Reviewerly/exHarmony huggingface dataset:
Meningkatkan Kualitas Literasi Masyarakat Kelurahan Air Tawar Barat dengan Penerapan E-Library

This paper aims to facilitate and improve public literacy, especially school age and equivalent. It is necessary to carry out evaluation actions in the school environment for literacy, especially reading interest. This is proven from the results of UNESCO's research (2016) on Indonesia which shows that only 1 person has an interest in reading as well as a report from PISA (Program Of International Student Assessment) 2018 Indonesia is ranked in the bottom 6 of 78 countries in terms of reading. The younger generation, especially students, must be instilled or instilled a critical literacy attitude to obtain truth information, knowledge, enlightenment and avoid false information (HOAX) and theories that have no knowledge base. Libraries have a vital role in terms of providing information and reference sources of knowledge. Therefore, the authors want to implement E-Library in the library as an effort to facilitate the public in obtaining information and increasing students' reading interest by using artificial intelligence that helps students understand the material or information provided efficiently and easily. The application of e-library has changed the perspective of Generation Alpha and Generation Z of libraries and the selection of libraries as sources of information and references. The results of this study change the point of view of users from generation Alpha and generation Z to the library as a printed or digital reference source in meeting information needs.
Implementasi Model Golden Rules Of User Interface Design Oleh Theo Mandel Pada Aplikasi Diary Sumsel

This study aims to evaluate the interface design of the Sumsel Diary application and find out its strengths and weaknesses using the Golden Rules of User Interface Design model by Theo Mandel. The research method used is a case study supported by literature studies such as scientific journals and books that are in line with the discussion of this article, and reinforced by simple interviews with users of the Sumsel Diary application. The results of the discussion show that the design of the Sumsel Diary application interface can be said to be good, although there are still many shortcomings. This can be seen from the evaluation results with three aspects from Theo Mandel namely, the first aspect positions the user as a control which shows that the Sumsel Diary application is user friendly even though there are deficiencies in collection downloads and supported smartphones. The features and interface display are easy for all users to understand, then finally there is the value of consistency from coloring, layout, positioning of features and menus in the Sumsel Diary application. However, there are also some deficiencies in technical issues and book collections in the application database.
Optimization of Archive Digitization at the Padjadjaran University Central Library

Digitizing archives or converting archival media from conventional to digital is one way to optimize archive management in an institution so that archives can be archived more efficiently and easily accessed. The purpose of this study is to provide an overview of the optimization of the digitization of archives in the Central Library of Padjadjaran University. The method used is descriptive qualitative. Techniques in data collection, researchers carried out three series of stages, namely interviews, observation and literature study. The results of this study show that the digital archives at the Padjadjaran University Central Library are compiled in a system called e-Office and centralized with the Padjadjaran University Record Center. With this digital archive, archivists and users can easily access it simultaneously and make it easier to retrieve information. Digital archive management goes well through four stages, namely creation, use, maintenance, and depreciation. However, there are still obstacles that are experienced, including the low awareness of some higher education institutions in collecting files for digital archives, a lack of human resources with special expertise in the field of archiving, and a lack of human resources with expertise in technology. It can be concluded, the digitization of archives and their overall management at the Padjadjaran University Central Library is considered optimal.
Numerical Simulation Evaluation of Solar Radiation on Solar Power Station in Yangjiang

Based on the mesoscale model in GuangDong, which is belong to China Meteorological Administration (hereinafter referred to as CMA-GD model), this paper conducted a forecast test on the total solar radiation in Yangjiang City, Guangdong Province for four typical months in 2022. The forecast capability of this test on the total solar radiation from different perspectives is evaluated by using statistical methods based on the time-by-time total solar radiation observations of five photovoltaic power stations in Yangjiang. The results show that the overall simulation effects are good. The correlation coefficients between 24-hour forecast and observation of solar radiation in Yangjiang City in 2022 are between 0.82-0.86. And the differences between 48-hour and 24-hour forecasts are insignificant. Among the typical months, the correlation coefficients in October is the best (0.87<R<0.95), which is related to the climate characteristics of Yangjiang City with more sunshine and less rain in autumn. The relatively large errors in the solar radiation forecasts for each photovoltaic power station in January and August are related to factors such as more cloudy weather in winter and more convective weather in summer in Yangjiang. Furthermore, from the assessment of daily variation, the forecast of solar radiation at noon has a larger deviation than other parts of the day. The forecast effect is better in the afternoon than in the morning. In addition, weather conditions have a large impact on solar radiation, with sunny days having the highest correlation coefficients (0.72<R<0.82) and rainy days having the smallest correlation coefficients (0.37<R<0.52). The coefficients of overcast sky are only next to sunny days. The daily fluctuations of solar radiation in cloudy days are relatively obvious and the deviation is between overcast sky and rainy day. In addition to weather type, the topography also has a large influence on the forecast of surface solar radiation. The further research is needed to improve and revise the solar radiation forecast considering factors such as topography and weather type.
Study on recognition technology of QR code superimposed on images using GAN

As part of our series of study on optical watermarking, we studied technology for recognizing QR codes embedded in subject images. Since the QR code is superimposed on the subject image, it cannot be recognized by a normal QR code reader. In this study, in order to recognize the QR code, we tried to reproduce the original QR code image before it was embedded in the subject image using a u-net type pix2pix GAN. (Generative Adversarial Network). From an experiment in which training was performed more than a certain number of times using 4000 training images, it was confirmed that the QR code image could be separated from the subject image, the original QR code image could be reproduced, and the character information represented by the QR code could be recognized.
Pelatihan Teknik Cinematic sebagai Media Bantu Promosi Digital

In the world of beauty service business, the increasingly competitive competition encourages entrepreneurs to improve the quality of their services and products so they can compete in the market. Salon Bricela, a beauty salon specifically for women, offers various types of grooming services to attract consumers. However, with the emergence of many salons and spas in the city of Mataram, Bricela Salon needs to find a different way to promote its products and increase its presence. One of the solutions chosen is to make promotional videos that use cinematic techniques to attract consumer interest. The purpose of this thesis is to make a promotional video that introduces Salon Bricela's Spa care products that are not well known in the wider community. The result of this research is a promotional video using Cinematic Techniques as a Media for Digital Promotion which displays the types of treatments and beauty products used in the Bricela salon. It is hoped that by using this technique, the promotional video for Bricela Salon will become more attractive and easily understood by consumers, so it can increase the existence of Bricela Salon in the city of Mataram.
Summarization of Investment Reports Using Pre-trained Model

In this paper, we attempt to summarize monthly reports as investment reports. Fund managers have a wide range of tasks, one of which is the preparation of investment reports. In addition to preparing monthly reports on fund management, fund managers prepare management reports that summarize these monthly reports every six months or once a year. The preparation of fund reports is a labor-intensive and time-consuming task. Therefore, in this paper, we tackle investment summarization from monthly reports using transformer-based models. There are two main types of summarization methods: extractive summarization and abstractive summarization, and this study constructs both methods and examines which is more useful in summarizing investment reports.
Generating Distributed Representations of Words from Japanese Wiktionary with BERT

In this paper, we introduce a novel approach to create distributed representations of words. While existing methods such as Word2Vec learn from unstructured datasets of plain text, our approach leverages the structured contents of Wiktionary. It employs a pre-trained BERT model to obtain representation vectors of individual Wiktionary headwords by text embedding the corresponding contents of Wiktionary entries. We demonstrate that our proposed method outperforms a Word2Vec model in a XABC test result, potentially due to its ability to leverage both the quality of a pre-trained BERT model and expert-moderated Wiktionary, whereas further research is needed to fully understand the effectiveness of our proposed method under various conditions.
Tracking Learners’ Visual Attention of a Virtual Platform during the COVID-19 Pandemic: Evidence from Eye Movements

Due to COVID-19, higher education institutions around the world are resorting to real-time online platforms as a solution to the impacts of the pandemic. This study used a portable eye tracker and an eye movement analysis software to explore learners’ visual attention of online learning platform during the COVID-19 pandemic. The study recruited 40 students studied in the school of information and design at a university in southern Taiwan. With the Google Meet online learning platform as material, eye-tracking technology was used to collect the participants’ eye movement data, and their fixation data were analyzed with eye movement indicators to infer the participants’ visual attention behavior based on attention-based regions of interest (ROIs). The finding results showed that (1) the shared screen of learning material on online learning platform received the most visual attention and first attracted the attention of the participants; (2) the featured area of learning material has the greatest capacity to hold attention; and (3) the shared screen has a stronger visual attention than any other areas. The results can illustrate the cognitive behavior presented in online learning from eye movement behaviors in the post-pandemic era, and can serve as reference for educators to provide adaptive assistance according to the learners’ cognitive processes, which can help maintain educational quality with high effectiveness despite the threat of the pandemic.
A Cyber-Physical Mixed Reality System to Facilitate Chemical Laboratory Safety Education

This research develops a novel cyber-physical mixed reality system (CPMRS) to assist chemical laboratory safety education, allowing learners to conduct inquiry-based experimental operations in an environment integrating virtual and physical space by using a free and safe way so that chemical laboratory safety problems normally occurred in real chemical laboratories that may hurt learners can be avoided. This study adopted a true-experimental research design. A total of 36 Grade 11 students from a senior high school in Taipei City were recruited. 17 students were randomly assigned to the experimental group who used the CPMRS developed by this study to conduct chemical laboratory safety education, while the remaining 19 students were randomly assigned to the control group taught by a teacher in a physical chemical laboratory. The results show that the CPMRS developed in this study could effectively support learners to develop and enhance their chemical laboratory safety knowledge and contribute an innovative learning model to chemical laboratory safety education.
Combination and Knowledge Extension of Pre-trained Language Model for Offensive Language Detection

Nowadays, more and more offensive comments are posted on social media. Those offensive comments can seriously cause mental damage to other people. Therefore, those toxic and harmful comments should be detected timely and accurate. In this paper, we exploit the powerful pre-train language models (PLM) in detecting offensive language. We consider two PLMs in our paper: BERT and DeepMoji. We finetune their combination and evaluate the performance with two datasets: Ask FM and Curious Cat. We found that DeepMoji outperforms BERT. We analyze the result from two aspects and conclude that the task and data of pre-training are important to PLM. Seeing that BERT is less effective than DeepMoji, it is possible to improve the performance of BERT. We then propose a “Knowledge Extension” method to improve the performance of the BERT model. We find that the performance of PLM with high-quality extensional knowledge can be improved significantly.
Using Interactive Visualization for Guiding Non-IT Students to Understand the Concepts of Artificial Intelligence

The paper discusses the use of interactive visualization tools to teach artificial intelligence concepts to non-IT students, who may find the subject abstract or complex. Specifically, an open interactive visualization tool is introduced in a learning activity of model exploration, which includes simulators of common machine learning algorithms of classification. Guided questions are provided to help scaffold students’ learning and facilitate effective and efficient learning strategies. The paper suggests that interactive visualization tools and guided questions can promote active exploration and scaffold students’ learning of information concepts. The aim is to help non-IT students understand the concepts of artificial intelligence and adapt to the future workplace early, so that they can apply artificial intelligence to solve problems in the future.
A Study of Correcting Handwritten Answers for Short Essay Self-learning Systems

We aim to develop an e-learning system for improving Japanese language proficiency. This system not only provides immediate scoring and advice for learners’ answers but also automatically generates questions to offer a wide range of problems across various fields. As the first step for this purpose, we aim to accurately extract the content described in handwritten essays. When dealing with handwritten characters, OCR software alone cannot achieve sufficient accuracy due to noise, distortion, and idiosyncratic handwriting. Therefore, we first train a neural network for character recognition using a handwritten character database, and then divide the essay images into single characters to determine the most likely character candidates. Furthermore, we treat character identification as a fill-in-the-blank problem for sentences and use BERT’s Masked Language Model task to determine characters that form natural sentences. Applying this method to actual handwritten essays on manuscript paper, we were able to extract characters with higher accuracy than before.
Topic Classification of Key Audit Matters in Japanese Audit Reports by Zero-shot Text Classification

Japanese listed companies must submit audit reports to the authorities. In principle, these reports must include Key Audit Matters (KAMs), which are matters that the auditors, as professional experts, have determined to be especially important in the audit of the financial statements. This paper provides a promising approach for classifying KAMs topics using zero-shot text classification, which can save time and resources in the analytical process related to audits. The experimental results demonstrate that the method using Generative Pre-trained Transformer 4 (GPT-4) achieves the highest classification accuracy.
Applying Augmented Reality Technology to Develop an Internet of Things Assembly Learning Guide System

The Internet of Things (IoT) has become one of the most significant technological developments today. Therefore, teaching relevant knowledge to students has become a subject that teachers attach great importance to. In addition to teachers’ traditional, unilateral teaching methods, many scholars have introduced mobile devices into lessons. This involves putting the teaching content on a mobile device and letting the students watch the operation on screen. However, students cannot manage both the teaching content and the object to be assembled simultaneously, which causes a decrease in learning absorption. Therefore, this study proposes a set of teaching systems for IoT assembly. It combines augmented reality technology with mobile devices and adds augmented reality elements to the teaching methods. By intuitively presenting teaching content and interactive operation, it could allow students to assemble and understand information about objects simultaneously just by watching the phone screen. Moreover, students could independently complete the entire learning process under the system’s guidance. We expect this study to reduce students’ challenges in studying IoT through such learning activities and, thus, increase students’ curiosity in learning IoT knowledge.
Research on Atari Games using Evolutionary Computation with Successive Halving

Currently, distributed deep reinforcement learning is one of the most popular approaches in game AI research. However, research on game AI using distributed evolutionary computation is limited. These methods utilize large amount of computational resources. Therefore, reducing the computational complexity of the algorithm is very important to improve the training efficiency of game AI agents. In this study, we propose a method for efficiently selecting top individuals from a set of game AI agents, based on Successive Halving. We applied Successive Halving to Genetic Algorithm and trained game AI agents on three Atari 2600 games. Consequently, we succeeded in improving the training efficiency of these three games in the early stages of training. We have concluded that proposed method can be utilized as a fast initial solution generation algorithm. We suggest that hyperparameter optimization techniques can be applied to algorithmic improvements in evolutionary computing.
A Recommendation Mechanism Combined with Bayesian Networks and Incentive Theory - A Recommend System Design

In recent years, due to the development of e-commerce, recommendation systems have been widely used in many fields. Although the recommendation technology has become increasingly mature, there are still some problems. For example, the recommendation system cannot provide recommendation information correctly under the premise of insufficient user information. This paper proposes a recommendation mechanism combining Bayesian network and incentive theory, by finding out the potential rules in the user profile and encouraging users to share the evaluation of new items under the premise of individual rationality and incentive compatibility. Experiments have shown that expanding the user profile and encouraging users to rate can help the system improve the recommendation accuracy of the system in the case of insufficient user information.
Using Google forms as a Learning Evaluation Tool in Information and Communication Technology Training for Teachers

This study aims to describe participants' responses or perceptions of the use of Google forms as an alternative learning evaluation tool in Information and Communication Technology (ICT) Technical Training for Madrasah Teachers in East Seram District. This type of research is qualitative research using the descriptive analysis method. Data collection was carried out using a questionnaire distributed to all participants, totaling 30 people. The results of the study show that learning evaluation using Google forms is very effective, there are no problems when using it, the access is fast, it is very easy to use and not complicated, and the results are very accurate so that the evaluation objectives can be achieved, it is also fun, efficient in terms of time and cost, so can be recommended for the facilitator to use it.
Pengaruh Model Pembelajaran Bermain Peran Terhadap Hasil Belajar Pembelajaran IPS Siswa Kelas V SD

This study aims to determine the effect of models role playing on the results of social studies learning in fifth grade students of Elementary School Group XIII Bengkulu City. This research is quantitative research. The research used was a quasy experiment with a matching only pretest-posttest control group design study design. The population in this study was SD Cluster XIII Bengkulu City. The sampling technique uses cluster random sampling. The sample in this study was elementary school with B accreditation and KTSP curriculum. Class V at SDN 77 with students as many as 32 students as the experimental class and class V at SDN 83 with students as many as 30 students as the control class. The instrument used is a multiple choice test sheet.. Data analysis techniques used descriptive statistical analysis, prerequisite test analysis, and hypothesis test analysis. From the results of the study it is known that the results of the t-test obtained by tcount 1.850&gt; t table 1.673. So, the conclusion is that there is an influence of discovery learning through media images on the results of social studies learning in fifth grade students of Elementary School Group XIII Bengkulu City.
Penerapan Model Think Talk Write Berbantuan Media Gambar Seri Untuk Meningkatkan Aktivitas dan Kemampuan Menulis Karangan Narasi Siswa SD

This Study aims to determine the application of the Think Talk write model using the media series on the writing material narrative essay in CLASS VI B SDN 17 Bengkulu in Indonesian subjects. This research aims to increase activities and capabilities with the implementation of the Think Talk Write model using the Media series image in class VI B SDN 17 Bengkulu. This research is class action research. The research subject is teacher and student of class VI B SDN 17 Bengkulu City. Research instruments in the form of observation sheets and test sheets. The test data analysis technique uses the average formula value and percentage of the classical learning submission. Observation Data is analyzed using average formula score, highest score, lowest score, score difference and value range for each criterion. Results of the average teacher activity cycle I acquired 32.25 Cycles II acquired 40.25. The student activity of cycle I got an average of 34.75 and cycle II gained 40.75, while for the ability to compose a narrative of students at cycle I with an average of 74.6 and a classical learning submission of 60%. and cycle II with an average of 80.55 with a classical study of the classic, 90%. Thus, it can be concluded that the application of Model learning Think Talk Write using the Media Image series can increase the activity and ability of writing narrative essay in class VI B SDN 17 Bengkulu City ".