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/ICETSIS61505.2024.10459532
Muhammad Nur Iqbal Wariesky, Z. Baizal
It is common for customers to face challenges when trying to choose a vehicle that fits their modern lifestyle. Even though there are many recommender systems available to assist with making informed decisions based on unique needs, these systems often lack direct user involvement. Additionally, their recommendations are primarily based on technical specifications rather than functional requirements. To address these limitations, a recent study aimed to create an ontology-based conversational recommender system. This system incorporates user preferences and offers personalized recommendations based on functional requirements. The study evaluated the system based on accuracy and user satisfaction metrics and found that it achieved an impressive recommendation accuracy rate of 87.84%. Furthermore, the study received positive feedback from users searching for motorcycles based on various functional requirements. This feedback is a testament to the system's effectiveness in aiding customers in making informed decisions.
{"title":"Ontology-Based Conversational Recommender System for Motorcycle","authors":"Muhammad Nur Iqbal Wariesky, Z. Baizal","doi":"10.1109/ICETSIS61505.2024.10459532","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459532","url":null,"abstract":"It is common for customers to face challenges when trying to choose a vehicle that fits their modern lifestyle. Even though there are many recommender systems available to assist with making informed decisions based on unique needs, these systems often lack direct user involvement. Additionally, their recommendations are primarily based on technical specifications rather than functional requirements. To address these limitations, a recent study aimed to create an ontology-based conversational recommender system. This system incorporates user preferences and offers personalized recommendations based on functional requirements. The study evaluated the system based on accuracy and user satisfaction metrics and found that it achieved an impressive recommendation accuracy rate of 87.84%. Furthermore, the study received positive feedback from users searching for motorcycles based on various functional requirements. This feedback is a testament to the system's effectiveness in aiding customers in making informed decisions.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"382 7","pages":"1673-1678"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530440","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}
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/ICETSIS61505.2024.10459606
Vaidehi Manurkar, Sumedh Kulkarni, Suyash Rokade, Riddhi R. Mirajkar
In the dynamic context of India's pivotal cotton industry, we embark on a pioneering research endeavor that harnesses the formidable synergy of agriculture, state-of-the-art artificial intelligence, and cutting-edge computer vision technologies. Our work attempts to accomplish two goals: first, we will build a flexible and intelligent AI model that has been fine-tuned to quickly and correctly detect common cotton plant diseases from a collection of images; second, we will build an approachable and user-friendly platform that enables farmers to upload images of their sick cotton crops for quick analysis. Our research aspires to endow the agricultural community with timely, data-driven insights and customized recommendations, thereby elevating disease management and fostering sustainable practices that augment the resilience and prosperity of India's cherished cotton industry.
{"title":"Cotton Plant Disease Prediction and Remedy Recommendation System","authors":"Vaidehi Manurkar, Sumedh Kulkarni, Suyash Rokade, Riddhi R. Mirajkar","doi":"10.1109/ICETSIS61505.2024.10459606","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459606","url":null,"abstract":"In the dynamic context of India's pivotal cotton industry, we embark on a pioneering research endeavor that harnesses the formidable synergy of agriculture, state-of-the-art artificial intelligence, and cutting-edge computer vision technologies. Our work attempts to accomplish two goals: first, we will build a flexible and intelligent AI model that has been fine-tuned to quickly and correctly detect common cotton plant diseases from a collection of images; second, we will build an approachable and user-friendly platform that enables farmers to upload images of their sick cotton crops for quick analysis. Our research aspires to endow the agricultural community with timely, data-driven insights and customized recommendations, thereby elevating disease management and fostering sustainable practices that augment the resilience and prosperity of India's cherished cotton industry.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"5 4","pages":"1616-1620"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530193","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/ICETSIS61505.2024.10459572
Menatalla Haggag, Lubana Al Rayes, Z. Aghbari
The core algorithms of data mining (DM) enable the discovery of new information and insights by analyzing large amounts of data. Association rules mining (ARM), one of the several DM approaches, is extremely important in DM research. By utilizing ARM in medical diagnosis, early disease detection can be enhanced, and treatment recommendations can be improved based on data-driven insights. Breast cancer remains the leading cause of cancer-related deaths among women on a global scale. It is a huge challenge to researchers in the medical field concerning its diagnosis and prognosis. This paper aims to leverage ARM for the generation of associations that contribute to either recurrence or no-recurrence events in breast cancer. The study utilizes the Breast Cancer dataset from the UCI repository. To ensure comprehensive coverage of associations in both classes, the dataset is balanced using Synthetic Minority Over-sampling Technique (SMOTE) and Generative Adversarial Networks (GAN). Utilizing GAN to balance the dataset enhanced the performance of the association classification.
数据挖掘（DM）的核心算法能够通过分析大量数据发现新信息和新见解。关联规则挖掘（ARM）是几种数据挖掘方法之一，在数据挖掘研究中极为重要。在医疗诊断中利用关联规则挖掘，可以提高疾病的早期发现率，并根据数据驱动的洞察力改进治疗建议。乳腺癌仍然是全球妇女因癌症死亡的主要原因。对于医学领域的研究人员来说，乳腺癌的诊断和预后是一个巨大的挑战。本文旨在利用 ARM 生成有助于乳腺癌复发或不再复发的关联。该研究利用了 UCI 数据库中的乳腺癌数据集。为确保两类关联的全面覆盖，数据集使用合成少数群体过度采样技术（SMOTE）和生成对抗网络（GAN）进行平衡。利用 GAN 平衡数据集提高了关联分类的性能。
{"title":"Enhancing Association Rules using Generative Adversarial Networks for Breast Cancer Classification","authors":"Menatalla Haggag, Lubana Al Rayes, Z. Aghbari","doi":"10.1109/ICETSIS61505.2024.10459572","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459572","url":null,"abstract":"The core algorithms of data mining (DM) enable the discovery of new information and insights by analyzing large amounts of data. Association rules mining (ARM), one of the several DM approaches, is extremely important in DM research. By utilizing ARM in medical diagnosis, early disease detection can be enhanced, and treatment recommendations can be improved based on data-driven insights. Breast cancer remains the leading cause of cancer-related deaths among women on a global scale. It is a huge challenge to researchers in the medical field concerning its diagnosis and prognosis. This paper aims to leverage ARM for the generation of associations that contribute to either recurrence or no-recurrence events in breast cancer. The study utilizes the Breast Cancer dataset from the UCI repository. To ensure comprehensive coverage of associations in both classes, the dataset is balanced using Synthetic Minority Over-sampling Technique (SMOTE) and Generative Adversarial Networks (GAN). Utilizing GAN to balance the dataset enhanced the performance of the association classification.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"40 1","pages":"634-638"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530221","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}
In the contemporary digital landscape, this project presents an innovative ATM security system that seamlessly integrates face recognition authentication and OTP (One-Time Password) verification, significantly enhancing security in financial transactions. The system adopts a robust yet flexible approach, initiating with users entering their username and password. Subsequently, their face is captured and analyzed through the LBPH algorithm. Successful face recognition grants access for secure transactions. For situations necessitating an alternative access method, such as withdrawals by trusted individuals, the system smoothly transitions to OTP verification. In case face recognition fails, an OTP is generated and dispatched to the user's registered mobile number, enabling authorized parties to proceed with transactions. This dynamic approach ensures stringent control over account access while facilitating secure and convenient financial transactions. By amalgamating cutting-edge technology with adaptability and user-friendliness, this system offers a comprehensive security framework for ATM systems in the modern financial technology landscape.
{"title":"Additional Security in ATM Transactions Using Face Recognition and OTP Verification","authors":"Aditi Mohite, Sourav Joshi, Riddhi Joshi, Riddhi R. Mirajkar, Siddhi Kunjir","doi":"10.1109/ICETSIS61505.2024.10459580","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459580","url":null,"abstract":"In the contemporary digital landscape, this project presents an innovative ATM security system that seamlessly integrates face recognition authentication and OTP (One-Time Password) verification, significantly enhancing security in financial transactions. The system adopts a robust yet flexible approach, initiating with users entering their username and password. Subsequently, their face is captured and analyzed through the LBPH algorithm. Successful face recognition grants access for secure transactions. For situations necessitating an alternative access method, such as withdrawals by trusted individuals, the system smoothly transitions to OTP verification. In case face recognition fails, an OTP is generated and dispatched to the user's registered mobile number, enabling authorized parties to proceed with transactions. This dynamic approach ensures stringent control over account access while facilitating secure and convenient financial transactions. By amalgamating cutting-edge technology with adaptability and user-friendliness, this system offers a comprehensive security framework for ATM systems in the modern financial technology landscape.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"250 4","pages":"583-588"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530234","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/ICETSIS61505.2024.10459648
Mohammad Kamal Hossain, Md Arifuzzaman, M. Seliaman, Arifur Rahman, Debasish Sarker, Hussain Altammar
This paper explores into Saudi Arabia's global leadership in renewable energy, particularly its solar initiatives. The study employs a detailed analysis of input variables, including time, temperature, wind speed, humidity, and air pressure, forming the basis for a predictive model focused on Umax (voltage). Rigorous data analysis establishes the reliability of findings, paving the way for further exploration into the models' inner workings. The paper concludes by highlighting the significance of the research for stakeholders, offering nuanced insights into Umax variations and optimizing solar power generation on a global scale.
{"title":"Ensemble Learning Algorithms for Solar Power Prediction in Saudi Arabia: A Data-Driven Approach","authors":"Mohammad Kamal Hossain, Md Arifuzzaman, M. Seliaman, Arifur Rahman, Debasish Sarker, Hussain Altammar","doi":"10.1109/ICETSIS61505.2024.10459648","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459648","url":null,"abstract":"This paper explores into Saudi Arabia's global leadership in renewable energy, particularly its solar initiatives. The study employs a detailed analysis of input variables, including time, temperature, wind speed, humidity, and air pressure, forming the basis for a predictive model focused on Umax (voltage). Rigorous data analysis establishes the reliability of findings, paving the way for further exploration into the models' inner workings. The paper concludes by highlighting the significance of the research for stakeholders, offering nuanced insights into Umax variations and optimizing solar power generation on a global scale.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"46 5","pages":"1368-1372"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530199","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/ICETSIS61505.2024.10459521
Fadi Alkhatib, Ali Daris, Aiman H. H. Almasaudi, A. M. Alawag, Abdullah O. Baarimah, A. K. Alakhali
Tall buildings have emerged in popularity as a solution for accommodating swift urban population growth, economic expansion, and spatial constraints. However, as sustainability takes precedence in urban development, the performance and optimization of tall buildings have assumed critical research significance. Wind loads predominantly dictate the parameters for the design and optimization of these structures, mandating a wind-responsive approach to assess structural behaviors. This challenge is compounded by contemporary architectural trends favoring asymmetrical shapes and intricate geometries, where external form crucially influences wind-induced motion on tall buildings. This paper firstly undertakes a review study based on prior research works to investigate the main challenges and associated impediments in the pursuit of optimizing asymmetrical tall buildings for designs that are sustainable, safe, and economically viable. In response, a conceptual design workflow is developed and proposed by utilizing advanced computational technology to address the array of challenges inherent in designing and optimizing asymmetrical tall buildings. Hence, this research work lays the groundwork for further exploration and broader application to facilitate its implementation for the effective realization of asymmetrical tall buildings within industrial practices.
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