Reviewerly/exHarmony huggingface dataset:
SATISFACTION OF UNIVERSITY STUDENTS WITH PHYSICAL EDUCATION AND SPORTS COURSES. ALTERNATIVE METHODS OF SOCIOLOGICAL RESEARCH (ON THE EXAMPLE OF METAMORPHIC MODELS)

Currently, the social well-being of Russian citizens, the quality of life of its residents, are the subject of numerous sociological studies. The results obtained provide the opportunity to make adjustments to the state policy in the social sphere. Studies that identify key social problems of the young generation of Russians are especially important. One of the most acute problems is the quality of education. Educational institutions realize the importance of this issue. They carry out numerous surveys, questionnaires and focus groups among students and educators, and seek the opinion of the expert community. Of course, such studies provide an overview of the key issues, but they are mainly based on traditional methods that are well known to both educators and students. As a result, participants are not always ready to provide objective information, which ultimately affects the quality of research. This situation requires the use of modern research methods both in the field of sociology and in the field of marketing. The purpose of the study: to identify determining factors for the lack of satisfaction of students with physical education at the university. This will increase motivation for attendance of physical education classes at the university. Methods and organization of research: We used the focus group [1] method with elements of the metamorphic method to obtain reliable information about the attitude of students to the "Physical culture" course. The study consisted of two stages. At the first stage, participants visually displayed their attitude to the "Physical culture" course. At the second stage, respondents were asked additional questions. Results. The main factors that contribute to willingness to attend the "Physical culture" course are: the ability to choose the type of activity during classes and characteristics of the educator. At the same time, we revealed the factors that repel from attending the "Physical culture" course. This is an infrastructure and not appropriate time for physical education according to students’ opinion. Conclusion. The research revealed the attitude of students to the "Physical culture" course. It helped to understand how to enhance willingness to attend these classes.
Neural Knowledge Base Repairs

The curation of a knowledge base is a crucial but costly task. In this work, we suggest to make use of the advances in neural network research to improve the automated correction of constraint violations. Our method is a deep learning refinement of [], and similarly uses the edits that solved some violations in the past to infer how to solve similar violations in the present. Our system makes use of the graph content, literal embeddings, and features extracted from Web pages to improve its performance. The experimental evaluation on Wikidata shows significant improvements over baselines.
MotionNet architecture with Randomized Emission training strategy for adaptive bit rate video compression

The traditional methods of video compression are hand designed and fundamentally based on frame prediction strategies. Even though they are working efficiently but significant improvements have been observed by some deep learning based enhancements. In the way, to explore pure deep learning based approaches, the commendable performance motivated further research in the same domain. Adaptive bit rate representation of the videos is preferred over fixed bit representation providing flexibility for adjusting video quality with varying bandwidth in addition to efficient bit utilization. The proposed pure deep learning video compression architecture comprises of frame autoencoder and motion prediction network to propagate motion information for reconstruction of predicted frames. The network was trained with both fixed and random emission steps independently. The experimental results reveal that randomized emission training strategy gives better results for adaptive bit-rate video compression when compared in SSIM, PSNR, EPE and TPF performance parameters.
What Can 100,000 Books Tell Us about the International Public Library e-lending Landscape?

Introduction: We investigated the relative availability of e-books to libraries for e-lending in five English-language countries, and analysed their licence terms and prices. Method: We created a unique dataset recording author, publisher, price and terms for 100,000 titles and 388,045 e-lending licences across Australia, New Zealand, Canada, the United States and United Kingdom via aggregator Overdrive. We developed new algorithms to estimate the original publication year for each title, and to match titles across jurisdictions.Analysis: We examined the relationships between title price, age, terms, jurisdiction, publisher and publisher type using various statistical analyses and machine learning. Results: Price and licence differences across countries are largely attributable to ‘Big 5’ publishers. Prices are largely independent of title age (unless the title is in the public domain) or the rights libraries obtain in exchange. Licence terms are not affected by age either, meaning that the most restrictive terms are often applied to older, less demanded books. Conclusions: By setting terms independent of titles’ value to libraries, publishers may discourage libraries from adding older and less-demanded books to their collections. We will test this hypothesis in a follow-up library survey.
TRABAJO CON PROYECTOS: INNOVACIÓN PARA PROMOVER MODOS DE ACTUACIÓN INTEGRADOR EN PROFESORES DE LENGUAS EXTRANJERAS

The present article systematizes the project work impact, in the period 2010-2018, through a qualitative approach carried out in Foreign Languages pre-service education at the Central University  Marta Abreu  de Las Villas, Cuba. This article defends the idea that project works are innovations that potentiate the development of comprehensive professional performance since they are intended to contribute to the concrete fulfillment of the functions. Although perfectible, the work will contribute to have better prepared professionals in the education field able to face the challenges of the 21st century.
Laplacian Pyramid Adaptive Residual Network Satellite Image Super-Resolution

Aiming at the application of super-resolution reconstruction of Tiangong-1 satellite image, a deep structure model of Laplacian pyramid adaptive residual network is proposed. In the research of this paper, the popular residual module is improved to make full use of the feature information with all convolutional layer in the residual block to improve the image quality; propose the Laplacian pyramid structure, deepen the network structure and strengthen the image features extraction ability, thereby extracting more image features; propose feature adaptive selection structure, through the feature adaptive selection structure layer to adaptively optimize the image features, enhance the quality of the reconstructed image. The experiment of Tiangong-1 images shows that the Laplacian pyramid adaptive residual network proposed in the study has high PSNR and SSIM values in the application of satellite image super-resolution reconstruction, and the band shift is smaller, which has high application value and deeper research significance.
LibGuides: Missouri A&OER Symposium: Code of Conduct

All the information attendees need for the March 2021 Missouri Affordable & Open Educational Resources Symposium.
Tokens, 'Smart Contracts' and System Governance

Cryptocurrencies embodied or represented in a “smart contract”, at first glance may be a new asset class, where depending on the internal method of classification and use different frameworks may be applicable. Although, most concepts are not necessarily new (inventive). As the digitalization of databases, information and systems do not change, the underlying object. It is analyzed, in particular, the case of payments tokens (contrasting with other forms of - public - money, in a narrow sense, so as with the hybrid cases, so-called “stable coins”), across jurisdictions, namely Switzerland, the UK, Germany and the US (as having most of the regulatory response or litigation), besides Portugal. It is broken down from the micro-level (token) to its exchange (as a means of exchange in a given contract) and infrastructure (messages, communications and infrastructure). There is a need to go beyond the formal representation (and dimensions) of a given entity, or the problem of knowledge representation and the need of (actual) systematic approach, to access function (rather than formal representation) and governance of the blockchain infrastructure.
Monitoring General Education: Sociological Aspects [Мониторинг Общего Образования: Социологические Аспекты]

The scientific report presents the results of a monitoring study of the effectiveness of general education conducted by the Center for Continuing Education Economics of the RANEPA in 2013–2018. The participants of a sociological survey of the sixth monitoring wave of 2018 were 40 school principals, 2195 representatives of households, 2077 teachers of educational institutions located in urban settlements and rural areas of the Chelyabinsk region, Altai and Stavropol areas, as well as in St. Petersburg. The positions of teachers on a wide range of issues related to general education are considered: the staffing situation in schools, the quality of teaching, the requirements of families for the organization of the educational process, the satisfaction of teachers with their professional activities. Monitoring research is based on assessments of participants in educational relations and is one of the key resources for managing change in education and improving the performance of schools.
PROBABILISTIC FRAMEWORK FOR LOSS DISTRIBUTION OF SMART CONTRACT RISK

Smart contract risk can be defined as a financial risk of loss due to cyber attacks on or contagious failures of smart contracts. Its quantification is of paramount importance to technology platform providers as well as companies and individuals when considering the deployment of this new technology. That is why, as our primary contribution, we propose a structural framework of aggregate loss distribution for smart contract risk under the assumption of a tree-stars graph topology representing the network of interactions among smart contracts and their users. To our knowledge, there exist no theoretical frameworks or models of an aggregate loss distribution for smart contracts in this setting. To achieve our goal, we contextualize the problem in the probabilistic graph-theoretical framework using bond percolation models. We assume that the smart contract network topology is represented by a random tree graph of finite size, and that each smart contract is the center of a random star graph whose leaves represent the users of the smart contract. We allow for heterogeneous loss topology superimposed on this smart contract and user topology and provide analytical results and instructive numerical examples.
Research Guides: SJU Library Streaming Video Resources: Ambrose Digital Streaming Video

Overview of the streaming video content providers currently available for SJU campus members through the library.
The economics of development

A leading development economist in the postcolonial era, E. Wayne Nafziger was an energetic researcher (sub-Saharan Africa, Japan, India), a prolific author (19 books, many articles and lectures), and an esteemed teacher and graduate student mentor (chair of 22 dissertations). Although his analyses of economic and social development incorporated all the conventional factors of Gross National Product, Gross Domestic Product, monetary and investment policies, class differentiation, and the relationship between agriculture and industrial sectors in national economies, usually in a comparative perspective, he persistently addressed the obstacles to development brought about by inequality, injustice, war, and manipulation by elites of resources to their own benefit at the expense of the marginalized. The values and priorities of his Mennonite upbringing and college education shone through his scientific rigor to offer a nuanced understanding of the importance of empowering and enabling the poor as the most effective path to sustainable development.
ADAPTIVE PHYSICAL EDUCATION AS A NECESSARY COMPONENT OF STUDENTS ' PHYSICAL DEVELOPMENT

The article presents the results of a study on the need to introduce adaptive physical education in schools of Zolotukhinsky district. Adaptive physical education is a necessary component of both physical and social development of the student. For conducting adaptive physical education classes, an annual plan is drawn up, which reflects the number of hours for classes, topics, and the planned result. The article deals with the problems of introducing adaptive physical education, the possibility of an educational organization to have full-time teachers with special education.
Technical Terminology and Argument Analysis and Appraisal

This chapter examines the contention of Michael Scriven that post-secondary courses designed to enhance students’ skills in analyzing, evaluating and using arguments should not employ the technical vocabularies of specialized theories of argument. Scriven contends that the resources of ordinary language are adequate for these purposes and the reliance on technical terminology would block the possibility of communication among those unfamiliar with one another’s theories. In order to assess this position I first attempt to clarify what constitutes a technical term. I next examine what sorts of technical terms in argument theory Scriven might take issue with. I argue that the learning objectives of the sort of course Scriven has in mind can be met using the resources of a non-technical vocabulary. Moreover, the use of any technical vocabulary brings with it a commitment to the theoretical baggage that any such terminology presupposes, implying that Scriven is envisaging a theory-free or theory-neutral pedagogy. I argue that the “non-technical” language of everyday natural language embodies a folk theory of argument in at least three respects. It presupposes a foundationalist epistemology; adopts an eclectic approach to logic; and assumes that the assignment of the burden of proof is open to negotiation.
PERANCANGAN DAN IMPLEMENTASI STORAGE BERBASIS CLOUD PADA PERUSAHAAN PT INDONESIA WEDA BAY INDUSTRIAL PARK

AbstractWith limited storage media space, damage to storage hardware and sensitive data against viruses and malware also efficiency in the process of data exchange become a problem experienced by every employee of the office of PT. Indonesia Weda Bay Industrial Park. Separation of data between employee PCs causes the need for other extra storage media in the form of a flash drive to exchange data. Therefore we need a centralized and secure storage media that can be accessed anytime and anywhere. This makes cloud storage a solution and alternative to overcome these problems. The methods used in this study include the analysis of problems and needs, design, and implementation. The cloud storage service is designed by using Google Drive as a cloud storage technology platform. The implementation process is by registering and configuring each user's access to the storage directory. Implementation results show users can easily upload and download files also record any additions or changes to the contents of the file.
Uncertainty for deep image classifiers on out of distribution data.

In addition to achieving high accuracy, in many applications, it is important to estimate the probability that a model prediction is correct. Predictive uncertainty is particularly important on out of distribution (OOD) data where accuracy degrades. However, models are typically overconfident, and model calibration on OOD data remains a challenge. In this paper we propose a simple post hoc calibration method that significantly improves on benchmark results [Ovadia et al 2019] on a wide range of corrupted data. Our method uses outlier exposure to properly calibrate the model probabilities.
High-Likelihood Area Matters --- Rewarding Correct,Rare Predictions Under Imbalanced Distributions

Learning from natural datasets poses significant challenges for traditional classification methods based on the cross-entropy objective due to imbalanced class distributions. It is intuitive to assume that the examples from rare classes are harder to learn so that the classifier is uncertain of the prediction, which establishes the low-likelihood area. Based on this, existing approaches drive the classifier actively to correctly predict those incorrect, rare examples. However, this assumption is one-sided and could be misleading. We find in practice that the high-likelihood area contains correct predictions for rare class examples and it plays a vital role in learning imbalanced class distributions. In light of this finding, we propose the Eureka Loss, which rewards the classifier when examples belong to rare classes in the high-likelihood area are correctly predicted. Experiments on the large-scale long-tailed iNaturalist 2018 classification dataset and the ImageNet-LT benchmark both validate the proposed approach. We further analyze the influence of the Eureka Loss in detail on diverse data distributions.
Katakana and Japanese National Identity. The Use of Katakana for Japanese Names and Expressions

This paper examines Japanese names and expressions written using katakana in the contemporary Japanese media and their relation to Japanese national identity. In modern Japanese, katakana is normally used for Western loanwords as well as certain mimetics and phonetic annotations. However, it is observed that today some Japanese  words are also written in katakana. They include place names associated with past tragedies such as Hiroshima, Nagasaki, or Fukushima, as well  as  names  and  expressions  associated with internationally renowned Japanese culture such as Kurosawa, Kitano, Murakami, samurai, etc. The use of katakana for these words reflects the awareness of the Japanese that they are known to the world outside Japan. Such words are treated as if they were ‘re-imported’ to Japan following their acceptance as loanwords abroad. It  also involves a change in perception of certain historical events or cultural products from something seen and discussed within Japan to something that is exposed to external eyes. In other words, when the script type is shifted to katakana, the gaze looking at Japan from within is replaced by a gaze looking at Japan from without. This shift is important in understanding the current dynamics of Japanese identity negotiation. Drawing on media accounts, the paper will analyse recurrent wordings in the news media to reveal: 1) the types and characteristics of Japanese words and expressions written in katakana, 2) how those specific words are associated with Japanese national consciousness and 3) images of Japanese identity suggested by the use of katakana. It will be argued that Japanese words in katakana represent images that the Japanese themselves project onto the eyes of the external world. Through the examination of the primary data extracted from media sources, the ultimate goal of the paper is to contribute to the understanding of Japanese national identity and its representation in contemporary media.
Decoupling State Representation Methods from Reinforcement Learning in Car Racing

In the quest for efficient and robust learning methods, combining unsupervised state representation learning and reinforcement learning (RL) could offer advantages for scaling RL algorithms by providing the models with a useful inductive bias.For achieving this, an encoder is trained in an unsupervised manner with two state representation methods, a variational autoencoder and a contrastive estimator.The learned features are then fed to the actor-critic RL algorithm Proximal Policy Optimization (PPO) to learn a policy for playing Open AI's car racing environment.Hence, such procedure permits to decouple state representations from RL-controllers.For the integration of RL with unsupervised learning, we explore various designs for variational autoencoders and contrastive learning.The proposed method is compared to a deep network trained directly on pixel inputs with PPO.The results show that the proposed method performs slightly worse than directly learning from pixel inputs; however, it has a more stable learning curve, a substantial reduction of the buffer size, and requires optimizing 88% fewer parameters.These results indicate that the use of pre-trained state representations has several benefits for solving RL tasks.
Analysis on the Development of Innovative Education in Colleges and Universities from the Perspective of Cultural Confidence

With the rapid development of China, the environment of contemporary college students is diversified, informationized and complicated, and their outlook on life, values and world view are gradually influenced by the characteristics or cultures of different fields. Therefore, the establishment of cultural self-confidence of college students has become an indispensable part in the development of innovative education in colleges and universities. As an important factor for the growth and development of college students, innovation education in colleges and universities should be improved in the process of ideological and political education, professional teaching and innovation training. The purpose of this paper is to propose meaningful Suggestions and views on the future teaching mode, innovative talent cultivation and school-enterprise cooperation in colleges and universities based on the results of field investigation and questionnaire survey of the research group and the current situation and existing problems of China's college education innovation and development.
HUMAN4D: A Multimodal Human-Centric Dataset for Motion & Volumetric Capture

HUMAN4D constitutes a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by a professional marker-based MoCap, a volumetric capture and an audio recording system.
Determination of quantitative indicators of earthquake destruction by different time space images

Summary Throughout history, natural disasters have constantly plagued humanity, the greatest damage was caused by earthquakes, taking many lives, destroying cities and infrastructure. Determining the results of an earthquake, namely damages and destructions of buildings is one of the main needs in dealing with the consequences of a natural disaster. Recently, natural disasters caused by anthropogenic phenomena have increased in the world. Therefore, the scientific study of the destructions caused by cataclysms of natural origin is an extremely important problem. Involvement of digital photogrammetry and geoinformation technologies is very effective in this matter. The area that has been destroyed on a large scale on the Earth&apos;s surface needs to be determined with the help of satellite images and remote sensing data. The main purpose of the work is the processing of digital satellite images obtained from the GeoEye-1 satellite on 15.07.2017 and 18.11.2017, in order to identify areas affected by the earthquake on the border of Iraq and Iran. Namely, part of the city of Sarpol-e Zahabb, located in Iran. When performing the work, a comparison of the automatic and manual methods was used. During the experimental studies, photogrammetric, cartographic methods and methods of remote sensing of the Earth were used. The work was performed using the Erdas Imagine software and he Delta CUE module. The technique of determining the difference indicators of the earthquake consequences by the automatic method is described. The results of the work can be used to calculate losses after natural disasters. As the results of detecting the area of damaged objects due to the earthquake it was found in automatic mode that 61 objects were damaged, and the total area of damage is 19103m2, the area of the largest object is 3300m2.