Reviewerly/exHarmony huggingface dataset:
Sejari Padlet (Semangat Belajar IPS Dengan Padlet)

SEJARI PADLET (Semangat Belajar IPS dengan Padlet) which is carried out on grade 6 students at Karangasem State Elementary School aims to increase students' enthusiasm or interest in learning. Padlet application as a container for sharing learning materials from teachers. Students independently explore the features of the Padlet application which has been filled in with learning material by the teacher. Students do not need to download the application but simply open the link. The Padlet application can be opened at any time so students can study the material again in sequence. Best practice has been implemented by applying the learning by doing method in several stages. The first stage is the preparation stage, the second stage is training, the third stage is the implementation of the learning process. The results of questionnaire analysis and observations during social studies learning before and after using the Padlet application increased by 42.8% to 86.8% from 44% before learning using the Padlet application. Previously, only around 4 students out of 9 students showed interest in taking part in social studies lessons. After using the Padlet application, around 8 out of 9 students have shown interest in taking part in social studies learning. The average student learning outcomes also increased by 13.75 to 90 from the previous 76.25. All student learning outcomes are above or equal to the KKM, meaning students understand the lesson material more easily. From these data it can be concluded that the Padlet application is able to increase students' enthusiasm and interest in learning social studies.
Telugu Dependency Treebank

We discuss Telugu Language and Treebanks briefly in this work. Initially, we'll go over the Telugu language briefly. The paninian grammatical model utilized for Telugu dependency representation is then described. Following that, we explain Telugu treebanks and the various formats used to express these treebanks. We also discuss the Telugu language and its representation in the Telugu Dependency Treebank, and we give information on the Telugu language and the Telugu Dependency Treebank. Natural languages are often morphologically rich, and they create sentences in a variety of ways. Researchers have been investigating approaches to annotate text with linguistic knowledge since the advent of machine translation in the 1960s. Previous studies on Indian languages were done at the chunk level. The present shallow parser morphologically parses the input text to the chunk label. Researchers are considering working at the phrase level in the future. They broke the phrases down into smaller parts. The relationship between chunk heads is essential to proceed to sentence-level parsing. This results in reliance parsing.
Application of Interactive Learning Games in Stimulating Knowledge About Object Recognition in Early Childhood

Teachers and parents must pay close attention to the golden age phase of early infancy since children's growth and development can occur swiftly during this time. In the early childhood learning process, it is crucial to transfer knowledge so that children can acquire information, including the introduction of objects into the child's environment. There are already a plethora of diverse, entertaining learning materials for young children. One of them is interactive learning media that emphasizes visual features to catch children's attention during the learning process. Based on the relevance of learning media in early childhood, the purpose of this research is to build interactive learning game media in order to promote comprehension and stimulate early children's ability to recognize the introduction of things. 93.3% of students like object recognition learning media and the Figures on the learning media, 80% of students can comprehend object recognition material and can answer according to choice, and 86.67 % of students stated that the terms of color, animation, audio, video, and text were feasible. So that this object identification learning material has an appealing visual design, is simple to use, and can be comprehended by pupils.
Ontology for Architectural Knowledge Condensation in a Co-Localized Agile Environment

Agile software development companies considered small entities (VSE) face a new reality of remote development. Remote communication has generated many videos derived from video calls recorded for later reference. The video calls recorded contains architectural knowledge from virtual meetings and is essential for companies facing the knowledge vaporization problem. However, only some proposals in the literature can potentially manage AK in videos. This article proposes a solution to recover this architectural knowledge contained in videos using an ontology as a classification scheme, following the architectural knowledge condensation concept. We validated our proposal to manage architectural knowledge following the Methontology guidelines. Implementing an ontology as a classification scheme represents a step forward to achieving the condensation of architectural knowledge in an agile development environment for VSE.
Performance Analysis of Federated Learning in Orbital Edge Computing

Federated Learning (FL) is a promising solution for collaborative machine learning while respecting data privacy and locality. FL has been used in Low Earth Orbit (LEO) satellite constellations for different space applications including earth observation, navigation, and positioning. Orbital Edge Computing (OEC) refers to the deployment of edge computing resources and data processing capabilities in space-based systems, enabling real-time data analysis and decision-making for remote and space-based applications. While there is existing research exploring the integration of federated learning in OEC, the influence of diverse factors such as space conditions, communication constraints, and machine learning models remains uncertain. This paper addresses this gap and presents a comprehensive performance analysis of FL methods in the unique and challenging setting of OEC. We consider model accuracy, training time, and power consumption as the performance metrics under different working conditions including IID and non-IID data distributions to analyse the performance of centralised and decentralised FL approaches. The experimental results demonstrate that although the asynchronous centralised FL method has high fluctuations in the accuracy curve, it is suitable for space applications in which power consumption and training time are two main factors. In addition, the number of sampled satellites for decentralised FL methods is an important parameter in non-IID data distribution. Moreover, increasing altitude can reduce the training time and increase the power consumption. This study enables us to highlight a number of performance challenges in OEC for further investigation.
PERAN LEMBAGA PENJAMIN SIMPANAN TERHADAP SALDO UANG ELEKTRONIK PADA DOMPET ELEKTRONIK DANA

DANA is a technology for electronic wallet or e-wallet that is used for transactions without cash or cards but only with a user's start. That ease and effectiveness led to the high consumption of DANA. But lately electronic wallet users have concerns over the balance on their electronic wallets. Indonesian have Institution Lembaga Penjamin Simpanan (LPS) is regulated number 24 of 2004, it provides security and gives its customers confidence in existing systems and institutions. It is still a matter of whether LPS played a part in the transaction. The research aims to see the extent of LPS 'role in transactions in DANA applications. By using descriptive research methods of anaitis by using secondary data of legislation, previous research, and literature. The study shows that LPS has no role in the protection of public money that is kept in the application of DANA because legal regulations do not permit it. The LPS also have no intervention function in policy or financial transaction activities in the fund in DANA
Analyzing the Impact of Digital Media on Promoting High-Quality Skiing Education: A Case Study of Online Tutorials and Social Media Campaigns

This study investigates the impact of digital media on promoting high-quality skills by assessing its impact on collaborative education and technological skills within Chinese higher education. A survey-based strategy was adopted and three explanatory variables were incorporated, namely students’ learning using social media, students’ experience of using social media in teaching and social media usage frequency. The learner’s motivation was also included as a mediator. The study collected data from university students across mainland China, focusing on those engaged in learning using social media platforms. Structural Equation Modelling (SEM) was employed to analyze the data. The findings showed that usage of social media for learning positively impacts collaborative education, indicating students’ preference for interactive projects and online lectures on social media. Regarding the impact on technological skills, the findings showed that social media usage frequency positively influencedtechnological skills among students in Chinese universities. Additionally, it was found that learner’s motivation significantly mediated the association of social media usage frequency with collaborative education and technological skills. Learner’s motivation played a significant mediating role in the relationship between students’ experience of social media learning and collaborative education. The findings hold implications for educators, institutions, and policymakers striving to leverage digital media to advance high-quality skills in educational settings.
Automated coding Non-manual Markers: Sign language corpora analysis using FaceReader

The present study aims to introduce the possibility of coding facial expressions and head movements in different sign languages using the FaceReader program. Considering that Non-Manuals Markers (NMMs) (facial expressions, head and torso movements) are an important part of the signed languages grammar, the FaceReader’s automatic coding ability would be very useful for investigating a larger number of signed data, The program can calibrate participants’ faces, automatically annotate emotions (emotive facial expressions), Action Units (AUs) (grammatical NMMs), their intensities, as well as head movements. Overall, it seems highly beneficial to use the program for recognizing facial and head movements in sign languages. However, there are some disadvantages to adopting it, such as pricing, the lack of torso movements and head protraction/retraction coding, and difficulties in analyzing participants with beards and glasses. Some of these disadvantages can be addressed through the use of other softwares or methodologies strategies.
The Current State Of Scientific Support In Investigating Criminal Offenses Involving Illegal Takeover And Seizure Of Enterprises And Their Assets

In order to ensure sustainable development of economy and national security, which includes economic security, it is crucial to create corresponding protection instruments and support the unhindered legitimate operation of economic entities. To prevent infringements upon their rights, such as illegal takeovers and seizures of enterprises, organizations, and institutions of various ownership forms, encroachments on their property, assets, and land plots, it is necessary to ensure appropriate countermeasures against such occurrences, in particular, through criminal and criminal procedural methods. To support activities aimed at countering these phenomena through criminal procedural methods, it is vital to ensure scientific development of relevant aspects associated with such activities. In this context, the Article Purpose is to determine the current state of scientific support for investigating criminal offenses involving the illegal takeover and seizure of enterprises, institutions, organizations, their property, and agricultural land plots. On the basis of generalizing normative provisions of the current criminal legislation, theoretical developments of Ukrainian scientists, the paper outlines scientific development peculiarities of the problematics related to criminal responsibility for offenses associated with takeovers, as well as research and development of the methodology for investigating these offenses.
Architektura informacji a ekologia informacji

The focus of this article is the relationship between information architecture and information ecology. The paper wants to signal and show the potential mutual usefulness of the achievements of both research domains that would serve their development. Using the method of literary analysis and criticism to start with the information on information ecology found in the classic book by L. Rosenfeld and P. Morville, “Information architecture for the world wide web” (2005), infoecological requirements were presented on the basis of information architecture requirements for websites. Examples of achievements in information architecture and information ecology are also presented. The conclusion states that information architecture and information ecology are new research domains that open new gateways to the world of inspiration in the information space of human beings in the 21st century.
Textures of Volcanites as Indicators of Dangerous Impacts of Environment (on the Example of the Late Cenozoic Volcanics of the Caucasus)

Textural features of lava and ignimbrite formations indicate the high role of volatile components in their formation and the rapid release of volatile from the solidifying melt. This creates a high level of danger to the environment. Therefore, it is important to study the textures of the formed volcanites to predict the degree of danger in the event of a possible resumption of magmatic activity.
Changing the development trajectory of Russian postgraduate studies

Today, the institute of postgraduate studies, as one of the important tools for training highly qualified personnel, is moving to a new algorithm of work, enshrined in a number of regulatory documents. In this regard, it is necessary to assess the essence and possible consequences of reforming the third level of higher education. For this purpose, we used: analysis of a corpus of materials published in leading Russian journals that specialize in issues of education and management of scientific and educational activities; secondary analysis of sociological data; a number of general scientific and private law methods. It has been established that the process of reforming graduate school is a necessary step designed to resolve accumulated problems and contradictions. A proposal has been put forward on the need for government agencies and the academic community to maintain a constructive dialogue in order to effectively adjust the ongoing legislative measures and develop a future national educational policy in the field of higher education. As a result of a comparative analysis of two postgraduate study models, their key differences are highlighted and the difficulties of transition to a new model are predicted. Measures are proposed to further improve the effectiveness of third-level higher education programs.
Implementation of K-Nearest Neighbor for Fall Position Detection of Dementia Patients Based Microcontroller

A microcontroller-based detection tool for the presence of patients with dementia has been made using the K-Nearest Neighbor (KNN) method with the help of coordinate points that can be seen via Google Maps. which is based on patient care with a patient-oriented approach. The targets of this research are (a) designing and implementing a fall detection system using the mpu6050 sensor, (b) using the (KNN) method to determine the coordinates of the location of dementia patients using GPS. The research method starts from making a prototype and measuring system performance. The test results on GPS produced an average latitude error of 0.002091% and an average longitude error of 0.000032% in Pauh District, while in Lubuk Kilangan District the average latitude error was 0.002641% and an average longitude error of 0.000150%. The KNN method with the Eucledian distance formula can help supervisors find out the nearest police station to the patient through the coordinate points detected by GPS by taking the smallest value from the comparison of values in the form of degrees between the Pauh police station and the Lubuk Kilangan police station for the patient. Overall the tool can function well.
Technology Modernization for Enhanced Cybersecurity in Banking Applications

This paper addresses the imperative need for technology modernization in banking applications to mitigate the escalating threat of cyber attacks. As the financial industry increasingly relies on technology to deliver services, the vulnerabilities and risks associated with outdated technology stacks become more pronounced. This paper explores the benefits of upgrading banking application technology stacks to the latest and most advanced solutions to bolster cybersecurity defenses and safeguard sensitive financial information.
Navigating the Digital Frontier: Strategies for Securing Personal and Financial Data in Mortgage Applications

The digital transformation of the mortgage industry has significantly enhanced the efficiency and accessibility of mortgage applications. However, this evolution also introduces complex challenges in securing personal and financial data. The research paper delves into the multifaceted strategies and technological advancements employed to safeguard sensitive borrower information in the digital mortgage landscape. Drawing from a diverse array of scholarly papers and industry articles, the paper explores the integration of cutting-edge technologies such as blockchain, encryption, and secure online portals, which collectively fortify the security framework within the mortgage application process. It examines the role of blockchain in creating immutable records and ensuring transparent transactions, while also discussing how encryption and secure data storage methods are pivotal in protecting against data breaches and cyber threats. The paper further highlights the importance of regulatory frameworks and industry standards in guiding and enforcing data security practices. Through this comprehensive analysis, the research provides insights into how these technological and regulatory mechanisms interplay to maintain the integrity and confidentiality of borrower data, thereby fostering trust and reliability in the digital mortgage sector
[The encounter of the 'Golden Priestess' with Sanyika - An analysis of the creative dynamics of the Weöres-Károlyi couple from the perspective of Amy Károlyi's oeuvre].

The circumstances of the encounter of the Weöres-Károlyi couple, as well as some dynamic details of their marriage, have been surrounded by considerable literary and public interest during the past decades. This interest however largely focused on the poetic oeuvre of Sándor Weöres and on his struggle with alcohol. However, the impact of this legendary encounter on Amy Károlyi's art has been a subject of few analyses. The purpose of this study is to gain a deeper understanding on the impact of this encounter with Sándor Weöres and the life- and creative fellowship with him had on Amy Károlyi's art and life, as well as what creative influences can be identified in the couple's oeuvre. The study identifies the most common beliefs ("legends") regarding the Weöres-Károlyi couple, as well as the most important literary imprints of their marital and creative community and their effects on Károlyi's poetry through an overview of Károlyi's confessional works. Based on the revealed biographical and artistic associations, it can be concluded that despite the fact, that Amy Károlyi's literary work was fulfilled in her marriage, and creative fellowship with Weöres, her figure still appears in literary memory as the support and "savior" of her husband, Weöres.
The Impact of Quantum Computing on Cybersecurity

The advent of quantum computing heralds a transformative shift in the computational landscape, offering unparalleled processing power that promises to solve complex problems far beyond the reach of classical computing. This quantum leap also poses significant challenges to the foundations of current cybersecurity practices, especially encryption methods that safeguard digital communications and data.
PaperObjective classificationof empirical probability distributionsand the issue of event detection

The paper concentrates on the issue of classifica-tion of empirical probability distributions (histograms), whichis useful both in management situations and in event detectionor event mining. While existing approaches to event detectionconcentrate on the use of selected moments or other character-istics of empirical probability distributions, we postulate thatfull empirical distribution preserves more of needed informa-tion then selected moments of this distribution, thus multiplecriteria classification of distributions can be most effective inevent detection.
Approximation of BPS Skyrme model using modified Lagrangian Skyrmion

One of the nuclear atomic models represented by Skyrmion was the Skyrme model. This model was a modified nonlinear sigma model with a Skyrme field where the classical solution use generalized sixth order terms and potential terms. The binding energy that will be studied in the Skyrme SU(2) model is to generalize the second order nonlinear sigma model terms with sixth order derivative terms. The Lagrangian will be obtained for these two terms to find the BPS (Bogomolny Prasad Sommerfield) solution for the profile function numerically. The result of numerical calculation will be used to calculate static energy and rotational energy, where the characteristic of the nucleus can be observed from these two energies. Furthermore, the value of the coupling constant in the Lagrangian Skyrmion will be calculated from the static energy and rotational energy obtained previously. These values are expected to help in the application of Skyrme model for many research physics field.
Automated Facial Recognition in Older Photographs Using One-Shot Learning in Siamese Networks and Transfer Learning

A lot of historical information comes in various forms, such as old documents, papers, photographs, videos, audio, and even artefacts and sculptures. Photographs, audio, and videos are especially important because they effectively convey information. When we convert these into digital versions, it becomes easy to share, access online or offline, copy, move around, back up, and store in numerous places. However, a challenge with digital content is that it is often difficult to search due to the absence of readable text. Consequently, we cannot effectively analyse and utilise critical information. To make it useful, we manually look at pictures and add tags to create labels. While basic labels suffice for most searches, it becomes more complicated when dealing with a large number of photographs. Enhancements in search capabilities are needed to make the process easier, quicker, and more efficient. Fortunately, recent technological advances, such as artificial intelligence, provide us with facilities to simplify this process. This paper explores how artificial intelligence can streamline this process, enhancing search efficiency and enabling automatic identification and tagging of individuals in photos, thus facilitating easier access and analysis of digital archives.It is anticipated that manual tagging efforts could be reduced by approximately 80%, and the searchability of photographs could be enhanced by about 84%.