Reviewerly/exHarmony huggingface dataset:
Aplikasi Sistem Pakar Diagnosa Kerusakan Motor Matic Injeksi Berbasis Web (Studi Kasus: Bengkel Pelangi Motor)

Abstract&#x0D; &#x0D; In the case study at the Pelnagi Motor workshop located on Jl.Raya Serua Cinangka, Bojongsari District, Depok City, there is a problem that there is no automatic system to analyze damage to an injection matic motorbike to ease the work of mechanics or workshop mechanics. This research aims to design a web-based expert system application to help and facilitate the work of a mechanic or workshop mechanic. Researchers use the Prototyping Model as a method of designing systems that are built. And the use of the Forward Chaining method as the brain of the expert system. The system is implemented into a damage detection/diagnosis web application that can help mechanics or mechanics analyze customer vehicle damage and receive repair instructions quickly.&#x0D; &#x0D; Keywords: Injection Matic Motorcyle, Expert System, Forward Chaining
Writing Strategies of Freshmen and Sophomore Students in a Tertiary Institution: Implications to English Teacher

This research aims to determine students' writing strategies in a tertiary institution in Olongapo City, Philippines. Seventy-two (72) college freshmen and sophomore students participated in the study. The researchers used a standardized survey questionnaire to gather pertinent data. Also, the researchers calculated the descriptive and inferential statistics using SPSS 20. The study results revealed that the student respondents have a "neutral" response to the monitoring and planning for writing. On the other hand, the student-respondents gave an "agree" remark for the revising and thinking aspects of writing. Furthermore, the study also found significant differences in the writing strategies of the freshmen and sophomore students when grouped according to their sex regarding revising, thinking, and planning.
A Collaborative Fault Detection Navigation Method for Cluster Aircrafts

The traditional receiver autonomous integrity monitoring (RAIM) algorithm is used to detect the pseudorange estimation residuals of a single aircraft. For the relatively small and medium-sized pseudorange errors, RAIM algorithm has low fault detection sensitivity and cannot be applied to navigation systems with accurate positioning requirements. A cooperative observation integrity monitoring (COIM) algorithm is proposed in this work, which makes full use of the characteristics of the cluster and uses GNSS receivers of multiple aircrafts to construct common-mode residual detection statistics to improve the performance of fault detection. This constitutes a key innovation presented in this paper. Besides, the navigation system can monitor whether the auxiliary sensor is abnormal while monitoring the satellite fault. The simulation results show that COIM greatly improves the fault detection rate of GNSS satellites, and can be extended arbitrarily on the basis of satellite fault monitoring to detect whether the measurement values of auxiliary sensors in the navigation system are abnormal.
Upaya Meningkatkan Motivasi Belajar Siswa Kelas IV (EMPAT) SD N. 173434 Pollung Melalui Model Pembelajaran Problem Based Learning (PBL)

Motivation is something that is important for every person, perhaps even without motivation it will be difficult for us to achieve the expected goals. Therefore, movitavi is also very necessary for students in undergoing or pursuing education, both from the basic education level and also beyond.This motivation is especially important for students when taking part in teaching and learning activities, with this, students truly realize that the learning activities they undertake are really important and really only for their own benefit. So that students always make maximum efforts in participating in teaching and learning activities to develop their abilities.Without basic awareness and motivation from students regarding the importance of developing abilities through learning activities, they will lose direction and not know the benefits or goals and perhaps even learning activities will be a burden for them, not something interesting even if they are involved or take part in learning activities. on a daily basis.Students at the basic unit level (SD) may not yet be aware of or understand the motivation within themselves, as well as a fundamental and strong understanding of why they should take part in education. In addition, environmental factors (maintained) by the community regarding the world of education also influence their understanding, mindset and character in participating in learning activities at school.Based on the above, I try to build student motivation in teaching and learning activities through the problem based learning (PBL) learning model so that students experience interesting learning experiences, in an effort to increase their learning motivation. From the classroom action research activities carried out, it was concluded that this model can stimulate and increase students' motivation which actually shows the development of their learning achievements.
The Determinants of Environment Disclosures of Public Listed Firms in Malaysia

Determining environmental disclosure is important because it promotes corporate transparency, ensures accountability for environmental impacts, and aids stakeholders in making informed decisions.The objective of this study is to investigate the link between specific firm attributes and environmental disclosure.A final sample of this study consists of 429 Malaysian public listed firms in the year 2016.Data on firm size, profitability, leverage and disperse share ownership were obtained from Eikon database while dependent variable which is environmental disclosure and other variables such as environmental management systems (EMS), age and auditor type were manually collected from firm annual reports.The environmental disclosure is measure based on 11 environment related-words highlighted which are energy or electric, water, biodiversity, emission, effluent, waste, recycle, reuse, spill, environmental impacts and ISO 14001.The regression results show that firm size, industry type, EMS and disperse share ownership are significantly influence environmental disclosures.This study proves that certain firm characteristics, coupled with good corporate governance mechanisms, can motivate firms to provide environmental disclosures.Further research proposes using alternative proxies for environmental disclosure to examine its relationship with foreign associations, brand awareness, firm value, and the cost of financing, which could offer new insights into environmental disclosure practices.
The Effect of Using VOA Podcast on Students Intensive Listening Skill

The purpose of this research was to find out the effect of podcast or VOA podcast in improving the eight grade students English listening skill. This research utilized a sample of 30 students from a class, comprising 13 males and 17 females. Data collection for this research involved the use of measurement techniques, specifically the gap-filling test as the instrument. The collected data was analyzed to assess the impact of podcasts on students' listening skills. The results of the study revealed a significant improvement in students' listening skills with a t-value of 7.131, exceeding the critical value of 2.045 (t-value = 7.131, df=29). This indicated a significant impact of using podcasts in EFL students' listening learning (7.131 &gt; 2.045) with a medium effect size of 0.77. Therefore, the findings suggest that the use of podcasts effectively contributed to the improvement of students' listening skills.
Implicit collaboration with a drawing machine through dance movements

We demonstrate the initial results of our exploratory work, investigating the potential for creative machines to collaborate with people through movement as a form of implicit interaction. The paper describes a Wizard-of-Oz demo, where a hidden wizard controls an AxiDraw drawing robot while a participant collaborates with it to draw a custom postcard. This demonstration aims to gather perspectives from the computational fabrication community regarding how practitioners of fabrication with machines experience interacting with a mixed-initiative collaborative machine.
Comparative Study of Approaches for an Ontology of Digital Artifacts

Abstract Modern business, engineering, and manufacturing are supported by many software tools. Those tools not only help create new products for customers but also enable delivering them in increasingly shorter time periods. To achieve both, the ability to transfer, exchange, integrate, and analyze digital data among supply chain participants with diverse software tools is needed. Creating that ability, however, requires a higher level of interoperability with support from semantics tools, such as knowledge graphs and ontologies. As many engineering and business tasks involve digital communication, it is important to develop ontologies for digital artifacts of various fidelity levels and various scopes of the product life cycle to enable the required interoperability. There are ontologies associated with the various stages of the product life cycle. Those ontologies have various fidelity levels that correspond to specific lifecycle stages and that enable the required interoperability within those stages, with very few enabling interoperability between the stages. To address those ontology needs, the Industrial Ontology Foundry (IOF) has released the first version of its Core ontology. The Core provides a basis to represent information about some digital objects such as plan specification as well as physical objects such as occurrence of a process (that may or may not be proceeding according to the plan). While that is the case, there is still a need for the IOF Core to provide further guidance on how they should be related and how to scale to various types of digital and physical objects. To address the issues of relations between physical and digital objects, this paper provides an overview of approaches from recent literature and efforts by the authors and collaborators. It then illustrates in more detail four approaches that are more aligned with the Basic Formal Ontology (BFO), on which the IOF Core is based. General and use case specific requirements are used to arrive at our initial observations. Finally, we discuss a plan for further analysis.
Simultaneous Prediction of Hand Gestures, Handedness, and Hand Keypoints Using Thermal Images

Hand gesture detection is a well-explored area in computer vision with applications in various forms of human–computer interactions. In this work, we propose a technique for simultaneous hand gesture classification, handedness detection, and hand keypoints localization using thermal data captured by an infrared camera. Our method uses a novel deep multi-task learning architecture that includes shared encoder–decoder layers followed by three branches dedicated for each mentioned task. We performed extensive experimental validation of our model on an in-house dataset consisting of 24 users’ data. The results confirm higher than 98% accuracy for gesture classification, handedness detection, and fingertips localization, and more than 91% accuracy for wrist points localization.
Konsep Pembelajaran Mahasiswa Dalam Memahami Algoritma Melalui Komputer Pemograman

A programing algorithm means a number of activities to complate a process. Its done according to the procedure. Algorithm can be basis for the development of computer programs. The core of the science is algorithms.. The literary based on data metodology found in various refrences. The goal is tho get help students recognize and faciliate student understanding theeby increasing motivation in learning.
Immerscape: Supporting the Creation of Immersive Soundscapes by Users in Cultural Heritage Contexts

In this paper, we introduce Immerscape, an interactive tool for composing immersive soundscapes. Immerscape can be used to support the study and creation of historical soundscapes, enhancing the experience for visitors at culture and heritage sites. The tool allows non-technical users to compose immersive auditory scenes, by simply combining different sound recordings that simulate moving sound sources, as well as sound sources positioned in different locations in the scene. A preliminary evaluation of the tool’s usability and acceptance has been conducted, involving domain users and other volunteers.
Reducing Human Effort in Keyphrase-Based Human-in-the-Loop Topic Models: A Method for Keyphrase Recommendations

Human-in-the-loop topic modeling (HLTM) empowers users to modify topic models and enhance their quality, by enabling them to directly refine the model. Prior studies have made significant strides in this area, specifically keyphrase-based refinements. However, the challenge is selecting suitable keyphrases from a large pool of them. To address this issue, we present a novel method for keyphrase recommendation that capitalizes on the connections between document-topic and document-keyphrases associations. The objective is to assist users of keyphrase-based HLTM by offering effective refinement recommendations. To evaluate the effectiveness in reducing human effort, we compared it with baseline and all-keyphrase approaches, while also evaluating F1 scores across multiple levels of human effort. Our method achieves comparable performance with minimal human effort, akin to ideal situations where human effort is maximized. Furthermore, our method surpasses the baseline and the approach of utilizing all keyphrases at the same level of human effort, demonstrating superior performance.
STUDENTS’ DIFFICULTIES IN SPEAKING ENGLISH AT THE SECOND GRADE OF MTs NEGERI 1 BUNGO

This research sought to identify students' difficulties in speaking English and the root causes of those difficulties. This research was carried out in MTsN 1 Bungo. The research design utilizes qualitative descriptive methodology. This investigation focuses on the second-grade MTsN 1 Bungo students. The data for this research were gathered through observation and interviews. The researcher determined, based on the findings and discussion, that speaking English presents and is accompanied by a number of difficulties and causes of difficulty. The linguistic difficulties the student encountered when speaking English were a lack of pronunciation, vocabulary, and grammar. When speaking English, students struggle with a lack of confidence, shyness, and apprehensiveness. pronunciation difficulties predominate among difficulties. The majority of students stated that they are afraid of pronouncing English words incorrectly. Student difficulties are caused by a fear of making a blunder.
INVESTIGATING HOW INCLUSIVE LEADERSHIP IMPACTS TEACHERS' INNOVATIVE WORK BEHAVIOUR

The aim of this study is to examine how the leadership style of department heads or principals, which emphasizes inclusivity, influences teachers' innovative work performance and teaching pedagogical skills. Researcher used the quantitative method; data were gathered applying for survey research design through Google form. There were 336 teachers from schools, colleges and universities of Baluchistan and Sindh. Data was used hierarchical regression and descriptive analysis; Researcher confirmed the positive association among inclusive leadership IL and innovative work behavior IWB.
A Deep Anomaly Detection System for IoT-Based Smart Buildings

In recent years, technological advancements in sensor, communication, and data storage technologies have led to the increasingly widespread use of smart devices in different types of buildings, such as residential homes, offices, and industrial installations. The main benefit of using these devices is the possibility of enhancing different crucial aspects of life within these buildings, including energy efficiency, safety, health, and occupant comfort. In particular, the fast progress in the field of the Internet of Things has yielded exponential growth in the number of connected smart devices and, consequently, increased the volume of data generated and exchanged. However, traditional Cloud-Computing platforms have exhibited limitations in their capacity to handle and process the continuous data exchange, leading to the rise of new computing paradigms, such as Edge Computing and Fog Computing. In this new complex scenario, advanced Artificial Intelligence and Machine Learning can play a key role in analyzing the generated data and predicting unexpected or anomalous events, allowing for quickly setting up effective responses against these unexpected events. To the best of our knowledge, current literature lacks Deep-Learning-based approaches specifically devised for guaranteeing safety in IoT-Based Smart Buildings. For this reason, we adopt an unsupervised neural architecture for detecting anomalies, such as faults, fires, theft attempts, and more, in such contexts. In more detail, in our proposal, data from a sensor network are processed by a Sparse U-Net neural model. The proposed approach is lightweight, making it suitable for deployment on the edge nodes of the network, and it does not require a pre-labeled training dataset. Experimental results conducted on a real-world case study demonstrate the effectiveness of the developed solution.
Use of Keypoint-RCNN and YOLOv7 for Capturing Biomechanics and Barbell Trajectory in Weightlifting

Weightlifting is a demanding sport requiring power, flexibility, and the correct technique. The snatch and the clean and jerk involve the fast lifting of weight to an overhead position. Incorrect technique or posture may lead to inefficient lifts or even injury. This paper presents a new framework for biomechanics analysis and barbell trajectory tracking in weightlifting by leveraging the capabilities of Keypoint-RCNN and YOLOv7 deep learning models. The proposed framework extracts skeletal information from weightlifting video sequences using a pre-trained Keypoint-RCNN model for human pose estimation and a custom YOLOv7 model to detect and track barbell trajectories. The Keypoint-RCNN model estimates human pose without manual annotation or specialised apparatus, while the YOLOv7 model provides real-time, non-intrusive barbell tracking. The efficacy of barbell trajectory tracking with YOLOv7 on a public weightlifting dataset of 973 images (70–30 train-test ratio) was evaluated, obtaining high precision (0.9214), recall (0.9678), and mAP@0.5 of 0.9792 and mAP@0.5:0.95 of 0.7765, indicating the applicability of this model to weight training applications. The proposed framework presents a cost-effective, user-friendly, and easily accessible alternative to conventional motion capture and analysis systems, making it accessible for lifters of all skill levels and training environments.
Mapping the global free expression landscape using machine learning

Abstract Freedom of expression is a core human right, yet the forces that seek to suppress it have intensified, increasing the need to develop tools that can measure the rates of freedom globally. In this study, we propose a novel freedom of expression index to gain a nuanced and data-led understanding of the level of censorship across the globe. For this, we used an unsupervised, probabilistic machine learning method, to model the status of the free expression landscape. This index seeks to provide legislators and other policymakers, activists and governments, and non-governmental and intergovernmental organisations, with tools to better inform policy or action decisions. The global nature of the proposed index also means it can become a vital resource/tool for engagement with international and supranational bodies.
FACTORS INFLUENCING STUDENTS’ SPEAKING ANXIETY AT ONE PUBLIC UNIVERSITY IN JAMBI: PERSONALITY TRAITS, MOTIVATION, AND FAMILY ENVIRONMENT ASPECTS

This research aimed to describe factors that influence students’ speaking anxiety and to explore the strategies used by the students to overcome their anxiety. The site of this research was at one public university in Jambi. The researcher utilised purposive sampling technique in selecting the participants. There were 12 participants of this research which including 7th semester students, 5th semester students, and 3rd semester students who have passed speaking classes. This research employed qualitative study with case study approach in one English teacher study program. In collecting the data, the researcher used interview and documentation as the data collection.&#x0D; The results of this research indicated that there were still several factors faced by the students which influenced their speaking anxiety. Those factors were afraid, shy, unconfident, overthinking, nervous, mood, low motivation, and family support. The most factors felt by the students were overthinking and unconfident. This research also pointed out that the participants used several strategies to overcome their anxiety in speaking. There were 9 strategies employed by the participants including taking a deep breathe, practicing, being confident, calming down, studying hard, being well-prepared, being alone, discussing with friends, and getting motivation from friends.
Comparison of Multiple Book Recommendation Algorithms After Analysis of User Characteristics Using Big Data

ABSTRACTThrough big data analysis of borrowing information, it is possible to find the characteristics of different users. This paper applied K-means clustering to classify users. User feature vectors were extracted, and several algorithms were utilized to recommend books to different users. The hybrid algorithm achieved a precision of 96.29%, a recall rate of 92.13%, and an score of 94.16%, significantly higher than other algorithms. The findings prove that it is feasible to discover the characteristics of different users through big data analysis for book recommendation, and the hybrid algorithm performs the best.KEYWORDS: clustering analysisuser characteristicsbook recommendationrecommendation algorithm Disclosure statementNo potential conflict of interest was reported by the author(s).
EFL STUDENTS’ PERCEPTION ON THE TEXTBOOK SELECTED BY THEIR COURSE INSTRUCTOR

Students perception on selected textbook they use can be a meaningful information in helping them achieve their learning goal and generally in helping the teacher in designing the course. This paper was aimed at describing EFL students’ perception on a selected textbook entitled Second Language Acquisition: An Introduction written by Muriel Saville-Troike published in 2012. The participants of this descriptive study were 40 EFL students enrolled in Second Language Acquisition course in academic year 2019/2020 in a public university in Jambi, Indonesia. The data were gathered through questionnaire response and WhatsApp discussion. It was revealed that majority of the students perceive that the book is informative, useful, and needed but difficult to understand. The students suggested to develop additional simple material to the book which consist of brief explanation and example, easy to understand words, and have interesting and eye-catching design. This information could be used to design and develop additional course material.