Reviewerly/exHarmony huggingface dataset:
Practical Provenance in Astronomy

Recently the International Virtual Observatory Alliance (IVOA) released a standard to structure provenance metadata, and several implementations are in development in order to capture, store, access and visualize the provenance of astronomy data products. This BoF will be focused on practical needs for provenance in astronomy. A growing number of projects express the requirement to propose FAIR data (Findable, Accessible, Interoperable and Reusable) and thus manage provenance information to ensure the quality, reliability and trustworthiness of this data. The concepts are in place, but now, applied specifications and practical tools are needed to answer concrete use cases. During this session we discussed which strategies are considered by projects (observatories or data providers) to capture provenance in their context and how a end-user might query the provenance information to enhance her/his data selection and retrieval. The objective was to identify the development of tools and formats now needed to make provenance more practical needed to increase provenance take-up in the astronomical domain.
User Evaluation to Measure the Perception of Similarity Measures in Artworks

Similarity measures do not typically capture subjective elements of perception of similarity. Our research contributes an experimental methodology for validating and learning similarity computation algorithms against human perceptions of similarity in subjective domains like Art and emotions. In this paper, we explain the first experiment to check our hypotheses and methodology. We have obtained promising results that explain the differences between users profiles and their perception of similarity between artworks and how to combine local similarity functions to be able to compute similarity measures reflecting users’ perception.
Aplikasi Monitoring Persediaan Barang Berbasis Web Pada Koperasi Pegawai Logistik Dolog Semarang Menggunakan Barcode Reader

Stock reports on purchases and sales of a period. useful for helping employees to assess the amount of inequality in the flow of purchases, monitor stock / inventory of goods, and provide reports both purchase reports, sales reports, stock condition reports, and profit / profit reports to management to determine further business policies The process of recording transactions in a conventional or paper-based manner is identical with several weaknesses, namely easily damaged, difficult / long when looking for stored data, difficult / long when it comes to generating reports. These weaknesses can be corrected by implementing computer-based monitoring applications. If the monitoring application is planned/made properly, the computer-based information system is relatively safer. The model to be developed refers to the Research and Development (R&amp;D) model from Borg and Gall and the tools used and the tools used to design the system are use case diagrams, sequence diagrams, activity diagrams, and class diagrams. while the implementation of making stock/inventory monitoring applications is done with PHP web-based programming and databases using MySQL. This application can help and get more accurate information about the stock data of goods that have run out.
Upaya Guru PAI Menciptakan Suasana Pembelajaran yang Efektif

In learning students often experience boredom, teachers must be able to create an effective learning atmosphere for students with various methods. Schools as places of learning must also be able to create a good atmosphere especially in the classroom. However, sometimes in teaching and learning activities in schools, there are often problems related to learning experienced by these students. The problem is influenced by internal factors (which come from within the students themselves) and also external factors (which come from outside). One of the internal factors is the boredom experienced by students while studying. A teacher who can create an effective learning atmosphere for students in order to achieve learning. The essence of effective learning is a teaching and learning process that is not only focused on the results achieved by students, but how an effective learning process is able to provide good understanding, intelligence, perseverance, and provide behavior and apply it in their lives.
Application of Integral Invariants to Apictorial Jigsaw Puzzle Assembly

We present a method for the automatic assembly of apictorial jigsaw puzzles. This method relies on integral area invariants for shape matching and an optimization process to aggregate shape matches into a final puzzle assembly. Assumptions about individual piece shape or arrangement are not necessary. We illustrate our method by solving example puzzles of various shapes and sizes.
Information technology of visualization for technological processes for research modes of functioning of complex technological systems

The development of a mathematical model of a technical system based on the means of discrete-continuous networks and taking into account the interaction with a multimedia platform is presented. The efficiency of the process for visualizing the functioning of the complex technical system is increased by implementing the interaction of the modeling environment with the Unity platform in the feedback mode. The experiments linked to the integration of the DC-Net simulation software environment with the Unity cross-platform development environment are implemented. An example of developing the model of a technical system in the DC-Net environment and an example of developing a process for visualizing the functioning of a corresponding technical system based on the Unity platform are presented. The fundamental suitability of using the integration of various information technologies linked with various software environments has been confirmed.
Multi-modal Program Inference: a Marriage of Pre-trained Language Models and Component-based Synthesis

Multi-modal program synthesis refers to the task of synthesizing programs (code) from their specification given in different forms, such as a combination of natural language and examples. Examples provide a precise but incomplete specification, and natural language provides an ambiguous but more complete task description. Machine-learned pre-trained models (PTMs) are adept at handling ambiguous natural language, but struggle with generating syntactically and semantically precise code. Program synthesis techniques can generate correct code, often even from incomplete but precise specifications, such as examples, but they are unable to work with the ambiguity of natural languages. We present an approach that combines PTMs with component-based synthesis (CBS): PTMs are used to generate candidates programs from the natural language description of the task, which are then used to guide the CBS procedure to find the program that matches the precise examples-based specification. We use our combination approach to instantiate multi-modal synthesis systems for two programming domains: the domain of regular expressions and the domain of CSS selectors. Our evaluation demonstrates the effectiveness of our domain-agnostic approach in comparison to a state-of-the-art specialized system, and the generality of our approach in providing multi-modal program synthesis from natural language and examples in different programming domains.
PEMBELAJARAN PERCAKAPAN BERBAHASA INGGRIS UNTUK SISWA SEKOLAH MELALUI SIARAN RADIO KARYSMA FM PADA PANDEMI COVID-19

Learning in the Covid-19 pandemic has changed offline learning become online learning. Online learning has several problems for teachers, students, and parents. The covid-19 pandemic in 2020 has had a significant impact in all fields, especially in the education field. Learning English daily conversation through Karysma FM Radio aims to teach students daily conversation and motivate students to deepen their understanding of English subjects outside of school time. The methodology applied in the implementation of community service is observation and the implementing teaching process. The conclusions of learning English daily conversation through Karysma FM Radio are 1) Teaching English daily conversation with students at Karysma FM Radio requires creativity and English language skills; 2) Knowing the psychology of students, it is necessary to invite students to be willing to speak in English daily conversation considering that English subjects are lessons outside of school; 3) The obstacles in teaching English daily conversation with students at Radio Karysma FM are preparation of time and teaching materials
The Effectiveness of Augmented Reality for English (AR4E) in Vocabulary Learning among Primary 2 Pupils

This paper presents and discusses a part of an action research conducted to evaluate the effectiveness of Augmented Reality for English (AR4E) in vocabulary learning among Primary 2 pupils as indicated in the results of the pre-test, post-test and observation checklist. An action research was employed. However, this paper reports on the pre-test, post-test and observation checklist conducted in the observation, evaluation and reflection stages only. Purposive sampling was employed as the participants were of the same proficiency level in which it was carried out with 14 below average Primary 2 pupils in SKTEN. Two data collection instruments which were pre-test, post-test and observation checklist were analysed statistically and thematically. The pre-test and post-test were analysed using SPSS Version 25 and it showed a higher mean score in the post-test and this is supported by the findings obtained through the given themes of observation. The results reflected that the implementation of AR4E has shown a significant improvement in learner’s vocabulary learning. In addition, the findings have also raised the concern regarding the impact of AR4E in encouraging fun learning, collaborative learning and providing the learners with new language learning experience. Accordingly, the use of AR4E is recommended in vocabulary teaching and learning for English. Finally, the researcher suggests future research can be carried out taking into account differentiated learning tasks in AR4E, larger target users and different language skills to be integrated in AR4E.
Creating Guidance for Canadian Dataverse Curators: Portage Network’s Dataverse Curation Guide

Purpose: This paper introduces the Portage Network’s Dataverse Curation Guide and the new bilingual curation framework developed to support it. Brief Description: Canadian academic institutions and national organizations have been building infrastructure, staffing, and programming to support research data management. Amidst this work, a notable gap emerged between requirements for data curation in general repositories like Dataverse and the requisite workflows and guidance materials needed by curators to meet them. In response, Portage, a national network of data experts, organized a working group to develop a Dataverse curation guide built upon the Data Curation Network’s CURATED workflow. To create a bilingual resource, the original CURATE(D) acronym was modified to CURATION—which has the same meaning in both French and English—and steps were augmented with Dataverse-specific guidance and mapped to three conceptualized levels of curation to assist curators in prioritizing curation actions. Methods: An environmental scan of relevant deposit and curation guidance materials from Canadian and international institutions identified the need for a comprehensive Dataverse Curation Guide, as most existing resources were either depositor-focused or contained only partial workflows. The resulting Guide synthesized these guidance materials into the CURATION steps and mapped actions to various theoretical levels of data repository services and levels of curation. Resources: The following documents are supplemental to the Dataverse Curation Guide: the Portage Dataverse North Metadata Best Practices Guide, the Scholars Portal Dataverse Guide, and the Data Curation Network CURATED Workflow and Data Curation Primers.
Modular coinduction up-to for higher-order languages via first-order transition systems

The bisimulation proof method can be enhanced by employing `bisimulations up-to' techniques. A comprehensive theory of such enhancements has been developed for first-order (i.e., CCS-like) labelled transition systems (LTSs) and bisimilarity, based on abstract fixed-point theory and compatible functions. We transport this theory onto languages whose bisimilarity and LTS go beyond those of first-order models. The approach consists in exhibiting fully abstract translations of the more sophisticated LTSs and bisimilarities onto the first-order ones. This allows us to reuse directly the large corpus of up-to techniques that are available on first-order LTSs. The only ingredient that has to be manually supplied is the compatibility of basic up-to techniques that are specific to the new languages. We investigate the method on the pi-calculus, the lambda-calculus, and a (call-by-value) lambda-calculus with references.
DETEKSI LEMBAR JAWABAN KOMPUTER MENGGUNAKAN OMR (OPTICAL MARK RECOGNITION) DI MTS NURUL IMAN

Conventional exams or manual exams were implemented decades ago and are still used today. This type of test uses a writing instrument as a test medium, namely the test is carried out in the form of general stationery such as paper, pencil, and pen, the questions and answers to the test are written by hand. One way to assess the success of the teaching process in schools is to carry out exams. In the implementation of the exam at MTS Nurul Iman, he used a computer answer sheet as an entry. Meanwhile, schools are required to have certain scanners that are expensive to correct computer answer sheets. Another alternative that can be done by schools is to manually correct computer answer sheets, but this makes a lot of time wasted, and can cause errors in correcting and slow work productivity. From the problems that have been described, to detect the computer answer sheet, a method is needed. Through this research, it is hoped that a method can be developed that automatically detects the answer choices on the computer answer sheet, so that more accurate and faster results are obtained. Based on the problems of this study, the researchers used the OMR (Optical Mark Recognition) method to detect computer answer sheets automatically. From the test results, it can be concluded that the accuracy of detection of computer answer sheets using OMR is 97%.
A Matching Algorithm T-AKAZE for Image Recognition of Hydroelectric Equipment Failure

Abstract Aiming at the shortcomings of the current image-based fault identification algorithm for hydropower station equipment, such as low efficiency and poor accuracy, an improved image matching algorithm based on AKAZE, T-AKAZE was proposed. In this paper, AKAZE algorithm is firstly used to obtain image feature points. Then, the improved algorithm T-AKAZE is used for coarse matching of feature points. On the basis of Tanimoto coarse matching, RANSAC algorithm is used for fine matching to improve the algorithm accuracy. In order to verify the matching effect of the improved algorithm, ORB algorithm, AKAZE algorithm and ORB+Tanimoto algorithm were compared and analyzed. The experimental results show that the proposed algorithm has good robustness for image matching of different scales and similarity, and its timeliness also meets the application requirements, which provides convenience for the staff to identify the fault of hydropower station equipment.
Prediksi Kepribadian Berdasarkan Media Sosial Twitter Menggunakan Metode Naïve Bayes Classifier

Analysis of a person's personality is very helpful as an assessment in various matters such as recruitment, career, health. The methods commonly used in personality analysis are interviews, observations, and questionnaire surveys. This study tries to provide a solution by simply using social media, namely twitter, by analyzing twitter user information data called tweets, this is to add to the method of personality analysis. The method used in this personality prediction research is to classify a tweet into 5 personality forms. The personality method used by the researcher is the Big Five Personality which consists of openness, conscientiousness, extraversion, agreeableness, and neuroticism with classification calculations using Naive Bayes. The result of this research is an accuracy of 42% with the highest class, namely Agreeableness.
WAYS OF IMPROVING PROFESSIONAL AND PEDAGOGICAL TRAINING OF FUTURE VOCATIONAL EDUCATION TEACHERS

The article is devoted to the issues of professionals in the field of vocational education training and the factors that affect the students’ and lecturers’ activities. Research of well-known scientists who deal with future professionals in the field of vocational education training (masters of vocational education, teachers of technology) in higher educational institutions (HEI) is analyzed; the formation of the teacher (lecturer) in the process of training is revealed.&#x0D; The content and forms of educational motivation, which has specific components, are considered; the statement concerning the reasons of better results of the received knowledge when students consciously aspire to get a profession, to get competencies, to receive pleasure from the process of knowledge, to have material prosperity in the future is substantiated.&#x0D; Emphasis is placed on the formation of the appropriate level of professional and pedagogical competence, including the basics of pedagogical skills of future professionals in the field of vocational education.&#x0D; One of the main factors influencing the activities of both students and lecturers is the appropriate scientific and logistical base of higher education, which allows improving the quality of education through the use of various modern technologies, multimedia equipment, and technical means in the educational process.&#x0D; It is proved that professional in the field of vocational education training is currently based on the formation of the necessary set of competencies: knowledge, skills, and methods of their use, personality traits, and pedagogical values to solve professional and pedagogical issues by mastering new technologies, techniques, and types of professional activities. It has been found that the activity of a modern professional in the field of vocational education as a teacher and an organizer is constantly expanding, so the ways to improve this activity are determined by the professional orientation of the educational process and compliance with the requirements for specialists to the social order; creating an atmosphere of partnership, joint productive activities of lecturers and students of higher education; modernization and improvement of technologies and methods of professional and personal development of vocational education teachers in the process of professional training.
Automatic dependent bug reports assembly for bug tracking systems by threshold-based similarity

&lt;p&gt;Bug reports contain essential information for fixing problems that occur in software. Many studies have proposed methods for automatic analysis of bug reports. One such task could affect the completion of software bug fixing, known as “bug dependency”. Although this problem was mentioned by many researches, most of them discussed about the related bugs but not really dealt with dependency issue in bug reports. One possible solution used for addressing this issue is to assemble all relevant/dependent bug reports together before analysis of the next processing stages. This study presents a method of assembling dependent bug reports. The main mechanism is called “threshold-based similarity analysis”, and the three similarity techniques of cosine similarity (CS) multi aspect TF (MATF), and BM25 are compared with feedback, precision and likelihood value. As the BM25 with the threshold as 0.5 gives the best results, it was used to compare with the state of the art method. The results show that our method increases precision and likelihood values by 12% and 12.4% respectively. Therefore, our results can be used to encourage developers to recognize all dependent bugs in the same problem domain.&lt;/p&gt;
DETECTING ANOMALOUS ACTIVITIES IN SPATIO-TEMPORAL REGION

Anomaly detection system using Machine Learning helps to detect the anomalies like accidents etc. Detecting anomalies in videos is important but it is an unsolved problem. This system will automatically detect the anomaly by image analysis from the surveillance videos. This system is capable of tracking abnormal event in each frame and generates a notification of such event. The proposed K-means algorithm performs existing anomaly detection techniques, while being comparatively time efficient. The system just requires a dataset of video frames and is fed as input to the anomaly detecting module
Evaluation of Lossy Compressed Mosaic for SPOT-6/7 Remote Sensing Data in SPACeMAP

SPACeMAP is a remote-sensing data portal system owned by LAPAN used to distribute mosaic data of Medium-Resolution to Very-High-Resolution for Provincial Governments. The frequently arising problem is that mosaic images have very large data size, especially for SPOT-6/7 mosaic images. The increasing number of data and users may affect the data loading process on the portal so that mosaic data compression can be considered. SPACeMAP has the Image Compressor feature using the Tile and Line algorithms with a compression ratio (target rate) recommended for optics (15 to 20). This study aims to determine the best algorithm and target rate to get compressed mosaic SPOT-6/7 imagery. The comparison method was done qualitatively through visual comparison and quantitatively by using Compression Ratio (CR), Bit per Pixel (BPP), and Peak Signal to Noise Ratio (PSNR).Â Results of the experiment show that, quantitatively, both Tile and Line algorithms give a different performance, depends on the zoom level and land cover characteristics. In terms of the qualitative result, the Tile algorithm gives better overall results compare to the Line algorithm. Quantitatively, both algorithms show good performance in the homogenous area. The target rate difference on the testing range does not affect process duration, nevertheless, the Line algorithm has a long process duration compare to the Tile algorithm. However, compression mosaics with lower or higher resolution remote sensing data may provide different results. Hence, this need be addressed on further studies.
Performance Evaluation Using Reward Point and Social Media (Case Study in Utility Company)

This paper aims at two things; first, see the participants' interest if learning is carried out with e-learning. Second, how the impact of the use of social media and reward point methods on the improvement in evaluation of learning outcome. The method used is a survey and experiment. The survey is used to find out whether the reward point and/or social media method will affect employee motivation in e-learning process. Experiments are used to see the impact of the use of both methods on selected samples. The sample used was employees of PT PJB Services located in Head Office and selected by purposive technique. Data analysis used ANOVA Test to measure whether the treatment had a significant effect on the dependent variable. This paper is expected to prove that learning, especially studied in this paper, that combined with these both methods will affect positively to employee learning motivation and support the improvement of learning outcome. The results obtained are e-learning with reward points and posting the learning process on Instagram significantly increase employee motivation in learning. However, e-learning with reward points and posting the learning process on Instagram did not significantly affect on increased of evaluation of employee learning outcomes. Keywords: Performance Evaluation, Reward Points, Social Media, Evaluation E-Learning