Pub Date : 2021-11-01DOI: 10.1109/ITSS-IoE53029.2021.9615267
Jitender Singh Virk, Surender Singh
A composite of several pictures is what we call a Photomontage or a collage. Having a large collection of photographs from an event, wedding, or trip is common these days. It is tedious to manually select meaningful images from the large collection of pictures to create a summary or story-telling montage. With the rapid development of computer vision algorithms, the modern digital world operates on automated and intelligent vision systems. Regular users highly demand these intelligent, automatic, and user-friendly systems. Our focus is to create an intelligent and user-friendly system that requires little to no manual work to create a digital photomontage. As a result, this paper describes the procedure of an automated digital photomontage web app. This system aims to construct an eye-pleasing image from a collection of input images without any effort. The system constructs a montage, also known as collage, of given images using several computer vision algorithms to identify each image’s right placement. The algorithms involve saliency detection, face detection, smooth image-to-image transition, auto-orientation, and image-borders blending. The web app is available at https://jsvirk47.pythonanywhere.com and code is available at https://tinyurl.com/h4ccehrx. The proposed system is easy to use and provides high-quality results. This system is ideal for regular users to process images to share with their friends and family or social media profiles.
{"title":"Automatic Image Alignment and Fusion in a Digital Photomontage","authors":"Jitender Singh Virk, Surender Singh","doi":"10.1109/ITSS-IoE53029.2021.9615267","DOIUrl":"https://doi.org/10.1109/ITSS-IoE53029.2021.9615267","url":null,"abstract":"A composite of several pictures is what we call a Photomontage or a collage. Having a large collection of photographs from an event, wedding, or trip is common these days. It is tedious to manually select meaningful images from the large collection of pictures to create a summary or story-telling montage. With the rapid development of computer vision algorithms, the modern digital world operates on automated and intelligent vision systems. Regular users highly demand these intelligent, automatic, and user-friendly systems. Our focus is to create an intelligent and user-friendly system that requires little to no manual work to create a digital photomontage. As a result, this paper describes the procedure of an automated digital photomontage web app. This system aims to construct an eye-pleasing image from a collection of input images without any effort. The system constructs a montage, also known as collage, of given images using several computer vision algorithms to identify each image’s right placement. The algorithms involve saliency detection, face detection, smooth image-to-image transition, auto-orientation, and image-borders blending. The web app is available at https://jsvirk47.pythonanywhere.com and code is available at https://tinyurl.com/h4ccehrx. The proposed system is easy to use and provides high-quality results. This system is ideal for regular users to process images to share with their friends and family or social media profiles.","PeriodicalId":230566,"journal":{"name":"2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132469958","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 : 2021-11-01DOI: 10.1109/ITSS-IoE53029.2021.9615311
Vivine Nurcahyawati, Z. Mustaffa
Online media serve as a potential secondary data source for studies on sentiment analysis. The current conditions of the data sources are very different, and it offers a variety of writing systems. Therefore, the results of accuracy in sentiment analysis are very important. An improved approach was proposed to increase the sentiment analysis accuracy based on text pre-processing and Naïve Bayes Classifier algorithm hybrid with Particle Swarm Optimization (NBC-PSO). Furthermore, the proposed algorithm solves the complex background problems about noise data and feature selection that affect the classification performance on sentiment analysis. This proceeded with the classification of positive or negative sentiments on these texts using NBC. Subsequently, the feature selection based on PSO was created to improve the accuracy. The experimental results showed that the proposed approach has a significant effect on sentiment score and polarity detection.
{"title":"Feature Selection based on Particle Swarm Optimization Algorithm for Sentiment Analysis Classification","authors":"Vivine Nurcahyawati, Z. Mustaffa","doi":"10.1109/ITSS-IoE53029.2021.9615311","DOIUrl":"https://doi.org/10.1109/ITSS-IoE53029.2021.9615311","url":null,"abstract":"Online media serve as a potential secondary data source for studies on sentiment analysis. The current conditions of the data sources are very different, and it offers a variety of writing systems. Therefore, the results of accuracy in sentiment analysis are very important. An improved approach was proposed to increase the sentiment analysis accuracy based on text pre-processing and Naïve Bayes Classifier algorithm hybrid with Particle Swarm Optimization (NBC-PSO). Furthermore, the proposed algorithm solves the complex background problems about noise data and feature selection that affect the classification performance on sentiment analysis. This proceeded with the classification of positive or negative sentiments on these texts using NBC. Subsequently, the feature selection based on PSO was created to improve the accuracy. The experimental results showed that the proposed approach has a significant effect on sentiment score and polarity detection.","PeriodicalId":230566,"journal":{"name":"2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122867462","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 : 2021-11-01DOI: 10.1109/ITSS-IoE53029.2021.9615291
Redhwan Al-amri, Shuhd Al-Shami, Hussein Mohammed Esmail Abualrejal, Mohammed A. Al-Sharafi, Tareq Khaled Yahya Alormuza
Cryptocurrency is the first successful application of blockchain technology that represents a breakthrough in the financial industry. Cryptocurrencies are decentralized currencies with no central issuer, allowing users to perform transactions, such as virtual payment for goods and services and fund transfer with low fees independently and effectively by utilizing blockchain platforms to ensure the legitimacy and validity of the transactions conducted. However, the acceptance rate of cryptocurrency globally and in Malaysia, is not at the desired level because of consumers' concerns such as Shariah compliance. Therefore, this paper attempts to examine user perception of the acceptance of the cryptocurrency system application from the Shariah perspectives. UTAUT is utilized in this paper, together with a Shariah compliance integration to formulate and evaluate various hypotheses that would establish the proposed conceptual model. The study used a sample of 496 persons. The hypothesis testing revealed that Performance Expectancy, Effort Expectancy, Social Influence, and Shariah compliance all affect behavioral intention to adopt cryptocurrency from a Shariah perspective in Malaysia.
{"title":"Role of Shariah compliance on Cryptocurrency Acceptance among Malaysians: An Empirical Study","authors":"Redhwan Al-amri, Shuhd Al-Shami, Hussein Mohammed Esmail Abualrejal, Mohammed A. Al-Sharafi, Tareq Khaled Yahya Alormuza","doi":"10.1109/ITSS-IoE53029.2021.9615291","DOIUrl":"https://doi.org/10.1109/ITSS-IoE53029.2021.9615291","url":null,"abstract":"Cryptocurrency is the first successful application of blockchain technology that represents a breakthrough in the financial industry. Cryptocurrencies are decentralized currencies with no central issuer, allowing users to perform transactions, such as virtual payment for goods and services and fund transfer with low fees independently and effectively by utilizing blockchain platforms to ensure the legitimacy and validity of the transactions conducted. However, the acceptance rate of cryptocurrency globally and in Malaysia, is not at the desired level because of consumers' concerns such as Shariah compliance. Therefore, this paper attempts to examine user perception of the acceptance of the cryptocurrency system application from the Shariah perspectives. UTAUT is utilized in this paper, together with a Shariah compliance integration to formulate and evaluate various hypotheses that would establish the proposed conceptual model. The study used a sample of 496 persons. The hypothesis testing revealed that Performance Expectancy, Effort Expectancy, Social Influence, and Shariah compliance all affect behavioral intention to adopt cryptocurrency from a Shariah perspective in Malaysia.","PeriodicalId":230566,"journal":{"name":"2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE)","volume":"20 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123565213","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 : 2021-11-01DOI: 10.1109/ITSS-IoE53029.2021.9615300
G. Rajesh, Rishikesh Narayanan, Karthik Srivatsan, Parthiban S, X. M. Raajini
The mathematical expression is an essential part of every domain they provide the mathematical explanation for one’s theory. The technological advancement in the domain of artificial intelligence has aided in various handwritten recognition systems such as handwritten mathematical expression recognition. Symbol recognition and structural analysis are two major obstacles in handwritten mathematical expression recognition. In this paper, we propose a hybrid neural network algorithm called validator, tracker, attention, and parser (VTAP). The hybrid neural network algorithms like CRNN is a blend of recurrent neural network (RNN) and convolutional neural network (CNN). It has shown better and more accurate outputs than the native CNN and RNN algorithms alone. CROHME dataset is used, which is the most widely used dataset. The recognition is divided into 4 parts validator, tracker, attention, and parser (VTAP). A tracker is equipped with a group of Bi-Directional Recurrent Network (BRNN) with the Gated Recurrent Unit (GRU). Succeeded by a tracker, the parser uses a GRU lead by guided hybrid attention. The accuracy and the time complexity of VTAP is compared with existing work Tracker, Attention and Parser (TAP), VTAP shows up to 92.2% of accuracy while TAP shows an accuracy of 89%.
{"title":"Hybrid Neural Network for Handwritten Mathematical Expression Recognition system","authors":"G. Rajesh, Rishikesh Narayanan, Karthik Srivatsan, Parthiban S, X. M. Raajini","doi":"10.1109/ITSS-IoE53029.2021.9615300","DOIUrl":"https://doi.org/10.1109/ITSS-IoE53029.2021.9615300","url":null,"abstract":"The mathematical expression is an essential part of every domain they provide the mathematical explanation for one’s theory. The technological advancement in the domain of artificial intelligence has aided in various handwritten recognition systems such as handwritten mathematical expression recognition. Symbol recognition and structural analysis are two major obstacles in handwritten mathematical expression recognition. In this paper, we propose a hybrid neural network algorithm called validator, tracker, attention, and parser (VTAP). The hybrid neural network algorithms like CRNN is a blend of recurrent neural network (RNN) and convolutional neural network (CNN). It has shown better and more accurate outputs than the native CNN and RNN algorithms alone. CROHME dataset is used, which is the most widely used dataset. The recognition is divided into 4 parts validator, tracker, attention, and parser (VTAP). A tracker is equipped with a group of Bi-Directional Recurrent Network (BRNN) with the Gated Recurrent Unit (GRU). Succeeded by a tracker, the parser uses a GRU lead by guided hybrid attention. The accuracy and the time complexity of VTAP is compared with existing work Tracker, Attention and Parser (TAP), VTAP shows up to 92.2% of accuracy while TAP shows an accuracy of 89%.","PeriodicalId":230566,"journal":{"name":"2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125363660","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 : 2021-11-01DOI: 10.1109/ITSS-IoE53029.2021.9615287
Gurjot Singh Sodhi, Jasjot Singh Sodhi
The innovation of currency recognition intends to look, distinguish and remove the noticeable just as imperceptible subtleties on paper-money for effective classification of currency. Many a times, currency notes are hazy or harmed; a considerable lot of them have complex structures as well. This makes the assignment of currency recognition troublesome. Currency recognition is applied in order to diminish the human influence, put resources into this procedure. So it is essential to choose the correct highlights and legitimate calculation for this reason. This work presents a framework for automated currency notes recognition utilizing supervised image processing strategies. This work is critical considering the mentioned dimensions, namely, a) They got worn-out ahead of their schedule in comparison to coins; b) The possibility of joining wear-out currency is more noteworthy than that of coin currency; c) Coin currency is restricted to lesser population. We have to actualize a calculation which should be straightforward, less mind-boggling and profoundly effective. Recognition of Paper-Currency is significant in the zone of pattern recognition. Image processing is used to acquire the final outcome, with accuracy of 51.0%, 56.8%, 65.6% for the Decision Tree, SVM, Fine-KNN classifiers respectively.
{"title":"A Robust Invariant Image-Based Paper-Currency Recognition Based on F-kNN","authors":"Gurjot Singh Sodhi, Jasjot Singh Sodhi","doi":"10.1109/ITSS-IoE53029.2021.9615287","DOIUrl":"https://doi.org/10.1109/ITSS-IoE53029.2021.9615287","url":null,"abstract":"The innovation of currency recognition intends to look, distinguish and remove the noticeable just as imperceptible subtleties on paper-money for effective classification of currency. Many a times, currency notes are hazy or harmed; a considerable lot of them have complex structures as well. This makes the assignment of currency recognition troublesome. Currency recognition is applied in order to diminish the human influence, put resources into this procedure. So it is essential to choose the correct highlights and legitimate calculation for this reason. This work presents a framework for automated currency notes recognition utilizing supervised image processing strategies. This work is critical considering the mentioned dimensions, namely, a) They got worn-out ahead of their schedule in comparison to coins; b) The possibility of joining wear-out currency is more noteworthy than that of coin currency; c) Coin currency is restricted to lesser population. We have to actualize a calculation which should be straightforward, less mind-boggling and profoundly effective. Recognition of Paper-Currency is significant in the zone of pattern recognition. Image processing is used to acquire the final outcome, with accuracy of 51.0%, 56.8%, 65.6% for the Decision Tree, SVM, Fine-KNN classifiers respectively.","PeriodicalId":230566,"journal":{"name":"2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124652695","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 : 2021-11-01DOI: 10.1109/ITSS-IoE53029.2021.9615325
Abdulrahman A. Alsewari
Nowadays, smart cities depends on the integration between the systems via internet connections which are known as the Internet of Everything (IoE). The integrated systems raise several concerns involving the potential presence of critical integration defects. Therefore, there is a need for an interaction testing approach. In this paper, we present a Nomadic People Optimizer as a search engine for the test list generation for interaction testing. The proposed test list generation strategy is called Nomadic People Strategy (NPS). The results show the NPS is also capable of outperforming the existing strategies such as Genetic Algorithm (GA), Ant Colony Algorithm (ACA), Coco Search Algorithm (CS), Harmony Search Algorithm (HS), Jaya Algorithm (JA), Firefly Algorithm (FA) and Melody Algorithm (MA).
如今，智慧城市依赖于通过互联网连接的系统之间的集成，即所谓的万物互联(IoE)。集成系统提出了几个涉及潜在的关键集成缺陷的问题。因此，需要一种交互测试方法。在本文中，我们提出了一个游牧人优化器作为一个搜索引擎，用于交互测试的测试列表生成。提出的测试表生成策略称为游牧民族策略(Nomadic People strategy, NPS)。结果表明，NPS比遗传算法(GA)、蚁群算法(ACA)、Coco搜索算法(CS)、和声搜索算法(HS)、Jaya算法(JA)、萤火虫算法(FA)、旋律算法(MA)等现有的算法性能更好。
{"title":"Nomadic People Optimizer for IoT Combinatorial Testing Problem","authors":"Abdulrahman A. Alsewari","doi":"10.1109/ITSS-IoE53029.2021.9615325","DOIUrl":"https://doi.org/10.1109/ITSS-IoE53029.2021.9615325","url":null,"abstract":"Nowadays, smart cities depends on the integration between the systems via internet connections which are known as the Internet of Everything (IoE). The integrated systems raise several concerns involving the potential presence of critical integration defects. Therefore, there is a need for an interaction testing approach. In this paper, we present a Nomadic People Optimizer as a search engine for the test list generation for interaction testing. The proposed test list generation strategy is called Nomadic People Strategy (NPS). The results show the NPS is also capable of outperforming the existing strategies such as Genetic Algorithm (GA), Ant Colony Algorithm (ACA), Coco Search Algorithm (CS), Harmony Search Algorithm (HS), Jaya Algorithm (JA), Firefly Algorithm (FA) and Melody Algorithm (MA).","PeriodicalId":230566,"journal":{"name":"2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117041931","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 : 2021-11-01DOI: 10.1109/ITSS-IoE53029.2021.9615338
Sarah Talal, Walid M. Yousef, Belal A. Al-fuhaidi
Vehicular Edge Computing (VEC) is a promising paradigm that approximates cloud services near vehicles with the assistance of offloading. Data and task offloading have aided vehicles to overcome their limited resources since those vehicles' applications are delay-sensitive and resource restrictions. The excessive dynamic nature of vehicular networks is the main challenge of task offloading in VEC. The constant changing of the network topology disconnects the wireless communication channels hence, putting an extra burden on exploring an optimal offloading scheme. Many studies consider the mobility issue, low latency, and resource utilization in the VEC environment. In this paper, a variety of offloading schemes deployed in the VEC environment is examined in the current state of the art, with a new taxonomy of offloading approaches proposed.
{"title":"Computation Offloading Algorithms In Vehicular Edge Computing Environment: A Survey","authors":"Sarah Talal, Walid M. Yousef, Belal A. Al-fuhaidi","doi":"10.1109/ITSS-IoE53029.2021.9615338","DOIUrl":"https://doi.org/10.1109/ITSS-IoE53029.2021.9615338","url":null,"abstract":"Vehicular Edge Computing (VEC) is a promising paradigm that approximates cloud services near vehicles with the assistance of offloading. Data and task offloading have aided vehicles to overcome their limited resources since those vehicles' applications are delay-sensitive and resource restrictions. The excessive dynamic nature of vehicular networks is the main challenge of task offloading in VEC. The constant changing of the network topology disconnects the wireless communication channels hence, putting an extra burden on exploring an optimal offloading scheme. Many studies consider the mobility issue, low latency, and resource utilization in the VEC environment. In this paper, a variety of offloading schemes deployed in the VEC environment is examined in the current state of the art, with a new taxonomy of offloading approaches proposed.","PeriodicalId":230566,"journal":{"name":"2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128376053","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 : 2021-11-01DOI: 10.1109/ITSS-IoE53029.2021.9615302
F. Alqasemi, Salah Al-Hagree, Nail Adeeb Ali Abdu, Baligh M. Al-Helali, G. Al-Gaphari
Text mining applications became important in various intelligent tasks. Text documents are the most materials that record many important procedures in various worldwide organizations and different people cultures. Text poetry is an important type of people culture and education domains media. Arabic text poems classification is a few experimented fields, however, it has an important presence and special influence. Both new and ancient Arabic poetry has the same unique approach for rhythmical harmony measure, which can be used for identifying Arabic poems types. Deep learning as a machine learning method has many distinctive achievements in many areas, as well as, text classification tasks. In this paper, Arabic poetry text is categorized. A customized feature selection is proposed, which is fused with a clustering technique for enhancing models efficiency. Deep learning has experimented alongside two popular machine learning techniques; support vector machine and decision tree. The proposed feature extraction method has achieved high accuracy with all three techniques. The results are better than many related works.
{"title":"Arabic Poetry Meter Categorization Using Machine Learning Based on Customized Feature Extraction","authors":"F. Alqasemi, Salah Al-Hagree, Nail Adeeb Ali Abdu, Baligh M. Al-Helali, G. Al-Gaphari","doi":"10.1109/ITSS-IoE53029.2021.9615302","DOIUrl":"https://doi.org/10.1109/ITSS-IoE53029.2021.9615302","url":null,"abstract":"Text mining applications became important in various intelligent tasks. Text documents are the most materials that record many important procedures in various worldwide organizations and different people cultures. Text poetry is an important type of people culture and education domains media. Arabic text poems classification is a few experimented fields, however, it has an important presence and special influence. Both new and ancient Arabic poetry has the same unique approach for rhythmical harmony measure, which can be used for identifying Arabic poems types. Deep learning as a machine learning method has many distinctive achievements in many areas, as well as, text classification tasks. In this paper, Arabic poetry text is categorized. A customized feature selection is proposed, which is fused with a clustering technique for enhancing models efficiency. Deep learning has experimented alongside two popular machine learning techniques; support vector machine and decision tree. The proposed feature extraction method has achieved high accuracy with all three techniques. The results are better than many related works.","PeriodicalId":230566,"journal":{"name":"2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127217337","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 : 2021-11-01DOI: 10.1109/ITSS-IoE53029.2021.9615285
F. Alqasemi, Salah Al-Hagree, R. Q. Shaddad, Ammar T. Zahary
For communication and computing sciences researchers, the Internet of Everything (IoE) is one of the most attractive topics. It is the field that represents the interconnection between the internet of things (IoT) and people's need for several kinds of technological services. Thus, some literature considers the modern ages as the IoE era. Smart city, 5G, and 6G become part of IoE vocabularies list, besides many techniques and applications that have been utilized by researchers for conducting IoE business and academic projects. In this study, IoE directions have been explored, so papers that have IoE in IEEE Xplore’s indexed terms have been investigated. Retrieved papers have been categorized and systematically reviewed. Diverse perspectives have been studied statistically, presented visually, and papers’ directions are reviewed carefully. The relations between categories have been counted and available information about the IoE world is introduced, the main goal was discovering IoE methods and applications, that have been presented from 2020 to 2021.
{"title":"An IEEE Xplore Database Literature Review Concerning Internet of Everything During 2020-2021","authors":"F. Alqasemi, Salah Al-Hagree, R. Q. Shaddad, Ammar T. Zahary","doi":"10.1109/ITSS-IoE53029.2021.9615285","DOIUrl":"https://doi.org/10.1109/ITSS-IoE53029.2021.9615285","url":null,"abstract":"For communication and computing sciences researchers, the Internet of Everything (IoE) is one of the most attractive topics. It is the field that represents the interconnection between the internet of things (IoT) and people's need for several kinds of technological services. Thus, some literature considers the modern ages as the IoE era. Smart city, 5G, and 6G become part of IoE vocabularies list, besides many techniques and applications that have been utilized by researchers for conducting IoE business and academic projects. In this study, IoE directions have been explored, so papers that have IoE in IEEE Xplore’s indexed terms have been investigated. Retrieved papers have been categorized and systematically reviewed. Diverse perspectives have been studied statistically, presented visually, and papers’ directions are reviewed carefully. The relations between categories have been counted and available information about the IoE world is introduced, the main goal was discovering IoE methods and applications, that have been presented from 2020 to 2021.","PeriodicalId":230566,"journal":{"name":"2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129286404","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 : 2021-11-01DOI: 10.1109/ITSS-IoE53029.2021.9615351
R. M. Tawafak, Abdulrahman A. Alsewari, S. I. Malik, Ghaliya Alfarsi
Educational institutions in different contexts of the world are increasingly working on exploring the potential of educational development and challenges that might enhance student performance. Still, there are missing benefits of using applications that directly impact the enhancement of student performance in Oman. This paper aims to create a "Tool Model Group" (TMG) model to improve student performance using technological learning techniques in modified evaluation to enhance academic performance. In the first phase of this study, a systematic review of the existing literature was conducted to determine the degree of acceptability and effectiveness of existing applications in e-learning. The second stage involved designing a model for the hybrid e-learning tools. It is followed by a system efficiency check that can measure the technology’s suitability for academic performance. The findings of this paper show a significant result of TMG impact on student performance in Oman.
{"title":"A Tool Model Group (TMG) Development to Enhance Student Performance","authors":"R. M. Tawafak, Abdulrahman A. Alsewari, S. I. Malik, Ghaliya Alfarsi","doi":"10.1109/ITSS-IoE53029.2021.9615351","DOIUrl":"https://doi.org/10.1109/ITSS-IoE53029.2021.9615351","url":null,"abstract":"Educational institutions in different contexts of the world are increasingly working on exploring the potential of educational development and challenges that might enhance student performance. Still, there are missing benefits of using applications that directly impact the enhancement of student performance in Oman. This paper aims to create a \"Tool Model Group\" (TMG) model to improve student performance using technological learning techniques in modified evaluation to enhance academic performance. In the first phase of this study, a systematic review of the existing literature was conducted to determine the degree of acceptability and effectiveness of existing applications in e-learning. The second stage involved designing a model for the hybrid e-learning tools. It is followed by a system efficiency check that can measure the technology’s suitability for academic performance. The findings of this paper show a significant result of TMG impact on student performance in Oman.","PeriodicalId":230566,"journal":{"name":"2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126449957","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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