Reviewerly/exHarmony huggingface dataset:
Evaluasi Perbandingan Kinerja Algoritma Cheng and Church Biclustering Terhadap Algoritma Clustering Klasik K-Means untuk Mengidentifikasi Pola Distribusi Barang Ekspor Indonesia

Clustering is a process of grouping data into several groups (clusters) so that data in one cluster has a homogeneous level of similarity and data between clusters has heterogeneous similarity. A common example of a clustering algorithm is K-Means Clustering. Compared with classical clustering algorithms, the biclustering algorithm is a two-dimensional data grouping process. The biclustering algorithm functions to find data submatrices, namely row subgroups and column subgroups that have high correlation. One example of a biclustering algorithm is Cheng and Church Biclustering (CC Biclustering). The aim of this research is to evaluate the performance of the biclustering algorithm against classical clustering algorithms. Analysis applied to CC Biclustering and K-Means Clustering to identify distribution patterns of Indonesian export goods in the period 2013 to 2022. Based on research results, the optimal scenario for the K-Means algorithm is scenario 2, that is the application of the 7 cluster K-Means algorithm with pre- processing data scaling. Meanwhile, the optimal scenario for the CC Biclustering algorithm is scenario 1, that is the application of the CC Biclustering algorithm with a tolerance value of 0.10 with data scaling pre-processing. However, from these two scenarios, based on the MSR/Volume value, it was concluded that the best scenario is scenario 1 in the application of the CC Biclustering algorithm which has an MSR/Volume value of 0.077.
Analisis Faktor Konfirmatori untuk Mengidentifikasi Peubah Indikator Utama dalam Pengukuran Peubah Laten

Research on attitudes, preferences and behavior are research that involves latent variables. Latent variables are measured by observing some indicator variables. Indicator variables that measure a latent variable are selected based on the researcher's perspective, however, it is necessary to consider the previous of related research. Indicator variables need to have theoretical meaning, be valid and reliable in measuring latent variables. Confirmatory factor analysis (CFA) is a statistical method that can be used to determine the validity of the indicator variables. In this research, CFA is used to determine the main indicator variables that characterize the reasons for choosing a study program at a university by high school graduates (or equivalent). There are 20 indicator variables chosen to represent several latent factors such as image, job prospects, interests and campus facilities. The results indicate that the latent factors of image, job prospects, interest and facilities can be respectively represented by the majority of alumni occupying strategic positions in their careers, the easiness of alumni for getting a job, a large number of individuals in surroundings who are working as a data analysts and representative library. The findings also reveals that all the selected indicators are significant so that no indicators need to be excluded. Evaluation of the model shows that the specified model fits the analyzed data. This is indicated by the Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR) values ​​which reach good fit criteria.
A Proposal for Lightweight Human Action Recognition Model with Video Frame Selection for Residential Area

Residential area closed-circuit televisions (CCTVs) need human action recognition (HAR) to predict any accidents and crucial problems. HAR model must be not only accurate but also light and fast to apply in the real world. Therefore, in this paper, a cross-modal PoseC3D model with a frame selection method is proposed. The proposed cross-modal PoseC3D model integrates multi-modality inputs (i.e., RGB image and human skeleton data) and trains them in a single model. Thus, the proposed model is lighter and faster than previous works such as two-pathway PoseC3D. Moreover, we apply the frame selection method to use only the meaningful frames based on differences between frames instead of using the whole frame of a video. AI Hub open dataset was used to verify the performance of proposed method. The experimental results showed that the proposed method achieves similar or better performance and is much lighter and faster than those in the previous works.
An Analysis of the Needs of Learners on the Online Buddhist Education: Focusing on Focus Group Interview

The purpose of this study is to examine learners’ needs related to online Buddhist education. For this purpose, focus group interviews were conducted and analyzed with seven learners who participated in online Buddhist education. Learners’ needs related to online Buddhist education were centered around ‘motivation to use online Buddhist education,’ ‘experience of participating in online Buddhist education,’ and ‘support needed to increase the field usability of online Buddhist education.’ From the ‘motivation for using online Buddhist education’, ‘desire to study Buddhism’, ‘acquiring psychological stability’, ‘communication with believers’, ‘desire to live a spiritual life’, and ‘strengthening accessibility to Buddhist content through non-face-to-face’ were derived. From the ‘experience of participating in online Buddhist education’, ‘various teaching methods through online’, ‘use of various class contents’, ‘progress-oriented classes’, ‘specific classes’, and ‘communication in non-face-to-face classes’ were derived. From ‘Support needed to increase field usability of online Buddhist education’ to ‘Need to improve system for non-face-to-face classes’, ‘Development of highly attractive non-face-to-face content’, ‘Development of communicative small group activity classes’, ‘Instructors and learners’ ‘Strengthening communication among students’, ‘Need to systematize non-face-to-face Buddhist curriculum’, ‘Need to evaluate online classes’, and ‘Need to consider non-face-to-face counseling’ were identified. This study is significant in that it contributed to deriving directions for the composition, content, and methods of online Buddhist education and diversifying Buddhism-related research methods by conducting a needs analysis of learners.
Enhancing Early Childhood Literacy through Reading Corners: A Phenomenological Study at Thiflah Early Childhood Education, Aceh Besar

This study explores the effectiveness of reading corners in enhancing literacy among early childhood learners at Thiflah Early Childhood Education (ECE) in Aceh Besar, Indonesia. Employing a phenomenological research design with qualitative methods, this study aims to understand the subjective experiences of educators and learners about literacy enhancement strategies. The research incorporated observations, interviews, and documentation, with a focus on the role of the reading corner in fostering literacy. Results indicated significant improvements in children’s engagement and comprehension in reading, writing, and arithmetic, attributed to the interactive and play-oriented learning environment. However, challenges such as insufficient resources and reliance on student teachers with limited experience were identified. The findings suggest that the reading corner approach, aligning with Indonesia's National Literacy Movement, can be a viable model for enhancing early literacy in various educational settings. The study recommends further research into the effectiveness of reading corners in diverse ECE contexts and emphasizes the need for resource enhancement and teaching methodology improvements. These insights are crucial for developing engaging, child-centric learning environments for early literacy development and overall child growth, contributing significantly to Indonesia's National Literacy Movement.
A Critical Review on the Discourses on ‘Donation for Education’

‘Donation for Education’, which has been expanding over the past decade, has a problem in that it is difficult to identify in detail due to the use of the unclear term ‘education’. This study critically reviewed discussions on ‘Donation for Education’ to understand what efforts were made to solve this problem. As a result of the research, behind the discussion, there were problems with wrong views of education, such as confusion between schools and education, borrowing concepts from other disciplines, and result-oriented views of education. With these reasons, ‘education’ referred to different things at each time and was difficult to discuss. By leaving the context, it was becoming an obstacle to the progress of the ‘Donation for Education’ discussion. In addition, due to the drifting term ‘education’, not only the omnipresent education inside and outside of schools, but also various facts within schools have been concealed and distorted. The term ‘education’ in ‘Donation for Education’ should be deleted and replaced with a term that reveals what actually happens. As a result, discussions on donations to support various aspects of schools become clearer, and education can be separated into a separate object of recognition.
Development of Performance Indicators to Foster Professional Manpower Project in Promising New Technology Fields at Vocational High Schools

This study was conducted to develop performance indicators to foster professional manpower in promising new technology fields at vocational high schools and provide a foundation for continuous operation and development of the project. To this end, a draft was developed through prior literature and FGI for developing performance indicators targeting teachers, training institution personnel, and experts participating in the project. The validity of the developed draft was secured through two Delphi surveys targeting relevant experts. The developed performance indicators consisted of 14 detailed areas in three areas: input, process, and output, and included 41 performance indicators. The input area consisted of three areas: budget, organization and personnel, and training time, and included five performance indicators. The course area consists of 8 areas: business plan and goals, recruitment and management of participating students, education (training) operation, improvement of faculty expertise, cooperation and exchange, improvement of student major ability, career and employment counseling, and evaluation/feedback area. 28 Performance indicators were included. The calculation area consisted of three areas: student growth, school competitiveness, and business satisfaction, and included eight performance indicators.
Perceptions of Parents, Teachers, and related Educational Experts on the Status and Needs of Educational Support for Learners with Borderline Intellectual Functioning: Focusing on Gyeonggi-do

This study investigated the perceptions of parents, teachers, and related education experts regarding the status and needs of educational support for learners with borderline intellectual functioning in Gyeonggi-do. A total of 545 people participated in the online survey, including 148 parents, 243 teachers, and 154 related educational experts. The research participants said that they are currently experiencing difficulties in adapting to school life due to the fact that there is a blind spot in the education law and related system for learners with borderline intellectual functioning, and that there is no individualized educational support system according to the life cycle. The research participants requested the development of a school life support plan that reflects curriculum and career progression guidance, and social skills guidance that takes into account the characteristics of learners with borderline intellectual functioning. Based on the research results, a screening and diagnosis system was established based on the characteristics and support needs of learners with borderline intellectual functioning, a cooperation plan to strengthen school education accountability, and support for lifelong education in adulthood were proposed.
Development and Application of a Recurrent Learning-Based Early Childhood Media Literacy Education Program

As the age of starting to use media decreases, early childhood media literacy ed-ucation is becoming an important task. This study aims to develop a circular learn-ing-based early childhood media literacy education program and to explore its influence. By analyzing literature and previous studies on media literacy, a survey of teachers' per-ceptions was conducted. A total of 6 sessions of an early childhood media literacy educa-tion program for 20 children aged 5-year-old were developed and conducted, and quanti-tative changes were measured through repeated measurement analysis before and after the program was implemented. In order to measure the observed process change, a qual-itative analysis was conducted using data such as an observation diary and an activity sheet. As a result of the analysis, it was found that the six components of media literacy were improved. Through the observed changes, children have improved their ability to use the media to express their thoughts and to communicate with others. These results will help children develop the ability to use them safely and effectively in the media environment. Furthermore, a wide range of contents and methods will be needed to in-crease children's media literacy capabilities, and continuous program development and evaluation will be essential.
A Qualitative Research on Technology Teachers’ Experience with High School Credit System

The study aims to provide implications, based on the experience of technology teachers, regarding the direction for technology instruction in high schools in view of the high school credit system. To this end, in-depth interviews were conducted with seven technology teachers, experienced in the research and preparation of the high school credit system, and field data were collected. Additionally, some of their classes were observed. The collected data were analyzed and categorized through the process of emic coding and structural coding. According to the analysis, the participants faced limitations because of a high school culture that is oriented towards college entrance, since technology is not covered in South Korea’s national college entrance exam. The teachers experienced “difficulty in securing class time,” “burden of teaching multiple subjects,” “difficulty in teaching unfamiliar subjects,” and “difficulty in conducting classes” due to the introduction of the high school credit system. The analysis reveals that this system caused the following changes in the attitude towards the technology class: ‘avoidance,’ ‘survival,’ and ‘opportunity.’ Based on these findings, the pedagogical implications of technology teachers’ experiences, due to the introduction of the high school credit system, may be interpreted as ‘establishing firm values for the subject matter' and ‘thinking from the students’ perspective.’ The following steps are proposed based on the analysis outcomes: an experiential study for students who undertook technology instruction under the high school credit system, development of a program to enhance the expertise of technology teachers at high schools, and action research on “delivering good technology instruction” in high schools. This study is meaningful as it interprets and analyzes not only the changes in the technology instruction due to the introduction of the high school credit system, but also their significance, thereby deriving the aforementioned implications. The findings of the study may serve as useful data for offering implications regarding the direction for technology as a subject in high schools.
Analysis of previous questions related to subject pedagogy of the emplyment exam for secondary school teachers in the ‘Technology’ subject: Focusing on the school year 2014 to 2024

The purpose of this study is to analyze previous questions related to the employment exam for technology teachers in secondary schools. To achieve this, we collected and analyzed subject pedagogy-related questions from employment exams conducted from the 2014 to 2024 school years, after the multiple-choice test was abolished. The results of the study are as follows: First, in analyzing the number of questions, there were 4 to 5 questions related to subject pedagogy before the essay-type test was abolished and 6 to 7 questions after its abolition. In terms of item distribution, 26.93% of the total distribution of subject pedagogy-related questions occurred before the essay-type test was abolished, and 27.50% occurred after its abolition. Second, in analyzing the composition of the evaluation area and contet elements, the area with the highest frequency of questions was the ‘technology curriculum.’ and the content elements with the highest frequency of questions were the ‘current technology curriculum’ (15.60%) and ‘technology subject teaching and learning methodology’ (15.06%). Since 2014, two evaluation areas and ten evaluation content elements have had zero frequency of questions. Third, in analyzing the topics of teaching and learning activities appearing in questions related to subject pedagogy, the most frequently included subject content studies were the elements of evaluation for solving common invention problems with engineering technology. Since 2014, only once each of life technology and information and communication technology has been included. Based on these findings, improvement measures were proposed, such as reorganizing the number and allocation of questions, balancing questions across evaluation areas and content elements, and reorganizing evaluation areas and content elements based on field technical education.
Analysis of Secondary School In-service Teachers’ Stages of Concern regarding the 2022 Revised Technology Curriculum

The purpose of this study was to analyze secondary school in-service teachers’ stages of concern (SoC) regarding the 2022 revised technology curriculum and seek implications for enhancing technology teachers’ expertise. To achieve the purpose of the study, an online survey was conducted using the CBAM Questionnaire (SoCQ) targeting technology teachers belonging to the technology teacher online learning community, and a total of 224 questionnaires were used for analysis. The results of this study are as follows. First, as a result of analyzing the profile of technology teachers’ SoC in the 2022 revised technology curriculum, it was found to be similar to the profile of a renewing user in the form of tailing up, with interest at a high level gradually increasing. Second, as a result of analyzing the SoC by gender, male teachers showed a statistically significantly higher level than female teachers at the level 6 (alternative concern). Third, the difference of concerns by teaching experience was not found to be statistically significant. Fourth, teachers with a bachelor’s degree were found to have a statistically significantly higher concern than teachers with a master’s degree or higher at the level 3 (operational concern). Based on these results, the need for support measures to increase technology teachers’ concern in the 2022 revised technology curriculum was presented as an implication.
Hierarchical Latent Representation-based Framework for Automatic Detection of Cybercrime Slang

Cybercriminals constantly produce and use slang by adding criminal meanings to existing words or replacing them with similar words for communication. Continuous monitoring and manual work are required to respond to this, and a large amount of labeled training data is required when using deep learning. However, the ability to collect a large amount of training data is limited because direct labeling by a person requires a lot of time and money and proceeds secretly due to the nature of cybercrime. Thus, we develop a framework based on an autoencoder and propose a method to effectively detect contextual cybercrime slang and neologisms through hierarchical latent vector similarity comparisons to address these limitations. Experiments using a cybercrime post dataset showed that the framework had an accuracy of up to 99.1% at a similarity threshold of 0.5.
Gender Classification Model Based on Colloquial Text in Korean for Author Profiling of Messenger Data

With explosive social network services (SNS) growth, there has been an extensive generation of text data through messenger services. In addition, various applications such as Sentiment Analysis, Abusive text Detection, and Chatbot have been developed and provided due to the recent development of Natural Language Processing. However, there has not been an attempt to classify various characteristics of authors such as the gender and age of speakers in Korean colloquial texts. In this study, I propose a gender classification model for author profiling using Korean colloquial texts. Based on Kakao Talk data for the gender classification of the speaker, the Domain Adaptation is carried out by additionally learning ‘Nate Pan’ data to KcBERT(Korean Comments BERT) which is learned by Korean comments. Results of experimenting with a model that combines External Lexical Information showed that the performance was improved by achieving an accuracy of approximately 95%. In this study, the self-collected ‘Nate Pan’ data and the
Computationally Efficient Decoders for Semantic Segmentation Models

The recently proposed semantic segmentation models are characterized by high computational complexity, which can lead to usability challenges on edge devices or result in high cloud costs. Various methods have been proposed to address these problems using efficient encoders. However, unlike in the past, the models proposed recently perform complex operations that involve combining feature maps generated from multiple stages on the encoder side, which in turn significantly increases the computational complexity of the decoder. Despite this, the issue of computational efficiency for the decoder is still relatively under-addressed. In this study, we propose efficient decoders that combine feature maps through simple weighted summation. Through experiments, we demonstrate that the proposed decoders employing weighted summation techniques, when applied to different combinations of datasets and models, minimize performance degradation while greatly improving computational efficiency.
Traducció dels sobrenoms de la màfia napolitana a l'anglès i al castellà de la sèrie de televisió 'Gomorra'

This study deals with the translation for subtitling and dubbing of a type of Italian expression called contronomi traditionally used by members of the Neapolitan mafia. We have focused on this special kind of nickname used in the Italian series Gomorra to identify and describe the techniques employed in the translation of these meaningful linguistic cultural elements found in the series into English and Spanish. A contrastive analysis of the source text in the Neapolitan dialect and the subtitled version in English and the dubbed version in Spanish of the first season has been carried out. Through this analysis, conclusions could be drawn about the translation tendency regarding the handling of a cultural aspect of the Neapolitan series: the contronomi of the main and secondary characters of this audiovisual product in the two target languages and cultures.