Reviewerly/exHarmony huggingface dataset:
FEATURES OF FORMING AN EFFECTIVE SYSTEM OF EDUCATIONAL SERVICES

The article discusses the trends in the development of Russian education, the formation and development of the educational services’ market that affect the effectiveness of the educational system. The analysis of scientific papers on the problem of the research allowed us to identify areas for improving the quality of educational services. The relevance of the topic is due to the peculiarity of adapting the Russian education system to the European tradition, the real needs of society, business and the state. The object of research is educational services, the subject of research is features of an effective educational services’ system formation. Taking into account strategic trends in the development of society and economy is the main element for making management strategic decisions regarding the further development of the educational environment. The quality of training specialists is of great importance in implementing the strategic goals of state development and improving the quality of human capital. The relevance of this topic is related to the complexity of this system, the high rate of educational services’ market development, the emergence of educational services’ new types and forms. The purpose of the article is to analyze trends in an effective system of educational services’ system formation. Research methods are semantic analysis of the functioning of educational systems, statistical analysis. The directions of improving the development of the education system related to social and economic aspects of functioning are defined. The growth in the number of private educational institutions indicates that the quality of services does not meet the needs of the economy, and the link with the production environment is low. A specialist with a higher education is forced to retrain in the conditions of an employer, which significantly increases the time of adaptation. Measures to overcome existing restrictions are described. The adaptation of the education system to the socio-economic conditions of Russia should be carried out in conjunction with the country’s development strategy, taking into account the features and role of training qualified personnel in the conditions of scientific and technological progress, changing the requirements for the competence of future specialists
Video-Based Content Recognition of Bank Cards with Mobile Devices

In this paper, we propose an algorithm for detection and recognition of all information fields at the bank card front side based on video sequences. The algorithm is intended for use on mobile devices. This algorithm consists of the following basic steps: detection of the card boundaries in a frame, segmenting the information fields, improving the quality of segments, localizing the boundaries of symbols, and recognizing blocks of symbols. We also conduct a series of experiments. Experimental results show that our algorithm can achieve higher detection rates of 88% for all information fields and 92.5% for the bank card number and expiration date. The processing time per frame at different resolutions for each step by using iPhone 7 is presented. The experimental results confirm the efficiency of the proposed approach.
Effective contact tracing and the role of apps: lessons from Europe. (Special Issue: COVID-19 health system response.)

Contact tracing is an essential tool to support the transition back to normal life during the COVID-19 pandemic This article explores how 31 countries operate contact tracing, using data extracted from the COVID-19 Health Systems Response Monitor (HSRM) Two main approaches emerge: centralised (led by one national agency) and decentralised (at regional/district level) In most cases, trained staff conduct phone interviews, and many countries have moved to strengthen the capacity of tracing teams Further, contact tracing apps are being developed and implemented, although some difficulties related to privacy concerns have arisen, necessitating more transparency on how data are collected
A General Model for Publicly Verifiable Secret Sharing

Publicly verifiable secret sharing (PVSS) is of remarkable significance for confidential data processing and storage in complex interactive systems. In this correspondence subtly deviating properties of preceding PVSS models are studied and a general PVSS model is proposed to satisfy possible requirements without ambiguity. The new model comprises a secret sharing algorithm, a secret recovering algorithm, cryptosystems for shareholders and relative zero-knowledge protocols. Two kinds of security for PVSS are formally defined: all-or-nothing security and indistinguishability security. It is also justified that the zero-knowledge protocol in the distribution phase does not influence security for the new PVSS model.
aCIOSm4: An Asynchronous CIOS Algorithm

This article proposes a novel asynchronous CIOS algorithm and its asynchronous architecture that can accelerate the encryption and decryption of RSA cryptosystem without increasing area. This algorithm merges two loops of the classical CIOS algorithm with the following advantages: reducing the number of operations by half, decreasing the complexity of hardware implementation by facilitation of the asynchronous pipelined parallel calculation, and saving the resources. Experimental results show that the average calculation time of our algorithm is only 9.8us, which is 36.5% faster than the classical one. In addition, our algorithm is also embedded in an asynchronous 1024-bits RSA cryptographic circuit, compared with the CIOS algorithm, the encryption and decryption speed are increased by 37.5%.
PHC-GAN: Physical Constraint Generative Adversarial Network for Single Image Dehazing

Recently, most existing single image dehazing methods adopt the physical scattering model to generate clear images. The model variables are often estimated by trainable neural networks. However, estimating the variables heavily rely on dataset that usually does not take into account of the physical process induced by the scattering model. In this scheme, error accumulation cannot be avoided when applying the end-to-end methods. In this paper, we propose a physical constraint generative adversarial network (PHC-GAN) for single image dehazing. The PHC-GAN is a physics aware model that leveraging the physical scattering process as an additional constraint. To the best of our knowledge, we are the first introducing physical constraint in learning an end-to-end image dehazing model. Our proposed model not only effectively reduce the error accumulation, but can be well adapted in complex and realistic natural scenes compared to the existing methods. In detail, we realize the physical constraint in terms of a double discriminator architecture. The self-attention module is also utilized to guarantee fast convergence. In experiments, quantitative and qualitative results on both synthetic and natural images demonstrate that PHC-GAN is superior to state-of-the-art dehazing methods.
Predicting the Objective and Priority of Issue Reports in a Cross project Context.

Proper documentation plays an important role in successful software management and maintenance. Software repositories such as GitHub host a large number of software entities. Developers collaboratively discuss, implement, use, and share these entities. Users exploit Issue Tracking Systems, a facility of software repositories, to keep track of issue reports, to manage the workload and processes, and finally, to document the highlight of their team's effort. An issue report can contain a reported problem, a request for new features, or merely a question about the software product. As the number of these issues increases, it becomes harder to manage them manually. GitHub provides labels for tagging issues, as a means of issue management. However, about half of the issues in GitHub's top $1000$ repositories do not have any labels. In this work, we aim at automating the process of managing issue reports for software teams. We propose a two-stage approach to predict both the objective behind opening an issue and its priority level using feature engineering methods and state-of-the-art text classifiers. We train and evaluate our models in both project-based and cross-project settings. The latter approach provides a generic prediction model applicable to any unseen software project or projects with little historical data. Our proposed approach can successfully predict the objective and priority level of issue reports with 83% and 75% accuracy, respectively.
Psychometric analysis of a test to assess the digital competence of compulsory education students

espanolPara que las investigaciones sobre la competencia digital puedan aportar informacion valiosa que contribuya a guiar las politicas educativas de desarrollo de la misma y de integracion de las Tecnologias de la Informacion y la Comunicacion en los sistemas educativos de los paises, es necesario contar con instrumentos de recogida de informacion validos y fiables. El objetivo del presente trabajo es el de validar una prueba para evaluar la competencia digital en estudiantes de Educacion Obligatoria, en los ambitos de conocimiento, capacidad y actitud; teniendo como base el Marco para el Desarrollo y la Comprension de la Competencia Digital en Europa. Este instrumento, disenado por un equipo de investigacion universitario, fue aplicado a una muestra de 771 estudiantes. Se analiza el indice de facilidad/dificultad de la prueba y por dimensiones, asi como la validez y la fiabilidad. Se concluye que la prueba es original, novedosa y presenta unas buenas propiedades psicometricas que permiten calificarla como un instrumento fiable y valido para medir la competencia digital en todas sus dimensiones, de manera directa, mediante la reflexion sobre situaciones reales y la resolucion de problemas. EnglishValid and reliable information-gathering tools are necessary if research on digital competence is to provide valuable information that is able to guide education policies on the development of digital competence and the integration of information and communication technologies (ICT) into the educational systems of different countries. The aim of the present work is to validate a test that assesses the digital competence of students in compulsory education (ECODIES) in the areas of general knowledge, ability and attitude, using the Development and Understanding of Digital Competence in Europe Framework (DigComp) as the foundation for this research. This tool, designed by a university research team, was used on a sample of 771 students. The easiness/difficulty index and dimensions of the test were analyzed, as well as its validity and reliability. It was concluded that ECODIES is an original and novel test that features good psychometric properties that qualify it as a reliable and valid instrument for directly measuring digital competence by reflecting on real situations and problem solving.
Pain Points and Solutions: Bringing Data for Startups to Campus

Entrepreneurship is growing as a cross- and inter-disciplinary area of focus for higher education. From patent and tech transfer offices to business, science, and engineering programs, the demand for entrepreneurship resources and support delivered via libraries is booming. Building library collections to help patrons design, launch, and run successful businesses is challenging: Market research and private equity/venture capital resources arrive at premium prices. Increasingly, these resources must interoperate with software used to clean, analyze, and visualize data. This data is often difficult to find and deploy. Restrictive, corporate-style licenses reflect that new vendors are not yet acclimated to the academic market’s access requirements and licensing constraints. This paper will share a framework for how to understand entrepreneurship in higher education and explain the types of information commonly requested by users. Such information often exists in disciplinary silos, emphasizing the importance of collaborative collection development across subject lines. The authors will explore the unique challenges to building collections that serve patrons developing new ventures. This includes collaborating with external stakeholders to fund resources that have not been traditionally purchased by libraries. Strategies for licensing data and other e-resources in this space will be discussed, including the central complications arising from universities as incubators for for-profit startups. The authors will suggest best practices for building relationships with stakeholders, developing relevant collections and services, and marketing these resources to support communities.
All Children Reading

This chapter sketches out a vision for how existing actors and new partners can meet the global need for multilingual children's literature within a decade. This strategy begins with mass translation of existing children's books, enabled by one or more of the copyright solutions: permissions, fair use, exceptions, and open licensing. Once the titles are translated, a second challenge remains: expanding distribution strategies so that a billion children can get their hands on these books. The chapter further explains that it will be essential to take full advantage of both digital and print formats and through both non-profit and commercial distribution venues in providing books to children. Utilizing a mass translation strategy can realistically create an adequate book supply for 95 percent of the world's children within a few years.
Determination of the typical load profile of industry tasks using fuzzy C-Means

This paper aims to promote the importance and advantages that the clustering method brings to the world of industry, making it possible to increase production efficiency and to manage the energy resources available better. The purpose of this paper is to group the consumption profiles of a task, in order to be able to determine which is the typical load profile of the task through the Fuzzy C-Means clustering method. The case study of this paper focuses on a task performed by three machines that make up a textile production line that makes several products. Each product, when going through a task performed by a specific machine, has a specific consumption and duration. Thus, by machine, it is determined which is the typical profile of ideal consumption to perform the designated task. In the same way, the general consumption profile of the task is highlighted, that is, the possible consumption profile to be expected when executing this task on one of the three machines.
Review of Image-Based Person Re-Identification in Deep Learning

Person Re-identification (re-ID) is a hot research topic in the field of computer vision now, which can be regarded as a sub-problem of image retrieval. The goal of person re-ID is to give a monitoring pedestrian image an... | Find, read and cite all the research you need on Tech Science Press
Peningkatan Prestasi Belajar Melalui Strategi Pembelajaran Kooperatif Tipe Team Assisted Individualization (TAI) Mata Pelajaran IPS Siswa Kelas III SDN Kalianget Barat II Kab. Sumenep

This research aims to; Want to know an increase in social studies learning achievement after the implementation of cooperative learning model Teams Assisted Individualization class III students of SDN Kalianget Barat II Kab. Sumenep "; Want to know the effect of motivation to study social studies after the implementation of cooperative learning model Teams Assisted Individualization class III students SDN Kalianget Barat II Kab. Sumenep ", provides an overview of appropriate learning methods in an effort to improve student achievement and make students become active in teaching and learning activities. In this study using a class action research design (CAR). The design of the classroom action research was chosen because (1) the study of classroom context research was carried out by the teacher to solve social studies learning problems, because the third grade students of SDN Kalianget Barat II Regency. Sumenep still experiencing difficulties in achievement especially social studies subjects, has not found the right learning strategy. Based on the results of the research that has been presented for three cycles, the results of the entire discussion and analysis that have been carried out can be concluded as follows; The TAI model of cooperative learning methods can improve the quality of social studies learning; The TAI model of cooperative learning method has a positive impact in increasing student achievement which is marked by an increase in student learning completeness in each cycle, namely cycle I (68.42%), cycle II (81.58%), cycle III (94.74% ).
Robot motion estimation with a multi-camera system

In this paper, we propose efficient solutions to estimate the robot motion with a multi-camera system. Specifically, we focus on the case that the camera is rigidly mounted on the robot, which roams in indoor environments. In this case, the roll and pitch angles with respect to the ground plane can be initially estimated, and we only need to care about a 3-DOF pose estimation problem. We derive closed-form and approximate minimal 3-point algorithms based on the hidden variable technique. We show that they lead to a 6-degree univariate polynomial with up to 6 real solutions and a 3-degree univariate polynomial with up to 3 real solutions, respectively. Experimental results show that the proposed algorithms are robust enough for real applications and significantly faster than the existing algorithms.
Developing project skills in future prımary school teachers within the university-based initial teacher education

Introduction. The authors investigate the problem of developing programme-specific competencies in future primary school teachers using project methodology in the process of initial teacher education. The purpose of the study is to assess the level of project skills in future primary school teachers and analyze the obtained empirical data. Materials and Methods. The research was conducted using the method of psychological and educational experiment. The empirical data included students’ essays and questionnaires. The sample consisted of students of Karaganda university named after academician E. A. Buketov and Pavlodar pedagogical university. The obtained data were interpreted and subjected to statistical analysis using the Student's t-test. Results. The authors have developed criteria and indicators for evaluating future teachers’ project skills in order to experimentally interpret their project activities. The identification of students' priorities for the choice of certain types of project activities determined the validity of the questionnaire. Frequency and percentage analyses revealed the insufficient level of project skills in future primary school teachers related to the following components: (1) the motivational component of programme-specific competencies; (2) the cognitive component; (2) the reflexive component. Conclusions. The results of the research showed that students demonstrated a low level of project skills, which can significantly complicate the process of improving the quality of initial teacher training for a new type of primary schools. Keywords Project activity of students; Formation of design skills; Special competence; Future primary school teachers; Initial teacher education; Modernization of education.
Question embeddings for semantic answer type prediction

This paper considers an answer type and category prediction challenge for a set of natural language questions, and proposes a question answering classification system based on word and DBpedia knowledge graph embeddings. The questions are parsed for keywords, nouns and noun phrases before word and knowledge graph embeddings are applied to the parts of the question. The vectors produced are used to train multiple multi-layer perceptron models, one for each answer type in a multiclass one-vs-all classification system for both answer category prediction and answer type prediction. Different combinations of vectors and the effect of creating additional positive and negative training samples are evaluated in order to find the best classification system. The classification system that predict the answer category with highest accuracy are the classifiers trained on knowledge graph embedded noun phrases vectors from the original training data, with an accuracy of 0.793. The vector combination that produces the highest NDCG values for answer category accuracy is the word embeddings from the parsed question keyword and nouns parsed from the original training data, with NDCG@5 and NDCG@10 values of 0.471 and 0.440 respectively for the top five and ten predicted answer types.
An Overview Studying of Deep Learning

Deep learning is a subfield of machine learning however both drop under the broad category of artificial intelligence. Deep learning is what powers the most human-like artificial intelligence that consents computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. Deep learning is making major advances in solving problems hence categorized in wider section of artificial intelligence. The main advantage of Deep Learning is to create an artificial neural network that can learn and make intelligent decisions on its own and to process large numbers of features makes deep learning very powerful when dealing with unstructured data.
Begin at the Beginning: Revamping Collection Development Workflows

“Begin at the beginning,” the King said, very gravely, “and go on till you come to the end: then stop.” This paper describes how two librarians newer to the University of Tennessee Libraries refreshed collection development workflows at the Libraries after a reorganization. This reorganization distributed tasks across departments in a different manner due to the new departmental configurations. In this new matrix environment, more communication was required to achieve desired outcomes, but more buy-in was also needed from constituents such as the subject librarians. This paper describes how a new Collections Committee was formed to make decisions on high-dollar resources; what information was added to the traditional request form to facilitate the committee’s decisions; what information was asked of vendors at the point of trial or initial interest; and how this fed into a new collection development policy. By revamping the workflows to ask for more information up front, the presenters were able to help the new Collections Committee obtain all the information needed for decision-making at the point of decision. The authors share insights into how organizational changes can be used as an opportunity to instigate workflow changes that help libraries acquire resources more nimbly and flexibly.