Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459710
Mohana Hari Mohan, Muhammad Ehsan Rana
In an era where telehealthcare is becoming increasingly pivotal, this paper presents an extensive exploration of cloud computing as the key to unlocking its full potential. The research pivots around the unprecedented challenges and opportunities brought forth by the COVID-19 pandemic, showcasing cloud computing as a transformative force in telehealthcare. It meticulously dissects the critical issues of scalability, data security, and real-time analytics, offering robust solutions through cloud technology. This study extends beyond theoretical analysis, providing a detailed comparative assessment of leading cloud service providers such as Amazon Web Services, Microsoft Azure, and Google Cloud, and their instrumental roles in redefining healthcare delivery. Through a series of compelling case studies, the paper vividly illustrates the real-world impact of cloud computing in telehealthcare, underpinned by both quantitative and qualitative evaluations. Furthermore, it navigates the complex landscape of technical, economic, and user-centric considerations, culminating in strategic policy recommendations. This paper not only charts a new course in telehealthcare but also serves as a beacon for future research and implementation in the field, positioning cloud computing as the cornerstone of modern medical innovation.
{"title":"Revolutionizing Telehealthcare: Cloud Computing as the Catalyst for a New Medical Frontier","authors":"Mohana Hari Mohan, Muhammad Ehsan Rana","doi":"10.1109/ICETSIS61505.2024.10459710","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459710","url":null,"abstract":"In an era where telehealthcare is becoming increasingly pivotal, this paper presents an extensive exploration of cloud computing as the key to unlocking its full potential. The research pivots around the unprecedented challenges and opportunities brought forth by the COVID-19 pandemic, showcasing cloud computing as a transformative force in telehealthcare. It meticulously dissects the critical issues of scalability, data security, and real-time analytics, offering robust solutions through cloud technology. This study extends beyond theoretical analysis, providing a detailed comparative assessment of leading cloud service providers such as Amazon Web Services, Microsoft Azure, and Google Cloud, and their instrumental roles in redefining healthcare delivery. Through a series of compelling case studies, the paper vividly illustrates the real-world impact of cloud computing in telehealthcare, underpinned by both quantitative and qualitative evaluations. Furthermore, it navigates the complex landscape of technical, economic, and user-centric considerations, culminating in strategic policy recommendations. This paper not only charts a new course in telehealthcare but also serves as a beacon for future research and implementation in the field, positioning cloud computing as the cornerstone of modern medical innovation.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530386","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 : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459615
A. Muttar, Ayda Isa Al Saadoon, M. Abdeldayem, S. Aldulaimi
This study aimed to examine the impact of digital skills of human resources, which was measured through (digital literacy, communication and cooperation, solving technical problems) on the job performance which measured in this study through (quality, efficiency, achievement) of the employees in the public schools in the Kingdom of Bahrain. The study further used the descriptive research method by using within the questionnaire instrument to collect the data which was formulated based on previous studies with a five-point Likert scale. The study analyzed the data and tested the research hypotheses by using the Statistical Packages for Social Sciences SPSS through some tests include one-way analysis of variance, regression analysis, reliability, and differences between groups. The results found a statistically significant impact of the digital skills of human resources in its dimensions (digital literacy, communication and cooperation, and solving technical problems) on the job performance in the Bahraini public schools. Also, the results revealed differences among the sample's perceptions about the digital skills for human resources and job performance due to the gender variable in favor of females, and a difference in the sample's perceptions due to the age, educational qualification and job title variable, while the years of experience variable came with no differences between the groups.
{"title":"Unleashing the Power of Digital Skills in Human Resources: Exploring the Relationship between Digital Transformation and Job Performance in the Government of Bahrain","authors":"A. Muttar, Ayda Isa Al Saadoon, M. Abdeldayem, S. Aldulaimi","doi":"10.1109/ICETSIS61505.2024.10459615","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459615","url":null,"abstract":"This study aimed to examine the impact of digital skills of human resources, which was measured through (digital literacy, communication and cooperation, solving technical problems) on the job performance which measured in this study through (quality, efficiency, achievement) of the employees in the public schools in the Kingdom of Bahrain. The study further used the descriptive research method by using within the questionnaire instrument to collect the data which was formulated based on previous studies with a five-point Likert scale. The study analyzed the data and tested the research hypotheses by using the Statistical Packages for Social Sciences SPSS through some tests include one-way analysis of variance, regression analysis, reliability, and differences between groups. The results found a statistically significant impact of the digital skills of human resources in its dimensions (digital literacy, communication and cooperation, and solving technical problems) on the job performance in the Bahraini public schools. Also, the results revealed differences among the sample's perceptions about the digital skills for human resources and job performance due to the gender variable in favor of females, and a difference in the sample's perceptions due to the age, educational qualification and job title variable, while the years of experience variable came with no differences between the groups.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530404","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 : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459590
Priya Chanda, Sukanta Ghosh
Human capital is a paramount asset within any organization, evolving into distinct facets that fortify its competitive edge amid a perpetually shifting market landscape. Securing high-quality candidates necessitates minimizing human intervention and validating candidate credentials during recruitment. Moreover, gauging employee performance and anticipating attrition prove pivotal in effective human resource management. This study endeavors to introduce an innovative human resource management system employing machine learning and blockchain. The objective is to create an intelligent system that reduces human subjectivity and time in candidate selection while forecasting employee performance and attrition. Leveraging unsupervised learning algorithms and natural language processing, the system conducts skill assessment and resumes categorization after the extraction of raw data via object character recognition. Candidate validation relies on comparing blockchain-stored records. Supervised machine learning classification predicts employee performance and attrition with high precision, generating standardized scores based on multiple attributes aligned with specific e-competence frameworks, aiming to foster workplace productivity while minimizing financial losses.
{"title":"Optimizing Workforce Efficiency Using an Artificial Intelligence Approach: A Next-Gen HR Management System","authors":"Priya Chanda, Sukanta Ghosh","doi":"10.1109/ICETSIS61505.2024.10459590","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459590","url":null,"abstract":"Human capital is a paramount asset within any organization, evolving into distinct facets that fortify its competitive edge amid a perpetually shifting market landscape. Securing high-quality candidates necessitates minimizing human intervention and validating candidate credentials during recruitment. Moreover, gauging employee performance and anticipating attrition prove pivotal in effective human resource management. This study endeavors to introduce an innovative human resource management system employing machine learning and blockchain. The objective is to create an intelligent system that reduces human subjectivity and time in candidate selection while forecasting employee performance and attrition. Leveraging unsupervised learning algorithms and natural language processing, the system conducts skill assessment and resumes categorization after the extraction of raw data via object character recognition. Candidate validation relies on comparing blockchain-stored records. Supervised machine learning classification predicts employee performance and attrition with high precision, generating standardized scores based on multiple attributes aligned with specific e-competence frameworks, aiming to foster workplace productivity while minimizing financial losses.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530410","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 : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459709
Raya Fadel, S. Abu-Eisheh
This research explores the application of the Cross-Impact Balances (CIB) method in identifying the factors that need to be included in the strategic planning process for the adoption of smart mobility solutions in new cities within developing countries. Smart mobility systems use emerging technologies to arrive at solutions to many of the mobility related problems that affect the urban environment by creating connected and sustainable transportation systems that can move people more efficiently and safely. The CIB method, known for its ability to assess interdependencies and uncertainties in complex systems, is employed as a decision support tool. The research investigates the descriptors influencing smart mobility success in developing cities, and found that relevant aspects such as infrastructure readiness, technological disparities, socio-economic dynamics, and regulatory environments. Factors like citizen engagement, strategic region, and sustainable mobility urban plans are high-priority factors, emphasizing community involvement and thoughtful planning. Medium-priority factors highlight the need for comprehensive infrastructure and strategic collaboration. Low-priority factors, that include employed population and political situation, are found to have a comparatively lesser impact. Based on the outcome of the CIB method, the paper recommends using the resulting high- and medium-priority factors for the preparation of the strategic planning framework (the goals, objectives, and broad strategies) to achieve the vision of establishing new cities that could be characterized to have smart mobility systems.
{"title":"Identification of Strategic Planning Factors to Achieve Smart Mobility for New Cities in Developing Countries Using CIB Method","authors":"Raya Fadel, S. Abu-Eisheh","doi":"10.1109/ICETSIS61505.2024.10459709","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459709","url":null,"abstract":"This research explores the application of the Cross-Impact Balances (CIB) method in identifying the factors that need to be included in the strategic planning process for the adoption of smart mobility solutions in new cities within developing countries. Smart mobility systems use emerging technologies to arrive at solutions to many of the mobility related problems that affect the urban environment by creating connected and sustainable transportation systems that can move people more efficiently and safely. The CIB method, known for its ability to assess interdependencies and uncertainties in complex systems, is employed as a decision support tool. The research investigates the descriptors influencing smart mobility success in developing cities, and found that relevant aspects such as infrastructure readiness, technological disparities, socio-economic dynamics, and regulatory environments. Factors like citizen engagement, strategic region, and sustainable mobility urban plans are high-priority factors, emphasizing community involvement and thoughtful planning. Medium-priority factors highlight the need for comprehensive infrastructure and strategic collaboration. Low-priority factors, that include employed population and political situation, are found to have a comparatively lesser impact. Based on the outcome of the CIB method, the paper recommends using the resulting high- and medium-priority factors for the preparation of the strategic planning framework (the goals, objectives, and broad strategies) to achieve the vision of establishing new cities that could be characterized to have smart mobility systems.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530235","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 : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459651
Indira Salsabila Ardan, R. Indraswari
Brain tumor is an abnormal proliferation of brain cells, which may be benign or malignant in nature. Brain cancer, which is frequently diagnosed in individuals of all ages, is a malignant form of a brain tumor and one of the most severe forms of cancer. Each year, an estimated 300 cases of brain tumors, including those in children, are diagnosed in Indonesia. To detect brain tumors, imaging methods such as Magnetic Resonance Imaging (MRI) are utilized. However, radiologists' manual examination of MRI scans might lead to conclusions that differ from one doctor to the next (interobserver error). Research on brain tumor type classification on MRI images is also limited. To identify various types of brain tumors in MRI images, we will therefore construct a system utilizing Convolutional Neural Networks (CNN) and transfer-learning methods. In this study, the Flask framework was successfully used to develop a web-based application to identify distinct form of brain tumors in MRI scans. The model makes use of CNN architecture, a ResNet50V2 base model trained on the ImageNet dataset, a head model with 512 nodes and one entirely connected layer, and an output layer that forecasts the input into four classes of brain MRI images, including “Normal”,”Glioma”, “Meningioma”, and”Pituitary”. Appropriate parameter settings were used to achieve the highest accuracy. In this study, Adam optimization algorithm was used with 60 epochs and a batch size of 32. Additionally, a ten-fold cross-validation technique was implemented. 95% accuracy rate was achieved by implementing the proposed architecture.
{"title":"Design of Brain Tumor Detection System on MRI Image Using CNN","authors":"Indira Salsabila Ardan, R. Indraswari","doi":"10.1109/ICETSIS61505.2024.10459651","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459651","url":null,"abstract":"Brain tumor is an abnormal proliferation of brain cells, which may be benign or malignant in nature. Brain cancer, which is frequently diagnosed in individuals of all ages, is a malignant form of a brain tumor and one of the most severe forms of cancer. Each year, an estimated 300 cases of brain tumors, including those in children, are diagnosed in Indonesia. To detect brain tumors, imaging methods such as Magnetic Resonance Imaging (MRI) are utilized. However, radiologists' manual examination of MRI scans might lead to conclusions that differ from one doctor to the next (interobserver error). Research on brain tumor type classification on MRI images is also limited. To identify various types of brain tumors in MRI images, we will therefore construct a system utilizing Convolutional Neural Networks (CNN) and transfer-learning methods. In this study, the Flask framework was successfully used to develop a web-based application to identify distinct form of brain tumors in MRI scans. The model makes use of CNN architecture, a ResNet50V2 base model trained on the ImageNet dataset, a head model with 512 nodes and one entirely connected layer, and an output layer that forecasts the input into four classes of brain MRI images, including “Normal”,”Glioma”, “Meningioma”, and”Pituitary”. Appropriate parameter settings were used to achieve the highest accuracy. In this study, Adam optimization algorithm was used with 60 epochs and a batch size of 32. Additionally, a ten-fold cross-validation technique was implemented. 95% accuracy rate was achieved by implementing the proposed architecture.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530236","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 : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459503
D. Wiryawan, Wisnu Ramadhan, Faldo Krisnata, Fakhri Dhiya' Ulhaq
Throughout technological developments throughout the world, including developments in 5G technology, Artificial Intelligence, Machine Learning, etc., data has become crucial and widely needed. However, the rapid development of technology worldwide cannot be separated from risks, especially those related to data breaches. As a place for human development, educational institutions need to maintain high data security to ensure the security of crucial data for their students. This urgency can be seen in the high percentage of attacks in the education sector. The method used in this research uses a qualitative approach using the systematic literature review. This research proposes a new framework related to data security to enhance the data security of higher education, an explanation of the importance of student element factors, and the process of applying data security in educational institutions.
{"title":"Data Security Framework with Cognitive Theory on Higher Education","authors":"D. Wiryawan, Wisnu Ramadhan, Faldo Krisnata, Fakhri Dhiya' Ulhaq","doi":"10.1109/ICETSIS61505.2024.10459503","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459503","url":null,"abstract":"Throughout technological developments throughout the world, including developments in 5G technology, Artificial Intelligence, Machine Learning, etc., data has become crucial and widely needed. However, the rapid development of technology worldwide cannot be separated from risks, especially those related to data breaches. As a place for human development, educational institutions need to maintain high data security to ensure the security of crucial data for their students. This urgency can be seen in the high percentage of attacks in the education sector. The method used in this research uses a qualitative approach using the systematic literature review. This research proposes a new framework related to data security to enhance the data security of higher education, an explanation of the importance of student element factors, and the process of applying data security in educational institutions.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530482","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 : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459576
Muhammad Ehsan Rana, Kamalanathan Shanmugam, Kar Yee Chong
In the contemporary global economy, technology serves as the driving force behind industries spanning diverse sectors, marked by transformative industrial revolutions that significantly impact businesses and communities. Despite the commerce industry's substantial digital evolution, it faces persistent challenges on online platforms, including issues like shopping cart abandonment, elevated product return rates, and a lingering lack of customer confidence in eCommerce establishments. This paper delves into the potential of Augmented Reality (AR) and Virtual Reality (VR) to address these challenges, offering a novel perspective on merchandise representation and the overall retail experience. By integrating AR and VR technologies into Malaysian eCommerce companies, this research proposes a solution aimed at fostering positive consumer engagement and enhancing the psychological aspects of online retailing.
在当代全球经济中，技术是各行各业的驱动力，以变革性的产业革命为标志，对企业和社区产生了重大影响。尽管商务行业在数字化方面取得了长足的发展，但它在在线平台上仍面临着持续的挑战，包括购物车放弃率、产品退货率升高以及客户对电子商务企业始终缺乏信心等问题。本文深入探讨了增强现实（AR）和虚拟现实（VR）在应对这些挑战方面的潜力，为商品展示和整体零售体验提供了一个新的视角。通过将 AR 和 VR 技术整合到马来西亚的电子商务公司中，本研究提出了一种解决方案，旨在促进消费者的积极参与，并增强在线零售的心理层面。
{"title":"An Evaluation of Leveraging AR and VR for Enhanced Customer Engagement and Operational Efficiency in e-Commerce","authors":"Muhammad Ehsan Rana, Kamalanathan Shanmugam, Kar Yee Chong","doi":"10.1109/ICETSIS61505.2024.10459576","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459576","url":null,"abstract":"In the contemporary global economy, technology serves as the driving force behind industries spanning diverse sectors, marked by transformative industrial revolutions that significantly impact businesses and communities. Despite the commerce industry's substantial digital evolution, it faces persistent challenges on online platforms, including issues like shopping cart abandonment, elevated product return rates, and a lingering lack of customer confidence in eCommerce establishments. This paper delves into the potential of Augmented Reality (AR) and Virtual Reality (VR) to address these challenges, offering a novel perspective on merchandise representation and the overall retail experience. By integrating AR and VR technologies into Malaysian eCommerce companies, this research proposes a solution aimed at fostering positive consumer engagement and enhancing the psychological aspects of online retailing.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530200","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 : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459405
Nadia Gouda, Hamed H. Aly
When employing renewable energy within a smart micro grid (SMG), the management of distributed energy resources (DER) plays a crucial role in optimizing practical objectives of SMG. This study utilizes the Shuffled frog leaping algorithm (SFLA) to manage DER and implement demand response programs (DSP), aiming to optimize economic, technical and environmental problems of SMG. The modeling of renewable energy resources (RES) is a challenge due to its uncertainty, therefore, cumulative distribution function (CDF) is used for predicting the energy sources before its integration with SMG. The DER included in this study consists of the wind and solar energy, battery, micro turbine and the utility. This model is implemented in three different scenarios: a) basic grid operation, b) operation with maximum usage of renewable energy resources, c) operation with maximum usage of RES and DRP. The results obtained show the superiority of proposed SFLA algorithm in terms of avoiding pre-mature convergence which is a common challenge in optimization, and achieving global optimum for the proposed objectives. For validation, this model is implemented in MAT LAB considering different constraints.
在智能微电网（SMG）中采用可再生能源时，分布式能源资源（DER）的管理对优化 SMG 的实际目标起着至关重要的作用。本研究利用洗牌蛙跃算法（SFLA）管理 DER 并实施需求响应计划（DSP），旨在优化 SMG 的经济、技术和环境问题。可再生能源（RES）的建模因其不确定性而面临挑战，因此，在将其与 SMG 集成之前，使用累积分布函数（CDF）对能源进行预测。本研究中的 DER 包括风能、太阳能、电池、微型涡轮机和公用事业。该模型在三种不同情况下实施：a) 基本电网运行；b) 最大限度利用可再生能源的运行；c) 最大限度利用可再生能源和 DRP 的运行。结果表明，所提出的 SFLA 算法在避免过早收敛（这是优化中的常见挑战）和实现所提目标的全局最优方面具有优势。为进行验证，考虑到不同的约束条件，在 MAT LAB 中实现了该模型。
{"title":"Distributed Energy Sources Management using Shuffled Frog-Leaping Algorithm for Optimizing the Environmental and Economic Indices of Smart Microgrid","authors":"Nadia Gouda, Hamed H. Aly","doi":"10.1109/ICETSIS61505.2024.10459405","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459405","url":null,"abstract":"When employing renewable energy within a smart micro grid (SMG), the management of distributed energy resources (DER) plays a crucial role in optimizing practical objectives of SMG. This study utilizes the Shuffled frog leaping algorithm (SFLA) to manage DER and implement demand response programs (DSP), aiming to optimize economic, technical and environmental problems of SMG. The modeling of renewable energy resources (RES) is a challenge due to its uncertainty, therefore, cumulative distribution function (CDF) is used for predicting the energy sources before its integration with SMG. The DER included in this study consists of the wind and solar energy, battery, micro turbine and the utility. This model is implemented in three different scenarios: a) basic grid operation, b) operation with maximum usage of renewable energy resources, c) operation with maximum usage of RES and DRP. The results obtained show the superiority of proposed SFLA algorithm in terms of avoiding pre-mature convergence which is a common challenge in optimization, and achieving global optimum for the proposed objectives. For validation, this model is implemented in MAT LAB considering different constraints.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530227","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 : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459515
Essohanam Djeki, Jules R. Dégila, M. Alhassan
The rapid growth of e-learning environments has brought the urgent need to address security and privacy concerns in digital education. Existing research does not focus on the security best practices to be adopted by learners to support a secure e-learning environment. This research identifies various security threats and risks in the e-learning environment. Additionally, the study discusses the adoption of data protection laws by different countries and international organizations and emphasizes the need for compliance by e-learning platform providers. It highlights the responsibility of learning platform providers in ensuring the security of courses and user data. It delves into the importance of implementing measures such as access control, encryption, and regular updates to protect sensitive information and maintain a secure learning environment. By implementing the best practices outlined in this study, stakeholders (providers, learners, teachers) can create a safe online learning environment that protects personal data and respects privacy. The paper calls for collaborative efforts among learning platform providers, learners, and teachers to prioritize data protection and adhere to privacy regulations, ultimately enabling a safe and conducive digital education experience.
{"title":"Best Practices for Ensuring Security and Privacy in E-Learning Environments","authors":"Essohanam Djeki, Jules R. Dégila, M. Alhassan","doi":"10.1109/ICETSIS61505.2024.10459515","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459515","url":null,"abstract":"The rapid growth of e-learning environments has brought the urgent need to address security and privacy concerns in digital education. Existing research does not focus on the security best practices to be adopted by learners to support a secure e-learning environment. This research identifies various security threats and risks in the e-learning environment. Additionally, the study discusses the adoption of data protection laws by different countries and international organizations and emphasizes the need for compliance by e-learning platform providers. It highlights the responsibility of learning platform providers in ensuring the security of courses and user data. It delves into the importance of implementing measures such as access control, encryption, and regular updates to protect sensitive information and maintain a secure learning environment. By implementing the best practices outlined in this study, stakeholders (providers, learners, teachers) can create a safe online learning environment that protects personal data and respects privacy. The paper calls for collaborative efforts among learning platform providers, learners, and teachers to prioritize data protection and adhere to privacy regulations, ultimately enabling a safe and conducive digital education experience.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530231","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 : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459461
Himanshu Chaudhari, Aditi Gandhi, Varun Gabhane, Hanmant Magar
Managing a portfolio is important for getting the most profit and reducing risks in today's complicated financial markets. This paper talks about a simple platform made to help all kinds of investors keep an eye on their different investments easily. These investments include stocks, real estate, gold, fixed deposits, and more. The goal of the study is to see how well the investments are doing, look at the risks and rewards, check out ways to manage risks, explore different investment choices, and give practical advice to make more profit. The paper is useful for people who invest in many things because it connects investors with their investments in different areas. The new platform suggests better ways to invest so users can reach their money goals. In simple words, this paper introduces a place where regular people can watch all their investments and get advice for future ones, based on what they've done before. The platform also looks at how much risk a person can handle, considering things like their age and income.
{"title":"Multi-Asset Portfolio Management System: Integrating Diverse Investments for Optimal Returns and Risk Mitigation","authors":"Himanshu Chaudhari, Aditi Gandhi, Varun Gabhane, Hanmant Magar","doi":"10.1109/ICETSIS61505.2024.10459461","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459461","url":null,"abstract":"Managing a portfolio is important for getting the most profit and reducing risks in today's complicated financial markets. This paper talks about a simple platform made to help all kinds of investors keep an eye on their different investments easily. These investments include stocks, real estate, gold, fixed deposits, and more. The goal of the study is to see how well the investments are doing, look at the risks and rewards, check out ways to manage risks, explore different investment choices, and give practical advice to make more profit. The paper is useful for people who invest in many things because it connects investors with their investments in different areas. The new platform suggests better ways to invest so users can reach their money goals. In simple words, this paper introduces a place where regular people can watch all their investments and get advice for future ones, based on what they've done before. The platform also looks at how much risk a person can handle, considering things like their age and income.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530080","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：