Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459364
Amjad Al Nagrash, Nawal Alareed, S. Aldulaimi, M. Abdeldayem, Abed Rzaij Aswad
With the digital transformation occurring in both public and private institutions, leading to the provision of services through electronic means and the digitization of most transactions, there arose a need for legal regulations to govern electronic transactions and address crimes committed through electronic means. In the Kingdom of Bahrain, the legislator took steps to regulate such crimes through a dedicated law separate from the Penal Code. The objective of this research is to assess the level of integration achieved among various laws pertaining to the regulation of electronic crimes, particularly those related to the Social Insurance Law that occur using electronic means. The Social Insurance Law in Bahrain establishes detailed provisions for implementing all associated obligations. This study highlights the importance of granting judicial control officer status to the inspectors of the General Authority, and also emphasizes the need to activate Article 18 of the Information Technology Crimes Law. This is where the Public Prosecution has delegated authority to the General Authority's inspectors to seize evidence of crimes related to the Social Insurance Law.
{"title":"Unveiling the Legal Implications of Regulating Information Technology Crimes in Violations of the Social Insurance Law","authors":"Amjad Al Nagrash, Nawal Alareed, S. Aldulaimi, M. Abdeldayem, Abed Rzaij Aswad","doi":"10.1109/ICETSIS61505.2024.10459364","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459364","url":null,"abstract":"With the digital transformation occurring in both public and private institutions, leading to the provision of services through electronic means and the digitization of most transactions, there arose a need for legal regulations to govern electronic transactions and address crimes committed through electronic means. In the Kingdom of Bahrain, the legislator took steps to regulate such crimes through a dedicated law separate from the Penal Code. The objective of this research is to assess the level of integration achieved among various laws pertaining to the regulation of electronic crimes, particularly those related to the Social Insurance Law that occur using electronic means. The Social Insurance Law in Bahrain establishes detailed provisions for implementing all associated obligations. This study highlights the importance of granting judicial control officer status to the inspectors of the General Authority, and also emphasizes the need to activate Article 18 of the Information Technology Crimes Law. This is where the Public Prosecution has delegated authority to the General Authority's inspectors to seize evidence of crimes related to the Social Insurance Law.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"176 1","pages":"39-47"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530258","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/ICETSIS61505.2024.10459697
R. Tiwari, Anurag Kumar
Growing beans is important since they are a staple meal for so many people throughout the world. Bean rust and angular leaf spot are just two of the many diseases that threaten the well-being of bean crops and, in turn, cause considerable output losses. In this research, an ensemble deep learning strategy named EnDeel, is proposed to solve the problem of reliably identifying bean leaf lesions as healthy, angular leaf spots, or bean rust. Five different deep convolutional neural network architectures (MobileNetV2, ResNet50, EfficientNetB2, DenseNet121, and VGG16) are trained and have their parameters initialized via transfer learning. Images of bean leaf lesions are fed into these models to extract relevant features, and the fully connected layer was classified using softmax. By using majority voting, the predictions from the top three deep learning architectures are combined to construct the EnDeeL ensemble classifier. To gauge how well each deep learning classifier did, it is compared to the ensemble classifier EnDeeL. The findings show that EnDeeL outperformed the examined single deep-learning classifiers with an astounding 92.12% test accuracy. This performance improvement demonstrates the usefulness of the ensemble strategy, which increases classification accuracy when compared to that of individual classifiers.
{"title":"Bean Leaf Lesions Image Classification: A Robust Ensemble Deep Learning Approach","authors":"R. Tiwari, Anurag Kumar","doi":"10.1109/ICETSIS61505.2024.10459697","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459697","url":null,"abstract":"Growing beans is important since they are a staple meal for so many people throughout the world. Bean rust and angular leaf spot are just two of the many diseases that threaten the well-being of bean crops and, in turn, cause considerable output losses. In this research, an ensemble deep learning strategy named EnDeel, is proposed to solve the problem of reliably identifying bean leaf lesions as healthy, angular leaf spots, or bean rust. Five different deep convolutional neural network architectures (MobileNetV2, ResNet50, EfficientNetB2, DenseNet121, and VGG16) are trained and have their parameters initialized via transfer learning. Images of bean leaf lesions are fed into these models to extract relevant features, and the fully connected layer was classified using softmax. By using majority voting, the predictions from the top three deep learning architectures are combined to construct the EnDeeL ensemble classifier. To gauge how well each deep learning classifier did, it is compared to the ensemble classifier EnDeeL. The findings show that EnDeeL outperformed the examined single deep-learning classifiers with an astounding 92.12% test accuracy. This performance improvement demonstrates the usefulness of the ensemble strategy, which increases classification accuracy when compared to that of individual classifiers.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"406 13","pages":"986-993"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The application of the metaverse in business can be seen as an emerging application of media in communication technology especially marketing via new media technology, such as virtual reality. However, does the application of the metaverse to market products, especially in the fashion industry on a smaller business scale which uses simple metaverse tools, also have a positive effect on the product brand? Based on this, we want to see the relationship between variables related to the use of metaverse seen from the customer's perspective, namely metaverse user experience, customer engagement, and brand awareness in case studies of product marketing using metaverse carried out by the SME's industry in the fashion sector. Different from previous research, this research is action research that uses a simple metaverse application especially a virtual world to market fashion products in SME businesses, to see how it affects brand awareness of the products. This research was analyzed quantitatively to look at the relationship between metaverse user experience and brand awareness through the mediation of customer engagement. By using SMART PLS as a tool, we looked at the relationships between these variables among the 90 respondents we got. From the results we got, the metaverse user experience variable has a positive relationship with brand awareness through the mediation of customer engagement. The metaverse, especially the virtual world, is applied as a marketing strategy to increase brand awareness of fashion products in the SME business environment based on those variables.
{"title":"Metaverse User Experience, Customer Engagement, and Brand Awareness Relation as SMEs Marketing Strategies in Virtual Worlds","authors":"Anita Safitri, Nanang Husin, Ika Diyah Candra Arifah, Renny Sari Dewi, Fresha Kharisma, Achmad Kautsar","doi":"10.1109/ICETSIS61505.2024.10459506","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459506","url":null,"abstract":"The application of the metaverse in business can be seen as an emerging application of media in communication technology especially marketing via new media technology, such as virtual reality. However, does the application of the metaverse to market products, especially in the fashion industry on a smaller business scale which uses simple metaverse tools, also have a positive effect on the product brand? Based on this, we want to see the relationship between variables related to the use of metaverse seen from the customer's perspective, namely metaverse user experience, customer engagement, and brand awareness in case studies of product marketing using metaverse carried out by the SME's industry in the fashion sector. Different from previous research, this research is action research that uses a simple metaverse application especially a virtual world to market fashion products in SME businesses, to see how it affects brand awareness of the products. This research was analyzed quantitatively to look at the relationship between metaverse user experience and brand awareness through the mediation of customer engagement. By using SMART PLS as a tool, we looked at the relationships between these variables among the 90 respondents we got. From the results we got, the metaverse user experience variable has a positive relationship with brand awareness through the mediation of customer engagement. The metaverse, especially the virtual world, is applied as a marketing strategy to increase brand awareness of fashion products in the SME business environment based on those variables.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"397 8","pages":"1092-1096"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530031","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}
“Baby Sentry” is designed as an automated cradle that operates on sensors. This cradle is mainly designed to detect any possible external harm while keeping the baby comfortable and notifying the parents of the baby's condition. The cradle would monitor the baby's activities continuously, including the expressions, moisture, temperature, surroundings, etc. To make sure that the baby is comfortable, the cradle would automatically swing when required and play soothing audio(like ragas, mother's voice, music, etc.) to calm the baby. A Health Algorithm is applied to these real-time datasets to get information about the body's conditions. All these actions can be handled using the app. An external camera will photograph anyone who approaches the cradle, and the app will notify the parents.
{"title":"Baby Sentry: A Smart Cradle","authors":"Pradnya V Kulkarni, Madhura Phatak, Ashwathha Sahasrabuddhe, Anagha Langhe, Rohan Disa, Harsh Choudhary, Astha Munot","doi":"10.1109/ICETSIS61505.2024.10459610","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459610","url":null,"abstract":"“Baby Sentry” is designed as an automated cradle that operates on sensors. This cradle is mainly designed to detect any possible external harm while keeping the baby comfortable and notifying the parents of the baby's condition. The cradle would monitor the baby's activities continuously, including the expressions, moisture, temperature, surroundings, etc. To make sure that the baby is comfortable, the cradle would automatically swing when required and play soothing audio(like ragas, mother's voice, music, etc.) to calm the baby. A Health Algorithm is applied to these real-time datasets to get information about the body's conditions. All these actions can be handled using the app. An external camera will photograph anyone who approaches the cradle, and the app will notify the parents.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"388 5-6","pages":"1084-1091"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper addresses the growing global health concern of dementia through the introduction of an innovative Cognitive Assistance System to locate personal items. Our proposed system utilizes smart spectacles equipped with a camera, driven by an ESP 32 CAM to capture the user's field of vision and Live stream. This Real-time video feed is processed using YOLO v8 for object detection, and the extracted labels data is stored in a MongoDB database. This data is then used to find the objects and recognize the location of the objects, using a list of object labels seen at that time. The proposed methodology involves continuous video streaming, object detection, and scene recognition. Notably, a Random Forest Classifier, trained on a custom dataset, attains an average accuracy of 91 % in recognizing indoor scenes based on label data. A DialogFlow-integrated chatbot on Telegram assists users in locating personal belongings and retrieves details on the scene detected and time of objects. Hardware development focuses on creating compact, comfortable, and lightweight spectacles tailored for regular use. Results showcase the effectiveness of the Random Forest Classifier and YOLO v8 in scene detection and object recognition. The seamless integration of the chatbot with Telegram enhances user accessibility, representing a significant advancement in providing practical support for dementia patients and addressing challenges for caregivers. Future work involves integrating voice assistants, refining accuracy, and expanding capabilities for indoor navigation, aiming to extend the solution's reach and enhance the lives of those affected by cognitive decline.
{"title":"Cognitive Assistance for Dementia Patients","authors":"Dheeraj Kiran Enna, Pratyus Basuli, Ayush Hrishikesh Mishra, Sunil Kumar Singh","doi":"10.1109/ICETSIS61505.2024.10459484","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459484","url":null,"abstract":"This paper addresses the growing global health concern of dementia through the introduction of an innovative Cognitive Assistance System to locate personal items. Our proposed system utilizes smart spectacles equipped with a camera, driven by an ESP 32 CAM to capture the user's field of vision and Live stream. This Real-time video feed is processed using YOLO v8 for object detection, and the extracted labels data is stored in a MongoDB database. This data is then used to find the objects and recognize the location of the objects, using a list of object labels seen at that time. The proposed methodology involves continuous video streaming, object detection, and scene recognition. Notably, a Random Forest Classifier, trained on a custom dataset, attains an average accuracy of 91 % in recognizing indoor scenes based on label data. A DialogFlow-integrated chatbot on Telegram assists users in locating personal belongings and retrieves details on the scene detected and time of objects. Hardware development focuses on creating compact, comfortable, and lightweight spectacles tailored for regular use. Results showcase the effectiveness of the Random Forest Classifier and YOLO v8 in scene detection and object recognition. The seamless integration of the chatbot with Telegram enhances user accessibility, representing a significant advancement in providing practical support for dementia patients and addressing challenges for caregivers. Future work involves integrating voice assistants, refining accuracy, and expanding capabilities for indoor navigation, aiming to extend the solution's reach and enhance the lives of those affected by cognitive decline.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"119 3-4","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":"140530376","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/ICETSIS61505.2024.10459647
Zafrul Allam, Shaju George, Karim Ben Yahia, Ansa Savad Salim, Nasir Ali
Psychological contract breach (PCB) is a phenomenon that occurs when employees perceive that their organization has failed to fulfill its obligations or promises can lead to a number of negative consequences for employees, including reduced well-being. PCB has been widely studied in various contexts and disciplines, but there is a lack of comprehensive and systematic review of the literature on PCB in the Indian context. This paper aims to fill this gap by conducting a bibliometric analysis of the literature on PCB in the Indian context using data from Scopus database. The paper analyzes 31 articles published between 2011 and 2023, and examines the patterns, trends, and gaps in the literature based on various indicators, such as publication year, author, affiliation, documents type, and subject area. In this paper, we offer insights and implications for researchers and practitioners who are interested in PCB in the context of India, and we suggest directions for further research in this field.
{"title":"A Bibliometric Review of Psychological Contract Breach Studies in India from 2011 to 2023","authors":"Zafrul Allam, Shaju George, Karim Ben Yahia, Ansa Savad Salim, Nasir Ali","doi":"10.1109/ICETSIS61505.2024.10459647","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459647","url":null,"abstract":"Psychological contract breach (PCB) is a phenomenon that occurs when employees perceive that their organization has failed to fulfill its obligations or promises can lead to a number of negative consequences for employees, including reduced well-being. PCB has been widely studied in various contexts and disciplines, but there is a lack of comprehensive and systematic review of the literature on PCB in the Indian context. This paper aims to fill this gap by conducting a bibliometric analysis of the literature on PCB in the Indian context using data from Scopus database. The paper analyzes 31 articles published between 2011 and 2023, and examines the patterns, trends, and gaps in the literature based on various indicators, such as publication year, author, affiliation, documents type, and subject area. In this paper, we offer insights and implications for researchers and practitioners who are interested in PCB in the context of India, and we suggest directions for further research in this field.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"117 9-10","pages":"386-390"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530378","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/ICETSIS61505.2024.10459402
Mithilesh Lathkar, Parth Deshmukh, Aditya Patil, Priya M. Shelke
The project aims to create a decentralized system for tracking donations based on blockchain technology built using ReactJS and WEB 3.0. The goal is to integrate transparency and convenience into the online donation methods. Our system offers a clear record of transactions for donors, allowing them direct interaction with the recipients, whether charitable foundations or individual beneficiaries. Smart contracts, composed in Solidity programming language, are stored on the Ethereum public blockchain, enabling automatic execution under specified conditions. Currently, blockchain technology finds extensive application across various sectors. Payments are now facilitated through this technology, ensuring transparency in the processes of donation and fund transfers. To track donations, a single database that contains all donor information, transaction history, and donation records must be established. This blockchain-based system facilitates the operations of donors, nonprofit organizations, and recipients by offering a transparent and safe platform.
该项目旨在利用 ReactJS 和 WEB 3.0 创建一个基于区块链技术的去中心化捐款跟踪系统。我们的目标是将透明度和便利性融入在线捐赠方法中。我们的系统为捐赠者提供清晰的交易记录，使他们能够与受捐者（无论是慈善基金会还是个人受益者）直接互动。用 Solidity 编程语言编写的智能合约存储在以太坊公共区块链上，可在指定条件下自动执行。目前，区块链技术在各行各业得到广泛应用。目前，该技术为支付提供了便利，确保了捐赠和资金转移过程的透明度。为了追踪捐赠，必须建立一个包含所有捐赠者信息、交易历史和捐赠记录的单一数据库。这种基于区块链的系统通过提供一个透明、安全的平台，为捐赠者、非营利组织和受赠者的运作提供了便利。
{"title":"Increasing Donation Transparency in Disaster Relief: A Blockchain-based Solution","authors":"Mithilesh Lathkar, Parth Deshmukh, Aditya Patil, Priya M. Shelke","doi":"10.1109/ICETSIS61505.2024.10459402","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459402","url":null,"abstract":"The project aims to create a decentralized system for tracking donations based on blockchain technology built using ReactJS and WEB 3.0. The goal is to integrate transparency and convenience into the online donation methods. Our system offers a clear record of transactions for donors, allowing them direct interaction with the recipients, whether charitable foundations or individual beneficiaries. Smart contracts, composed in Solidity programming language, are stored on the Ethereum public blockchain, enabling automatic execution under specified conditions. Currently, blockchain technology finds extensive application across various sectors. Payments are now facilitated through this technology, ensuring transparency in the processes of donation and fund transfers. To track donations, a single database that contains all donor information, transaction history, and donation records must be established. This blockchain-based system facilitates the operations of donors, nonprofit organizations, and recipients by offering a transparent and safe platform.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"347 6-7","pages":"1527-1532"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530490","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/ICETSIS61505.2024.10459705
Pranay Dongre, Simran Kedia, Janhavi Banubakade, Deepali M. Kotambkar
In individuals around the world, Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) is the most prevalent consequence of diabetes and a major factor in visual loss. The Convolutional Neural Network (CNN) architecture shown in this research is intended to automatically identify Diabetic Macular Edema (DME) and Diabetic Retinopathy (DR) from retinal fundus images. After being trained on a sizable dataset made up of several classes, the CNN model used inception is capable of outperforming earlier methods by reliably diagnosing the presence and severity of specific diseases. Its ability to handle a wide range of image qualities and intricate pathological aspects makes it a solid instrument for improved patient outcomes and early intervention, which lessens the toll that Diabetic eye disease takes on society and healthcare systems. We give a thorough experimental assessment of our methodology on a benchmark dataset, illustrating its efficacy in precisely identifying various stages involves Diabetic Retinopathy and Diabetic Macular Edema. The obtained results demonstrate a good level of performance and highlight the potential of deep learning methods in diagnosis.
{"title":"Diabetic Eye Health: Deep Learning Classification","authors":"Pranay Dongre, Simran Kedia, Janhavi Banubakade, Deepali M. Kotambkar","doi":"10.1109/ICETSIS61505.2024.10459705","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459705","url":null,"abstract":"In individuals around the world, Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) is the most prevalent consequence of diabetes and a major factor in visual loss. The Convolutional Neural Network (CNN) architecture shown in this research is intended to automatically identify Diabetic Macular Edema (DME) and Diabetic Retinopathy (DR) from retinal fundus images. After being trained on a sizable dataset made up of several classes, the CNN model used inception is capable of outperforming earlier methods by reliably diagnosing the presence and severity of specific diseases. Its ability to handle a wide range of image qualities and intricate pathological aspects makes it a solid instrument for improved patient outcomes and early intervention, which lessens the toll that Diabetic eye disease takes on society and healthcare systems. We give a thorough experimental assessment of our methodology on a benchmark dataset, illustrating its efficacy in precisely identifying various stages involves Diabetic Retinopathy and Diabetic Macular Edema. The obtained results demonstrate a good level of performance and highlight the potential of deep learning methods in diagnosis.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"335 5","pages":"1410-1415"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530496","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/ICETSIS61505.2024.10459617
Mohamed Albaz, Mahmoud Khalifa
Although there is a gap between traditional education and technological education, technological education has been the best and most secure means of communicating information to students and continuing education. Hence, the human component of organizations is one of the most important assets they possess, and attention to intellectual capital (IC) is one of the most important challenges facing human resources management because of the urgent need to regulate creativity, innovation, and cognitive work, intellectual capital focuses on the innovative and creative potential of human resources and how to discover, invest and preserve them. The study aimed to analyze the role of the technological education strategy in developing intellectual capital in the university education sector in Egypt, which dealt with the universities of the Canal Cities and Sinai, in light of the Egypt Sustainable Development Strategy 2030. It has been shown that technological education has a positive impact on the development of the intellectual capital of the universities under study. The research relied on the descriptive analytical method to determine the framework to develop the proposed framework to clarify the relationship between technological education and intellectual capital development in the universities of the Canal Cities and Sinai. An analysis of the literature in the field of technological learning and intellectual capital was also used to identify the most important axes of intellectual capital development in the universities in question. The study, main question of the research was what is the role of Technological Education Strategy in developing Intellectual Capital in the universities of the Canal cities and Sinai.
{"title":"Technological Education Strategy and Its Role in Developing Intellectual Capital - A Field Study","authors":"Mohamed Albaz, Mahmoud Khalifa","doi":"10.1109/ICETSIS61505.2024.10459617","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459617","url":null,"abstract":"Although there is a gap between traditional education and technological education, technological education has been the best and most secure means of communicating information to students and continuing education. Hence, the human component of organizations is one of the most important assets they possess, and attention to intellectual capital (IC) is one of the most important challenges facing human resources management because of the urgent need to regulate creativity, innovation, and cognitive work, intellectual capital focuses on the innovative and creative potential of human resources and how to discover, invest and preserve them. The study aimed to analyze the role of the technological education strategy in developing intellectual capital in the university education sector in Egypt, which dealt with the universities of the Canal Cities and Sinai, in light of the Egypt Sustainable Development Strategy 2030. It has been shown that technological education has a positive impact on the development of the intellectual capital of the universities under study. The research relied on the descriptive analytical method to determine the framework to develop the proposed framework to clarify the relationship between technological education and intellectual capital development in the universities of the Canal Cities and Sinai. An analysis of the literature in the field of technological learning and intellectual capital was also used to identify the most important axes of intellectual capital development in the universities in question. The study, main question of the research was what is the role of Technological Education Strategy in developing Intellectual Capital in the universities of the Canal cities and Sinai.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"331 3-4","pages":"100-104"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530202","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/ICETSIS61505.2024.10459348
Anas Tawalbeh, Moustafa Elsharqawy, Mohamed Soliman
The current study aims to explore university students' engagement in the use of online learning with a theoretical foundation beyond the pandemic. This technology was recently introduced to higher education, but few studies have examined its effects. A combination of the technology acceptance model (TAM) and social cognitive theory (SCT) is used in this study to examine the factors that impact university students' engagement and their academic performance in using online learning to teach Arabic language among non-native speakers. A questionnaire will be given to university students to acquire data for the suggested model. The effect of students' engagement using the online learning platform will be investigated using a hybrid approach consisting of partial least squares structural equation modelling (PLS-SEM) and an artificial neural network (ANN) to capture linear and nonlinear relationships within a non-compensatory model. The study will be interesting for scholars, policymakers, and practitioners from the higher education context.
{"title":"Exploring the Drivers of University Students' Engagement of Online Learning Platforms Among Non-Native Arabic Speakers: A Case of Thailand's Southern Border Provinces","authors":"Anas Tawalbeh, Moustafa Elsharqawy, Mohamed Soliman","doi":"10.1109/ICETSIS61505.2024.10459348","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459348","url":null,"abstract":"The current study aims to explore university students' engagement in the use of online learning with a theoretical foundation beyond the pandemic. This technology was recently introduced to higher education, but few studies have examined its effects. A combination of the technology acceptance model (TAM) and social cognitive theory (SCT) is used in this study to examine the factors that impact university students' engagement and their academic performance in using online learning to teach Arabic language among non-native speakers. A questionnaire will be given to university students to acquire data for the suggested model. The effect of students' engagement using the online learning platform will be investigated using a hybrid approach consisting of partial least squares structural equation modelling (PLS-SEM) and an artificial neural network (ANN) to capture linear and nonlinear relationships within a non-compensatory model. The study will be interesting for scholars, policymakers, and practitioners from the higher education context.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"149 3","pages":"718-722"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530088","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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