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":"40 1","pages":"1164-1167"},"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}
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/ICETSIS61505.2024.10459576
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":"45 4","pages":"917-923"},"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/ICETSIS61505.2024.10459572
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}
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":"255 1","pages":"1108-1112"},"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}
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/ICETSIS61505.2024.10459532
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/ICETSIS61505.2024.10459503
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":"357 2","pages":"263-268"},"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/ICETSIS61505.2024.10459648
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.
{"title":"Review and Conceptual Workflow for Enhancing Wind Loads Design of Sustainable Asymmetrical Tall Buildings","authors":"Fadi Alkhatib, Ali Daris, Aiman H. H. Almasaudi, A. M. Alawag, Abdullah O. Baarimah, A. K. Alakhali","doi":"10.1109/ICETSIS61505.2024.10459521","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459521","url":null,"abstract":"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.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"31 1","pages":"812-816"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530050","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：