Reviewerly/exHarmony huggingface dataset:
A Study on the Perception of University Officials on the Allowance of University Education of Foreign Workers(E-9)

The purpose of this study is to explore the perception of university officials on the provision of university education for foreign workers(E-9), and to suggest ways to revitalize foreign workers(E-9) study abroad based on this. For the study, data were collected and analyzed through in-depth interviews with 10 university officials who provide university education to foreign workers(E-9). As a result of the analysis, first, university officials recognized the provision of foreign workers(E-9) study abroad as a desirable decision. The university education of foreign workers(E-9) was a timely decision in a situation where the number of students at junior colleges decreased as Korea's education level increased, and junior colleges were in financial crisis. Second, an operation plan was prepared to conduct industrial consignment education for foreign workers(E-9). They were planning a systematic curriculum suitable for the characteristics of foreign workers based on the educational experience of international students. Third, university officials recognized that foreign workers(E-9) would have a positive ripple effect in various areas, from individuals to schools, businesses, communities, and countries, after receiving university education. Based on these findings, it is necessary to prepare a place for learning where foreign workers(E-9) can cultivate professional knowledge and develop and inspect curriculum suitable for the characteristics of foreign workers. In addition, it is necessary to find a way for foreign workers to use it as a human resource for the local community and the country without leaving the community after graduation. Through this, it is hoped that foreign workers(E-9) will be able to train foreign workers beyond the aspect of the workforce that simply provides labor, transfer Korean technology, and play a role in emerging as a global Korea.
IN-SCHOOL READING AND FREE CHOICES – WHAT THE EIGHTH-GRADERS PREFER AND WHY

Reading literacy is a key factor in education, life, and work in the modern age, which is recognized in the Montenegrin subject curricula for teaching the mother tongue and literature in primary (2017) and secondary schools (2020) and is noticeable in educational and knowledge outcomes aimed at the development of both different reading strategies and this demanding cognitive skill as a whole. Concerning the described topic, in this paper, we also cite the results of research into the reading interests of children and young people carried out in Montenegro and the region, and we also refer to international research from similar fields, given that the problem of (non)reading among young people is a global trend. The mentioned topic in the region was mostly researched at the high school age, but considering that the researched population (primary school eighth-graders) goes to high school as the next level of education, and a step forward in the development of literacy competence, of which reading is an inseparable part, the mentioned results we considered significant for our research. A comparison with similar research in the region and beyond has shown that, when it comes to the genre of literary works, and partly their titles, both inschool and out-of-school reading, the preferences of the respondents largely coincide with the choices of their peers from the region and beyond, which is why it is most likely contributed by a strong generational connection based on the possibilities provided by modern technology. The results of the research are proof that future dedicated readers, seekers of a good book, and sincere devotees can still be successfully formed during the teaching of literature in modern circumstances. Therefore, it is the task of adults, as creators and implementers of education, to dedicate themselves to the development of the reading of literary-artistic texts, in an organized and synergistic way, and to change themselves by accepting changes for the sake of those they educate.
Automated service delivery in hotels: balancing efficiency and human interaction for optimal guest satisfaction

The area of implementation of automated business in the tourism and hospitality sector attracts increasing attention due to the difference compared to the traditional way of providing service, which is characterized by warmth and interpersonal communication. With the increase in automation technologies in the hospitality industry, it is essential to examine how these systems affect the guest's satisfaction and the delicate balance between efficiency and human interaction. Automated service delivery in hotels offers numerous benefits, including streamlined operations, faster service, reduced waiting times, reduced staff workload along with others. Technologies such as self-check-in kiosks, automated concierge services, and robotic assistants have the potential to enhance efficiency and convenience for guests. However, finding the right balance between automation and human interaction is essential to ensure optimal guest satisfaction. This paper aims to explore the challenges and opportunities associated with automated service delivery in hotels. It examines the impact of reduced human interaction on guest satisfaction, considering factors such as personalisation, emotional connection, and perception of service quality. It also addresses the challenges that arise from implementing automated systems, including costs, guest adaptation, need for proper staff training, cultural differences, resistance of employees and guests to technology, etc. This paper emphasises the importance of leveraging automation to improve efficiency while preserving key aspects of personalised guest experiences and high-quality service. In the paper, preliminary results are presented that support all the previously mentioned points, with the note that they are subject to change because the survey is still active, and data is still being collected. Ultimately, finding the right balance between efficiency and human interaction is crucial forachieving optimal guest satisfaction in an automated hotel environment.
Analisis Bibliometrik Implementasi E-Learning Dalam Pendidikan Ekonomi

Ongoing learning must be able to increase effectiveness in order to achieve educational goals. Technology and information that are currently developing have spread in various fields of human life, including education. The inclusion of technology and information in education has an impact on changes in both aspects of the education system, the material provided, including how the learning process is carried out and the obstacles that may be accepted by educators and students. This study aims to determine the implementation of e-learning in economics education to improve students' competence. This study uses bibliometric analysis to map e-learning in various previous research journals in relation to economic education using Vosviewer. The results of this study conclude that e-learning is a must in improving the competence of students, especially women who run home-based and small-scale business activities.
Effect of Webtoon Major's Core Competencies on the Use of Generative AI

The purpose of this study was to clarify the influence of the students majoring in webtoon on the use of generative AI and the core competencies of their majors. To this end, a survey was conducted on 187 students in webtoon-related departments.&#x0D; As a result of the study, 105 students were aware of what generative AI was, accounting for 55.6%, and when asked about its use in the future, it showed a high percentage of negative views. When looking at the effect of major core competencies on the use of generative AI, communication was found to have no significant influence on the use of generative AI, and collaboration was found to have a significant influence on the use of generative AI. It can be seen that self-development and problem-solving have a significant influence on the use of generative AI, and flexibility has no significant influence on the use of generative AI.&#x0D; Based on the identified research results, this study suggested as an alternative to consider students who are prospective creators when opening majors using generative AI in webtoon-related departments.
Two-Dimensional Model Designing to Evaluate Employees' Performance Using Fuzzy Approach

Performance management is a critical topic in contemporary management studies due to its impact on employee performance. Performance evaluation is a process that assesses employees based on predetermined criteria and methods. This research examines the criteria for general and specific evaluations of employee performance, based on related research. The employees under consideration work in the software development section. The main active sections in software development companies, including IT, software engineering, finance, sales and marketing, and project control, were explored to identify primary criteria. These criteria were derived from related studies and job descriptions and are used to evaluate the special criteria of each section. The experts were given the primary criteria and subsequently interviewed. No changes in content were made, as per the instructions. The secondary general and specific criteria related to the four active sections were examined. The number of appropriate samples was calculated for each section, and questionnaires related to general and specific performance evaluation were created and distributed. The language used is clear, concise, and objective, adhering to formal register and avoiding biased or ornamental language. The text is grammatically correct and follows conventional structure, with a logical flow of information and causal connections between statements. Technical terms are explained when first used, and precise word choice is employed where necessary. The text adheres to formatting guidelines and citation style, with quotes clearly marked and filler words avoided. After collecting and analyzing the data from the questionnaires, the employees were evaluated using regular and fuzzy Topsis. The study compared two approaches and found that Fuzzy Topsis was the superior method. The employees underwent two evaluations: one based on general criteria for all employees and another based on specific criteria for employees in their own section. The study revealed that the best or worst employees in their own section were not necessarily the best or worst in the entire organization.
The Use of Dall-E Artificial Intelligence Platform for Enhancing Students’ Vocabulary Acquisition

The use of technology in the field of English Language Teaching (ELT) has been valued giving positive results proven by scholars. However, among myriad research on the use of technology, little has been discussing the influence of AI in expanding students’ vocabulary acquisition. In contrast, previous researchers were limited to examining the effect of web-based 2.0 on several micro and macro skills. In fact, the use of Artificial Intelligence (AI) web-based platforms seems promising because of its innovation. Therefore, this paper aims at examining the effectiveness of the DALL-E AI platform in increasing the students’ vocabulary acquisition. To reach the aim, experimental design was employed. This current research invited thirty-one senior high school students from one of Islamic based schools in Yogyakarta. Three treatments were conducted along with a pretest before the treatments and posttest after the treatments. A paired-sample t-test showed an increasing score mean from 56.35 in the pretest to 67.58 in the posttest. Apart from the mean results, the t-test revealed that there was a significant difference between the pretest and posttest mean, where the significance value was at .000. By finding this, the alternative hypothesis is accepted. In accordance with the result, it could be asserted that the DALL-E Platform could be employed by the teacher to expand the students’ vocabulary acquisition.
Comparison of Air Quality Prediction using Random Forest and Gradient Boosting Tree

Air quality has become one of the most pressing environmental issues of the 21st century. Rapid population growth, industrialization, and mobility have led to increased emissions of pollutants such as harmful particles, greenhouse gases, and toxic chemicals into the atmosphere. Air quality prediction plays an essential role in addressing global challenges related to air pollution. With accurate air quality predictions, governments, health agencies, and communities can take preventive and proactive measures to protect human health, the environment, and the economy. Projection can be done with methods that use the concept of Decision Tree. Random Forest and Gradient Boosting Tree are methods that use the image of a Decision Tree. The best GBT results were obtained with data combination parameters 60:40, number of trees 900, max depth 10, and learning rate 0.01 with RMSE 0.024 and SE 0.001. The best Random Forest results are obtained with data combination parameters 60:40, number of trees 800, and max depth 20 with RMSE results 0.071 and SE 0.005. This study found that the Gradient Boosting Tree can provide better results than the Random Forest because the Gradient Boosting Tree uses the concept of Boosting on the Decision Tree; thus, it can provide better prediction results.
Optimization of SVC Placement and Capacity in the Electric Power System Transmission Networks using Multi-Objective Improved Sine Cosine Algorithm

Current technological developments are in line with the increasing consumption of electrical energy. There is a value of power losses of the electricity transmission process caused by an increase in the value of power losses, to overcome this, SVC (Static VAR Compensator) of the Flexible AC Transmission System (FACTS) can be used. From previous studies, the optimization of SVC placement in the transmission network has not been carried out to get better power losses. This research uses the Improved-Sine Cosine Algorithm (ISCA) that has a different function of r1 compared to the ordinary SCA, in which the use of the ISCA method is able to overcome the weaknesses of the SCA method. The determination of location and capacity can use more than one objective function. From the result, the optimization of SVC placement and capacity is able to reduce the value of power losses by up to 85%.
An analysis on digital competencies of university students: A case study of A university

This study was conducted to diagnose the digital competencies of university students and derive implications for improving educational programs and providing educational support based on the results. To achieve this, a digital competency diagnostic tool designed by A university was conducted, with the participation of 1,097 students. The key findings of this study are as follows. Firstly, among the six sub-competencies of information collection, collaborative communication, content creation, tool utilization, ethical compliance, and problem-solving, tool utilization competency appeared to be somewhat lower. Secondly, an analysis of the difference in digital competencies based on academic year revealed that the competencies of first-year and fourth-year students were somewhat lower(p&lt;.05~p&lt;.001). Thirdly, an analysis of differences based on academic disciplines showed that students in the arts and humanities·social sciences disciplines exhibited slightly lower competencies compared to students in the natural sciences·engineering disciplines(p&lt;.05~p&lt;.001). Fourthly, the analysis for digital competencies perception indicated that students had the highest demand for tool utilization competency. They expressed a desire to cultivate various tool utilization competencies through major education. This study emphasizes the significance of digital competency diagnosis in understanding the competency levels and status of students. It also highlights the potential and utility of providing educational improvements and support through the digital competency diagnosis of the results.
Predictive Breast Cancer Statistical Modelling for Early Diagnosis

Breast cancer is a significant global health concern, stressing the urgent need for early detection. Early diagnosis improves access to varied treatments and significantly enhances patient outcomes. This study explores breast cancer detection over two days, aiming to create a precise and efficient machine learning model. The research uses a diverse dataset, combining clinical, genetic, and imaging data, including magnetic resonance imaging (MRI), X-ray, and electromagnetic data. Rigorous data preprocessing, including variable normalization and feature identification, enhances dataset quality. Predictive models use statistical techniques like logistic regression, decision trees, and random forest. Key metrics, such as accuracy, precision, recall, and area under the curve (AUC), assess model efficacy. Results reveal high accuracy and AUC scores, indicating potential for precise breast cancer detection. The study enhances our understanding of breast cancer dynamics, showcasing the effectiveness of machine learning for accurate and efficient early diagnosis. The research underscores diverse datasets and careful statistical modeling as crucial for predictive breast cancer capabilities.
On the general form of a linear continuous functional in the space of regulated functions

The author's research continues on the theory of regulated functions (functions having finite one-sided limits at each point) and $\sigma$-continuous functions (bounded functions having no more than a countable set of discontinuity points), as well as on the theory of the *-integral. The representability of a regulated function in the form of a sum of a right-continuous function and a left-continuous function is proved ($rl$-representability of the proper function). It is shown that the general form of a linear continuous functional in the space of regulated functions ($\sigma$-continuous functions) is the *-integral of a regulated ($\sigma$-continuous) function over a function of bounded variation.
EXPERIMENTAL CUT MARK REPLICATION AS A MEANS FOR UNDERSTANDING LINEAR MARKS ON ARCHAEOLOGICAL BONES FROM THE MEDZHIBOZH LOWER PALAEOLITHIC SITES

The paper presents the first results of experimental modelling of a series of cut marks on bones in different states of preservation. We used experimental (quartz, flint) and technogenic (granite) flakes with sharp and blunt unretouched working edges and trimmed edges produced by the bipolar on-anvil technique. V-, П-, and U-shaped cut marks and surface damage were obtained. The data gained are useful for the reconstruction of conditions of occurrence of cut marks on bones found in the uppermost culture-bearing horizons of the Lower Palaeolithic sites near Medzhibozh, located in the upper reaches of the Southern Bug River and dated to MIS 11. The data can also be used for differentiating between anthropogenic and natural damage and as a significant statistical point of reference.
The Aspect of the Transmission of Oral Narrative Unique to Each Region Analyzed through Text Mining: Focusing on Legends of Place Names and Historical Figures

This study identified and cataloged the legends of place names and historical figures from a compilation of oral narratives collected from nine regions nationwide, as documented in the 『Comprehensive Korean Oral Literature』 and the 『Complementary Edition of Comprehensive Korean Oral Literature』. For this, text mining techniques were employed, involving the analysis process of “data collection → preprocessing of regional information → preprocessing of proper nouns → analysis of regional folklore → data generation.” First, we collected data on 26,542 oral narrative titles and preprocessed the regional information, which was not organized by administrative divisions at the “provincial” level. Subsequently, we categorized the data into nine regions. Next, we conducted a task to identify proper nouns that were not recognized by the morphological analyzer and registered them as nouns. In this process, we used the “associated word network” analysis technique to identify proper nouns. Once the preprocessing task of verifying and modifying the proper nouns was completed, we extracted the frequency of the nouns in each region. Then, to select nouns that guarantee the uniqueness of the region, the frequency was “normalized” and the value was “scaled.” Additionally, the criterion for selecting the unique place names and people of each region was defined by the term “maximum regional share” and selected as 80%.&#x0D; As a result, 520 nouns were extracted, of which only proper nouns corresponding to place and personal names were filtered. Based on this, for legends of place names, place names were classified into “natural features,” “artificial features,” and “village names” for each region, according to the “nature of the evidence.” This list has been compiled. In the legends of historical figures, the corresponding personal names are presented for each region. Legends of place names are crucial as they reveal how residents of each region shape and give meaning to their lives in the “space where history intersects.” However, legends of historical figures deserve attention for their exploration of individuals in the region who have been marginalized or excluded from historical awareness accumulated over time and documented in written records.
Institutional Changes in the Meister High School Policy: Perspectives of Historical Institutionalism

This study analyzed the trajectory of policy change in Meister High School from a historical institutionalism perspective. Through this analysis, the causes for the continuity of Meister High School policy as part of the secondary vocational education system, regardless of changes in government, and the internal catalysts for change were examined from a historical perspective.&#x0D; The key findings of the study, summarized using the perspective of historical institutionalism and commonly used terms in this discourse, are as follows. First, the Meister High School policy emerged by highlighting the differentiation point of "Meister" while maintaining existing elements of the secondary vocational education system. Second, the Meister High School policy relied on the performance indicator of employment rates during the preparatory and implementation stages, forming path dependence. Various pre-existing policy elements combined institutionally to form a layering effect in the path formation. Third, the policy drifted due to unintended consequences such as negative public discourse on fair access for youth, negative perceptions of employment upon high school graduation, and issues related to early employment and working conditions, as well as the impact of the COVID-19 pandemic on industries and educational settings.&#x0D; In summary, the Meister High School policy is undergoing a gradual transformation, and has the uniqueness of attempting issue framing by the same minister in different periods of government. As an actor, the Minister of Education sought to dominate and frame the agenda of vocational education, but the influence varied depending on the timing and context in which the policy was situated. Based on the research findings, implications for the Meister High School policy are derived, and suggestions for the institutional aspects of the development of Meister High School are provided.