Online-Journals.org (International Association of Online Engineering)
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Information Technology Students' Perceptions Toward Using Virtual Reality Technology for Educational Purposes
Get PDFThis study aims to examine information technology students' perceptions toward the use of virtual reality technology, their behavioral intention to use such technology for educational purposes, and the relationship between their perceptions toward the use of virtual reality technology and their behavioral intention to use virtual reality technology for educational purposes. The study used a descriptive and cross-sectional survey research design. The data collection tool was developed based on the second Unified Theory of Acceptance and Use of Technology UTAUT2 framework. Data were collected from participants using an online questionnaire. The number of participants was 147 undergraduate information technology students. The results showed that the participants had variations in their perceptions of virtual reality technology. The results showed that participants had positive perceptions of hedonic motivation and effort expectancy concerning the use of virtual reality. However, the students had close to neutral perceptions of performance expectancy, social influence, facilitating conditions, price value, and habits concerning the use of virtual reality. Furthermore, the results showed that the students had a positive behavioral intention to use virtual reality for educational purposes. Part of students' positive behavioral intention to use virtual reality for educational purposes can be ascribed to their perceptions of effort expectancy, performance expectancy, social influence, hedonic motivation, price value, facilitating conditions, and habits concerning the use of virtual reality. Students' perceptions of performance expectancy concerning virtual reality had the greatest effect on their behavioral intention to use virtual reality for educational purposes. Based on the findings, a set of recommendations was provided
Joint Microservices Caching and Task Offloading Framework in VEC Based on Deep Reinforcement Learning
Get PDFVehicle capacities and intelligence are rapidly increasing, which will likely support a wide range of novel and interesting applications. However, these resources are not effectively utilized. To take advantage of these invaluable capabilities in smart vehicles, they can be used in the cloud environment and can be operated through distributed computing platforms in order to benefit from their combined processing power, storage capacity, and memory resources. Vehicular edge computing (VEC) is a promising field that allows computing tasks to be transferred from cloud servers to vehicular edge servers for processing, allowing data and apps to be placed closer to vehicles (users).
This paper proposes a framework that combines two modules, the first one for managing microservice caching in vehicle-mounted edge networks, such that we use cluster-based caching technique to deal with the case where similar microservices are frequently requested in VEC. The second one integrates the computational capabilities of the edge servers with the capabilities of vehicles to perform task offloading in a collaborative manner.
Our solution addresses the limitations of existing edge computing platforms during peak times by combining microservices caching with computational task offloading to improve overall system performance.
 
Designing of a Flipped STEM Classroom Engineering-Based Module: Fuzzy Delphi Approach
Get PDFAbstract— The National Innovation System found that research in Jordan did not contribute sufficiently to economic growth and to solving real-world challenges, particularly those related to STEM (science, technology, engineering, and mathematics). This was attributed to several reasons, including the inability of educational curricula to guide students in dealing with real-world issues. In addition, education in Jordan is content-intensive and primary school children lack the time to build functional competencies such as problem-solving. Therefore, it was necessary to adopt an approach allowing students to learn the theoretical content on their own while allocating class time to practice problem-solving activities with their teacher and peers. To address this gap, this study aimed at designing an engineering-based module for a flipped STEM classroom to aid grade seven students in developing their problem-solving abilities based on Merrill’s first principles of instruction as an instructional design model. To generate the module components and aspects, semi-structured interviews were performed with 9 subject matter experts. Then, 29 experts responded and offered a consensus on what was reached in the previous interview. A total of 36 items were discussed by the expert panel using the Likert 7-point scale in the fuzzy Delphi approach. The five-module aspects namely; the form of STEM integration, the assessment, the resources, and the pre-class and in-class instructional activities, were determined. This research will usher in a new era for the Ministry of Education. in planning and teaching integrated STEM disciplines in line with Jordan’s vision 2025 to equip all learners with 21st-century skills such as problem-solving to enhance education standards to international levels
A Determinant of Optimal and Inhibited Mobile Language Learning Activity: Quiz Level Length
Get PDFLearner analytic driven research concerned with mobile app learner survivability. An app was developed to indicate productiveness of quiz app usage for global mobile assisted language learning (MALL). The research focused on inhibiting and optimizing effects of level length on total questions answered. How many questions per level leads to the highest total unique questions being answered? The research focused on nine-day cohort timeframes and included three phases: a small-scale pilot study to establish parameters, an exploratory stage undertaken within the parameters and finally the use of a quadratic regression predictive model. The null hypothesis (H0) was rejected. A one-way analysis of variance found a statistically significant difference in the mean productivity of the lengths. Results of a Tukey post hoc test (p < .05) suggests question sets with less than eight questions, or more than 15 questions, appear to inhibit MALL autonomous learning. Optimal level question sets appear to be between lengths 8-14. The results visually encapsulated by a quadratic regression model broadly support H1 and H2. Set 12 is the statistically most significant optimal load. Gains of up to 107% are reported for switching from suboptimal to optimal approaches
Video Copyright Protection
Get PDFIllegal distribution of digital data is a common danger in the film industry, especially with the rapid spread of the Internet, where it is now possible to easily distribute pirated copies of digital video on a global scale. The Watermarking system inserts invisible signs to the video content without changing the content itself. The aim of this paper is to build an invisible video watermarking system with high imperceptibility. Firstly, the watermark is confused by using the Arnold transform and then dividing into equal, non-overlapping blocks. Each block is then embedded in a specific frame using the Discrete Wavelet Transform (DWT), where the HL band is used for this purpose. Regarding the method of selecting the host frames, the chaotic map (tent map) was used to choose a number of frames which are greater or equal to the number of blocks of the watermark. The host frame selection method makes the discovery of the watermark information by illegal means very complicated. The experimental results show that the proposed method can produce excellent transparency with robustness against some attacks where the average_ PSNR reaches to 72.806
Online Training in Music Education Based on a Signature Pedagogy
Get PDFThe paper presents the investigation of the effectiveness of the online training for future music teachers based on the signature pedagogy at the university. The literature review let us stated the gap in researches which cover online learning strategies for training music teachers in the professional preparation process. Due to the shifting of the educational process to the online way in the emergency situation COVID19 pandemic, the relevance of pedagogical tools for pre-paring of future specialists online extremely increased. The comparative analysis of music education standards in different countries let us determine the set of teachers` professional activities in general school music class. The main contribution is the design of a small private online course based on the signature pedagogy which delivered the set of specific pedagogical tools for training music teacher professional skills online. This course was implemented at [removed for blinded review]. The experimental work was based on the teacher` assessment of online tasks, in which students demonstrated the music teacher` professional skills. The results were proved by the statistical methods of median, standard deviation and Pearson's correlation. The obtained results proved the effectiveness of the online training based on the signature pedagogy which provided learning activities according to the specific features of music teacher professional practice
A Cloud Based Interactive Setting for Medical Simulation
Get PDFThe process of learning by doing within an online interactive setting – accessible by a single and simple click of the mouse, without downloads of software or other technical procedures - is highly effective and leaves learners with a memorable experience, if the experience is multiplayer, highly cooperative, and glasses-free. That is the case with the e-REAL Online experience introduced in this article, which revolves around a case of multiple injuries acting in an alpine environment. Within this scenario, the learners are challenged to recognize a situation requiring rapid intervention, communication, knowledge sharing, decision-making, and management of an unforeseen event—while taking into consideration critical contextual factors such as a lack of time, scarcity of resources and tools, and a multitude of additional impactful factors (weather conditions, broadband availability, etc.).
The entire experience is based on the visual exploration of an alpine environment and on a dialogue with the patient, which is an avatar performing as a female that was injured during a hiking activity performed alone and was found by chance by an interprofessional rescue team
An Integrated Grasshopper Optimization Algorithm with Artificial Neural Network for Trusted Nodes Classification Problem
Get PDFWireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classification approach, hence strengthening the safety of such networks. Feature extraction process is done by using Linear Regression-Based Principal Component Analysis (LR-PCA). The test results demonstrated that the proposed IGO-ANN method attains the greatest performance in terms of accuracy, end to end delay and packet delivery ratio regarding trusted WBAN nodes classification than certain existing methods
Comparison YOLOv5 Family for Human Crowd Detection
Get PDFRecent years have seen widespread application of crowd counting and detection technology in areas as varied as urban preventing crime, station crowd statistics, and people flow studies. However, getting accurate placements and improving audience counting performance in dense scenes still has challenges, and it pays to devote a lot of effort to it. In this paper, crowd counting models are proposed based on the YOLOv5 algorithm, and four YOLOv5 models (YOLOv5l, YOLOv5m, YOLOv5s, YOLOv5x) were built for the purpose of comparing the models and increasing the accuracy of crowd identification as each model contains certain characteristics such as Filter sizes. Each model was trained on a human dataset (indoor and outdoor) for the purpose of comparing the results of each model and showing which model reaches higher accuracy in detecting people. Through this study and practical experiments conducted on each model, it was found that the best model is YOLOv5x, and YOLOv5l, where the accuracy of detecting humans reached more than 96%, while YOLOv5s reached more than 92%, and YOLOv5m reached the lowest accuracy, which is 91%
Design and Implementation of Experiment Online Teaching Platform for Oil and Gas Storage and Transportation Based on WeChat Mini-Program
Get PDFWith the emergence of “Internet + higher education,” online teaching platforms have become increasingly important, particularly for practical teaching courses. The study of oil and gas storage and transportation is a fundamental and essential course for students in this major. In light of the issues related to limited space, lack of openness, and low student enthusiasm for traditional experimental teaching methods, an online experimental teaching platform for oil and gas storage and transportation was developed. This platform is based on the WeChat mini-program and follows the principles of cross-platform computability, user friendliness, and low investment. Its aim is to explore effective learning models for mobile devices. This study compares and analyzes the differences in classroom effects before and after the implementation of the WeChat learning platform. The study examines the design of the platform, teaching session cases, and the analysis of application effects. The research utilizes questionnaires and statistical data as research methods. The results indicate that the WeChat online teaching platform has significantly improved the enthusiasm and learning outcomes of students in the independent learning of experimental courses. It has received high recognition from both teachers and students and has greatly enhanced the quality of teaching. This has considerable potential for further promotion