Reviewerly/exHarmony huggingface dataset:
Reliable Matching by Combining Optimal Color and Intensity Information Based on Relationships Between Target and Surrounding Objects

Due to the revitalization of the semiconductor industry and efforts to reduce labor and unmanned operations in the retail and food manufacturing industries, objects to be recognized in image processing technology are becoming increasingly colorful and diversified in design. In this paper, we optimize the combination of color and intensity information of a small number of pixels used for matching based on the interrelationship between the target object and surrounding objects. We propose a fast and reliable matching method using these few pixels. Pixels with a low pixel pattern frequency are selected from color and grayscale images of the target object, and pixels that are highly discriminative from surrounding objects are carefully selected from these pixels. The use of color and intensity information makes the method highly versatile for object design. The use of a small number of pixels that are not shared by surrounding objects enables high discriminability and fast matching. Experiments using real images have confirmed that when 68 pixels are used for matching, the processing time is 18 msec and the recognition success rate is 99.7%.
GERT: Transformers for Co-speech Gesture Prediction in Social Robots

Social robots are becoming an important part of our society and should be recognised as viable interaction partners, which include being perceived as i) animate beings and ii) capable of establishing natural interactions with the user. One method of achieving both objectives is allowing the robot to perform gestures autonomously, which can become problematic when those gestures have to accompany verbal messages. If the robot uses predefined gestures, an issue that needs solving is selecting the most appropriate expression given the robot’s speech. In this work, we propose three transformer-based models called GERT, which stands for Gesture-Enhanced Robotics Transformer, that predict the co-speech gestures that better match the robot’s utterances. We have compared the performance of the three models of different sizes to prove their usability in the gesture prediction task and the trade-off between size and performance. The results show that all three models achieve satisfactory performance (F-score between 0.78 and 0.86).
A Systematic Literature Review: Challenges of Implementing Indonesian Language Proficiency Test for Students at Universitas Merangin

The research was conducted to describe perspectives on the challenges of implementing the Indonesian Language Proficiency Test (UKBI) among students, especially at Universitas Merangin. The method used is a systematic literature review consisting of identification, screening, feasibility, quality assessment, and qualitative synthesis. The results of the research show that: 1) Complete and comprehensive information about UKBI has not reached the Universitas Merangin academic community properly, 2) There is no policy for higher education institutions to implement UKBI for students; 3) the Relevance of UKBI results to student needs; 4) The current UKBI is paid, so it doesn’t motivate students to take UKBI.
Decoding Creativity in the Digital Age: Blockchain Unveiled - Navigating Opportunities and Challenges in Copyright Protection

Introduction: The advent of blockchain technology is heralded as a promising solution to address the challenges associated with digital copyright. Nevertheless, given the nascent stage of blockchain development, there exist a number of formidable challenges that necessitate resolution.Purposes of the Research: This study endeavors to analyze the opportunities and challenges associated with the implementation of blockchain technology in safeguarding digital copyright.Methods of the Research: This study employs the normative legal research method with a qualitative approach. The utilization of a qualitative approach in normative legal research allows for a nuanced exploration of legal principles and norms. Results of the Research: The findings of the research underscore that blockchain technology, characterized by features such as decentralization, security, transparency, and immutability of data, presents opportunities for enhancing information transparency, detecting fraudulent claims, safeguarding the digital music industry, and automating license payments through smart contracts. Nevertheless, challenges must be addressed before blockchain can be widely implemented, including regulatory uncertainties and cybersecurity threats. Collaboration among government entities, academia, industry players, the private sector, and regulatory authorities is imperative to establish a clear and secure legal framework for the adoption of blockchain technology.
Anomaly detection and visualization for sound data with pre-trained deep neural networks

Anomaly detection in the industrial domain is a critical issue. Although anomaly detection needs expert's experiences or huge person-hours, recent researches of deep neural networks can save much labor. This paper proposes an anomaly detection method for sound data with pre-trained deep neural networks, and an anomaly visualization method to specify the frequency components of anomalous sounds. Common anomaly detection methods train deep neural networks which can detect anomalies in specific domains. However, training such networks from scratch costs a lot because the neural networks have numerous parameters and use lots of data to improve the performance. To address this problem, anomaly detection using the pre-trained image classification networks has been proposed. This method uses feature representations of classification networks and the Mahalanobis distance as the anomaly scores. In this paper, we propose a method which can apply the above method to sound data and evaluate its performance with a dataset for industrial sound which contains machine sounds under normal and anomalous operating conditions in real factory environments. We also propose a visualization method to specify the frequency components when abnormal sounds occur.
From Text to Speech: Enhancing EFL Students' Descriptive Speaking Skills through Picture-Guessing Games

English is a compulsory subject taught at all educational levels in Indonesia. However, many EFL students struggle to achieve fluency in spoken English despite years of study. This disinterest stems from limited enthusiasm and participation. Incorporating innovative media into learning is expected to improve students' speaking skills. Therefore, this research investigates the effect of using pictures in speaking skills development through guessing games. The study employed a quantitative method with a pre-experimental design. A sample of 25 eighth-grade students was selected from a population of 118 at a private school in Sidoarjo. SPSS Version 26 was used to analyze pre- and post-test data. The findings indicate that using pictures in guessing games effectively increased EFL students' speaking abilities, as evidenced by significant score disparities between the pre-test average (11.12) and post-test (16.32). Additionally, the t-count value of 14.066, compared to the t-table value of 2.064 at a 0.05 significance level, suggests a substantial improvement. These results demonstrate that guessing games using pictures significantly enhance student engagement and interest in learning speaking skills. The findings imply that employing pictures in guessing games can potentially enhance student engagement in speaking class activities. Teachers are encouraged to use innovative media to inspire students and enhance their speaking skills.
Role of Federated Learning for Internet of Vehicles: A Systematic Review

The Internet of Vehicles (IoV) is one of the most exciting and practical ways that corporations and academics are interested in, especially by employing coordinated unmanned vehicles to explore areas like the automobile industry. To provide long-term possibilities for task investigations, the IoV connects vehicles, transportation networks, and communication infrastructure. Data privacy, however, may be compromised by the coordination of information gathering from numerous sources. Federated Learning (FL) is the answer to these concerns of privacy, scalability, and high availability. A well-distributed learning framework designed for edge devices is federated learning. It makes use of large-scale processing from edge devices while allowing private data to remain locally. In this work, different categories of federated learning have been discussed. A review of various systems implementing FL for IoV has been presented followed by the applications and challenges of FL in the IoV paradigm. The paper concludes by providing future research directions for FL in the IoV.
Analysis of Detection and Recognition of Human Face Using Support Vector Machine

Recently, Support Vector Machines (SVMs) have been suggested as an additional technique for design identification. In this study, a face detection framework with demeanor recognition utilizing Support Vector Machines (SVMs) with a double tree identification process is used to tackle the face recognition issue. It plays a crucial role in applications including face delineation data set management, human PC interaction, and video examination. Through two steps, the face recognition with appearance appraisal framework accomplishes look recognition. The captured image is initially processed to identify the face, and then the perceived appearance. The first two stages of the framework handle facial recognition and face trimming using picture handling, while the third stage handles converting the altered image’s colors from RGB to grayscale and applying the appropriate smoothing channel. We employ a simple method to create our own SVM classifier with a Gaussian component that can recognize eyes in grayscale photos as the first step towards a part-based face identifier. The architecture of an iterative bootstrapping method is discussed in detail, and we show how choosing boundary values will usually result in the best outcomes. The findings of our study are in line with earlier studies, and the challenges encountered are typical for anybody developing an article identification system. Large support vector SVM classifiers are sluggish, and accuracy is highly reliant on the caliber and diversity of training data.
Towards Better English to Bharti Braille Neural Machine Translation Through Improved Name Entity Translation

In this paper, the expansion of English to Bharti Braille neural machine translation system has been carried out. It is shown how a baseline Neural Machine Translation (NMT) model can be improved by adding some linguistic knowledge to it. This was done for five language pairs where English sentences were translated into five Indian languages and then subsequently to corresponding Bharti Braille. This has been demonstrated by adding a sub-module for translating name entities. The approach shows promising results across language pair and improvement in the quality of NMT outputs. The least improvement was observed in English-Tamil language pair with 8.79% and the most improvement was observed in English-Hindi language pair with 15.01%.
Alpha Mini as a Learning Partner in the Classroom

Social robots such as NAO and Pepper are being used in some schools and universities. NAO is very agile and therefore entertaining. Pepper has the advantage that it has an integrated display where learning software of all kinds can be executed. One disadvantage of both is their high price. Schools can hardly afford such robots. This problem was the starting point for the project described here, which took place in 2023 at the School of Business FHNW. The aim was to create a learning application with an inexpensive social robot that has the same motor capabilities as NAO and the same knowledge transfer capabilities as Pepper. The small Alpha Mini from Ubtech was chosen. It was possible to connect it to an external device. This runs a learning game suitable for teaching at primary level. Alpha Mini provides explanations and feedback in each case. Three teachers tested the learning application, raised objections, and made suggestions for improvement. Social robots like Alpha Mini are an interesting solution for knowledge transfer in schools when they can communicate with other devices.
Development of Employment Skills and Career Growth of Higher Education Graduates in the Context of Best International Practices

The article discusses the challenges of employment for higher education graduates and justifies effective approaches to developing employment skills and further career growth. It is noted that the key skills for employment include multitasking, leadership, critical thinking, creativity, determination, communicativeness, the ability to present activity results, flexibility, decision-making, teamwork, responsibility for achieving common goals, and so on. Approaches to organizing educational activities and skill development methods are highlighted: a differentiated approach, student-centered learning, the use of active teaching methods, networking, mentoring, coaching. Traditional and innovative methods of graduates' skill development are singled out (project method, puzzles, mind maps, discussions, debates, interactive mini-lectures, presentations, problem-based learning, inquiry-based learning, case method, etc.). Emphasis is placed on the activities of university structural units in providing comprehensive preparation of graduates for the job market, covering skills such as successful resume writing, interviewing, job interviews, adaptation to the first job, lifelong learning, and time management.
Overview of Breast Examination Screening in Labuhan Haji and Pengadangan Village East Lombok Regency

Breast lump is a condition that is often experienced by many women. Breast cancer is ranked second after cervical cancer which is most common suffered by women in the world. This article was written with the aim of early detection of breast lumps and the number of cancer cases. The subject of this study was a ≥18-year-old woman in Labuhan Haji Village and Pengadangan East Lombok Regency. This study used a non-analytical obssional descriptive method using a cross-sectional study. The data that has been obtained will be analyzed descriptively in the form of diagrams. The results of this study can be concluded ingeneral that the type of lump neoplasma found FAM (Fibroadenoma) which is as many as 7 respondents compared to other types of tumors. The type of non-neoplasma lump that was found in this study was Fibrocystic disease or commonly called fibrostic as many as 6 respondents. Mammae aberans were found in this study, namely as many as 2 respondents aged 53 and 60 years. Ductal Carcinoma or breast cancer with ductal type as many as 1 respondent with the age of 60 years. Ginecomastia there was 1 male respondent aged 33 years.Each tumor in the breast has a tendency to occur in a certain age range and each tumor in the breast has a type of benign and malignant tumor.
Didactic foundations of digitalization of the educational process in the Gymnasium at the University

The article analyzes the modern didactic foundations that influence the development of digital processes in the educational activities of the gymnasium at the university. The object of the study is Gymnasium No. 52 at the Don State Technical University (Rostov-on-Don), the subject of the study is the processes aimed at developing didactic approaches to digitalization in the educational activities of the gymnasium, with deep involvement in the professional, project, research work of gymnasium students for further study at the university. In the course of the theoretical analysis, the content characteristics of the didactic approach in the aspect of digitalization of education (methodology, competencies, tools, technologies) are clarified. Based on didactic principles, the attitude, involvement and perception of digitalization of education in the gymnasium and at the university were empirically determined. The results of the study are summarized graphically, which reflects the importance of improving the basic principles of didactics in pedagogy, and the formation of author’s approaches to the use of digitalization in the educational process as a basis for the development of competencies, teaching techniques and technologies.
Linking e-leadership to innovative and proactive work behaviors in tourism higher education institutions: a moderated mediation model using SEM

E-leaders should encourage academics to manage their multi- dimensional work requirements and even to go beyond these requirements to innovate in their tasks and achieve sustainable development in educational institutions. This study aims to examine the relationship between e-leadership, innovative work behavior and proactive work behavior in the presence of work engagement as a mediator. Researchers implemented a quantitative methodology. This study used data from an online survey of 398 academics in Egyptian tourism higher education institutions. The results of structural equation modeling presented strong support for the proposed model. E- leadership has been proven to affect innovative and proactive work behavior among academic staff positively. Work engagement has shown an effective and significant mediating role between the examined variables. Further, the academic department was proven to moderate the relation between e-leadership and innovative work behavior, while age had no moderation effect in this relation. The study draws researchers’ attention to the role of e-leadership in helping academics to cope with the dynamic nature of research and education.
Sistem Pakar Diagnosa Penyakit Lambung Menggunakan Metode Certainty Factor

The digestive system is very important for humans, there are several digestive systems, one of which is the stomach. The main function of the stomach in the digestive system is to store and digest food before it is absorbed by the body's cells as a source of energy. A healthy lifestyle in life is very important, including maintaining a diet, not eating carelessly, and getting enough rest. An unhealthy life will also trigger various diseases, one of which is gastric disease. Early and accurate diagnosis of kidney disease can aid in timely and effective management of the condition. an expert system for diagnosing gastric disease with the CF (Certainty Factor) method to assist people in diagnosing gastric disease along with advice based on perceived treatment symptoms. This study aims to develop an expert system for diagnosing kidney disease using the CF method. The developed system consists of components of data collection, data storage, and data processing, with the CF method used to calculate the diagnosis level of confidence and make decisions based on predetermined rules. The CF (Certainty Factor) method shows a measure of certainty about a fact, it is known that user 1, user 3, user 4, and user 5 have the highest proportion of gerd disease, namely 36.7%, 38.8%, 48.9%, 47.6%. While user 2 has the highest proportion of stomach cancer with 24.8%. So this study only has an accuracy rate of 80%. Diagnosis can be an alternative to early detection of several types of gastric disease.
Pendampingan Motivasi Belajar Siswa melalui Penggunaan Ice Breaking dan Media Visual di MI Islamiyah Bumijaya

The aim of community service activities is to provide learning motivation through the use of Ice Breaking and Visual Media at MI Islamiyah Bumijaya. The implementation of PKM activities is carried out in several activity stages, including Problem Identification, Preparation of Program Plans, Training and Preparation, Program Implementation, Monitoring and Evaluation and Preparation of Final Reports. The results of this PKM activity obtained good results, such as increased motivation, student activity in class, and increased student learning concentration both in class and outside of class. The active involvement of teachers, students and parents has contributed to the success of this PKM program. This shows that investment in education has a positive impact on students' development and creates a brighter future for them
Pendampingan Edukasi Cerdas Menyikapi Tren AI (Artifial Intelligence) dalam Dunia Pendidikan

This community service activity aims to provide education about the importance of students at Permata Harapan Batam School being smart in responding to the Artificial Intelligence trend. This activity was attended by 33 participants. Delivery of material is carried out using video conferencing, namely using the zoom application. From the results of this service activity, it is known that after participating in this educational activity, it was found that the students of Permata Harapan Batam School stated that this service activity was very useful, in that the students became aware of the skill requirements that must be possessed to be needed in the future in facing the world of work. gain new knowledge and understand the importance of Artificial Intelligence in the current era of digitalization.
Pendampingan Edukasi Keuangan bagi Peserta Didik SMP Isen Mulang Palangka Raya

Community Service Activities (PKM) with the theme financial education aim to build a culture of financial literacy among Isen Mulang Palangka Raya Middle School students. PKM activities were initiated and implemented by lecturers and students from the Faculty of Economics and Business, Palangka Raya University. There were 16 students who attended this educational activity consisting of 6 class VII students, 3 class VIII students, and 7 class IX students. Student enthusiasm is very high. This is demonstrated by the high level of interaction between students and presenters as well as responses from written questionnaires distributed by the Team at the end of the activity. There are 7 questions related to financial management asked by students to the presenters as well as 12 quizzes from the presenters which the students are able to answer.