Reviewerly/exHarmony huggingface dataset:
POLYNOMIAL ESTIMATION OF DATA MODEL PARAMETERS WITH NEGATIVE KURTOSIS

Context. The paper focuses on the problem of estimating the center of distribution of the random component of experimental data for density models with a negative kurtosis.&#x0D; Objective. The goal of this research is to develop methods to improve the efficiency of polynomial estimation of parameters of experimental data with a negative kurtosis coefficient.&#x0D; Method. The study applies a relatively new approach to obtaining estimates for the center of the probability distribution from the results of experimental data with a stochastic component. This approach is based on polynomial estimation methods that rely on the mathematical apparatus of Kunchenko's stochastic polynomials and the description of random variables by higher-order statistics (moments or cumulants). A number of probability density distributions with a negative kurtosis coefficient are used as models of the random component.&#x0D; As a measure of efficiency, the ratio of variance of the estimates for the center of the distribution found using polynomial and classical methods based on the parameter of amount of information obtained is used.&#x0D; The relative accuracy of polynomial estimates in comparison with the estimates of the mean, median and quantile estimates (center of curvature) is researched using the Monte Carlo method for multiple tests.&#x0D; Results. Polynomial methods for estimating the distribution center parameter for data models of probability distribution density with a negative kurtosis coefficient have been constructed.&#x0D; Conclusions. The research carried out in this paper confirms the potentially high efficiency of polynomial estimates of the coordinates of the center of the experimental data, which are adequately described by model distributions with a negative kurtosis. Statistical modeling has confirmed the effectiveness of the obtained estimates in comparison with the known non-parametric estimates based on the statistics of the mean, median, and quantile, even with small sample sizes.
K-NN’S NEAREST NEIGHBORS METHOD FOR CLASSIFYING TEXT DOCUMENTS BY THEIR TOPICS

Context. Optimization of the method of nearest neighbors k-NN for the classification of text documents by their topics and experimentally solving the problem based on the method.&#x0D; Objective. The study aims to study the method of nearest neighbors k-NN for classifying text documents by their topics. The task of the study is to classify text documents by their topics based on a dataset for the optimal time and with high accuracy.&#x0D; Method. The k-nearest neighbors (k-NN) method is a metric algorithm for automatic object classification or regression. The k-NN algorithm stores all existing data and categorizes the new point based on the distance between the new point and all points in the training set. For this, a certain distance metric, such as Euclidean distance, is used. In the learning process, k-NN stores all the data from the training set, so it belongs to the “lazy” algorithms since learning takes place at the time of classification. The algorithm makes no assumptions about the distribution of data and it is nonparametric. The task of the k-NN algorithm is to assign a certain category to the test document x based on the categories k of the nearest neighbors from the training dataset. The similarity between the test document x and each of the closest neighbors is scored by the category to which the neighbor belongs. If several of k’s closest neighbors belong to the same category, then the similarity score of that category for the test document x is calculated as the sum of the category scores for each of these closest neighbors. After that, the categories are ranked by score, and the test document is assigned to the category with the highest score.&#x0D; Results. The k-NN method for classifying text documents has been successfully implemented. Experiments have been conducted with various methods that affect the efficiency of k-NN, such as the choice of algorithm and metrics. The results of the experiments showed that the use of certain methods can improve the accuracy of classification and the efficiency of the model.&#x0D; Conclusions. Displaying the results on different metrics and algorithms showed that choosing a particular algorithm and metric can have a significant impact on the accuracy of predictions. The application of the ball tree algorithm, as well as the use of different metrics, such as Manhattan or Euclidean distance, can lead to improved results. Using clustering before applying k-NN has been shown to have a positive effect on results and allows for better grouping of data and reduces the impact of noise or misclassified points, which leads to improved accuracy and class distribution.
Variational Inference via Rényi Bound Optimization and Multiple-Source Adaptation

Variational inference provides a way to approximate probability densities through optimization. It does so by optimizing an upper or a lower bound of the likelihood of the observed data (the evidence). The classic variational inference approach suggests maximizing the Evidence Lower Bound (ELBO). Recent studies proposed to optimize the variational Rényi bound (VR) and the χ upper bound. However, these estimates, which are based on the Monte Carlo (MC) approximation, either underestimate the bound or exhibit a high variance. In this work, we introduce a new upper bound, termed the Variational Rényi Log Upper bound (VRLU), which is based on the existing VR bound. In contrast to the existing VR bound, the MC approximation of the VRLU bound maintains the upper bound property. Furthermore, we devise a (sandwiched) upper–lower bound variational inference method, termed the Variational Rényi Sandwich (VRS), to jointly optimize the upper and lower bounds. We present a set of experiments, designed to evaluate the new VRLU bound and to compare the VRS method with the classic Variational Autoencoder (VAE) and the VR methods. Next, we apply the VRS approximation to the Multiple-Source Adaptation problem (MSA). MSA is a real-world scenario where data are collected from multiple sources that differ from one another by their probability distribution over the input space. The main aim is to combine fairly accurate predictive models from these sources and create an accurate model for new, mixed target domains. However, many domain adaptation methods assume prior knowledge of the data distribution in the source domains. In this work, we apply the suggested VRS density estimate to the Multiple-Source Adaptation problem (MSA) and show, both theoretically and empirically, that it provides tighter error bounds and improved performance, compared to leading MSA methods.
Peningkatan Hasil Belajar Bahasa Indonesia melalui Penerapan Model Pembelajaran Problem Based Learning (PBL) Siswa Kelas 4 SDN 3 Mataram

This research was designed with the aim of improving student learning outcomes in Indonesian language subjects using a problem based learning model for class IV students at SDN 3 Mataram. Based on researchers' findings regarding learning, student learning outcomes at SDN Blimbing decreased. This can be seen from the results of the assessment carried out by the teacher. Only 25% of SDN Blimbing Class IV students are able to meet the KKM, while the other 75% of students have not been able to meet the specified KKM. By using the Problem Based Learning learning model, students learn to face problems in the real world to start learning. Before students learn the concept/material, students will be given a problem that must be solved. Therefore, to solve this problem students will have an awareness of the need for new knowledge that must be learned to solve the given problem. Based on the results of the research conducted, it can be concluded that using the Problem Based Learning learning model can improve the learning outcomes of class IV students at SDN 3 Mataram Kediri. This can be seen from the percentage of completion in cycle I of 60%, increasing to 85% in cycle II. Based on these conclusions, the suggestion that can be given is that teachers should look for the right method according to the material to be taught to students. Teachers should always reflect after carrying out the learning process.
Upaya Meningkatkan Hasil Belajar Peserta Didik pada Muatan Matematika Materi Jam Kelas II SD Negeri 08 Mataram melalui Model Pembelajaran Project Based Learning

The aim of this research is to improve student learning outcomes in the cognitive domain through the application of the Project Based Learning (PJBL) learning model. This type of research is classroom action research. Data collection methods use interviews and documentation. The type of data used is qualitative data and quantitative data. The subjects in this research were class 2 students at SDN 08 Mataram, totaling 28 students. The results of the research showed that there was an increase in the percentage of student learning outcomes, namely in the pre-cycle the percentage was 72% with the sufficient category (C), then in the first cycle it increased to 77% with the sufficient category (C) and increased to 83% in the second cycle with the good category (B ) which means that the use of the Project Based Learning learning model is effective in improving the learning outcomes of class 2 students at SDN 08 Mataram.
Philosophical and Methodological Challenges of Creativity

At all stages of its development, higher education considered the training of an educated specialist capable of improving their professional qualities, reproducing and expanding social experience, transforming the material conditions of society and its culture as well as accumulating and creating new values and knowledge as its main goal.&#x0D; At a certain stage, however, this social function of higher education – the formation and development of a creative personality of a specialist, became distorted, devalued, and lost its fundamental meaning. Higher education gradually began to lose its creative functions.&#x0D; The process of restructuring the political, spiritual, social, and economic life of society has posed new questions about the individual and the objective need for increasing the role of the creative personality.&#x0D; Studying the patterns of students’ thinking development, the peculiarities of their socialization under new conditions, and the realization of the creative abilities of the individual, while changing priorities and values, allows for predicting promising trends in the development of science, technology, and culture in the nearest future.&#x0D; An important methodological principle that should be embedded in the center of educational policy during the predicted period is the recognition that the progress of any society is measured by the ability to realize the essential capacities of individuals, their degrees of freedom, moral self-improvement, personal development, and the movement of society towards a new historical form of humanism.&#x0D; An individual in society should be free and retain the freedom of conscience, thought, skills, profession choice, cultural interests, aspirations, and priorities.
Pelatihan Pembuatan Aplikasi E-raport dengan Menggunakan Microsoft Office Excel Bagi Guru-guru SD di Wilayah Insana Fafinesu

The activity of filling in school data, student data, and student final grades in report card at elementary schools in the Insana Fafinesu District, Timor Tengah Utara Regency has been carried out in handwriting (conventional), which have some constraints such as taking a long time to processing grades, has a tendency to miscalculation if the student report card is lost or damaged, it does not have documentation/ back-up documents. For teachers who have sloppy handwriting, it will be difficult for a parent to read. One software that can be used in making student report cards is Microsoft Office Excel. This software is easy to understand and can overcome problems in making student report cards such as the length of time for processing grades, the tendency of grade processing error, difficulties in reading teacher writing by parents, and overcoming problems with documentation/backup documents. This service activity aims to provide training in making e-report card applications using Microsoft Excel for elementary school teachers in the Insana Fafinesu area, Timor Tengah Utara Regency. The methods used in this activity are workshops and ongoing mentoring. As a result, teachers better understand the functions in Microsoft Excel that are useful in the process of filling out student report cards, each teacher succeeds in making their own e-reports, and they agree that e-reports with Microsoft Excel are more efficient and effective than filling out report cards manually (conventional) and will use e-reports in their respective schools. The next plan for this service activity will be an application for Teacher Performance Assessment (TPA) and Employee Work Targets (EWT). &#x0D;
PKM Digital Literacy to Improve Ethics and Digital Security for SMKS PGRI 3 Denpasar Students

This article is based on the Community Partnership Program (PKM) which seeks to increase digital literacy knowledge for students. This knowledge is an asset to have the ability to sort and evaluate digital media content sharply and thoroughly. It is hoped that this knowledge will enable students to utilize information according to their needs. The method used is lectures to explain material related to digital literacy and the practice of applying several digital security methods to the WhatsApp application. Discussions were also held with students regarding material or experiences regarding digital literacy that they had. The target of the activity was 70 students of SMKS PGRI 3 Denpasar. The results of this activity indicate an increase in knowledge about digital literacy. This increase can be seen from the comparison of the pre-test and post-test results of 1.9.
Dissemination of Evacuation Routes for Earthquake and Tsunami Hazards in the Red Zone of Johan Pahlawan District at the Aceh Health Polytechnic

This community service activity provides information related to disaster and tsunami evacuation routes in the city of Meulaboh, West Aceh Regency, especially in the red zone area. Poltekkes is a vocational college located in Meulaboh, West Aceh District, which is in the red zone area. Communities in the red zone are prone to earthquakes and tsunamis, so they must carry out an evacuation process. The method of implementing this community service activity consists of socializing evacuation routes consisting of 7 routes in Johan Pahlawan District and 5 routes in Meureubo District. Measuring the achievements of socialization activities was carried out by distributing questionnaires to students, including filling in suggestions and input for planning earthquake and tsunami disaster evacuation routes. The results of the questionnaire showed that the Poltekkes students, after the socialization was carried out, already knew the 12 evacuation routes provided. On average, students understand the current condition of the evacuation routes that have been socialized. Students also mostly answered agree from each question given. For questions related to problems encountered during the evacuation process, 63.8% answered that there was congestion at the intersection because each vehicle met from a different direction, 53.2% mixed residents who evacuated with vehicles and people who ran during the evacuation process ongoing, and 29.8% answered that the capacity of the road section exceeded the capacity of the community conducting the evacuation.
Optimizing Management of the Jeumpa Journal: Journal of Science &amp; Biology Education, Journal of the Biology Education Department, Samudra University

Scientific journals are publication media that contain articles that present the results of research and scientific studies. Management of journals by departments at universities is essential in improving the quality and reputation of departments, especially in supporting the implementation of tridharma in research. Based on the results of observations, the management of the Jeumpa Journal carried out by the Department of Biology Education at Samudra University is still not optimal. Through the Community Partnership Program (PKM), efforts were made to solve problems related to the not yet optimal management of the journal. Together with Jeumpa Journal editorial partners, efforts to optimize the journal were carried out through four stages, namely optimizing the appearance of the journal's website, compiling author guidelines, compiling article templates, and socializing and promoting the journal. Evaluation with Jeumpa Journal editorial partners on all stages of optimization activities that have been carried out is used as a benchmark in preparing follow-up programs in the development.
Improving Student Reading Literacy Through the Thematic Reading Corner Assistance Program at SDN 42 Ternate City

The results of the situation analysis revealed that the condition of the library at SDN 42 Kota Ternate was not optimal, and students' interest in reading was still low. In facing this challenge, the PkM program created a solution by creating a thematic reading corner that aims to stimulate students' interest in reading and increase their literacy. The method used is action research which emphasizes the active participation of all parties involved, including students and teachers. In the process, servants along with teachers and students are actively involved in the development, implementation, and evaluation of this program. Various activities have been carried out, such as outreach, setting up reading corners, and training to increase reading interest. The results show an increase in students' interest in reading, as well as a positive response to the existence of a reading corner. With these results, the PkM program objectives have been achieved. Overall, this PkM program provides an overview of initiatives that focus on increasing students' literacy and in reading interest can have a positive impact. Through collaboration between servants, teachers, students, and school partners, this program has succeeded in creating solutions that are relevant to school and community conditions at SDN 42 Ternate City.
CHALLENGES AND DILEMMATIC CONDITION OF HUMAN RESOURCE MANAGEMENT DURING THE FOURTH INDUSTRIAL REVOLUTION (4IR)

Economic growth necessitates a circular economy in which production and productivity must be improved quickly. One of the major needs of economic management is efficiency throughout the process, one of which is the employment of fewer employees who are replaced by IT and advanced machinery. The purpose of this work is to present the problems and dilemmatic state of that situation by acquiring information and data from current reviews and research articles published in scientific publications. According to this viewpoint, the large population, particularly those of productive age, may be projected as prospective primary participants in the economic sector. These can be accomplished through the development of IT skills. This issue necessitates government attention and a vital role in which human skill vision may be improved via education and training. The demographic dividend can be tailored to boost economic growth in the coming years. Furthermore, initiative, innovation, and entrepreneurship must be essential human resource skills.
Dynamic data‐driven railway bridge construction knowledge graph update method

Abstract Effectively integrating and correlating multisource data involved in the bridge construction process is crucial for the improvement of the bridge informatization level. In the current issues of dynamic numerous data and low information sharing between different engineering departments, the traditional information management methods are inefficient in providing comprehensive and accurate data support for construction safety. Focusing on the bridge construction stage, this article proposes a dynamic data‐driven construction method of railway bridge construction knowledge graph (KG) in combination with dynamic data (materials, personnel, equipment and sensors) in the construction process and KG technology. By taking a railway bridge as a case, the study develops a prototype system and analyzes the effectiveness of bridge construction KG in material traceability, personnel and equipment management and construction safety guidance, which can provide comprehensive and accurate data support for bridge construction management and construction optimization. The results show that: (1) bridge construction KG that takes into account the dynamic features of bridge projects can effectively integrate multiple elements; (2) the bridge construction KG is dynamically updated through real‐time comparison and advance prediction based on the dynamic data collected by multi‐sensing equipment at the construction site, and can provide effective data support for guiding bridge construction safety; and (3) the construction management prototype system based on railway bridge construction KG can provide accurate data support for material traceability, personnel and equipment management and assisted risk event decision‐making. The results of the comparative experiment between the KG group and the spreadsheet group showed that utilizing the KG saved approximately 50% of time and achieved a 20% higher accuracy rate in the material traceability task compared to the spreadsheet group. In general, this study proposes a dynamic data‐driven construction method of railway bridge construction KG, which can effectively realize the effective integration and management of multisource data in the bridge construction process, provide the necessary scientific basis for fine bridge management, and help to improve bridge informatization management level.
Exchange Rate Effects and Performance of Financial Institutions in South Sudan

The different financial institutions, including those in South Sudan, have continued to have an uncertain future due to the changes in the macroeconomic environment and the political state of the country. The argument for financial reforms and arrangements requires South Sudan's authorities to devise informed decisions on how to critically match money supply and fulfillment of demand for money to a fairly standardized financial system. The objectives that underpinned the study were to examine the impact of foreign exchange rates on the performance of financial institutions in South Sudan. The study was based on the positivist philosophy because the researchers collected data from the field and used it to arrive at a conclusion. The target population was composed of the 30 registered financial institutions of the CBSS, which was used as the sample. The researcher used secondary data to obtain the findings of the study. In addition to descriptive statistics and diagnostic tests, the researcher also performed regression and correlation analysis to test the effects of independent variables on the dependent variable and the linear relationship between the variables, respectively. The different financial institutions that were considered in the study were selected using systematic random sampling. The researcher collected data from various sources, including the leading financial institutions in South Sudan. The Econometric Views (EViews) software was used for data analysis and management. The correlation matrix was estimated to check for severe correlation and the possibility of multicollinearity in the estimated model. The results showed that there was an inverse and statistically significant relationship between foreign exchange rate and the performance of financial institutions in South Sudan. In conclusion, the government can use macroeconomic variables to influence the performance of financial institutions and improve policy formulation and implementation. Keywords: Exchange Rate, Performance, Financial Institutions, South Sudan &nbsp