Reviewerly/exHarmony huggingface dataset:
Analysis of Nutrition Knowledge and Weight Loss Strategies of Elite Athletes According to the Differences in Nutrition Knowledge of Coaches: A Pilot Study

This study was conducted to investigate the nutritional knowledge of elite domestic athletes and Coaches who conduct weight loss, and to identify differences in weight loss patterns and strategies according to nutritional knowledge. The subjects of the study were 16 incumbent Coaches registered as Coaches of the Korea Sports Council and 42 elite high school athletes registered as athletes under the same affiliation. The survey was conducted by translating the General Nutrition Knowledge Questionnaire (GNKQ), which consists of 88 items and 4 sections, and by using the SPSSWIN 24.0 program, a paired t-test, a correlation analysis, and a logistic regression analysis were performed. The statistical significance level of all data was set to p.05. Research shows that GNKQ is a Coaches (p.001) and athletes (p.022) both, there was a statistically significant difference between High rank and Low rank. Looking at the correlation analysis results, there was a statistically significant correlation in the teachers and athletes GNKQ (p.026), and as a result of the logistic regression analysis, the GNKQ scores of the athletes were confirmed to have a statistical significance during the weight loss period (p.035). Through this study, it was also possible to indirectly confirm the effect of the coaches
A Comparative Study on the Prediction of Fake Job Posts using Various Data Mining Techniques

In recent years, due to advancement in modern technology and social communication, advertising new job posts has become very common issue in the present world. So, fake job posting prediction task is going to be a great concern for all. Like many other classification tasks, fake job posing prediction leaves a lot of challenges to face. This paper proposed to use different datamining techniques and classification algorithm like KNN, decision tree, support vector machine, naive bayes classifier, random forest classifier , multi-layer perceptron and deep neural network to predict a job post if it is real or fraudulent. We have experimented on Employment Scam Aegean Dataset (EMSCAD) containing18000 samples. Deep neural network as a classifier, performs great for this classification task. We have used three dense layers for this deep neural network classifier. The trained classifier shows approximately 98% classification accuracy (DNN) to predict a fraudulent job post. Index Terms--false job prediction, deep learning, data mining.
An investigation of Hertzian contact in soft materials using photoelastic tomography

Hertzian contact of a rigid sphere and a highly deformable soft solid is investigated using integrated photoelasticity. The experiments are performed by pressing a styrene sphere of 15 mm diameter against a 44 x 44 x 47 mm$^3$ cuboid made of 5% wt. gelatin, inside a circular polariscope, and with a range of forces. The emerging light rays are processed by considering that the retardation of each ray carries the cumulative effect of traversing the contact-induced axisymmetric stress field. Then, assuming Hertzian theory is valid, the retardation is analytically calculated for each ray and compared to the experimental one. Furthermore, a finite element model of the process introduces the effect of finite displacements and strains. Beyond the qualitative comparison of the retardation fields, the experimental, theoretical, and numerical results are quantitatively compared in terms of the maximum equivalent stress, surface displacement, and contact radius dimensions. A favorable agreement is found at lower force levels, where the assumptions of Hertz theory hold, whereas deviations are observed at higher force levels. A major discovery of this work is that at the maximum equivalent stress location, all three components of principal stress can be determined experimentally, and show satisfactory agreement with theoretical and numerical ones in our measurement range. This provides valuable insight into Hertzian contact problems since the maximum equivalent stress controls the initiation of plastic deformation or failure. The measured displacement and contact radii also reasonably agree with the theoretical and numerical ones. Finally, the limitations that arise due to the linearization of this problem are explored.
MODEL INFOGRAFIK GASTRONOMI SASTRA INDONESIA UNTUK MENGEMBANGKAN KEMAHIRAN MEMBACA SASTRA SISWA SMA

Infographic currently used widely to expose the data, information, and knowledge visually. Thisstudy focuses on the preparation of a model infographic narrative to expose quotations themedgastronomic literature Indonesia. The research method is a research and development (Research&amp; Design / R &amp; D), with two stages of research. Two stages of the research was a preliminarystudy and design of products based on the preliminary study. Selection of Indonesian literaturegastronomic theme based on the analysis of the needs of the 70 high school students in EastJava, Jakarta, and West Nusa Tenggara which showed that they liked the themed infographicsgastronomic Indonesia, including the quotation of literature that discusses the relationship betweenfood and culture of Indonesia. Results from the initial needs analysis study showed that 95,89%repondents agreed that Indonesia infographic gastronomic literature as reading materials to developability of literary reading. The questionnaire result and principles of designing infographics areused to make two models of Indonesia infographic gastronomic literature.
VIDI: A Video Dataset of Incidents

Automatic detection of natural disasters and incidents has become more important as a tool for fast response. There have been many studies to detect incidents using still images and text. However, the number of approaches that exploit temporal information is rather limited. One of the main reasons for this is that a diverse video dataset with various incident types does not exist. To address this need, in this paper we present a video dataset — Video Dataset of Incidents, VIDI — that contains 4,534 video clips corresponding to 43 incident categories. Each incident class has around 100 videos with a duration of ten seconds on average. To increase diversity, the videos have been searched in several languages. To assess the performance of the recent state-of-the-art approaches, Vision Transformer and TimeSformer, as well as to explore the contribution of video-based information for incident classification, we performed benchmark experiments on the VIDI and Incidents Dataset. We have shown that the recent methods improve the incident classification accuracy. We have found that employing video data is very beneficial for the task. By using the video data, the top-1 accuracy is increased to 76.56% from 67.37%, which was obtained using a single frame. VIDI will be made publicly available. Additional materials can be found at the following link: https://github.com/vididataset/VIDI
CONSTRUCTS OF ORGANIZATIONAL PSYCHOLOGY AND BUSINESS PROCESSES IN THE PHYSICAL CULTURE AND SPORTS ACTIVITIES OF UNIVERSITY STUDENTS ON THE FORMATION OF UNIVERSAL COMPETENCIES

The purpose of the research is to develop criteria for assessing the involvement of students in physical culture and sports activities for the formation of universal competencies based on the analysis of the constructs of organizational psychology and business processes. Methods and organization of the research. Analytical and synthetic methods, methods of abstraction and systematization were used. Results and discussion. As a result of the research, the constructs of organizational psychology and business processes such as «personal involvement», «organizational commitment», «organizational civic behavior», «involvement in work», «passion for work», «personal resource», «job satisfaction» and universal competencies of physical and sports activity in the system of higher education were studied. Based on the synthetic method, the possibilities of using these constructs in the process of developing competencies among university students are formulated through the criteria for assessing involvement in physical culture and sports activities according to the expert opinions of the higher-education teaching personnel, questionnaires and social surveys. In conclusion, it is postulated: a low degree of knowledge of the possibility of using the presented constructs; lack of a clear and well-formed classification of criteria for the students’ involvement in physical culture and sports activities for the formation of universal competencies; the process of formation of universal competencies of physical culture and sports activities of students contributes to their personal involvement; the possibility of using the author's criteria-based assessment of students’ involvement, depending on the material and technical organizational conditions and professional capabilities of the higher-education teaching personnel.
Scrum in Project Risk Management in Cultural Institutions

Cultural animation and education is one of the goals of cultural institutions. In practical terms, this goal is often implemented through projects, which are also a way to obtain additional financial resources. Hence, projects are part of the work of cultural institutions. Agility understood as flexibility in management, is, therefore, becoming a necessity in cultural institutions, and project risk management as an important part of the management process. This resulted to the proposal to apply the Scrum approach to risk management in projects implemented by cultural institutions. Empiricism, adaptation, and iteration are inherent in Scrum. In this respect, they correspond to both the mission of cultural institutions and the need to adapt activities to the changeability of the environment. Pilot research carried out in three cultural projects indicates that the proposed model of risk management using the Scrum approach allows to manage project risk thanks to systemised work of the project team, transparency of activities, and adaptation of the project to the variability of the environment in subsequent iterations resulting from the Scrum approach. This article presents the results of the research and their implications for project management in cultural institutions.
The Relationship between Emotional Labor and Job-related Attitudes and Behaviors of Employees in Sport Organizations Using Meta Analysis

The purpose of this study was to examine the effect size of the relationship between emotional labor and a job-related attitude and behavior of employees in sport organizations using Meta-analysis. Toward this end, multiple databases were utilized and previous research were collected using keyword of “emotional labor”, “burnout”, and “turnover intention”. A total of 21 studies provided Pearson correlation coefficients between emotional labor and job-related attitude and behavior. Collected data were analyzed with Comprehensive a Meta Analysis(CMA) program. The results of this study were as follows. Firstly, the overall effect size between surface acting and burnout was .19 and -.10 for between deep acting and burnout indicating medium effect size. Secondly, the overall effect size between surface acting and turnover intention was .11 and -.17 for between deep acting and turnover indicating medium effect size. Discussions and practical implications were also suggested.
Impacts of covid-19 social distancing on the sleep of health students

Introduction: Sleep plays an important role in the balance of the human body. Its deprivation influences the development of cardiovascular, metabolic, psychological, and learning disorders. The restrictions imposed by Covid-19 on social activities affected the routine of many people, including university students, possibly impacting sleep conditions. Objective: To analyze the sleep characteristics of university students in the health area during the Covid-19 social distancing. Methodology: Cross-sectional study with 656 students from two community universities of Santa Catarina. Behavior characteristics were analyzed before and during the pandemic, relating them to sleep. Proportion analysis, crude and adjusted analyzes of the factors associated with sleep problems were performed. Results: 48.8% of the students had sleep problems. Of these, 41% were developed during social distancing. There was an increase in the difficulty to start sleep (42.4%), to stay asleep (29.4%), and dissatisfaction with sleep (36.6%). Sleep time was adequate, but insufficient to feel good for 25.6%. More sleep problems were observed among students that were older (PR=1.17; CI95%: 0.76-1.80), studied at UNOESC (PR=1.87; CI95%: 1.12-3.14), had greater use of social media (PR=2.03; CI95%: 1.21-3.39), had anxiety, sadness, and concern (PR=1.78; CI95%:1.02-3.10), had worse eating habits (PR=1.45; CI95: 1.01-2.07) and consumed alcohol (PR=1.59; IC95%: 0.98-2.58). Conclusion: Proper sleep time did not guarantee satisfaction with sleep. The prevalence of students with sleep problems increased with social distancing. Unhealthy eating habits, alcohol consumption, and social media use increased the risk of these problems.
A Vibrotactile Reaction Time Task to Measure Cognitive Performance in Virtual and Real Environments

Cognitive load is an important concept to understand people's cognitive processing performance of information. To assess cognitive load, several methods can be applied. For performance-based measure, Reaction times (RT) tasks can be used. Compared to physiological measures such as electroencephalography, RT tasks can be easily implemented and can be used as an alternative to subjective questionnaires, like NASA-TLX. In this paper we present two evaluation studies of a vibrotactile wearable for RT tasks. The first study evaluates its potential for Choice Reaction Time (CRT) tasks to compare real and virtual settings, the second study uses a simple Reaction Time (RT) task to evaluate cognitive effort on two different VR locomotion techniques while working on tasks in VR. The system is based on a vibrotactile wearable for the cues/stimuli and is suited for VR settings as well as real environments. We argue that such systems allow to compare cognitive performance between real and virtual tasks and discuss the limitation of the system.
A Bibliometric Analysis of Robot Collaborative Service During 2011–2021

This article aims to conduct a bibliometric analysis of robot collaborative service from 2011 to 2021 based on VOS viewer. 5141 articles have 162,358 cited references were analyzed. Publication source, publication organization, authors, country and citation of articles were recorded and analyzed. Bibliometric maps of authorship, citation, co-citation and network of co-occurrence of keywords are drawn. The China and USA dominates the publications (1279,24.87% or 895, 16.71%) and citations (15960 times or 22017 times). Chinese Academy of Science is the most productive organization. Bu jiajun is the most productive author. The top 5 highly cited journals are “Intelligent Service Robotics”, “IEEE Access”, “Sensors”, “International Journal of Advanced Robotic Systems”, “Robotics and Computer-integrated Manufacturing”. The 215 minimum number of occurrences of a keyword was set 35, of the 18681 keywords, 97 keywords were divided into four clusters. Cluster 1 mainly about design of robot. Cluster 2 mainly design about task of robot collaborative service. Cluster 3 mainly technology of robot collaborative service. Cluster 4 mainly about fields of application of robot collaborative service. The latest keyword analysis shows that “task”, “robot sensing system”, “robot kinematics”, “deep learning” and “manipulators” have burst end time of 2021.
A Mixed Reality-Based Framework for Blended Learning Environment

The process of bridging the gap between reality and virtual data has been possible through exponential technologies such as Mixed Reality (MR), Augmented Reality (AR) and Virtual Reality (VR). MR has so far proffered numerous advantages ranging from communication, navigation, medical aid, data modelling, visualization, and education to remote accessibility across diverse platforms. This paper proposes a systematic framework for knowledge acquisition and synthesis through MR based constructivism learning theory. The methodology uses a bottom-up approach and is based upon the Dryfus modelling. The existing drawbacks of poor learning retention, interactive knowledge acquisition and synthesis are addressed based upon MR technology. The framework provides the basis for embedding MR technology into analyzing and enabling human practical knowledge, as well as extending the scope for knowledge acquisition to rediscover the learning process in educational environments. Furthermore, existing MR based solutions for learning theories are reviewed. The validation of the proposed framework is carried out using technology acceptance model. The real-time knowledge acquisition device embedded with MR technology is explored and enhanced to demonstrate the accuracy and efficacy of the proposed framework.
Angular-Angular and Linear-Angular Regression Using ANN

Artificial neural networks(ANN) have been found to be an effective nonparametric method in many predictive applications. However, they have not been discussed much in the literature for angular data. In this article, we present two separate ANN models for angular-angular and linear-angular regression. We compare the performance of these ANN models with other regression models used in these contexts available in the literature. We find that the presented ANN models perform competitively and sometimes better as a predictive tool. We also propose two new methods for generating prediction intervals for ANN models. We find these prediction intervals provide good coverage probabilities on the Test dataset.
Cultivation of New Energy Power Generation Talents under the Mode of College Students' Innovation and Entrepreneurship Education

<p style="text-align: justify;"><span style="font-family: "times new roman";">In the past ten years, China's new energy industry has developed rapidly and is a world leader in wind power generation, solar thermal power generation, biomass energy utilization, and hydrogen energy development. In view of the current shortage of talents in the new energy industry, under the innovative and entrepreneurial mode of college students, combined with the characteristics of this specialty, cultivate multi-level talents that are in line with the new energy power generation industry. At the same time, promote the curriculum adjustment of the major, enhance professional vitality, and create a more professional team of teachers. After the implementation of the project, students will be trained and improved in many aspects such as professional skills, innovative thinking, entrepreneurial ability, management ability, and business ability. To a certain extent, they will increase the employment channels of the major and alleviate the social problems of employment pressure.</span>
Choose Your Weapon: A Survey of Cybersecurity

A roundtable of young cybersecurity professionals joins the hosts of The Looking Glass podcast, the audio complement of The SAIS Review, for a brief overview of the US cybersecurity landscape and the cyber challenges that confront the public and private sectors alike. They discuss how different types of cyber malware operate, aspects of US security that can be vulnerable to cyberattacks, and what the US government should do to mitigate its vulnerabilities. The opinions expressed here are solely those of the participants and do not necessarily reflect the positions of their employers or affiliates.
Realization of Animal Recognition Knowledge System under Language Education

<p style="text-align: justify;"><span style="font-family: "times new roman";">Nowadays, the concept of human and nature is deeply rooted in people's hearts, and the chances of contact between animals and humans are greatly increased. Therefore, the identification of animals has become a difficult problem. Research on animal recognition knowledge system is an important method to solve this problem. With the help of computer language, the animal recognition knowledge system can be implemented in many fields to solve many animal-related problems. Therefore, it is very necessary to actively carry out the realization of knowledge system based on animal recognition under language education. The purpose of this article is to discuss the realization of animal recognition knowledge system under language education, establish animal recognition knowledge system under C language education, perform texture comparison, feature capture, and accuracy analysis to evaluate the effectiveness of animal recognition knowledge system. The results of the study show that there are 431 pictures in the bird dataset and 404 pictures successfully recognized by the system, with a recognition rate of 94.61%; 277 pictures in the dog dataset, and 251 pictures successfully recognized by the system. The rate reached 90.6%, 189 cattle dataset images, 147 pictures successfully recognized by the system, and the recognition rate reached 79.03%; 187 tiger dataset images, 178 pictures successfully recognized by the system, the recognition rate reached 97.6%. It can be seen that the recognition system proposed in this paper is feasible, and the realization of animal recognition knowledge system under language education is of great significance.</span>
Artikel Administrasi Keuangan

Financial administration is one of the substance of school administration that will also determine the running of educational activities in schools. As happened in the substance of education administration in general, financial management activities are carried out through the process of planning, organizing, directing, coordinating, controlling or controlling.Some financial administration activities are obtaining and determining sources of funding, utilization of funds, reporting, inspection and accountability.The purpose of this research is to increase the effectiveness and efficiency of school finance use, improve accountability and transparency in school finance, and minimize misuse of school budgets.
Empathy and Symbiosis: Design Preferable Future AI Product and Service

Design theory is evolving with rapidly changing societies and accelerating technologies. In the past, the design concept of “starting from the problem” was challenging to face the ever-changing design challenges, so the concept of “starting from the future” in design combined with futurology is being valued. At the same time, the relationship between products and people in the future will change from a tool related to a collaborative relationship, and human-machine symbiosis will become a future trend. In human-machine symbiosis collaboration, empathy experience plays an important role, and human-machine empathy can help people trust products more and influence decision-making. We hope to help designers find the most suitable future products and services with a new design concept. Therefore, this paper will describe new design theories and design tools and rethink the issue of human-machine symbiosis and empathy from a future perspective. We analyze the empathy and symbiosis relationship and create empathy and symbiosis tools according to the characteristics of three different degrees of empathy and symbiosis. The tool has undergone two user tests and has received good feedback, and the tests also point us in the direction of future improvement.