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                <text>Education is a crucial factor in ensuring sustainable progress, In particular, for countries with growing economies. Due to resource virtualization, Cloud computing has both the Internet and complex scalability. Both public and private learning institutions should take advantage of the potential benefit of cloud infrastructure to ensure high-quality service regardless of the minimum resources available. Because of its numerous advantages, cloud computing is taking center stage in academia. This research will seek to establish the benefits associated with the use of cloud computing in education. Cloud technology solutions ensure research and development as well as teaching, and its more sustainable and efficient, thereby having a positive impact on the quality of teaching and learning in educational institutions. The goal of this research is to identify the benefits of cloud computing usage in education. Cloud technology solutions make research and development as well as teaching more competitive and effective, thereby having a positive impact on the quality of education.</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 24 (2021); pp. 191-200</text>
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                <text>Considering that application’s security is an important aspect, especially nowadays with the increase in technology and the number of fraudsters. It should be noted that determining the security of an application is a difficult task, especially since most fraudsters have become skilled and professional at manipulating people and stealing their sensitive data. Therefore, we pay attention to spot insecure apps by analyzing user feedback on Google Play platform using sentiment analysis. As it is known, user reviews reflect their experiments and experiences in addition to their feelings and satisfaction with the application. But unfortunately, not all of these reviews are real, fake reviews do not reflect the sincerity of feelings, so we have been keen in our work to filter the reviews and deliver accurate and correct results. This tool is useful for both users wanting to install an android app and for developers interested in app’s optimization.</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 23 (2021); pp. 178-185</text>
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                <text>1865-7923</text>
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                <text>Considering that application security is an important aspect, especially nowadays with the increase in technology and the number of fraudsters. It should be noted that determining the security of an application is a difficult task, especially since most fraudsters have become skilled and professional at manipulating people and stealing their sensitive data. Therefore, we pay attention to trying to spot insecurity apps, by analyzing user feedback on the Google Play platform and using sentiment analysis to determine the apps level of security. As it is known, user reviews reflect their experiments and experiences in addition to their feelings and satisfaction with the application or not. But unfortunately, not all of these reviews are real, and as is known, the fake reviews do not reflect the sincerity of feelings, so we have been keen in our work to filter the reviews to be the result is accurate and correct. This study is useful for both users wanting to install android apps and for developers interested in app optimization.</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 24 (2021); pp. 123-133</text>
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                <text>Android Apps Security Assessment using Sentiment Analysis Techniques: Comparative Study</text>
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                <text>Hammoudeh, Mohammad Ali A.</text>
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                <text>Nowadays, technology has an important role of our life, including smart devices, social media due to the importance of security and web for interaction so it has become targeted it by cybercriminal. The growing threat of cybersecurity has prompted the kingdom to pay more attention to its national cybersecurity strategy as the state embarks on a Vision 2030 plan, which aims to diversify the economy and create new jobs. Therefore, Web Applications are always having security threats, which considered as a big problem. Several steps introduced successful analysis of vulnerabilities in web applications. There are no efficient and easy to use tools for the security assessment of such applications. This paves the way for hackers to easily attack. In this paper, we recommend an efficient method to assess the vulnerability using Python, which can used to conduct Vulnerability Assessment on web applications. This work will be useful for organizations and programmers to keep their information and applications more secure and viable for usage in sensitive environments.</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 23 (2021); pp. 120-135</text>
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                <text>1865-7923</text>
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                <text>The Study on Assessment of Security Web Applications</text>
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                <text>Almuteer, Arjwan H.</text>
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                <text>Credit card is getting increasingly more famous in budgetary exchanges, simultaneously frauds are likewise expanding. Customary techniques use rule-based master frameworks to identify fraud practices, ignoring assorted circumstances, the outrageous lopsidedness of positive and negative examples. In this paper, we propose a CNN-based fraud detection system, to catch the natural examples of fraud practices gained from named information. Bountiful exchange information is spoken to by an element lattice, on which a convolutional neural organization is applied to recognize a bunch of idle examples for each example. Trials on true monstrous exchanges of a significant business bank show its boss presentation contrasted and some best-in-class strategies. The aim of this paper is to merge between Convolutional Neural Network (CNN), Long-Short Term Memory (LSTM), and Auto-encoder (AE) to increase credit card fraud detection and enhance the performance of the previous models. By using these four models; CNN, AE, LSTM, and AE&amp;amp;LSTM. each of these models is trained by different parameter values highest accuracy has been achieved where the AE model has accuracy =0.99, the CNN model has accuracy =0.85, the accuracy of the LSTM model is 0.85, and finally, the AE&amp;amp;LSTM model obtained an accuracy of 0.32 by 400 epoch. It is concluded that the AE classifies the best result between these models.</text>
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            <description>Information about rights held in and over the resource</description>
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              <elementText elementTextId="46164">
                <text>Copyright (c) 2021 Arjwan H. Almuteer, Asma A. Aloufi, Wurud O. Alrashidi, Jowharah F. Alshobaili, Dina M. Ibrahim</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 24 (2021); pp. 108-122</text>
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                <text>1865-7923</text>
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                <text>Detecting Credit Card Fraud using Machine Learning</text>
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                <text>Internal Visualization challenges concerning sub-microscopic particles in chemistry often result in some difficulties in learning the change of state of matter. Therefore, this study aims at developing an augmented reality ProCAR module that utilizes a project-based learning approach to facilitate learning changes of matter. This study employs ADDIE (Analysis, Design, Development, Implementation and Evaluation) instructional design model. The quality of the module was evaluated by a group of 5 Chemistry teacher-educator experts of Universiti Teknologi Malaysia to identify the suitability of the module. Inter-rater reliability (IRR) percentages were determined and the feedback was analyzed based on thematic analysis. The result shows that 100% of its learning objectives, Content, Usability, and Assessment and 75% of its performances were good and reliable all having IRR value 75% and above. Such revealed that AR Module is potentially effective for the teaching phase change to Secondary school students.  Recommendations for future studies were highlighted</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/27343/10421</text>
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                <text>Copyright (c) 2021 Mangai Solomon Mahanan, Nor Hasniza Ibrahim, Johari Surif, Chee Ken Nee</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 23 (2021); pp. 72-88</text>
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                <text>1865-7923</text>
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                <text>AR Module for Learning Changes of Matter in Chemistry</text>
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                <text>Badawood, Ashraf</text>
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                <text>AlBadri, Hamad</text>
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                <text>Technological enhancements as well as the demand of students to access learning information on time and quickly has resulted to the development of e-learning across the world. Mobile learning has been adopted by most learning institution as a mobile technology that allows learners to access learning materials and share information among themselves and respective educators easily and quickly. This article discusses the intention of users in learning environment adopting m-learning, their perceptions as well as factors that hinder implementation of m-learning in the gulf region. Effective mobile technology adoption also enhances knowledge management through mobile applications that allow information capture, storage, retrieval and sharing.  This study uses systematic literature review to collect information from post 2017 studies previous conducted by other researchers. Articles were searched through highly ranked databases from which 657 journals were identified. After the screening and eligibility assessment, 24 journals were retrieved. The back and forward search retrieved 4 more journals bringing the total to 28 journals that were included in the study. Based on this information, a conceptual model is developed to help assess the m-learning perceptions, adoption intentions and factors influencing its adoption among learning institutions in the gulf region. This model is built based on the Theory of Planned Behavior and Unified Theory of Acceptance and Use of Technology. Based on the developed model, main constructs such as performance expectancy, effort expectancy and social influence are greatly impacted by other factors like learner’s creativity and mobility.</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/27335</text>
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                <text>10.3991/ijim.v15i24.27335</text>
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                <text>International Association of Online Engineering (IAOE), Vienna, Austria</text>
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                <text>https://online-journals.org/index.php/i-jim/article/view/27335/10483</text>
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              <elementText elementTextId="46113">
                <text>Copyright (c) 2021 Ashraf Badawood, Hamad AlBadri</text>
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                <text>https://creativecommons.org/licenses/by/4.0</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 24 (2021); pp. 49-60</text>
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              <elementText elementTextId="46116">
                <text>1865-7923</text>
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            <name>Subject</name>
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                <text>M-learning</text>
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                <text>Technology Based Model of a Mobile Knowledge as a Service to Facilitate Education Community</text>
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                <text>Information Security is the foremost concern for IoT (Internet of things) devices and applications. Since the advent of IoT, its applications and devices have experienced an exponential increase in numerous applications which are utilized. Nowadays we people are becoming smart because we started using smart devices like a smartwatch, smart TV, smart home appliances. These devices are part of the IoT devices. The IoT device differs widely in capacity storage, size, computational power, and supply of energy. With the rapid increase of IoT devices in different IoT fields, information security, and privacy are not addressed well. Most IoT devices having constraints in computational and operational capabilities are a threat to security and privacy, also prone to cyber-attacks. This study presents a CIA triad-based information security implementation for the four-layer architecture of the IoT devices. An overview of layer-wise threats to the IoT devices and finally suggest CIA triad-based security techniques for securing the IoT devices.</text>
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                <text>Copyright (c) 2021 Mana Saleh Al Reshan</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 24 (2021); pp. 61-76</text>
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                <text>1865-7923</text>
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                <text>IoT-based Application of Information Security Triad</text>
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                  <text>International Journal of Interactive Mobile Technologies (iJIM)</text>
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                <text>Tenh, Hock Kuan</text>
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                <text>Shiratuddin, Norshuhada</text>
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                <text>Adaptive augmented reality (AAR) is the latest concept of the augmented reality that responds and adapts to a real-time context and thecharacteristics of the users. This concept is said to provide adaptation of 3Daugmented reality, better engagement and more emotional experience to theusers. In AAR, the information is provided to the users through interaction tracking and sensor on the device. However, this technology is still in itsinfancy. Therefore, a study to explore positive ways of providing relevantinformation that can enhance user experience is urgently required. Theobjective of this paper is to identify the components of an AAR model forheritage mobile application. It is hypothesized that such model would enhance user experience and provide better engagement. Consequently, models from past studies on Augmented Reality, UX Design and storytelling are reviewed. Findings indicate that personalization and emotion are among the important components. Inclusion of these components seems to allow users to be more engaged and inspired to learn about the cultural heritage, hence enhances user experience.</text>
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                <text>Copyright (c) 2021 HOCK KUAN TENH, Norshuhada Shiratuddin</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 02 (2022); pp. 17-27</text>
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                <text>1865-7923</text>
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                <text>mobile augmented reality</text>
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                <text>Components of Adaptive Augmented Reality Model for Heritage Mobile Application</text>
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                <text>Alebeisat, Farhan</text>
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                <text>Altarawneh, Haroon</text>
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                <text>Alhalhouli, Zaid T.</text>
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                <text>Qatawneh, Ali</text>
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                <text>Almahasne, Mohmmad</text>
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                <text>Over the last few years, particularly during the COVID-19 pandemic, the stage of education has clearly shifted from face-to-face instruction to e-learning. Human-Computer Interaction (HCI) paved the way for developing alternative and advanced methods for implementing the concept of e-learning by identifying what aids educational applications and platforms in visualizing content and thus providing students and their education with easy access in their homes during quarantine and providing them with easy access to educational materials throughout time. Students' impressions of the impact of the human-computer interaction process on the quality of e-learning at Tafila Technical University are discussed in this study. Within one year and four months of the COVID-19 quarantine, students got sufficient experience to apply e-learning. Students responded to a questionnaire that contained closed-ended questions. The responses were analyzed to ascertain the influence of the continual human-computer interaction process. The study's primary objective was to determine the beneficial effect of this contact on the quality of e-learning. Despite their academic and academic performance being greatly impacted by the COVID-19 epidemic, students' positive attitudes toward e-learning have been extremely enthusiastic.</text>
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                <text>Copyright (c) 2022 Farhan Alebeisat</text>
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                <text>International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 04 (2022); pp. 58-69</text>
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                <text>1865-7923</text>
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                <text>E – learning</text>
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                <text>The Impact of Human and Computer Interaction on eLearning Quality</text>
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