Reviewerly/exHarmony huggingface dataset:
The Influence of Interest Groups on U.S. Foreign Policy under D. Trump: An Experience of Cognitive Analysis

Significant changes in U.S. foreign policy, which were first declared during the election campaign and then began to be consistently implemented by Donald Trump and his administration, were in many ways a break with the established and successive foreign policy strategy, which has made this case the subject of numerous analyses and studies. This study attempts to examine the influence of interest groups on U.S. foreign policy under D. Trump through the prism of several approaches - interest group theory, network approach, cognitive analysis (using cognitive mapping methodology). As a result of the conducted research, practical results in the form of cognitive maps were obtained, and the limitations of the used methodology within the framework of the analysis of this case study were revealed.
Layout Aware Resume Parsing Using NLP and Rule-based Techniques

As a result of the rapid development seen in the field of IT, there has been a surge in the number of students choosing IT field related degrees in recent years When those students try to secure job a better fob position in the field of IT, resume plays a vital role as it is often the first document a recruiter will see in the recruitment process. Therefore, this paper introduces a layout aware resume parsing system based on NLP and rule-based techniques to extract the section wise text content from the resume. This output can be used as the input for the resume content scoring model as a resume content review system to get feedback for the resume. When comparing existing methods with the proposed system, the layout of the resume would be considered in the proposed system, and it would extract content for each section. In addition to that, the proposed system would extract all the text content, but existing systems only extract the entities. In summary, this study is focused on developing a layout aware resume parsing system based on NLP and rule-based techniques to extract the section wise text content from the resume for an accurate resume review.
Dominant Color Palette Extraction in Resumes using the New Color Pixel Quantifier Algorithm

In the realm of resume analysis and enhancement, the extraction of dominant color palettes plays a pivotal role in assessing the visual impact of resumes. Existing methods designed for images with extensive color ranges have proven to be suboptimal when applied to the distinct context of resumes, which inherently possess a limited color palette. This paper introduces a novel approach that addresses this challenge effectively and efficiently. By minimizing the time required for palette extraction without compromising accuracy, the proposed method offers a practical solution for resume feedback systems. It is important to clarify that this research neither rejects nor supports existing methods; instead, it presents an alternative, tailor-made solution for resume analysis. In summary, this paper sets a promising precedent for more streamlined and functional dominant color palette extraction methods in the context of resumes, promising advancements in resume analysis and improvement.
An Agile Project Management Supporting Approach for Estimating Story Points in User Stories

While significant research has been conducted on software analytics for effort estimation in traditional software projects, limited attention has been given to estimation in agile projects, particularly in estimating the effort required for completing user stories. In our study, we present a novel prediction model for estimating story points, which serves as a common unit of measure for gauging the effort involved in completing a user story or resolving an issue. To achieve this, we propose a unique combination of two powerful deep learning architectures, namely LSTM and RHN. What sets our prediction system apart is its end-to-end training capability, allowing it to learn directly from raw input data without relying on manual feature engineering. To support our research, we have curated a comprehensive dataset specifically tailored for story points-based estimation. This dataset comprises 6801 issues extracted from 6 different open-source projects. Through an empirical evaluation, we demonstrate the superiority of our approach over three common baselines. In summary, our study addresses the gap in research regarding agile project estimation by introducing a prediction model that effectively estimates story points. By leveraging the combined power of LSTM and RHN architectures.
Distributed Posterior Fusion for Vehicle Tracking with Gaussian Processes

We focus on the distributed posterior fusion for vehicle tracking in this paper. With rectangular prior information of vehicles’ shapes, we build a non-zero mean Gaussian Processes (GP) model to initialize the extents. In order to improve the estimation accuracy of targets’ kinematic and extent states, we try to make progress in two aspects. For one thing, we propose the unscented Kalman extended target Probability Hypothesis Density (UK-ET-PHD) filter with a tailor-made GP model. It can track multiple targets simultaneously and solve the nonlinear problems. For another thing, we realize the posterior fusion using the Generalized Covariance Intersection (GCI) rule with the proposed UK-ET-PHD local trackers. Finally, we evaluate the performance of the proposed method in the view of both vehicles’ position and extent estimation.
WAVELET BASED PARAMETER ESTIMATION OF MIXTURE OF GAUSSIANS

This paper presents a family of new continuous wavelet function and describes few properties of it. A method of estimating parameters for a Gaussians using this new continuous wavelet transform is described. The robustness of this method for estimating the parameters in the presence of noise is also studied by simulating different possible cases.
Hate Speech in Nigerian Politics: An Islamic and Christian Perspectives

The prevalence of hate speech in Nigerian politics is alarming. This paper aims to examine the remedy for hate speech in the Islamic and Christian perspectives. To achieve the designed objectives, qualitative methods involving historical and contextual approaches were used in data collection and analysis. The findings reveal that nowadays, in Nigeria, hate speech causes political sentiments and manipulations, religious insinuations and misinterpretations, and tribal jingoism and still is being used by some undesirable elements among the politicians. The findings further show that hate speech leads clergies and tribal jingoists to cause disaffection and civil insurrection among Nigerian citizens. This caused a huge setback to Nigerian sustainable development, both religiously and economically. The paper, therefore, recommends that Muslim scholars and priests should endeavour to create a conducive environment where a public lecture would be organized to emphasize the impacts of peaceful coexistence among Nigerian Muslims and Christians just to remedy the disease of hate speech.
Error Analysis Analysis of Compositions Written by IT Students

This study aims to identify the common linguistic errors among the third and the fourth grade students of IT at the Collage of Computer Technology. The researcher used the analytical descriptive method. He chose a random sample consisting of 80 male and female students. He constructed a list comprising of 294 common linguistic errors. He then built an objective test in the light of the list as the study tool, which is analytical description of students' written compositions. The results showed that the level of frequency at which these errors occur differ from one category to another. Errors in spelling and tense took the highest rate of occurrence raging from (27.8%) to (22.4%) whereas errors in. Articles and capitalization took the lowest rate of occurrence raging from (15.6%) to (14.2%). Further studies are suggested to investigate the causes, which constitute this huge numbers of errors.
Exploring the Convergence of Digital Currencies and E-Commerce

The convergence of digital currencies and e-commerce represents a period of transformation in the financial landscape, reshaping transactions in the digital era. This chapter examines their intricate relationship, focusing on their effects on security, consumer behaviour, regulations, and access to global markets. Stakeholders must understand this synergy to exploit opportunities and overcome obstacles. Understanding this change is essential for success in the dynamic world of online finance and business.
Digital Currency Adoption in Nigeria

Nigeria is one of the countries with the highest volume of trade in digital currency worldwide after the United States of America, with over $500 million dollars. This shows that there are possible opportunities to harness in the sector while taking several steps to limit the threats. The objective of this chapter is to discuss digital currency adoption in Nigeria with particular emphasis to its determinants of adoption, opportunities, and threats/risks. Factors determining adoption include socioeconomic status, expectations on the profitability, and stability of the naira. Opportunities include employment and ease of payments, especially for international trade. Unregulated nature and anonymity/secrecy are the major threats identified which enhance illegal activities that cannot be traced easily. Cross-country overview shows that some countries such as Iran and China have out-rightly banned cryptocurrency in their countries, but users still maneuver their ways to invest in the sector; therefore, outright ban will still not remove the threats in the long run.
Bibliometric Analysis on Digital Wallets

The emergence of digital finance was taken to the next level by the world economy due to Covid-19 situation. The adoption of digital wallets by the citizens of advanced countries, as well as advancing countries, has been drastically increased in the past decade long with digital wallets research. The aim of this research is to produce a comprehensive analysis on digital wallet research and to provide future research directions to potential researchers by providing bibliometrics like most cited articles, most cited authors, top keywords, top journals, etc. related to digital wallet research. The appropriate articles, book chapters, conference papers, and reviews from available sources were identified from Scopus database using the search term “digital wallets” (TITLE-ABS-WALLETS) where 686 articles (as of 24-04-2023) from the year 1977 to 2023 were considered for bibliometric analysis using Vosviewer software. After researching current trends, the research findings were generated from several themes to give future research directions in the sphere of digital wallets.
Investor Behaviour, Market Efficiency, and Regulatory Challenges in Digital Currency Investments

The rapid proliferation of digital currencies has ignited significant interest in understanding investor behaviour and the regulatory challenges within this evolving financial landscape. The study seeks to elucidate the factors that influence investor behaviour in the cryptocurrency/digital currency market and explore the regulatory implications associated with digital currency investments. A systematic approach was adopted to identify, review, and analyze relevant scholarly articles from reputable databases. The selected articles span various dimensions of the cryptocurrency/digital currency ecosystem, including investor behaviour, market efficiency, technological innovation, and regulatory measures. It reveals that investor behaviour in the digital currency market is influenced by a complex interplay of emotions, market sentiment, and information asymmetry. Additionally, market efficiency theories are being reconsidered in light of the highly volatile nature of cryptocurrencies. Regulatory challenges encompass issues related to fraud, pump-and-dump schemes, and legal ambiguity.
Construction of a Parametric Family of Wavelets and Its Use in Image Processing

&lt;p&gt;This article is devoted to the construction of a parametric family of biorthogonal wavelets according to the lifting scheme and subdivision schemes, and the use of such a family in the problem of image rendering when part of the pixel data in the image is missing or overwritten in some way. The parametric family of wavelets provides a parametric family of filters for restoring damaged images. With such a recovery, the desired wavelet is selected not from any general considerations, but from a parametric family in the process of solving an optimization problem.&lt;/p&gt;
Modeling Processes for Automated Generation of Work Programs

&lt;p&gt;A method for formalizing educational text into an ontology is proposed. It is proposed to preserve the transmission of the meaning contained in the text by operating with minimal educational elements: definitions of specific entities, descriptions of its properties, actions performed, rules, formulas and similar fragments of knowledge. The formal structure representing the educational text, which can be considered as a directed graph, the vertices of which make up frames describing educational elements, provides the opportunity to develop models and algorithms that can effectively solve a number of problems in the field of education. The same structure makes it possible to develop a model of the content of a work program devoted to the study of knowledge contained in a given educational text.&lt;/p&gt;
Establishing Similarities between Text Documents

&lt;p&gt;This article discusses a method for assessing the similarity of texts, which is based on the analysis of comparison of sentences from different texts. The advantages of the method are that it takes into account the coverage of the standard sentence by a sentence from the compared text, the general assessment of the informational significance of the words of the standard sentence in the sentence of the compared text, the similarity of the syntactic structures of sentences, the coincidence of semantic meanings and connections. The application of this method is illustrated by the example of solving the problem of finding the similarities between two texts.&lt;/p&gt;
Blockchain Technology Adoption Against Corruption in Emerging Economies

Corruption overwhelms the functionality of all countries, with the developing countries lacking the resources to combat it effectively, leaving society in serious jeopardy. This chapter analyzes the potential of the adoption of blockchain technology to curb corruption in developing countries. The method adopted for the study is conceptual analyzes. Specifically, the blockchain technology framework for government procurement processes and monitoring of government contract execution in developing country was developed. It showed that the immutable nature of blocks in the chain and the consensus protocol of the nodes make the technology adoption a good fit for curbing corruption, make project execution timely, and make the government procurement process transparent. The conclusion of the chapter is that governments of the developing countries should take bold steps to lay out the framework for the adoption of blockchain technology as a panacea against endemic corruption in procurement.
Discriminant Analysis Based on Kohonen Statistics

&lt;p&gt;The paper describes a new method of discriminant analysis based on T. Kohonen's neural networks. The analysis algorithm and its advantages are considered.&lt;/p&gt;
Demonstration exam as a form of final certification: the NEFU experience

The article discusses various theoretical and empirical methods used in research, including the analysis of the regulatory framework, conducting expert assessment and statistical processing of results, using descriptive examination methods, theoretical and methodological features of organizing and conducting demonstration exams. The article presents the experience and results of conducting exams on in-demand competencies; students have the opportunity to demonstrate their skills in specific situations and show how ready they are for professional activity. The general purpose of such examinations is to assess students’ readiness for work, where the key is not only the presence of basic knowledge, but also the ability to apply it in practical activities. The pilot testing took place in 2018, and in 2021 the NEFU introduced competency exams as the final certification of students and a mechanism for organizing educational activities of the university. The introduction of the exam into the main professional educational programs determines the degree of formation of professional skills and abilities by conducting an independent assessment of practical tasks performed by the student, performed in real time and simulating professional activity. The exam results determine the level of development of competencies of future specialists. 2022-2023 participation in the Future Skills project, implementation of tools for developing skills of the future. The role of the Future Skills University project in the qualitative transformation of the training system and mobile response to new technological structures, as well as new needs of the labor market.
Methods for assessing the involvement of communities in managing the development of territorial educational system

The article presents the characteristics of methods for assessing the involvement of various groups of the local population in the processes of managing the development of territorial systems. The phenomenon of community involvement in educational development management processes is revealed. Based on the analysis of the experience of assessing community engagement in 2020-2023 using surveys, in-depth interviews, data analysis, and studying the subjective opinions of users of social networks, the specifics of various assessment methods are shown.
The Riddle of (Literary) Machine Translation Quality

This study aims to gauge the reliability and validity of metrics and algorithms in evaluating the quality of machine translation in a literary context. Ten machine translated versions of a literary story, provided by four different MT engines over a period of three years, are compared applying two quantitative quality estimation scores (BLEU and a recently developed literariness algorithm). The comparative analysis provides an insight not only into the quality of stylistic and narratological features of machine translation, but also into more traditional quality criteria, such as accuracy and fluency. It is found that evaluations are not always in agreement and that they lack nuance. It is suggested that metrics and algorithms cover only parts of the notion of “quality”, and that a more fine-grained approach is needed if potential literary quality of machine translation is to be captured and possibly validated using those instruments.
Бібліометричний картографічний аналіз компетенцій, адаптованих до промисловості 4.0 та 5.0 на основі літератури про великі дані: наслідки для кар’єрної орієнтації

This study recognizes the presence of a competence-based foundation in the career orientations of both graduate students and professionals. The career orientations of graduating students and professionals, encompassing their interests and objectives, are strongly influenced by their competencies. Competence is an essential foundation for making career choices and aligns with the firm-based competitive advantage that relies on competence (e.g., core competence and dynamic capability). Fundamentally, competence is also a structure of “career orientation” that delivers unique functions of a person or an organization, manifesting VRINO properties of differentiation (e.g., valuable, rare, inimitable, non-substitutable, and organized). Graduating students and professionals build know-why competencies (that relate to career motivation, personal meaning and identification, know-how competencies (functioning strengths that contribute to a firm’s repertoire of overall capabilities), and know-whom competencies, including communication capability. The concept of competence in career orientation is often overlooked, and only a select few deeply understand how competencies should be integrated with other aspects of career orientation. This study examines the typological characteristics of career orientation and its anchors, addressing the need for more knowledge in the current literature. Industry 4.0 and 5.0 exemplify the competencies that graduating students and professionals should possess. These industries and societies utilize intelligent cyber-physical interactions to impact various aspects such as lifestyles, product development, process controls, and industry advancement. This study utilizes the bibliometric analysis method within the limitations of research papers. It applies the Sciencedirect.com databases and focuses on the keywords “Industry 4.0 and Industry 5.0” to identify the competence clusters, essentially a thematic analysis of the interrelationships of a cluster of themes that explain the competence profile for Industry 4.0 and Industry 5.0. Six competence profiles are identified using the bibliometric method: (1) key driver cluster represented by the cyber-physical system, (2) intelligence infrastructure and intelligent factory, (3) intelligence system and resilience, (4) sustainable development goals, (5) supply chain management, stakeholders, sustainable economy, big data analytics, and digital technology, and (6) intelligent businesses. Three typological dimensions of career orientation are proposed: instrumentality (self-organization continuum), value (stability-flexibility continuum), and competence superimposition, which includes core competence in the stability segment and dynamic capability in the flexibility segment. In the context of I4 and I5, it is suggested that graduating students and professionals build a global mindset and technological competence to support globally competent organizations and their businesses.
Adapting the Education and Training System to Technological Evolution

Teachers have faced the challenge of adjusting their pedagogical approaches and teaching methods to help students with disabilities adapt to the distance education context, often without specific training or adequate resources. To address these challenges, the "Do IT Yourself" project aims to increase the involvement of students with disabilities in digital education. Its primary focus is promoting "innovative practices in the digital age" with a two-fold approach: encouraging social inclusion and using technological means to integrate vulnerable student groups. This study aims to highlight teachers' digitisation needs and the digital tools they use in the classroom. The data obtained supporting this quantitative study are part of the Erasmus Plus "Do It Yourself" project, of which Romania is a part, together with Portugal, Italy, Finland and Slovenia. The main objective of this study is to obtain data on the digitisation of education in Romania. The present study applies a research method that focuses on completing structured questions. In this research, 79 participants were involved, representing both pre-university teachers and school principals. The data collection process was carried out using a questionnaire consisting of 12 questions to evaluate the type of digital resources used in the teaching environment, the frequency of their use, and the level of training of the participants regarding the training courses for the integration of the tools digital or self-taught learning.