Reviewerly/exHarmony huggingface dataset:
The Effect of Nepotism and Knowledge Sharing on the Performance of Academic Staff in Jordan: The Mediating Role of Trust

The performance of employees is important for all organizations. The literature has focused on this performance in the business organization while few examined it in the educational context. Important variables such as knowledge sharing (KS), nepotism, and trust have not been widely investigated in educational settings in developing countries. The aim of this study is to investigate the impact of KS, nepotism, as well as trust on the performance of academic staff (PAS). In addition, the study investigates trust as a mediator in the link between nepotism-KS-PAS. Based on the review of theories and prior studies, the study proposed a positive effect of KS and trust on PAS while the negative effect of nepotism on PAS Trust will mediate these effects. The population of this study is the academic staff in Amman, the capital of Jordan. A total of 332 responses were collected using stratified random sampling. The data was collected via an online questionnaire. The data was analyzed using Smart PLS. The finding showed that KS, and trust affected positively PAS while Nepotism negatively affected PAS. Trust mediated the effect of KS on PAS. Universities have to establish a trusting culture to encourage KS. Nepotism is harmful to the performance of organizations and individuals. Universities have to eliminate the source of nepotism by implementing a fair and justice culture.&#x0D; &#x0D; Received: 31 October 2022 / Accepted: 28 February 2023 / Published: 5 March 2023
A Comprehensive Analysis of the Research on Blockchain-Enabled Information Sharing Inside a Supply Chain

Abstract: Customers, suppliers, and transporters are just a few of the many stakeholders that make up a supply chain. Due to the rapid expansion of economic globalization and fierce market competition, which has resulted in fragmented information sharing within a supply chain, it is frequently challenging. By utilizing a "single trustworthy ledger," which has the potential to alter the aspect of data trust, blockchain technology may alleviate this issue. The motivation behind this article is to distinguish and fathom the impact of blockchain innovation on store network data sharing. The decentralized design of blockchain innovation gives a serious level of straightforwardness, drawing in interest from various enterprises to carry out this innovation. Utilizing a few information bases, a far reaching survey of the scholastic writing was finished. Blockchain-empowered data trade might get worth to cooperative work a few stock chains, including wellbeing and clinical, development, and shrewd urban communities. As per our outcomes, one potential advantage of utilizing blockchain-empowered data sharing across a store network is that it guarantees all chain members approach checked data, which works on cooperative joint efforts. We recognized potential obstacles to the development of blockchain innovation in production network by means of our top to bottom examination, for example, an absence of consciousness of blockchain innovation in associations and an irreconcilable situation. Future examination, for example, data covering pair with data sharing, could assist with diminishing the hole in taking on this innovation inside a production network. Understanding the qualities of different supply chains is likewise key for really planning for blockchain execution. We acknowledge that our strategy for picking literary works for our efficient audit might have brought about the rejection of specific writings. In any case, we endeavored to incorporate however many important writings as practical to give a guide on the current situation with blockchain-empowered data trade all through a production network
Factors to increase the effectiveness of an online foreign language course for young scientists

Introduction. The rapid development of digital technologies, online format of the educational process due to the spread of Covid-19 have actualized online learning in universities. The combination of work and postgraduate studies by young scientists, limited time frames, low motivation make it necessary to find the optimal ways to organize the educational process in a foreign language. The considered online course provides young scientists with the opportunity to improve the level of foreign language communicative competence in academic and research fields. Purpose of the article: to improve the effectiveness of the online foreign language course for young scientists. Research methods. The experiment involved 445 first- and second-year graduate students of South Ural State University. To determine the effectiveness of the online course in the program of foreign language study in graduate school and increase the level of foreign language communicative competence the following methods were used: method of pedagogical experiment, method of observation, econometric method of mathematical statistics Difference in Differences (DID). The method of questionnaires was used to identify the educational needs of graduate students. The B.D. Jones's MUSIC® Model of Motivation was chosen as the methodological basis for the redesign of the online course. The relevance and completeness of the strategies of the B.D. Jones's MUSIC® Model of Motivation according to graduate students’ opinions were tested using a parametric Student's t-test with dependent sampling. Results. As a result of the experiment aimed at improving the effectiveness of the online foreign language course for graduate students, positive dynamics in the level of foreign language communication competence of graduate students in the experimental group compared with students in the control group was verified by the Change criterion, which reflects the difference in the results of the PhD Foreign Language Exam of graduate students, recorded by DID: "excellent" – (Change &gt; 12%), "good" – (Change &lt; 9.5%), "satisfactory" – (Change &lt; 2.5%). Discussion and conclusion. It was proved that the identified factors to improve the effectiveness of the online course for young scientists (redesign of the online course, taking into account the educational needs of graduate students) determined the positive dynamics of the level of foreign language communication competence of graduate students.
The English language textbook for future automotive engineers: a case of assessment and self-assessment

Introduction. Over decades, the profession-oriented foreign language textbook has been in the focus of researchers’ attention. In this regard, we carried out research to evaluate the effectiveness of the implementation of a previously elaborated concept of the profession-oriented textbook, which was based on the competency approach, taking the example of the author’s textbooks and using procedures of assessment and self-assessment. Materials and methods. Instructors, pre-service teachers and 1st-4th year engineering students of Togliatti State University (the Russian Federation) participated in the testing of pilot versions of English textbooks. For obtaining empirical data, the research adopted methods of interviews and an anonymous Likert scale survey. The data obtained from the procedure of assessment were then processed using analysis of interview recordings and texts of peer-reviews as well as a method of descriptive statistics. A procedure of self-assessment of textbook materials was also carried out to evaluate the realization of the concept of a profession-oriented textbook. Research results. Results of the survey indicate the success of the implementation of the concept of a profession-oriented textbook: 92 % of 56 questionnaires contained only positive responses. At the same time, the survey shows that the content of the textbooks meets students’ expectations (96 %), correlates with the content of their training (98 %) and the level of English proficiency (92 %). 94 % of respondents would like to recommend the textbooks for mastering professional communication. All the instructors and a reviewer also praised the quality of the textbooks. Conclusion. Assessment and self-assessment procedures allowed to effectively evaluate the quality of the textbooks, to receive students’ feedback and to identify ways of improving textbooks for engineering universities. The findings can be used in the development and evaluation of foreign language textbooks for other non-language majors.
Research-based approaches to the development and assessment of the creative abilities of future international specialists by means of teaching a foreign language

Introduction. Updated requirements for specialists in foreign relations in line with currently changing practice of foreign relations call for developing in undergraduates such professionally relevant creative skills as finding creative solutions to professional challenges and introducing innovative approaches in the conservative paradigm. Conventional approaches prevalent in teaching a foreign language cannot reveal the full potential of fostering creative skills in future professionals in foreign relations, thus calling for developing and substantiating new effective tools of comprehensive development of creativity through teaching a foreign language in undergraduates majoring in foreign relations. Materials and Methods. The study was conducted at MGIMO University, in 2017-2021. The total number of participants was 151 undergraduates, School of International Business and Business Administration, and International Institute of Energy Policy and Diplomacy, with 74 participants in the educational experiment. The analysis was based on the data obtained through administration of the psychometric instruments the Rokeach Value Survey, the Torrance Test of Creative Thinking, and additional instruments designed on the basis of relevant projective techniques. Results. The analysis of data obtained for the experimental and control groups shows more noticeable changes in the parameters under study in the experimental group. For high developmental level of creativity, 22.16% increased to 51.88% in the experimental group, compared to increase from 13.3% to 14.2% in the control group. For basic developmental level, 36.2% reduced to 15.14% in the experimental group, compared to decrease from 44.78% to 40.8% in the control group (tEXP=6; p&lt;0,05). The findings from the psychometric measurements are consistent with the findings from the projective techniques, where improvement in performance correlates positively with higher scores for the relevant parameters. The analysis additionally looked into the changes in the profile of scores and in separate scores in the experimental group. Discussion and Conclusion. The findings of the study support the expected increase in the parameters under study in the experimental group, and substantiate effectiveness of the set of instruments designed to develop and measure professionally relevant creative skills through teaching a foreign language in undergraduates majoring in foreign relations. The approaches verified in the study were used to develop the authors’ foreign-language course, which offers practical application of the instruments described here. Further research should explore the correlation of higher creativity scores with higher academic performance as well as the quality of knowledge
Autonomous Systems and Reliability Assessment: A Systematic Review

The advancement of technology has heralded novel computing devices and gadgets like self-driving cars, IoT devices,and autonomous systems. These advancements required high computational demand in achieving its goals. In matching the highcomputational demand of these new technologies, machine learning, parallelism, multicore processing and scaling are some of theapproaches and techniques put in place. However, there is a pressure on the architectural development of recent computing devices asthe traditional transistors seem to be fast outgrown. This article examines the reliability of autonomous systems using the PRISMAapproach. Autonomous systems are systems that can fully operate and perform operations (computational or otherwise) with minimalhuman intervention.
Data for Electronic Learning, A Social Media Clustering Model

Through Social media, people are able to write short messages on their walls to express their sentiments using varioussocial media like Twitter and Facebook. Through these messages also called status updates, they share and discuss things like news,jokes, business issues and what they go through on a daily basis. Tweets and other updates have become so important in the world ofinformation and communication because they have a great potential of passing information very fast. They enable interaction amongvast groups of people including students, businesses and their clients. These numerous amounts of information can be extracted,processed and properly utilized in areas like marketing and electronic learning. This paper reports on the successful development of away of searching, filtering, organizing and storing the information from social media so that it can be put to some good use in anelectronic learning environment. This helps in solving the problem of losing vital information that is generated from the social media.It addresses this limitation by using the data from twitter to cluster students and by so doing support group electronic learning.
An Artificial Intelligence Cyber Security Algorithm for Cooperative P2P File Sharing in Social Network &amp;amp; Artificial Intelligence for Offence and Defense

Artificial intelligence offense perspective refers to the capability of cybercriminalsusing intelligence to sophisticate their attacks. While the AI defense side is about companies andindividuals, using AI tools to counter cyber-attacks. The study has revealed that machine languageis a part of AI with potential benefits to the current and future of cybersecurity. The Networksecurity is believed to be a subset or sub domain of cyber security. They differ significantly in theimplementation of network security to protect internal information by examining the activities ofemployees and network access. In contrast, cyber security focuses on external threats, such assecurity breaches created by hackers. Its performance has been compared with some of thealgorithms currently in practice and its results are given. The currently proposed algorithm will beoptimized for financial institutions as it exhibits better performance.
A fuzzified model for soft tissue prediction using a knowledge-based deep learning approach

Medical image analysis gains huge advancements with deep learning approaches which boosts the computational capability and accurate prediction. An expert in the field analyzes the feature representation, and an intelligent model helps to categorize and forecast diseases. The MRI images from cancer imaging archives are used to give a novel learning approach for soft tissue diagnosis. This work suggests a Type-2 fuzzy model that chooses local and maximum absolute value to handle the data. According to the experimental investigation, the predicted model works better than several current strategies. Deep convolutional neural networks built on the VGG-16 architecture and the Adam optimizers are used to pre-train the proposed model. The classification accuracy is anticipated based on the experimentation, demonstrating the need for complementary information for learning systems. The goal is to forecast the depth of knowledge extraction by boosting pre-trained CNN’s ability to be fine-tuned by improving the accuracy of soft tissue classification. The proposed model improves performance and validates the significance of the network model by categorizing the tissues as benign or cancerous. The proposed model attains 96.8% accuracy and 9% for depths of 5 and 8 mm and 93% for 10 mm. Similarly, the model attains 96.8% without inclusion, 100% with inclusion and an average outcome of 99%.
The Hybrid Neuro-Fuzzy Models' Most General Intelligent Architectures

Hybrid systems of the fuzzy logic and neural networks, are widely spread in real world problems with high effectivenessand versatility for different kinds of applications. The state description of unknown plant by using mathematical models, sometimes,is difficult to obtain. The fuzzy logic systems with their ability of tackling imprecise knowledges, and neural networks with theiradvantages of establishing a relationship between the inputs and the outputs of the system, are represented as qualified tools forsystems of unknown plant. Furthermore, the hybrid systems which utilize the features of the fuzzy logic and Neural networks hasbeen employed for better characteristics. Whilst, there are several different architectures of the neuro-fuzzy system proposed inliterature, this article come out to highlight the common known architectures of how these techniques fuse together to build anenhanced system that can complement the lack of each method individually and improve the system performance over all.
Unsupervised Learning vs. Round-Tripping in SpanishTurkish Machine Translation

The quality of data-driven Machine Translation (MT) strongly depends on the quantity as well as the quality of thetraining dataset. However, collecting a large set of training parallel texts is not easy in practice. Although various approaches havealready been proposed to overcome this issue, the lack of large parallel corpora still poses a major practical problem for manylanguage pairs. Since monolingual data plays an important role in boosting fluency for Neural MT (NMT) models, this paperinvestigates and compares the performance of two learning-based translation approaches for Spanish-Turkish translation as a lowresource setting in case we only have access to large sets of monolingual data in each language; 1) Unsupervised Learning approach,and 2) Round-Tripping approach. Either approach completely removes the need for bilingual data or enables us to train the NMTsystem relying on monolingual data only. We utilize an Attention-based NMT (Attentional NMT) model, which leverages a carefulinitialization of the parameters, the denoising effect of language models, and the automatic generation of bilingual data. Ourexperimental results demonstrate that the Unsupervised Learning approach outperforms the Round-Tripping approach in SpanishTurkish translation and vice versa. These results confirm that the Unsupervised Learning approach is still a reliable learning-basedtranslation technique for Spanish-Turkish low-resource NMT.
Self-organizing Map Taxonomy of Living Organisms

The Self Organizing Map (SOM) is an unsupervised network algorithm that projects high dimensional data into lowdimensional maps. The projection preserves the topology of the data so that similar data items are mapped to nearby locations on themap. The algorithm has been so popular because of its application in Computer Science and other areas; it has been applied in speechrecognition, pattern identification, control engineering, earthquake detection et al. This research aimed to apply the SOM in thetaxonomy of living organisms using 46 attributes. 68 animals from 6 phyla were considered and 46 attributes were used detailingtheir physical features, physiological features, evolution, adaptation, habitat et al. The features extracted were converted to 0s and 1sfor the SOM algorithm to process. The result shows 96.569% accuracy of the SOM’s classification but better accuracy can beobtained if the SOM had processed the data for about 1000 iterations. This research revealed that SOM is a veritable tool or algorithmthat can be used to classify living organisms. This research will help taxonomists, biologists and students who spend much time inclassifying living organism and it will be of help to researchers who want to explore the SOM algorithm as a solution to taxonomy ofliving organisms. The SOM will ease taxonomy and will help to minimize the stress and time involved in classifying thousands ofliving organisms.
Proposed Business and Marketing Strategy for Recovering Kb Kupu-Kupu and Tk Harapan Bunda after Pandemic

KB Kupu-Kupu and TK Harapan Bunda are early childhood education institutions located in Sepinggan Pratama Complex, Balikpapan, East of Kalimantan. Since the Covid-19 pandemic, they suffer from the declining number of students in the school. This research intended to find the internal and external factors which are affected the performance of KB Kupu-Kupu and TK Harapan Bunda. The internal factors are obtained by analyzing the general environment, industrial environment, and competitor analysis. The resource analysis and value chain analysis were performed to obtain the internal factors. This research employed a qualitative approach. The primary data were collected through observation and interviews. While secondary data are collected through reports, journals, news, brochure, article, website, and social media. The novelty of this research is the utilization of the Holistic Marketing approach, everything matters connected with resources and activities. The SWOT quantification was performed to choose the significant factors of strength, weakness, opportunity, and the threat of KB Kupu-Kupu and TK Harapan Bunda, and to assess the dominant factors which determined the appropriate corporate strategy. The TOWS matrix was performed to formulate the functional strategies. Based on the analysis, the appropriate corporate strategy for KB Kupu-Kupu and TK Harapan Bunda is growth, the proposed business strategy is differentiation, and marketing strategies are proposed through the 4P marketing mix (Product, Price, Promotion, and Place).