Reviewerly/exHarmony huggingface dataset:
Preface

The GIREP-MPTL 2018 Conference combines the efforts and interests of two communities, researchers in physics education and physics teachers. It presents a broad field of research and innovation that ranges from basic research to innovations in classroom teaching. The research and proposals include different educational levels from Primary to University. The proceedings present selected contributions from the Conference, organized by the organization GIREP and Multimedia in Physics Teaching and Learning and Donostia Physics Education Research Group of the University of the Basque Country. This event offered the opportunity to fruitfully exchange on their experience and ideas and share the latest information on Physics Education. The Conference was sponsored by Real Sociedad Española de Física, European Physics Society-Physics Education Division (EPS-PED), City Hall of San Sebastian, Provincial Council of Guipuzcoa and International Conference on Physics Education (ICPE) of the Commission C14 of the International Union of Pure and Applied Physics (IUPAP). The Conference organizers gratefully appreciate the patronage received from the Department of Education of the Basque Government for this conference. The Conference was attended by 282 participants representing 41 countries. Altogether, there were 181 oral presentations, 49 poster presentations, 10 workshops, 6 plenary, 2 plenary dialogues, 5 Girep Thematic Group contributions, across the seven conference topics: 1) Physics teaching and learning at Primary and Secondary Education 2) Physics teaching and learning at University 3) Preservice and in-service physics teachers’ education 4) Physics education in non-formal setting 5) Physics into STEM teaching and learning 6) ICT and multimedia in physics education 7) Nature of Science, gender and socio-cultural issues in physics education The Conference presents for first time in the GIREP events the idea of “Dialogue”. It involves two experts with a leader who gives a brief feedback on the subject and proposes to the two experts questions for the discussion. The two invited dialogues were about “Primary, Secondary and University pre-service physics teacher Education” and “The actual and potential impact of physics education research in students’ learning”. The second and third day of the Conference were dedicated to celebrating the teachers of physics. The organization of the Conference would not have been possible without the help of many people. In particular, we would like to thank Prof. Marisa Michelini, President of GIREP, for her constant support. We thank the members of the Local Organizing Committee and the reviewers for their dedication and commitment to this event, without them the proven quality of the contributions would not have been possible. We hope that these proceedings provide the reader with a contemporary vision of the teaching and learning process of physics San Sebastian, Spain Jenaro Guisasola Kristina Zuza
Anatomical Sciences Education Vol. 13, Issue 6, 2020 Cover Image

Anatomical Sciences EducationVolume 13, Issue 6 p. C1-C1 Cover ImageFree Access Anatomical Sciences Education Vol. 13, Issue 6, 2020 Cover Image First published: 06 November 2020 https://doi.org/10.1002/ase.2026AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume13, Issue6November/December 2020Pages C1-C1 RelatedInformation
Djibouti – World Bank Invests in Education

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 56, Issue 9 p. 22714B-22714C Policy and Practice Djibouti – World Bank Invests in Education First published: 06 November 2019 https://doi.org/10.1111/j.1467-6346.2019.09143.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume56, Issue9November 2019Pages 22714B-22714C RelatedInformation
Interactive QoS browsing for web service selection

In most of the current research works on Quality of Service (QoS) based web service selection, searching is usually the dominant way to find the desired services. This approach comes with the potential problem of framing search queries properly due to requestor's lack of knowledge or vague requirement about QoS attribute values. In this thesis, we propose an interactive QoS browsing mechanism that uses the concept of clustering to present the QoS value distribution to requestors followed by finer views of service quality. By analyzing various QoS attributes, we believe that the symbolic interval data is a proper type of representation, compared with the single valued numerical data. Therefore, we use interval data clustering algorithms to implement our browsing system. We conducted experiments on simulated QoS datasets to compare the performance of using different distance measures and show the effectiveness of the interval data clustering algorithm used. The result of the experiments show that the proposed approach provides an effective, user guided QoS based service selection approach that can conceivably overcome the problems with current approaches.
Nearest Neighbor Forecasting Using Sparse Data Representation

The method of the nearest neighbors as well as its variants have proven to be very powerful tools in the non-parametric prediction and categorization of experimental measurements. On the other hand, the number of data available today as well as their dimensionality and complexity is growing rapidly in many scientific fields, such as economics, biology, chemistry, medicine, and others. Usually, the data and their characteristics have semantic dependence and a lot of noise. At this point, the sparse data representation that deals with these problems with great success is involved. In this paper we present the application of these two tried and tested techniques for prediction in various fields related to economics. New techniques are presented as well as exhaustive tests for the evaluation of the proposed methods. The results are encouraging to continue research into the possibilities of sparse representation combined with good proven machine learning techniques.
A Study on the Developmehnt A Conceptual Model of Teaching Practicum and Its Validity

이 연구의 목적은 교육실습 개념 모형을 개발하고 이를 타당화하는 데에 있다. 이를 달성하기 위해서 교육실습에 대한 선행연구들을 고찰하여 교육실습의 개념을 정립하고 그 개념으로부터 개념 모형의 하위 요소를 추출하였다. 그리고 추출된 요소를 각 차원으로 하여 교육실습 개념 모형(안)을 구안하였다. 또한 구안된 교육실습 개념 모형(안)과 그 하위 요소들에 대한 타당화를 위하여 교육실습전문가 20명을 대상으로 5점 리커트 식의 질문을 통해 전문가 의견 조사를 실시하였다. 분석 결과 9 개 요소 및 정의에 대한 값이 모두 기준 값보다 높게(CVR>0.42) 분석되어 연구에서 개발한 모형(안) 의 각 차원과 요소에 대한 정의들이 타당한 것으로 나타났다. 또한 평균 4.0이상, 표준편차 1.0 미만으로 각 차원별 요소들에 대한 분석 결과 모든 요소에서 전문가들의 의견이 일치하고, 타당한 것으로분석되었다. 이로써 본 연구는 교육실습 개념 모형(안)의 각 차원 및 하위 요소, 그리고 각 요소들의정의에 대한 내용 타당도 검증에 성공하였다. 교육실습 개념 모형(안)의 타당화로 인해 교육실습 개념 모형의 현장 적용 가능성이 높아졌다는 데에 본 연구의 의의가 있다.The purpose of this study is to develop a conceptual model of teaching practicum and to justify it. To achieve this, the researchers established a conceptual model of teaching practicum in consideration of prior research on teaching practicum and extracted its sub-elements. Then, we devised a conceptual model of teaching practicum(proposal) with extracted elements. In addition, the researchers conducted an expert opinion survey of 20 experts to verify the feasibility of the proposed the conceptual model of teaching practicum and its sub-elements. According to the analysis, the values for the nine elements and definitions that form the conceptual model of teaching practicum were all higher than the reference value(CVR>0.42). Therefore, it was found that the definition of each dimension and element of the conceptual model of teaching practicum developed in this study was reasonable. In addition, an analysis of factors at each dimension with an average of 4.0 or higher and a standard deviation of less than 1.0 showed that the opinions of the experts agreed on all factors. This confirms the validity of each elements. Therefore, this study succeeded in verifying the sub-elements of the conceptual model of teaching practicum and the definition of each element. As a result, it is meaningful that the validity of the the conceptual model of teaching practicum has increased the development of the the conceptual model of teaching practicum and its applicability to the field.
Preface

This conference keeps the tradition of having regular scientific and technical conferences on the urgent issues of applied mathematics, computer science and mechanics at the Voronezh State University, which has been developed over the past 20 years. Every year, well-known authorities, who represent various scientific areas, educational organizations, industrial enterprises and IT companies, gather at this scientific forum. Within the framework of the conference, thorough analyses of modern scientific advances in fundamental and applied areas are made, original reports on the current trends in the development of modern mathematics, computer science and mechanics are made. In general, the work of the conference is aimed at identifying and systematizing the issues and trends in the development of the scientific areas of modern mathematics, computer science and mechanics; discussion of the results of solving scientific problems and projects; development of scientific cooperation; involving students and graduate students in scientific work. List of Organizing Institutions, Supporting Institutions, Organizing and Program Committees and Conference Paper Review Process are available in this pdf.
Implementation of DBSCAN Clustering to Relate Various Parameters to Predict Primary Education Growth Based on Previous Data

Primary Education can be defined as first step of compulsory education which contributes in the development of future of country. Our aimis to develop a prototype based on DBSCAN Clustering Algorithm to monitor the primary education and corresponding utilization of previous data to estimate and predict the future growth of primary Education in India.The major goal of primary education is achieving basic literacy and numeracy amongst all people as well as establishing foundations in science, mathematics, geography, history &amp; social sciences. DBSCAN Clustering Algorithm can be utilized to establish relationship between human resources, infrastructure, government expenditure, actual utilization of these resources and the outcome which is socio-economic makeover of Society of India. It would help to predict and formulate correct path to transform the process of growth of Indian Primary Education System.
Increased PSNR with improved DWT digital watermarking technique

Today, the world is moving towards a digital era in every walk of life. Every business, government and private sectors, and research organisation use the digital image, as a transfer mode for critical data. The images over the internet are not secure therefore, image security is needed. In this work, a new technique of image security is proposed using digital watermarking which is more efficient and robust than the discrete wavelet transform (DWT). The whole mechanism is greatly reliable on the human visual system, as the watermark is not visible to the human eye. This increases the security of the hidden image or messages. The technique is tested against the PSNR of several images. The average PSNR calculated of all the tested images was compared to other techniques and found that the new technique is better than the existing techniques. This technique can be used for security of multimedia data.
Editorial notice

The article, “Automating event location monitoring for induced seismicity” by Willacy et al., in the July 2020 issue of TLE was originally published under SEG copyright. Since publication, the authors have allowed the article to be published as open access under a Creative Commons Attribution 4.0 Unported License (CC BY) ( https://creativecommons.org/licenses/by/4.0/deed.ast ), and copyright is held by the authors.
Clustering mixed data using an Artificial Bee Colony

In this paper, we have proposed a clustering technique which optimizes the total compactness and separation (measured using the Silhouette index) of the clusters. The proposed algorithm uses an Artificial Bee Colony (ABC) based optimization method as the underlying optimization criterion. We used similarity based prototypes as cluster centers. The proposed clustering technique is able to suitably handle mixed and incomplete data types in such a way that the original characteristics of the data are preserved. Assignment of points to different clusters is done based on a dissimilarity function rather than the Euclidean distance. Results on real-life data sets show that the proposed technique is well-suited to detect true partitioning from data sets. Results are compared with those obtained by four existing clustering techniques, one genetic algorithm based clustering technique (AGKA), the k-Prototypes (KP) algorithm, well-known based K-means clustering technique for similarity functions (KMSF) and a newly developed algorithm with dissimilarity based clustering technique (AD2011).
Neural Computation

This chapter rejects the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous signals; digital computation requires strings of digits. But typical neural signals, such as spike trains, are graded like continuous signals as well as constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. The chapter draws three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on nonneural notions of computation ought to be replaced or reinterpreted in terms of neural computation.
Financial Inclusion and Economic Growth Utilizing Panel Co-Integration

This paper attempts to test the co-integration association flanked by financial inclusion and economic growth. The study uses a composite score of financial inclusion and GDP per capita as a proxy of economic growth for its empirical analysis. The panel data covers a large sample of 52 countries for the time period 2005-2015, separated in three groups depending on their income level – low, middle and high. For the analysis, first the study constructed an index of financial inclusion (IFI) utilizing the methodology adopted by Sarma [41]. Then the study applied unit root checks to validate if the variables are non-stationary and co-integrated. Last, the study utilized Pedroni’s panel co-integration analysis to investigate the long-run affiliation. The study also cross checked the results using Fisher’s panel co-integration test. The empirical analysis is based on 11 countries from high income economies, 19 countries from middle income economies and 21 countries from low income economies. The findings confirm a long-run association flanked by economic growth and index of financial inclusion for the middle income countries. This concludes that financial inclusion can contribute substantially to economic growth through better penetration, availability and use of financial services in the middle income countries.
Web Document Classification Using Fuzzy K-Nearest Neighbor

With surge in the number of documents across the internet, increasing the efficiency of any retrieval model is a challenging task. As non-relevant information is retrieved across the internet, increasing the accuracy of any search model is one of the research concerns. Fuzzy classification is broadly applied to address the search issue in search engines. Fuzzy logic provides a methodology to interpret natural language using membership functions. A variant of k-Nearest Neighbor (kNN) called Fuzzy kNN is explored in this paper. This paper provides a comparative analysis of results obtained using kNN and Fuzzy kNN. The Fuzzy kNN results obtained show significant improvement.
Elastic Graph-based Semi-supervised Embedding with Adaptive Loss Regression

Fast track article for IS&amp;T International Symposium on Electronic Imaging 2020: Image Processing: Algorithms and Systems proceedings.
An ensemble of grapheme and phoneme-based models for automatic English to Kannada back-transliteration

The task of mapping graphemes or phonemes of one language into phoneme approximations of another language is known as machine transliteration. In this paper, three machine transliteration approaches, 'grapheme-based model', 'phoneme-based model' and 'hybrid model' have been proposed to achieve back transliteration of Romanised Kannada word to its native script Kannada, a resource poor language. A bilingual corpus of around 3 lakh words is built, which comprises of pairs of Romanised Kannada word with its corresponding word in Kannada script. The paradigms are assessed with 3,000 Romanised Kannada test words. Hybrid model achieved better accuracy of 85.93% when compared with other two models.
Creating Custom SQL Server on Windows Container Images

Being in private school means following certain dress codes – white collared shirt with the school logo, navy blue dress pants, and black leather shoes. Come rain or shine, school uniforms must be worn. Imagine carrying a 15-lb backpack with all your books and notebooks as you walk across the campus while the monsoon rain is pouring. It doesn’t matter how good your ready-to-wear leather shoes are, they won’t last an entire semester. It didn’t help that ninth grader boys like playing rough and running around during recess. My mom had given me a good amount of scolding whenever I complained about my worn-out leather shoes.
Quality Driven Approach for Product Line Architecture Customization in Patient Navigation Program Software Product Line

Patient Navigation Program (PNP) is considered as an important implementation of health care systems that can assist in patient's treatment.Due to the feasibility of PNP implementation, a systematic reuse is needed for a wide adoption of PNP computerized system.SPL is one of the promising systematic reuse approaches for creating a reusable architecture to enabled reuse in several similar applications of PNP systems which has its own variations with other applications.However, stakeholder decision making which result from the imprecise, uncertain, and subjective nature of architecture selection based on quality attributes (QA) further hinders the development of the product line architecture.Therefore, this study aims to propose a quality-driven approach using Multi-Criteria Decision Analysis (MCDA) techniques for Software Product Line Architecture (SPLA) to have an objective selection based on the QA of stakeholders in the domain of PNP.There are two steps proposed to this approach.First, a clear representation of quality is proposed by extending feature model (FM) with QA feature to determine the QA in the early phase of architecture selection.Second, MCDA techniques were applied for architecture selection based on objective preference for certain QA in the domain of PNP.The result of the proposed approach is the implementation of the PNP system with SPLA that had been selected using MCDA techniques.Evaluation for the approach is done by checking the approach's applicability in a case study and stakeholder validation.Evaluation on ease of use and usefulness of the approach with selected stakeholders have shown positive responses.The evaluation results proved that the proposed approach assisted in the implementation of PNP systems.
Special issue on “Mind and Cognition in the Future of Decision Support Systems”

International Transactions in Operational ResearchVolume 28, Issue 2 p. 1100-1101 Call for Papers Special issue on “Mind and Cognition in the Future of Decision Support Systems” First published: 17 October 2020 https://doi.org/10.1111/itor.12891Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume28, Issue2March 2021Pages 1100-1101 RelatedInformation
Using Lexicon-Based Opinion Mining to Gauge Customer Satisfaction

The web offers businesses a great tool to get instant feedback from their customers. Decision-makers need to improve the decision quality and increase the business performance, they required applications that provides data analysis and data visualization. In this paper, we will try to test users’ reviews about hotels in Europe, they stayed and left a comment expressing their feelings about their experience, by applying opinion mining and sentimental analysis methodology on 515,000 customers reviews to uncover how effective and useful a lexicon-based Sentiment Analysis system will be for business executives to improve the performance and quality of hotels. We wish to explore key-concepts of sentiment analysis, classification levels, different approaches to Sentiment Analysis. And we will apply step by step SA techniques to preprocess the text, tokenize, lemmatize, analyze text, then produce business intelligence visualization results.
Graph Based Digital Spammer Identification by User Click Behavior

As social media network popularity increases day by day, content writer are spamming on these platform for potential benefits of some organizations. Some of blogs are fabricate which invite users to external phishing sites or malware downloads huge security issue online and undermined the user experience. This work has proposed an un-supervised technique for identifying the real users from the social network spammers. Here graph based clustering algorithm was proposed to develop a binary cluster on the basis of serial or sequential action perform by the user. As per series of action social network graph is reduce into spanning tree where highly distance nodes are identified as abnormal behavior. So group of highly distance nodes are consider as the social spammers while other are real users. Experiment was perform on real social sequential dataset of twitter. Results were compared on various evaluation parameters and it was obtained that proposed approach has improved all such parameter values as compared to previous approach adopt by researcher.