Reviewerly/exHarmony huggingface dataset:
Pengelolaan Perpustakaan Berbasis Teknologi di Perpustakaan Sma Negeri 1 Padang (Studi Kasus: Pada Perpustakaan Sma Negeri 1 Padang)

AbstractThe writing of this paper aims to describe how to process tecnologi digital-based collections, to describe how to manage information technology-based technology services, describing what are the facilities and infrastructure of technology library-based management at the Padang 1 Public High School Library. Data was collected through observation and interviews with librarians and visitors at the Padang 1 Public High School Library. Data analysis was carried out descriptively. Based on the discussion described above, it can be concluded that First, digital-based collection processing is processing physical collections in the form of systematic collection of collections ranging from checking library materials to compiling books on a shelf, processing book collections into digital collections using SLiMS applications, processing physical data collection of digital-based books by transferring media collections of books to digital-based collections by using a scanner machine. Second, the management of technology-based information services, namely the creation of membership cards, on the membership card library has information about member identities, member names, identity numbers, addresses and telephone numbers of users, information search services, application of corner literacy services. Third, library-based infrastructure management tools, namely infrastructure literacy corner bookshelves provided by schools, the application of barcode scanners, library building infrastructure that is quite extensive as a forum for educational information services in libraries, television facilities as learning media for students in Padang 1 Public High School and internet-connected computer facilities.Keywords: management; processing; technology
Learning to Reuse Translations: Guiding Neural Machine Translation with  Examples

In this paper, we study the problem of enabling neural machine translation (NMT) to reuse previous translations from similar examples in target prediction. Distinguishing reusable translations from noisy segments and learning to reuse them in NMT are non-trivial. To solve these challenges, we propose an Example-Guided NMT (EGNMT) framework with two models: (1) a noise-masked encoder model that masks out noisy words according to word alignments and encodes the noise-masked sentences with an additional example encoder and (2) an auxiliary decoder model that predicts reusable words via an auxiliary decoder sharing parameters with the primary decoder. We define and implement the two models with the state-of-the-art Transformer. Experiments show that the noise-masked encoder model allows NMT to learn useful information from examples with low fuzzy match scores (FMS) while the auxiliary decoder model is good for high-FMS examples. More experiments on Chinese-English, English-German and English-Spanish translation demonstrate that the combination of the two EGNMT models can achieve improvements of up to +9 BLEU points over the baseline system and +7 BLEU points over a two-encoder Transformer.
Data-driven graph drawing techniques with applications for conveyor systems

Abstract The visualization of conveyor systems in the sense of a connected graph is a challenging problem. Starting from communication data provided by the IT system, graph drawing techniques are applied to generate an appealing layout of the conveyor system. From a mathematical point of view, the key idea is to use the concept of stress majorization to minimize a stress function over the positions of the nodes in the graph. Different to the already existing literature, we have to take care of special features inspired by the real-world problems.
Towards Efficient Discrete Integration via Adaptive Quantile Queries.

Discrete integration in a high dimensional space of n variables poses fundamental challenges. The WISH algorithm reduces the intractable discrete integration problem into n optimization queries subject to randomized constraints, obtaining a constant approximation guarantee. The optimization queries are expensive, which limits the applicability of WISH. We propose AdaWISH, which is able to obtain the same guarantee but accesses only a small subset of queries of WISH. For example, when the number of function values is bounded by a constant, AdaWISH issues only O(log n) queries. The key idea is to query adaptively, taking advantage of the shape of the weight function being integrated. In general, we prove that AdaWISH has a regret of only O(log n) relative to an idealistic oracle that issues queries at data-dependent optimal points. Experimentally, AdaWISH gives precise estimates for discrete integration problems, of the same quality as that of WISH and better than several competing approaches, on a variety of probabilistic inference benchmarks. At the same time, it saves substantially on the number of optimization queries compared to WISH. On a suite of UAI inference challenge benchmarks, it saves 81.5% of WISH queries while retaining the quality of results.
Object Tracking Via ImageNet Classification Scores

Object tracking is a challenging task in computer vision. The correlation filter based trackers are widely used for visual tracking due to their efficiencies. However, they cannot handle occlusion very well. In this paper, an effective method is proposed for occlusion detection based on high-level classification scores from the Convolutional Neural Network (CNN) trained on the ImageNet dataset. Also, we propose a novel tracking method by holistically considering multiple tracking models trained previously. In each frame, multiple correlation filters are first trained using hierarchical convolutional features, and then progressively selected according to the so-called tracking quality (status). Finally, a linear motion model is adopted to effectively re-detect the lost target. Experimental results have demonstrated that our method achieved good performance for handling occlusion.
LibGuides: Using Git and GitHub for Version Control: Getting Started

Describes how to use Git (a versioning control system) and GitHub (a web-based git repository) to track changes to your code.
IMPROVING ENGLISH COMMUNICATIVE COMPETENCE FOR VOCATIONAL HIGH SCHOOL USING SCAFFOLDING TEHNIQUE

Indonesia must prepare the high-skill categories needs for every aspects. One of the aspects is theability to compete in this era, the ability to communicate with other. Indonesian needs Englishcommunicative skill to face the Industrial Revolution 4.0. The aims of the study are: to understandVocational High School students’ English competence and to understand the effect of ScaffoldingTehnique on Improving English Communicative competence for Vocational High School. This researchused descriptive qualitative method. The study used a pre-test, post-test to know the result of the study:the researcher tested the participants orally as the pre-test and post-test of study. In this research, thepopulation of the research is the first grade of Citra Medika Vocational High School. There were 2classes and there were 54 students and all the students are the population of the research. The resultsof independent sample t-test showed that there was a significant difference between the performance ofintervening and control groups (t = 4.60, p&lt; .05) on posttest in such a way that the intervening groupoutperformed in posttest
Pemanfaatan Aplikasi Evaluasi Belajar Berbasis Web Era Covid - 19

Learning evaluation can provide opportunities for teachers to make plans and estimations, whether the predetermined goals will be achieved according to the planned target time. If based on the data from the evaluation results it is estimated that the goal will not be achieved as planned, the teacher would try to find the factors causing the problems found, and provide solutions to the problems. The corona pandemic period really needs an online learning and evaluation process, the use of web-based applications will be able to provide assistance to teachers who can quickly assess learning evaluations on teaching materials as well as make time efficiency. The method of making an application is by Rapid Application Development (RAD) or rapid prototype; it is a model for developing a software system with a tiered pattern. The main thing used is a tool in the form of a web-based learning evaluation application resembling an application that can carry out evaluations related to a certain exam process as a trial during entry data training of all existing subjects by the teacher concerned with the authority as a teacher, scheduling and instructor arrangement by the principal, and finally student entry by the operator. Each application a different task according to its function.
LibGuides: eBook Collections at UVic Libraries: eBooks @ UVic Libraries

A guide to the eBook collections at UVic Libraries An introduction to the e-book collections accessible via UVic Libraries.
Analisa Sistem Informasi Geografis Pemetaan Rumah Sakit di Kota Samarinda Berbasis Web

There have been many hospitals in Samarinda, but the rapid development of hospitals in Samarinda, not accompanied by the development of media support facilities and hospital information is still lacking especially in terms of mapping hospitals in Samarinda City. Currently, the hospital in Samarinda has 14 hospitals. To speed up and facilitate the search of data of hospitals that currently number 14 hospitals, the proposed problem is to build a web based application  of Hospital Geographic Information System (GIS)  in Samarinda. The research was conducted at the Samarinda City Health Office. Methods used in data collection include field studies (interviews and observations), and library studies. Data analysis was conducted  qualitatively based on technological analysis, GIS data analysis, and analysis of  GIS output information. The results showed that this geographic information system could display a map of Samarinda city along with the hospital information. This geographic information system can provide solutions in solving the search for the nearest specialist doctor and show the closest route to the hospital.
A Human-Robot Skill Transfer Framework of Mobile Medical Robots for Autonomous Motion with Teaching by Demonstration

The accuracy of autonomous motion is the main challenge for mobile medical robots, especially running in narrow space conditions to transport the casualties in the hospital. This article mainly centers on the human-robot transmission of the mobile medical robot for narrow space autonomous motion. In order to enable mobile medical robots to autonomously and smoothly transport hospital casualties through narrow aisles, in this paper, we present a robot skill transfer technology, namely a human-robot skill transfer framework of mobile medical robots for autonomous motion with teaching by demonstration, which is that a smooth optimal path is planned through the human motion, and then the Kinect sensor is used to detect human bone movement to learn its motion trajectory so as to achieve trajectory tracking control. Meanwhile, using the Remote Center of Motion (RCM) constraint to minimize the error between the actual trajectory of the medical robot and the tracking reference path to control the motion trajectory accurately, human-computer interactive mobile medical robots can smoothly pass through narrow channels. Through research and analysis, it is demonstrated that the mobile medical robot proposed in this paper has great feasibility, which is of great reference value in the field of medical rescue.
Neural Networks in Evolutionary Dynamic Constrained Optimization: Computational Cost and Benefits.

Neural networks (NN) have been recently applied together with evolutionary algorithms (EAs) to solve dynamic optimization problems. The applied NN estimates the position of the next optimum based on the previous time best solutions. After detecting a change, the predicted solution can be employed to move the EA's population to a promising region of the solution space in order to accelerate convergence and improve accuracy in tracking the optimum. While previous works show improvement of the results, they neglect the overhead created by NN. In this work, we reflect the time spent on training NN in the optimization time and compare the results with a baseline EA. We explore if by considering the generated overhead, NN is still able to improve the results, and under which condition is able to do so. The main difficulties to train the NN are: 1) to get enough samples to generalize predictions for new data, and 2) to obtain reliable samples. As NN needs to collect data at each time step, if the time horizon is short, we will not be able to collect enough samples to train the NN. To alleviate this, we propose to consider more individuals on each change to speed up sample collection in shorter time steps. In environments with a high frequency of changes, the solutions produced by EA are likely to be far from the real optimum. Using unreliable train data for the NN will, in consequence, produce unreliable predictions. Also, as the time spent for NN stays fixed regardless of the frequency, a higher frequency of change will mean a higher produced overhead by the NN in proportion to the EA. In general, after considering the generated overhead, we conclude that NN is not suitable in environments with a high frequency of changes and/or short time horizons. However, it can be promising for the low frequency of changes, and especially for the environments that changes have a pattern.
Human Posture Reconstruction and Recognition for Real World Applications

New ideas in motion capture and virtual reality applications have been made possible by the recent advancements in motion recognition. Using a pattern recognition algorithm, Microsoft kinect can detect the different body postures of the human body. But due to the single-depth camera, the accuracy of recognition is not significant. This also has a significant effect due to the surrounding environment. The accuracy is still reduced, when the body parts are not recognized correctly. In this paper we propose a method to remove noise and increase the efficiency of the posture recognition. A similar set of postures are synthesized based on the position of the body parts. These values are then learned by a machine to give the posture of the human. This is plied to the frame based optimization to create a new posture which resembles the older one.
To Interpret or To Recreate: A Theory of Authenticity in Performance Practice

Among the discourses on the art of music performance, both in the verbal communication of the performers and the analyses and critical evaluations of their art, a recurrent concept is that of the “authentic performance.” Functioning in musical contexts in several interrelated senses, this concept and the ideology behind it can undoubtedly be considered an influential current which, by the end of the twentieth century, had a significant impact on the whole industry of classical music in its broadest sense. Hence, it deserves to be introduced as a distinctive type of a performance-related issue and analysed as such. Since the final decades of the twentieth century, the most common use of this concept has referred to the type of performance that synonymously is termed “historically informed” or “historically aware.” An important aspect of such a performance, besides the study of treatises and manuscripts from the period, is the employment of “period”, “original”, or, indeed, “authentic” instruments and playing techniques from the times when the interpreted music was first performed. Thorough studies have been devoted to the issue where, along with the arguments in favour of and motives for an authentic performance, a great deal of criticism has been levelled against the idea. What, then, lies behind the concept of being “authentic”? The present article draws on the existing discussion of the meaning(s) and (im)possibility of an authentic performance, placing particular interest in the semiotic approach to the issue of authenticity in music and, in particular, in musical performance. Two main sources are relied on here: Eero Tarasti’s Existential Semiotics (2000) and Dario Martinelli’s Authenticity, Performance and Other Double-Edged Words (2010), which are at the same time part of a continuum (Martinelli’s reflections are inspired by Tarasti, and both refer to Greimas and Eco) as well as displays of different conclusions (starting from the fact that Tarasti, generally speaking, defends the concept, while Martinelli shows signs of scepticism towards a certain (ab)use of the idea). Adding her reflections on the matter, the author offers a new perspective on how to analyse the idea of authenticity in art music performance.
LibGuides: LibrarySkills@UCL: Referencing and managing information: Assignments

A guide to skills and support for referencing and managing information sources and research data.
An Analysis of Students’ Needs in Reading Comprehension of Eight Grader of SMP IT Fathona Baturaja

The Problems of the study concerned with whether or not the students’ need English for specific purposes in reading. In addition, the study was done to find out the student’s need in reading comprehension. Total sampling method was used to take the sample. The sample was 11 students from the eighth grade in academic year 2019/2020. A Descriptive method was used in this study. The writer used questionnaires and documentation in collecting the data. The result of study from view of Target needs (necessities) showed that 72.8% claimed that they hope that learning English could support their future works. The result of target needs showed that 45.5% were in beginner level. 81.8% want to be able to master both general vocabulary and Islamic world terms. Moreover, the result of learning needs, input in reading comprehension 72.7% claimed that reading can add English vocabulary. From procedure in reading, 54.5% said that they were agree with arranging random paragraphs or sentences into a correct or logical paragraph sequence of sentence. Next, 90.9% students wanted to do the study outside the classroom, 45.5% claimed that they were strongly agree with activity in discussing and being active in investigation. The last, 54.5% students were strongly agreed that teachers must create an active atmosphere to solve problems and doing assignment.
Faktor Penentu Pemahaman Mahasiswa Akuntansi Era Covid19 (Studi Empiris Mahasiswa Akuntansi di Jawa Timur)

This study aims to provide empirical evidence regarding the factors that affect student’s understanding in accounting during Covid 19 pandemic in East Java. There are there variables tested which are learning from home that represent the attitude and behavior of accounting students, the avalilability of IT and students understanding regarding the accounting knowledge. This study is a quantitative method to empirically tested those factors. Sampling method was carried out using a proportional random sampling technique and data was collected using a survey method through an online questionnaire. The results showed that the learning from home variable and the availability of IT had a significant positive effect on students' accounting understanding.
The Impact of Democratization on ‘FDI’ in Tunisia-A Comparison of Pre and Post Revolution Periods

The article aims to provide arguments of the favorable political conditions for FDI, the purpose is to know; whether, democracy and autocracy attract FDI in the Pre and Post-event of revolution in Tunisia. In addition, this investigation discusses the key elements for path dependency in democratic transitions from autocracy to democracy.
A Privacy-Preserving Approach for Continuous Data Publication

To ensure the privacy protection and improve data availability, addressing the problem of loss of data in continuous data publication. This paper provides a continuous privacy-preserving data publishing algorithm inspired by the slicing algorithm, where the τ-safety condition is applied as an extension of the m-invariance algorithm. The algorithm divides the published data records into several bins horizontally based on the sum of the distances between the attributes corresponding to the records. Then, each bin is divided into multiple columns vertically based on the relationship between attributes. Next, the columns in the same bin are randomly rearranged. Finally, a differential privacy protection algorithm is applied to any remaining records that do not satisfy the L-diversity condition. Application of the proposed algorithm to actual medical data demonstrates that the proposed approach effectively reduces information loss and enhances the retention rate of association relationships compared with a state-of-the-art algorithm.
Federated and intelligent datacubes

&amp;lt;p&amp;gt;We face unprecedented environmental challenges as a species, that threaten our existing way of life.&amp;amp;#160; We are still learning to understand our planet, although we have a good idea how it works.&amp;amp;#160; The speed of research needs to accelerate to provide information to decision makers, to better respond to our societal challenges.&amp;amp;#160; To do this we need to move towards leveraging large datasets to speed up research, as proposed by Jim Grey in &amp;amp;#8216;The Fourth Paradigm&amp;amp;#8217;. In the world of research infrastructures we need to provide a means for scientists to access vast amounts of research data from multiple data sources in an easy and efficient way.&amp;amp;#160; EOSC is addressing this but we are only scratching the surface when it comes to unleashing the full potential of the scientific community.&amp;amp;#160; Datacubes have recently emerged as a technology in the Environmental and Earth system domain to store imagery data in a way that makes it easier and quicker for scientists to perform their research.&amp;amp;#160; But with the scales of data volumes that are being considered, there are many challenges to curating, hosting, and funding this information in a centralised centre.&amp;amp;#160; Our proposal seeks to leverage the existing National Research and Education (NRENs) infrastructures to store national repositories of regional Environmental and Earth system domain data, for this to be shared with scientists in an open, federated but secure way, conforming to FAIR principles.&amp;amp;#160; This would provide levels of redundancy, data sovereignty and scalability for hosting global environmental datasets in an exascale world.&amp;lt;/p&amp;gt;
Browser Simulation-based Crawler for Online Social Network Profile Extraction

The rapid proliferation and extensive use of online social networks (OSNs) like Facebook, Twitter, Instagram, etc., has attracted the attention of academia and industry, since these networks store massive information in them. But, acquiring data from these OSNs, which is a prerequisite for conducting any research on them, is a daunting task, which can be because of privacy concerns on one hand and complexity of underlying technologies of these complex networks, on the other. This paper presents the design and implementation of a crawler based on browser simulation for extraction of Facebook users profile data while preserving the privacy. The breadth-first-search (BFS) algorithm approach was also adopted for sampling of around 0.235 million Facebook users. Though the main purpose of this work is the design of a crawler still, the results have been briefly presented in terms of various social network metrics and analysed from different aspects of privacy.