Reviewerly/exHarmony huggingface dataset:
The Effect of Online Learning on The Academic Achievement Among Students of Jordanian Private Universities in Light of The Covid-19 Pandemic, Based on The Variables of Comprehension and Analysis from The Perspective of Faculty Member

The current study aimed to identify the impact of online learning on the academic achievement among students of private Jordanian universities in light of the COVID-19 pandemic. The study sample, which was a stratified random sample, consisted of (378) faculty members. Descriptive survey method was used in the current study. In order to achieve the objectives of the study, a questionnaire was developed, and its validity and reliability were verified. The results showed that the effect of online learning on the academic achievement among students of private Jordanian universities in light of the COVID-19 pandemic was average; results of the study also showed statistically significant differences at the significance level (a less or equal 0.05) according to the gender variable in favor of females, and no statistically significant differences according to either the type of college variable, or years of experience’ variables. In light of these results, the study recommended that private Jordanian universities pay great attention to online education, providing it with the appropriate infrastructure, because this may contribute to enriching the cognitive skills received, upgrading students' behavioral level, and actively contributing to improving students’ academic achievement.
Penanaman Karakter Siswa Melalui Ragam Bahasa dalam Kegiatan Pembelajaran Bahasa Indonesia

[STUDENT CHARACTER BUILDING THROUGH VARIOUS LANGUAGES ​​IN INDONESIAN LANGUAGE LEARNING ACTIVITIES]. This study aims to describe character planting through the variety of languages used in Indonesian language and literature learning activities in schools. Learning activities are activities that are dominated by the delivery of material by the teacher. In delivering the material, the teacher uses a variety of languages. Therefore, the use of various languages can also be used as a way to instill student character. The research method used in this research is descriptive qualitative. The location of this research is Triguna Utama Senior High School with the research subjects of class XA on Indonesian Language and Literature learning. The method of data collection was carried out by direct observation in learning activities and in-depth interviews with students and teachers as well as several parties involved in learning activities. Based on the analysis carried out, it can be concluded that in learning activities, the use of formal (formal), consultative, relaxed, and familiar modes are found. The use of various languages by the teacher is able to create various situations and contexts that take place in learning. The variety of languages used can also be used to instill student character both in the classroom environment and outside the classroom. When the teacher uses language with a polite choice of words, students will also follow. Likewise in other contexts when the teacher chooses to use a variety of familiar languages, students will also follow the familiar language choice.
Indexing algorithm based on storing additional distances in metric space for multi-vantage-point tree

Introduction: The similarity search paradigm is used in various computational tasks, such as classification, data mining, pattern recognition, etc. Currently, the technology of tree-like metric access methods occupies a significant place among search algorithms. The classical problem of reducing the time of similarity search in metric space is relevant for modern systems when processing big complex data. Due to multidimensional nature of the search algorithm effectiveness problem, local research in this direction is in demand, constantly bringing useful results. Purpose: To reduce the computational complexity of tree search algorithms in problems involving metric proximity. Results: We developed a search algorithm for a multi-vantage-point tree, based on the priority node-processing queue. We mathematically formalized the problems of additional calculations and ways to solve them. To improve the performance of similarity search, we have proposed procedures for forming a priority queue of processing nodes and reducing the number of intersections of same level nodes. Structural changes in the multi-vantage-point tree and the use of minimum distances between vantage points and node subtrees provide better search efficiency. More accurate determination of the distance from the search object to the nodes and the fact that the search area intersects with a tree node allows you to reduce the amount of calculations. Practical relevance: The resulting search algorithms need less time to process information due to an insignificant increase in memory requirements. Reducing the information processing time expands the application boundaries of tree metric indexing methods in search problems involving large data sets.
Application of the z39.50 protocol in distributed information systems

To date, the most effective way to solve the problems of organizing access to distributed information resources is to organize information about them in information systems, denounced in the form of electronic libraries. The article describes the search for terms in the thesaurus and the algorithm for constructing a term tree based on abstract access to the thesaurus, organized in accordance with the Zthes profile of the Z39.50 protocol
Permutation Reconstruction From a Few Large Patterns

Every permutation of rank $n \geqslant 5$ is reconstructible from any $\lceil n / 2 \rceil + 2$ of its $(n-1)$-patterns.
An Analysis of English Education Students’ Morphological Awareness (Morpheme Identification and Structure Awareness)

This study aims to describe English Education Students’ morpheme identification awareness, morpheme structure awareness, and overall morphological awareness. This research employed descriptive quantitative method. The samples of this research involved the whole sixth semester students of English Study Program IAIN Curup which consisted of 51 students who had taken morphology subject in previous semester. The data were taken by giving the students a Morphological Awareness Test (MAT) which consists of Morpheme Identification Awareness test (MIAT) and Morpheme Structure Awareness test (MSAT). The results showed that the average score obtained in MIAT was 70,84 % in percentage, and the average score obtained in MSAT was 67,32 % in percentage. So, it can be concluded that both students’ morphological identification and structure awareness were in enough category. Then, students’ morphological awareness which was calculated from both MIAT and MSAT was also categorized as enough, 69,08% in percentage. From the overall average score, it was found that there were only 2 students who had very good morphological awareness. For good category, there were 18 students. Meanwhile, there were 19 students in enough category, and 12 students had low morphological awareness.
A Blockchain based Algorithm for Electronic Voting System

The lack of fidelity in the present system of voting has made many researchers to advocate for a better system.This has resulted in developing peer-to-peer version of election voting system like the online voting system.This system would allow online voting to be done without the need of worrying about the authenticity of the result generated.This kind of digital signatures provide part of the solution, but the main benefits are lost if the verification and counting of the votes are entrusted to an organization.This paper proposed a solution to the counting and result authenticity problem faced while using the peer-to-peer system of voting that must be manage by a single organization.The solution is the development of a blockchain based voting system to achieving optimal vote's fidelity in the election after voting.The network timestamps votes by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be altered without redoing the proof-of-work.
Methods of Using the Google Classroom Service in Teaching Historical Disciplines During Blended and Distance Learning

The article deals with the methods of using the Google Classroom service in teaching historical disciplines during blended and distance learning. The author of the article has come to the conclusion that with the help of distance education technologies it is not only possible to put a number of routine pedagogical activities on a computer’s shoulders, but to organize really qualitative, individual, differentiated teaching. In the author’s opinion, in the Google Classroom service it is convenient and effective to work both for a teacher and a student/pupil, as the service provides the users with a generic working device, possesses a human-engineered interface and capabilities necessary for the participants of the educational process
Error analysis of the students’ English written descriptive text

Making errors is a natural process of learning. Writing as a productive skill is important for students to express their ideas. However, students conducted errors in the productive skills. Therefore, this study is intended to find out types of errors made by students in written English. This study employed the qualitative method where the Error Analysis was implemented. The subject of this study is students in first grade of SMAN 1 Abdya and the object of this study were the errors found in written English. The population of this research was all of students in first grade which consists of 208 students from all study programs where 25 % of the populations were taken as the sample. To collect the data, written tests were conducted. The written test shows the percentage of writing errors, including omission errors, which is 58.38%, misformation errors with a total of 16.48%, misordering error 13.89%, and addition of 11.26%. The errors were found when students omitted 'to be' as main verb. Second, students tend to add 'to' after modal auxiliaries such as 'can' or 'will'. Third, misformation errors happened when students could not form the verb correctly. Last, the misordering errors were produced when students put words randomly. Consequently, it was discovered that the errors made by students were impacted by their native language, and this is the interlanguage move.
Implementation of the PIECES Method in the Student Assessment System of SMPN 201 Jakarta

The development of technology has developed very rapidly along with the many human needs. Web technology systems are one of the most frequently used applications in everyday human life. Assessment in the learning process is important, so that good value data processing will produce report cards as a good evaluation result, besides that the results of value data processing will be used as one of the benchmarks for the success of students taking education in school. This study aims to implement the PIECES method at the stage of developing a student assessment system at SMPN 201 Jakarta in the form of a web application. PIECES analysis consists of Performance, Information, Economy, Control, Efficiency and Service. The conclusion of the research is that the application of a multi-user student assessment data system application at SMPN 201 Jakarta can improve work services and time efficiency in terms of processing student grade data. The student assessment data processing system using analysis using the PIECES method in a multi-user manner aims to make a computerized system in schools able to integrate all recording activities that are carried out manually and require office stationery (ATK) to be minimized.
CREATION OF A UNIFIED “SCHOOL – HOUSE” INFORMATION SPACE IN THE CONTEXT OF STUDENTS' ICT-CULTURE FORMATION IN THE EDUCATIONAL PROCESS

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AI for AEC: Open Data and VPL Approach for Urban Seismic Vulnerabilit

This contribution provides an overview of the VPL evolution and an application case concerning the classification of seismic vulnerability indices with AI.This research aims to contribute to the scientific debate on the use of these technologies in architecture, deepening the themes of seismic assessment on urban and territorial scale.The whole experimentation was conducted using only the potential of Grasshopper's VPL and possessing, as basic knowledge, the main concepts of machine learning and supervised learning.The VPL is therefore an effective tool to introduce and disseminate the topics and applications of artificial intelligence within the AEC sector, effectively decreasing the gap between domain experts and programmers.
Reply to reviewers of 'Dragonii dezvoltării: Revine istoria pe supercontinentul euroasiatic?'

The common denominator of some of the questions and problems raised by the reviewers is represented by the new technological revolution, the role of AI in this revolution, and their impact on the world today. No one doubts the fact that we are living the greatest transformation of the information environment since Gutenberg’s printing press. Nevertheless, as John Naughton emphasized, “we’re as clueless about where it’s heading and what’s driving it as the citizens of Mainz were in 1495” (Naughton, 2019). Four centuries have passed since then; during this time, the printing press shaped society and thinking, introduced new forms of communication, occasioned a massive improvement in the general population’s level of education, made public schools and the mass dissemination of knowledge possible. It radically influenced everything. Now, we are at the dawn of a new era, one which will lead to least as many transformations as print did.
Personnel training for high-tech industries in the system of lifelong education

At present the higher education system does not meet the employer’s requests. Therefore, the concept of lifelong education is becoming more and more relevant. One of the aspects of such education is a corporate university which not only provides the necessary knowledge to work for a particular company, but also improves general cultural skills. On the basis of expert interviews (N = 100) conducted in 2017–2019. it was considered as high-tech industries are ready to participate in personnel training in order to have well-trained employees and receive economic profit. Attention is also drawn to the current state of the professional education system. The experts’ opinion on the corporate education, as well as on the basic university departments as one of the forms of such education is pondered upon. The interview is also focused on the effectiveness of continuing education courses. Attention is paid to the problems of insufficient level of professional competencies facing the employers and the possibilities of overcoming them. The experts expressed their opinion on the changes that they would like to see in the professional education system. Possible options for the development of professional training for lifelong education were considered. The article focuses on the interaction between lifelong education institutions and high-tech industries which will help bridge the gap between the education system and real production.
Suitability of Single Image Super Resolution Models for Video Super Resolution

This project is an attempt to understand the suitability of the Single image super resolution models to video super resolution. Super Resolution refers to the process of enhancing the quality of low resolution images and video. Single image super resolution algorithms refer to those algorithms that can be applied on a single image to enhance its resolution. Whereas, video super resolution algorithms are those algorithms that are applied to a sequence of frames/images that constitute a video to enhance its resolution. In this paper we determine whether single image super resolution models can be applied to videos as well. When images are simply resized in Open CV, the traditional methods such as Interpolation are used which approximate the values of new pixels based on nearby pixel values which leave much to be desired in terms of visual quality, as the details (e.g. sharp edges) are often not preserved. We use deep learning techniques such as GANs (Generative Adversarial Networks) to train a model to output high resolution images from low resolution images. In this paper we analyse suitability of SRGAN and EDSR network architectures which are widely used and are popular for single image super resolution problem. We quantify the performance of these models, provide a method to evaluate and compare the models. We further draw a conclusion on the suitability and extent to which these models may be used for video super resolution. If found suitable this can have huge impact including but not limited to video compression, embedded models in end devices to enhance video output quality.
Development of the World Englishes Instructional Model to Enhance Students’ Listening Comprehension toward Varieties of English

This research aimed to develop the World Englishes instructional model to enhance students&amp;rsquo; listening comprehension of varieties of English. The student&amp;rsquo;s needs analysis was conducted in the first step of the study to gather data concerning the needs, problems, and opinions on teaching and learning English listening. Thirty students participated in the needs assessment questionnaire data collection by answering alternative and open-ended questions. Three experts evaluated the model&amp;rsquo;s quality was evaluated in terms of the consistency of its components and the appropriateness of its component descriptions. Based on the results of the needs assessment questionnaire and expert evaluation, three main elements&amp;mdash;students&amp;rsquo; needs analysis, theoretical concepts, and course components of the World Englishes instructional model&amp;mdash;were developed as instructional components comprising course objectives, course contents, media and materials, teaching strategies, and learning activities, as presented in this paper.
UEPF：A blockchain based Uniform Encoding and Parsing Framework in multi-cloud environments

The emerging of cloud data sharing can create great values, especially in multi-cloud environments.However, "data island" between different cloud service providers (CSPs) has drawn trust problem in data sharing, causing contradictions with the increasing sharing need of cloud data users.And how to ensure the data value for both data owner and data user before sharing, is another challenge limiting massive data sharing in the multi-cloud environments.To solve the problems above, we propose a Uniform Encoding and Parsing Framework (UEPF) with blockchain to support trustworthy and valuable data sharing.We design namespace-based unique identifier pair to support data description corresponding with data in multi-cloud, and build a blockchain-based data encoding protocol to manage the metadata with identifier pair in the blockchain ledger.To share data in multi-cloud, we build a data parsing protocol with smart contract to query and get the sharing cloud data efficiently.We also build identifier updating protocol to satisfy the dynamicity of data, and data check protocol to ensure the validity of data.Theoretical analysis and experiment results show that UEPF is pretty efficient.
Personality Traits and Individual Effectiveness: Moderating Role of Electronic Medical Records

This research investigates the impact of five traits of personality on individual effectiveness in Pakistani medical industry.The study also examines the moderating role of Electronic Medical Records (EMRs) among personality traits and individual effectiveness.Simple random and stratified techniques of sampling were utilized in the study, 413 respondents (doctors) were engaged as sample size.The different statistical methods like correlation, cronbach alpha, descriptive statistics, regression and moderated regression were employed in the study.The results indicated that personality traits (Agreeableness, conscientiousness, extraversion and openness to experience) have an influence on individual effectiveness.Neuroticism has no effect on individual effectiveness.The results also supported the moderating relationship among personality traits (eliminating neuroticism) and individual effectiveness.The present study is an excellent contribution in the current literature on individual effectiveness.
How does Victim Precipitation Theory explain Deviant Behaviours of Internet Romance Offenders? Gamer’s Perspective of Victim Precipitation

Internet romance fraud is a global canker with severe consequences to the victims ranging from significant financial loss, emotional trauma, to loss of life and property. The paper examines how internet romance offenders rationalize their deviant criminal behaviours and how these criminals use victim precipitation to commit internet romance fraud. The three dimensions of victim precipitation theory in this study are victim facilitation, victim provocation and victim openness. The research explains how internet romance offenders rationalize and justify their deviant behaviour. The data from this research model elicited 320 individual responses from hotspots associated with internet fraud activities. The findings from this study highlight the conditions under which victim precipitation theory dimensions in the context of internet romance fraud occur. The findings shows that offenders of internet romance fraud rely heavily on victim precipitation to perpetuate their criminal activities: all the three dimensions studied are used by these criminals as justification techniques to increases offenders’ predisposition to commit internet romance fraud. All three victim precipittion techniues ae used; victim openness, victim facilitation and victim provocation, respectively. This expands the boundaries of victim precipitation theory. The study contributes to new dimensions of victim precipitation in online romance fraud. This study has theoretical and criminology implications; and it gives a new perspective of how victims should conduct themselves in internet romance fraud cases. It also enriches the debate of victim precipitation in criminology discipline.&#x0D; Citation:Offei, M. O. (2021). How does Victim Precipitation Theory explain Deviant Behaviours of Internet Romance Offenders? Gamer’s Perspective of Victim Precipitation.&#x0D; International Journal of Technology and Management Research (IJTMR), Vol. 6 (2): Pp.59-72&#x0D; Received: March 3, 2021Accepted: September 1, 2021
Unsupervised Causal Binary Concepts Discovery with VAE for Black-Box Model Explanation

We aim to explain a black-box classifier with the form: "data X is classified as class Y because X has A, B and does not have C" in which A, B, and C are high-level concepts. The challenge is that we have to discover in an unsupervised manner a set of concepts, i.e., A, B and C, that is useful for explaining the classifier. We first introduce a structural generative model that is suitable to express and discover such concepts. We then propose a learning process that simultaneously learns the data distribution and encourages certain concepts to have a large causal influence on the classifier output. Our method also allows easy integration of user's prior knowledge to induce high interpretability of concepts. Finally, using multiple datasets, we demonstrate that the proposed method can discover useful concepts for explanation in this form.