Reviewerly/exHarmony huggingface dataset:
Don't Walk Away! Virtual Safety Boundaries for Collaborative Virtual Reality Learning Environments

This Work-in-Progress Research paper explores how to design and implement Collaborative Virtual Reality Learning Environments (CVRLE) taking Teacher-Student Dynamics (TSD) into account. CVRLEs engage students in a virtual representation of a learning space. However, they do not incorporate TSDs, which are key elements of in-person teaching. The current work explores how to recreate one specific TSD: the watchfulness teachers have over the students' location during a field trip. We propose and compare seamless approaches to recreate this TSD inside CVRLEs via virtual safety boundaries around the teacher. These boundaries keep students in proximity to their instructor as they explore the CVRLE. The current work explores five approaches: 1) an invisible wall (used as baseline), 2) sound-based feedback, 3) a virtual companion, 4) a translucent rope connected to the teacher and 5) a translucent dome mesh around the teacher. The approaches were validated by five middle school teachers, who provided feedback about them from an educator's point of view. The interviews highlighted the importance of subtle and simple approaches that provide a sense of freedom to the students and minimize cognitive load while maintaining the TSDs. Overall, the vision of this Work-in-Progress is to solidify CVRLEs into a plausible method to perform teaching and learning when co-presence between teacher and students cannot be guaranteed. The design guidelines from this project will inform the creation of future interactive CVRLEs.
LS-14 Test Suite for Long Sequences

Random number sequences are used in many branches of science. Because of many technical reasons and their practicality, pseudo random sequences are usually employed in place of true number sequences. Whether a sequence generated through a deterministic process is a pseudo random, in other words, random-looking sequence or it contains certain patterns, can be determined with the help of statistics and mathematics. Although, in the literature there are many statistical randomness tests for this purpose, there is no much work on test suites specialized for long sequences, that is sequences of length 1,000,000 bits or more. Most of the randomness tests for long sequences use some mathematical approximations to compute expected values of the random variables and hence their results contain some errors. Another approach to evaluate randomness criteria of long sequences is to partition the long sequence into a collection short sequences and evaluate the collection for the ran- domness using statistical goodness of fit tests. The main advantage of this approach is, as the individual sequences are short, there is no need to use mathematical approximations. On the other hand when the second approach is preferred, partition the long sequence into a collection of fixed length subsequences and this approach causes a loss of information in some cases. Hence the idea of dynamic partition should be included to perform a more reliable test suite. In this paper, we propose three new tests, namely the entire R2 run, dynamic saturation point, and dynamic run tests. Moreover, we introduce a new test suite, called LS-14, consisting of 14 tests to evaluate randomness of long sequences. As LS-14 employs all three approaches: testing the entire long sequence, testing the collection of fixed length partitions of it, and finally, testing the collection obtained by the dynamic partitions of it, the proposed LS-14 test suit differs from all existing suites. Mutual comparisons of all 14 tests in the LS-14 suite, with each other are computed. Moreover, results obtained from the proposed test suite and NIST SP800-22 suite are compared. Examples of sequences with certain patterns which are not observed by NIST SP800-22 suite but detected by the proposed test suite are given.
THE IMPLEMENTATION OF SELF-DIRECTED DIALOGUE TO IMPROVE STUDENTS’ SPEAKING ABILITY AT ELEVENTH GRADE OF MAN 2 BULUKUMBA

This study aims to determine whether the implementation of self-directed dialogue could improve the speaking ability of class XI MAN 2 Bulukumba. The researcher applied the pre-experimental research method using a one group pre-test and post-test design and collected data by giving a pre-test and post-test. The sample of this study were 24 students of class XI A MAN 2 Bulukumba. The samples were taken using purposive sampling technique. Data were analyzed using pre-experimental. Based on the results of data analysis, it was obtained that the t-test value was 14.11 and t-table was 1.714 at the significance level of 0.05. Thus, it could be assumed that H₁ is accepted, which indicates that there is a significant increase in the students' abilities before and after being taught with the implementation self-directed dialogue. Therefore, it can be concluded that the implementation of self-directed dialogue was effective for improving students' speaking ability in grade eleventh of MAN 2 Bulukumba in the 2023/2024 academic year.
A Hybrid Undersampling-SMOTE Method for Imbalanced Big Data Classification

Imbalanced data is an important issues and challenges faced in data classification. This will lead to poor performance of binary classifiers, this is due to bias in classification in favour of the majority class and lack of understanding of the influence of the minority class, while the minority class is usually the most important in the classification process. In order to find a compromise between the information loss and balance the data set before applying the classification, the research proposed a hybrid algorithm based on the use of clustering methods to divide the majority class into subgroups in the first phase, and using a method to encode the majority class. The Algorithm used the code to group samples that are similar to each other and reduce the majority class count. At the same time, the Synthetic Minority Oversampling Technique (SMOTE) was used to increase the number of minority class samples in the next phase. The study examined the impact of the proposed algorithm on five classifiers based on the AUC and F-score post-classification performance parameters using benchmark datasets with different sizes and imbalance factors. The results showed that the proposed algorithm significantly improved the performance of the classifiers when applied to the resampled data.
Innovating Healthcare IoT with a Secure Blockchain Consensus Algorithm based on Verifiable Random Ranking

The Internet of Things (IoT) is helping the healthcare industry innovate. Medical professionals are no longer confined to hospitals or physical locations. IoT devices are used in healthcare for remote monitoring of vital signs, transmission and reception of private data, and other similar applications. Protection from cyber threats is the most vital aspect of IoT device operation. Malicious activities result in the leakage of sensitive data and the malfunctioning of devices, which becomes a critical issue. As a result, it is now a serious endeavor to create effective solutions that can safeguard the data and record exchange networks of every IoT device. To address some critical issues with current consensus algorithms, this paper proposes the verifiable random ranking (VRR) based Secure Blockchain Consensus (SBC) mechanism. In place of conventional algorithms, we developed new techniques for managing active nodes and evaluating node reliability and robustness. Our experiments show that the VRR-SBC algorithm speeds up consensus, improves security, and reduces the price of verification. The results of the simulation demonstrate the usefulness of the blockchain era for limited devices and provide an opportunity to assess the scope of the consensus algorithm's applicability.
Personalized control in foreign language learning

The article considers personalized control as the basis for an individual development trajectory, an individual plan for improving foreign language communication skills. The tool for its implementation is individual success monitoring in foreign language learning followed by the analysis of test results with the participation of the teacher as a consultant, which makes it possible to identify the ways of overcoming existing problems in mastering a foreign language. The article analyzes the results of monitoring, conducted among students at the Institute of Philology and Intercultural Communication (Kazan Federal University), and concludes that further work should be done to determine the individual path of each student in eradicating their weak points. The decision-making remains with the students themselves; however, additional courses in the development of receptive skills may become a motivating factor, when the period of pseudo-passivity actually lays the foundation for improving communicative competence through the involuntary acquisition of foreign language vocabulary and grammar. Success in listening or reading comprehension, based on authentic texts, inspires confidence in further improvement of communicative competence and allows, through self-analysis and self-assessment, determining guidelines for each student’s progress in learning a foreign language.
The Use of Timetable Learning Media to Enhance Student Engagement in Mathematics for Grade II A at Baiturrohman GMI Jember Elementary School

This research is a qualitative study that explores the use of a timetable board as a learning tool to enhance student engagement in Mathematics, specifically the topic of time units, for Grade II A students at Baiturrohman GMI Jember Elementary School. The objectives of this study are to determine 1) The process of using the timetable board in teaching Mathematics, focusing on time units, for Grade II A students at this school, and 2) The improvement of student engagement in Mathematics, particularly in the topic of time units, through the use of the timetable board in Grade II A at this school. The data collection techniques include lectures (material delivery), observation, discussion, tests, and documentation. The subjects of this study are 18 students in Grade II A. The implementation of the learning activities using the timetable board as a teaching aid is deemed successful due to the students' significant curiosity during the learning process. This curiosity has led to increased student activity during the learning process, with a majority of students showing a 50% improvement in understanding the material related to time units in Mathematics. In conclusion, this research suggests that using the timetable board as a learning tool effectively enhances student engagement in Mathematics, particularly in the topic of time units, for Grade II a students at this Elementary School.
The Role of Lecturers and Support of Educational Personnel and Student Understanding of Program Governance the Study Will Improve the Quality of the Study Program Services

The role of lecturers and support from educational staff as well as student understanding in improving study program services. The location of the activity is in the Informatics Study Program, Faculty of Computer Science, Bhayangkara University. The research method used is a quantitative method with a cause and effect relationship approach with a sample of respondents from 3 independent variables and 1 dependent variable. The sampling technique uses Proportionate Stratified Random Sampling so that it can be used proportionally according to groups or strata of the population or respondents. Analysis of the role of lecturers and support from educational staff as well as students' understanding of study program governance can improve the quality of study program services and have an impact on increasing accreditation scores. Research regarding the role of 3 (three) independent variables as discussion material is still rarely discussed in Study Program Governance. So it is necessary to consider whether students' understanding of the existence of study program services can improve the quality of study program services and will have an impact on increasing the value of study program accreditation.
Comparison of State-of-the-Art Algorithms for Graph Isomorphism

#그래프 동형 #안정된 색칠 #백트래킹 #그래프 표준형 #graph isomorphism #stable coloring #backtracking #graph canonization
A Comparative Analysis of the Motion Recognition Rate by Direction of Push-up Activity Using ELM Algorithm

In this paper, we propose a motion recognition system for each direction of push-up activity using ELM algorithm. In the proposed system, a recognized motion consists of three parts. The first part is the process of reading motion data. In the process, the data acquired from the motion capture system is entered into the system
INCONSISTENT REALITIES OF ONLINE-EDUCATION

The article discusses some issues related to the transformation of the education system, which is largely due to the penetration of digital tools into the educational environment. The demand for IT technologies is emphasized, on the one hand, by the requirements of digitalization of the economy, which needs highly qualifi ed information specialists, and on the other hand, by methodological and didactic teaching practices, which are largely based on the use of electronic resources. The analysis of the contradictory nature of online education is given, the positive and negative consequences of its use in the educational process are investigated, its role in the processes of adaptation to the rapidly changing social and educational context is considered, its importance as the most important factor of socialization is emphasized. It is emphasized that distance learning is not only qualitatively new, but also a suffi ciently productive and fl exible form of learning that can be applied in various educational settings, and this is its universality. Attention is drawn to the fact that the success and relevance of distance education depend on the degree of use of traditional forms of education, the use of educational methods and practices that have become classical. The role of digitalization in strengthening the processes associated with the individualization of learning is emphasized, which is dictated by the requirements of industry 4.0. Digitalization creates conditions for self-realization, the formation of a space of competencies and skills that are in demand in post-industrial times. At the same time, negative psycho-emotional consequences of excessive fascination with IT tools are revealed, which often become mechanisms of manipulation of individual and collective consciousness. These problems taken together determine the objectives of the study – to draw attention to the ambiguous nature of online education, to show its relevance to the realities of socio-economic and educational time, to demonstrate the benefi ts and advantages that are provided by real-time learning, but based on the use of electronic resources. Being essentially an innovative pedagogical practice, distance learning meets the requirements of a transforming education system in which increased attention is paid to the issues of individualization of learning. Personalization as one of the leading trends allows us to expand the range of additional knowledge, as well as digital competencies demanded by modern modernization processes, which are somehow caused by the digitalization of the economy. The results of the study allow us to identify objective factors contributing to the disclosure of the contradictory nature of online education, the defi nition of the main trends in its development, the need to use it as an educational technology. The scientifi c novelty consists in identifying and analyzing those factors that ensure the effectiveness of digitalization of education, taking into account its possible consequences.
Enhancing Early Childhood Financial Literacy Through FinSOLEkid Indonesia: A Comparative Study of Digital Platforms

This study investigates the impact of FinSOLEkid Indonesia, a game-based educational application, on financial literacy among early childhood learners aged 5-6 years. Utilizing a quasi-experimental design with two experimental groups, one using a PC version and the other an Android version, the study aims to determine the effectiveness of digital platforms in enhancing financial understanding. Subjects were chosen through purposive sampling based on their interaction with money, comprehension of in-game instructions, and ability to use digital devices. Data collection involved multiple-choice tests tailored with game elements and visual aids to suit the developmental stage of the participants. The analysis, conducted using the Kruskal-Wallis test and N-Gain scores, revealed that the PC version of FinSOLEkid Indonesia was more effective in augmenting financial knowledge than its Android counterpart and conventional methods. However, the suitability of the application for children under the age of 5-6 remains questionable due to the presence of written instructions. The study highlights the importance of selecting appropriate educational media and content for early childhood. It suggests that such technology-enhanced learning tools, while effective, need to be tailored to the developmental needs of the learners. These findings offer insights into the potential of digital learning platforms in early childhood education, emphasizing the need for age-appropriate design and content in educational technology.
Accounting Information System in Egg Trading Business with Consignment Sales Method

UD Berkah Mutiara Telur is a company engaged in the sale and purchase of eggs. Because the company sells on consignment, wholesale, and retail, recording transactions that have been carried out using books and Microsoft Excel has become difficult because variations in sales cannot be recorded properly and the data becomes out of sync so that data differences often occur, especially on stock. goods, the amount of receivables, and the amount of debt that is not monitored. Therefore, companies need an accounting information system that can record the entire transaction process running in the company so that the data becomes integrated and facilitates data monitoring. The system was developed using the System Development Life Cycle (SDLC) method which consists of planning, analysis, design, implementation, testing, and maintenance stages. The system can assist companies in managing sales on consignment, wholesale, and retail, generate financial reports, and help monitor stock, accounts payable, and receivables.
Implementasi Algoritma Naïve Bayes Dalam Menganalisis Jumlah Live Stream VTuber Skem

YouTube is evidence of the development of leading digital technology in the media and entertainment sector. YouTuber is a term for those who create content or broadcast live on YouTube media. Not all YouTubers are able to express themselves directly in the content they create. For this reason, Virtual YouTubers were created, which are 2-dimensional or 3-dimensional virtual characters created using computer software to make it easier for YouTubers to interact with viewers. This research aims to analyze the live broadcasts of VTuber HoloH3ro, namely Kaela Kovalskia, Vestia Zeta, and Kobo Kanaeru, which contain schemes during the live streaming. With a large amount of data for each live stream time, a Naïve Bayes algorithm is needed through the use of range and frequency features, so accuracy results will be obtained which will be tested using the Confusion Matrix. The dataset used was taken from the kaggle.com site regarding the scheme live stream schedule conducted by HoloH3ro.
Analisis Metode Certainty Factor Pada Sistem Pakar Diagnosa Kerusakan Sepeda Motor

Motorcycles are a predominant mode of transportation in Indonesian society, comprising 84.5% of the total transportation vehicles in 2021 according to national BPS data. Despite providing convenience in mobility, motorcycles are susceptible to disturbances or damages that can hinder normal usage and potentially lead to accidents. Many motorcycle riders lack knowledge or awareness regarding potential issues with their motorcycles. This research aims to analyze the implementation of the certainty factor method in an expert system for identifying motorcycle malfunctions, with a focus on Giska Servis workshop. The certainty factor method serves as a reasoning tool to determine identification outcomes based on identified symptoms. The results of this study are expected to contribute to facilitating motorcycle riders in diagnosing symptoms of malfunctions in their vehicles. The certainty factor method offers a systematic and structured approach to identifying motorcycle issues. Through the implementation of this method, the research attempts to measure the success rate of the expert system in diagnosing malfunctions. Data from the identification results at Giska Servis workshop will be comprehensively analyzed to evaluate the accuracy and effectiveness of the certainty factor method in this context.By highlighting the success of this method, this research is expected to provide valuable insights for the development of expert systems for motorcycle issue identification. The findings of this study can serve as a guide for workshops and motorcycle users to enhance understanding and management of vehicle issues, thereby minimizing the potential for accidents and extending the lifespan of motorcycles.
Implementasi Algoritma Naïve Bayes dalam Menganalisis Sentimen Review Pengguna Tokopedia pada Produk Kesehatan

It must be realized that customer satisfaction is the main goal for companies in developing their business. Because customers' opinions written on social media will have a big influence on the company and potential customers. In its development, it is increasingly found in various online media, one of which is Tokopedia. Product reviews are an important source of information regarding quality, service and delivery from both consumers and manufacturers. With a very large amount of data for each product on Tokopedia, analyzing and concluding product review information will definitely take a lot of time if done manually. To overcome this, a sentiment analysis system is needed that can automatically extract important information that can objectively determine product quality and handle large amounts of textual information. The sentiment analysis system consists of several stages, namely crawling, pre-processing, word weighting, and sentiment classification. By applying the Naïve Bayes algorithm through selecting range and frequency features, accuracy, accuracy and recall results will be obtained using the Confusion Matrix test. The dataset used is from the kaggle.com site regarding customer sentiment on health products with the type of mask. using the Naïve Bayes Algorithm Method to determine the sentiment of user reviews by classifying 2 positive and negative classes using the NLP approach produces an accuracy value of 88%.&#x0D;
The Expert System of Determining the Type of Malaria by using Dempster-Shafer Method

Malaria is the most dominant disease in Asia and Africa and may become a life-threatening disease for it suffers. The types of malaria such as Plasmodium Vivax, Plasmodium Ovale, Plasmodium Malariae, and Plasmodium Falciparum are mostly infected people around the world. These types of malaria have certain symptoms that drives difficulties for some patients to confirm which malaria that their infected. A clinical testing and medical diagnostic assessments may be performed to determine the types of malaria, but utilizing a system also brings some benefits for rural areas which lack of medical facilities. The study develops a system by implementing the Dempster Shafer method to determine types of malaria. We collected the knowledge from the experts including 18 possible symptoms along with the density value. This paper present 5 cases of sufferers and provide the system result with the possibilities of malaria types. The result pointed out a various percentage of malaria types that may infected to the patients.