration, and dialogue among stakeholders to realize the transformative potential of ML in drug discovery fully. \u0000Keywords: Machine Learning, Drug Discovery, Predictive Toxicology, Data Quality, Interdisciplinary Collaboration.","PeriodicalId":282796,"journal":{"name":"Computer Science & IT Research Journal","volume":"160 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140693432","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 : 2024-04-16DOI: 10.51594/csitrj.v5i4.1027
Oladele Junior Adeyeye, Ibrahim Akanbi
This research review article provides a comprehensive examination of optimization techniques in systems engineering, highlighting their pivotal role in enhancing system performance, efficiency, and problem-solving capabilities. Through a structured exploration encompassing theoretical frameworks, methodologies, applications, and significant findings, the article synthesizes current knowledge and advancements in the field. It delves into various optimization methods, including traditional linear and nonlinear programming, alongside emerging trends such as swarm intelligence, nature-inspired algorithms, and the integration of machine learning. Case studies and recent research findings underscore the practical implications and effectiveness of these techniques across diverse engineering challenges. The review identifies key insights, demonstrating the versatility and potential of optimization techniques to drive innovation in systems engineering. Furthermore, it offers recommendations for future research directions and practical applications, emphasizing the importance of interdisciplinary approaches, algorithm development, and the adoption of advanced techniques in industry practices. This article aims to inform researchers and practitioners alike, fostering the continued evolution and application of optimization techniques in systems engineering. Keywords: Optimization Techniques, Systems Engineering, Swarm Intelligence, Machine Learning, Algorithm Development.
{"title":"OPTIMIZATION IN SYSTEMS ENGINEERING: A REVIEW OF HOW DATA ANALYTICS AND OPTIMIZATION ALGORITHMS ARE APPLIED","authors":"Oladele Junior Adeyeye, Ibrahim Akanbi","doi":"10.51594/csitrj.v5i4.1027","DOIUrl":"https://doi.org/10.51594/csitrj.v5i4.1027","url":null,"abstract":"This research review article provides a comprehensive examination of optimization techniques in systems engineering, highlighting their pivotal role in enhancing system performance, efficiency, and problem-solving capabilities. Through a structured exploration encompassing theoretical frameworks, methodologies, applications, and significant findings, the article synthesizes current knowledge and advancements in the field. It delves into various optimization methods, including traditional linear and nonlinear programming, alongside emerging trends such as swarm intelligence, nature-inspired algorithms, and the integration of machine learning. Case studies and recent research findings underscore the practical implications and effectiveness of these techniques across diverse engineering challenges. The review identifies key insights, demonstrating the versatility and potential of optimization techniques to drive innovation in systems engineering. Furthermore, it offers recommendations for future research directions and practical applications, emphasizing the importance of interdisciplinary approaches, algorithm development, and the adoption of advanced techniques in industry practices. This article aims to inform researchers and practitioners alike, fostering the continued evolution and application of optimization techniques in systems engineering. \u0000Keywords: Optimization Techniques, Systems Engineering, Swarm Intelligence, Machine Learning, Algorithm Development.","PeriodicalId":282796,"journal":{"name":"Computer Science & IT Research Journal","volume":"25 46","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140697248","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 : 2024-04-16DOI: 10.51594/csitrj.v5i4.1026
Oladele Junior Adeyeye, Ibrahim Akanbi
This review examines the role of Artificial Intelligence (AI) and Machine Learning (ML) in addressing the complexities of systems engineering. It highlights how AI and ML are revolutionizing system design, integration, and lifecycle management by enabling automated design optimization, predictive maintenance, and efficient configuration management. These technologies allow for the analysis of large datasets to predict system failures and optimize performance, thereby enhancing the reliability and sustainability of engineering systems. Despite the promising applications, the integration of AI into systems engineering presents challenges, including technical hurdles, ethical considerations, and the need for comprehensive education and training. The paper emphasizes the importance of interdisciplinary approaches and the continuous evolution of educational programs to equip engineers with the skills to leverage AI effectively. Concluding thoughts underscore AI's potential to redefine systems engineering, advocating for a balanced approach that addresses both the opportunities and challenges presented by AI advancements. Keywords: Artificial Intelligence, Machine Learning, Systems Engineering, Automated Design, Predictive Maintenance, Configuration Management, Education and Training, Technology Integration.
本综述探讨了人工智能（AI）和机器学习（ML）在解决系统工程复杂性方面的作用。它强调了人工智能和 ML 如何通过实现自动设计优化、预测性维护和高效配置管理，彻底改变系统设计、集成和生命周期管理。这些技术可以分析大型数据集，预测系统故障并优化性能，从而提高工程系统的可靠性和可持续性。尽管人工智能的应用前景广阔，但将其融入系统工程仍面临诸多挑战，包括技术障碍、伦理考虑以及全面教育和培训的必要性。本文强调了跨学科方法和教育计划不断发展的重要性，以使工程师掌握有效利用人工智能的技能。最后，本文强调了人工智能重新定义系统工程的潜力，提倡采用一种平衡的方法来应对人工智能进步带来的机遇和挑战。关键词人工智能、机器学习、系统工程、自动化设计、预测性维护、配置管理、教育与培训、技术集成。
{"title":"ARTIFICIAL INTELLIGENCE FOR SYSTEMS ENGINEERING COMPLEXITY: A REVIEW ON THE USE OF AI AND MACHINE LEARNING ALGORITHMS","authors":"Oladele Junior Adeyeye, Ibrahim Akanbi","doi":"10.51594/csitrj.v5i4.1026","DOIUrl":"https://doi.org/10.51594/csitrj.v5i4.1026","url":null,"abstract":"This review examines the role of Artificial Intelligence (AI) and Machine Learning (ML) in addressing the complexities of systems engineering. It highlights how AI and ML are revolutionizing system design, integration, and lifecycle management by enabling automated design optimization, predictive maintenance, and efficient configuration management. These technologies allow for the analysis of large datasets to predict system failures and optimize performance, thereby enhancing the reliability and sustainability of engineering systems. Despite the promising applications, the integration of AI into systems engineering presents challenges, including technical hurdles, ethical considerations, and the need for comprehensive education and training. The paper emphasizes the importance of interdisciplinary approaches and the continuous evolution of educational programs to equip engineers with the skills to leverage AI effectively. Concluding thoughts underscore AI's potential to redefine systems engineering, advocating for a balanced approach that addresses both the opportunities and challenges presented by AI advancements. \u0000Keywords: Artificial Intelligence, Machine Learning, Systems Engineering, Automated Design, Predictive Maintenance, Configuration Management, Education and Training, Technology Integration.","PeriodicalId":282796,"journal":{"name":"Computer Science & IT Research Journal","volume":"6 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140695607","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 : 2024-04-14DOI: 10.51594/csitrj.v5i4.1025
Yahaya Haleem, E.M George Ditsa
The study examines the relationship between the external factors (government policy, external support and competitive pressure) and the implementation of the HRIS (acceptance and effectiveness). The study assessed the level of acceptability of each variable in the study. The study was a quantitative study which centers on question-based survey. The study used purposive sampling technique and a sample of 187 line managers of the eleven (11) MMDAs in the Upper West Region of Ghana were selected. The unit of analysis was at the individual level where opinions of the line managers were sought to assess the relationship between the individual characteristics and the implementation the HRIS. The unit of measurement was likert scale. SPSS was used to carry out the analysis of this study. Bivariate correlation was used to establish one-on-one relationship between variables operationalized in this study. The findings revealed that Competitive Pressure and External Support had a moderate level of acceptance whereas Government Policies have a low level of acceptance as factors that affect the implementation of the HRIS. The study revealed that, government policies, external support, competitive pressure had correlation with the acceptance of the HRIS. Lastly, it concluded that government colicies, competitive pressure had correlation with the effectiveness of the HRIS whereas external support had no correlation with the effectiveness of the HRIS. The study recommended Ghana's government to create sound regulations that will facilitate the HRIS adoption and implementation. Keywords: Human Resource Information System, Environmental Factors, Implementation, Government Policy, External Support, Competitive Advantage, Acceptance, Effectiveness.
{"title":"THE INFLUENCE OF EXTERNAL ENVIRONMENTAL FACTORS ON THE IMPLEMENTATION OF THE HUMAN RESOURCE INFORMATION SYSTEM IN GHANA. AN EMPIRICAL STUDY IN THE UPPER WEST REGION MMDA’S","authors":"Yahaya Haleem, E.M George Ditsa","doi":"10.51594/csitrj.v5i4.1025","DOIUrl":"https://doi.org/10.51594/csitrj.v5i4.1025","url":null,"abstract":"The study examines the relationship between the external factors (government policy, external support and competitive pressure) and the implementation of the HRIS (acceptance and effectiveness). The study assessed the level of acceptability of each variable in the study. The study was a quantitative study which centers on question-based survey. The study used purposive sampling technique and a sample of 187 line managers of the eleven (11) MMDAs in the Upper West Region of Ghana were selected. The unit of analysis was at the individual level where opinions of the line managers were sought to assess the relationship between the individual characteristics and the implementation the HRIS. The unit of measurement was likert scale. SPSS was used to carry out the analysis of this study. Bivariate correlation was used to establish one-on-one relationship between variables operationalized in this study. The findings revealed that Competitive Pressure and External Support had a moderate level of acceptance whereas Government Policies have a low level of acceptance as factors that affect the implementation of the HRIS. The study revealed that, government policies, external support, competitive pressure had correlation with the acceptance of the HRIS. Lastly, it concluded that government colicies, competitive pressure had correlation with the effectiveness of the HRIS whereas external support had no correlation with the effectiveness of the HRIS. The study recommended Ghana's government to create sound regulations that will facilitate the HRIS adoption and implementation. \u0000Keywords: Human Resource Information System, Environmental Factors, Implementation, Government Policy, External Support, Competitive Advantage, Acceptance, Effectiveness.","PeriodicalId":282796,"journal":{"name":"Computer Science & IT Research Journal","volume":"164 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140706619","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}
This comprehensive review delves into the transformative impact of artificial intelligence (AI) on drone technology, examining its pivotal role in revolutionizing various applications. As drones continue to evolve from recreational gadgets to indispensable tools across industries, the integration of AI enhances their capabilities, enabling advanced functionalities and expanding their potential use cases. The convergence of AI and drone technology has given rise to a myriad of applications, transforming industries ranging from agriculture to surveillance. Machine learning algorithms empower drones with autonomous navigation capabilities, allowing them to navigate complex environments and adapt to dynamic scenarios. Computer vision technologies enable drones to perceive and analyze visual information, facilitating tasks such as object recognition, tracking, and environmental monitoring. These advancements significantly contribute to enhanced aerial surveying, precision agriculture, and disaster response efforts. In the realm of precision agriculture, AI-equipped drones aid in crop monitoring, disease detection, and yield estimation, optimizing resource allocation and boosting agricultural productivity. Drones with AI-driven capabilities are increasingly employed in environmental monitoring, wildlife conservation, and disaster response, providing real-time data for efficient decision-making. Recent trends in AI-infused drone technology highlight its dynamic evolution. Edge computing solutions empower drones to process data locally, reducing latency and enhancing real-time responsiveness. Reinforcement learning algorithms enable drones to learn from their experiences, adapting and optimizing their performance over time. Swarm intelligence, an emerging field in drone technology, leverages AI to enable coordinated and synchronized actions among multiple drones, expanding their capabilities for collaborative tasks. In conclusion, this review sheds light on the pivotal role of AI in transforming drone technology and expanding its applications. The synergy between AI and drones has unlocked new possibilities across various industries, ranging from agriculture to disaster response. As technology continues to advance, the collaborative integration of AI and drones promises to redefine the future of aerial technology, introducing unprecedented efficiencies and capabilities across diverse sectors. Keywords: Role, AI, Drone, Applications, Technology.
{"title":"REVIEWING THE ROLE OF AI IN DRONE TECHNOLOGY AND APPLICATIONS","authors":"Nwankwo Constance Obiuto, Igberaese clinton festus-ikhuoria, Oladiran Kayode Olajiga, Riliwan Adekola Adebayo","doi":"10.51594/csitrj.v5i4.1019","DOIUrl":"https://doi.org/10.51594/csitrj.v5i4.1019","url":null,"abstract":"This comprehensive review delves into the transformative impact of artificial intelligence (AI) on drone technology, examining its pivotal role in revolutionizing various applications. As drones continue to evolve from recreational gadgets to indispensable tools across industries, the integration of AI enhances their capabilities, enabling advanced functionalities and expanding their potential use cases. The convergence of AI and drone technology has given rise to a myriad of applications, transforming industries ranging from agriculture to surveillance. Machine learning algorithms empower drones with autonomous navigation capabilities, allowing them to navigate complex environments and adapt to dynamic scenarios. Computer vision technologies enable drones to perceive and analyze visual information, facilitating tasks such as object recognition, tracking, and environmental monitoring. These advancements significantly contribute to enhanced aerial surveying, precision agriculture, and disaster response efforts. In the realm of precision agriculture, AI-equipped drones aid in crop monitoring, disease detection, and yield estimation, optimizing resource allocation and boosting agricultural productivity. Drones with AI-driven capabilities are increasingly employed in environmental monitoring, wildlife conservation, and disaster response, providing real-time data for efficient decision-making. Recent trends in AI-infused drone technology highlight its dynamic evolution. Edge computing solutions empower drones to process data locally, reducing latency and enhancing real-time responsiveness. Reinforcement learning algorithms enable drones to learn from their experiences, adapting and optimizing their performance over time. Swarm intelligence, an emerging field in drone technology, leverages AI to enable coordinated and synchronized actions among multiple drones, expanding their capabilities for collaborative tasks. In conclusion, this review sheds light on the pivotal role of AI in transforming drone technology and expanding its applications. The synergy between AI and drones has unlocked new possibilities across various industries, ranging from agriculture to disaster response. As technology continues to advance, the collaborative integration of AI and drones promises to redefine the future of aerial technology, introducing unprecedented efficiencies and capabilities across diverse sectors. \u0000Keywords: Role, AI, Drone, Applications, Technology.","PeriodicalId":282796,"journal":{"name":"Computer Science & IT Research Journal","volume":"223 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140719731","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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