Reviewerly/exHarmony huggingface dataset:
Gilsonite Mineral Potential of Gilan-e Gharb to Qasr-e Shirin using FAHP-FTOPSIS Prediction Model

Gilan-e Gharb region has been located in the west of Iran and it has special features in terms of geology. Remote sensing data (satellite images), geology, tectonics and mineral data sets of the region were used to prepare an innovative integrated algorithm for the exploration of Gilsonite mineral. Effective criteria and sub-criteria in the exploration of this mineral were identified and evaluated according to the available exploration data. These criteria were weighted using analytical fuzzy hierarchical process and finally, using the method most similar to the ideal positive and negative solution were ranked in fuzzy environment to prepare a mineral potential map of Gilsonite in Gilan-e Gharb region. Accordingly, a potential map was produced using a combination of the above methods for optimal identification in the early stages of exploration of this valuable mineral to reduce the time, cost, and risk of exploration. Finally, field visit and investigation has been accomplished for the regions with a high potential of Gilsonite mineralization to evaluate the method. The results showed that 82% of the identified points have proper adjustment to the MPM. This high adaptation showed that the method is of good performance for use in Gilsonite exploration.
Risk and Complexity Assessment on the Context of Language Migration

Language Migration is a highly risky and complex process. Many authors have provided different ways to tackle down the problem, but it still not completely resolved, even-more it is considered almost impossible on many circumstances. Despite the approaches and solutions available, no work has been done on measuring the risks and complexity of a migration process based on the technological gap. In this article we contribute a first iteration on Language Migration complexity metrics, we apply and interpret metrics on an industrial project. We end the article with a discussion and proposing future works.
Real-Time Facial Expression Recognition Based on Attention Mechanism

This paper presents a novel method for solving Facial Expression Recognition (FER) task which integrates Manifold Regularization Dictionary Pair Learning and Intra-class Variation Reduced Feature (MRDPL-IVRF) model and Iterative Optimization Classification Strategy (IOCS). In the proposed framework, we firstly divide the facial image into overlapping patches. Weighted Patch-based Local Binary Patterns (WPLBP) is proposed for feature extraction by cascading the weighted LBP features from each patch, which highlights the informative facial regions. MRDPL-IVRF model is then adopted for robust sparse representation of facial features, where IVRFs are generated from the difference between query images and their corresponding approximation of each expression class, which can reduce the intra-class variations resulted by illumination and identity. Finally, IOCS is presented for expression classification which can explore the most unlikely class according to the maximum reconstruction residual. Different from traditional sparse coding classification scheme, our IOCS method iteratively removes irrelevant samples to obtain a more precise representation model, thus can further improve the recognition performance. The feasibility of our framework has been successfully tested on CK, CK+, SEFW, CMU-PIE and Multi-PIE databases. Furthermore, the experiments combining deep features shows that our model can be integrated with existing deep models and obtain better FER results.
Frank-Wolfe Algorithm for Learning SVM-Type Multi-Category Classifiers

Multi-category support vector machine (MC-SVM) is one of the most popular machine learning algorithms. There are lots of variants of MC-SVM, although different optimization algorithms were developed for different learning machines. In this study, we developed a new optimization algorithm that can be applied to many of MC-SVM variants. The algorithm is based on the Frank-Wolfe framework that requires two subproblems, direction finding and line search, in each iteration. The contribution of this study is the discovery that both subproblems have a closed form solution if the Frank-Wolfe framework is applied to the dual problem. Additionally, the closed form solutions on both for the direction finding and for the line search exist even for the Moreau envelopes of the loss functions. We use several large datasets to demonstrate that the proposed optimization algorithm converges rapidly and thereby improves the pattern recognition performance.
INTERACTION OF GIFTED PERSONALITY WITH ARTISTIC CULTURE WITHIN THE CONDITIONS OF OPEN EDUCATIONAL AND CULTURAL SYSTEMS: EXPERT ANALYSIS

The purpose of the article is to analyze the opportunities and prospects for the development of open educational and cultural systems in Ukraine, aimed at meeting the special cultural needs of gifted individuals. The methodology of the research is general scientific principles of systematization and generalization of the researched problem, as well as interdisciplinary approach, which allows to study the problem with wide involvement of scientific achievements from different fields of knowledge, including culturology, art history, theory and practice. socio-cultural activities. Methods of questionnaires, surveys and expert analysis of written documents and video courses revealed the peculiarities of the development of open educational and cultural systems. The scientific novelty of the study is to identify the features of the interaction of a gifted person with artistic culture, opportunities to activate its creative forces and intellectual abilities by engaging in open resources of education and culture. During the research, students of National Academy of Managerial Staff of Culture and Arts (Kyiv) were involved in working on the platforms "Coursera" and "Prometeus", after which their written feedback was analyzed. A survey of managers and specialists (hereinafter referred to as experts) working in the field of management, planning and development of artistic culture in Ukraine (2,100 respondent experts) was also conducted. The article presents the results of a study of the patterns of functioning of art (past, present and future) in the context of its impact on the cultural development of a gifted person; the possibilities of using the potential of open educational and cultural systems in order to meet the special cultural needs of a gifted person are analyzed. Conclusions. The results of the research work showed that in the process of interaction of a gifted person with art, there are certain problems in activating his creative forces and intellectual abilities, due to limited access to many types of artistic and creative activities in reality during quarantine. To this end, it is necessary to use the potential of open educational and cultural systems online, which contributes to the internalization and exteriorization of cultural values, meeting the cultural and artistic needs of the gifted individual in the structure of his professional activities and daily life; allows to more actively involve the young generation of Ukraine in virtual creativity, artistic design and modeling.
Scientific Competence in Preschool Education in Times of Pandemic: Theoretical Review.

The purpose of this review article is to know and reflect on how scientific competence is being developed in early childhood education, how teachers have been intervening to make the acquisition of competence in this area viable, contributing to the improvement of the community's progress. For the literature review, 26 articles were explored, being the database used Scopus, ESBCO and Scielo in English and Spanish. It was identified that the development of scientific competence in preschool age has lagged behind since before the beginning of the pandemic and is accentuated in this context; the need for teachers to renew themselves and fit into virtual teaching led to the training and empowerment of teachers on virtuality.
Oppugning Pause and Punctuation of Documentary Evidences in Encyclopedic Dictionary of Chinese Words·Huo Radicals(《汉语大词典·火部》)

The documentary evidences cited in Encyclopedic Dictionary of Chinse Words· Huo Radicals 《(汉语大词典·火部》) still should be discussed in terms of pause and punctuation. Through the review of some parts of documentary evidences of huo(火) radicals in the dictionary, we found that there are four main problems in the pause and punctuation, namely, the inappropriate interception of example sentences, the loss of the function words, the error of pause in the internal of some sentences and the error of punctuation in some sentences. Therefore, we suggest that the interception of the example sentences should be thought over carefully to avoid the fragmentation and redundancy of the first and last sentence in one sentence. At the same time, strengthen the collation and verification of the words, especially the formal meaning of the difficult words, clarify the internal relationship of the sentence, ensure the reliability of documentary evidences, together with the accuracy of pause and punctuation to effectively improve the quality of the dictionary.
SpatialViewer: A Remote Work Sharing Tool that Considers Intimacy Among Workers

Due to the influence of the new coronavirus disease (COVID-19), teleworking has been expanding rapidly. Although existing interactive remote working systems are convenient, they do not allow users to adjust their spatial distance to team members at will, %"Arbitrarily" is probably not the best word here. It means without apparent reason. A better expression might be "at will." and they ignore the discomfort caused by different levels of intimacy. To solve this issue, we propose a telework support system using spatial augmented reality technology. This system calibrates the space in which videos are projected with real space and adjusts the spatial distance between users by changing the position of projections. Users can switch the projection position of the video using hand-wave gestures. We also synchronize audio according to distance to further emphasize the sense of space within the remote interaction: the distance between projection position and user is inversely proportional to the audio volume. We conducted a telework experiment and a questionnaire survey to evaluate our system. The results show that the system enables users to adjust distance according to intimacy and thus improve the users' comfort.
Multivalent Graph Matching for Symbol Recognition

This paper deals with a symbol recognition problem where symbols are deformed in different ways. To address this difficulty, the multivalent graph matching problem is considered to allow more matching possibilities between the symbols. More precisely, a solution to the multivalent graph matching problem is formulated as an extended graph edit distance minimum with additional splitting and merging operations. This minimization problem is tackled with a variant of ant colony optimization, the max-min ant system. Besides, a neighborhood search strategy added to the solution building process of the max-min ant system aims to accelerate the computational time. The efficiency of the proposed approach is illustrated in a symbol dataset in several aspects, covering both quality and quantity analyses. The result shows the interest in using multivalent graph matching to deal with noisy symbols and their meaningful interpretability in the context of sub-part correspondence against other bijective graph matching-based approaches.
Survey of Sentiment Analysis and Its Impact on Data Extraction

With the advent of information exploration over the years, the most important thing to make the business decision is to consider the opinion of the people. Sometimes the opinions which are transformed to sentiments plays a vital role in the aforementioned areas. The opinion of the people is shared by the e-commerce, and social media networks like Twitter, Facebook, blogs, forums, etc. The opinion is categorized into positive, negative, and neutral opinion. To extract the sentiments, opinion there are different approaches available in the literature such as Support Vector Machine, Naïve Bayes, Neural Networks, lexicon based approaches, etc. In this paper, it is aimed at comparing different types of machine learning approaches, such as supervised, unsupervised, and semi-supervised learning algorithms, which are useful to extract the various opinions over the Net. It is further surveyed to understand various performance measures when the extracted opinions were transformed to sentiments.
Driving Product Sales Performance by Analysing Product Prelaunch in a Linguistics Approach

This paper uses a natural linguistics analytic approach, by studying product prelaunch events’ script, to investigate the determinants of driving the product sales based on customer values framework as well as “Nextopia” consumer psychology. This research contributes to the theoretical framework of identifying the customer values, which have impacts on the product sales. Moreover, we investigate how product sales be driven by the optimism attitude and affective forecasting feeling, which are vocal during product prelease events. Through the study of analysing the essential words, which represent the underlying customer values from the script of Apple Inc. product prelaunch events, we found that product functional and experiential/ hedonic of customer values drive product sales. Induced affective forecasting message negatively moderated the impact of cost/ sacrifices values on product sales. In addition to the theoretical contributions, this research provides practical guidelines of how to shape the product prelaunch speech to maximize the sales of the to-be-released products.
EU Parliament Speech corpus

A collection of 1040 EU parliament speeches with transcription and annotations. Includes original speeches and PL/EN translations.
The impact of media and social media on residents' perception of the frequency of crime occurences in Shah Alam: a multinomial logistic regression approach / Noor Syafiqah Ariffin, Nur Hanim Aziz and Nur Fadhilah Anis Mansor

This research was to determine the impact of media and social media on residents' perceptions of crime occurrences in Shah Alam. In addition, the researcher was interested to determine the extent to which perception of crime occurrences were related to the mass media. The information required for the study was obtained through a self¬ administered questionnaire distributed in public areas including shopping mall, mosque, food court, library and University in Shah Alam. By using convenience sampling method, 300 Shah Alam residents were selected as respondents. A Multinomial Logistic Regression analysis shows social media and media influenced their perceptions of how frequently crime occurs in Shah Alam. More specifically, social media had a greater influence on the resident's perception of crime occurrences in Shah Alam than media. In addition, gender, race and view social media posts on crime were significantly to the Shah Alam residents' perceptions of crime occurrences. The findings from this study provide insights to the citizens with information related to crime and how technology could be an element of interest and influence.
LibGuides: Scholarly Communication Toolkit (ACRL): Related Topics

Additional topics that relate to scholarly communication, including digital humanities, OER, and research data management.
Determination of conditions for motivating the development of key competencies of higher education students

The article defines the concept of "competence", which allows discussing the academic culture model as a set of educational competencies. As key competencies are not only a system of knowledge, skills and attitudes, but the ability to apply them in a specific situation to solve everyday problems effectively. In the process of professional development in higher education, how competencies are designed from the objectives of the courses, expanding the personal and social experience in the area of knowledge and beyond. It is concluded that the conditions for the development of competencies should not be well used, since they are provocations from the field of knowledge.
The phenomenon of professional competence of a teacher: the main trends of formation

The article defines the concept and specifics of the phenomenon of professionalization of activities. The features of professionalization of the activity of a teacher of vocational training are characterized. The possibilities of professional competence as a way of solving the problem of professionalization of the teacher's activity have been determined, criterion characteristics determined, on the one hand, by the level of professionalism of the teacher's personality, on the other hand, themselves act as determinants of efficiency in achieving acme and self-realization.
When in Doubt, Ask: Generating Answerable and Unanswerable Questions, Unsupervised

Question Answering (QA) is key for making possible a robust communication between human and machine. Modern language models used for QA have surpassed the human-performance; however, these models require large amounts of human-generated training data which are costly and time-consuming to create. This paper studies augmenting human-made datasets with synthetic data as a way of surmounting this problem. A state-of-the-art model based on deep transformers is used to inspect the impact of using synthetic answerable and unanswerable questions to complement a well-known human-made dataset. The results indicate a tangible improvement in the performance of the language model (measured in terms of F1 and EM scores) trained on the mixed dataset. Specifically, unanswerable question-answers prove more effective in boosting the model: the F1 score gain from adding to the original dataset the answerable, unanswerable, and combined question-answers were 1.3%, 5.0%, and 6.7%, respectively. Repository of this paper: github.com/lnikolenko/EQA .
Intrinsic Schreier special objects

Motivated by the categorical-algebraic analysis of split epimorphisms of monoids, we study the concept of a special object induced by the intrinsic Schreier split epimorphisms in the context of a regular unital category with binary coproducts, comonadic covers and a natural imaginary splitting in the sense of our article [Intrinsic Schreier split extensions, Appl. Categ. Structures 28 (2020), 517--538]. In this context, each object comes naturally equipped with an imaginary magma structure. We analyse the intrinsic Schreier split epimorphisms in this setting, showing that their properties improve when the imaginary magma structures happen to be associative. We compare the intrinsic Schreier special objects with the protomodular objects, and characterise them in terms of the imaginary magma structure. We furthermore relate them to the Engel property in the case of groups and Lie algebras.
Multi-Stage Attention-Enhanced Sparse Graph Convolutional Network for Skeleton-Based Action Recognition

Graph convolutional networks (GCNs), which model human actions as a series of spatial-temporal graphs, have recently achieved superior performance in skeleton-based action recognition. However, the existing methods mostly use the physical connections of joints to construct a spatial graph, resulting in limited topological information of the human skeleton. In addition, the action features in the time domain have not been fully explored. To better extract spatial-temporal features, we propose a multi-stage attention-enhanced sparse graph convolutional network (MS-ASGCN) for skeleton-based action recognition. To capture more abundant joint dependencies, we propose a new strategy for constructing skeleton graphs. This simulates bidirectional information flows between neighboring joints and pays greater attention to the information transmission between sparse joints. In addition, a part attention mechanism is proposed to learn the weight of each part and enhance the part-level feature learning. We introduce multiple streams of different stages and merge them in specific layers of the network to further improve the performance of the model. Our model is finally verified on two large-scale datasets, namely NTU-RGB+D and Skeleton-Kinetics. Experiments demonstrate that the proposed MS-ASGCN outperformed the previous state-of-the-art methods on both datasets.
PENGARUH INTERAKSI, KEHADIRAN PENGAJAR DAN KEHADIRAN SOSIAL TERHADAP KEPUASAN PEMBELAJARAN ONLINE PADA MATA PELAJARAN EKONOMI DI SMA NEGERI 13 SURABAYA PADA MASA COVID-19

Abstract Online learning satisfaction in students is the most important thing in determining a successful learning, learning satisfaction can be influenced by interaction, the presence of teachers, and social presence. Good online learning will support student learning satisfaction. The purpose of this study was to analyze whether there was an effect of interaction, teacher presence and social presence on online learning satisfaction in economic subjects at SMA Negeri 13 Surabaya during the Covid-19 period. The research subjects in this study were class X and XI IPS SMA Negeri 13 Surabaya which contained economic subjects with a total of 271 students. Data were collected using an instrument in the form of a questionnaire. The data analysis in this study used Structural Equation Modeling (SEM) using the WarpPLS version 7.0 software. The results of this study indicate that (1) The interaction has a significant effect on online learning satisfaction. (2) The interaction has a significant effect on social presence, (3) The presence of the teacher has no effect on online learning satisfaction (4) the presence of the teacher has a significant effect on social presence and (5) Social presence has a significant effect on online learning satisfaction. (6) significant interaction has an indirect effect on online learning satisfaction through social presence. (7) The presence of the teacher indirectly has no significant effect on online learning satisfaction through social presence. Keywords : Interaction, Teacher Attendance, Social Presence, and Online Learning Satisfaction
Оценка результатов обучения в рамках академической мобильности: национальный и международный опыт

The article presents the results of the analysis of national and international experience in assessing learning outcomes. Examines the main problems of assessing learning outcomes by belarusian higher education institutions and some aspects of newapproaches.
Challenges in Using AI in Online Commerce

With the sharp rise in digitalization, we see an increase in human-machine interaction. In the context of the pandemic, online commerce has risen sharply and so have the challenges both retailers and customers face. This article explains the role of Industry 4.0 in accelerating economic development in general, it defines the categories of bots (robots) that can be used in different types of activities/services, it presents the challenges, advantages - disadvantages of technology and of artificial intelligence use in global development. We present an analysis of the current general situation while investigating the future trends regarding the increasingly accelerated use of artificial intelligence in industry and services. The article is based on studies conducted during this period regarding the role of artificial intelligence in the current economic context, as well as those regarding the human-machine relationship. It represents a kind of explanatory research on this huge challenge caused by unprecedented scientific and technological development.