Reviewerly/exHarmony huggingface dataset:
Evaluating the influence of interaction technology on procedural learning using Virtual Reality

Within the context of industry 4.0, this paper studies the influence of interaction technology (Vive controller and Knuckles) on manufacturing assembly procedural training using Virtual Reality. To do so, an experiment with 24 volunteers have been conducted and these participants have been separated in two groups: one using Vive controller and the other using Knuckles. Our conclusions are based on two indicators: Time to realize all tasks and the number of manipulations. This study shows that, after get used to, volunteers using Knuckles are faster than the other group but for some very delicate tasks, they need more manipulations to succeed.
유헬스케어 서비스 사용자의 만족도와 재사용의도 영향 요인에 대한 연구: 개인용 의료정보 애플리케이션 사용자의 반응을 중심으로

Purpose The purpose of this study is to analyze the causal relationship between user satisfaction, expected satisfaction, quality of service, perceived value, and expertise that should be emphasized in personalized medical information services for the development of personalized medical information services based on big data analysis and the spread of their demand.Design/methodology/approach This study established research models and hypotheses on the basis of the theory of reuse intent, and applied the PLS methodology for analysis, the factors that make it applicable to personalized medical services in the theory of service quality and satisfaction.Findings According to the empirical analysis result, this study confirmed that it can be seen that the expertise, perceived value, and quality of medical services did not directly affect the user's intention to reuse, but formed a direct causal relationship through variables such as whether they met expectations.
Algorithms for normalized multiple sequence alignments

Sequence alignment supports numerous tasks in bioinformatics, natural language processing, pattern recognition, social sciences, and others fields. While the alignment of two sequences may be performed swiftly in many applications, the simultaneous alignment of multiple sequences proved to be naturally more intricate. Although most multiple sequence alignment (MSA) formulations are NP-hard, several approaches have been developed, as they can outperform pairwise alignment methods or are necessary for some applications. Taking into account not only similarities but also the lengths of the compared sequences (i.e. normalization) can provide better alignment results than both unnormalized or post-normalized approaches. While some normalized methods have been developed for pairwise sequence alignment, none have been proposed for MSA. This work is a first effort towards the development of normalized methods for MSA. We discuss multiple aspects of normalized multiple sequence alignment (NMSA). We define three new criteria for computing normalized scores when aligning multiple sequences, showing the NP-hardness and exact algorithms for solving the NMSA using those criteria. In addition, we provide approximation algorithms for MSA and NMSA for some classes of scoring matrices.
APPLICATION OF DIFFRACTIVE OPTICAL ELEMENTS FOR OPTICAL-ELECTRONIC DIMENSIONAL INSPECTION SYSTEMS

The work is devoted to the application of diffractive optical elements in systems using the structured illumination method to the geometric parameters inspection of industrial articles. The objects of inspection in these systems are: weapon barrels, fuel pellets, fuel elements, spacer grids, ceramic ring insulators. The used diffractive optical elements are computer-synthesized holograms that focus laser radiation into geometric shapes, the configuration of which is optimally combined with the inspected objects shape.
Determining the Significant Part in an Electrical appliance using Fuzzy Cognitive Map and to Minimize the Cost in the Creation of a Circuit

There are many parts in an electrical appliance, each performing various operations. In particular, if a part fails, then the appliance will not be able to carry out its operations in a better way. Thus, to determine the significant part, fuzzy cognitive map can be used. However, it is noticed that in the washing machine, the outcome of the experiment lists all the parts to play an equal role. Therefore, in order to reduce the cost, the circuit must be minimized which can be done using a Java script software. Using the above circuit in the washing machine, it is easy to identify the fault in the part even before it gets damaged.
Pathologies in priors and inference for Bayesian transformers.

In recent years, the transformer has established itself as a workhorse in many applications ranging from natural language processing to reinforcement learning. Similarly, Bayesian deep learning has become the gold-standard for uncertainty estimation in safety-critical applications, where robustness and calibration are crucial. Surprisingly, no successful attempts to improve transformer models in terms of predictive uncertainty using Bayesian inference exist. In this work, we study this curiously underpopulated area of Bayesian transformers. We find that weight-space inference in transformers does not work well, regardless of the approximate posterior. We also find that the prior is at least partially at fault, but that it is very hard to find well-specified weight priors for these models. We hypothesize that these problems stem from the complexity of obtaining a meaningful mapping from weight-space to function-space distributions in the transformer. Therefore, moving closer to function-space, we propose a novel method based on the implicit reparameterization of the Dirichlet distribution to apply variational inference directly to the attention weights. We find that this proposed method performs competitively with our baselines.
Autonomous Human Recognition System for Various Challenging Postures in Various Postures in Various Environments

This paper introduces a deep learning method by using YOLOv3 as a medium to train human data samples and verify the presence of humans. The existing automated vehicles are designed and created for improving people’s everyday life. However, they have the limitation in term of safety technologies such as slow human detection speed and inaccuracy and unstable sensing capability [1]. Therefore, there is a need to improvise the current safety technologies by reducing the span time for recognition and more accurate data detection. This enhances the reliability of the system which will able to lower the accidence rate. This project aims to develop a reliable system, YOLOv3 that can recognize the human being with different postures indoors and outdoors environments. Besides, to evaluate the performance of YOLOv3 toward human detection in the image, video, and real-time. Lastly, to determine the best training last weight in performing human recognition. Google Colaboratory is used as a core training environment. It offers powerful Nvidia k80 and T4 with GPU memory 12 GB and 16 GB respectively that provided rapid training speed but there have two limitations which are maximum execution time is only 12 hours and maximum idle time is only 90 minutes. In order to detect the amount of light intensity surrounds the environment, the Arduino Uno R3 with LDR photosensor is used. As a result, the overall accuracy of the YOLOv3 human recognition model has achieved above 88 percent in bright environment. However, the system does not run efficiently when it is dark. In the future, more data could be used in the training to increase the accuracy of the YOLOv3 model. Further possible attempts also can include the use of an IR camera or a Learning-to-see-in-the-dark model with YOLOv3 to solve the problem of recognizing low-light images.
E-DIAGNOSIS PENYAKIT MATA MENERAPKAN METODE NAIVE BAYES

This study aims to develop an e-diagnosis application for eye diseases using the naive bayes method. The reasons for choosing this method are because it is simple, fast and has high accuracy. The expert system development method used is the Expert System Development Life Cycle (ESDLC). The steps that must be carried out in the ESDLC method are assessment, knowledge acquisition, design, testing and documentation. There are 14 types of eys diseases discussed, including : macular degenaration, cataracts, optic neuristics, open angle glaucoma, angle closed glaucoma, graves, keratitis, presbyopia, retinal ablation, acute iridocyclics, xerophthalmania, orbital cellulitis, dacryocystitis and piteregium. Each disease has symptoms, there are several diseases with the same symptoms. This e diagnosis system for eye diseases can help people to find out what eye diseases are being experienced. Implementing the Naive Bayes method can help writers build a more structured e diagnosis system for eye diseases
Automated Chinese Essay Scoring using Pre-Trained Language Models

Automated Essay Scoring (AES) aims to assign a proper score to an essay written by a given prompt, which is a significant application of Natural Language Processing (NLP) in the education area. In this work, we focus on solving the Chinese AES problem by Pre-trained Language Models (PLMs) including state-of-the-art PLMs BERT and ERNIE. A Chinese essay dataset has been built up in this work, by which we conduct extensive AES experiments. Our PLMs-based AES models acquire 68.70% in Quadratic Weighted Kappa (QWK), which outperform classic feature-based linear regression AES model. The results show that our methods effectively alleviate the dependence on manual features and improve the portability of AES models. Furthermore, we acquire well-performed AES models with a limited scale of the dataset, which solves the lack of datasets in Chinese AES.
ANALISA DAN PERANCANGAN SISTEM INFORMASI GEOGRAFIS PENGELOLAAN PAJAK REKLAME PADA BADAN PENGELOLAAN KEUANGAN DAN ASET DAERAH (BPKAD) KABUPATEN JEPARA

The problem faced by the Regional Financial and Asset Management Agency (BPKAD) of Jepara Regency is the number of billboards in Jepara Regency, but BPKAD has difficulty monitoring the location of the billboards that have been installed because the parties concerned do not report the installation of billboards. The purpose of this report is to analyze and design a geographic information system for advertising tax management at BPKAD, Jepara Regency. The material in the research is data that will be input to the system, namely data from the advertisement tax object, data on the location of the billboard point. In the system design that the author proposes, the system design is made using UML (Unified Modeling Language), namely Usecase Diagrams, Class Diagrams, Activity Diagrams and Sequence Diagrams. The methodology used to design the system is the RAD (Rapid Application Development) method at the design stage using the RAD method which is divided into three stages, namely Requirement Planning, Design Workshop, and Implementation. The results of this study are in the form of reports on the analysis and design of the geographic information system to display all tax object locations that have been inputted by the officer, the benefits of the analysis and design of the Geographic Information System for Advertising Tax Management at BPKAD Jepara. This system can assist in managing the advertisement tax. those in Jepara tax can more easily take care of advertising taxes at home
Linguistic Loans from Italian into Japanese: focusing on the Meiji Period

The history of cultural exchanges between Japan and Italy can be traced back to the second half of the 16th century. However, it was only in the Meiji era that Japanese and Italian began to come into contact, and that gairaigo (loanwords) of Italian origin began to emerge in Japanese.Gairaigo of Italian origin can refer both to Italian words borrowed directly from Italian, and to words of Italian origin borrowed indirectly through other languages. The aim of this study is to examine the gairaigo of Italian origin that entered Japanese during the Meiji period, in order to shed light on their characteristics and their borrowing route.The corpus for this study has been compiled by selecting the words with their earliest recorded use in the Meiji era, drawing from the general lists of Italian loanwords in Koura (1997) and Calvetti (2003). In order to find clues to their route, I examined the first Italian-Japanese dictionary, the Futsu-I-Wa sangoku tsūgo by Magaki Yukinaga, published in 1876, then carried out an analysis of the corpus from a phonetic perspective.I also traced the history of four words, selected to represent the fields in which the influence of Italian is stronger: “opera”, “madonna”, “chiaroscuro”, and “macaroni”.The results of this study suggest that these Meiji loanwords entered the Japanese vocabulary through an indirect route and underline the importance of Italian as an international cultural language in the field of the arts, and especially of music.
Penerapan model pembelajaran Snowball Throwing untuk meningkatkan hasil belajaran pada siswa kelas II SDN 01 Kalirejo Talun

The scope of elementary Indonesian subjects includes language and literary skills, namely listening, speaking, reading and writing (Khasanah, 2015). For this reason, the purpose of this research is the application of thelearning model snowball throwing to improve learning outcomes for second grade students at SDN 01 Kalirejo Talun. This type of research is Classroom Action Research (CAR). The subjects in this study were 19th graders of SDN 01 Kalirejo Talun. Data collection methods used in this study are tests, observations, documentation and interviews. The data analysis technique used is descriptive both qualitatively and quantitatively. For the success criteria in this study, the indicator of success in this study is individual learning completeness if the proportion of students' correct answers is more than the predetermined KKM and for classical learning completeness if at least 85% of students score above the predetermined KKM, which is 75. The results of In this study, cycle 1 shows that the number of students who have reached the predetermined KKM is 14 students with a percentage of 78.95%. Meanwhile, the results of cycle 2 show that the number of students who have reached the predetermined KKM is 17 students with a percentage of 89.57%.
PARADIGM SHIFT IN HIGHER EDUCATION PEDAGOGIES ECOSYSTEM IN 4IR ERA

A. Chopra1, E. Zabalawi1, A.R. Chopra2 1Amity University Dubai (UNITED ARAB EMIRATES) 2WISDOM Banasthali University (INDIA)
Role of Database Marketing in Improving Quality of Service in Jordanian Private Hospitals

Current study aims to determine the role of database marketing in improving quality of service in Jordanian private hospitals. The study&amp;#39;s population is consisted of marketing managers only or their deputies in the Jordanian private hospitals which contains (69) hospitals. Online questionnaire was distributed over a random sample amounting (59) managers, (51) questionnaires were collected, that is (86.44%) of the total sample. The study results indicated that Jordanian private hospitals use database marketing in improving quality of Service in Jordanian Private Hospitals. There is no difference in the role of database marketing in improving quality of service in Jordanian private hospitals according to the managers&amp;rsquo; educational level. There is a difference in the role of database marketing in improving quality of service in Jordanian private hospitals according to the managers&amp;rsquo; experience.
Machine Learning for Compositional Data Analysis in Support of the Decision Making Process

In recent years, the development of digital technologies brings a lot of changes in the way of operating, leading, and the working processes in companies. Accordingly, advanced technologies such as Artificial Intelligent, Big Data, the Internet of things, etc., are widely applied to aggregate, transform, and analyze data, thereby inferring meaningful information and making important decisions. As a branch of Artificial Intelligent, Machine Learning is a method of data analysis that constitutes analytical model-building automation. The main objectives of Machine Learning are designing algorithms that can learn from data, identify patterns, and adapt them without human intervention. This chapter will summarize the researches related to applying Machine Learning to compositional data, including principal component analysis, clustering, classification, and regression. Compositional data is a special type of data, well-defined on the Simplex space. Since it carries only relative information, the traditional methods cannot be applied directly to this type of data without adapting or transforming data into normal form. A transformation method based on Dirichlet density estimation to transform compositional data into real data to apply in anomaly detection using Support Vector Data Description is also introduced together with a simulation example at the end of the chapter.
Curvature Aware Motion Planning with Closed-Loop Rapidly-exploring Random Trees.

The road's geometry strongly influences the path planner's performance, critical for autonomous navigation in high-speed dynamic scenarios (e.g., highways). Hence, this paper introduces the Curvature-aware Rapidly-exploring Random Trees (CA-CL-RRT), whose planning performance is invariant to the road's geometry. We propose a transformation strategy that allows us to plan on a virtual straightened road and then convert the planned motion to the curved road. It is shown that the proposed approach substantially improves path planning performance on curved roads as compared to prior RRT-based path planners. Moreover, the proposed CA-CL-RRT is combined with a Local Model Predictive Contour Controller (LMPCC) for path tracking while ensuring collision avoidance through constraint satisfaction. We present quantitative and qualitative performance results in two navigation scenarios: dynamic collision avoidance and structured highway driving. The results demonstrate that our proposed navigation framework improves the path quality on curved highway roads and collision avoidance with dynamic obstacles.
OCR based Image Text to Speech Conversion using Python

Optical Character Recognition (OCR Optical Character Recognition (OCR) assumes a significant part in report picture handling. Acknowledgment of characters in a shrewd manner is acquiring significance in the advanced days, as gigantic heaps of information is produced, and it should be handled and controlled. OCR disposes of the need of retyping if there should arise an occurrence of deletion of a significant advanced record unintentionally, it stimulates computerized look, empowers quicker content editing, sets aside the extra room with the utilization of proficient calculation. Availability of OCR to the outwardly impeded is an incredible advancement, Where clients can examine books, magazines, approaching sends or different projects. OCR can likewise be combined with a voice-over utility, or voice synthesizer, that peruses out the text perceived optically by the product. OCR likewise has its own bottlenecks. It may not perceive complex text, numerical factors, manually written contents. Very good quality OCR utilities are utilized in regions where required, yet it accompanies an extra computational expense.
Syntactic Requirements for Well-defined Hybrid Probabilistic Logic Programs.

Hybrid probabilistic logic programs can represent several scenarios thanks to the expressivity of Logic Programming extended with facts representing discrete and continuous distributions. The semantics for this type of programs is crucial since it ensures that a probability can be assigned to every query. Here, following one recent semantics proposal, we illustrate a concrete syntax, and we analyse the syntactic requirements needed to preserve the well-definedness.
THE EFFECTIVENESS OF USING ARCS (ATTENTION,RELEVANCE, CONFIDENCE, SATISFACTION)MOTIVATION STRATEGY TOWARD STUDENTS’ WRITINGRECOUNT ACHIEVEMENT AT THE FIRST GRADE OF MADARUL HUDA

ABSTRACTMu’thi, Fina Ismatul. Students Registered Number. 17203153031.2019. TheEffectiveness of Using ARCS (Attention, Relevance, Confidence,Satisfaction) Motivation Strategy toward Students’ Writing RecountAchievement at the First Grade of MA Darul Huda. Sarjana Thesis. EnglishEducation Department. Faculty of Tarbiyah and Teacher Training. StateIslamic Institute (IAIN) of Tulungagung. Advisor: Dr. H. Nursamsu, S.Pd.I.,M.Pd.Keyword: Effectiveness, ARCS Motivation Strategy, Recount TextWriting is considered as the most difficult skill for language learnerto master. Language learners need motivation to get the point of the lesson.One of strategy in motivation is ARCS model. This motivation strategy canbe used the teacher to teach English lesson especially in writing. In thisstudy, ARCS motivation strategy used in teaching writing, so the teachergive motivation and applies step by step from this strategy. For the first, theteacher gives an attention to students. Then, the teacher gives relevancebetween the materials of lesson with the fact in daily life. This motivationstrategy is also to make the students feel confident with themselves. Finally,they get satisfaction; it is the result of their entire goal. This strategy willhelp the students to learn English especially in writing recount text.The formulation of research problem: is there any significant effectusing ARCS motivation strategy toward students’ writing recountachievement at the first grade of MA Darul Huda?. Based on theformulation of research problem, the purpose of this study was toinvestigate the effectiveness of using ARCS motivation strategy towardstudents’ achievement at the first grade in writing recount text.This study used quantitative approach with pre-experimental design.The participant of the study comprised 20 students from X MIA. Theinstrument of this research is test. After getting the data of students’ scoreeither from pretest and posttest, the data was analyzed by using PairedSample T-test in IBM SPSS Statistic 22.After get a treatment, the score of the students’ increased. It can beseen from the mean of the score that the mean of pretest is 71 and the meanof posttest is 82. The significant value is lower than 0.05. The significantlevel is 0.000, so (Ho) is rejected and (Ha) is accepted. In other words,ARCS Motivation Strategy is effective to teach writing recount text to thestudent as MA level. The students will be more interested to learningEnglish by using this strategy, because the teacher give motivate to them.The researcher recommended to use ARCS Motivation Strategy in writingrecount text.
DISASTER AWARENESS” PERAN PERGURUAN TINGGI DALAM MEMBANGUN BUDAYA MITIGASI BENCANA DALAM MEMBANGUN PERADABAN YANG ADAPTIF DENGAN BENCANA

Indonesia, as a nation sitting on the Pacific Ring of Fire has a potential natural disaster that can occur anytime and hard to predict. Therefore, the Indonesian government has made serious efforts of reducing the impact on disaster loss through a disaster-related curriculum in high education. The aim of this article is to find out university’s role in disaster risk reduction efforts through formal education sector. This article was arranged through library research. The basic, intermediate and advance knowledge of disaster risk management reduction through formal education is a necessary part of systematic efforts of increasing student’s awareness, knowledge and skill capability to face the disaster. Later on the Student are becoming agents of change, in turn teach their communities and involve effectively in order to construct the culture of disaster preparedness. Therefore, these efforts will support Indonesian Disaster Risk Reduction (DRR) program so that the damaged due to disaster can be prevented or minimized. Trisakti of Institute Transportation and Logistics already set up for disaster-related curriculum as part of disaster awareness development.