Reviewerly/exHarmony huggingface dataset:
Mastering Principles of Risk Management, Insurance, and Takaful: A Comprehensive UiTM Massive Open Online Course

The need to integrate technology into the education system has always been on the rise in the 21st century. The emergence of Coronavirus 2019 (COVID-19) has further increased the need for web-based education since educational institutions have to temporarily close to curb the spread of the virus. Universiti Teknologi MARA (UiTM) has also chosen to migrate its face-to-face classroom teaching and learning approach to open and distance learning (ODL). UFUTURE is a platform developed by UiTM for lecturers and students to have online learning through the development of massive online open courses (MOOCs) which can also be accessed by anyone who wants to self-learning. Principles of Risk Management, Insurance and Takaful course has also been transformed into MOOC to assist anyone especially UiTM students in learning this course remotely. This paper will discuss the design of ASC173 in the UFUTURE platform that implements various types of learning materials and evaluate the usability of the platform using the System Usability Scale (SUS) test among the students who took this course in the semester March 2022. The obtained SUS score 92/100 indicated that respondents were satisfied with the form of the proposed MOOC and it is acceptable to be implemented for anyone who wants to learn this course.
Study of the assessment system for the achievements of the planned subject results of mastering the educational subject "Biology"

This study presents an analysis of the methodological recommendations of L.A. Parshutina and A.V. Ovchinnikov "Assessment system for the achievements of the planned subject results of mastering the educational subject "Biology". The reviewed publication describes various types and forms of assessment, within the framework of which an assessment system for subject results in Biology is designed. The authors studied the most relevant approaches in the assessment system that meet the requirements of the updated Federal State Educational Standards.
Machine learning for detecting substance use behaviors from wearable biosensor data streams: A survey and outlook for 5G/6G connectivity

Wearable biosensors allow continuous monitoring of physiological and behavioral signals associated with substance use disorders. Nevertheless, generating clinically meaningful insights requires novel machine learning techniques capable of handling high-velocity, noisy data streams. This paper surveys existing algorithms proposed for detecting substance use from wearables, highlighting key trends such as deep learning approaches and personalization. Ongoing challenges related to ground truth labeling, model interpretation, and computational efficiency are also discussed. The advent of 5G/6G networks is poised to transform this field by facilitating coordinated sensing across multiple wearables and enabling advanced on-device analytics. This work consolidates progress in wearable analytics for substance use monitoring and identifies open problems to steer future research. An experimental evaluation using wearable data from 20 participants demonstrates that a personalized CNN model achieved the best performance in detecting cannabis use events, boasting 89% precision, 83% recall, and a 0.94 AUROC score, outperforming classical machine learning approaches such as random forests.
PERAN MEDIA PEMBELAJARAN DALAM MENINGKATKAN MINAT BELAJAR SISWA SEKOLAH DASAR

When children enter primary education, the role of learning media in increasing interest in learning is very popular in education. There are many technologies that have been developed in the present and implemented for the first time in the world of education. Giving rewards in the use of media is also very good in the learning process. This allows the use of media to adapt to the learning on that day so as to be able to answer material problems from the media used. This makes it one of the few developed countries in the world that already uses learning media. Which, able to improve student learning in elementary school. This allows teachers to make better learning media and be able to give the best to students and show their work and creativity in making these learning media. In addition, the media does not cause boredom when learning in class and is able to increase motivation in the learning process.
EDUCATIONAL EVENT AS A MEANS OF CHANGING THE PERSONAL POTENTIAL OF PEDAGOGICAL UNIVERSITY STUDENTS

The priority task of modern education is the development of the student’s ability to self-regulate, create and live his own life, which is the essence of personal potential. One of the promising areas is event-based pedagogy (Event-based learning). This approach has shown effectiveness in the pedagogical process and aroused great interest in many countries. The paper presents the development and implementation of an educational event that helps to increase the student’s personal potential, and provides recommendations for creating such an event.
DEMO EXAMINATION IN PEDAGOGICAL UNIVERSITY: FIRST RESULTS

The article presents some experience and outcomes of introducing a demo examination into a pedagogical establishment of higher education (Altai State Pedagogical University). In order to provide theoretical generalization there has been realized a complex integrated review of practical evaluation and implementation of a demo exam as an alternative option during midterm and end-of-term (final) academic assessment of the students getting instruction in pedagogical universities.
The Security of Blockchain-based Electronic Health Record: A Systematic Review

The healthcare industry makes rampant strides in sharing electronic health records with upgraded efficiency and delivery. Electronic health records comprise personal and sensitive information of patients that are confidential. The current security mechanism in cloud computing to store and share electronic health records results in data breaches. In the recent era, blockchain is introduced in storing and accessing electronic health records. Blockchain is utilized for numerous applications in the healthcare industry, such as remote patient tracking, biomedical research, collaborative decision making and patient-centric data sharing with multiple healthcare providers. In all circumstances, blockchain guarantees immutability, data privacy, data integrity, transparency, interoperability, and user privacy that are strictly required to access electronic health records. This review paper provides a systematic study of the security of blockchain-based electronic health records. Moreover, based on thematic content analysis of various research literature, this paper provides open challenges in the blockchain-based electronic health record.
Comparative Study of Learning Motivation for Boarding House Students and Students Who Live with Their Parents in Civics Study Program Students at the University of Riau

This research is motivated by the difference in motivation of boarding house students and students who live with their parents, where it is known that students who live with their parents are more punctual in coming to class and submitting assignments and are more ready to study than students who live in boarding houses, but during student learning hours. boarders are more active in asking questions than students who live with their parents. The aim of this research is to find out whether there is a comparison of learning motivation between boarding house students and students who live with their parents among students at the PPKn FKIP Study Program, Riau University. This research was conducted at the PPKn FKIP Study Program, Riau University. The method used in this research is quantitative comparative. Data collection techniques in this research were questionnaires, interviews and literature studies. The results of this research are that there is no comparison of learning motivation between boarding house students and students who live with their parents in students at the PPKn FKIP Study Program, Riau University. This is based on the percentage value of the alternative score for the learning motivation answer for boarding students, which is (94.83%) and the percentage value The alternative answer score for students who live with their parents is (90.91%) and the independent sample t-test using SPPS version 25, the value obtained in the sig column (2-tailed) is 0.173 and the value 0.173 0.05.
Significance of NFT Avtaars in Metaverse and their Promotion: Case Study

The metaverse is undergoing a transformative shift with the introduction of Non-Fungible Token (NFT) avatars, offering users unique and tradable digital identities. This research paper explores the significance of NFT avatars in the metaverse, emphasizing their role in redefining digital ownership, self-expression, and user engagement. Additionally, the paper delves into the issues and challenges associated with the promotion of NFT avatars, considering factors such as market dynamics, technological barriers, and user adoption. This paper is considering different NFT that are developed by various NFT Brands. These NFT could be used in future in Metaverse. At the end of research paper a case study of “Sizzling monster” NFT has been made. This NFT has very limited supply and several NFT brands have bought it at initial stage from Young Parrot Platform.
Convolutional Neural Network (CNN) Layer Development for Effectiveness of Classification Tasks

This paper presents a novel 2D convolutional layer motivated by the principles of Partial Differential Equation (PDE) of Neural Interaction. Our objective is to leverage this layer to enhance the classification accuracy of Deep Convolutional Neural Networks (DCNN) for various classification tasks. We place a particular emphasis on its integration within the ResNet architecture, and we conduct experimental evaluations on the CIFAR10 and STL10 datasets to validate its efficacy.
Primitive Action Recognition Based on Semantic Facts

To interact with humans, a robot has to know actions done by each agent presents in the environment, robotic or not. Robots are not omniscient and can’t perceive every actions made but, as humans do, we can equip the robot with the ability to infer what happens from the perceived effects of these actions on the environment. In this paper, we present a lightweight and open-source framework to recognise primitive actions and their parameters. Based on a semantic abstraction of changes in the environment, it allows to recognise unperceived actions. In addition, thanks to its integration into a cognitive robotic architecture implementing perspective-taking and theory of mind, the presented framework is able to estimate the actions recognised by the agent interacting with the robot. These recognition processes are refined on the fly based on the current observations. Tests on real robots demonstrate the framework’s usability in interactive contexts.
A Comprehensive Overview of the Unequivocal Influence and Evolution of Cryptography on Security

Abstract: As this society unfolds into a conundrum of new possibilities and technical advancements, it simultaneously sets ground to several unprecedented challenges for its users. What today’s digitally ensnared society doesn’t understand is its vulnerability to malicious software, cyber attacks, and innumerable privacy violations that come their way as they mold themselves into this digital realm. For a country like India, that well adapts to the newer technologies invented across the globe, it is astonishing to see almost 1.3 million cybersecurity breaches being recorded in 2022, a hideous spike from 2019. Current internet users feel the need to be active on such delusional platforms every minute of their day, exposing themselves at every stage. This empowers unethical practices and practitioners to lure unsuspecting candidates into their traps and obtain private information linked to several sensitive, especially monetary affairs of the individual, consequently resulting in severe financial losses. Ironically, the very technological influence that facilitates security breaches is one that helps in its deterrence and prevention. One of the most predominant and recent technologies that have empowered its influence over such prevention is cryptography and encryption. Traditionally, prior to the widespread awareness about cryptography, companies and individuals used Access Control Lists(ACLs) that work on the basic principle of restricting or revoking access on certain administrative grounds offering data confidentiality and security on the internet. Apart from these companies, in the ancient times, there was significant use of Caesar Cipher, a way of encryption that works on the principle of substitution by a shift of some number down the alphabet. These traditional methods lacked transparency, had increased complexity, were insufficient for rapidly growing networks such as online social media, and also lacked scalability. In order to compensate for these challenges, a newer technology concatenated with cryptography is to be made prevalent in society so that it can offer more scalable and trustworthy encryption and security prevention from online security breaches across the globe. With this ideology, prevention and awareness both can be obtained and a better and safer society can be established in this generation.
Penyeleksian Beasiswa Berprestasi pada Universitas XYZ Menggunakan Metode MOORA

XYZ University has a scholarship program intended for outstanding students. Determination of recipients of outstanding scholarships is still constrained by the unclear system for determining scholarship recipients. This can affect the fairness of receiving scholarships. Students who really deserve to get a scholarship do not receive the scholarship. The solution to overcome this problem, the researcher came up with an idea in the form of a Multi-Objective Optimization by Ratio Analysis (MOORA) Decision Support System method, with the aim of being able to solve the problem of selecting an objective scholarship acceptance process. The MOORA method was chosen because it can solve the problem with a fairly effective method. After conducting research, it was found that 5 (five) candidates were eligible to receive scholarships for outstanding students, namely Alt7, Alt10, Alt37, Alt49, and Alt35. Furthermore, from the results of this study, it was concluded that students who get achievement scholarships are students with the highest scores from the results of the MOORA method, there is no element of subjectivity.
A Hybrid Personalized Text Simplification Framework Leveraging the Deep Learning-based Transformer Model for Dyslexic Students

This study proposes a hybrid personalized text simplification framework leveraging the deep learning-based Transformer model to generate simplified expository texts by addressing all sentence perspectives: semantic, syntactic, and lexical. This study targets dyslexic students due to its increasing population in the education context. Dyslexia is a learning disability characterized by reading deficiency and cognitive weakness. Thus, they need a more personalized learning experience i.e., personalized text simplification to support their classroom learning. Unfortunately, the current models of personalized text simplification can only address the syntactic and lexical perspectives of sentences, ignoring the semantic perspective. Other models employed text complexity classification at the beginning of the text simplification workflow with the intention to address the personalization element. Still, no mapping to the deficiencies of its intended users was made, and the semantic perspective of sentences remains under study. Therefore, this study is conducted to introduce hybrid methods to enhance the current personalization elements, as well as to accommodate generation of simplified expository texts at all sentence perspectives. An extensive literature was conducted using established online databases. The proposed hybrid framework is further divided into three distinct phases: Phase 1) two-phase personalization, Phase 2) multi-label text complexity classification, and Phase 3) explicit editing. It is expected that a successful implementation of the proposed hybrid personalized text simplification framework can accelerate the learning motivations of dyslexic students, hence increasing their academic achievements and reducing academic dropout rates.
The Power of Proactivity: UOW Library's Successful Live Chat Implementation

ABSTRACTSince 2016, UOW Library staff have been engaged in developing a culture of agility, strong digital literacy, and experimental exploration as part of the Future-Ready Library and the Thriving Digital Library strategies. This culture enabled the trial and implementation of a proactive chat widget at University of Wollongong Library prior to the COVID-19 pandemic. Qualitative and quantitative data show how valuable proactive chat was to the students and staff at UOW during a period of high uncertainty. Pro-active chat achieved the goal of equitable provision of resources to library users at a time when visitor and travel rules restricted physical access to UOW Library buildings and on-site staff. The pandemic has been declared over, however, UOW Library continues to utilise proactive chat and to build upon and expand its functionality. The lessons learned during the COVID-19 pandemic have shown that to withstand and succeed in the face of continued change to the provision of services in the GLAM sector, the attributes of agility and flexibility as well as strong and ongoing growth in digital literacy skills are vital.KEYWORDS: Digital literacydigital transformationproactive chatacademic librariesstaff development Disclosure StatementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsCate SlaterCate Slater joined the University of Wollongong Library in 2016, starting in the Client Services team before transitioning into her current role as a Learning and Engagement Librarian. She partners with academic staff to create digital learning objects that support students to develop their digital and information literacy skills. Her areas of interest include the student experience, digital learning and teaching and utilising technologies to deliver content to students.Leanne CampbellLeanne Campbell began working at the University of Wollongong Library in 2016 following completion of a Graduate Diploma of Library and Information Studies through Curtin University. After spending six years in the Client Services team, including as casual staff coordinator and team leader during the COVID-19 pandemic, she is now leading the Resources and Discovery team providing optimal access to UOW Library’s electronic resources.Lara DugganLara Anne Duggan worked at the University of Wollongong Library for over 27 years supporting researchers, academics, and students. While in the Client Services Team she was part of the three-person team that investigated, trialled and implemented the pro-active chat before and during the COVID-19 pandemic. She now works at the Graduate Research School, University of Wollongong, administering scholarships and progression.
MyRoom: A Unity Plugin for Procedural and Interactive Indoor Scene Synthesis

The demand for indoor synthesis has increased significantly in recent years because of the emergence of computational design. This work designs and develops MyRoom, a Unity plugin that can import layout datasets for indoor synthesis and procedurally generate and interactively design indoor scenes. MyRoom enables users to easily edit and visualize non-intuitive layout description data, making it easier to generate and manipulate indoor scenes in Unity. MyRoom provides a user-friendly interface and powerful tools for designing and optimizing indoor layouts, including an automatic layout generator, making it ideal for game developers, interior designers, and researchers in the digital world-building industry. With MyRoom, users can streamline the process of creating high-quality indoor scenes in games and achieve their design goals efficiently.
Ros-Gazebo Based Virtual PVTOL Experimental Platform to Validate Control Algorithms

This paper presents the methodology to build a customized virtual experimental planar vertical takeoff and Landing (PVTOL) vehicle using ROS, which acts as a middleware between the user interface and the Gazebo simulator. CAD is used to create the virtual prototype, allowing the conversion to the simulation environment. The creation of ROS plugin, and implementation of control algorithms for validation of the simulation environment is addressed, where the classical PID control is used to test the realistic behavior of the platform in simulation. A comparison of results with Simulink- MATLAB, demonstrated using the Pearson correlation coefficient.
Novel MITM attack scheme based on built-in negotiation for blockchain-based digital twins

As smart contracts, represented by Solidity, become deeply integrated into the manufacturing industry, blockchain-based Digital Twins (DT) has gained momentum in recent years. Most of the blockchain infrastructures in widespread use today are based on the Proof-of-Work (PoW) mechanism, and the process of creating blocks is known as “mining”. Mining becomes increasingly difficult as the blockchain grows in size and the number of on-chain business systems increases. To lower the threshold of participation in the mining process, “mining pools” have been created. Miners can cooperate and share the mining rewards according to the hashrate they contributed to the pool. Stratum is the most widely used communication protocol between miners and mining pools. Its security is essential for the participants. In this paper, we propose two novel Man-In-The-Middle (MITM) attack schemes against Stratum, which allow attackers to steal miners' hashrate to any mining pool using hijacked TCP connections. Compared with existing attacks, our work is more secretive, more suitable for the real-world environment, and more harmful. The Proof-of-Concept (PoC) shows that our schemes work perfectly on most mining softwares and pools. Furthermore, we present a lightweight AI-driven approach based on protocol-level feature analysis to detect Stratum MITM for blockchain-based DTs. Its detection model consists of three layers: feature extraction layer, vectorization layer, and detection layer. Experiments prove that our detection approach can effectively detect Stratum MITM traffic with 98% accuracy. Our work alerts the communities and provides possible mitigation against these more hidden and profitable attack schemes.
Improved Food Region Extraction Using State-of-the-Art Saliency Detection

In this study, the accuracy of food region extraction, which is used to obtain image pixels in the food regions from food images and remove pixels in the background regions such as table and plate, was improved. In the proposed method, state-of-the-art saliency detection, which is used to predict pixels that attract human gaze based on the deep neural network (DNN), and semiautomatic segmentation, which is used to iteratively refine food and background regions by using graph theory, are employed. The comparative experiment demonstrated that the proposed method significantly increased the mean F-measure, which is a comprehensive evaluation metric, over that of conventional saliency-based food region extraction by 9.15% by reducing the erroneous determination of the background as the food region. Furthermore, the F-measure was higher than that of UNet+, which is a DNN-based semantic segmentation trained on a well-known public image dataset. This paper comprehensively details the analysis of performance improvement.