Reviewerly/exHarmony huggingface dataset:
A Exploratory Study on the Postures of Social Policy Decision-Maker: In Connection with Interpretation of Four Hexagrams of Hardship in 「the Book of Change」 from the Standpoint of the Social Policy

The purpose of this study is to indentify the postures of the social policy decision-makerwhich require in solving the most difficult social problems such as four hexagrams of hardshipin the Books of Change. For the purpose, this study has used the study framework with theaspects such as the situation of social policy, the behavior of social policy decision-maker andthe prospect of social policy which was explored through revising and supplementing theexisting study framework. The posttures of the desirable social policy decision-maker indentifiedin this study are such as followings. First, the social policy decision-maker must sufficientlyunderstand the situation of social policy. Second, the social policy decision-maker mustpositively use allied experts in order to solve the situation of social policy. Third, the socialpolicy decision-maker must make sure that the inplementing social policy will be succeeded. The Book of Change contains the useful contents about the desirable statures of social policydecision-maker related with solving the situation of social policy. Therefore the Book of Changemust be the human heritage to be newly highlighted and actively utilized in the fields of socialwelfare or social policy.
Implementing an AI-based scenario-type voice chatbot server

This study aims to innovatively improve services in public places such as museums and art galleries by implementing a scenario-type voice chatbot server based on artificial intelligence. The system integrates three key deep learning models: speech recognition, sentence intention classification, and speech synthesis, recognizing the user
Impact of contamination on training data in the output of a large language model

As deep learning technology has been applied to the field of natural language processing and generation, the field of artificial intelligence natural language generation has advanced significantly. In addition, as the natural language processing capabilities of GPT-based language models have recently improved, the demand to utilize them is increasing. However, models with good performance have limitations in that they require a lot of resources to be implemented by individuals or organizations. Accordingly, a transfer learning process such as fine tuning is used using a pre-trained language model to suit the intended use, but there is concern about the possibility of fine-tuning the pre-trained language model using data contaminated by manipulation. Therefore, in this paper, we fine-tuned the language model with training data generated according to the degree of contamination and analyzed how much it affected the output.
Factors of Preferences for Virtual and Physical Japanese Exchange Programs

In Malaysia, Japanese exchange programs have been in place for decades. Both countries have enjoyed continuous knowledge and cultural exchange throughout the years. Unfortunately, the COVID-19 pandemic outbreak has temporarily halted the exchange activities. In this period, virtual exchange has started to gain the attention of academia. Despite current situation continues to improve and travel restriction has been largely lifted, virtual exchange continues to co-exist with physical exchange program. Hence, it is vital to understand the level of interest towards both physical and virtual exchange programs among the Malaysian academia so future exchange program can be further refined in the post COVID-19 era. Analysis was conducted by using the Partial Least Squares. The findings demonstrated that participants who express a strong preference for Physical Exchange Programmes (PPE) are more likely to have a heightened Interest in Exchange Programmes (IEP). Factors such as safety measures, flexible program options, and technological advancements have played a crucial role in keeping exchange programs relevant and attractive in the post-Covid-19 world.
The Implementation of Interactive PowerPoint Media in Thematic Learning at an Elementary School

The rapid development of technology is inseparable from human life, significantly impacting educational systems. Technological advancements, particularly in information technology, indirectly alter conventional teaching strategies. Current educational strategies emphasize student-centered approaches, wherein students play a more active role than teachers, while still recognizing the teacher's role as a source of learning. The implementation of Curriculum 2013 provides a reference in the education sector. Creating an enjoyable learning process involves considering various factors, such as student engagement and the use of effective teaching strategies and methods. This qualitative descriptive research explores the application of the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) design model in the context of interactive PowerPoint media for thematic learning in Grade V at Madrasah Ibtidaiyah Bustanul Ulum 02 Tegalwangi Umbulsari Jember. Data collection methods include observation, interviews, and documentation. The analysis involves data reduction techniques. The research findings reveal that a teacher at Madrasah Ibtidaiyah 02 Tegalwangi Umbulsari Jember utilizes interactive PowerPoint media in thematic learning, resulting in improved student understanding. The use of interactive PowerPoint has positively impacted student achievement, as evidenced by increased end-of-year assessment scores. The observation also highlights the significant role of instructional media in the learning process, stimulating student interest and creating a more relaxed and engaging learning atmosphere.
Armamentarium Phantasmagoria

Purpose – This author will argue for the establishment of a formalised area of study and science centered around the objective, observable phenomena of ideas and ideation and the creation of a formalised Armamentarium (guide, toolkit and practicum) to serve as the foundation for such a science and practice. Methodology – What would someone who practices and studies ideas and ideation need to conduct work around such concepts? This question is the core of creating a science of ideas. Previous attempts at creating such a science will be discussed. Observations shall be made pertaining to common themes and patterns that can be observed about ideas. The Idom Hypothesis will be introduced, alongside avenues of experimentation. Current technologies and techniques will be considered on the merits of relatedness and usefulness in researching, understanding and working with ideas and ideation as both a micro and macro phenomenon. By extension, significant consideration will be given to how ideas relate to physics and how one might study them non-anthropocentrically. Connections will be made across disciplines, as ideas permeate them all. By making such connections one can state the goals needed to connect the world’s scholarly pursuits into one large interdisciplinary science, with ‘the study of ideas’ as the binding agent. This author contends that with a formalised debate and framework Ideonomy would not only be practically possible, but inevitable. Value – Ideas are an integral part of all intelligent pursuits. Being able to understand their properties, limits and dynamics furthers the greater need for creative solutions in our sciences, technologies, and social systems which garner more complex problems. All professions require more flexible and creative thinking in the context of their work. The advent of technologies like artificial intelligence, augmented reality, virtual reality, and mixed reality finds these tools in need of application. Their very nature is based around creative potential. Ideonomy and a common ideonomic literacy would inform the average individual and the professional practitioner on how to create new ideas and track old ones. For sciences that often have difficulty translating their concepts to one another, it would be used as a medium for avoiding linguistic traps. Ideonomy would inform on how rigidity of language leads to assumptions of fact. It would create the tools for representing ideas better and for understanding why some worked and others did not. It would inform how time affects ideas. An armamentarium for Ideonomy would give us the knowledge needed for the world, work, and problems of the near future. It would help prepare us for the professions that have yet to be invented.
M<sup>3</sup>CI-Net: Multi-Modal MRI-Based Characteristics Inspired Network for IDH Genotyping

Isocitrate dehydrogenase (IDH) is a key molecular feature for gliomas, and the prediction of IDH is also an important task for computer-aided diagnosis using magnetic resonance imaging (MRI). To address this changllenge, we introduce a multi-modal MRI-based characteristics inspired network for IDH Genotyping (M <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> CI-Net), which pay more attention to the different characteristics information of different MRI modalities T1, T2, T1ce, Flair. In M <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> CI-Net, a pre-fusion module with multi-channel attention mechanism is used to fuse T1ce and Flair modalities and capture as much as possible luminance and contrast information, and the edge information is obtained from T2 modality by using edge detection module. Finally, the feature information between modalities are fused and input into a CNN-Transformer based encoder structure to extract shared spatial and global information from multi-modal MRI, and the information of multiple scales frome encoder are input into the linear layer for IDH genotype classification after pooling, meanwhile, the CNN based decoder with skip-connection for glioma segmentation works for assisting IDH genotyping. Then, we proposed images’ pre-fusion loss, segmentation loss, IDH genotyping loss, and use uncertainty weight training method to balance the weights of these loss. we evaluate our proposed method on Brats2020, and achieve an acceracy of 0.88, an AUC of 0.94, a specificity of 0.92, a sensitivity of 0.84 in IDH genotyping, which is superior to the state-of-the-art methods.
Machine Learning-Based E-Archive for Archives Management of South Sumatra Province

Archives play a crucial role in institutional operations, yet efficiently retrieving specific information from them can be challenging. This research addresses this issue by developing an information retrieval system that incorporates advanced methods to enhance search efficiency. The system employs the TF-IDF (Term Frequency-Inverse Document Frequency) formula, which assesses the significance of a word within a document set, and the BM25 method, a sophisticated algorithm for ranking documents based on their relevance to the input query. Both methods undergo a preprocessing stage, enabling the system to calculate the relevance of each document to the given query accurately. The effectiveness of this system is evaluated using key performance metrics: precision (accuracy), recall (completeness), and the F1 Score (the harmonic means of precision and recall, representing the best value). Testing with various keywords revealed that the BM25 method yielded impressive results, achieving an average precision of 0.75, recall of 0.6, and an F1 Score of 0.6665. In contrast, the TF-IDF method scored lower, with a precision of 0.33, recall of 0.2, and an F1 Score of 0.2500. The system was tested using a dataset of 350 documents.
Product Stock Supply Analysis System with FP Growth Algorithm

This study explores the application of Data Mining in deciphering consumer purchasing patterns at Tani Heritage Shop, a retailer specializing in agricultural products. Facing the challenge of managing a high volume of daily sales transactions, the shop often encounters difficulties in tracking which products are frequently purchased together. This lack of insight leads to a critical issue: popular products running out of stock unexpectedly. To address this, the research focuses on developing a product stock supply analysis system, utilizing the FP Growth Algorithm. The FP Growth Algorithm, a powerful tool in Data Mining, is employed to analyze sales transaction data and identify consumer purchasing trends, particularly products bought simultaneously. This approach is designed to provide insights into optimal stocking strategies, ensuring the availability of in-demand products. The research methodology involves applying the FP Growth Algorithm to model the product stock supply system, using specific sales data attributes. The results of this study are significant. By setting parameters such as a minimum support value of 30%, a confidence value of 70%, and targeting the highest lift ratio value of 3.67, the research successfully derives several key association rules from the FP Growth algorithm. These rules are instrumental in optimizing the product stock supply analysis system.
Web and Mobile Data Management System for Garongan Asri Garbage Bank: A Case Study

This research addresses the inefficiencies of manual garbage data management by developing a dual-platform system: a website-based application for Garongan Asri Garbage Bank staff and a mobile application for customers. Utilizing the waterfall method for systematic development, the project involved stages of analysis, design, coding, testing, support, and maintenance. Key technologies used include the Bootstrap framework, Visual Studio Code, Android Studio, and MySQL database. The resulting website application enables staff to efficiently manage garbage data, while the mobile app allows customers to access their disposal history. The effectiveness of these applications was confirmed through black box testing, demonstrating their functionality and suitability for improving garbage data management and customer service.
Recurrent Neural Network-Gated Recurrent Unit for Indonesia-Sentani Papua Machine Translation

The Papuan Sentani language is spoken in the city of Jayapura, Papua. The law states the need to preserve regional languages. One of them is by building an Indonesian-Sentani Papua translation machine. The problem is how to build a translation machine and what model to choose in doing so. The model chosen is Recurrent Neural Network – Gated Recurrent Units (RNN-GRU) which has been widely used to build regional languages in Indonesia. The method used is an experiment starting from creating a parallel corpus, followed by corpus training using the RNN-GRU model, and the final step is conducting an evaluation using Bilingual Evaluation Understudy (BLEU) to find out the score. The parallel corpus used contains 281 sentences, each sentence has an average length of 8 words. The training time required is 3 hours without using a GPU. The result of this research was that a fairly good BLEU score was obtained, namely 35.3, which means that the RNN-GRU model and parallel corpus produced sufficient translation quality and could still be improved.
Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers

Nutritional status is a crucial foundation for human health and development. Global facts indicate serious challenges in ensuring adequate nutrition, and the situation is no different in Indonesia. This research collected data from the Kelapa Dua Tangerang community health center and utilized data mining techniques with the k-means clustering algorithm to delve deeper into the nutritional status of toddlers. The research findings revealed that nearly 37.3% of toddlers experience issues with abnormal height or weight, as well as poor nutritional conditions, highlighting the importance of careful and timely intervention. With regular health monitoring by community health centers and active parental involvement, actions can be taken to support the optimal growth and development of these children. The results of this research provide a strong understanding to address malnutrition issues, which will ultimately support the formation of a healthier and more promising future generation in Indonesia.
Student’s Mastery Of Grammar In Simple Present Tense

This journal aims to analyze students' level of grammar mastery in using Simple Present Tense at school. Research was carried out through data collection. The results of the analysis show that the majority of students still experience difficulties in mastering the use of Simple Present Tense. There are common mistakes such as using inappropriate auxiliary words, adding -s/es to the wrong verb, and using inappropriate adverbs of time. However, there are some students who show good mastery in using this tense. In conclusion, this research shows the importance of supporting students' grammar mastery in the Simple Present Tense. Educators need to provide appropriate exercises, such as using example sentences and direct interaction in class, to help students overcome their difficulties and improve their mastery of these tenses. Apart from analyzing the difficulties students face in mastering the Simple Present Tense, this research also explores factors that might influence their mastery. Factors such as language background, training intensity, and grammar teaching methods were also considered in this study. The research results show that students' language background can influence the level of mastery of Simple Present Tense grammar. Students who have a language background that is more similar to English tend to have better abilities in understanding and applying these tenses.
Pelatihan Bingo Review untuk Joyful English Di Fajar English Course Pare, Kediri

Fajar English Course as one of the course institutions in the English village of Pare has had difficulties in improving the teaching abilities of its tutors. This is because the tutor recruitment system focuses more on alumni of the course institution and those who will still be living in Pare for a long time. So Fajar English Course collaborates with the Community Service team from the English Education Department at Hasyim Asy'ari University to conduct training on teaching strategies using Bingo Review and making teaching materials using the Bingo Review method. After two days of training, the Fajar English Course tutors were able to practice teaching with Bingo Review in speaking, grammar and vocabulary well in microteaching. Apart from that, they are also able to make good teaching materials for speaking, grammar and vocabulary using the Bingo review method. Teaching method training is really needed by Fajar English Course tutors to improve the quality of their teaching. To create a pleasant learning atmosphere, it is highly recommended that English teachers or tutors implement Bingo Review in their respective classes
Towards a User-Friendly Web Application Firewall

Web Application Firewall (WAF) systems play a vital role in protecting web applications from various security vulnerabilities. However, existing WAF solutions are often costly and complex to configure, limiting their accessibility to smaller organizations. This paper aims to develop an affordable and user-friendly WAF framework that mitigates the most common security vulnerabilities identified in the Open Web Application Security Project (OWASP) Top 10. The proposed WAF framework provides protection against attacks such as Cross-Site Scripting (XSS), Structured Query Language Injection (SQLi), Operating System (OS) Command Injection, File Upload, Denial of Service (DoS), Cross Site Request Forgery (CSRF), Path Traversal, and XML External Entity (XXE) attacks. The framework offers an easy-to-use interface with features for easy configuration of mitigation settings. Users can monitor web traffic and receive real-time alerts to quickly identify and respond to potential security threats. Proxy techniques are used to intercept and handle user requests, sanitizing them using the mitigation techniques to prevent the inclusion of malicious code or unauthorized data. Additionally, two machine learning models were implemented. The first model detects malicious requests, and the second model classifies attacks based on their type. Mitigation techniques are employed to filter requests and prevent specific attack types. Regular expressions (Regex) are used to remove malicious code related to XSS, SQL injection, OS Command Injection, File Upload, CSRF, XXE, and Path Traversal attacks. Rate limiting is implemented to mitigate DoS attacks.
Video Stream and Controllable Illuminance for Portable Colposcope

Portable colposcope is used for diagnosing cervical cancer in Visual Acetic Acid test. It’s used for real-time observation by medical personnel or saved to be predicted by artificial intelligence algorithm. The high cost for the device and the high prevalence of specular reflection found in the generated image inspired us to propose a method for low-cost portable colposcope and specular reflection reduction with real time video streaming and controllable light projection using integrated mobile application. The video streaming using local flask server resulting in 21 FPS of average frame rate and 502 ms latency. The mobile application was capable to interact with the portable colposcope to control the light projection with 0.8 average time latency. The illuminance control was also effective in reducing specular reflection with 0.8 average time latency.
Sistem Absensi Cerdas Menggunakan Open CV Berbasis Pengenalan Wajah

Abstract&#x0D; &#x0D; The face is an important part of the human body uniquely identify a person. Using facial characteristics as biometrics, facial recognition systems can be implemented. That the most demanding task in any organization is marking attendance. In the traditional attendance system, students are summoned byteachers and their presence or absence marked accordingly. However, this traditional technique is time consuming and boring. In this project, Open CV is based on face recognition approach has been proposed. This model integrates a camera captures the input image, an algorithm for detecting the face of a input images, encoding and identifying faces, tagging presence in a spreadsheet and convert it to a PDF file. That the training database is created by training the system with faces from authorized students. The cropped image is then saved as a database with their respective labels. The features are extracted using the LBPH algorithm.&#x0D; &#x0D; Keywords: LBPH, , Attendance, Biometric, Face Recognition
The Effect of Metaverse Technologies on Education and Human-Computer Interaction: A Systematic Analysis of the Literature

Digital transformation encompasses all the principles of people, working methods, and technology that support organizations in achieving their goals with the possibilities provided by the constantly developing information technologies that are in almost every aspect of our lives. Today, the impact of digital transformation is visible in every field with constantly developing technologies, and there is a rapid transition to digital innovations in almost all sectors. Web 3.0 and Metaverse, which are two innovations that support each other, are technological developments that can be used in many areas and it is curious what role they will play in daily life. This study aims to present research on how the education and human-computer interaction fields can be synchronized with Metaverse technology with the impact of the digital age. In this study, the articles accessed by using the systematic analysis method were examined under the headings of subject, journal, year, research method, study group &amp; sample, data analysis method, data collection method, field, country, conclusion, and suggestions for future studies. As a result of the research, 61 articles were found in the Web of Science database. Thus, it is aimed to obtain and discuss the results of how Metaverse technologies are reflected in the fields of education and human-computer interaction, in which direction they evolve, and how they will be reflected in future studies.