Reviewerly/exHarmony huggingface dataset:
The Research on Methods for Generating Random Passwords

Today, passwords are used to protect various personal, financial and other information in our daily lives. To ensure security, these passwords must be of high complexity, i.e. so that the hacking time is “infinitely” long. Many methods are proposed for generating random passwords with different character sets. The work selects a method among possible proposals in the languages C#, Python and Java. To determine a more suitable method, clustering of passwords obtained using C#, Python and Java methods was carried out using the K-means, G-means and EM algorithm methods. As a result, the java.security.SecureRandom method was chosen for further use in developing a mobile application.
Selection of the K Parameter in the K-Nearest Neighbor Algorithm for Solar Power Prediction

This article introduces a new method for optimizing K-Nearest Neighbor (KNN) neighbor selection of k value for solar power prediction. It estimates a low-error range of the nearest neighbors based on Euclidean distance analysis, outperforming traditional methods in accuracy and effectiveness using real solar station data.
Evaluation of an Enhanced Dynamic Knowledge-Based Authentication System (EDKBA) in the Era of Social Media

Services related to information and communication technology (ICT) today require secure personal identity verification methods to guard against unauthorized access. There are several authentication methods, with traditional passwords being the most popular one. Passwords are susceptible to threats like eavesdropping and forgotten passwords, though. One of the finest substitutes for conventional passwords was knowledge-based authentication (KBA), which verifies identification using public records. Static and dynamic KBAs are examples of KBAs that are vulnerable to theft and modification. The goal of the study was to develop and implement an enhanced DKBA (EDKBA) system that uses challenge response questions and answers to authenticate users in real time. Two attack models, naive attack (guessing) and strategic attack (brute force), were used to evaluate the effectiveness of the EDKBA system. The developed EDKBA provided improved security by dynamically generating authentication questions based on real-time information about users' weekly Facebook activities. The EDKBA experiment showed a success rate and True Positive of 72.57% with an acceptable error rate (False Negative) of 27.43%. The study concluded that implementing EDKBA will reduce the rising risks brought on by unauthorized access to data and cybercrime, which would directly improve the overall security of sensitive data and information.
A Critical Review of The Intersection of Artificial Intelligence and Cybersecurity

Cyberattacks have significantly increased in frequency and sophistication over time. The detection and prevention of potential attacks are becoming very difficult using traditional cybersecurity technologies. Cybercriminals are experts in using sophisticated techniques and potent weapons to compromise, assault, and hack information. However, contemporary developments in artificial intelligence (AI) techniques demonstrate that AI can play a significant role in defending against the continually expanding cyberthreats posed by malign actors. AI-based solutions can provide powerful and effective cyber defense capabilities in defending against cyberthreats. The main objective of this research is to highlight the applications and challenges of AI in cybersecurity and identify mitigating strategies for addressing these challenges. A number of existing literatures is reviewed to examine the intersection of AI in Cybersecurity. We discussed some exciting new research directions for developing robust and efficient AI-based cybersecurity systems that can promote a safe and secure ecosystem.
A Quantum Abacus for Teaching Quantum Algorithms

At the time of this writing more than 60 (sixty) companies in the world are building quantum computers. These computers, based on quantum physics principles, are radically different from those that operate according to the more familiar principles of classical physics. A quantum algorithm takes a number of classical bits as its input, manipulates them so as to create a superposition of all their possible states, further manipulates this exponentially large superposition to obtain the final quantum result, and then measures the result to get (with the appropriate probability distribution) the same number of output bits as in its input. For the middle phase, there are elementary operations which count as one step and yet manipulate all the exponentially many amplitudes of the superposition. The natural language of these quantum gates is that of linear algebra in a complex (Hilbert) vector space. Since 2017 it is known that it is possible to replace the linear algebra with some string-rewriting rules which are no more complicated than the basic rules of arithmetic. The original system was introduced by Terry Rudolph and has been promoted and disseminated in large-scale outreach projects (among others) by Diana Franklin (University of Chicago) and Sofia Economou and Ed Barnes (Virginia Tech) as well as several other educators at the high-school level. In this paper we show how a slightly modified (though still very elementary) system can be used to communicate a visual and entirely operational understanding of key quantum computation concepts such as: superposition, probability, entanglement, phase, interference and unitary state evolution, as they occur in well-known quantum algorithms. We give concrete examples of proving properties for quantum gates and quantum circuits without resorting at all to complex numbers or matrix multiplication. Only simple, abacus-like operations are used-hence the title of the paper. The system we present allows a novice learner to actually trace a quantum algorithm as if it were a classical computation, which is a rare (and, frankly, borderline incredible) luxury in the area of quantum computation, where traditional debugging is impossible. Examples include the phase kickback phenomenon and the famous Deutsch-Josza algorithm. We end with a discussion (and more examples) of how this approach can create a genuine bridge to the mathematics of quantum computation, that is, of vector and tensor algebras in complex spaces for students who may have little or no proper mathematical background.
Improving Delivery of UML Class Diagrams Concepts in Computer Science Education Through Collaborative Learning

This work-in-progress paper aims to understand hard-to-comprehend class diagrams concepts (a standard in Unified Modeling Language (UML)) by CS students and to improve their understanding of these concepts. Fresh graduates have been reported (by the software industry) to face difficulties in solving real-world problems with class diagrams (one of many problematic areas). This incompetency affects software development negatively in the software industry when they join the workforce. Lack of proficiency in modeling knowledge leads to fault-prone software designs, which require additional testing and time for the developers in software development. To fill the skill gap, this research intends to develop a systematic pedagogical approach to help students understand these concepts better through checklist-based intervention and pair programming. Our proposed approach, in accordance with the SoTL (Scholarship of Teaching of Learning), in this study aims at conducting an empirical study in a software design course at North Dakota State University to (a) conduct a pretest to identify students' basic conceptual understanding and (b) post-tests to evaluate the impact of pair programming and checklist-based interventions. We will analyze the data collected from this session to find how much intervention and pair programming helped improve the learning concepts of software design in students and to meet industrial expectations by building skill setups for workforce industries.
Publishing Marketing Communication Strategy in the Era of AI : Focusing on College Students' Book Exploration Experience Using ChatGPT

The purpose of this study was to examine the perceptions of college students on ChatGPT and explore their using behavior. For this purpose, targeted group interviews were conducted with 120 college students, and 84 people who commonly use ChatGPT were asked to experience book research activities through ChatGPT. This study explored how user experience influences trust in book information and purchase intention through ChatGPT. The results of the study showed that users' cognitive and relational experience in book exploration activities using ChatGPT had a positive and significant effect on information trust and purchase intention. Furthermore, educational opportunities had a statistically significant moderating effect on the relationship between relational experience and information trust, and critical thinking had a statistically significant moderating effect on the relationship between relational experience and book purchase intention. The results of this study emphasize the importance of customer experience and digital media literacy education as a proper reading activity and publishing marketing communication strategy using ChatGPT.
The sociological dimension of media interactions: current state and author's design of the study

In the research of modern digital society, interaction through various channels and media is increasingly coming to the fore as a “|gaining momentum” trend of social development. Meanwhile, despite the abundance of empirical data in this area, the scientific understanding of interactions understood as media is in the process of formation, which is especially noticeable from the point of view of sociological discourse. It thoroughly represents the interactions of the traditional type, that is, social, in the works of E. Durkheim, M. Weber, G. Simmel, T. Parsons, J. Homans, J. Mead, P. Bourdieu and other classics of sociological thought. The Russian sociological science, starting with P.A. Sorokin and up to the present day, in which interactions form the essence of all social processes, does not stand aside either. Actually, media interactions have been considered by foreign sociologists since the 70s of the twentieth century, in line with the interaction of the audience with the media and social networks (J. Nordlund, P. Robinson, J. Blommaert). The paper is intended to represent the author’s vision media interactions studies design and is based sociolinguistic and socio- communication approaches allowing to most accurately identify essence of these processes.
Hate speech and social media: Combating a dangerous relationship

The article proposes a reflection on the configuration of the contemporary digital agorà as a powerful ‘hate factory’, focusing on the dangers deriving from pervasive and planetary practices of divisive news construction and sharing trough the social media. In the first part, it will be argued that the increase of lexical choices based on hate or verbal violence must be connected to the characteristics of the contemporary hybrid media system, and considered as a concrete threat for democracies, which challenges institutions to find innovative ways to face it at a legislative as well as at a cultural level. In the second part of the article, some EU recent normative actions against hate speech will be presented in order to underline links with the 2022 “Code on hate speech”, promoted by Italian Authority for Communications (AGCOM) in Italy: this document established the binding criteria for the programming of Italian audio-visual media service providers, in order to prevent and combat hate speech by avoiding any dissemination, justification, minimization of violence, hatred or discrimination both in information and entertainment. From all these institutional initiatives clearly emerges the need to reinforce the legal framework for tackling hate speech and discrimination, starting from the normative lack of strict rules in many European countries.
Computational Analysis of Printed Arabic Text Database for Natural Language Processing

A frequency dictionary of printed Arabic text is essential for natural language processing. It includes 1,251 XML files of Arabic documents collected from ten newspapers and magazines from different countries and created as the PATD database. A total of 2,344 articles were created with various structures: open vocabulary, multi-font, multi-size, and multi-style text. From these articles, 1,102,078 tokens, 19,926 sentences, and 1,000,000 words were extracted. This dictionary provides detailed information for each word, including English equivalents, usage statistics, usage distribution, and the most widely used terms. A thematic vocabulary list of the top words on various topics is also provided. This frequency dictionary is a useful resource of modern Arabic vocabulary for various specialists, students, and learners. The frequency dictionary is freely available to interested researchers on the webpage.
10 Facilitators of sense of belonging through Digital Competences: a qualitative study with educational science students

This study explores how digital competences (DC) can contribute to fostering the sense of belonging in social groups. It examines the factors that shape belonging agency, trust, and social capital, while considering the potential of digital technologies to promote it and the role of DC in enhancing social inclusion, also in an intersectional perspective. This research uses qualitative methods and peer-research following the last version of the DigComp model developed by European Commission. A total of 108 participants from two universities from the European context were involved. The results identified 10 facilitators of sense of belonging: common interest, learning and engagement, voice and empowering, communication, interculturality, leisure activities, shared emotions, being informed, freedom of speech, and group values and norms. The findings highlight the ways in which DC, such as content creation, problem-solving, and communication and collaboration, contribute to fostering a sense of belonging into social groups. Finally, the study points out that digital technologies can be a tool to support the facilitators of belonging rather than being the central focus. The research underscores the importance of considering actions and abilities rather than specific tools in promoting social belonging in the digital era.
Academic Leadership in Higher Education

Purpose: The effectiveness of our higher education system depends on effective and vibrant teachers with knowledge of Academics, Assessment and evaluation, Pedagogy, Research Culture, and Innovation in teaching &amp; learning. The National Education Policy (NEP) 2020 specifies that the “most important factor in the success of higher education institutions is the quality and engagement of its faculty. The study focuses on the understanding of NEP and OBE amongst faculty members and academic leaders, the factors affecting teaching and learning in higher education, and the role of academic leadership in implementing outcome-based education in higher education. Approach: The study is based on the data collected from 53 academic leaders from 53 different B- schools. To have better results the study has collected data from different regions in India, covering East, West, North, and South. Data is collected through a data triangulation approach. For this purpose, structured questionnaires were used, telephonic interviews of the sample and Focus Group Discussions with members of the senior cadre were conducted. The study employed different methods of data collection, preliminary interviews, and focus group discussions to yield the parameters on which a structured questionnaire was prepared. After deciding on the constructs of the scale, indicator items were prepared. Statistical analysis is done to assess the awareness and application of NEP 2020 in Management Education. Results: The focus group discussion and primary interview with the academic leader helped to design the application of Maslow’s Hierarchy of needs to Employee Engagement in Higher Education. The faculty need to know the level of their performance and areas in which they need improvement. Performance improvement helps the organization to meet its goals and objectives. Performance counselling is a very important activity that helps employees to know themselves better. It has been observed that employee engagement increases with performance counselling. Hence the desired result of NEP implementation will be better with faculty training and counselling. The attributes of Academic Leadership for academic, administrative, and research &amp; extension activities are identified, analyzed, and evaluated. A conceptual model with the required attributes and qualities for a Role model/Super academic leader is also described. Type of Paper: Exploratory and descriptive
A Secure IoT-Cloud Based Remote Health Monitoring for Heart Disease Prediction Using Machine Learning and Deep Learning Techniques

The Internet of Things (IoT) refers to a network of interconnected devices as well as technology that enables objects to communicate with one another and the cloud for modern medical treatment. To analyze and handle remotely collected electronic clinical records, it is important to create a disease prediction model with increased accuracy. An RHMIoT framework is proposed in a secure cloud context using lightweight block encryption and decryption approaches. The accuracy levels of cardiac disease are calculated using machine learning and deep learning methods. The ensemble voting classifier provided the greatest accuracy of 95%.
Assessing Student Programming Process Using Automated Reasoning

This Innovative Practice Full Paper presents an automated reasoning approach to the assessment of a student's programming process as captured by an autograder. When students are assessed in computing courses, they are typically assessed on their completed work, such as a programming assignment. Although such an assessment measures a student's general ability, it provides only an indirect measure of the effectiveness of their programming (or problem-solving) process. Without the ability to examine the process by which a student completes an assignment, an instructor may have difficulty teaching problem-solving skills since they cannot measure how the student's skill develops. Some computing courses make use of an autograder which automatically assesses student homework. The trace captured by an autograder is a unique source of information about a student's problem-solving ability, which can be analyzed to measure properties of that learner's process. This provides a way to assess the process-based aspect of student learning, enabling instructors to not only teach problem-solving skills but to determine how well students acquire these skills. This enables teachers to evaluate the methodology they employ and to select instructional material based on student need. Automatically analyzing the trace captured by an autograder has two major challenges: the scale of the data makes traditional approaches computationally expensive, and the definition of a problem-solving process is often expressed in a commonsense way based on an expert's intuition. These challenges can be addressed by using an Answer Set Programming (ASP) approach. ASP is a declarative language that is intended for solving computationally hard problems, and through various extensions, supports human-style commonsense reasoning. Assessing a student is computationally hard due to the combinatorial nature of the different ways an assignment may be solved. In this paper, we discuss the design of an ASP-based system for automatically assessing a student's problem-solving process using the trace captured by an autograder, and present a preliminary evaluation of the system applied within a university-level course on data structures & algorithms.
Towards an Intelligent Tutoring System for Virtual Reality Learning Environments

This Work-in-Progress Research paper explores the development of an Intelligent Tutoring System (ITS) inside a Virtual Reality Learning Environment (VRLE). As technology becomes more pervasive in teaching, platforms that afford immersive learning experiences, such as VRLEs, are receiving increased attention. VRLEs engage students in a virtual representation of a learning space; however, understanding how to use and interact with a VRLE usually represents a steep learning curve, particularly for the instructor. Our work addresses this problem by integrating an ITS into the VRLE. In doing so, timely guidance can be provided to the students, and the instructor can adapt the ITS support to best guide student learning across multiple skill levels. Our approach immerses students in an engineering-based VRLE that resembles a space launch mission control. Inside the environment, students interact with the system to acquire data, compute, and evaluate options to attempt the successful landing of a spacecraft. The VRLEs' ITS provides the students with feedback as they interact with the environment to address challenges. The feedback is provided in various modalities, such as virtual floating panels with general suggestions, hints on which parameters from the calculations should be changed, and visual demonstrations of the calculations' outputs. To perform an initial validation of our approach, we compare its effectiveness against a physical laboratory version of the same experiment. The results of the interviews validated the ITS as a successful approach in providing students with prompt feedback while they are immersed in the VRLE. Overall, the work strengthens the validity of VRLEs as platforms that support more engaging and immersive learning experiences, and informs how to effectively integrate ITS within them.
FAIRifying STEM Data Ecosystem to Enhance Data Reuse

In the science, technology, engineering, and mathematics (STEM) community, academic and research workflows and work practices are increasingly mediated and informed by data. However, making digital materials and resources findable, accessible, interoperable, and reusable (FAIR) for teaching, learning, and research is an under-researched area. Thus, it is vital to examine the current data practices of STEM students and faculties and acquaint them with the FAIR data concept. FAIR Data Principles is a set of guidelines that underscore metadata, vocabularies, licences, and standards to enhance data reuse. A study was conducted among students and faculties in the STEM community of the Royal University of Bhutan (RUB) to unpack their current data practices and explore areas for improvement using the FAIR Data Principles. The STEM students and faculties of the RUB share and reuse digital materials and resources for teaching, learning, and research. Nevertheless, their data practice is not as widespread or desired in the literature on optimum data reuse. Moreover, the compliance of current data practices to the tenets of FAIR Data Principles is not satisfactory. A pragmatic solution is complementing data practices with policies and infrastructural systems that underscore FAIR Data Principles. A sensitisation programme such as seminars and hands-on exercises on data FAIRification is crucial to familiarise people with the essentialness of FAIR data, and doing so will provide a platform to develop their repertoire for FAIRifying data and encourage systematic sharing and reuse of data. An in-depth account of the FAIRifying STEM data ecosystem in the study contributes to the growing knowledge base on adopting FAIR Data Principles in other areas of data-informed work and life.