Reviewerly/exHarmony huggingface dataset:
Loop Selection for Multilevel Nested Loops Using a Genetic Algorithm

Loop selection for multilevel nested loops is a very difficult problem, for which solutions through the underlying hardware-based loop selection techniques and the traditional software-based static compilation techniques are ineffective. A genetic algorithm- (GA-) based method is proposed in this study to solve this problem. First, the formal specification and mathematical model of the loop selection problem are presented; then, the overall framework for the GA to solve the problem is designed based on the mathematical model; finally, we provide the chromosome representation method and fitness function calculation method, the initial population generation algorithm and chromosome improvement methods, the specific implementation methods of genetic operators (crossover, mutation, and selection), the offspring population generation method, and the GA stopping criterion during the GA operation process. Experimental tests with the SPEC2006 and NPB3.3.1 standard test sets were performed on the Sunway TaihuLight supercomputer. The test results indicated that the proposed method can achieve a speedup improvement that is superior to that by the current mainstream methods, which confirm the effectiveness of the proposed method. Solving the loop selection problem of multilevel nested loops is of great practical significance for exploiting the parallelism of general scientific computing programs and for giving full play to the performance of multicore processors.
Pengembangan Multimedia Interaktif Berbasis Ispring Suite 8 sebagai Media Pembelajaran Pada Mata Pelajaran Praktikum Akuntansi Lembaga

In a learning activity, learning media has a very important function for the learning process in the classroom. Through technology development, sophisticated ICTs make a major contribution to the world of education needed for learning media. One interactive multimedia application software that can be used is Ispring Suite 8, which can make the material more interesting and interactive based on flash. In the accounting expertise program and financial institutions additional subjects that must be learned by students, namely practicum of accounting institutions. Therefore it is necessary to develop multimedia for the subjects of institutional accounting practicum. This research belongs to the development research with the ADDIE development model. The feasibility of this interactive multimedia can be known by looking at the results of the validation of the experts while to find out the opinions of students related to the media developed, limited trials were conducted on 20 students of class XI Accounting and financial institutions. The results of the validation of the material experts and media experts showed an average percentage of 90.11% classified as "very feasible" criteria. Then based on a limited trial conducted by students showing a positive response with an average percentage of 90% classified as "very good" criteria. Providing interactive multimedia that is developed can be recommended to be very useful for learning activities on the subjects of practicum accounting institution.
DPVI: A Dynamic-Weight Particle-Based Variational Inference Framework

The recently developed Particle-based Variational Inference (ParVI) methods drive the empirical distribution of a set of fixed-weight particles towards a given target distribution by iteratively updating particles' positions. However, the fixed weight restriction greatly confines the empirical distribution's approximation ability, especially when the particle number is limited. In this paper, we propose to dynamically adjust particles' weights according to a Fisher-Rao reaction flow. We develop a general Dynamic-weight Particle-based Variational Inference (DPVI) framework according to a novel continuous composite flow, which evolves the positions and weights of particles simultaneously. We show that the mean-field limit of our composite flow is actually a Wasserstein-Fisher-Rao gradient flow of the associated dissimilarity functional. By using different finite-particle approximations in our general framework, we derive several efficient DPVI algorithms. The empirical results demonstrate the superiority of our derived DPVI algorithms over their fixed-weight counterparts.
Social and Psychological Adaptation First-year University Students in the Conditions of Distance Learning

О. А. Андриенко (Орск, Россия
An augmented wavelet reconstructor for atmospheric tomography

Atmospheric tomography, i.e., the reconstruction of the turbulence profile in the atmosphere, is a challenging task for adaptive optics (AO) systems for the next generation of extremely large telescopes.Within the AO community, the solver of first choice is the so-called Matrix Vector Multiplication (MVM) method, which directly applies the (regularized) generalized inverse of the system operator to the data.For small telescopes this approach is feasible, however, for larger systems such as the European Extremely Large Telescope (ELT), the atmospheric tomography problem is considerably more complex, and the computational efficiency becomes an issue.Iterative methods such as the Finite Element Wavelet Hybrid Algorithm (FEWHA) are a promising alternative.FEWHA is a wavelet-based reconstructor that uses the well-known iterative preconditioned conjugate gradient (PCG) method as a solver.The number of floating point operations and the memory usage are decreased significantly by using a matrix-free representation of the forward operator.A crucial indicator for the real-time performance are the number of PCG iterations.In this paper, we propose an augmented version of FEWHA, where the number of iterations is decreased by 50% using an augmented Krylov subspace method.We demonstrate that a parallel implementation of augmented FEWHA allows the fulfilment of the real-time requirements of the ELT.
An android-based mobile educational game for disaster preparedness: an input to risk reduction management

&lt;span lang="EN-US"&gt;The Philippines is one of the countries in the world who suffers in different disasters, particularly natural disasters. Every year, there are more than twenty incidents recorded in the country related to different disasters which involve numerous lives of its citizens. It is found that most Filipinos have lack of knowledge in terms of disaster preparation specially, teenagers. This paper intended to develop a mobile-based game that aims to spread awareness on what to do during disasters. Upon development, forty-five (45) respondents were chosen to test the reliability of the application which composed of elementary students, household owners, police officers, fire fighters and IT experts. Further, ISO 25010 was adapted and modified in assessing the project. The results showed that the application is strongly acceptable and gives appropriate output in terms of disaster preparation garnering a total mean of 3.83&lt;br /&gt;&lt;/span&gt;
Sentimental Analysis of Product Review Data using Deep Learning

A significant undertaking of Natural Language Processing is sentimental analysis. It can be used to identify an individual's expression towards something. In this paper, we aim to tackle the problem of sentiment polarity categorization, which is one of the fundamental problems of sentiment analysis. A very important issue in sentimental analysis is to estimate the extremity arrangement that decides if a review is positive, negative or unbiased. A general process for sentiment polarity categorization is proposed with detailed itemized measure portrayals. Information utilized in this study are online item audits gathered from Amazon.com. Experiments for both sentence-level categorization and review-level categorization are performed with promising outcomes. Sentimental categorization has gained much traction in recent times.
Fraud Detection in Credit Cards with Machine Learning

Online transactions have increased dramatically in this new 'Social-distancing' era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking of sensitive information related to the credit card which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding Credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used Decision tree, XGBOOST, k-nearest neighbour, Logistic-regression, Random forest and SVM on a dataset inwhich there are transactions done online mode using Credit cards.We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.
Grammatical Errors in English Informal Essays by The Sixth Semester of English Literature Students

This research focused on Dulay's and Richard's theories about grammatical errors. This research purposed to (1) describe grammatical error types in English informal essay were made by the sixth semester of English Literature students in Makassar Islamic University and (2) find grammatical error causes in the informal essay were made by the sixth semester of English Literature students in Makassar Islamic University. The researcher used qualitative methods to analyse the types of error in students' questionnaires and essays based on Dulay's theory: omission, addition, misformation, and misordering. Meanwhile, the researcher also found error causes by Richard's theory, namely, interference, overgeneralization, ignorance of the rule restriction, incomplete rule restriction, and false concept hypothesized. This research demonstrated 210 errors in students' questionnaires and essays. First, fifty-two errors in omission: twenty-nine errors in the omission of the auxiliary verb, three errors in the omission of the ordinary verb, six errors omission of the noun, eight errors in the omission of a plural noun, two errors in the omission of gerund noun and four errors in the omission of the preposition. Second, ninety-three errors, in addition, those were: twelve errors in double marking, fifty-one errors in regularization, and thirty errors in simple addition. Third, fifty-one errors in misinformation last were fourteen errors in misordering, which were found in interference, overgeneralization, ignorance of the rule restriction, incomplete rule restriction, and false concept hypothesized.&#x0D; Keywords: Grammatical, Error, Informal Essays.
Encrypted Traffic Identification by Fusing Softmax Classifier with Its Angular Margin Variant

Encrypted traffic identification is to predict traffic types of encrypted traffic. A deep residual convolution network is proposed for this task. The Softmax classifier is fused with its angular variant, which sets an angular margin to achieve better discrimination. The proposed method improves representation learning and reaches excellent results on the public dataset.
DEVELOPMENT OF METHOD TO IDENTIFY THE COMPUTER SYSTEM STATE BASED ON THE «ISOLATION FOREST» ALGORITHM

Context. The problem of identification a computer system state was investigated. The object of the research is the identification process of the computer system state. The subject of the research is computer system state identifying means and methods.&#x0D; Objective. The purpose of the work is to develop a method for identifying the computer system state.&#x0D; Method. The method has been developed for identifying a computer system state based on integrated use the procedure for grouping unlabeled initial data and using machine learning technology based on the «Isolation Forest» algorithm, which provides to identify a computer system state and to distinguished the process name that initiated the abnormal state. Therefore, for collecting statistical data in the form of operating system functioning events, data method has been proposed and developed along with software. The analysis of functioning events has been performed. The result of analysis showed that the most informative are read and write operations. To set up a single dataset, read and write operations compared with the process name and combined into one array of event groups, so that it is possible to single out the process that causes the abnormal state of the computer system. As a result of the research, the «Isolation Forest» algorithm has been selected as a component of the method for identifying the computer system state. An accuracy and efficiency assessment of the developed method of identifying a computer system state has been carried out.&#x0D; Results. The developed method is implemented and investigated when solving the problem of identifying anomalies in the functioning of computer systems.&#x0D; Conclusions. The experiments carried out confirmed the efficiency of the proposed method. It allows us recommended the method for practical use in order to improve efficiency of identifying the computer system state and use it as an express method. Areas for further research may lie in the creation of the ensemble of fuzzy trees based on the proposed method and optimization of this software implementation.
The role of strategic innovation for sustainability of businesses during the covid-19 pandemic

This study aimed to know the role of strategic creativity in the sustainability of business in the Jordanian tourism sector in the shadow of the Corona pandemic, in addition to knowing the impact of its growth and what is the level of strategic creativity in the Jordanian tourism sector. The study population may consist of all employees of tourism companies in Jordan with all their services, and a questionnaire was created in order to achieve the aim of the study. The study used the analytical, descriptive, quantitative approach, whereby a random sample (319) respondents were distributed. After analyzing the study, the results showed that the level of strategic creativity in the Jordanian tourism sector is high, and that strategic innovation has an impact on the sustainability of businesses in that sector. The study recommended the necessity of supporting the Research and Development Department as a strategy for tourism companies to get out of the Corona pandemic.
Academic Staff in the Context of Known Theories of Motivation

Purpose:The main goal of the research is to identify the motivators used in the work of public university employees in relation to known theories of motivation, and to determine the importance of individual motivators for their involvement in work.Design/methodology/approach: The article uses qualitative research with the participation of experts and quantitative research using a survey among academic staff.Data analysis was made in the context of three theories of motivation and a simplified structure of the studied motivators was established during the analysis of factors.Findings: The research results indicated that motivators connected with the theory of selfdetermination (SDT) and Herzberg's theory (HT) are of the greatest importance for the involvement of academic staff in Polish universities.Motivators that result from the internal motivation of an academic staff member should be most often used in universities.The most important for scientists are motivators regarding mutual internal relations (superiors, colleagues, administration) or organization of working time and job security.In another important motivating group for academic staff, there were motivators related to funding scientific research and access to knowledge.Practical Implications: Applying an appropriate motivation system in universities is not possible without knowledge of the theory of motivating people.A properly applied motivator can improve the effectiveness of scientists' work, which in turn increases the ranking of universities in terms of competitiveness with others.Therefore, it is important to construct an appropriate incentive system, adequate to the needs and capabilities of employers, and at the same time meeting the expectations of employees.Originality/value: The article presents an attempt to match the identified motivators to individual motivation theories.In addition, the importance of individual motivators in relation to these theories and their application was determined.
The Effects of Mind Maps on Computational Thinking

Her research is centered around metamorphic relations ranking for reducing testing costs in scientific software.Safia's research interests expanded to include computer science education after observing
AI and Machine Learning

Film, television, and streaming delivery of news, sports, and entertainment—along with the associated media asset management, production, and distribution processes—are increasingly information-heavy. Such volume of data makes applications for machine learning (ML) and artificial intelligence (AI) even more important.
INFORMATION TECHNOLOGIES IN A TODAY'S MUSEUM'S VIRTUAL COMMUNICATION

The author traces historical evolution of philosophical and scientific views on a concept “virtual”, notices that academic though of our days defines virtual communication as a type of information exchange run through telecommunication systems. The paper argues the point that digitalization of museum environment lets to practice innovative approaches to preservation and popularization of objects of historical and cultural heritage by means of museum work with the use of special program and technological measures. The review of the today's computer­based forms of museum communication getting widespread in work of leading museum institutions of Russia and a number of foreign countries is given.
MACH PRINCIPLE AND PRINCIPLE OF RELATIVITY

The article considers the “many-faced” Mach principle and the principle of relativity, which are organically related due to the unity of nature, and provides a brief historical overview of the primary sources of these principles. Ernst Mach formulated his principle by criticizing Newtonian mechanics in his book [1] in 1896. A. Einstein, first using the term “Mach principle” in 1918, wrote that the general theory of relativity is based on three main points, one of which was the Mach principle [2. P. 613]. Currently, Mach principle is used as one of the three main provisions of the relational theory of Yu.S. Vladimirov [3]. The article also describes A. Einstein’s thought experiment from the article “Is there a gravitational effect similar to electrodynamic induction?” [2. P. 223] and about numerous experiments based on various physical principles, with the aim of checking Mach principle.
Students’ Acceptance of Teaching Interaction through the Diversity of Media in M-Learning

The technological and telecommunication development of this decade has had a profound impact, especially on the education system. In relation to this development, mobile technology in learning or M-learning is a new concept in the learning process. Examples of portable technology include PDAs (Personal Digital Assistants), Smartphones, iPads, Tablets, and more. Thus, the availability of these advanced technologies promotes an environment of m-learning among students as it is easy to carry, lightweight, and not burdensome. Through the applications of Google, Facebook, YouTube, Edmodo, Twitter, WhatsApp, and Instagram, information is available anytime and anywhere and to anyone. The objectives of this study were to identify the level of students’ knowledge of m-learning, identify students’ perceptions of m-learning, identify the applicability of students' application to m-learning and identify the relationship between students' level of knowledge and applications usage of m-learning. This questionnaire was used in the data generation, which was analyzed descriptively by using statistical Package for the Social Version 20 (SPSS Statistic 20). The respondents of this study were 204 students in the first year of Faculty Technical and Vocational Education. The finding of the study showed that the use of m-learning in the teaching and learning process has a positive impact which had a min value of 4.00 and above. Besides, this study showed that the use of m-learning is highly recommended as it provides a more engaging learning experience for students. Researchers have suggested that its use of m-learning includes urban and rural students in line with the government's goal of developing an innovative and competitive convergence-based generation.
Nexus among Trust, Job Satisfaction, and Affective Organizational Commitment: A Developing Country Perspective

The organizational commitment of employees plays a vital role in the success of any business. In the era of competition, companies are struggling to retain the employees committed to the organizations. There is a scarcity of research to investigate the factors that influence effective organizational commitment in a developing country. The researcher conducted a survey to collect data from employees working in the banking sector of Pakistan. The present study utilized the convenience sampling method to get responses. A total of 300 questionnaires were distributed, from which 215 responses were received, where 15 questionnaires were found partially filled, which were discarded for further analysis. The 200 questionnaires proceeded for statistical analysis using the partial least square structural equation modeling (PLS-SEM) technique. The software of SmartPLS ver 3.0 was used to analyze the significance of hypotheses. Current research revealed the significant relationship between trust and affective commitment mediated through job satisfaction. The present study provides several theoretical and practical implications by extending social exchange theory and delivering guidelines to banks' human resource departments to build trust among employees, and gauging job satisfaction to increase affective organizational commitment.
Current challenges in the conditions of distance education: Inquiry based learning

The article highlights the relevance of using innovative teaching methods by means of modern digital tools and resources. The authors present the pedagogical capabilities of Go-Lab ecosystem (https://www.golabz.eu) for the implementation of Inquiry Based Learning (IBL), digital competence development and critical thinking of students. It is noted that this educational platform today has the largest collection of remote / virtual laboratories, educational applications, more than a thousand research learningenvironments (Inquiry Learning Space –ILS) for distance learning. This is especially relevant in the modern era of the spread of the coronavirus pandemic, because the platform provides interesting resources to motivate students to learn, stimulate their cognitive interests and develop social skills.The advantages of virtual / remote laboratories in working with students, as opposed to traditional learning, including in inclusive education, are described. The stages of a holistic research cycle on the Go-Lab portal are described: orientation, conceptualization, research, conclusions and discussion. Examples of some ILSs for active online experimentation, self-study, development of research skills, group work, etc. are given. Emphasis is placed on the need for teachers to create their own virtual lesson using laboratories and Go-Lab educational applications. The criteria for evaluating the quality of ILS on the Go-Lab portal are presented.