Reviewerly/exHarmony huggingface dataset:
Chapter 14. Embedding-Based First-Order Rule Learning in Large Knowledge Graphs

Numerous large knowledge graphs, such as DBpedia, Wikidata, Yago and Freebase, have been developed in the last decade, which contain millions of facts about various entities in the world. These knowledge graphs have proven to be incredibly useful for intelligent Web search, question understanding, in-context advertising, social media mining, and biomedicine. As some researchers have pointed out, a knowledge graph is not just a graph database, but it should have a layer of conceptual knowledge, which is usually represented as a set of first-order rules. However, it is challenging to automatically extract first-order rules from large knowledge graphs. In particular, traditional models are usually unable to handle rule learning in large knowledge graphs. This chapter aims to present state-of-the-art techniques and models on learning first-order rules using representation learning. By first recalling some basics of rule learning in knowledge graphs, we will introduce useful techniques of embedding-based rule learning through major models such as RLvLR and TyRuLe, which embed paths in knowledge graphs into latent spaces for candidate rule search. Then we evaluate the rule learning efficiency and the quality of automatically learned rules by applying them in link prediction. Before the chapter is concluded, we will also discuss some future research problems in the area.
A neonatológia technikai fejlődésének története

The science of neonatology started its proper development in the 1960s with technological advances in providing care for premature neonates. Parallel, the expansion of professional knowledge about prematurity gave hope for babies regarded earlier as ‘by-products’ of obstetrical wards. Through a number of technological achievements and an understanding of the pathophysiology of neonates, the survival of premature and sick babies became business as usual instead of being exceptional. This study provides insight into this complex development in specific fields simultaneously
Deep-Learning-based Analysis of the Patterns Associated with the Changes in the Grit Scores and Understanding Levels of Students

The purpose of this study is to classify the pattern of the understanding level changes for university students during class term, and analyze the relation between them and the changes in the Grid score before and after the class term.Dynamic time warping was applied for classification of the understanding level, and the decision tree was applied to analyze the relation between the changes in the understanding level and that in the Grid score.As a result, it was shown that a large variety of the patterns of changes in the understanding level, and the relations between the understanding level and Grid score cover a wide variety, too.It is necessary to take these results for conducting effective lectures.
Automatic Fraud Detection in e-Commerce Transactions using Deep Reinforcement Learning and Artificial Neural Networks

Fraud is a serious issue that has plagued ecommerce for many years, and despite significant efforts to combat it, current fraud detection strategies only catch a small portion of fraudulent transactions.This results in substantial financial losses, with billions of dollars being lost each year.Given the expected surge in the volume of online transactions in the upcoming years, there is a critical need for improved fraud detection strategies.To tackle this problem, the article proposes a deep reinforcement learning approach for the automatic detection of fraudulent e-commerce transactions.The architecture's policy is built on the implementation of artificial neural networks (ANNs).The classification problem is viewed as a step-by-step decision-making procedure.The implementation of the model involves the use of the artificial bee colony (ABC) algorithm to acquire initial weight values.After that, in each step, the agent obtains a sample and performs a classification, with the environment providing a reward for each classification action.To encourage the model to concentrate on detecting fraudulent transactions precisely, the reward for identifying the minority class is higher than that for the majority class.With the aid of a supportive learning setting and a specific reward system, the agent ultimately determines the best approach to achieve its objectives.The performance of the suggested model is assessed utilizing a publicly available dataset contributed by the Machine Learning group at the Université Libre de Bruxelles.The experimental outcomes, determined using recognized evaluation measures, indicate that the model has attained a high level of accuracy.As a result, the suggested model is considered appropriate for identifying deceitful transactions in e-commerce.
Pengembangan Media Berbasis Augmented Reality (AR) Pada Pembelajaran Biologi Kelas XI SMA Negeri 13 Pangkep

This study is a development research that aims to produce a product in the form of media based on Augmented Reality (AR) in Circulatory System material. This development research refers to ADDIE development model which consists of five (5) stages, namely Analysis, Design, Development, Implementation, and Evaluation. The research instruments employed instrument validation sheet, teacher’s response questionnaire, students’ questionnaires, and learning outcomes test. The sample of the study were students of grade XI at SMAN 13 Pangkep. Based on the results of data analysis, it is discovered that 1) Augmented Reality (AR)-based media in Circulatory System material meets valid criteria with a mean score of 4.8 (valid); 2) the Augmented Reality (AR)-based media in Circulatory System material meets very practical criteria based on the average result of teacher’s response of 96.08% (very positive) and the result of students’ responses 83.25% (very positive); and 3) the Augmented Reality (AR)-based media in the circulatory system material meets effective criteria with the percentage of completeness of learning outcomes by 83.73% (high). Based on the results of the study, it can be concluded that Augmented Reality (AR)-based media in Circulatory System material has met valid, practical, and effective criteria.
Random centroid initialization for improving centroid-based clustering

A method for improving centroid-based clustering is suggested. The improvement is built on diversification of the k-means++ initialization. The k-means++ algorithm claimed to be a better version of k-means is tested by a computational set-up, where the dataset size, the number of features, and the number of clusters are varied. The statistics obtained on the testing have shown that, in roughly 50 % of instances to cluster, k-means++ outputs worse results than k-means with random centroid initialization. The impact of the random centroid initialization solidifies as both the dataset size and the number of features increase. In order to reduce the possible underperformance of k-means++, the k-means algorithm is run on a separate processor core in parallel to running the k-means++ algorithm, whereupon the better result is selected. The number of k-means++ algorithm runs is set not less than that of k-means. By incorporating the seeding method of random centroid initialization, the k-means++ algorithm gains about 0.05 % accuracy in every second instance to cluster.
“DIA SMART” Android-Based Intelligent Application Expert System for Diagnosis and Mapping of 10 Diseases at Teaching Factory Nutrition Care Center

The Basic Health Research in 2018 showed that the prevalence of non-communicable diseases including cancer, stroke, chronic kidney disease, diabetes mellitus, and hypertension increased in Indonesia. The main risk factors are metabolic factors, behavioral factors, and environmental factors. Based on the existing problems, an Android-based intelligent application for the diagnosis and mapping of 10 diseases was proposed at the Teaching Factory Nutrition Care Center. This application development used the Expert System Development Life Cycle model and Dart Language. The framework used is Flutter. This article only discusses the implementation and testing of applications made based on Android. This application was developed to perform a diagnosis based on some patients’ data. This application is used as a reference for early detection of a disease, allowing patients to take preventive measures. It can map the number of patients who had health consultations in each department. The users of the application were a doctor, nutritionist or health consultant at the Teaching Factory Nutrition Care Center. System functionality tested using Blackbox-testing showed that the application ran well.
WiFi-Based Lightweight Gesture Recognition for Coal Miners

With the advancement of smart mines, the need for gesture recognition for remote interaction between underground workers and machines has become crucial. However, traditional gesture recognition techniques require complex models that are very difficult to be deployed to the edge. To address this challenge, a gesture recognition method based on knowledge distillation is proposed in this study. First, the CSI ratio model is used to eliminate phase error and environmental noise, followed by the application of discrete wavelet transform to eliminate hardware noise interference. Then, the processed data is adaptively segmented using the principal component analysis and local anomaly factor algorithm to eliminate redundant static components. After that the processed CSI data is transformed into images using the relative position matrix method. Finally, knowledge distillation is employed to migrate knowledge from a teacher model to a student model, reducing the number of model parameters. Experiments conducted on the proposed method showed that it can achieve a recognition accuracy of 94.2% for hand gesture detection, which meets the requirement for gesture recognition in the mining industry.
Exploring Students’ Difficulties in Learning Listening Comprehension at Second Semester English Education Department of Muhammadiyah University of Makassar

The results of the research from questionnaires and FGD showed that there were seven difficulties faced by students when studying listening comprehension based on listening material factors. First, the difficulty of unfamilliar words. 50% of students have this difficulty because they lack vocabulary. second, the difficulty of unfamiliar topics. students find it difficult when trying to understand the discourse, 40% experienced by students. third, difficulties in interpreting the meaning of spoken texts, especially when dealing with words that have multiple meanings, were also experienced by 40% of students in this study. fourth, difficulty due to the length of the spoken text which causes loss of concentration and motivation of students due to boredom, 60% of students find it difficult with the length of the spoken text. fifth, the difficulty in the type of input (eg the type of input from direct teaching by the lecturer) the fact that the listening comprehension class faced by the respondents was an online class, which made students experience various problems such as disruption of the teaching and learning process. the process of receiving information from lecturers due to unstable networks in some areas. sixth, 60% of students face difficulties in verbal instruction, because lecturers or native speakers have different accents and the last is difficulty in understanding when the speaker speaks very fast, based on the findings of this study it was found that the speaker's speaking speed is a difficulty experienced by all students.
Analysing The Problems Faced by The Students at The Sixth Semester to Speak English at English Education Department

This study aimed to find out the problems faced by the students in the sixth semester of English Education Department at Unismh Makassar to speak English fluently in the class and the factors causing the problems. This study used descriptive qualitative method in type of phenomenology in which the researcher used observation checklist and semi-structure interview to collect the data. The results showed that there are two main problems faced by the students to speak English fluently, namely linguistic problems which consist of: poor in grammar, lack of vocabulary and lack of pronunciation and also non-linguistic problems which consist of: blankness, shyness and anxiety. The factors causing students are poor in grammar manly caused by: seldom to learn grammar by themselves and were seldom to learn grammar in the previous semesters. Lack of vocabulary is caused by the students are not motivated to improve vocabulary by themselves. Lack of pronunciatiaon are caused by: the interference of mother tongue, lack of practice by themselves and pronunciation classes lacked of practice. In addition, blankness are mainly caused by: forget what to say, interruption and eye contact. Furthermore, shynes is caused by the students are afraid of making mistakes. Lastly, anxiety is caused by the students are afraid of being laughed or judged and commentated by the lectures if making mistakes.
Effect evaluation of ideological and political guidance in university party construction based on hierarchical analysis model

Abstract To further explore the evaluation model of the quality of college students working in vocational colleges, this paper proposes to establish an evaluation index system for the quality of college students working in vocational colleges according to the four main factors of the domestic vocational college, which is based on the analysis of the quality. the work of the party building, the quality and responsibility of the party members, and the mass examination; In the process of evaluating the quality of college students’ dormitory building, various useful and useful information were determined, and the evaluation model was established by using the analytic hierarchy process, and the weight coefficients of various influential factors were determined by the combined method. First of all, according to the characteristics and requirements of the student’s institution, combined with the system of employment management widely used in China, combined with the practice of students’ institution, thoroughly analyzed various factors which affect the quality of the student’s institution building, and establish a more effective and objective evaluation index system. Secondly, using the analytic hierarchy process to scientifically classify the indicators, and determine the evaluation factor set and evaluation criteria, establish a hierarchical structure model. Finally, combined with the hierarchical structure model, the relative weight of each evaluation factor is given using the principle of fuzzy mathematics.
Translation Error In Advertisements

The researcher intends to conduct a study to examine advertisement banners that have an error in translating or modifying the word from source language to target language. the research is to investigate the many sorts of translation errors in advertisement banners. The study concentrated on the incorrect translation of source language to target language that occurred in advertising. This research is classified as Descriptive Qualitative Research. Qualitative research is a descriptive method in which data is collected in the form of written or spoken words. The data was collected from 20 public signs in Medan by the researcher. These public signs display the name of the service to the public. After assessment the data, it was discovered that translation error is 70% in spelling mistakes, 10% in grammatical errors, 15% in vocabulary misspellings, and 5% in punctuation. The greatest percentage is found in spelling errors. In the interview section, spelling mistakes and vocabulary misspellings occurred because they did not know how to produce the correct word due to a lack of vocabulary in English. Grammatical errors occurred because they did not know how to arrange the words correctly, and punctuation is the lowest error since it is not difficult to know how to apply proper punctuation in text
ANALISIS SENTIMEN PENILAIAN MASYARAKAT INDONESIA TERHADAP KONFERENSI G20 DI BALI DENGAN MENGGUNAKAN METODE NAIVE BAYES

Lot of Indonesian people support the holding of the G20 conference in Bali and many people also disagree with the G20 that will held/hold in Bali for various reasons. Therefore this research is conducted to find out how much the Indonesian people agree or disagree with the holding of the G20 High-Level Conference (Summit) which was held in Bali, Indonesia. In this study used research methods of data collection, preprocessing stage, Naive Bayes classification stage, and confusion matrix evaluation stage. In this study, 2,255 data were used with 1,000 training data and 1,255 test data. After the data is processed and the sentiment predicted in the test data, the confusion matrix is calculated to calculate the accuracy of the results. On data that has been processed the accuracy obtained is 95.60%.
Privacy Concerns in Document Sharing: “A Study on Indian Photocopy Shops and Cyber Centers"

In the context of India's document printing practices, this research paper sheds light on the existing shortfalls in privacy and security. Despite the prevalence of digital sharing, conventional methods such as email and messaging platforms continue to be widely used, putting sensitive documents at risk of unauthorized access, data breaches, and potential misuse. This paper aims to address these concerns by proposing a practical approach tailored to the unique needs of photocopy making shops and cyber centers. By focusing on enhancing privacy and security measures, the proposed approach aims to empower individuals and organizations with greater control over their sensitive documents. The research delves into the pressing concerns surrounding document handling in these environments and explores ways to ensure data protection while utilizing modern document printing and sharing technologies. Through this timely endeavor, the aim is to create a safer and more secure ecosystem for document management in India's photocopy making shops and cyber centers. Keywords: Document printing, Privacy, Security, Data breaches, Misuse, Photocopy making shops, Cyber centers, Document handling, Data protection, Modern document printing, Sharing technologies, Safer ecosystem.
Sosialisasi Tentang Manusia Sebagai Homo Digital Pada Siswa Kelas XII SMA Ikarasi Melalui Pengenalan Aplikasi Corel Draw

The result of community service on the socialization of Humans as Homo Digital to class XII students of Ikarasi High School through the introduction of the Corel Draw application is an increase in students' technological skills in graphic design. This activity involves training and practice in using the Corel Draw application to create creative and attractive graphic designs. In this activity, students learn about how to use the Corel Draw application to create quality graphic designs. They also learn about techniques and strategies in creating attractive graphic designs as well as how to use digital technology wisely and effectively. The result of this activity is students who have technological skills in creating graphic designs, as well as understanding how digital technology can improve the quality of their work. In addition, this activity also increases students' awareness of the risks and potential negative impacts of unwise use of digital technology, such as addiction, social isolation, and mental health disorders. In conclusion, the community service activity on the socialization of "Humans as Digital Homo" to class XII students of Ikarasi High School through the introduction of Corel Draw application is an effective way to improve students' technological skills in graphic design, as well as increase their awareness about the wise and effective use of digital technology. This can provide benefits for students in improving the quality of their work and preparing them to live and work in the digital era.
ANALISIS PENGGUNAAN APLIKASI PENGOLAH NILAI RAPORT DALAM MENINGKATAN KEMAMPUAN TEKNOLOGI GURU DI PKPPS AL HIDAYAH KARANGSUCI

This study aims to analyze the use of report card processing applications in improving the technological abilities of teachers at PKPPS Al Hidayah Karangsuci. The research method used is a case study approach using a qualitative approach. The time for the research was carried out for one month, from February 1 to March 1 2023. The research subjects consisted of school principals, curriculum representatives, and homeroom teachers. Data collection techniques namely interviews, observation, and documentation. The results of this study indicate that the use of a report card processing application has the potential to provide convenience and efficiency in managing report card grades. Teachers can reduce the time needed to calculate and process data manually by using this application. However, weaknesses were also found in terms of lack of facilities and infrastructure which could affect the teacher's enthusiasm in learning and understanding grade processing applications.
Comparison of canonical correlation and discriminant analysis

Learning from data is at the heart of the statistical discipline known as statistics. Understanding statistics, you will be able to use the right techniques to obtain the data, carry out the relevant analysis, and present the results in an effective way if you have a working knowledge of statistics. The process of creating scientific discoveries, as well as decisions and projections that are founded on data, involves the use of statistics, which is a key element in the process.
EFEKTIFITAS PENGGUNAAN BUKU AJAR STATISTIK DALAM MENINGKATKAN HASIL BELAJAR MAHASISWA

At the beginning of 2020, the world was shaken by a deadly virus attack, namely, Covid 19. As a result, all activities were completely paralyzed, including teaching and learning activities. Seeing these conditions, the researchers compiled a statistics textbook as a guide for STIE Bima students. For this reason, the purpose of this study was to look at the effectiveness of using statistics textbooks in improving student learning outcomes in semester II of STIE Bima in the 2021/2022 Academic Year. Thus, lecturers will be able to compile teaching books by taking into account the characteristics and needs of students. This research involved 80 students who were divided into 2 classes. This research is a development research. Before the Statistics Textbook is distributed to students, validity is first tested. From the results of the two statistics textbook validators are in the valid criteria, that is, minor improvements were made such as the use of language, typing errors and others. The results of the analysis, it was found that the use of statistical textbooks had a high effectiveness in increasing student learning outcomes, this was indicated by the N-Gain value of 0.71 greater than or equal to 0.7 with an N-Gain percentage value of 70.54%. Not only that, it can also be seen in the increase in the average score in the pre-test versus post-test by 65.79%.
Robust Hadith IR using Knowledge-Graphs and Semantic-Similarity Classification

Hadith is the term used to describe the narration of the sayings and actions of Prophet Mohammad (p.b.u.h.). The study of Hadith can be modeled into a pipeline of tasks performed on a collection of textual data. Although many attempts have been made for developing Hadith search engines, existing solutions are repetitive, text-based, and manually annotated. This research documents 6 Hadith Retrieval methods, discusses their limitations, and introduces 2 methods for robust narrative retrieval. Namely, we address the challenge of user needs by reformulating the problem in a two-fold solution: declarative knowledge-graph querying; and semantic-similarity classification for Takhreej groups retrieving. The classifier was built by fine-tuning an AraBERT transformer model on a 200k pairs sample and scored 90% recall and precision. This work demonstrated how the Hadith Retrieval could be more ef icient and insightful with a user-centered methodology, which is an under-explored area with high potential.