2022 International Arab Conference on Information Technology (ACIT)最新文献

{"title":"Open-SBS: Smart Building Simulator","authors":"Houssem Eddine Degha, F. Z. Laallam, O. Kazar, Issam Khelfaoui, B. Athamena, Z. Houhamdi","doi":"10.1109/ACIT57182.2022.9994156","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994156","url":null,"abstract":"With the rise of machine learning and deep learning techniques in recent years, a representative dataset has become an inspiring source of prediction and knowledge extraction. Furthermore, ambient intelligence environments have emerged as one of the most important research areas. Many complex tasks and challenges face this area to validate and evaluate field research. One of the major challenges in the smart building domain is the lack of a simulation tool capable of simulating complex contexts, executing semantic rules, and collecting representative datasets for experiments. To address these issues, we present in this paper a cross-platform, open-source Smart Building Simulator (Open-SBS). Open-SBS offer an opportunity for researchers in the field of Ambient Intelligence environments to simulate complex contexts and collect representative datasets, save and share their models of experiments. We propose a new simulation process that is divided into four distinct phases: designing, scenario creation, semantic rule addition, and data-set generation. On the System Usability Scale, we conducted a study to assess the ease of use of Open-SBS (SUS).","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131756240","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}

{"title":"Motivating Pre-School Children to Learn Creative Thinking in Jordan Using iPad Applications: A Mixed-Methods Approach","authors":"M. A. Al-Zu’bi, Kholoud I. AL-MSEIDIN, Abdullah Falah Almajali, Reda S.M. Al-Mawadieh, Hayel Khafajeh, Noor Abutayeh","doi":"10.1109/ACIT57182.2022.9994097","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994097","url":null,"abstract":"The review of iPad's literature confirms that the studies are limited only to improving literacy levels among pre-school children. Other aspects of technology on cognition and behaviors among pre-school children are explored. Further, there are conflicting findings of the iPad. Some studies confirm the iPad is a positive tool. Other studies confirm the iPad is a negative tool. The purpose of the study was to examine the effect of iPad applications on the Motivation to learn creative thinking. Secondly, factors influencing the use of iPad applications in a play-based environment were discussed. Lastly, consideration has been made of elements that affect the utilization of iPad applications in a playing context. These applications were subjected to an experimental design incorporated in a mixed-methods approach to a classroom in the kindergarten (n =51). Significant gains were noted between the control and experimental groups. The MLCT -Scale scores demonstrated that pre-school children in the experimental group gained more Motivation to learn creative thinking than the control group. The iPad applications help students cooperate and engage in a play-based learning environment. Learning creative thinking has increased significantly. Score and high engagement levels indicate that iPad applications can improve creative learning thinking in kindergarten classrooms. Factors affecting the use of iPad applications included the quality of the software, which promotes the engagement of children to learning creative thinking.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126822426","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}

{"title":"Electronic Monitoring in the Criminal Justice System of the UAE & France","authors":"Ahmad Ateeq Al Dhaheri, M. Alkrisheh, M. Kandeel, T. Kameel","doi":"10.1109/ACIT57182.2022.9994099","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994099","url":null,"abstract":"The Electronic Monitoring is one of the new topics in the field of criminal justice, as it represents the development of modern techniques in the enforcement of penalties by replacing custodial penalties with a penalty of home confinement or restricting the person's freedom in his home through the use of Electronic Monitoring techniques. The UAE law and French law have introduced and implemented Electronic Monitoring. This paper reviews and compares the temporary placement of the accused under Electronic Monitoring instead of pretrial detention, placement under Electronic Monitoring as an alternative to custodial penalty, conditional release and placement under Electronic Monitoring, and finally placing juveniles under Electronic Monitoring in both the UAE and French legislation.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114230310","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}

{"title":"The Past, Present, and Future of Robotic Systems in Automotive Applications","authors":"A. Shaout, Sarah Overbeck","doi":"10.1109/ACIT57182.2022.9994143","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994143","url":null,"abstract":"This paper focuses on the automotive applications of robotic systems and their evolution on two fronts: manufacturing and autonomous vehicles. The first will be divided into chronological generations and while the second will be based on level of automation, with several key elements identified and detailed.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114293879","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}

{"title":"Stellar Objects Classification Using Supervised Machine Learning Techniques","authors":"Deen Omat, Jood Otey, Amjed Al-mousa","doi":"10.1109/ACIT57182.2022.9994215","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994215","url":null,"abstract":"Machine Learning is used in many fields of study. This paper used machine learning to classify instances from the Sloan Digital Sky Survey Data Release 17 (SDSS DR17) as a galaxy, quasar, or star. Supervised learning was used to make the classification. Multiple machine learning models were built, Decision Trees, K-Nearest Neighbors, Multinomial Logistic Classification, Multilayer Perceptron, Naïve Bayes Classifier, Support Vector Classification, Random Forest, and Soft Voting Classifier. Random Forest performed the best with 98% accuracy and correctly classified all instances labeled as stars in the dataset. The worst-performing algorithm was Naïve Bayes, with 91% accuracy.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"37 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115823497","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}

{"title":"A Prediction Approach for the Functional Effects of Non-Coding Gene Variants","authors":"Gözde Yurtdas, Kagan Aslan, S. Özyer, Tansel Özyer, Mehmet Kaya, R. Alhajj","doi":"10.1109/ACIT57182.2022.9994094","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994094","url":null,"abstract":"The aim of this study is to develop an approach for predicting the functional effects of variants of non-coding genes which have great importance in human genetics. Non-coding genes have formed a very vital field of study since they have a high effect on diseases. However, little is known about non-coding genes compared to coding genes, and they are found in the body almost 9 times more than coding genes. This is a critical issue, and i t is very important to predict the effects of these genes, which are so abundant in the body and difficult to understand. This exhibits the motivation of the study described in the paper. For this purpose, an extensive literature review was first conducted, and possible datasets that could be used were examined. Then, using Python programming language, we developed a prediction model with high accuracy. After investigating how important non-coding gene variants are, and in what areas they can be used, we decided to use a functional interaction network from the deep learning models as the most suitable method. We used STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) which is a biological database and web resource of known and predicted protein-protein interactions. As a second step, we generated feature vectors. After checking the overlap of non-coding genes, we extracted three types of feature vectors. Identifying protein interaction network in Python, the outcome describes the interplay between the biomolecules encoded by genes. It allows to understand the complexities of cellular functions, and even predict potential therapeutics. As a last step, we implemented a deep learning model which included three fully connected (FC) layers, also known as dense layers, with dimensions 40, 10, and 2, respectively. Experimental results demonstrate that the proposed method captured high accuracy values.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117327479","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}

{"title":"The Emerging Engineering Applications of Artificial Neural Networks: A Visionary Study","authors":"M. Alhassan, Layla Amaireh, H. Salameh, Mohannad Alhafnawi, Nour Betoush","doi":"10.1109/ACIT57182.2022.9994098","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994098","url":null,"abstract":"In various engineering disciplines, researchers are always ambitious to understand and predict the behavior of an element or a system. Thus, for a specific area of research, various experimental and numerical studies are typically implemented resulting in a massive amount of data and findings. The findings are sometimes contradicting or lack the full picture due to the many entailed parameters that are difficult to consider in one study. To address this challenge, smart technologies such as Artificial Neural Networks (ANN) are recognized as vital techniques that allow system designers to compile and manage the huge collected data points pertinent to the problem under investigation. The ANN is capable of identifying the factors that significantly impact the behavior and performance of different engineering systems. This can be accomplished through the ANN systematic process that entails three consecutive stages: training, testing, and validation based on a sufficient number of data points. The outcomes of the ANN-based research study in the engineering area range from the development of a new model for the prediction of a performance characteristic, modifying a design code equation, or validation of experimental/numerical results. This visionary paper highlights a number of innovative applications of the ANN technique in various emerging engineering fields. Specifically, the transfer length of prestressing strands, strength of recycled aggregate concrete, and fracture parameters of fiber-reinforced concrete are highlighted in this study.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128654019","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}

{"title":"Network-based Intrusion Detection Datasets: A Survey","authors":"L. Ahmed, Y. A. M. Hamad, A. M. Abdalla","doi":"10.1109/ACIT57182.2022.9994201","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994201","url":null,"abstract":"The increasing reliance on computers and the internet has increased the need for protection against attacks and security threats. A network-based intrusion detection system (NIDS) is one of the promising research fields that could highly contribute to cyber-attacks detection and mitigation. Datasets are necessary for NIDS training and evaluation. This paper provides a comprehensive survey of publicly available NIDS datasets. The study covers the most used NIDS datasets, each dataset is briefly described along with its main properties and shortcomings. Moreover, the paper highlights the most important dataset characteristics and provides a clear datasets comparison accordingly. Finally, the paper discusses observations and provides some recommendations to help researchers identify future work.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130000774","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}

{"title":"Within-Project Defect Prediction Using Improved CNN Model via Extracting the Source Code Features","authors":"Alaa T. Elbosaty, W. Abdelmoez, Essam Elfakharany","doi":"10.1109/ACIT57182.2022.9994220","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994220","url":null,"abstract":"Errors in software systems are inevitable. However, fixing bugs requires cost and time. If they are detected early, this problem is solved with Artificial Intelligence in Software Engineering (AISE). Therefore, software error prediction is used to discover software errors in the source code and to take into account the testing effort in the development phase. The first of the three phases presented in this work is the re-implementation of the Congs model [12] on Colab. compared the result of the original Congs model to the newly implemented model result when we found that the Congs model under Colab approximates the original results using the Simplified PROMISE Source Code (SPSC) dataset. The second is to extract deep features from source codes or ASTs as model input and proposed deep models (CNN). Third, an improved CNN model for within-project defect prediction (WPDP) by hyperparameter tuning was proposed and our results are compared to current CNN results. Our improved CNN model outperforms the improved F -measure by 29% and achieves a 93% F1-measure in our CNN model.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116706473","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}

{"title":"The Effects of Information Technology on The Educational Sector in The United Arab Emirate","authors":"S. Alwaely, Hanene Lahiani, Hani Aljarrah, Hatem Alqudah","doi":"10.1109/ACIT57182.2022.9994137","DOIUrl":"https://doi.org/10.1109/ACIT57182.2022.9994137","url":null,"abstract":"Online education, distance learning, e-learning, flexible learning, collaborative learning, anytime, anywhere, virtual learning, a multimedia approach to learning, have all emerged as direct results of the information technology revolution in education. Teaching and learning have been greatly facilitated by IT applications' widespread use in higher education, and other educational institutions. In this study, we looked at how the introduction of new technologies has altered teaching and learning in the United Arab Emirate (UAE). Due in large part to claims made around the turn of the century about posited characteristics of today's youth, referred to in the debate as digital natives, international research in recent years has documented the access to, and use of, digital technologies by young people in many parts of the world. In response, many governments and educational institutions around the world have considered or accepted the need to rethink their educational systems, with an apparent focus on increased integration of technology into teaching and learning, in an apparent effort to remain relevant to students of today, and the society of the future. However, since most prior study on this topic has been undertaken in more developed nations, the recording of the impact of technology on the young Arab population of the UAE is a significant contribution to this debate. The rapidity with which new technology have altered traditional ways of life has had far-reaching consequences for people everywhere. Managing schools and educating students in the modern era is difficult because of the disruptive nature of new and developing technologies. While IT certainly merits study on its own, it is having a far-reaching impact in every discipline. Access to a plethora of information at anytime, anywhere in the globe is made possible by advances in communication technology, testing one's capacity for information assimilation and evaluation. In an era of instantaneous information sharing and widespread use of information technology (IT) in everyday life, work, and classrooms, lifelong education may finally become a reality, one in which the rapidity with which technology evolves necessitates a continual reevaluation of the learning process itself.","PeriodicalId":256713,"journal":{"name":"2022 International Arab Conference on Information Technology (ACIT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116707428","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}