Reviewerly/exHarmony huggingface dataset:
The formation of project thinking in training specialists in working with youth: Interaction with NPOs and educational institutions

Modern socio-economic conditions necessitate the active involvement of the population and, first of all, youth in the activities of civil society institutions, including the work of non-profit organizations that can become a driving force for the integration and mobilization of society. At the same time, in most sectors of human activity in recent years, a project approach has been actively introduced, in the implementation of which NPOs have significant experience. The development and implementation of a project requires a specialist possessing to have such a non-standard competence as design thinking. It is this personal and professional skill that can help a young person quickly adapt to changing conditions and can provide the necessary competitive advantage in employment and career advancement. Specialists in working with youth are able to become conductors of project thinking in the youth sphere; their activities can have a significant impact on the dissemination of the project approach among representatives of the new generation. In the course the sociological study, it was found that NPOs are a significant partner of educational organizations in the formation of project thinking of future specialists in working with youth. The existing practices of interaction between universities and NPOs in these matters serve as the basis for further expansion of cooperation and improvement of the educational process.
Features of agenda setting in Telegram

This article focuses on the aspects of agenda formation in Russian-language Telegram messenger channels. Within the framework of the classical model of M. McCombs and D. Shaw, the main principles of agenda setting by traditional media are analyzed. Building upon the findings of more recent research in the field of agenda setting in the digital space, the authors highlight the advantages of social media as communication platforms and potential reasons for their increasing popularity among both individuals and political actors. Furthermore, the relevant features of the Telegram messenger in the context of political communication are systematically described, such as the lack of strict content moderation, emphasis on the speed of information exchange, user privacy, and the need for an individualized approach to shaping the information field for each user. Based on the platform’s characteristics, a model for agenda formation is proposed, which involves categorizing channels into two levels: content information producers and news aggregators/interpreters. The hypothesis is also put forward that channels that aggregate and interpret information through an extensive network of links have the greatest potential for setting the agenda for their audience. To test the model, a pilot study was conducted using the Tgstat service, where the top 10 most cited channels from the “Media and News” and “Politics” categories for October 2023 were selected. Subsequently, no more than 50 channels were included in the analysis, those which were most frequently mentioned by the popular authors. The researchers conclude that multiple agendas can coexist within the messenger within various thematic blocks. These thematic blocks are formed through the network of links to channels that the most popular platforms on the messenger feature in their news feeds.
Online Teacher Professional Development (oTPD) for Digital Competencies in Higher Education: A Systematic Review of the Literature

The need for professional development for digital, subject-specific competencies is increasing among educators in higher education. With online teacher professional development (oTPD), this demand can be accommodated flexibly. The article presents a systematic review of the literature and evidence on oTPD for digital competencies in higher education. The purpose of the review is to identify factors that influence the effect of an oTPD programme. A total of 661 peer-reviewed articles that included empirical studies and literature reviews related to oTPD from 2010 and onwards were identified using the EBSCO and ERIC databases and screened. 57 of these were coded and included in the analysis, and 604 articles were excluded due to wrong focus, educational level, publication type, or year. The analysis identifies sixteen underlying factors that influence the effect of oTPD related to either the institutional aspect, the design of the programme, and/or the delivery of the programme. Furthermore, the review identifies political implications for research on oTPD—the institutional context including technical solutions, the general pedagogical approach, and educator support—and methodological limitations related to the ambiguity of the oTPD concepts and the transferability of case studies, which call for more research.
Full Online Teacher Training Service Scheme on Improving Pedagogical and Professional Competencies

Implementing teacher teaching training services for Islamic Religious Education and Islamic School teachers in the Indonesian Ministry of Religious Affairs ranks in 2021 was carried out with a complete online scheme. Implementing in-service teaching training aims to produce professional educators with academic, professional, personal, and social competencies. The difference in participants' conditions, such as different areas, technology tools mastery, and infrastructure availability, became a challenge for LPTK organizers. The article aims to measure the effectiveness of implementing teacher teaching training services in a whole online scheme at LPTK of the State Islamic University of Bukittinggi in 2023. This evaluation research was conducted in LPTK of the State Islamic University of Bukittinggi in 2023. The sample was selected by purposive technique with the number of samples 416 teachers, consisting of 266 Islamic Religious Education teachers and 150 Islamic School teachers. The data was collected by distributing questionnaires and analyzed using descriptive statistics. The results showed that the average paedagogic and professional competencies achievement score was 86.90 points, with a high interpretation of achievements. The implementation of teacher teaching training service in an entire online scheme at LPTK of the State Islamic University of Bukittinggi in 2023 has increased effectiveness.
Design of QR Code Technology in MC Swimming Pool Website Design to Improve User Experience and Operational Efficiency

QR Code which is an abbreviation of Quick Response Code, QR Code is in the form of a square box, similar to a barcode, but with a more detailed appearance. The use of QR Code Technology in this research serves to facilitate identification and confirmation of entrance tickets for swimming pool visitors increase the speed and easy to buy a ticket. The research methodology used in system design is waterfall method. The waterfall method displays simple processes that do not overlap with the SDLC (system development life cycle) model.The programming language used is PHP, with the implementation of the CodeIgniter 3 Framework, and MySQL as the Database management system.The problem that often occurs is when the queue of visitors enters on holidays or days when there are lots of visitors causing long queues and less efficiency in ticket sales operations and the process of entering visitors to the swimming pool.This research aims to improve the user's operational system in ordering tickets which must initially be done come directly to the swimming pool location and in the new system visitors can purchase tickets online and operational efficiency of the MC Swimming Pool through the application of QR Code technology on the website, it makes the process of checking ticket data easier so that visitors can enter the swimming pool area The result of this research is to create an information system plan that allows users to order tickets online and visitors can enter the swimming pool area quickly and easily using a QR code as a visitor entry ticket.
Path Planning Design for Avoiding Obstacles of Moving Objects Using Digital Twin Modeling

In order for autonomous driving to be effective, sufficient prior information and stability about the area of use must be guaranteed. To do this, it is necessary to ensure stability by avoiding obstacles that were not initially identified and regenerating the path. In this study, we design a DEVS-based moving path movement plan and conduct simulations in a digital twin environment. It also implements communication of moving objects to transmit and receive information about unidentified obstacles that are not within the detection range of moving objects. As a result, if an unidentified obstacle appeared, an avoidance path could be created and driven to the destination. Through the above experiment, we expect that the results of route movement in the digital twin environment will be pre-tested and used in reality.
Learned Mesh-Based Object Global Coordinate Estimation for Vehicle Tracking in Close Surveillance Environments Using Fisheye Cameras

Artificial intelligence-based methods for detecting and tracking objects in videos, typically represented by bounding boxes, are well established. However, accurately determining the global coordinates of these bounding boxes, especially in environments monitored by fisheye cameras, presents unique challenges. These challenges stem from significant variations in the bounding box
Typographic Analysis of Mapping Table for Similar Font Matching Between Hangul and Thai Fonts

When exporting or importing global content, it is essential to identify fonts with similar shapes, in addition to translating text. In our previous research, we developed a font-matching algorithm using deep learning that works across multiple languages. In this paper, we present the process of creating a pivot font mapping table, which serves as an example of matching actual Hangul and Thai fonts for similar font matching. We conducted a survey among experts to establish the pivot font mapping and confirmed its significance by analyzing typography. Using the mapping table generated through this process, we successfully matched similar fonts between Hangul and Thai, as well as Thai and Hangul. Our results demonstrate that our font matching system effectively identifies similar-looking fonts in each language.
A Case Study of Cyber Class Production Using a Multimedia Generation Tool Applied with Edutech and Analysis of Results on the Basic Survey to Identify Learners’ Characteristics and Course Evaluations

This paper is a case study in which classes were operated by creating contents using multimedia generation tools applied with Edutech for more effective cyber class operation, reinforcing the sense of reality, feedback, and interactions, and improving class satisfaction. To this end, I first planned and prepared suitable lecture contents and materials that could enhance learners
A Study on Technological Perception Analysis of LLMs through Big Data Analysis of News Articles

This study analyzed the technological perception of the LLMs through the analysis of big data in media articles and examined the changes, focusing on before and after the advent of ChatGPT. The analysis revealed that before the advent of ChatGPT, words related to chatbots and education were predominant in media reports. After the emergence of ChatGPT, keywords shifted to business, various technology sectors, and corporate-related terms. N-gram analysis showed that in 2022, articles were primarily focused on chatbots and virtual assistants, also mentioning education and content creation. However, in 2023, LLMs gained attention in diverse fields like blockchain, security, and data utilization. Topic modeling results indicated that while 2022 emphasized the use of chatbot technology, 2023 saw an expansion in the use of LLMs across various technological sectors including finance, data technology, chatbots, and semiconductors. In conclusion, the advent of ChatGPT marked significant developments in the application of generative AI across various sectors like healthcare, finance, education, and content creation, showcasing the potential of LLMs.
A Study on the Development of major competencies Diagnostic Tools for Children’s English Education: Focusing on K Women’s University

The purpose of this study is to develop the major competencies of the G department. It will do this by linking the core competencies of K Women's University with the major competencies of major subjects. Additionally, this study aims to conduct a self-diagnosis of the major competencies of students. A survey was carried out on 31 first and second-year students in Department G. The collected data underwent a data coding process. Descriptive statistics and independent sample testing using the SPSS v.21.0 statistical program were performed to conduct Levene's equal variance test F and significance probability analysis. The average achievement of the three significant competencies of Department G was analyzed to be 3.89. Among the major competencies, the creative convergence competency was found to be the highest with an average of 4.24. In addition, within the detailed competency analysis of major competencies, the highest performances were shown to be understanding multiculturalism in the development of convergence English curriculum, application of early English education in creative English education implementation, and interpersonal competency in creative convergence competency. This tool can be used as an example to evaluate the competency level of both the department's major field and individual students. Providing feedback on the current students using this tool is expected to aid in curriculum refonn and development. Additionally, it can be used as a benchmark to identify systematic improvements in major education and help create annual plans for the department. (Kwangju Women's University)
Mitigating land fire disasters: Implementation of agricultural land fire risk management information system in Aunupe Village, South Konawe Regency

Climate change, which causes increased temperatures, prolonged droughts, and dry conditions, heightens the risk of land fires. A similar scenario unfolded in Aunupe Village, where several fires occurred on agricultural land over the past three years, resulting in crop failure and degraded soil quality, leading to financial losses for land-owning farmers. To mitigate the risk of land fire disasters, an agricultural land fire disaster risk management information system is necessary in Aunupe Village, South Konawe Regency. The objective of this community-based empowerment program is to mitigate the risk of land fire disasters. To achieve the desired outcomes, initial coordination with farmer group partners is conducted, followed by the design and installation of fire sensor equipment sets in collaboration with farmer groups. Furthermore, focus group discussions (FGD) are conducted with farmer group partners to ensure their understanding and cooperation. The activities result in the development of an agricultural land fire risk management information system, facilitating the prompt detection, monitoring, and response to fire incidents in the agricultural land of the Lembah Harapan Farmers Group. Additionally, farmer group partners acquire knowledge regarding the utilization of fire mitigation systems.
International Comparative Analysis of Advanced Diagnostic Imaging Equipment Demand Characteristics Using the Bass Diffusion Model

Objectives: This paper proposed the direction of future supply and demand management policies through demand prediction and demand characteristics analysis of advanced diagnostic imaging equipment using new medical technology.Methods: This study used the Bass Diffusion Model to analyze demand characteristics for advanced diagnostic imaging equipment. Derived diffusion coefficients were applied for medium to long-term demand predictions (2021-2050). Parameter estimation employed non-linear regression analysis (SPSS 27.0). Demand characteristics were further analyzed using the ratio of the Bass model’s innovation to imitation coefficients for each country and device.Results: Comparing the imitation coefficients (&lt;i&gt;q/p&lt;/i&gt; ratio) for computed tomography (CT) and magnetic resonance imaging (MRI) among South Korea, the United States, and Japan, South Korea has the highest &lt;i&gt;q/p&lt;/i&gt; ratio for both CT and MRI. This implies that the influence of opinion leaders and group pressure is relatively more significant in South Korea, particularly in CT purchases. In the demand prediction results, South Korea’s &lt;i&gt;q/p&lt;/i&gt; ratio for CT and MRI is notably larger, suggesting that institutional pressures and collective decision-making, rather than individual clinical decisions, play a significant role in the purchase of advanced diagnostic imaging Equipment. The &lt;i&gt;q/p&lt;/i&gt; ratio for advanced diagnostic imaging Equipment in South Korea is higher than in other countries, reflecting a large power distance in the adoption of these technologies.Conclusions: This study utilizes the Bass Diffusion Model to predict the demand for advanced diagnostic imaging equipment in South Korea, Japan, and the United States. Findings highlight that imitation, not innovation, is the main driver of diffusion, with South Korea showing a faster adoption rate for CT and MRI. The study identifies factors influencing diffusion in South Korea, noting the impact of the quantity system on CT and the absence of influence on MRI. CT diffusion is positively linked to the quantity-based payment system, while MRI remains unaffected.
A Survey on the Utilization of Big Data in the Healthcare Sector and the Demand for Integrated Data

Objectives: To investigate the status of secondary data and big data platform utilization and the demand for integrated data in the health care sector.Methods: An online survey was conducted using a structured questionnaire targeting members of six academic societies in the healthcare field. A total of 220 researchers responded to the survey.Results: 88.2% of respondents said they had experience using secondary data sources in the healthcare field, and 19.0% responded that they had experience linking data using the healthcare big data platform. Among the data in the health and medical field, the most used dataset was health insurance claims data, and if linking between dataset, the most desired linked data type is ‘National Health and Nutrition Examination Survey-Health Insurance Claims Data–National Health Examination-Death Information’. The advantages of linked data on big data platforms were ‘large volume of big data or representative’, ‘diversity of data’, and ‘long-term follow-up’. The major items requiring improvement were ‘delay in time to provide data’, ‘limitation of data provision range’, and ‘low linkage rate between dataset’.Conclusions: To promote the use of linked data in the health care field, comprehensive efforts are needed, including rapid data provision, improvement of the combination rate, standardization of data, and establishment of ethical guidelines.
Distributed Ledger Technology (DLT) Regulation

The DLT Regulation aims to introduce a pilot regime for the practical application of distributed ledger technology (DLT) in post-trade services. The DLT Regulation seeks to provide a regulatory framework for the development of DLT multilateral trading facilities (DLT MTFs) and DLT securities settlement systems (DLT SSS), including for the granting and withdrawal of specific permissions (that is, permissions granted under this new regulation would allow market participants to operate a DLT market infrastructure and provide their services across all Member States). It aims at providing a mechanism, procedures and rules for allowing market infrastructures to experiment DLT with legal certainty and flexibility.
Using Learning Focal Point Algorithm to Classify Emotional Intelligence

Recognizing the fundamental role of learners' emotions in the educational process, this study aims to enhance educational experiences by incorporating emotional intelligence (EI) into teacher robots through artificial intelligence and image processing technologies. The primary hurdle addressed is the inadequacy of conventional methods, particularly convolutional neural networks (CNNs) with pooling layers, in imbuing robots with emotional intelligence. To surmount this challenge, the research proposes an innovative solution—introducing a novel learning focal point (LFP) layer to replace pooling layers, resulting in significant enhancements in accuracy and other vital parameters. The distinctive contribution of this research lies in the creation and application of the LFP algorithm, providing a novel approach to emotion classification for teacher robots. The results showcase the LFP algorithm's superior performance compared to traditional CNN approaches. In conclusion, the study highlights the transformative impact of the LFP algorithm on the accuracy of classification models and, consequently, on emotionally intelligent teacher robots. This research contributes valuable insights to the convergence of artificial intelligence and education, with implications for future advancements in the field.
Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations

In this paper, we introduce an efficient path planning algorithm designed for floor cleaning applications, utilizing the concept of Spanning Tree Coverage (STC). We operate under the assumption that the environment, i.e., the floor, is initially unknown to the robot, which also lacks knowledge regarding obstacle positions, except for the workspace boundaries. The robot executes alternating phases of exploration and coverage, leveraging the local map generated during exploration to construct a STC tree, which then guides the subsequent coverage (cleaning) phase. The extent of exploration is determined by the range of the robot's sensors. The path generation algorithms for cleaning fall within the broader category of coverage path planning (CPP) algorithms. A key advantage of this algorithm is that the robot returns to its initial position upon completing the operation, minimizing battery usage since sensors are only active during the exploration phase. We classify the proposed algorithm as an offline-online scheme. To validate the effectiveness and non-repetitive nature of the algorithm, we conducted simulations using VRep/MATLAB environments and implemented real-time experiments using Turtlebot in the ROS-Gazebo environment. The results substantiate the completeness of coverage and underscore the algorithm's significance in applications akin to floor cleaning.
Information Security and Risk Control Model Based on Plan-Do-Check-Action for Digital Libraries

To continuously and effectively control the potential risk factors of digital libraries, further improve the quality of digital library usage, ensure the smooth operation and information security of digital libraries, a security and risk factor control model for digital libraries based on the Plan-Do-Check-Action is constructed. A digital library security and risk identification model based on improved support vector machines is constructed. Based on the obtained risk identification results, a Plan-Do-Check-Action management model is implemented for information security in digital libraries. The R2L dataset in the network attack dataset is used for training and testing model performance. Then the proposed method is applied to two different digital libraries. The average accuracy of the risk identification model proposed in the research is 96.46%. The risk error of each level is maintained within 0.4%, which is within an acceptable range. The proposed method has a high recognition effect. It can be used to identify common security and risk issues encountered in digital libraries, and improve the information security performance.