Reviewerly/exHarmony huggingface dataset:
Anti-fraud measures and corporate policies to combat financial fraud in the financial institutes of Malaysia

The rising concern about fraud in the financial sector and its impact on the economy requires massive changes and efforts that provide an avenue to fight against fraud. The primary goal of this study is to examine the effectiveness of Anti-fraud measures and corporate policies to combat financial fraud in financial institutes in Malaysia. In this study, three variables that affect combatting financial fraud have been identified to be evaluated, including digital forensic tools, regulations, and corporate policies. This study used questionnaires to obtain data from workers of financial institutions as a primary data source. The findings indicated that all variables have a significant relationship with combating financial fraud. Thus, this study raises awareness about the need for anti-fraud measures in financial institutions to combat fraud.
Cryptocurrencies: An Epitome of Technological Populism

From a global perspective, which holds significant cryptocurrencies, this study discusses the volatility and spillover effect between the whales’ cryptocurrencies. Volatility in cryptocurrency markets has always been a time-varying concept that changes over time. As opposed to the stock market, which has historically and recently, the cryptocurrency market is much more volatile. The markets have evidenced many fluctuations in the prices of cryptos. As a result, countries are transforming their policies to suit financial technologies in their economic practices. Blockchain technology allows people to obtain more benefits in a financial transaction and breaks hurdles in the financial system. The study has found no ARCH effect in BinanceCoin, BT Cash, Bitcoin, Vechain, and Zcash. It is discovered that there is an ARCH effect in the case of Ethereum, Tether, Tezos, and XRP. Whale cryptocurrencies have an ARCH effect. Daily closing prices of ten cryptocurrencies, including bitcoin, from January 1, 2019, to December 31, 2020, to determine the price volatility where the bitcoin whales hold significant cryptocurrency values. It has given significant results in case of volatility since we also found that Bitcoin's largest cryptocurrencies among the sample taken for the study have less volatility than other currencies.
Multi-level Image Segmentation of Breast Tumors Using Kapur Entropy Based Nature-Inspired Algorithms

Medical image segmentation entails the extraction of essential Region of Interests (RoIs) for the further analysis of the image. Segmentation using the thresholding technique partitions an image into multiple objects and one background using multiple threshold values. This paper focuses on the application of dragonfly algorithm and crow search algorithm to optimize between-class variance using Kapur’s entropy as fitness function. The proposed methods have been assessed on benchmarked images for threshold values ranging from 2 to 14 and performance is compared with traditional methods like Kapur and Otsu’s multi-level threshold techniques. Experimental results have been evaluated using well-performed metrics like peak signal to noise ratio, visual information fidelity, structural similarity index matrix, and feature based similarity index matrix. Computational time is also compared. Experimental results show that the proposed method dragonfly algorithm with Kapur’s entropy performed better compared to crow search algorithm and traditional methods.
Ustoichivoe razvitie SSO s dual'noi innovatsionnoi tekhnologiei obucheniia v kolledzhe s nepreryvnym operezhaiushchim professional'nym obrazovaniem

September 2020 was the 10th anniversary of the dual education system in Russia. Germany (German school) is considered to be the ancestor of dual education. Its elements can be found in the systems of professional education in many European and Asian countries [2]. Today the dual system of professional education has received worldwide recognition – it is the most widespread and recognized form of personnel training, which combines theoretical training (in our country – 40%, in Germany – 20–25%) in an educational institution and industrial training (75–80% at the enterprises). This model of training is used in specialized secondary and higher educational institutions, and is financed jointly with business, which is interested in qualified personnel, and the state. The new training system should &amp;quot;arm&amp;quot; the graduates with three main competences, behavioral and personal qualities: Decision-making skills (Soft Skills); professional qualities (Hard Skills), because unprofessionalism is ruining Russia; modern technologies (Digital Skills).
Metodicheskaia podgotovka pedagoga-fizika v usloviiakh tsifrovizatsii obrazovatel'noi sredy

In the chapter the necessity and possibility of application of digital tools in the higher school for the organization of the educational process directed on formation of professional kinds of activity, connected with designing and carrying out of a modern physics lesson, is proved. Methodological basis of the study was the psychological and pedagogical theory of activity, the basic laws which are formulated by the well-known domestic psychologist P.Ya. Galperin. A system of digital educational resources aimed at the formation of abilities to design and conduct lessons in which students create concepts about a physical phenomenon, a physical object, a physical quantity, establish scientific facts and discover physical laws, as well as apply the acquired knowledge in specific situations was developed. The structure and the contents of electronic educational resources realized in electronic educational environment of higher educational institution in the course &amp;quot;Methods of teaching physics&amp;quot; are presented. They include information block, block of formed kinds of activity, block of educational-methodical materials, forum and control. The advantages of the educational process organization with the use of electronic educational resources are proved and the results of long-term pedagogical experiment in the implementation of the developed model of e-learning are presented.
On the roles of software testers: An exploratory study

Software development organizations need testers with high skill levels in a broad range of technical areas and application domains. Accordingly, we need a better understanding of how testers meet such skill demands in the practice of their role. This work aims to deepen the understanding of the typical tester role. We performed a thematic analysis of 19 in-depth, semi-structured interviews with software testers working in various industries. To investigate employers' views on such roles, we conducted a thematic analysis of 400 job ads. From the interviews, we identified five subroles of software testers: domain-specific tester, test automation specialist, test infrastructure specialist, user experience tester, and test manager. Most of the practitioners preferred to develop skills and act in one subrole. In contrast, most of the job ads requested that testers act in multiple subroles. Our findings provide a deeper understanding of the tester role, which may guide testers in their acquisition of skills and employers in the recruiting of testers.
Advanced reversible stenographic method for image and video frames by adapting dual tree complex wavelet transform and chaotic whale optimization algorithm

Summary In this article, an advanced reversible stenographic method is proposed for image and video frames by adapting dual tree complex wavelet transform and chaotic whale optimization algorithm. Here, the cover image and secret message are taken as input. In this image, the edges are identified by Canny edge detection system and embedded by the process of dual‐tree complex wave transformation method (DT‐CWT‐CWOA‐SDH) and pixel edges are optimized using the chaos whale optimization algorithm (CWOA), it optimizes the edge pixel variations and maximizes the robustness of the image and visual quality of stego image. The objective of this process is to increase the security of secret data hiding the secret message on cover image and forming the stego image by the embedding procedure and to maximize the peak signal‐to‐noise ratio (PSNR) and reduce the execution time. The proposed method runs on the MATLAB work site and the performance of proposed method is evaluated using different existing methods. The simulation outcomes illustrate that the proposed DT‐CWT‐CWOA‐SDH shows higher PSNR of 32.01%, 24.79%; lower mean square error (MSE) of 21.13%, 45.185%, normalized correlation (NC) of 11.24%, 19.04% compared with existing method.
An object‐oriented approach toward two‐dimensional engineering mechanics

Abstract The present work proposes an object‐oriented approach for the solution of problems in two‐dimensional engineering mechanics. New classes (in the terminology of object‐oriented programming) are proposed and implemented in the popular programming language ‘Python.’ These classes, along with the symbolic computation module of Python ‘sympy,’ enable one to reduce the solution of a large class of problems in undergraduate engineering mechanics to a set of Python statements. These statements are definitions of objects as instances of the proposed classes and calling of their relevant methods. If the thought process in the manual solution is represented by a flowchart, the present work can be viewed as a flowchart translator . As all the calculations are automatically performed, the present work relieves the student from the burden and fear of lengthy calculations. Different diagrammatic representations of velocity, acceleration, shear force, and bending moments are included for better physical understanding. It is believed that the proposed simple implementation would make problem‐solving and the learning process more enjoyable. Apart from a standard PC, the proposed work runs on a single‐board computer (tested in raspberry pi 4) and on an Android mobile device. A student feedback study ascertains the acceptability of the proposed method.
A Study on Determinants of Satisfaction with Teaching Jobs of an Elementary School Teachers - Focusing on Variables of Teacher Efficacy, Educational Environment, and Fellow Teachers

This study is to verify the influence of teacher efficacy (factor 1), educational environment (factor 2), and peer-teacher relationship (factor 3) as determinants of satisfaction with teaching profession of an Elementary school teachers.To this end, a three-step model of hierarchical regression analysis was applied to confirm the effects of teacher efficacy, educational environment, and peer teacher characteristics on teaching job satisfaction.As a result of the analysis, it was confirmed that all items, such as teaching activities and life guidance, which are factors of teacher efficacy, and educational environment factors, such as educational facilities, teaching job burden, academic atmosphere, and peerteacher relationships, have significant effects on teaching job satisfaction.In addition, the effect of factors 1 and 2 together was higher than that of one factor alone, and the combination of factors 1, 2, and 3 had the highest effect on the effect on teaching job satisfaction.The significance of this study is that it confirmed the effects of the research results, teacher efficacy, educational environment, and peerteacher relationships on teaching job satisfaction in multidimensional and integrated aspects.In addition, this study has the implication of presenting necessary evidence for teachers themselves and education policy makers who want to increase the satisfaction of the teaching profession.
Governance Implications of Applying Internal Auditing Standards to Blockchain-based Decentralized Autonomous Organizations (DAOs)

The research paper discusses governance implications, benefits, and challenges of applying internationally recognized internal auditing standards to the newly emerging Decentralized Autonomous Organizations (DAOs) that have quickly gained traction in the past years and are currently totaling market capitalizations of more than USD 20 billion globally. It is analyzed how standards established for traditional centralized organizations are compatible with a decentralized, often anonymous organization that makes decisions democratically based on majority votes while most operations are conducted autonomously subject to pre-defined self-executing smart contracts. After the technological attributes of blockchains, smart contracts, DAOs and other general considerations are determined, each IIA standard is applied separately and results are drawn from a qualitative analysis. The publication contains the major conclusions from a literature analysis followed by a summary of conceptual obstacles to complying with the standards in case of selecting a DAO as an organizational form which could make their overall legality impossible in a context where the implementation of an IA function is mandatory. Additionally, it is summarized how choosing a DAO can contribute and/or challenge compliance with the standards while giving a glimpse into what internal auditing could look like in the future.
The impact of Blockchain technology on the transformation of the nature of financial services

Subject. This article examines the impact of blockchain technology on changing the infrastructure of global financial services, as well as its key advantages and development challenges in the financial environment. Objectives. The article aims to analyze the impact of distributed ledger technology on the implementation of blockchain technologies in smart contracts, non-fungible tokens, cryptocurrencies, central bank digital currencies, and digital financial assets. Methods. For the study, I used the methods of theoretical generalization, structural grouping, and statistical analysis. Results. The article reveals the expansion of the scope and audience of consumers of blockchain tools in the financial environment, the prospects for creating enterprises with minimal management capital, and reducing the cost of making payments. Conclusions. Blockchain technologies have the potential to radically change the global financial services market. Reducing the energy consumption of technologies, introducing a legal regulatory framework, expanding the scalability of blockchain networks, training specialists who understand the specifics of introducing advanced blockchain technologies into the financial sector of the economy – all these and some other acute problems of blockchain development are outstanding.
Reshaping Blended Learning after the COVID-19 Period in Higher Education

The tragic situation caused by the COVID-19 epidemic also became the biggest experiment in higher education. We sought the answer to the challenges arising at University of Tokaj with a higher education pedagogical experiment. The experiment was based on the practice-oriented design of cooperative learning, which was implemented through the joint project work of groups of different ages. The research question at the center of the experiment was whether the learning effectiveness of the groups participating in the experiment changed as a result of the completely on-line training during the COVID period. Based on deductive logic, the conclusion can be drawn that students active in the COVID period can be effectively educated within the “blended learning” methodology with an online-dominant training organization of up to 80%. The so-called COVID groups do not belong to a uniform age group, but to a group of students with the same history. In higher education, it is advisable to use the effect of the “spontaneous experiment” caused by the global tragedy of COVID as soon as possible, so that within the “blended-learning” method, the ratio of contact (classroom) and online training is between 20% and 80% we approximate to.
Образовательная деятельность в СПО с применением электронного обучения

In recent decades the system of secondary vocational education in Russia has been going through a difficult path. Socio-economic development forecast for the period till 2030 defines priority directions in SPO transformation as the main production driver. Professional organizations of SPE system are undergoing reforming, which has touched such spheres of detail as the content and organization of the educational process; integration of SPE educational organizations; changes in the requirements of educational standards, etc. Significant challenges of our time are the need to update the content of SPE educational programs, the introduction of practice-oriented learning models in cooperation with core enterprises and organizations, updating the list (register) of professions and specialties based on the staffing needs of the regions, digitalization and transformation of different types of work. This publication is dedicated to the analysis of training activity in implementation of educational programs in SPE, including application of e-learning in the conditions of reforming the system of SPE in Russia. Materials and methods. General theoretical methods are used to achieve the goal of the study: analysis of theoretical sources, generalization and systematization of the data obtained; empirical methods: observation. The research materials are historical facts, scientific articles, dissertation studies, data of practitioners and experts, opinions of the leaders of education development in Russia and other authors.
Methodical Systematic Review of Abstractive Summarization and Natural Language Processing Models for Biomedical Health Informatics: Approaches, Metrics and Challenges

Text summarization tasks are primarily very useful for decision support systems and provide a source for useful data for training of bots as they can reduce and retain the useful information from the large corpus. This review article is for studying the literature that already exists in context of abstractive summarization and application of NLP language models in biomedical and associated healthcare applications. In past decade with trends like bigdata, IOT, enormous amount of data is getting processed in all structured, unstructured and semi structured formats. This review provides a comprehensive literature survey in research trends for abstractive summarization, foundations of machine translation and evolution of language models. This review identifies the potential of language model to provide a possible methodology for improving the performance and accuracy of various tasks in summarization. Deep neural network-based language models have now been the widely accepted state of art for various abstractive summarization and there exists an enormous scope to improvise and tune the language models for domain specific use case. This study shows current systems lack in faithfulness to original content and control of degree of hallucination. This review also details on the evaluation criteria and need for automated metrics and attempts to provide guideline for evaluation for abstractive summarization for health informatics.
Graph Neural Networks and Reinforcement Learning: A Survey

Graph neural network (GNN) is an emerging field of research that tries to generalize deep learning architectures to work with non-Euclidean data. Nowadays, combining deep reinforcement learning (DRL) with GNN for graph-structured problems, especially in multi-agent environments, is a powerful technique in modern deep learning. From the computational point of view, multi-agent environments are inherently complex, because future rewards depend on the joint actions of multiple agents. This chapter tries to examine different types of applying GNN and DRL techniques in the most common representations of multi-agent problems and their challenges. In general, the fusion of GNN and DRL can be addressed from two different points of view. First, GNN is used to influence the DRL performance and improve its formulation. Here, GNN is applied in relational DRL structures such as multi-agent and multi-task DRL. Second, DRL is used to improve the application of GNN. From this viewpoint, DRL can be used for a variety of purposes including neural architecture search and improving the explanatory power of GNN predictions.
A Comparative Review for Color Image Denoising

With the explosion in the number of color digital images taken every day, the demand for more accurate and visually pleasing images is increasing. Images that have only one component in each pixel are called scalar images. Correspondingly, when each pixel consists of three separate components from three different signal channels, these are called color images. Image denoising, which aims to reconstruct a high-quality image from its degraded observation, is a classical yet still very active topic in the area of low-level computer vision. Impulse noise is one of the most severe noises which usually affect the images during signal acquisition stage or due to the bit error in the transmission. The use of color images is increasing in many color image processing applications. Restoration of images corrupted by noises is a very common problem in color image processing. Therefore, work is required to reduce noise without losing the color image features.
Integration of Blockchain and Mobile Edge Computing

This chapter begins with the fundamentals of blockchain and MEC. Integrating new technologies like blockchain and MEC is seen as a potential paradigm for managing the voluminous amounts of data produced by today's pervasive mobile devices and subsequently powering intelligent services. With blockchain technology, they can boost the safety of existing MEC systems by using decentralized, immutable, secure, private, and service-efficient smart contracts. These smart contracts fall into three broad categories: public blockchains, consortium blockchains, and private blockchains. Moreover, this chapter discusses the classification and current defence mechanisms of security threats. Potential solutions to MEC's main security challenges are then discussed. Following that, the authors present a classification to assist developers of various architectures in selecting an appropriate platform for specific applications, as well as insights into potential research directions. Finally, the authors present key blockchain and MEC convergence features, followed by some conclusions.
A Methodological Study of Fake Image Creation and Detection Techniques in Multimedia Forensics

Nowadays, there is a huge concern of fabrication of real-world images/ videos using various computer-aided tools and software. Although these types of software are commonly used for personal entertainment but may create havoc when used by malicious people for concealing some sensitive contents from images for criminal forgery. Spread of fake information and illegal activities or creating morphed images of some individuals for taking revenge are some of the potentially destructive areas of advanced face information and structure manipulation technology in the wrong hands. Researcher fraternity in multimedia forensics have been working in this area since many years and in this paper, a comprehensive study of various techniques of fake image/video creation and detection are described. It also presents a survey on various benchmark datasets used by the researchers for fake image/video detection. The presented survey can be a useful contribution for the research community to develop a new method/ model for fake detection thereby overcoming the restrictions of the traditional methods.