Reviewerly/exHarmony huggingface dataset:
DEVELOPMENT OF MECHANISMS FOR UNIVERSITY GRADUATES’ EMPLOYMENT BY MODERNIZATION OF EDUCATIONAL COMMUNICATIONS

The objective of this article is to evaluate the implementation of different communicational mechanisms for effective graduates’ employment on the example of Udmurt State University as a participant of the program “Priority-2030”. The traditional and innovative universities’ forms of this activity are considered in the article. Innovative practices develop practice-oriented learning through cooperation between stakeholders, which present internal and external environment of universities. Educational policy of Udmurt State University aims at developing new formats of career planning including the use of digital services, professional scholarships, and trainings in organizations of the real sector of economy. The necessary component of this policy is the professional guidance by engagement in research and projective activities. The student survey demonstrated existence of some issues of contemporary higher education, such as low level of collaboration between universities and future employers, lack of demands for graduates, and disconnection between the content of educational programs and requirements for employee’s professional qualifications on the labor market. In the students’ opinion, the practical experience and professional training in organizations is one of significant factors of successful employment. Interviews with university employee revealed that traditional passive forms of graduates’ employment are mostly used: self-employment and informational work with students. The program “Priority-2030” has opened opportunities for innovative forms of employment by partnerships with organizations, creating consortiums with different agents. These opportunities motivate university administrations to transform internal communications and apply new approaches to the design of educational programs.
Restricted Boltzmann Machine and Matrix Factorization-Alternating Square Algorithm for Development Tourist Recommendation System

Abstract The rapid development of technology affects the growth of tourist attraction information in Indonesia. Therefore, an accurate recommendation system is needed in recommending tourist attractions. In this final project, we use the Collaborative Filtering method, namely the Restricted Boltzmann Machine (RBM) algorithm and the Matrix Factorization-Alternating Least Squares (MF-ALS) algorithm in recommending tourist attractions. Attraction recommendations will be generated from the type of tourist attraction available on the website and the rating that has been given by previous users who have visited the tourist attraction. We use a root mean square error (RMSE) to find the accuracy. From the results of the research and implementation of the two algorithms, it can be concluded that the RBM algorithm is more accurate than the MF-ALS algorithm. The RBM algorithm has an RMSE value of 41%, while the MF-ALS algorithm 81%.
Internal Quality Assurance of the Education Program at Higher Educational Institutions

Ongoing efforts on internal quality assurance of the educational program at higher educational institutions should be based on comprehensiveness and constant innovative activity. The development of modern and effective ways and measures in order to ensure the quality of educational programs is relevant both for modern higher educational institutions in practice and in the theoretical and methodological plane. The purpose of the research lies in establishing the principles of ensuring the quality of the educational program, which should be applied to achieve high quality teaching following the educational program of higher educational institutions in Ukraine; determining the shortcomings and prospects for the development of educational programs (curricula) and their assessment by educators. In the course of the research, an interpretive qualitative study has been used; along with this, the experiment as the main method, the methods of description, questionnaire and observation have been also used in the academic paper. The research hypothesis lies in the fact that ensuring the quality of the educational program is based on a balanced complex of innovative theoretical principles and their practical implementation. The result of the research is the establishment of the fundamentals for ensuring the quality of educational programs of higher educational institutions, taking into account their innovative nature and the evaluation of the strengths and weaknesses of the curriculum by the participants of the educational process. In the prospect, the implementation of research programs for the further development and improvement of the quality and demand of educational programs of the HEI at the level of the world market of educational services is expected.
Efficient Scrambling-Substitution Image Security Scheme using Chaotic Arnold-Logistic Maps in the Discrete Cosine Transform

This paper introduces an efficient scrambling-substitution image security scheme using chaotic Arnold and Logistic (Arnold-Logistic) maps in the discrete cosine transform (DCT). The Arnold map is employed as a scrambling stage while the Logistic map is employed as a substitution stage. The hybrid Arnold-Logistic mapping is performed in the DCT. The encipherment phase of the introduced DCT-based Arnold-Logistic security scheme begins by applying the DCT to the plainimage and the resulted DCT coefficient of the plainimage are scrambled for m iterations using the Arnold transformation. Then, the Arnold-based transformed DCT coefficients are substituted for n iterations using the Logistic map and the inverse of DCT (IDCT) is employed to produce the cipherimage. The decipherment phase of the introduced DCTbased Arnold-Logistic security scheme is the inverse of the encryption stage and begins by applying the DCT to the cipherimage. The resulted DCT coefficient of the cipherimage is inversely substituted for n iterations using the inverse Logistic map. Then, the inverse Logistic-based transformed DCT coefficients are inversely scrambled for m iterations using the inverse Arnold map and the IDCT is employed to produce the decrypted image. A series of test experiments are applied to investigate the introduced DCTbased Arnold-Logistic security scheme. The outcome results demonstrated the superiority of the introduced DCT-based Arnold-Logistic security scheme from the security point of view.
Detecting Spam Email With Machine Learning Optimized With Bio-Inspired Metaheuristic Algorithms

Electronic mail has eased communication methods for many organizations as well as individuals. Spammers use this strategy to make fraudulent gains by sending unsolicited emails. This project aims to present a method for detection of spam emails with machine learning algorithms that are optimized with bio-inspired methods. A literature review is carried to explore the efficient methods applied on different datasets to achieve good results. The bio-inspired algorithms like Particle Swarm Optimization and Genetic Algorithm were implemented to optimize the performance of classifiers. Multinomial Naïve Bayes with Genetic Algorithm performed the best overall. The comparison of our results with other machine learning and bio-inspired models to show the best suitable model is also discussed.
Motion Optimization and Control of Single and Multiple Autonomous Aerial, Land, and Marine Robots

Fast-paced developments in the fields of aerial, land, and marine robotics are steadily paving the way for a wide spectrum of scientific and commercial applications of autonomous vehicles with far-reaching societal implications [...].
Profile and Financial Behaviour of Crypto Adopters – Evidence from Macedonian Population Survey

Abstract Regulators and policymakers in many developing countries are facing challenges on how to create opportunities for the crypto industry to grow, but at the same time protect investors and consumers. This study aims to better understand the demographic and socio-economic characteristics of crypto adopters and their financial behavior. Our study advances the knowledge within an array of recent contributions to the token economy and covers the geographical and contextual research gaps through survey data from a developing country in South Eastern Europe. We use descriptive statistics and chi-square analysis and we find that Macedonian crypto-adopters are more men of younger age, employed, with higher education and living in their own apartments in an urban area, and are mainly passive investors. We compare the findings with studies from other countries to provide valuable insights for policymakers and regulators.
From Immersive to Metaverse: The Gap of Learning and Technology in Agriculture Education Application

&#x0D; &#x0D; &#x0D; Immersive technologies such as augmented reality, virtual reality, social media, virtual avatars, and online games have supported education. Agriculture, as one of the essentials process for human well-being, demands interaction-rich and content-rich educational technology to increase student understanding of the complex agriculture environment. The current trend of education technology is starting to shift to the metaverse. However, there is a gap between the current implementation of immersive technologies and the mature metaverse. Moreover, previous research indicates the lack of emphasis on learning theory, learning content, and design elements for immersive application in education. This research aims to identify those gaps, especially in agriculture education. We systematically analyze previous publications which developed an immersive application for agriculture education in higher education. We conclude that (1) most of the learning content and design element of metaverse technology is underutilized; (2) there are many implementation gaps between the current implementation with a mature metaverse; and (3) A mature metaverse education is complex and expensive, so careful long-term planning and identifying use cases is recommended. These gaps are essential for subsequent research on developing metaverse for education, especially in agriculture. We hope the results of this research will provide educators with a baseline knowledge of metaverse technologies to make better decisions on utilizing metaverse in educational institutions.&#x0D; &#x0D; &#x0D;
Soft Skills As A Component Of Sustainable Development In Modern Society

The modernization of the system of Russian higher education is due to the global focus on ensuring the quality of education within the framework of the Unesco department.Sustainable Development Goals 17 aim to meet the socio-economic needs of the present and future generations of the entire globe, and each of the 17 Goals solves a specific task.As a social institution, education serves as an indicator of the state of the world community.The Ministry of Education and Science of the Russian Federation is continuously improving the Federal State Educational Standards for Higher Professional Education.The prospects for introducing a competency-based approach into the educational process of new generation Russian universities are obvious.Recently, a variety of training and courses on the development of personal qualities have appeared.In accordance with modern world standards and advanced technologies, the implementation of an innovative cultural, scientific and educational environment is included in the list of project objectives.The authors conclude that education becomes essentially motivated, quick-thinking, focused on problemsolving and a risk-taking person acting in conjunction with other people, armed with knowledge, tolerance and socially oriented.Based on the proposed supposition, they propose a list of testing questions that can reveal the student's psychological abilities that stand for their soft skills development
Modified Ant Colony Optimization for Human Recognition in Videos of Low Resolution

Privacy protections for people filmed in public settings is a prerequisite to widespread camera use. For this reason, low-resolution videos are used from which specific people can be reliably obscured. Since the human region in low-resolution videos comprises of so few pixels and so little information, human detection is more challenging there than it is in high-resolution videos. With the current state of affairs, one of the most important challenges is tracking a target from lower resolution movies. Identification or monitoring of persons in low-resolution movies has become a common issue in many domains due to a lack of appropriate data. This study presents a novel people-detection algorithm that makes use of low-resolution film to overcome the aforementioned problem. In the first stage, a three-step procedure is executed, the video data gathered from low-resolution videos from various form of data is considered. The captured video is separated into frames and transformed from RGB to gray-scale. Local Binary Pattern (LBP) method is used in the second phase to accomplish background subtraction. Thirdly the feature extraction is performed in which histogram of optical flow (HOF)and some of the features are extracted in the form of eigen values. Finally these features are optimized using Modified Ant Colony Optimization (MACO) model to remove the unwanted features and select global features. Finally, classification operation is performed using Support Vector Machine (SVM) classifier to recognize the person from lower resolution videos. The results obtained using the implemented MACO-SVM obtains good results when compared with existing techniques with rate of accuracy 91.46% for soccer dataset, 90.8% for KTH dataset and 89.75% accuracy using VIRAT dataset.
The Development of Digital Module for Natural Sciences to Improve Islamic Elementary School Students’ Learning Outcomes

This study aims to develop a digital module in science learning to improve student learning outcomes. To this end, the research and development using the ADDIE model were applied. This research was conducted at Madrasah Ibtidaiyah Negeri 12 Langkat during the even semester of the 2021/2022 academic year. The study participants were fifth-grade students in Madrasah Ibtidaiyah Negeri 12 Langkat. The object of this research was the development of digital-based modules. Data were collected through observation, interviews, and documentation. The developed product was validated by three validators: a linguist, a media expert, and a material expert. Students' responses were also garnered. The developed digital module was proven to improve students’ learning outcomes 77.27% of students said they were happy with the subject matter and 86.36% of students were happy with the module components. Meanwhile, 72.73% of students were happy with the classroom learning atmosphere, and 86.36% of students were happy with the teacher's teaching method. The results of the assessment of the digital module showed that the product was deemed feasible. Students' responses to the digital module were very good. The digital science learning module developed in this study was proven to be able to improve the learning outcomes of fifth-grade students in Madrasah Ibtidaiyah Negeri 12 Langkat. This study contributes to the development of e-learning media in elementary education.
Features Of Legal Regulation In The Field Of Education In Russia

The scientific and practical problem addressed by the study is relevant for the system of modern Russian education (especially after the entry of the Russian Federation into the World Trade Organization) and can be considered as interdisciplinary (for example, jurisprudence, pedagogy, economics and public management).The study features the concepts of "service" and "educational service", as well as substantiates the need to preserve and legislate the status of "national treasure" for educational services in the Russian Federation.The analysis performed by the author presents the category "service" as an activity, as a method or algorithm of actions, and as a relationship.The category of "educational service" is considered by the author in terms of its outcomes (that is, acquired knowledge, skills) and activities for knowledge and skill transfer.The author proposes to differentiate services according to the provided branches of law.Delimiting constitutional law and civil law, the author introduces the concept of "constitutional (national) service", clarifying the definition "educational service" as a service guaranteed by the Constitution of the Russian Federation.In the study, the author proposes to expand the federal legislative framework governing the field of education, and to make structural changes in the Government of the Russian Federation.This paper is intended for undergraduates, graduate students, state management structures and other individuals interested in the field of educational activities on the territory of the Russian Federation.
Total quality management and its role in improving customer relations in Jordanian Islamic banks

Total quality management (TQM) is a method of managing a bank. TQM, which is considered as a critical instrument, directs the strategy of developing work and increasing performance in order to generate profits through quality services and products. Therefore, this study aimed to examine the function of TQM in improving customer relations in Jordanian Islamic banks. Primary data was gathered by surveying 163 workers of Jordanian Islamic banks. A questionnaire was employed as the data-gathering technique. To do the descriptive statistical analysis, SPSS version 25 was employed. The findings show that there is a statistical association between Jordanian Islamic banks' TQM, which includes customer satisfaction, strategic planning, continuous improvement, and relationships with customers.
The effect of key user capability on supply chain digital and flexibility in improving financial performance

Organizational competitiveness is enhanced by implementing supply chain integration. Organizations, through information technology, can integrate internal and external cross-functional. The team assigned to run the integration system in its function is designated as the key user who can implement and maintain an ongoing basis. Key user capabilities are needed to maintain a digital supply chain in information technology systems to integrate internally and externally. Data analysis using Partial least squares (PLS) on 89 hotel organizations with a one-star category or more shows that key user capability significantly affects internal cross-functional integration (β = 0.728) and external cross-functional integration (β = 0.127). Key user capability has an impact on supply chain flexibility (β = 0.370) while internal cross-functional integration influences increasing supply chain flexibility (β = 0.373) and financial performance (β = 0.421). External cross-functional integration increases supply chain flexibility (β = 0.316) and financial performance (β = 0.441). Lastly, supply chain flexibility impacts increasing financial flexibility (β = 0.192). The research contributes enrichment to the theory of digital supply chain and practical contribution to enlighten top management in information technology investment.
INTERCONNECTION AMONG CRYPTOCURRENCIES: USING VECTOR ERROR CORRECTION MODEL

The research paper aimed to investigate the relationship between the major popular cryptocurrencies in terms of market dominance and identify any pattern and/or causality between the short-run and long-run series. Cryptocurrency has received much attention because of media publicity and the financial returns it generates within a short time, with its associated risk level. This innovative financial research investigates for the first time by thoroughly analyzing nine top cryptocurrencies, excluding stablecoins. The study used the Vector Error Correction model to analyse how the various cryptocurrency under investigation are interconnected. The results demonstrated how concentrated the causality effect is on some specific cryptocurrencies. The study uses the top nine cryptocurrencies on the crypto markets, excluding stablecoins that have existed since October 2017. The frequency of the data is 1523 daily closing prices. The choice of the data stemmed from its availability and has existed since October 2017. The primary outcome is clear and possibly explains the dominance of Bitcoin and Ethereum as the main drivers of the prices of related or altcoins. Any movement in the price level of the two dominant cryptos affects all the altcoins on the crypto market. The research further unearths the interconnection or correlation between the major cryptocurrencies. It will assist institutional and retail investors, fund managers, and managers, with the possible mix of assets in their portfolio based on their risk appetite level in making investment decisions.
Information Accessibility in the Digital Age Empowering Women for Poverty Eradication

In recent times, there has been an increasing awareness of the need to empower women to improve their socio-economic status, cope with their economic situations, and contribute effectively to economic development.The contribution of women to economic development is germane and this necessitates the incorporation of gender equality in the Sustainable Development Goals (Goal 5).With that in mind, access to information is imperative to empower women in this digital era.However, there are perceptions, beliefs, and challenges about the use of information technology tools in women's information accessibility; hence there is gender inequality in information accessibility.Therefore, this study examined how women should be empowered in a manner that enables them to have access to information in the digital age, and the challenges faced in accessing information for economic development.A qualitative approach was used for the study.A review of relevant literature was done to examine how Nigerian women are empowered to have access to accurate and timely information.The study found that there are initiatives like Information Communication Technology (ICT) training skills, education, and financial support that are strategically planned to empower women, but this is still at an undesirably low rate.The study concludes by suggesting that policymakers ensure that information be provided for women in the format that it will be easy for them to access, younger women should be encouraged to be literate, and organisations should collaborate with library professionals who are trained to disseminate information to a diverse population of women so that they may access the information they need.
N/A Modern Approaches in Natural Language Processing

Natural Language Processing (NLP) is one of the major branches in the emerging field of Artificial Intelligence (AI). Classical approaches in this area were mostly based on parsing and information extraction techniques, which suffered from great difficulty when dealing with very large textual datasets available in practical applications. This issue can potentially be addressed with the recent advancement of the Deep Learning (DL) techniques, which are naturally assuming very large datasets for training. In fact, NLP research has witnessed a remarkable achievement with the introduction of Word Embedding techniques, which allows a document to be represented meaningfully as a matrix, on which major DL models like CNN or RNN can be deployed effectively to accomplish common NLP tasks. Gradually, NLP scholars keep developing specific models for their areas, notably attention-enhanced BiLSTM, Transformer and BERT. The births of those models have introduced a new wave of modern approaches which frequently report new breaking results and open much novel research directions. The aim of this paper is to give readers a roadmap of those modern approaches in NLP, including their ideas, theories and applications. This would hopefully offer a solid background for further research in this area.