Reviewerly/exHarmony huggingface dataset:
Obstacles to public elementary libraries development as learning resources in Singaraja City

The library is an essential learning resource center for schools. For this reason, every school or madrasa is required to have a library that meets national education standards. Although formal provisions require educational institutions to have a library, many schools do not yet have a library. The development of school libraries, especially elementary schools (SD), is still lacking compared to the middle school, high school, and college libraries, thus giving the impression that SD libraries are marginalized. This study explored the development constraints that led to the marginalization of elementary school libraries in Singaraja, Bali. This research used a qualitative approach in the form of multiple case studies. The data collection techniques were in-depth interviews with appointed informants, total and purposive samples, and snowball sampling. Data analysis in this study followed Peter Berger's model with conceptualization, proof, and objectivation steps. The results indicated that there were several obstacles to the development of elementary school libraries, namely (1) the dadi-dadi dogen ideology adopted by the principal; (2) the teaching and learning process is still teacher-centered; (3) a comprehensive education system; (4) unprofessional librarian; (5) the government is not in favor of the school library management policy; and (6) free school jargon. These findings prove that the general assumption about the constraints on developing school libraries due to limited financial capital is not entirely true. There are other more important factors, namely power relations related to ideology.
Assessing the effect of high school quality factors in selecting a high school

This study aims to analyze the effect of education quality, price, promotion strategy, quality of human resources, and physical facilities mediated by reputation on students' decision to select a high school. The research technique used to obtain data from 170 prospective students is purposive sampling, a non-probability method. The results showed that the education quality, promotion strategies, and physical facilities mediated by reputation positively affect students' decisions, as opposed to the price and quality of human resources. The originality value of this research is to choose high school mediation by reputation. In conclusion, the limitations of this research were clarified by adding a process variable which is very important in services marketing, due to its ability to handle consumers in marketing activities and in making final decisions.
Performative Artistic Practices in the Conditions of the Distance Learning Process

The performing arts practices in the conditions of distance learning are currently not only an actual phenomenon for the modern educational process but also a leading alternative to the classical type of knowledge transfer in certain disciplines to a new generation of specialists. This publication covers the importance and scientific originality of the stated subject. The author shares the methods of studying performing practices and the principles of their presentation by means of the latest digital technologies. In particular, the content of these categories and the principles of their implementation on the Internet are analysed. The result of the study of the problem is to show the overall picture (in the form of a table), which gives a description of teaching performing arts in distance. The publication also provides a discussion of the leading subject, referring to researchers and specialists from different countries, cultures, and schools.
Multi-objective optimization for solving mobile robot path planning problem employing hybridization of algorithms

Mobile Robot Path Planning problem (MRPPP) is the most prominent research area employed in different real-time environments. In this article, a hybrid strategy is employed and validated with different environments for the path planning of mobile robots. The Artificial Potential Field (APF) algorithm and Multi-objective Genetic Algorithm (MOGA) are hybridized to solve an MRPPP. In the proposed hybrid methodology, the implementation is accomplished in three phases. To generate the initial population, an Artificial Potential Field (APF) algorithm is applied to discover all viable routes in an environment between the start and destination points. The collision-free paths are generated by determining the artificial force produced by obstacles and the target. The population-based evolutionary algorithm is employed to derive an optimal solution path from the initial population consisting of candidate paths. The selection operator is used to select the qualified subpopulation to the next generation to converge into the optimal solution. The genetic operators such as two-point crossover and mid-point mutation are exercised which are specific to the path planning problem.
Professional Development of Participants in the Educational Process for Working With Students of an Inclusive Group on an Integrative Basis

The article analyses the conduct of training seminars for pedagogical specialists. Methodological features of the introduction of inclusive education based on integration in the study of natural sciences and special education are shown. The paper also presents statistical data from a survey of teachers working in inclusive classrooms with students with special educational needs. Such methods are aimed at introducing innovative work in inclusive groups of educational. The proposed measures make it possible to form the subject competence of teachers of an educational institution and contribute to improving the communication process of teachers working in an inclusive classroom. The results of the study show the importance of conducting such training seminars, the tasks of which are designed to familiarise teachers with the latest methods and technologies that will contribute to better assimilation of the knowledge system by students with special educational needs and the ability to apply them in the process of learning and practical activities.
Image Policy as a Reflection of the Corporate Culture Level of a Modern University Department

The study aims to substantiate the importance of forming the image of a modern university department in the context of corporate culture for the effective functioning of a structural unit of a higher education organisation. The paper provides a detailed description of image types undertaken by scientists of the Belgorod State Institute of Arts and Culture. Scientific novelty of the study lies in presenting corporate culture and the image of a university department as a whole in the socio-cultural space of a modern university. As a result, it has been proved that modern imageology is an actively developing branch of humanities research covering various spheres of social interaction. In particular, image can be considered as an integral component of modern pedagogical research when it comes to the areas of image policy and the formation of corporate culture of a structural unit of an educational organisation.
Automatic earthquake detection and phase picking in Muong Te, Lai Chau region: an application of machine learning in observational seismology in Vietnam

We applied the automatic detection and picking of P- and S-wave to one-year continuous raw seismic data from 17 seismic stations in the Muong Te area, northwestern Vietnam. The deep learning picker, Earthquake Transformer, has performed automatic picking of P- and S-waves, and phase association, then we located the earthquakes using Hypoinverse and NonLinLoc programs. The newly derived catalog consisted of 893 events, which is significantly higher than the number of events in the manual catalog. From this new catalog, we can observe more earthquakes related to the Muong Te ML 4.9 earthquake on June 16, 2020, and the earthquake activity in other faults such as the Dien Bien Phu and Muong Nhe faults. The extended catalog can further study the seismogenesis and the seismic velocity structure of the crust beneath northwestern Vietnam.
Transformation of the American academic system during the COVID-19 pandemic

The article explores the issue of the structural transformation of the contemporary American academic system, namely one of the main formats existing in it – universities and their functioning during the first months of the spread of coronavirus infection. The COVID-19 pandemic has had the vast and most comprehensive impact on the higher education systems of the first world countries, which was demonstrated in the article. It is worth noting that the actively current trends of digitalisation, computerisation and the general implementation of the advancements of the scientific and technological progress of the higher education system were overlapped by the new emergency conditions of the pandemic and the need to choose a different format of functioning in the current situation. The ongoing transformations and structural alterations are most visible in the United States of America, due to a number of factors – from the historical dynamism of the development of the American higher education system to its active role in the development and rollout of technological advancements. The American academic system is introduced and analysed in two main formats: public universities and private ones. Each group of the indicated universities has chosen its own strategy of functioning and implemented it in practice, resting on individual factors and conditions. Nevertheless, there is already a separation between these two large groups of American universities in the implementation of functioning strategies during the coronavirus pandemic. The analysis of factors, conditions, contexts and actions of universities from these groups allows us to understand not only the dynamics of the development of the American academic system at the moment but also will allow us to comprehend its future transformations and alterations.
A Research on the Blended Evaluation Mode in College English Writing Course

Evaluation plays a significant role in English writing course, which is an effective way to assess and motivate the learners. Traditional instructor’s scoring and feedback is considered helpful, yet straining and not efficient enough. Automated writing evaluation (AWE) is the use of specialized computer programs to grade and evaluate writings in educational settings. The idea of integrating machine feedback with human evaluation is supposed to be comprehensive and efficient. This paper is to investigate the reliability and feasibility of the integration of AWE and human evaluation in college English writing course. An empirical study was conducted in a Beijing foreign languages university, where a blended evaluation mode was applied and the feedback from the students verified that through proper design, the integration of AWE and human scoring was fairly feasible and efficient. The findings of this paper may provide some reference and enlightenment for the evaluation mode in college English writing course.
Learning Pinball TWSVM efficiently using Privileged Information and their applications

In any learning framework, an expert knowledge always plays a crucial role. But, in the field of machine learning, the knowledge offered by an expert is rarely used. Moreover, machine learning algorithms (SVM based) generally use hinge loss function which is sensitive towards the noise. Thus, in order to get the advantage from an expert knowledge and to reduce the sensitivity towards the noise, in this paper, we propose a fast and novel Twin Support Vector Machine classifier based on privileged information with pinball loss function which has been termed as Pin-TWSVMPI where expert's knowledge is in the form of privileged information. The proposed Pin-TWSVMPI incorporates privileged information by using correcting function so as to obtain two nonparallel decision hyperplanes. Further, in order to make computations more efficient and fast, we use Sequential Minimal Optimization (SMO) technique for obtaining the classifier and have also shown its application for Pedestrian detection and Handwritten digit recognition. Further, for UCI datasets, we first implement a procedure which extracts privileged information from the features of the dataset which are then further utilized by Pin-TWSVMPI to which lead to enhancement in classification accuracy with comparatively lesser computational time.
A Survey on Power Outage-related Information Use Cases in the Event of a Disaster

We are developing an information platform to enhance power resilience in the event of a disaster. To reflect it in the platform design, we investigated the use cases of power outage-related information in the event of a disaster. This paper reports the results of a survey of local governments and medical institutions.
Dirichlet law for factorization of integers, polynomials and permutations

Let $k \geq 2$ be an integer. We prove that factorization of integers into $k$ parts follows the Dirichlet distribution $\text{Dir}\left(\frac{1}{k},\ldots,\frac{1}{k}\right)$ by multidimensional contour integration, thereby generalizing the Deshouillers-Dress-Tenenbaum (DDT) arcsine law on divisors where $k=2$. The same holds for factorization of polynomials or permutations. Dirichlet distribution with arbitrary parameters can be modelled similarly.
An Integrated Fuzzy TOPSIS and Best-Worst Methodology for a Sinkhole Selection as a Geotourism Destination

Sinkholes are important formations for the tourism sector with their natural beauties and structures that scare people but make them want to see. The study aims to determine which of the sinkholes has the highest criteria for being a tourism destination, by weighting the criteria of being a tourism destination for the sinkholes according to their importance. In this way, it is aimed to contribute to directing the investments to be made through the sinkholes as a geotourism center to the right sinkhole. The criteria that a place should have to be a tourism destination have been ranked by the experts according to their importance with the Best-Worst Method (BWM). Thus, determine the weighting coefficients of the criteria. Then, expert opinions were taken for four different sinkholes and the FUZZY TOPSIS method, which facilitates decision making in blurred environments, was used. The most suitable sinkhole was chosen for the visitors.
A Result Analysis of Supervised Machine Learning Approach to Detect Anomaly from Network Traffic

Supervised Machine Learning (SML) is the quest for algorithms that reason from externally given cases to develop general hypotheses, which subsequently make predictions about future instances. Supervised categorization is one of the jobs most commonly carried out by the intelligent systems. This article presents numerous Supervised Machine Learning (ML) classification strategies, evaluates various supervised learning algorithms as well as finds the most effective classification algorithm depending on the data set, the number of instances and variables (features) (features). Seven alternative machine learning methods were considered: Decision Table, Random Forest (RF) , Naïve Bayes (NB) , Support Vector Machine (SVM), utilizing Waikato Environment for Knowledge Analysis (WEKA)machine learning program. To develop the algorithms, Diabetes data set was utilized for the classification with 786 cases with eight attributes as independent variable and one as dependent variable for the analysis. The findings suggest that SVM was determined to be the method with maximum precision and accuracy. Naïve Bayes and Random Forest classification algorithms were shown to be the next accurate after SVM appropriately. The research demonstrates that time spent to create a model and precision (accuracy) is a factor on one hand; while kappa statistic and Mean Absolute Error (MAE) is another element on the other side. Therefore, ML techniques demands precision, accuracy and least error to have supervised predictive machine learning.
System Design: Data Flow Diagrams of Sales Process, a Case Study of CV. Jatayu Catra Internusa

This study aims to analyze the flow of sales transaction data. The data flow is modeled using a data flow diagram. The procedure carried out for data flow analysis began by interviews with staff who handle sales, then proceeded to identify entities and documents that go in and out of these entities, then modelled the data flow into data flow diagrams, and taking into account the rules on data flow diagram modeling. The results of this study are data flow diagram modeling of sales transaction that can be used to perform advanced system models such as case modeling, entity relationship diagrams, and others.
Exploring Business Process Re-Engineering (BPR) ‎Efforts in Afghanistan s Public Sector -A Case ‎Study of the National Examination Authority (NExA)

‎‎ Recently the public sector of Afghanistan made a series of reforms to improve its service delivery ‎and eliminate widespread corruption. The National Examination Authority (NExA) being one of ‎them has made dramatic reforms aiming for a corruption-free and transparent process. The main ‎purpose of this study is to explore the efforts of Business Process Re-engineering (BPR) in the ‎public sector using NExA as a case study. The study adopted a qualitative methodology, with an ‎inductive approach, while the philosophy of the study is interpretivism and organization as the ‎unit of analysis. Based on the in-depth interviews, this study found that as a result of the ‎business process reforms, the examination process has improved vastly in terms of transparency, ‎cost, efficiency, and citizen happiness. This study also, found that Information Technology (IT) ‎played the main enabler role in the process. Other enablers were sound leadership, teamwork, ‎political and financial support, commitment to change, and merit-based recruitment. Resistance, ‎bureaucracy and insecurity were the constraints for BPR implementation. This study further ‎provides recommendations for the policymakers in terms of smooth implementation of the ‎business process re-engineering in the public sector organization. Limitations and future ‎implications are also discussed.‎‎
Active Exploration via Experiment Design in Markov Chains

A key challenge in science and engineering is to design experiments to learn about some unknown quantity of interest. Classical experimental design optimally allocates the experimental budget to maximize a notion of utility (e.g., reduction in uncertainty about the unknown quantity). We consider a rich setting, where the experiments are associated with states in a {\em Markov chain}, and we can only choose them by selecting a {\em policy} controlling the state transitions. This problem captures important applications, from exploration in reinforcement learning to spatial monitoring tasks. We propose an algorithm -- \textsc{markov-design} -- that efficiently selects policies whose measurement allocation \emph{provably converges to the optimal one}. The algorithm is sequential in nature, adapting its choice of policies (experiments) informed by past measurements. In addition to our theoretical analysis, we showcase our framework on applications in ecological surveillance and pharmacology.
VALIDATION OF LEARNING ACTIVITY SHEETS AND LEARNERS PERFORMANCE IN ARALING PANLIPUNAN

Expert opinion was taken for the validity of the Learning Activity Sheets depending on four characteristics: Utilization, Runtime, Appeal, and Comprehensiveness.Learning Activity Sheets.Learners' performance will be recorded in a monitoring tool whether they completed every task in their Learning Activity Sheets.Thus, the data will be validated through a questionnaire on the characteristics of Learning Activity Sheets.The Learning Activity Sheets are an advantage for the teachers who can't decide on activities most suitable for learners.Teachers may be aware of the appeal of learning activity sheets in delivering the lessons and activities to the learner's comprehension.This paper analyzes the significant difference between the Learning Activity Sheets and Performance Task components.Specifically, it ought to determine the significant effect of the learning activity sheet on the performance in Araling Panlipunan, the mean performance of grade 8 learners based on the result of Pre-Test and Post Test, significant difference in the mean performance of grade 8 learners based on the result of the pre-test and post-test, the level of Validity of the Learning Activity Sheets in Araling Panlipunan in terms of their characteristics as to: Utilization, Runtime, Appeal and Comprehensiveness, the level of validation of the Learning Activity Sheets in Araling Panlipunan in terms of content as to: Content, Organization and Language, Illustrations/Image and Design and Layout.With activity sheets created by the teachers, the researcher aims to determine the Academic Performance of Learners.The level of validity of learning activity sheets in terms of components and characteristics is significant to the learners' learning.The components of Learning Activity Sheets significantly affect the learners learning outcomes using the pre-test and posttest in Araling Panlipunan.There is a significant difference in the mean of grade 8 learners based on their pre-test and post-test results.In conclusion, teachers may be aware of the appeal of learning activity sheets in delivering the lessons and activities to the learner's comprehension.It is suggested that the Curriculum Developers and Writers may examine every aspect of the learning material to ensure the correctness and accurate information for students to establish prior knowledge of the lesson.
Why Robust Natural Language Understanding is a Challenge

With the proliferation of Deep Machine Learning into real-life applications, a particular property of this technology has been brought to attention: robustness Neural Networks notoriously present low robustness and can be highly sensitive to small input perturbations. Recently, many methods for verifying networks' general properties of robustness have been proposed, but they are mostly applied in Computer Vision. In this paper we propose a Verification specification for Natural Language Understanding classification based on larger regions of interest, and we discuss the challenges of such task. We observe that, although the data is almost linearly separable, the verifier struggles to output positive results and we explain the problems and implications.
Virtual worlds in distance learning

&lt;span lang="EN-US"&gt;Virtual worlds are considered an additional proposal within the e-learning model. Online platforms have not been enough resources to be successful in the teaching and learning processes, therefore, it is necessary to search more options that contribute to their improvement. Virtual worlds, through inverse and visual experiences for the student, offer new panoramas that allow living situations and solving problems in different areas, such as mathematics. This article analyzes the opinion of higher-level students regarding the use of virtual worlds in their distance classes. Likewise, the virtual worlds provide help in improving teacher-student and student-student relationships. Some cases of educational institutions that integrated the use of virtual worlds into their classes are shown. A Likert-type scale questionnaire has been applied to a sample of 65 higher-level students. Its reliability was validated by means of Cronbach's alpha coefficients and Pearson's. It was found that students consider that the use of virtual worlds would improve class work and relationships between their peers and their teachers. It is remarkably undoubted that virtual worlds within education path are considered an excellent tool for e-learning. However, although the interest on the part of students is high, it is necessary to carry out more researching and developing procedures on the virtual worlds as an alternative to support learning. &lt;/span&gt;