Reviewerly/exHarmony huggingface dataset:
Deriving the COVID-19 Formula from any Graph

Most of the graphics published about the COVID-19 have exponential behavior.A lot of them have been driven with only the data given by government institutions.In this paper, the authors attempt to describe a general procedure to convert any group of data into a graph, where the application of the Least Square Method can provide a mathematical formula that can be used for different situations and purposes including improving the current graphs of the disease.
Corpora-based Password Guessing: An Efficient Approach for Small Training Sets

Password guessing plays an important role in studying the vulnerability of passwords to improve security. In modern password guessing methods, the patterns of passwords from users in specific regions are discovered from a large number of leaked passwords. Most traditional methods, such as PCFG, Markov process, and other deep learning methods rely only on the training set. Different from other application areas of machine learning, the training set of password guessing comes from leaked real password sets, such as Rockyou, CSDN, and VK. Traditional approaches of password guessing are effective for large-scale training sets. However, the size of leaked password sets leaked by users of small languages or users of specific organizations is very small, which makes it difficult for current password guessing methods which relying only on training sets to discover enough words in passwords. In order to solve this problem, this paper proposed a corpus-based password guessing method. First, we analyzed the common words and their categories in the leaked password sets from users in three different countries. On this basis, we proposed an organization method for multiple language corpora, and constructed corpora of more than 3 million words. Secondly, we improved the traditional PCFG password segmentation method and described password structure based on corpora. Third, we evaluated the probability of words in the corpora which are not appearing in the training set based on the Lapalace smoothing. Actual tests show that our method can produce a finer structure than the PCFG. When the size of the training set decreases, the cracking rate of the PCFG decreases significantly, while the impact of our method is not significant, and the cracking rate is significantly higher than that of the PCFG.
Impact of COVID-19 Crisis on Knowledge Management Practices in Sultanate of Oman

This research was conducted with the aim of identifying various changes made to knowledge management (KM) practices implemented by organizations in the Sultanate of Oman following the onset of the COVID-19 crisis. Further, the study focused on identifying the impact of those changes on various aspects of human resources management. Snowball and purposive sampling techniques were used to collect relevant data from 110 line managers in various organizations in the Sultanate of Oman. Data were analyzed using descriptive statistics and Chi-squared and post-hoc tests. The Bonferroni correction method was adopted to reduce the risk of Type I error. The findings indicated that organizations started utilizing an inside-out approach to KM after the COVID-19 crisis began, shifted KM process from manual to computer-based and spending from conventional to e-KM activities. Key finding is that the organizations demonstrated an increased dependency on internal knowledge sources. In addition, line managers began measuring the effectiveness of KM practices, a metric which had been mostly neglected in the pre-pandemic period. Perceived benefits of these changes included increased employee motivation and engagement, increased employee learning and job-related skill, along with an enhanced knowledge-sharing culture across the organization. Important measures taken to mitigate the perceived negative impact of these changes, or enhance the perceived positive impact, included consistent persuasive communication with employees and identifying alternate financial resources to support KM activities. This research contributes to the field of KM and projects it as a supportive discipline to effective crisis management. Findings of this research can help in identifying the areas of training and improvements in the KM framework. This research is global and topical in nature as it relates to the e-KM practices during the ongoing global COVID-19 crisis and portrays the changing e-learning scenario in the organizations in Oman, one of the prominent countries in the middle east and represents the middle east regional culture and economy.
The Menzerath-Altmann law as the relation between lengths of words and morphemes in Czech

Abstract It is shown that the mean morpheme length (measured in phonemes) decreases with the increasing length of word types (in morphemes) in Czech texts, i.e., these language units behave according to the Menzerath-Altmann law. The law is not valid in general for word tokens. Some hints towards an interpretation of parameters are presented.
Facets of interaction between the Ministry of National Education and the Ministry of Culture of France in the musical and educational space

The problem of research. The relevance of the research is due to the urgent need to find new approaches to the musical development of students in general education, which makes it significant to refer to the experience of France in connection with the existence in the country of an original model of musical education with an established system of multifaceted partnerships controlled by the bodies of the Ministry of National Education and the Ministry of Culture of France. The purpose of the article: scientific and practical justification of the need to develop a Russian strategy of musical development based on the interaction of educational and cultural organizations. Materials and methods. As a methodological basis, a system-structural approach was used, which made it possible to conceptualize the data obtained as a result of the analysis of sources, as well as in the process of personal communication with French colleagues. The results of the study. The mechanism of the studied interaction in various forms of educational, extracurricular and out-of-school musical activities is based on a clearly structured scheme of cooperation between schools and partner structures in the field of culture and art at the state (conceptual), academic (coordination) and local (performing) levels. The impetus for the construction of this system of partnerships was the recognition by the pedagogical community and the authorities of France of the priority of musical education as a powerful stimulant for the development of personal, intellectual and creative abilities of students necessary for successful implementation in any field of activity. Discussion and conclusion. The initial impulse to the emergence of the concept of attracting artistic and cultural structures in the musical and educational field was the introduction in the early 80s of the twentieth century of the original system of professional and amateur musical training of students in the framework of general education in college and lyceum. In the future, the experience of partnership interaction in the field under study gradually spread not only to academic, but also to extracurricular and out-of-school activities. As an important "breakthrough" of the French musical and educational project, a significant contribution to the educational activities of musical and cultural centers of global importance should be recognized. The far-sighted policy of the French authorities aimed at substantial support of artistic, especially musical culture as the basis for the development of the whole society can serve as a strategic guideline for the modernization of the music education system in Russia in terms of developing management schemes and educational technologies based on the interaction of educational institutions with cultural and art institutions.
Overview of cryptographic algorithms for audio files and their properties

Any cryptographic algorithm that is claimed to be effective must be properly analysed to prove its effectiveness, reliability and security. In this paper the most used quality indicators are reviewed and classified. The principles of the audio encryption are reviewed. A classification of the analysing methods is made.
Blockchain logging for process mining: a systematic review

Considerable progress was forcasted for collaborative business processes with the rise of blockchain programmable platforms.One of the saliant promises was auditable traces of business process execution, but practically it has posed challenges specially with regard to blockchain logs' structure who turned out to be inadequate for process mining techniques.Approaches to answer this issue have started to emerge in the literature; some focusing on the creation process of event logs, and others dealing with their retrieval from the blockchain.This work outlines the generic steps required to solve these challenges and analyzes findings in these approaches with a consideration for efficiency and future research directions.
DCEM: An R package for clustering big data via data-centric modification of Expectation Maximization

Clustering is intractable, so techniques exist to give a best approximation. Expectation Maximization (EM), initially used to impute missing data, is among the most popular. Parameters of a fixed number of probability distributions (PDF) together with the probability of a datum belonging to each PDF are iteratively computed. EM does not scale with data size, and this has hampered its current use. Using a data-centric approach, we insert hierarchical structures within the algorithm to separate high expressive data (HE) from low expressive data (LE): the former greatly affects the objective function at some iteration i, while LE does not. By alternating using either HE or HE+LE, we significantly reduce run-time for EM. We call this new, data-centric EM, EM*. We have designed and developed an R package called DCEM (Data Clustering with Expectation Maximization) to emphasize that data is driving the algorithm. DCEM is superior to EM as we vary size, dimensions, and separability, independent of the scientific domain. DCEM is modular and can be used as either a stand-alone program or a pluggable component. DCEM includes our implementation of the original EM as well. To the best of our knowledge, there is no open source software that specifically focuses on improving EM clustering without explicit parallelization, modified seeding, or data reduction. DCEM is freely accessible on CRAN (Comprehensive R Archive Network).
Explainable Artificial Intelligence For Robot Arm Control

In this paper, we investigate reinforcement learning model explainability through a pick and place task.Two robots with three degrees of freedom learned to solve the pick and place task in simulation as well as reality.To investigate the explanatory factors implicitly learned by the models, we derive robot parameters, i.e., the length of the robot segments.To overcome the black box nature of reinforcement learning models and provide a physical explanation of the results, the robot dimensions are derived from the learned reinforcement learning model and compared to the real dimensions.The hypothesis in the presented work is that converged reinforcement learning models must learn the robot parameters implicitly in order to learn a task.This transforms black box models into white box models, where each model's decisions can be interpreted.Our experiments show that robot parameters can be derived from learned models and that the chosen reinforcement learning model implicitly learns physical context.In order to create robust and trustworthy AI systems for intelligent factories, we suggest that a physical interpretation of all black box models must be done.
COUNTING GAME APPLICATION FOR KINDERGARTEN CHILDREN

Problems The development of Information Technology plays an important role in human life. With the development of Information Technology, humans can easily get information and humans can easily carry out daily activities with the help of existing technology. Technology brings people to see the outside world further, open their minds to think, and build creativity to create new things, one of the technologies that is currently developing very rapidly is smartphone-based technology, especially Android. Many android applications are very helpful at this time such as health applications, transportation and there are also educational games. Educational games can make it easier to learn, sometimes when learning someone will be faced with conditions where it is difficult to understand the lesson, so with the educational game it is hoped that it can help users understand the lessons in the game, besides that educational games are a very fun learning tool for students. , because students will be happier and easier to understand by playing while learning
Improving Students' Independent Work under Teacher's Supervision during Foreign Language Learning at the University

Studying foreign languages contributes to introducing future specialists to universal humanitarian values, confident inclusion into the global community and successful professional adaptation.First-class higher education is instrumental in achieving this goal.The study deals with the techniques of improving the structure of the students' independent work under the teacher's supervision when studying a foreign language in a technical university.Factual material can be applied in the analysis of the methods used to organize the students' independent work with the teacher and contribute to the students' increased interest in additional education that will expand the students' horizons and promote the development of the diagnostic thinking process.The study provides the basis for giving several recommendations for improving the structure of the students' independent work on the foreign language under the teacher's supervision: apply modern innovative methods that activate the students' cognitive activity; implement the technique of organizing the students' independent work on the foreign language under the teacher's supervision and the algorithms for its application.
Analysis of the main activities of regional teachers associations

Introduction. Regional pedagogical associations are a mechanism of teachers' professional development, their creative growth, competence enhancement. The research purpose was to analyze the areas of regional teachers association's activity, to identify the most important and interesting types of work in professional communities. Materials and methods. As part of the study, the experience of regional pedagogical associations' work was analyzed and the main areas, forms and types of their activities were identified. A survey of primary school teachers in Nizhny Novgorod was carried out, in which 117 teachers with various work experience in school took part. Research results. Based on the survey results, it was determined that teachers consider the most important and interesting areas of the regional pedagogical association's activity the informational and advisory support of teachers (more than 75% of the respondents), raising the prestige and popularization of the teaching profession (more than 65%), professional development (more than 55%), exchange of work experience (over 65%), conducting scientific-educational events for schoolchildren and their parents (over 60%). The most significant types of the association's work are as follows: advising teachers in the field of protecting their rights and protecting the interests of the teaching community on topical issues of professional activity; informing teachers through the association's website about education-related documents and materials and ongoing activities; conducting master classes, open lessons and other events for the exchange of work experience by teachers. Discussion and conclusion. The teachers' assessment of the importance of areas of the pedagogical association's work can be used to develop indicators of efficiency of professional associations' activities.
The Effect of Academic Burnout of Elementary School Students on the Smartphone Game Addiction CRISIS: Mediating Effects of Anxiety and ADHD Tendency

Purpose: The purpose of this study was to examine and understand the effect of academic burnout of elementary school students on the smartphone game addiction and investigate as to what mediating effects of anxiety and ADHD tendency have in this process. Method: A survey was conducted targeting 654 elementary school students from two elementary schools in the capital area, and the levels of academic burnout, anxiety, ADHD tendency, and smartphone game addiction were surveyed. The collected data were analyzed based on the structural equation modeling (SEM). Results: The results were as follows. First, the academic burnout turned out to directly or indirectly increase the smartphone game addiction. Second, anxiety turned out to indirectly increase the smartphone game addiction, while the ADHD tendency directly increased the smartphone game addiction. Third, three pathways of academic burnout on the smartphone game addiction were verified, where the direct pathway of academic burnout → smartphone game addiction and the two indirect pathways of ‘academic burnout → ADHD tendency, → smartphone game addiction’ and ‘academic burnout → anxiety → ADHD tendency → smartphone game addiction’ turned out to be significant. Conclusion: The results of this study indicate that in order to prevent the smartphone game addiction of the elementary school students, the intervention for academic and emotional problems such as academic burnout, anxiety, and ADHD tendency ought to be conducted together.
Mobile Technologies in Education

The informatization of education is one of the priorities on the path to open education and is an indicator of the development of modern society. The use of information tools in education, including mobile technologies, creates conditions for the implementation of the educational process and ensures its continuity by integrating traditional and distance learning, which is especially relevant today, in quarantine times, when many educational institutions use distance or blended (combined) form of education. The aim of the article is to understand the notion of mobile education and its influence on current development of educational processes in higher educational institutions in Ukraine.
An Integrated Framework for the Performance Evaluation of Fruits and Vegetable Store Located in a Supermarket

The quality of fruits and vegetable stores should be maintained with high priority for customer satisfaction. The performance evaluation of fruits and vegetable store located in a supermarket is a big challenge for the managerial personnel of the supermarket. In this paper, a new performance evaluation framework is proposed for the fruits and vegetable store located in a supermarket. The criteria for performance evaluation have been found out in a hierarchical structure through a brainstorming session among the experts. The 4 top-level criteria are storage, processing, sales and transport. These 4 top-level criteria are broken into 9 lower-level criteria. Fuzzy AHP is used to calculate the weights of criteria for each level of the hierarchy. Fuzzy TOPSIS generally ranks the alternatives. An improved fuzzy TOPSIS, which is named fuzzy k-TOPSIS, is proposed here to find out the rank as well as classification of the stores of fruits and vegetables. The proposed framework is demonstrated here with a case study for a better understanding of the complete framework.&#x0D; HIGHLIGHTS&#x0D; &#x0D; The proposed framework integrates Fuzzy Set Theory, Analytic Hierarchy Process (AHP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and k-means clustering for the performance evaluation of fruits and vegetable store located in a supermarket&#x0D; The main contribution of this paper is that the proposed framework not only ranks the alternative fruits and vegetable stores but also does a classification among the alternative fruits and vegetable stores based on their performance&#x0D; The proposed framework is demonstrated here with an illustrative example, which includes 24 stores of fruits and vegetables, 9 criteria, and the expert’s committee of 3 members&#x0D; The proposed framework can also be used in other Multi-criteria Decision Making (MCDM) problems&#x0D; &#x0D; GRAPHICAL ABSTRACT
Detecting Speaker Personas from Conversational Texts

Personas are useful for dialogue response prediction.However, the personas used in current studies are pre-defined and hard to obtain before a conversation.To tackle this issue, we study a new task, named Speaker Persona Detection (SPD), which aims to detect speaker personas based on the plain conversational text.In this task, a best-matched persona is searched out from candidates given the conversational text.This is a many-to-many semantic matching task because both contexts and personas in SPD are composed of multiple sentences.The long-term dependency and the dynamic redundancy among these sentences increase the difficulty of this task.We build a dataset for SPD, dubbed as Persona Match on Persona-Chat (PMPC).Furthermore, we evaluate several baseline models and propose utterance-to-profile (U2P) matching networks for this task.The U2P models operate at a fine granularity which treat both contexts and personas as sets of multiple sequences.Then, each sequence pair is scored and an interpretable overall score is obtained for a context-persona pair through aggregation.Evaluation results show that the U2P models outperform their baseline counterparts significantly.
Visual error correction of continuous aerobics action images based on graph difference function

Abstract In order to solve the problem of the easy appearance of blurring images (easy to appear blur) or jagged effect after correction by traditional method, and as the visual error correction effect is not good, we propose a new visual error correction method of continuous calisthenics action image and a new algorithm for visual error correction. The continuous calisthenics action image is encoded and decoded, the error between the original image and the error image is obtained and with that the difference function is processed. Then the error compensation results are obtained and the visual error correction of the continuous calisthenics action image is realised. At the same time, a new algorithm for checking and correcting visual parallax matching errors is proposed in this paper. This algorithm can not only identify all matching errors in the parallax data, but also detect and correct them according to the continuity of shape representation, and effectively calculate the various performances of such matching algorithms automatically and quantitatively. The results show that the image processed by the proposed method has no significant visual error, and the peak signal-to-noise ratio and structural similarity are very high. The experimental results of the new algorithm also prove that the algorithm is very useful for the study of visual matching. It can be seen that the proposed method is effective and can be effectively used.