Subsea maintenance and production represent critical aspects of offshore operations, vital for sustaining energy production and ensuring operational efficiency. However, these endeavors face numerous challenges, including the complexities of deepwater environments, harsh weather conditions, and the high costs associated with traditional maintenance methods. To address these challenges, this paper explores the integration of technological innovations and optimized work methods in subsea operations. Technological innovations play a pivotal role in revolutionizing subsea maintenance and production. Remote monitoring and control systems enable real-time data collection and decision-making, enhancing operational visibility and efficiency. Autonomous underwater vehicles (AUVs) offer the capability to conduct inspections and repairs in remote and hazardous environments, reducing human intervention and associated risks. Robotics and automation further streamline maintenance tasks, improving accuracy and reducing downtime. Advanced materials and coatings enhance equipment durability and corrosion resistance, prolonging asset lifecycles and reducing maintenance requirements. In parallel, optimized work methods offer strategic approaches to enhance subsea operations' effectiveness. Predictive maintenance strategies leverage data analytics and machine learning to anticipate equipment failures, enabling proactive interventions and minimizing downtime. Condition-based monitoring facilitates real-time assessment of asset health, enabling timely maintenance interventions and cost savings. Integrated asset management systems provide holistic insights into asset performance and facilitate informed decision-making. Lean operations and continuous improvement methodologies further optimize workflows, driving operational excellence and cost efficiency. Through case studies and industry examples, this paper highlights the successful implementation of technological innovations and optimized work methods in subsea maintenance and production. Furthermore, it explores future trends, regulatory considerations, and the importance of industry collaborations in shaping the future of subsea operations. Ultimately, the integration of these approaches offers a pathway towards enhanced operational efficiency, reduced costs, and sustainable subsea operations. Keywords: Technological Innovations, Optimized Work Methods, Subsea Maintenance and Production.
{"title":"Technological innovations and optimized work methods in subsea maintenance and production","authors":"Obinna Joshua Ochulor, Oludayo Olatoye Sofoluwe, Ayemere Ukato, Dazok Donald Jambol","doi":"10.51594/estj.v5i5.1112","DOIUrl":"https://doi.org/10.51594/estj.v5i5.1112","url":null,"abstract":"Subsea maintenance and production represent critical aspects of offshore operations, vital for sustaining energy production and ensuring operational efficiency. However, these endeavors face numerous challenges, including the complexities of deepwater environments, harsh weather conditions, and the high costs associated with traditional maintenance methods. To address these challenges, this paper explores the integration of technological innovations and optimized work methods in subsea operations. Technological innovations play a pivotal role in revolutionizing subsea maintenance and production. Remote monitoring and control systems enable real-time data collection and decision-making, enhancing operational visibility and efficiency. Autonomous underwater vehicles (AUVs) offer the capability to conduct inspections and repairs in remote and hazardous environments, reducing human intervention and associated risks. Robotics and automation further streamline maintenance tasks, improving accuracy and reducing downtime. Advanced materials and coatings enhance equipment durability and corrosion resistance, prolonging asset lifecycles and reducing maintenance requirements. In parallel, optimized work methods offer strategic approaches to enhance subsea operations' effectiveness. Predictive maintenance strategies leverage data analytics and machine learning to anticipate equipment failures, enabling proactive interventions and minimizing downtime. Condition-based monitoring facilitates real-time assessment of asset health, enabling timely maintenance interventions and cost savings. Integrated asset management systems provide holistic insights into asset performance and facilitate informed decision-making. Lean operations and continuous improvement methodologies further optimize workflows, driving operational excellence and cost efficiency. Through case studies and industry examples, this paper highlights the successful implementation of technological innovations and optimized work methods in subsea maintenance and production. Furthermore, it explores future trends, regulatory considerations, and the importance of industry collaborations in shaping the future of subsea operations. Ultimately, the integration of these approaches offers a pathway towards enhanced operational efficiency, reduced costs, and sustainable subsea operations. \u0000Keywords: Technological Innovations, Optimized Work Methods, Subsea Maintenance and Production.","PeriodicalId":113413,"journal":{"name":"Engineering Science & Technology Journal","volume":"294 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012586","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}
Vincent Ugochukwu Oguanobi, Oloruntosin Tolulope Joel
The renewable energy sector has witnessed remarkable growth in recent years, driven by global efforts to mitigate climate change and transition towards sustainable energy sources. Startups play a crucial role in this transition, often pioneering innovative solutions and technologies. However, for these startups to thrive and contribute significantly to the renewable energy landscape, scalable business models are essential. This abstract explores strategies for leveraging Geographic Information System (GIS) technology to enhance scalability in small and medium-sized enterprise (SME) startups operating in the renewable energy sector. GIS technology offers a powerful framework for analyzing and visualizing spatial data, providing valuable insights into site selection, resource assessment, and infrastructure planning. By integrating GIS into their business models, startups can optimize operations, reduce costs, and accelerate growth. This review discusses various strategies for utilizing GIS technology, including market analysis, site suitability assessment, supply chain optimization, and infrastructure planning. Drawing on case studies and industry examples, this review highlights the effectiveness of GIS in enhancing scalability for renewable energy startups. It also addresses the challenges and limitations associated with GIS implementation, such as technical complexities, data accessibility, and cost considerations. Furthermore, this review discusses emerging trends in GIS technology and their potential impact on the renewable energy sector, offering insights into future opportunities for startups. In conclusion, this review emphasizes the importance of GIS technology in facilitating scalable business models for renewable energy startups. By harnessing the power of GIS, SMEs can unlock new growth opportunities, drive innovation, and contribute significantly to the transition towards a sustainable energy future. Keywords: Scalable Business Models, Startups, Renewable Energy, GIS Technology, SME Scaling.
{"title":"Scalable business models for startups in renewable energy: Strategies for using GIS technology to enhance SME scaling","authors":"Vincent Ugochukwu Oguanobi, Oloruntosin Tolulope Joel","doi":"10.51594/estj.v5i5.1109","DOIUrl":"https://doi.org/10.51594/estj.v5i5.1109","url":null,"abstract":"The renewable energy sector has witnessed remarkable growth in recent years, driven by global efforts to mitigate climate change and transition towards sustainable energy sources. Startups play a crucial role in this transition, often pioneering innovative solutions and technologies. However, for these startups to thrive and contribute significantly to the renewable energy landscape, scalable business models are essential. This abstract explores strategies for leveraging Geographic Information System (GIS) technology to enhance scalability in small and medium-sized enterprise (SME) startups operating in the renewable energy sector. GIS technology offers a powerful framework for analyzing and visualizing spatial data, providing valuable insights into site selection, resource assessment, and infrastructure planning. By integrating GIS into their business models, startups can optimize operations, reduce costs, and accelerate growth. This review discusses various strategies for utilizing GIS technology, including market analysis, site suitability assessment, supply chain optimization, and infrastructure planning. Drawing on case studies and industry examples, this review highlights the effectiveness of GIS in enhancing scalability for renewable energy startups. It also addresses the challenges and limitations associated with GIS implementation, such as technical complexities, data accessibility, and cost considerations. Furthermore, this review discusses emerging trends in GIS technology and their potential impact on the renewable energy sector, offering insights into future opportunities for startups. \u0000In conclusion, this review emphasizes the importance of GIS technology in facilitating scalable business models for renewable energy startups. By harnessing the power of GIS, SMEs can unlock new growth opportunities, drive innovation, and contribute significantly to the transition towards a sustainable energy future. \u0000Keywords: Scalable Business Models, Startups, Renewable Energy, GIS Technology, SME Scaling.","PeriodicalId":113413,"journal":{"name":"Engineering Science & Technology Journal","volume":"308 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012231","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 executive summary introduces the concept paper on Green Architecture, focusing specifically on the integration of vertical greenery in urban design. Green architecture, characterized by sustainable design principles and environmental consciousness, aims to enhance urban environments by incorporating vegetation into built structures. Vertical greenery, a key component of green architecture, involves the strategic placement of vegetation on vertical surfaces such as walls, facades, and rooftops. This concept paper explores the potential of vertical greenery to mitigate environmental issues in urban areas, improve air quality, reduce the urban heat island effect, and enhance biodiversity. The paper proposes a conceptual framework for conceptualizing vertical greenery in urban design, emphasizing the importance of integrating natural elements into the built environment. It discusses various strategies for implementing vertical greenery, including the selection of suitable plant species, design considerations for irrigation and structural stability, and the incorporation of greenery into urban planning processes. Moreover, the concept paper highlights the social and economic benefits of vertical greenery, such as improved health and well-being for residents, increased property values, and enhanced aesthetics of urban spaces. It also emphasizes the role of stakeholder engagement, interdisciplinary collaboration, and ongoing monitoring and evaluation in the successful implementation of vertical greenery projects. In conclusion, this executive summary outlines the significance of incorporating vertical greenery into urban design practices as a means to promote sustainability, resilience, and livability in cities. By embracing the principles of green architecture and integrating vertical greenery into urban landscapes, cities can create healthier, more vibrant, and environmentally sustainable communities for current and future generations. Keywords: Urban, Design, Green, Architecture, Vertical.
{"title":"Green architecture: Conceptualizing vertical greenery in urban design","authors":"Azubuike Chukwudi Okwandu, Dorcas Oluwajuwonlo Akande, Zamathula Queen Sikhakhane Nwokediegwu","doi":"10.51594/estj.v5i5.1114","DOIUrl":"https://doi.org/10.51594/estj.v5i5.1114","url":null,"abstract":"This executive summary introduces the concept paper on Green Architecture, focusing specifically on the integration of vertical greenery in urban design. Green architecture, characterized by sustainable design principles and environmental consciousness, aims to enhance urban environments by incorporating vegetation into built structures. Vertical greenery, a key component of green architecture, involves the strategic placement of vegetation on vertical surfaces such as walls, facades, and rooftops. This concept paper explores the potential of vertical greenery to mitigate environmental issues in urban areas, improve air quality, reduce the urban heat island effect, and enhance biodiversity. The paper proposes a conceptual framework for conceptualizing vertical greenery in urban design, emphasizing the importance of integrating natural elements into the built environment. It discusses various strategies for implementing vertical greenery, including the selection of suitable plant species, design considerations for irrigation and structural stability, and the incorporation of greenery into urban planning processes. Moreover, the concept paper highlights the social and economic benefits of vertical greenery, such as improved health and well-being for residents, increased property values, and enhanced aesthetics of urban spaces. It also emphasizes the role of stakeholder engagement, interdisciplinary collaboration, and ongoing monitoring and evaluation in the successful implementation of vertical greenery projects. In conclusion, this executive summary outlines the significance of incorporating vertical greenery into urban design practices as a means to promote sustainability, resilience, and livability in cities. By embracing the principles of green architecture and integrating vertical greenery into urban landscapes, cities can create healthier, more vibrant, and environmentally sustainable communities for current and future generations. \u0000Keywords: Urban, Design, Green, Architecture, Vertical.","PeriodicalId":113413,"journal":{"name":"Engineering Science & Technology Journal","volume":"253 6‐8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141012821","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 paper explores the transformative impact of artificial intelligence (AI) on personalized medicine and its potential to revolutionize healthcare outcomes. AI technologies, ranging from data analysis and interpretation to diagnostic tools and treatment planning, offer unprecedented opportunities for tailoring medical interventions to individual patient characteristics. Through sophisticated algorithms, AI facilitates the analysis of complex biological data, predicts disease risks, and enhances diagnostic accuracy. Furthermore, AI-powered personalized medicine promises to expand access to high-quality healthcare and address global health disparities. However, challenges such as data privacy, bias, and regulatory hurdles must be addressed to ensure the responsible integration of AI into healthcare practices. This paper underscores the importance of interdisciplinary collaboration, ethical considerations, and policy-making efforts in harnessing AI's potential to advance personalized medicine responsibly. Keywords: Artificial Intelligence, Personalized Medicine, Healthcare, Data Analysis, Ethical Considerations, Interdisciplinary Collaboration
{"title":"AI'S IMPACT ON PERSONALIZED MEDICINE: TAILORING TREATMENTS FOR IMPROVED HEALTH OUTCOMES","authors":"Francisca Chibugo Udegbe, Ogochukwu Roseline Ebulue, Charles Chukwudalu Ebulue, Chukwunonso Sylvester Ekesiobi","doi":"10.51594/estj.v5i4.1040","DOIUrl":"https://doi.org/10.51594/estj.v5i4.1040","url":null,"abstract":"This review paper explores the transformative impact of artificial intelligence (AI) on personalized medicine and its potential to revolutionize healthcare outcomes. AI technologies, ranging from data analysis and interpretation to diagnostic tools and treatment planning, offer unprecedented opportunities for tailoring medical interventions to individual patient characteristics. Through sophisticated algorithms, AI facilitates the analysis of complex biological data, predicts disease risks, and enhances diagnostic accuracy. Furthermore, AI-powered personalized medicine promises to expand access to high-quality healthcare and address global health disparities. However, challenges such as data privacy, bias, and regulatory hurdles must be addressed to ensure the responsible integration of AI into healthcare practices. This paper underscores the importance of interdisciplinary collaboration, ethical considerations, and policy-making efforts in harnessing AI's potential to advance personalized medicine responsibly. \u0000Keywords: Artificial Intelligence, Personalized Medicine, Healthcare, Data Analysis, Ethical Considerations, Interdisciplinary Collaboration","PeriodicalId":113413,"journal":{"name":"Engineering Science & Technology Journal","volume":"81 S363","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140694139","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 systematic review explores the advancements and challenges associated with the integration of artificial intelligence (AI) in promoting technical literacy. Technical literacy is increasingly important in today's digital age, where understanding and utilizing technology are essential skills. AI has the potential to enhance technical literacy by providing personalized learning experiences, facilitating hands-on learning, and offering innovative tools and resources. However, the integration of AI in education also presents challenges, such as ensuring equitable access, addressing ethical considerations, and overcoming technical barriers. The review examines a range of studies and literature related to AI integration for technical literacy, focusing on key themes such as personalized learning, hands-on learning, and innovative tools. It highlights the potential of AI to transform technical education by providing tailored learning experiences that cater to individual needs and preferences. AI-driven tools, such as simulations, virtual laboratories, and intelligent tutoring systems, have been shown to enhance student engagement and understanding of technical concepts. Despite the benefits, the review also identifies challenges associated with AI integration, including the need for teacher training, concerns about data privacy, and the risk of reinforcing existing inequalities. Addressing these challenges requires careful planning, collaboration between educators and technology developers, and a commitment to ensuring equitable access to AI-driven educational resources. Overall, this review provides insights into the current state of AI integration for technical literacy and highlights the opportunities and challenges associated with this approach. By addressing these challenges and leveraging the potential of AI, educators can enhance technical literacy and prepare students for success in a technology-driven world. Keywords: Advancement, Challenges, AI, Integration, Technical Literacy.
{"title":"ADVANCEMENTS AND CHALLENGES IN AI INTEGRATION FOR TECHNICAL LITERACY: A SYSTEMATIC REVIEW","authors":"Babajide Tolulope Familoni, Nneamaka Chisom Onyebuchi","doi":"10.51594/estj.v5i4.1042","DOIUrl":"https://doi.org/10.51594/estj.v5i4.1042","url":null,"abstract":"This systematic review explores the advancements and challenges associated with the integration of artificial intelligence (AI) in promoting technical literacy. Technical literacy is increasingly important in today's digital age, where understanding and utilizing technology are essential skills. AI has the potential to enhance technical literacy by providing personalized learning experiences, facilitating hands-on learning, and offering innovative tools and resources. However, the integration of AI in education also presents challenges, such as ensuring equitable access, addressing ethical considerations, and overcoming technical barriers. The review examines a range of studies and literature related to AI integration for technical literacy, focusing on key themes such as personalized learning, hands-on learning, and innovative tools. It highlights the potential of AI to transform technical education by providing tailored learning experiences that cater to individual needs and preferences. AI-driven tools, such as simulations, virtual laboratories, and intelligent tutoring systems, have been shown to enhance student engagement and understanding of technical concepts. Despite the benefits, the review also identifies challenges associated with AI integration, including the need for teacher training, concerns about data privacy, and the risk of reinforcing existing inequalities. Addressing these challenges requires careful planning, collaboration between educators and technology developers, and a commitment to ensuring equitable access to AI-driven educational resources. Overall, this review provides insights into the current state of AI integration for technical literacy and highlights the opportunities and challenges associated with this approach. By addressing these challenges and leveraging the potential of AI, educators can enhance technical literacy and prepare students for success in a technology-driven world. \u0000Keywords: Advancement, Challenges, AI, Integration, Technical Literacy.","PeriodicalId":113413,"journal":{"name":"Engineering Science & Technology Journal","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140693952","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}
Scrum, a popular Agile framework, has been widely adopted by U.S. technology companies to enhance team performance and deliver high-quality products efficiently. This review explores how successful U.S. technology companies leverage Scrum to elevate team performance, drive innovation, and achieve business objectives. Key insights from these companies reveal the transformative impact of Scrum on team dynamics, collaboration, and product delivery. By embracing Scrum principles, such as iterative development, self-organization, and continuous improvement, these companies have been able to overcome challenges, adapt to changing market demands, and deliver value to customers. Through case studies and real-world examples, this review highlights the strategies and practices that have contributed to the success of U.S. technology companies using Scrum. These include establishing cross-functional teams, empowering team members to make decisions, and fostering a culture of transparency and accountability. Furthermore, this Review discusses the role of leadership in supporting and enabling Scrum teams. Effective leadership is crucial for setting clear goals, removing obstacles, and creating an environment that fosters innovation and collaboration. Overall, this review provides valuable insights into how Scrum can be used to elevate team performance in U.S. technology companies. By adopting Scrum principles and practices, companies can improve their ability to respond to market changes, deliver products faster, and ultimately achieve greater success in today's competitive landscape. Keywords: Elevating, Team Performance, Scrum, Technology Companies, Insights.
{"title":"ELEVATING TEAM PERFORMANCE WITH SCRUM: INSIGHTS FROM SUCCESSFUL U.S. TECHNOLOGY COMPANIES","authors":"Excel G Chukwurah, Samuel Aderemi","doi":"10.51594/estj.v5i4.1038","DOIUrl":"https://doi.org/10.51594/estj.v5i4.1038","url":null,"abstract":"Scrum, a popular Agile framework, has been widely adopted by U.S. technology companies to enhance team performance and deliver high-quality products efficiently. This review explores how successful U.S. technology companies leverage Scrum to elevate team performance, drive innovation, and achieve business objectives. Key insights from these companies reveal the transformative impact of Scrum on team dynamics, collaboration, and product delivery. By embracing Scrum principles, such as iterative development, self-organization, and continuous improvement, these companies have been able to overcome challenges, adapt to changing market demands, and deliver value to customers. Through case studies and real-world examples, this review highlights the strategies and practices that have contributed to the success of U.S. technology companies using Scrum. These include establishing cross-functional teams, empowering team members to make decisions, and fostering a culture of transparency and accountability. Furthermore, this Review discusses the role of leadership in supporting and enabling Scrum teams. Effective leadership is crucial for setting clear goals, removing obstacles, and creating an environment that fosters innovation and collaboration. Overall, this review provides valuable insights into how Scrum can be used to elevate team performance in U.S. technology companies. By adopting Scrum principles and practices, companies can improve their ability to respond to market changes, deliver products faster, and ultimately achieve greater success in today's competitive landscape. \u0000Keywords: Elevating, Team Performance, Scrum, Technology Companies, Insights.","PeriodicalId":113413,"journal":{"name":"Engineering Science & Technology Journal","volume":"37 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140693955","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 study provides a comprehensive review of the cutting-edge intersections of biology and engineering in the realm of medical therapeutics, focusing on the advancements and applications of synthetic biology. The main objectives were to explore the historical evolution, define the scope, and analyze the current state-of-the-art in synthetic biology, particularly in drug development and treatment strategies. The methodology employed a systematic literature review and content analysis, utilizing a range of academic databases to gather relevant peer-reviewed articles published between 2013 and 2023. Key findings revealED that synthetic biology, through the integration of engineering principles and biological systems, has led to significant innovations in medical therapeutics. These include the development of novel drug delivery systems, targeted therapies, and personalized medicine approaches. The study highlights the challenges and limitations in current synthetic biology approaches, such as ethical concerns, regulatory hurdles, and the need for interdisciplinary collaboration. The future landscape of synthetic biology in medicine is marked by both challenges and prospects. The field holds immense potential for addressing complex diseases and enhancing healthcare delivery, yet faces significant challenges in ethical considerations and regulatory frameworks. Strategic recommendations are provided for researchers, industry leaders, and policymakers, emphasizing the need for continuous innovation, ethical applications, and comprehensive regulatory strategies. Finally, synthetic biology stands as a transformative force in medical therapeutics, with the potential to revolutionize healthcare. Future research should focus on overcoming current limitations and exploring new applications, ensuring the field's continued advancement and contribution to global healthcare. Keywords: Synthetic Biology, Medical Therapeutics, Drug Development, Bioengineering.
{"title":"SYNTHETIC BIOLOGY AND ITS POTENTIAL IN U.S. MEDICAL THERAPEUTICS: A COMPREHENSIVE REVIEW: EXPLORING THE CUTTING-EDGE INTERSECTIONS OF BIOLOGY AND ENGINEERING IN DRUG DEVELOPMENT AND TREATMENTS","authors":"Francisca Chibugo Udegbe, Ogochukwu Roseline Ebulue, Charles Chukwudalu Ebulue, Chukwunonso Sylvester Ekesiobi","doi":"10.51594/estj.v5i4.1041","DOIUrl":"https://doi.org/10.51594/estj.v5i4.1041","url":null,"abstract":"This study provides a comprehensive review of the cutting-edge intersections of biology and engineering in the realm of medical therapeutics, focusing on the advancements and applications of synthetic biology. The main objectives were to explore the historical evolution, define the scope, and analyze the current state-of-the-art in synthetic biology, particularly in drug development and treatment strategies. The methodology employed a systematic literature review and content analysis, utilizing a range of academic databases to gather relevant peer-reviewed articles published between 2013 and 2023. Key findings revealED that synthetic biology, through the integration of engineering principles and biological systems, has led to significant innovations in medical therapeutics. These include the development of novel drug delivery systems, targeted therapies, and personalized medicine approaches. The study highlights the challenges and limitations in current synthetic biology approaches, such as ethical concerns, regulatory hurdles, and the need for interdisciplinary collaboration. The future landscape of synthetic biology in medicine is marked by both challenges and prospects. The field holds immense potential for addressing complex diseases and enhancing healthcare delivery, yet faces significant challenges in ethical considerations and regulatory frameworks. Strategic recommendations are provided for researchers, industry leaders, and policymakers, emphasizing the need for continuous innovation, ethical applications, and comprehensive regulatory strategies. Finally, synthetic biology stands as a transformative force in medical therapeutics, with the potential to revolutionize healthcare. Future research should focus on overcoming current limitations and exploring new applications, ensuring the field's continued advancement and contribution to global healthcare. \u0000Keywords: Synthetic Biology, Medical Therapeutics, Drug Development, Bioengineering.","PeriodicalId":113413,"journal":{"name":"Engineering Science & Technology Journal","volume":"87 s1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140693696","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}
The Software-as-a-Service (SaaS) industry in the United States operates within a complex regulatory landscape, including data protection laws, intellectual property regulations, and industry-specific compliance requirements. This review explores the role of Technology Policy Managers (TPMs) in guiding SaaS companies to innovate while staying compliant with these regulations. SaaS companies are constantly innovating to meet the evolving needs of their customers and stay ahead in a competitive market. However, this innovation often intersects with regulatory boundaries that can impact product development and deployment. TPMs play a crucial role in navigating these boundaries by understanding and interpreting relevant regulations, ensuring that SaaS products comply with legal requirements. One of the key challenges for SaaS companies is data protection compliance, including regulations such as the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR). TPMs help SaaS companies implement privacy-by-design principles, ensuring that data protection is embedded into product development from the outset. This proactive approach not only helps companies comply with regulations but also enhances user trust and satisfaction. TPMs also play a crucial role in managing intellectual property (IP) risks in SaaS innovation. They help companies understand and protect their IP rights, ensuring that innovations are not infringing on existing patents or copyrights. TPMs work closely with legal teams to assess and mitigate IP risks, allowing SaaS companies to innovate confidently while respecting the rights of others. In addition to data protection and IP issues, TPMs help SaaS companies navigate industry-specific regulations and standards. For example, in the healthcare industry, SaaS companies must comply with the Health Insurance Portability and Accountability Act (HIPAA), which sets standards for the protection of patient health information. TPMs ensure that SaaS products meet these standards, enabling companies to enter and succeed in regulated markets. In conclusion, TPMs play a vital role in leading SaaS innovation within U.S. regulatory boundaries. By understanding and navigating complex regulations, TPMs help SaaS companies innovate responsibly, ensuring compliance while driving growth and success in the dynamic SaaS industry. Keywords: TPMs, Navigating Compliance, Regulatory Boundaries, Leading SaaS, Innovation.
{"title":"LEADING SAAS INNOVATION WITHIN U.S. REGULATORY BOUNDARIES: THE ROLE OF TPMS IN NAVIGATING COMPLIANCE","authors":"Excel G Chukwurah","doi":"10.51594/estj.v5i4.1039","DOIUrl":"https://doi.org/10.51594/estj.v5i4.1039","url":null,"abstract":"The Software-as-a-Service (SaaS) industry in the United States operates within a complex regulatory landscape, including data protection laws, intellectual property regulations, and industry-specific compliance requirements. This review explores the role of Technology Policy Managers (TPMs) in guiding SaaS companies to innovate while staying compliant with these regulations. SaaS companies are constantly innovating to meet the evolving needs of their customers and stay ahead in a competitive market. However, this innovation often intersects with regulatory boundaries that can impact product development and deployment. TPMs play a crucial role in navigating these boundaries by understanding and interpreting relevant regulations, ensuring that SaaS products comply with legal requirements. One of the key challenges for SaaS companies is data protection compliance, including regulations such as the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR). TPMs help SaaS companies implement privacy-by-design principles, ensuring that data protection is embedded into product development from the outset. This proactive approach not only helps companies comply with regulations but also enhances user trust and satisfaction. TPMs also play a crucial role in managing intellectual property (IP) risks in SaaS innovation. They help companies understand and protect their IP rights, ensuring that innovations are not infringing on existing patents or copyrights. TPMs work closely with legal teams to assess and mitigate IP risks, allowing SaaS companies to innovate confidently while respecting the rights of others. In addition to data protection and IP issues, TPMs help SaaS companies navigate industry-specific regulations and standards. For example, in the healthcare industry, SaaS companies must comply with the Health Insurance Portability and Accountability Act (HIPAA), which sets standards for the protection of patient health information. TPMs ensure that SaaS products meet these standards, enabling companies to enter and succeed in regulated markets. In conclusion, TPMs play a vital role in leading SaaS innovation within U.S. regulatory boundaries. By understanding and navigating complex regulations, TPMs help SaaS companies innovate responsibly, ensuring compliance while driving growth and success in the dynamic SaaS industry. \u0000Keywords: TPMs, Navigating Compliance, Regulatory Boundaries, Leading SaaS, Innovation.","PeriodicalId":113413,"journal":{"name":"Engineering Science & Technology Journal","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140691136","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 research review article explores the transformative impact of data-driven decision-making (DDDM) across various sectors, highlighting the integration of advanced analytics to enhance organizational efficiency, innovation, and strategic planning. Despite the potential benefits, the adoption of DDDM poses significant challenges, including data quality issues, integration complexities, and the need for a cultural shift towards valuing data analytics. Through a comprehensive analysis of recent research and case studies, this article synthesizes key findings, emerging trends, and future research areas in DDDM. It provides practical recommendations for practitioners aiming to implement and optimize DDDM processes, emphasizing the importance of fostering a data-driven culture, investing in robust data infrastructure, and ensuring the ethical use of data. Additionally, the article offers suggestions for continuous improvement and adaptation to technological advancements, advocating for regular strategy reviews, monitoring emerging trends, and fostering innovation. By addressing these challenges and leveraging the outlined recommendations, organizations can unlock the full potential of DDDM, driving significant advancements in efficiency, competitiveness, and strategic decision-making in the digital age. Keywords: Data-driven Decision Making, Engineering Management, Machine Learning, Big Data, Advanced Analytics, Organizational Efficiency, Data Quality and Infrastructure, Technological Advancements.
{"title":"A REVIEW OF DATA-DRIVEN DECISION MAKING IN ENGINEERING MANAGEMENT","authors":"Oladele Junior Adeyeye, Ibrahim Akanbi","doi":"10.51594/estj.v5i4.1028","DOIUrl":"https://doi.org/10.51594/estj.v5i4.1028","url":null,"abstract":"This research review article explores the transformative impact of data-driven decision-making (DDDM) across various sectors, highlighting the integration of advanced analytics to enhance organizational efficiency, innovation, and strategic planning. Despite the potential benefits, the adoption of DDDM poses significant challenges, including data quality issues, integration complexities, and the need for a cultural shift towards valuing data analytics. Through a comprehensive analysis of recent research and case studies, this article synthesizes key findings, emerging trends, and future research areas in DDDM. It provides practical recommendations for practitioners aiming to implement and optimize DDDM processes, emphasizing the importance of fostering a data-driven culture, investing in robust data infrastructure, and ensuring the ethical use of data. Additionally, the article offers suggestions for continuous improvement and adaptation to technological advancements, advocating for regular strategy reviews, monitoring emerging trends, and fostering innovation. By addressing these challenges and leveraging the outlined recommendations, organizations can unlock the full potential of DDDM, driving significant advancements in efficiency, competitiveness, and strategic decision-making in the digital age. \u0000Keywords: Data-driven Decision Making, Engineering Management, Machine Learning, Big Data, Advanced Analytics, Organizational Efficiency, Data Quality and Infrastructure, Technological Advancements.","PeriodicalId":113413,"journal":{"name":"Engineering Science & Technology Journal","volume":"86 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140695737","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 research review explores the transformative intersection of Big Data and Systems Engineering (SE), a convergence that leverages the vast capabilities of Big Data analytics to enhance the design, analysis, and management of complex systems. As the digital era ushers in unprecedented volumes of data, traditional systems engineering approaches are challenged to adapt, necessitating a paradigm shift towards integrating Big Data technologies. This review draws on recent scholarly contributions to highlight the implications, challenges, and innovative solutions emerging at this intersection. The integration of Big Data into Systems Engineering introduces significant opportunities for innovation. By processing and analyzing vast datasets, systems engineers can uncover hidden patterns and insights, leading to more efficient, reliable, and adaptable systems. However, this integration is not without its challenges. Information security emerges as a paramount concern, with the risk of insider attacks necessitating the development of new architectural solutions. Furthermore, the benchmarking and evaluation of Big Data systems present unique challenges due to the diversity of data and workloads involved. To address these challenges, this review examines several key contributions to the field. It discusses a formal framework for designing information systems that handle heterogeneous data, emphasizing the role of ontological models in separating system architecture from its implementation. The review also highlights the importance of security in Big Data systems, proposing a novel architecture for detecting insider attacks through data replication. Additionally, it explores the development of BigDataBench, a benchmark suite that facilitates the comprehensive evaluation of Big Data systems and architectures. Moreover, the review delves into the design of Big Data analytics architectures, focusing on goal-oriented modeling and the resolution of obstacles to quality goal achievement. It also introduces datar, a unified framework for Big Data Management Systems, showcasing a solution that manages Big Data in a pluggable, automatic, and intelligent manner. In conclusion, the intersection of Big Data and Systems Engineering heralds a new era of system design and management. By addressing the inherent challenges and leveraging innovative solutions, this convergence holds the potential to significantly enhance the capabilities of Systems Engineering, driving forward the development of complex, data-driven systems. Keywords: Big Data, Systems Engineering, Information Security, Data Management Systems, Benchmarking Big Data Systems.
{"title":"THE ROLE OF BIG DATA IN SYSTEMS ENGINEERING: A REVIEW","authors":"Oladele Junior Adeyeye, Ibrahim Akanbi","doi":"10.51594/estj.v5i4.1029","DOIUrl":"https://doi.org/10.51594/estj.v5i4.1029","url":null,"abstract":"This research review explores the transformative intersection of Big Data and Systems Engineering (SE), a convergence that leverages the vast capabilities of Big Data analytics to enhance the design, analysis, and management of complex systems. As the digital era ushers in unprecedented volumes of data, traditional systems engineering approaches are challenged to adapt, necessitating a paradigm shift towards integrating Big Data technologies. This review draws on recent scholarly contributions to highlight the implications, challenges, and innovative solutions emerging at this intersection. The integration of Big Data into Systems Engineering introduces significant opportunities for innovation. By processing and analyzing vast datasets, systems engineers can uncover hidden patterns and insights, leading to more efficient, reliable, and adaptable systems. However, this integration is not without its challenges. Information security emerges as a paramount concern, with the risk of insider attacks necessitating the development of new architectural solutions. Furthermore, the benchmarking and evaluation of Big Data systems present unique challenges due to the diversity of data and workloads involved. To address these challenges, this review examines several key contributions to the field. It discusses a formal framework for designing information systems that handle heterogeneous data, emphasizing the role of ontological models in separating system architecture from its implementation. The review also highlights the importance of security in Big Data systems, proposing a novel architecture for detecting insider attacks through data replication. Additionally, it explores the development of BigDataBench, a benchmark suite that facilitates the comprehensive evaluation of Big Data systems and architectures. Moreover, the review delves into the design of Big Data analytics architectures, focusing on goal-oriented modeling and the resolution of obstacles to quality goal achievement. It also introduces datar, a unified framework for Big Data Management Systems, showcasing a solution that manages Big Data in a pluggable, automatic, and intelligent manner. In conclusion, the intersection of Big Data and Systems Engineering heralds a new era of system design and management. By addressing the inherent challenges and leveraging innovative solutions, this convergence holds the potential to significantly enhance the capabilities of Systems Engineering, driving forward the development of complex, data-driven systems. \u0000Keywords: Big Data, Systems Engineering, Information Security, Data Management Systems, Benchmarking Big Data Systems.","PeriodicalId":113413,"journal":{"name":"Engineering Science & Technology Journal","volume":"30 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140697036","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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