Reviewerly/exHarmony huggingface dataset:
Library Automation: An Emerging Technology for State University and Colleges in Sulu Province

The importance of this research leads to the emerging technologies of libraries. The library is one of the most important places in any academic institution and remains the primary source of information for students, teachers, and many others. The researcher aims to suggest an option for the state university and colleges in the Province of Sulu on the technological advancement in the managing library. The breakthrough of technologies can help the library in various ways. Libraries need to adopt new technology that will allow them to operate and function efficiently and effectively, increasing their productivity and improving their user services without adding personnel. The main objective is to show that an automated library system using the latest technology is more beneficial. The present scenario demands an updated technology for faster, affordable, and user-friendly in providing various library services. Fortunately, new technologies have developed Barcode, Digital libraries, Quick Response codes, and RFID systems. Consequently, applying these technologies provides an end-to-end solution for easy library operation, such as borrowing and returning books, finding and locating books, and maintaining book records. The need to develop and enhance library services to meet users' demands is necessary.
Simple, Flexible Method to Extract Digital Image Features

The process of digital image features extraction is very important and it is required in many applications such as classification, prediction and regression. The extracted features for each image must be unique and capable to be used as an image identifier. In this paper we will introduce a method of image features extraction; it will be shown that this method will enhance the efficiency of the features extraction process. The proposed method will be experimentally tested using various images; the obtained experimental results will be compared with other existing methods of feature extraction to show the advantages of the proposed method and to show how to increase the speed up of the method.
Analysis of the MOOC Capabilities for Student Training in the Humanities

The article provides a quantitative analysis of the online courses which can be used for student training in the humanities. It is noted that the development of in-formation society influenced the ways of educational activities organization, the process of obtaining new knowledge and competency formation. Under the con-ditions when online education, blended and distance learning are considerably relevant, massive open online courses are an effective tool for learning and self-development. It was found that training in the humanities plays an important role in personal development of the future specialist. It involves the development of social competence, communication culture, leadership skills, as well as skills of conflict avoidance, teamwork, etc. The effectiveness of training in the humanities is influenced by active teaching methods, interactive technologies, and various means of information and communication technologies. The authors analyzed both the English-language (Coursera, Udemy, Edx) and Ukrainian-language (Prometheus, EdEra, OUM) online platforms. The article provides a quantitative analysis of online courses according to various directions in the humanities on each of the platforms. As of October 2021, we identified 4,769 free and fee-paying courses. The largest number of online courses for training in the humani-ties is presented on the Udemy platform (4,295 courses), the smallest number – on all Ukrainian-language platforms together (45 courses).
IDENTIFYING AND OVERCOMING SOME FATIGUE-CAUSING FACTORS EXISTING IN ONLINE READING CLASS OF AMIKOM PURWOKERTO PSDKU YOGYAKARTA DURING COVID-19 QUARANTINE

Abstract&#x0D; &#x0D; COVID-19 forced AMIKOM Purwokerto to convert its traditional classes to online learning. During this online learning, problems have started to unravel, and one of them is fatigue, which was confirmatively experienced by 55% students of Reading IV. This study, utilizing a quantitative research method, intended to find the causes of the fatigue and design practicable solutions. Through observations, group interview, and literature reviews, some main factors that caused fatigue were revealed: Zoom fatigue; tasks which were too difficult and numerous; presentation of materials which did not properly comply with the students’ online conditions and unfamiliarity to Google Classroom; eye fatigue (digital eye strain), bad postures during learning, lockdown fatigue, and frustration over signal and internet problems. To overcome the fatigue, the researchers reduced the time for video conferences and created asynchronous short videos for learning, selectively adjusted tasks in terms of number and difficulty, simplified presentations of materials and helped the students to become more familiar with Google Classroom, and addressed the problems from eye strain, bad postures, and lockdown fatigue in the reading materials so the students could solve those problems based on the texts given or find a more viable solution. Those solutions reduced the number of drained students to only 25% and in addition 60% students claimed that the modifications brought a positive impact on their learning.&#x0D; Keywords: fatigue, distance learning, COVID-19, Zoom fatigue
Utilization of Quizizz Educational Game Media to Increase Learning Interest and Achievement

When explaining the material, the teacher only uses blackboard learning media and is monotonous. This has an impact on student learning outcomes are low. This study aims to analyze the effectiveness of the Quizizz Game learning media in increasing enthusiasm and learning outcomes. This type of research is classroom action research. The research subjects were fourth-grade students with 23 students. The data in this study were obtained through pretest, post-test questions contained in the Quizizz Game application from observations and documentation. The instruments used to collect data are questionnaires and tests. The technique used to analyze the data is descriptive qualitative and quantitative analysis. The results of the study were that students obtained a percentage of learning completeness of 43.47%. After being given action I, the average score was 72, with a learning completeness percentage of 60.86% in Cycle I. In Cycle II, the average score increased to 85 with a learning completeness percentage of 95.65%. From the analysis above, it can be concluded that the application of the Quizizz Game learning media can increase students' interest and learning achievement. This research implies that teachers can use the application of the Quizizz Game learning media to increase student interest and learning outcomes.
Motivation Of Student Participation In University’s International Activities

The article dwells on motivation of student participation in the process of internationalization of higher education.Nowadays, motivation of university students to develop various academic competences is one of the key issues facing the higher education system.In accordance with tendencies of internationalization of modern world, university's international activities are becoming one of the most important tools for training specialists that are qualified enough for active competition in the global labor market.This article is based on the survey conducted among 244 students from different Russian universities.The results of the survey make it possible to determine which types of international activities of a university are the most popular among students, what factors hinder the participation of students in the international activities of the university and what motives for participation in the international activities of the university dominate in the student environment.Moreover, the results show the correlation between the performance of students, the level of their involvement in the scientific and educational activities of the university and the level of their involvement in international activities.The author sees the roots of insufficient involvement of students in university's international activities in the lack of language and communicative skills needed for effective intercultural dialogue.This assumption is confirmed by the results of the study.The paper stresses the necessity of stimulation of students' personal interest in international activities of a university in accordance with their cognitive, social and pragmatic needs.
ERROR ANALYSIS OF USING AUXILIARY VERBS IN WRITING DESCRIPTIVE TEXT

Grammar is complexity in learning English it makes many students often commit errors in learning. Making errors in writing is one of the processes for learning English .The aim of this research was to describe the students’ errors and its causes in using auxiliary verbs in the sentences. In this research, the writer limited the discussion on the error made by the students in using auxiliary verbs. The design of this research was quantitative approach in a form of descriptive analysis (percentage) that included observation, collecting the data the researcher used test as the instrument. The writer conducted the research to 31 students in first semester of English Literature in academic 2021/2022. The data were analyzed by using error analysis method. The error types were classified based on linguistic category, especially surface strategy taxonomy. The writer classified the types of error into omission, addition, misformation, and misordering. Among those four types, the most frequency error was misformation that reached 102 errors or 61.44% . the other finding was the sources of error which are divided into three categories. Those are interlingual errors, intralingual errors, and communicative strategies. Communicative strategies errors is the most common source of error, there were 45.78%
Exploration and Practice of Mechatronics Professionals Training Reform Based on “Competitions and Post Combination, Competitions and Education Integration”

Due to the poor connection between the current skill competition and regional posts, the ability to adapt to the post is weak.In view of the disconnection between skill competition and talent training process, it brings disadvantages such as "competition for competition", "top student preparation competition", "assault preparation competition", etc. Accordingly, the comprehensive mechanism of "competitions and post combination" and "competitions and education integration" was explored, and the reform and practice were carried out in the training of mechatronics professionals.Firstly, the skills competition was integrated into regional posts to build school-based competitions, and then integrated into professional skills courses and practice through the "four-dimensional competitions and post combination" mechanism.Subsequently, the skill competition such as "modern electrical control system installation and commissioning" and other skills competition and enterprise practical ability were integrated into the mechatronics professionals curriculum system.The "competitions and education integration" mechanism of "teaching preparation competition", "all staff preparation competition" and "whole process preparation competition" was realized.Finally, the national and provincial competition standards were layered into the curriculum standards, loose-leaf textbooks, teaching process and assessment, thus realizing the class-based skills competition.Practice has proved that mechanical and electrical students' ability to adapt to surrounding large-scale enterprises has been significantly improved, and the breadth and depth of students' benefit from the skills competition has been effectively improved.Also, the students' knowledge system is more comprehensive and solid, and their skills are more practical and stable.Therefore, the quality of mechatronics professionals talent training has been practically improved.
Methodological Framework for the Development of an English-Lithuanian Cybersecurity Termbase

The aim of the paper is to present a methodological framework for the development of an English-Lithuanian bilingual termbase in the cybersecurity domain, which can be applied as a model for other language pairs and other specialised domains. It is argued that the presented methodological approach can ensure creation of high-quality bilingual termbases even with limited available resources. The paper touches upon the methods and problems of dataset (corpora) compilation, terminology annotation, automatic bilingual term extraction (BiTE) and alignment, knowledge-rich context extraction, and linguistic linked open data (LLOD) technologies. The paper presents theoretical considerations as well as the arguments on the effectiveness of the described methods. The theoretical analysis and a pilot study allow arguing that: 1) a combination of parallel and comparable corpora enable to considerably expand the amount and variety of data sources that can be used for terminology extraction; this methodology is especially important for less-resourced languages which often lack parallel data; 2) deep learning systems trained by using manually annotated data (gold standard corpora) allow effective automatization of extraction of terminological data and metadata, which enables to regularly update termbases with minimised manual input; 3) LLOD technologies enable to integrate the terminological data into the global linguistic data ecosystem and make it reusable, searchable and discoverable across the Web.
Handwriting Arabic Character Recognition Using Features Combination

The recognition of Arabic handwriting is a challenging problem to solve. The similarity among the fonts appears as a problem in the recognition processing. Various styles, shapes, and sizes which are personal and different across individuals make the Arabic handwriting recognition process even harder. In this paper, the data used are Arabic handwritten images with 101 sample characters, each of which is written by 15 different handwritten characters (total sample 101x15) with the same size (81x81 pixels). A well-chosen feature is crucial for making good recognition results. In this study, the researcher proposed a method of new features extraction to recognize Arabic handwriting. The features extraction was done by grabbing the value of similar features among various types of font writing, to be used as a new feature of the font. Then, City Block was used to compare the obtained feature to other features of the sample for classification. The Average accuracy value obtained in this study was up to 82%.
Networking Of Educational Organizations At The Current Stage Of Society Development

The paper discusses the problematic aspects of networking, peculiarities of its regulatory support, and reveals the concept of networking and resources of an educational organization.In the era of globalization, cooperation between the representatives of public administration in the field of education, heads of educational organizations of various types, scientific and pedagogical workers, as well as students can contribute to the achievement of the country's strategic objectives.It presents the analysis of application practices and scientific research on the development of networking in educational institutions.The analysis of management problems of the networking of educational organizations (content method), as well as the methodology of studying management problems in the field of networking of educational institutions is also presented.Management problems are analyzed by considering the experience of managers of educational institutions.The results of the study confirmed the hypothesis that in the activities of educational organizations, the use of networking opportunities is insufficient due to management problems in the regulatory sphere and are caused by the lack of necessary experience in the management of educational institutions.
Tide Prediction in Prigi Beach using Support Vector Regression (SVR) Method

Purpose: Prigi Beach has the largest fishing port in East Java, but the topography of this beach is quite gentle, so it is prone to disasters such as tidal flooding. The tides of seawater strongly influence the occurrence of this natural event. Therefore, information on tidal level data is essential. This study aims to provide information about tidal predictions.Methods: In this case using the SVE method. Input data and time were examined using PACF autocorrelation plots to form input data patterns. The working principle of SVR is to find the best hyperplane in the form of a function that produces the slightest error.Result: The best SVR model built from the linear kernel, the MAPE value is 0.5510%, the epsilon is 0.0614, and the bias is 0.6015. The results of the tidal prediction on Prigi Beach in September 2020 showed that the highest tide occurred on September 19, 2020, at 10.00 PM, and the lowest tide occurred on September 3, 2020, at 04.00 AM. Value: After conducting experiments on three types of kernels on SVR, it is said that linear kernels can predict improvements better than polynomial and gaussian kernels.
Integration between Moodle and Academic Information System using Restful API for Online Learning

During the current pandemic, it is encouraging educational institutions to carry out distance learning, so many learning management system (LMS) platforms can be used to support distance learning. Each LMS has a different process flow but has the same goal of making it easier to manage learning content. When an LMS is implemented in an educational institution, it requires matching data for courses, students and lecturers that are available in the academic information system (AIS) at the institution, this is one of the weaknesses of all LMS because the data are not interrelated between AIS and LMS. The purpose of this research is to create an integrated system to equalize data between AIS and LMS using the synchronization method through the Application Programming Interface (API). The results of this application will combine data from AIS and LMS which will then be tested for automatic course creation according to class data, courses, lecturers and students at AIS. The test results of this system are said to be successful because each function that is designed has been running well without any fatal errors. The most important thing that needs to be considered when synchronizing is that there is a link between the data on the AIS and LMS, failure occurs on some courses because the email users in the AIS and LMS are different.
Development of Digital Corporate University Strategy at the Indonesian FDA to Strengthening Human Resources in Improving Competitiveness and Public Health through Quality Food and Drug Control in Indonesia

The quality of food and drug is a part that determines the level of public health in Indonesia. Nevertheless, several problems must be faced that cause food and drug control to be considered ineffective in the implementation, involve the weakness of the human resources of food and drug control competencies. This study aims to develop a learning and development strategy at the Indonesian Food and Drug Authority (Indonesian FDA) to strengthen human resources for solving the problem of food and drug control in Indonesia. The study was carried out through survey, focus group discussion, interview, dan literature study to get the data analyzed and the conclusion. The result findings showed that Corporate University with college and school strategy and digital learning relevant to human resources of food and drug control condition that spread in all Indonesia, in the Indonesian FDA office or other government agencies of central and regional government. This strategy is a new approach in learning and development for strengthening human resources of food and drug control to support improved public health through quality food and drug control and support for increasing competitiveness of Indonesian food and drug industries. This study can be helpful for public officials or policymakers in human resources development, particularly in learning and development program designing.
Applications and Challenges of Deep Reinforcement Learning in Multi-robot Path Planning

With the rapid advancement of deep reinforcement learning (DRL) in multi-agent systems, a variety of practical application challenges and solutions in the direction of multi-agent deep reinforcement learning (MADRL) are surfacing. Path planning in a collision-free environment is essential for many robots to do tasks quickly and efficiently, and path planning for multiple robots using deep reinforcement learning is a new research area in the field of robotics and artificial intelligence. In this paper, we sort out the training methods for multi-robot path planning, as well as summarize the practical applications in the field of DRL-based multi-robot path planning based on the methods; finally, we suggest possible research directions for researchers.
Knowledge Management Approach in Law Enforcement Division of Indonesian Food and Drug Authority to Improve Organizational Performance

Indonesian Food and Drug Authority (BPOM) functions are to conduct investigations into violations of Food and Drug Administration regulation. It protects the public from the illegal distribution of drugs, traditional medicines, dietary supplements, cosmetics, and foods that could harm health. However, in practice, the implementation of law enforcement has not been optimal due to several factors, including the lack of a system or database that allows for the sharing of knowledge, experience, and lessons learned that can aid in decision making regarding the law enforcement process. This research aims to assess the current system of knowledge management and find the knowledge management strategies that support the organization's performance. The findings show that the BPOM Law Enforcement Division currently lacks knowledge management. It shows that there is a lack of skill in converting tacit knowledge into explicit knowledge. The system does not support facilitation. Recommendations are made for the BPOM Law Enforcement Division to establish a standardized documentation and database system and build facilities, infrastructure, and information systems supported by the leader and system. This study can help all work units, particularly the Law Enforcement Division, improve quality and maximize available human resources.
DESIGN OF ELECTRONIC MEDICAL RECORD INFORMATION SYSTEM AT UNIVERSITY OF INDONESIA STUDENT HEALTH CENTER (PKM UI)

This thesis discusses the design of the medical record information system at the University of Indonesia Student Health Center (PKM UI). The purpose of this thesis is to design an electronic medical record information system in PKM UI that is useful to produce valid, complete, and timely information and to support the improvement of patient services in PKM UI. This research uses qualitative methods. And system design is done using the system development life cycle (SDLC)stages. The results of this study are in the form of the design of electronic medical record information systems in PKM UI.
Learn Quasi-Stationary Distributions of Finite State Markov Chain

We propose a reinforcement learning (RL) approach to compute the expression of quasi-stationary distribution. Based on the fixed-point formulation of quasi-stationary distribution, we minimize the KL-divergence of two Markovian path distributions induced by candidate distribution and true target distribution. To solve this challenging minimization problem by gradient descent, we apply a reinforcement learning technique by introducing the reward and value functions. We derive the corresponding policy gradient theorem and design an actor-critic algorithm to learn the optimal solution and the value function. The numerical examples of finite state Markov chain are tested to demonstrate the new method.