Reviewerly/exHarmony huggingface dataset:
Design and Development of an Ontology Driven Search Engine for a Mobile Cloud Asynchronous Remote Learning Platform

In the face of a global pandemic, the digital divide has become apparent especially in bandwidth-constrained countries. As contactless remote services have become increasingly necessary in the face of limited human mobility, remote learning has become the norm. To support remote learning, the research team developed a resilient asynchronous remote learning and content distribution platform as a digital library. Collaborating with corresponding stakeholders, the scope of content for the initial iterations of the platform was curated to accommodate resources for STEM educational content.Among the initial feedback for the prototype, there is a need for a consolidated means of retrieving information and resources across content channels while adhering to the prescribed Philippine K-12 curriculum. As such, the researcher proposes an implementation of an ontology-driven search engine deployed on the remote learning platform. The search engine will use an ontology encompassing the K-12 curriculum and an index of curated content across the educational content-hosting services within the digital library. This study develops a system to reliably retrieve and recommend contextually relevant results with the use of semantic web annotations and semantic information retrieval techniques to improve upon classical information retrieval.
FlowBot: A Learning-Based Co-bottleneck Flow Detector for Video Servers

Recent research has proposed that Content Delivery Networks (CDNs) can use better bandwidth allocation to improve video streaming services through congested links. Because CDNs are usually not located at the bottleneck link, shared bottleneck (co-bottleneck) detection on the video servers is necessary for joint flow shaping and the Quality of Experience (QoE) improvements. However, co-bottleneck detection is challenging in such environments due to the large number of flows, possible network topologies, and traffic patterns. Current detectors fail to balance detection accuracy, speed and overhead, and suffer performance degradation in the scale of thousands of flows on each video server. We propose FlowBot, a novel model-based passive co-bottleneck detector designed for deployment on a video server. FlowBot uses Siamese model to learn flow representations, and combines the training procedure with its clustering algorithm to continue to provide strong performance with up to thousands of flows. Our evaluations show that FlowBot can achieve consistently high accuracy (over 70% F1 with around 90% precision) in most tested scenarios, while maintaining a short detection delay of 3 s and overhead similar to the fastest benchmark algorithms.
Investigating the Effectiveness of Whitening Post-processing Methods on Modifying LLMs Representations

In contemporary natural language processing(NLP) tasks, it is common to utilize the representation of large language models(LLMs) directly in downstream applications. However, this approach is restricted to anisotropy due to the convex cone representation space of LLMs, which hinders performance evaluations across various NLP tasks. In light of this limitation, we investigate several whitening post-processing methods to modify the LLMs representation space, including PCA, ZCA, PCA-cor, ZCA-cor and Cholesky whitening methods, aiming to transform textual representation space into a decorrelated orthogonal basis space. Comprehensive experiments are conducted over 20 datasets encompassing diverse NLP tasks to evaluate the effectiveness of these methods based on models such as Bert, GPT2, and others. Our results indicate that ZCA-cor whitening is appropriate for supervised text classification, while PCA-cor whitening, after reducing dimensionality, is suitable for unsupervised semantic textual similarity. Furthermore, we perform analysis of the relationship between task evaluations and isotropy scores, indicating that whitening methods is capable of mitigating anisotropy.
A Survey on Recent Advancements in Lightweight Generative Adversarial Networks, their Applications and Datasets

Generative Adversarial Networks (GANs) have garnered significant research attention owing to their revolutionary generator-vs-discriminator architecture, making them versatile for various domains, including medical, military, and computer vision applications. Nevertheless, their computationally demanding nature during training and inference restricts their widespread adoption on mobile and edge devices. In this study, the latest advancements are explored in lightweight GAN implementations, considering their unique characteristics and diverse applications. The objective is to identify modifications that can enhance the efficiency of GAN-based models without compromising their robustness and accuracy, both for specific use-cases and in a more general context. Additionally, a discussion is presented on the availability of datasets suitable for lightweight GAN training and evaluation, as well as potential research directions for the future.
Eclipsing Security: An In-Depth Analysis of Advanced Persistent Threats

Abstract—Advanced Persistent Threats (APTs) pose a significant challenge in today's cybersecurity landscape due to their persistent, targeted, and secretive nature. In today's highly connected digital world, it's crucial to understand and tackle the risks linked to Advanced Persistent Threats (APTs). In this research paper, titled "Eclipsing Security: An In-Depth Analysis of Advanced Persistent Threats," we comprehensively explore the lifecycle, attack methodology, and practical aspects of APTs. Our focus extends to understanding how these threats gain access, the key tactics employed, and the technological aspects involved. Additionally, we also delve into how APTs differ from conventional attacks, emphasizing their unique characteristics that distinguish them from other cyber threats. Our goal is to provide valuable insights to the cybersecurity community, offering practical strategies to strengthen defenses against these elusive and enduring threats. Keywords—Advanced Persistent Threats (APTs), Cybersecurity, Lifecycle Analysis, Attack Methodology, Practical Implementation, Legal and Regulatory Frameworks, Case Studies, Mitigation and Defense Strengthening.
Teaching Turkish-Islamic Scholars in Mobile Augmented Reality Environment: Its Effect on Students' Scientific Attitudes

Science history showcases scientific thought's evolution and discoveries to students. Some topics include abstract concepts, making them challenging. Technology enhances teaching history of science, making it more effective and accessible. This study aims to examine the influence of teaching the lives of Turkish-Islamic scholars who have made significant contributions in various scientific disciplines such as astronomy, chemistry, and physics through TISAR-3D, a Mobile Augmented Reality (MAR) based learning environment, on secondary school students' scientific attitudes. A quasi-experimental method was employed in this study. This study was conducted in a public school in Elazığ, involving a total of 90 students in the 7th grade. Half of these students were assigned to the experimental group, while the other half formed the control group. The study was carried out for a duration of eight weeks on the experimental and control groups. The study lasted for eight weeks and consisted of an experiment group and a control group. The TISAR-3D application was used in the experiment group, while reading texts were used in the control group. The data obtained through the Scientific Attitude Scale were analyzed quantitatively using the SPSS 22 software package, and ANCOVA was applied. The study found that although the average scientific attitude scores of students in the experiment group, where the MAR application was used, were higher than the average scores of students in the control group, where reading texts were used, there was no statistically significant difference. Although primary textbooks are accessible to all students, insufficient coverage of Turkish-Islamic scholars and unfamiliarity with practical scholars may explain the lack of significant differences in scientific attitudes. Also, an eight-week study may not sufficiently alter students' scientific attitudes. By designing longer-term studies, a better understanding of how scientific attitudes develop and change over time can be achieved.
Cyberviolence and electronic evidence

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PENGEMBANGAN SISTEM INFORMASI PERPUSTAKAAN BERBASIS WEB DI SMK

This research aims to: (1) Develop a website-based library information system that provides easy data management for librarians to make library users more productive; (2) Develop a website-based library information system that meets ISO 9126 standards. The type of research used in this study is Research and Development (R&amp;D). Data collection techniques applied are field observation, related party interviews and documentation. This research develops a website-based library information system, which aims to make it easier for librarians to manage data and so that local library visitors get information quickly and accurately. Based on the results of the study, the value of the functionality aspect is close to number 1 with the category according to the eligibility requirements. The usability aspect value is 89% with a very good category. Assessment of efficienc aspects The average efficiency of web page load time of 2,225 seconds is up to standard. Assessment of portability aspects, information systems can be operated on all devices
Petrography, mineral chemistry and geothermobarometry of amphibolits in Gol-e-Gohar area (Sirjan), Kerman Province

Petrography, mineral chemistry and geothermobarometry of amphibolits in Gol-e-Gohar area (Sirjan), Kerman Province
A METHOD FOR EVALUATING EXPLANATIONS IN AN ARTIFICIAL INTELLIGENCE SYSTEM USING POSSIBILITY THEORY

The subject of the research is the process of generating explanations for the decision of an artificial intelligence system. Explanations are used to help the user understand the process of reaching the result and to be able to use an intelligent information system more effectively to make practical decisions for him or her. The purpose of this paper is to develop a method for evaluating explanations taking into account differences in input data and the corresponding decision of an artificial intelligence system. The solution of this problem makes it possible to evaluate the relevance of the explanation for the internal decision-making mechanism in an intelligent information system, regardless of the user's level of knowledge about the peculiarities of making and using such a decision. To achieve this goal, the following tasks are solved: structuring the evaluation of explanations depending on their level of detail, taking into account their compliance with the decision-making process in an intelligent system and the level of perception of the user of such a system; developing a method for evaluating explanations based on their compliance with the decision-making process in an intelligent system. Conclusions. The article structures the evaluation of explanations according to their level of detail. The levels of associative dependencies, precedents, causal dependencies and interactive dependencies are identified, which determine different levels of detail of explanations. It is shown that the associative and causal levels of detail of explanations can be assessed using numerical, probabilistic, or possibilistic indicators. The precedent and interactive levels require a subjective assessment based on a survey of users of the artificial intelligence system. The article develops a method for the possible assessment of the relevance of explanations for the decision-making process in an intelligent system, taking into account the dependencies between the input data and the decision of the intelligent system. The method includes the stages of assessing the sensitivity, correctness and complexity of the explanation based on a comparison of the values and quantity of the input data used in the explanation. The method makes it possible to comprehensively evaluate the explanation in terms of resistance to insignificant changes in the input data, relevance of the explanation to the result obtained, and complexity of the explanation calculation. In terms of practical application, the method makes it possible to minimize the number of input variables for the explanation while satisfying the sensitivity constraint of the explanation, which creates conditions for more efficient formation of the interpretation based on the use of a subset of key input variables that have a significant impact on the decision obtained by the intelligent system.
Mineralogy, geochemistry, and fluid inclusion of the Balestan Iron deposit, Southeast of Urmia, NW Iran

Mineralogy, geochemistry, and fluid inclusion of the Balestan Iron deposit, Southeast of Urmia, NW Iran
Neural Network and Chatbot “Valera” for Advanced Specialist Training

Purpose: To address the issue of linking education and industry, through the model of the quality of engineering activities in additional professional education for engineers in the preparation of highly qualified personnel. To demonstrate the feasibility of using a neural network to develop methodological foundations for the preparation of highly qualified personnel. Methods: A model for the learning process has been proposed, utilizing a neural network and the chatbot “Valera” for the preparation of highly qualified personnel. Results: An example of successful experience in applying the electronic educational and methodological complex “Competent Metrologist” and its methodological foundations in the system of additional professional education for engineers and the preparation of highly qualified personnel is provided. Practical significance: The necessity of using a neural network in the process of personnel training is demonstrated. Positive experience in implementing ideas and approaches to creating a neural network for the chatbot “Valera” and its methodological foundations in the system of additional professional education for engineers has been realized in the electronic educational and methodological complex “Competent Metrologist”. The proposed approaches to education can be recommended for practical implementation.
Qualities, personal characteristics, and responsibilities of qualified teachers in the 21st century

Education is critical for all elements of a person’s life. Educational actors mainly involve teachers, students, school principals, and administration staff. Nevertheless, teachers are considered the most essential actors. Without teachers, the process of learning and teaching will surely come to a halt. It is not difficult to be a teacher, but it is far more difficult to become a competent one because there are numerous duties for a qualified teacher to perform. This article argues that qualified teachers in the 21st century should have various value-added qualities and responsibilities. The article discusses the essential requirements for qualified teachers in the 21st century and offers recommendations for teachers to equip themselves with knowledge, skills, and qualities required to keep pace with the fast-changing world.
FAAQA-QAD: A Frequently Asked Arabic Question Answering Dataset for Diseases Detection System

Domain-specific question-answering (QA) systems are a specialized field in Natural Language Processing. Their objective is to generate answers to questions within a specific domain, such as healthcare. The existing Arabic datasets are often characterized by their low quality, resulting from inadequate preprocessing or inaccurate annotation because that translated from another language.
MalAware: A Tool for Safe Internet Browsing

In today’s digital age, ensuring user security while browsing the web is of paramount importance. However, the convenience and interconnectedness of the internet also expose users to various security risks. The increasing prevalence of phishing attacks, malware downloads, and insecure connections has highlighted the urgent need for effective solutions that prioritize user security during web browsing. In response to this pressing concern, our team has developed MalAware, a powerful web browser extension designed to enhance user security by providing real-time website analysis and proactive threat detection. This research paper introduces MalAware, a web browser extension designed to enhance user security by providing real-time website analysis. Acting as a vigilant guardian against potential threats such as phishing attacks, malware downloads, and insecure connections, MalAware employs sophisticated algorithms and scanning techniques to proactively detect and warn users of any suspicious behaviors or elements encountered during web browsing.
Impact Analysis of My Learning Link Information System Quality Towards Employee Performance at Schneider Electric Manufacturing Batam Company

The aim of this research is discovering My LearningLink information system quality’s impact towards employee performance at Schneider Electric Manufacturing Batam Company. The research applies quantitative descriptive approach along with multiple linear regression analysis technique. Questionnaire v
Introduction to Session-Based Recommender Systems

Due to the massive growth of data in recent years, recommender systems have become essential tools to improve people’s lives. However, access to users’ profiles and their long-term interests are crucial challenges of these systems. A session-based recommender system (SBRS) was developed to solve these problems and received much attention from the research community. In this chapter of the book, after presenting an overview of the definitions and techniques of traditional recommender systems, we focus on the fundamental concepts, descriptions, challenges, and approaches of SBRS and clarify the differences between SBRS and SRS (sequential recommender system) from various aspects.
DIGITAL TRANSFORMATION OF PROFESSIONAL FUTURE PHYSICAL EDUCATION TEACHER TRAINING IN THE CONDITIONS OF BLENDED LEARNING

The article defines and theoretically substantiates the directions of digital transformation of the professional future teacher of Physical Education training in the conditions of blended learning as a pattern of informatization in the field of higher education. It is noted that the digital transformation of higher education establishments requires new target orientations, organizational models, and innovative digital technologies to improve the quality and accessibility of education. It is emphasized that digitalization contributes to the emergence of innovative forms, such as blended learning, while the spread of blended learning leads to digital transformations in the system of professional training of future Physical Education teachers at the level of goals (formation of digital competence among students, positive motivation for continuous professional self-development in conditions of dynamic changes); content (introduction of mandatory and optional educational components to increase digital literacy, inclusion in work programs of topics related to the use of “digital health” devices, electronic educational resources, cloud technologies, virtual and augmented reality tools); forms, methods and ways (rational combination of face-to-face and remote interaction, traditional approaches with innovative digital tools; use of personal digital devices, use of mobile, cloud, immersive technologies) and expected results (formation of the graduate’s ability to creatively and effectively use information and communication technologies in professional activities, self-education and self-development; readiness to implement innovations in professional activity in conditions of digital transformation of physical education).
THE PROJECT OF THE UKRAINIAN CULTURAL FOUNDATION “UKRAINIAN LITERATURE IN COMICS”: IDEA, STRATEGIC GOALS, RESULTS

The article presents the results of the “Ukrainian Literature in Comics” project created with the support of the Ukrainian Cultural Foundation. The authors of the project (project manager Nadiia Hrachova, author of scripts for the online catalog Olha Khodatska, and project creative designer Olena Cherkun) created a cultural-artistic product – an online catalog in Ukrainian and English versions, which highlights the plot of the Ukrainian historical era with the help of graphic visualization. &#x0D; The results of the project “Ukrainian Literature in Comics,” which was done during two stages (2022 and 2023), represent a new interactive study of the Ukrainian written heritage of different periods, considering modern socio-cultural and ideological challenges. Among such challenges, the current one is the development of the motivation of the younger generation to read Ukrainian fiction, the development of the interest of children and adults in reading books by Ukrainian authors as a national treasure, popularization of the Ukrainian literary heritage as a factor of the national security, the creation of reliable interactive content for teachers-philologists, students, their parents, actually for all Ukrainians living in Ukraine and abroad. The result of the project is the creation of a cultural and artistic product for those who are interested in the Ukrainian language, literature, and culture. Furthermore, it will be included in the educational process to reformat the cultural narratives and meanings of Ukrainian society nowadays in Ukraine and abroad, where children-migrants from the temporarily occupied territories study. In the long term, this project is going to have a positive cultural and educational impact on strengthening the moral and spiritual state of Ukrainians, on the development of an individual who is able to care for the spiritual and cultural revival of the country in the post-war period, which will contribute to the unification of the world community against Russian military and cultural expansion as well.
THE IMPLEMENTATION OF HRYHORII LEVCHENKO’S CREATIVE WORK IN FUTURE TEACHERS’ NON-FORMAL EDUCATION

The article is devoted to the significance of the creative work of the outstanding Ukrainian conductor, composer, arranger, and teacher Hryhorii Levchenko in the process of its implementation in the field of future teachers’ non-formal education. It is emphasized that non-formal, in particular, art education is a source of improvement of general and professional competencies of future specialists obtained in the process of formal education. The prominent teacher's life and creative activity motivates gifted youth to realize their artistic and pedagogical potential, and to develop their own artistic talents.&#x0D; Acquaintance with the artist’s life and professional path proves exceptional dedication to the chosen profession and is an example to follow.&#x0D; An important aspect of scientific, pedagogical, and artistic activity is the focus on the realization of the national, aesthetic, educational, and educational potential of the Ukrainian folk song, which has become dominant in the artist's work. It can be traced in his scientific works, research, compositional work, and activities as artistic director, and conductor of the Ukrainian folk choir “Kalyna” of Poltava V. G. Korolenko National Pedagogical University.&#x0D; H. Levchenko’s long-term systematic work on the organization and implementation of informal art education in a pedagogical institution of higher education contributes to the preparation of future teachers for educational work in secondary general and extracurricular education institutions.