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":"247 3-4","pages":"1963-1967"},"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":"246 4","pages":"1388-1393"},"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/ICETSIS61505.2024.10459703
A. M. Alawag, W. Alaloul, Baker Nasser Saleh Al-dhawi, Abdullah O. Baarimah, Mahmood A. Bazel, Ahmed W. Mushtaha
Construction, like any other industry, is prone to conflicts. The construction industry has witnessed a rapid transformation driven by advancements in technology, with a particular focus on smart construction projects aimed at improving efficiency, transparency, and collaboration. Blockchain technology offers a decentralized method of managing the data and promotes the performance and sustainability of building projects. Nevertheless, a comprehensive analysis of the present status of blockchain research integration has not been undertaken utilizing scientometric analysis. This paper presents a comprehensive review and bibliometric analysis of blockchain technology adoption within the context of intelligent construction projects from 2018 through 2023. A total of 1079 papers were extracted from the Scopus database. The VOSviewer tool was used to visually represent the literature including various countries, scholarly publications, and keywords. Moreover, using an analysis of often-used phrases, three significant study fields associated with blockchain have been identified “Management,” “Project,” and “Building.”. This article contributes to the existing body of knowledge by synthesizing the current state of research on blockchain technology in smart construction projects, offering a holistic view of its applications, and highlighting areas that require further investigation.
{"title":"A Review and Bibliometric Analysis of Blockchain Adoption Within the Context of Smart Construction Projects","authors":"A. M. Alawag, W. Alaloul, Baker Nasser Saleh Al-dhawi, Abdullah O. Baarimah, Mahmood A. Bazel, Ahmed W. Mushtaha","doi":"10.1109/ICETSIS61505.2024.10459703","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459703","url":null,"abstract":"Construction, like any other industry, is prone to conflicts. The construction industry has witnessed a rapid transformation driven by advancements in technology, with a particular focus on smart construction projects aimed at improving efficiency, transparency, and collaboration. Blockchain technology offers a decentralized method of managing the data and promotes the performance and sustainability of building projects. Nevertheless, a comprehensive analysis of the present status of blockchain research integration has not been undertaken utilizing scientometric analysis. This paper presents a comprehensive review and bibliometric analysis of blockchain technology adoption within the context of intelligent construction projects from 2018 through 2023. A total of 1079 papers were extracted from the Scopus database. The VOSviewer tool was used to visually represent the literature including various countries, scholarly publications, and keywords. Moreover, using an analysis of often-used phrases, three significant study fields associated with blockchain have been identified “Management,” “Project,” and “Building.”. This article contributes to the existing body of knowledge by synthesizing the current state of research on blockchain technology in smart construction projects, offering a holistic view of its applications, and highlighting areas that require further investigation.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"350 3","pages":"805-811"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530486","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/ICETSIS61505.2024.10459406
Ali Ateeu, M. Alaghbari, A. Al-Refaei, Ammar Yousif Ahmed
This research investigates the use and consequences of environmentally-friendly technology in the operational activities of universities. We evaluate the incorporation of sustainable practices into the instructional structure and operational strategies of higher education institutions by conducting a thorough examination of relevant literature and conducting a comparative study. The methodological approach is based on a conceptual framework that combines the Triple Bottom Line theory with scholarly stakeholder involvement, offering a comprehensive view of sustainability from several angles. We use a variety of multidisciplinary research to assess the effectiveness of green technology in promoting an environmentally conscious campus culture and decreasing the ecological impact. Initial results indicate that while universities are making progress in adopting green technology, there is still much potential for improving policies and involving the community in order to achieve complete sustainability. This study enhances the discussion on green technology in academia and provides a solid groundwork for future research avenues.
{"title":"Sustainable Solutions: The Impact of Green Technologies in University Operations","authors":"Ali Ateeu, M. Alaghbari, A. Al-Refaei, Ammar Yousif Ahmed","doi":"10.1109/ICETSIS61505.2024.10459406","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459406","url":null,"abstract":"This research investigates the use and consequences of environmentally-friendly technology in the operational activities of universities. We evaluate the incorporation of sustainable practices into the instructional structure and operational strategies of higher education institutions by conducting a thorough examination of relevant literature and conducting a comparative study. The methodological approach is based on a conceptual framework that combines the Triple Bottom Line theory with scholarly stakeholder involvement, offering a comprehensive view of sustainability from several angles. We use a variety of multidisciplinary research to assess the effectiveness of green technology in promoting an environmentally conscious campus culture and decreasing the ecological impact. Initial results indicate that while universities are making progress in adopting green technology, there is still much potential for improving policies and involving the community in order to achieve complete sustainability. This study enhances the discussion on green technology in academia and provides a solid groundwork for future research avenues.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"349 12","pages":"225-229"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530487","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/ICETSIS61505.2024.10459604
Saira Yaqub, Saikat Gochhait, Hafiz Abdul Haseeb Khalid, Syeda Noreen Bukhari, Ayesha Yaqub, Muhammad Abubakr
WhatsApp has become a widely used medium to communicate in the modern era of technology, fostering diverse conversations and expressions among millions of users worldwide. This research introduces a robust analytical tool, the “WhatsApp Chat Ana-lyzer,” crafted to dissect and visualize the multifaceted landscape of group chats on WhatsApp. Imbued with Python's prowess and fortified by Streamlit, matplotlib, and Seaborn, the tool transcends conventional analyses by providing nuanced insights into user behavior, message statistics, and emerging content trends. In this research, we embark on an exploratory journey to decipher the complex dynamics embedded within WhatsApp group chats. By amalgamating sophisticated data preprocessing techniques, advanced statistical analyses, and captivating visualizations, the “WhatsApp Chat Analyzer” stands as a testament to our commitment to unraveling the facts of modern digital communication.
{"title":"WhatsApp Chat Analysis: Unveiling Insights through Data Processing and Visualization Techniques","authors":"Saira Yaqub, Saikat Gochhait, Hafiz Abdul Haseeb Khalid, Syeda Noreen Bukhari, Ayesha Yaqub, Muhammad Abubakr","doi":"10.1109/ICETSIS61505.2024.10459604","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459604","url":null,"abstract":"WhatsApp has become a widely used medium to communicate in the modern era of technology, fostering diverse conversations and expressions among millions of users worldwide. This research introduces a robust analytical tool, the “WhatsApp Chat Ana-lyzer,” crafted to dissect and visualize the multifaceted landscape of group chats on WhatsApp. Imbued with Python's prowess and fortified by Streamlit, matplotlib, and Seaborn, the tool transcends conventional analyses by providing nuanced insights into user behavior, message statistics, and emerging content trends. In this research, we embark on an exploratory journey to decipher the complex dynamics embedded within WhatsApp group chats. By amalgamating sophisticated data preprocessing techniques, advanced statistical analyses, and captivating visualizations, the “WhatsApp Chat Analyzer” stands as a testament to our commitment to unraveling the facts of modern digital communication.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"334 2","pages":"862-865"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530497","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/ICETSIS61505.2024.10459403
Mohamed Elmadani, Salem Sati
Network virtualization offers advanced technology solutions for data centers and clouds, specifically through the use of Virtual eXtensible Local Area Network (VxLAN) to interconnect multiple data centers. Nonetheless, it is crucial to take into account the Maximum Transmission Unit (MTU) when implementing overlay VxLAN technology. This technology introduces additional overhead to network packets, and exceeding the MTU can result in performance degradation and increased processing overhead due to packet fragmentation. The Virtual Tunneling End Point (VTEP) is employed in VxLAN overlay tunneling but does not forward packets that exceed the path MTU, leading to packet loss and significant delays caused by network misconfiguration. This paper thoroughly examines the issues related to MTU size and emphasizes the overhead introduced by overlay technologies like VxLAN. Additionally, it highlights the necessity of implementing MTU discovery features. Simulation results demonstrate that enabling MTU discovery features allows hosts to avoid packet loss while ensuring network stability and adaptability. Conversely, manually adjusting the MTU size may be restricted or blocked by device vendors, especially when data centers are interconnected via third-party networks. By comparing the manual configuration approach with MTU discovery methods, data center administrators can make informed decisions. The simulation results clearly indicate that MTU discovery surpasses manual configuration in terms of throughput, reduces packet loss, and minimizes delays.
网络虚拟化为数据中心和云提供了先进的技术解决方案，特别是通过使用虚拟可扩展局域网（VxLAN）实现多个数据中心的互联。不过，在实施叠加 VxLAN 技术时，必须考虑到最大传输单元（MTU）。这种技术会给网络数据包带来额外的开销，超过 MTU 会导致性能下降，并因数据包分片而增加处理开销。在 VxLAN 重叠隧道中采用了虚拟隧道端点（VTEP），但它不会转发超过路径 MTU 的数据包，从而导致数据包丢失和因网络配置错误而造成的严重延迟。本文深入研究了与 MTU 大小相关的问题，并强调了 VxLAN 等覆盖技术带来的开销。此外，它还强调了实施 MTU 发现功能的必要性。仿真结果表明，启用 MTU 发现功能可使主机避免数据包丢失，同时确保网络的稳定性和适应性。相反，手动调整 MTU 大小可能会受到设备供应商的限制或阻止，尤其是当数据中心通过第三方网络互连时。通过比较手动配置方法和 MTU 发现方法，数据中心管理员可以做出明智的决策。仿真结果清楚地表明，MTU 发现法在吞吐量、减少数据包丢失和最小化延迟方面都优于手动配置法。
{"title":"MTU Analyzing for Data Centers Interconnected Using VxLAN","authors":"Mohamed Elmadani, Salem Sati","doi":"10.1109/ICETSIS61505.2024.10459403","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459403","url":null,"abstract":"Network virtualization offers advanced technology solutions for data centers and clouds, specifically through the use of Virtual eXtensible Local Area Network (VxLAN) to interconnect multiple data centers. Nonetheless, it is crucial to take into account the Maximum Transmission Unit (MTU) when implementing overlay VxLAN technology. This technology introduces additional overhead to network packets, and exceeding the MTU can result in performance degradation and increased processing overhead due to packet fragmentation. The Virtual Tunneling End Point (VTEP) is employed in VxLAN overlay tunneling but does not forward packets that exceed the path MTU, leading to packet loss and significant delays caused by network misconfiguration. This paper thoroughly examines the issues related to MTU size and emphasizes the overhead introduced by overlay technologies like VxLAN. Additionally, it highlights the necessity of implementing MTU discovery features. Simulation results demonstrate that enabling MTU discovery features allows hosts to avoid packet loss while ensuring network stability and adaptability. Conversely, manually adjusting the MTU size may be restricted or blocked by device vendors, especially when data centers are interconnected via third-party networks. By comparing the manual configuration approach with MTU discovery methods, data center administrators can make informed decisions. The simulation results clearly indicate that MTU discovery surpasses manual configuration in terms of throughput, reduces packet loss, and minimizes delays.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"405 17","pages":"1825-1829"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530021","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/ICETSIS61505.2024.10459396
Rafi Indra Permana, Nur Aini Rakhmawati
This research examines the privacy concerns that have arisen during the Covid-19 pandemic, as a result of restrictions on outside activities, leading to an increased number of online seminars conducted via Zoom, commonly referred to as webinars. The objective of this study is to evaluate the extent to which webinars in Indonesia impact personal data privacy and to assess the level of awareness among webinar organizers regarding privacy concerns. The research approach employed is qualitative, involving literature reviews, identification of privacy issues in organizing Zoom-based webinars, design of a webinar survey, investigation of webinars, and integration of findings into a comprehensive project report. The outcomes of this investigation will determine the extent to which webinars implement privacy policies, while the survey results will provide insights into the level of understanding of webinar organizers concerning privacy issues.
{"title":"Privacy Issues in Zoom-Based Webinars","authors":"Rafi Indra Permana, Nur Aini Rakhmawati","doi":"10.1109/ICETSIS61505.2024.10459396","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459396","url":null,"abstract":"This research examines the privacy concerns that have arisen during the Covid-19 pandemic, as a result of restrictions on outside activities, leading to an increased number of online seminars conducted via Zoom, commonly referred to as webinars. The objective of this study is to evaluate the extent to which webinars in Indonesia impact personal data privacy and to assess the level of awareness among webinar organizers regarding privacy concerns. The research approach employed is qualitative, involving literature reviews, identification of privacy issues in organizing Zoom-based webinars, design of a webinar survey, investigation of webinars, and integration of findings into a comprehensive project report. The outcomes of this investigation will determine the extent to which webinars implement privacy policies, while the survey results will provide insights into the level of understanding of webinar organizers concerning privacy issues.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"410 28","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530408","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":"256 3","pages":"1507-1511"},"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/ICETSIS61505.2024.10459460
Md Arifuzzaman, Abdulrahman Fahad Alfuhaid, Abm Saiful Islam, M. T. Bhuiyan, Mokammel Hossain Tito, Aniq Gul
In the realm of construction, achieving high-performance concrete (HPC) involves incorporating supplementary materials like fly ash and blast furnace slag, along with superplasticizer. The conventional water-to-cement ratio (w/c) concept, established by Abrams in 1918, asserts an inverse relationship between w/c ratio and concrete strength in HPC. However, a critical analysis of experimental data challenges this perspective, revealing that the paste quantity also significantly influences comparable cement strength, introducing complexity to our understanding of HPC and concrete strength dynamics. Furthermore, an exploration of concrete mix models and machine learning algorithms sheds light on variables impacting compressive strength. Surprisingly, blast furnace slag emerges as a predominant contributor, highlighting the significance of water management. Key factors like cement and aggregates play pivotal roles in shaping compressive strength. Notably, the Vote algorithm demonstrates exceptional predictive accuracy with a high correlation coefficient (0.919) and low mean absolute error (4.9166), while RandomForest and AdditiveRegression also exhibit commendable performance, striking a balance between accuracy and efficiency. These insights guide decisions in concrete mix design and machine learning model selection, offering valuable guidance for optimal outcomes across diverse applications in construction.
{"title":"From Mix Design to Strength Prediction: Ensemble Learning Application on the Performance of High-Performance Concrete","authors":"Md Arifuzzaman, Abdulrahman Fahad Alfuhaid, Abm Saiful Islam, M. T. Bhuiyan, Mokammel Hossain Tito, Aniq Gul","doi":"10.1109/ICETSIS61505.2024.10459460","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459460","url":null,"abstract":"In the realm of construction, achieving high-performance concrete (HPC) involves incorporating supplementary materials like fly ash and blast furnace slag, along with superplasticizer. The conventional water-to-cement ratio (w/c) concept, established by Abrams in 1918, asserts an inverse relationship between w/c ratio and concrete strength in HPC. However, a critical analysis of experimental data challenges this perspective, revealing that the paste quantity also significantly influences comparable cement strength, introducing complexity to our understanding of HPC and concrete strength dynamics. Furthermore, an exploration of concrete mix models and machine learning algorithms sheds light on variables impacting compressive strength. Surprisingly, blast furnace slag emerges as a predominant contributor, highlighting the significance of water management. Key factors like cement and aggregates play pivotal roles in shaping compressive strength. Notably, the Vote algorithm demonstrates exceptional predictive accuracy with a high correlation coefficient (0.919) and low mean absolute error (4.9166), while RandomForest and AdditiveRegression also exhibit commendable performance, striking a balance between accuracy and efficiency. These insights guide decisions in concrete mix design and machine learning model selection, offering valuable guidance for optimal outcomes across diverse applications in construction.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"192 1","pages":"1584-1588"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530245","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/ICETSIS61505.2024.10459432
Y. Syaifudin, Dionisius Damarta Yapenrui, Noprianto, Nobuo Funabiki, I. Siradjuddin, Hidayati Nur Chasanah
Smartphones have drastically transformed communication and information access, becoming integral to various aspects of daily life. The surge in mobile application adoption for diverse needs has further solidified their importance. The study is motivated by the rising popularity of Flutter in mobile application development, particularly for interactive applications, due to its cross-platform capabilities and ability to create visually appealing interfaces with customizable widgets. However, there is a notable gap in mobile programming education, with a need for practical, hands-on learning. To address this, a learning topic in the Flutter Programming Learning Assistance System (FPLAS) is proposed which aims to facilitate self-learning in Android programming using Flutter. It incorporates test-driven development and automated testing, making it easier for students to learn through a project-based approach. The system's effectiveness was validated through an evaluation involving 40 students, resulting in a 100% success rate and positive feedback, highlighting its utility in enhancing UI design and programming skills, though some constructive suggestions were noted for improvement.
{"title":"Implementation of Self-Learning Topic for Developing Interactive Mobile Application in Flutter Programming Learning Assistance System","authors":"Y. Syaifudin, Dionisius Damarta Yapenrui, Noprianto, Nobuo Funabiki, I. Siradjuddin, Hidayati Nur Chasanah","doi":"10.1109/ICETSIS61505.2024.10459432","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459432","url":null,"abstract":"Smartphones have drastically transformed communication and information access, becoming integral to various aspects of daily life. The surge in mobile application adoption for diverse needs has further solidified their importance. The study is motivated by the rising popularity of Flutter in mobile application development, particularly for interactive applications, due to its cross-platform capabilities and ability to create visually appealing interfaces with customizable widgets. However, there is a notable gap in mobile programming education, with a need for practical, hands-on learning. To address this, a learning topic in the Flutter Programming Learning Assistance System (FPLAS) is proposed which aims to facilitate self-learning in Android programming using Flutter. It incorporates test-driven development and automated testing, making it easier for students to learn through a project-based approach. The system's effectiveness was validated through an evaluation involving 40 students, resulting in a 100% success rate and positive feedback, highlighting its utility in enhancing UI design and programming skills, though some constructive suggestions were noted for improvement.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"90 7-8","pages":"1103-1107"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530391","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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