Online-Journals.org (International Association of Online Engineering)
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LPCE-Based Replacement Scheme for Enhancing Caching Performance in Named Data Networking
Get PDFThe substantial surge in users has adversely impacted the performance of the present IP-based Internet. Named data networking (NDN) emerges as a future alternative, given its distributed content caching system, where data can be cached in multiple routers and retrieved from the closest one instead of the original producer, enhancing content availability, reducing latency, and minimizing data loss. This paper introduces the less popular content eviction (LPCE) policy, a novel cache replacement scheme designed to enhance the caching performance of the conventional LFU (least frequently used) policy in NDN routers, thereby improving overall network efficiency. The proposed method subsumes LFU and FIFO (first in first out) policies and employs an additional list controlled by the LRU (least recently used) policy. Utilizing the ccnSim simulator, we conduct a comparison of LPCE’s performance with that of the LFU technique and other competing caching techniques, considering variations in several simulation parameters. Experimental results reveal that the proposed LPCE algorithm excels over others across a majority of performance metrics, such as cache hit ratio, content delivery delay, upstream hop count, network traffic, and producers’ load. Besides, the findings indicate that LPCE outperforms LFU, with an increase in cache hit ratio ranging from 1.32% to 5.75%
Enhanced Agile Methodology for Ontology Development in E-Learning Environments
Get PDFThis study explores the use of agile approaches to the creation of ontologies for e-learning, evaluating the benefits and drawbacks as well as the impact on information display. Traditional strategies conflict with the need to fulfill the ever-evolving expectations of users and adapt to the ever-changing features of e-learning environments. The challenge aims to encourage cooperation and versatility in the creation of ontologies for e-learning through the use of Agile standards. Because they make it simpler to organize relationships and statistics, ontologies are vital elements in e-mastering domain names due to the fact that they permit adaptive knowledge of structures and individualized learning experiences. Agile ontology engineering approaches are proposed as a choice for one’s problems, emphasizing flexibility and response. This study highlights the need to work together with customers and incorporate their input into the advent of ontologies. It notably emphasizes using established feedback loops and cooperation with e-learning platform companies. The sensible usefulness and effectiveness of agile methodology for ontology development (AMOD) in e-learning settings are shown through validation efforts in real-global conditions
Visual Programming for Human Detection Using FaceNet in Pocket Code
Get PDFPocket Code is a visual programming-based mobile application for creating games, animations, music, videos, and other types of applications. This paper presents the integration of face recognition capabilities into Pocket Code through a visual programming interface based on the FaceNet architecture. The FaceNet dataset is used to train and deploy a face recognition model in Pocket Code visual programming. Integration of the FaceNet algorithm into Pocket Code aims to enhance the accessibility and simplicity of facial recognition technology for students and developers. Building face recognition applications typically involves writing complex code, which can be challenging for both beginners and experienced developers. The Pocket Code visual programming blocks have simplified the process, enabling anyone to easily incorporate face detection into their projects, irrespective of their coding experience. The article discusses the implementation and performance assessment of the FaceNet algorithm in Pocket Code visual programming
Inclusive Education from the Contributions in the Virtual Forums of the Students of the Degree of Pedagogy at the University of Malaga
Get PDFThe study of inclusive education (IE) today has a large body of international research that provides insights into the changes and strategies needed to make it a reality. However, we are witnessing the fact that educational and social changes are happening very slowly. We must continue to engage and delve into the judgments and opinions of the individuals who will make it achievable. We conducted a descriptive, analytical, and qualitative study to analyze the contributions of students in the virtual forums of five subjects over three academic years (2019–2020, 2020–2021, 2021–2022) in the pedagogy degree program (1st and 4th year). The study aimed to gather evidence of students’ commitment, involvement, learning, and knowledge construction in the context of IE. On the one hand, we have found evidence that students’ perceptions of IE are influenced by barriers and facilitators that either enable or restrict the progress of IE. On the other hand, we also present evidence of the level of engagement, reflection, and dedication of the students who have taken part in the online forums of the courses, as well as the knowledge they have gained through their participation. We recognize virtual forums as a space for students to meet, reflect, and collaboratively construct knowledge. It is a valuable tool for gaining insight into how students develop their perceptions, opinions, and learning
The Effectiveness of an Interactive WhatsApp Bot on Listening Skills
Get PDFThe present paper attempted to measure the effectiveness of an interactive WhatsApp bot on the listening skills of Omani English as a Foreign Language (EFL) learners. For this purpose, 40 Omani intermediate EFL learners were divided into two groups: a control and an experimental in a higher education institution. A pretest was conducted to ensure the homogeneity of listening skills among all the participants. While both groups received instructions and exercises on listening in class, an interactive WhatsApp bot was designed for the experimental group to receive more instructions and training without time and place limitations. Later, a posttest and a delayed posttest were conducted to compare learners’ performance. The study results showed smooth progress of both groups in listening exams during the posttest and delayed posttest; however, the experimental group’s performance was significantly high. The findings of the study are efficacious and helpful for teachers and learners
Classification of Diabetic Retinopathy by Deep Learning
Get PDFDiabetic retinopathy (DR), which is a leading cause of adult blindness, primarily affects individuals with diabetes. The manual diagnosis of DR, with the assistance of an ophthalmologist, has proven to be a time-consuming and challenging process. Late detection of DR is a significant factor contributing to the progression of the disease. To address this issue, the present study utilizes deep learning (DL) and transfer learning algorithms to analyze different stages of DR and precisely detect the condition. Using a large dataset comprising approximately 60,000 images, this study employs ResNet-101, DenseNet121, InceptionResNetV2, and EfficientNetB0 DL models to automatically assess the progression of DR. Images of patients’ eyes are inputted into the models, and the DL architectures are adapted to extract relevant features from the eye images. The study’s findings demonstrate that DenseNet121 outperforms ResNet-101, InceptionResNetV2, and EfficientNetB0 in accurately classifying the five stages of DR. The accuracy of the models was 97%, 96%, 95%, and 94%, respectively. These results underscore the effectiveness of DL in achieving an accurate and comprehensive classification of retinitis pigmentosa. By enabling accurate and timely diagnosis of DR, the application of DL techniques significantly contributes to the field of ophthalmology, facilitating improved treatment decisions for patients
Investigating the Role of Augmented Reality in Supporting Collaborative Learning in Science Education: A Case Study
Get PDFThis study investigates the application of augmented reality (AR) technology to facilitate collaborative learning in science education. The study involved 30 secondary school students in Kazakhstan, who were divided into an experimental group and a control group. The experimental group utilized an AR platform to facilitate collaborative learning during their science lessons, while the control group received traditional teaching methods. The study aimed to investigate the impact of AR on students’ learning outcomes, communication and collaboration skills, and overall satisfaction with science education. The research design involved pre- and post-tests, as well as a survey of students’ perceptions of the AR experience. The results indicated that the experimental group demonstrated statistically significant improvement in their science test scores compared to the control group. Furthermore, the students in the experimental group reported a high level of engagement and satisfaction with the AR platform, along with enhanced communication and collaboration skills. The study suggests that AR technology has the potential to improve collaborative learning in science education and provides new opportunities for engaging students and enhancing their learning outcomes. The findings have significant implications for educators interested in integrating AR technology into their teaching practices as well as for researchers exploring the use of AR in education. Further research is necessary to investigate the long-term effects of AR on learning outcomes and to determine the most effective methods for incorporating AR technology into science education
Benefits of Metaverse Application in Education: A Systematic Review
Get PDFThe COVID-19 pandemic has brought about significant changes in people’s lifestyles, with the educational sector being one of the most reliant on technology to facilitate the teaching and learning process. In this literature review, a search for articles related to the metaverse in education, published in 2022 and 2023, has been conducted across six databases: Scopus, EBSCO Host, ScienceDirect, Taylor & Francis Online, IEEE Xplore, and Springer. The PRISMA methodology was used to analyze and systematize the manuscripts found. The aim of this research was to examine how integrating the metaverse into education can enhance educational accessibility and equity by enabling students to utilize virtual learning resources and opportunities. In addition, they can engage in interactions with others to learn and create interactive content during the teaching and learning process. This requires a commitment from the student because a connection between the student and the machine will be established through the use of emerging technologies. These technologies offer unique opportunities to enhance teaching quality, broaden access to education, and prepare individuals for an increasingly digital and evolving world. The analysis identified 14 emerging technologies: artificial intelligence, cloud computing, big data, Internet of Things, blockchain, augmented reality, extended reality, virtual reality, 5G, EON-XR, digital twins, 3D virtual reality, and immersive virtual reality. These technologies offer immersion (simulation of a real world in a virtual world), interactivity (interaction with different people), improvement of the educational environment (innovative presentation of content), and motivation for learning (capturing attention). When it comes to the different types of learning, there are six categories: experiential (based on experience), collaborative (involving a guide to lead the process), cooperative (involving teamwork), significant (building on existing knowledge), explicit (self-directed learning), and emotional (involving the regulation of emotions)
A Case Study of Princess Sumaya University for Technology (PSUT) Engineering Students’ Perceptions of Utilizing Simulation Software via Online Learning
Get PDFThe primary goal of this research has been to examine the perceptions related to the use of simulation software in the context of e-learning at Engineering PSUT in Jordan, which is acknowledged as one of the leading private universities in the country. The present study and a descriptive study utilized a 25-item survey given to 270 students. The research findings indicate that, according to the students’ subjective viewpoint, the effectiveness of simulation software in the context of online learning was observed to be significantly high. This observation is supported by an average score of 3.89 and a standard deviation of 0.959, indicating a relatively consistent perception among the participants. The study’s results indicate that there were no significant variations observed in terms of academic year, computer skills, student GPA or gender parameters. The research findings underscore the importance of incorporating simulation software in higher educational institutions to improve the teaching and learning experience
Optimizing Performance in Wireless Sensor Networks through a Multi-Objective Rendezvous Points Selection Algorithm
Get PDFWireless sensor networks (WSNs) play a vital role in modern research and applications due to their potential to gather data from various environments. Because sensor nodes (SNs) within WSNs have limited battery life, those in close proximity to the sink often experience rapid power depletion, leading to the emergence of hotspot issues. To address this, the concept of a mobile sink (MS) has emerged as a potential solution, effectively mitigating power usage in SNs and thereby extending the network’s overall lifespan. Furthermore, many sensor-based applications necessitate specific data collection timeframes, underscoring the necessity of effective strategies. Leveraging rendezvous points (RPs) to enhance network efficiency becomes imperative in enabling the MS to efficiently collect data from all SNs within designated time periods. A sophisticated cost function is employed to strategically determine RPs, considering multiple factors that influence the efficacy of each RP. This process culminates in the selection of RPs, optimizing for the longest path with minimal delays. Through the proposed hybrid mobile vehicle (HMV) method, compared against the prevailing MOOVor method, significant enhancements are observed in terms of sensor coverage and reduced hop count within the network