Reviewerly/exHarmony huggingface dataset:
CONTENT-PROCESS ASPECTS OF PROFESSIONAL SELF-CREATION OF FUTURE EDUCATION MANAGER

The article is devoted to the problem of professional creation of a future education manager.The content of the concept "education management" is disclosed.The specifics of the specialty "education manager" are shown and the need for training management personnel for all links of the education system in the country is substantiated.The author's approach to the content of professional training of future managers is presented, in particular, the necessity of solving the problem of professional self-creation as a promising direction for improving the quality of professional training of qualified specialists for the field of education management is substantiated.The content-procedural aspects of the professional self-creation of future education managers have been analyzed and interpreted.For this purpose, such personal self-processes as: self-organization, self-regulation, self-presentation, self-image, self-management, self-marketing are considered.They ensure the effectiveness of professional creation of a specialist in the sphere of management.Under the influence of these self-processes, favorable conditions are created for the personal and professional development of a future manager in the field of education, prerequisites for career growth and profitable promotion of a specialist in the labor market in conditions of educational competition arise.
Mining Unexpected Sequential Patterns from MOOC Data

Massive Open Online Courses (MOOCs) are triggering a revolution in education, and the learning data accumulated by MOOC platforms contain a huge wealth of information for improving online learning effects. To improve learners' experience, we propose an algorithm for mining unexpected sequential patterns. First, we design unexpected support to replace support. Unexpected support also satisfies the downward closure property and ensures that each input sequence does not contribute equally to the measurement of sequential patterns. Second, we introduce an item list and sequence list according to the characteristics of MOOC data. The lists not only speed up the generation of new candidates but are also used for narrowing the search space. Third, we describe and explain the proposed algorithm FAST-USP in detail. Finally, we report the experimental results on efficiency, memory consumption, and the number of results, which demonstrate the superiority of the FAST-USP algorithm.
Semiotics of Advertising Communication in WEB 2.0 Network Social Services

The article is devoted to the study of semiotics in the advertising communication of web 2.0 network social services. The purpose of the article is to analyze the publications of various brands on social Internet services focused on communication with the consumer and the subsequent study of the features of the use of semiotics tools. The relevance of the article is due to the fact that the modern information society has increased interest in semiotic systems, including in the field of Internet communication. The modern vision of semiotics has gone beyond the traditional framework and defined it as part of global and local communication in web 2.0 social network services, not only between Internet users, but also in the areas of B2B and B2C. The study of the possibilities of semiotics in advertising communication on web 2.0 social platforms, using the example of search engine applications, the social network Instagram, and company sites, in this article is based on the works of R. Barthes, J. Baudrillard, Y. Lotman, and U. Eco. This material confirms our hypothesis that today, especially since the beginning of the pandemic, communication on web 2.0 services is not limited only to text with a picture/photos or videos, more and more often there are visualized scenes created with the help of graphic design with the use of symbols and iconic signs that are familiar to the consumer, which he easily decodes, since they are inscribed in his socio-cultural coordinate system. The innovation of the research is based on the fixation of modern criteria of advertising Internet communication: polycode, intertextuality and multimedia, used as a way of working with target audiences. The novelty of the material consists of the understanding that semiotics today is a new look not only at the branch of scientific knowledge, but also at the practical possibilities of sign systems in the digital age, when the sign becomes a part of the socio-cultural space, a trend of the global world, a tool for transmitting information, knowledge, positioning, a tool for manipulation, influence, and attracting attention. Thus, brands working with the audience in todays realities should take into account not only the product preferences of consumers, but also broadcast their social / civic activity.
Period Classification in Chinese Historical Texts

In this study, we study language change in Chinese Biji by using a classification task: classifying Ancient Chinese texts by time periods.Specifically, we focus on a unique genre in classical Chinese literature: Biji (literally "notebook" or "brush notes"), i.e., collections of anecdotes, quotations, etc., anything authors consider noteworthy.Biji span hundreds of years across many dynasties and conserve informal language in written form.For these reasons, they are regarded a good resource for investigating language change in Chinese (Fang, 2010).In this paper, we create a new dataset of 108 Biji across four dynasties.Based on the dataset, we first introduce a time period classification task for Chinese.Then we investigate different feature representation methods for classification.The results show that models using contextualized embeddings perform best.An analysis of the top features chosen by the word n-gram model (after bleaching proper nouns) confirms that these features are informative and correspond to observations and assumptions made by historical linguists.
Learning Multimedia Management Strategy at Home During Learning from Home

The extraordinary development of technology followed by changes in human life in all fields also impacts the behavior of technology users and consumer behavior than multimedia, all of which have accelerated changes both in terms of multimedia transformation and in the form of business models that use multimedia. This study will discuss how multimedia strategies and their sustainable governance will impact distance learning that has been practiced so far as part of the effort to respond, namely learning from home. Because the impact of this media is quite significant, the parties, including parents who have to guide their children's learning, must also get a good understanding of how their strategy is to manage multimedia management for their children's learning considering that today multimedia technology has become like food that must be adequately served, really not contaminated with viruses or other toxins. This study utilizes data from the latest findings from previous publications from the book, journals, and other websites that contribute to the voice of technology and its impact on its users. Based on the results of the study of these data sources and a very detailed discussion, we finally got a new entry where parents must gain an understanding of multimedia applications and also how to use them and their uses so that parents and students can take advantage of multimedia for their learning success and life.
WhatsApp e o contexto discursivo como prova de violência contra a Mulher

n Brazil, the ‘Maria da Penha’ law (Law 11.340, of August 7, 2006) isconcerned with the crime of feminicide and it creates mechanisms to protect wo-men who are victims of psychological and/or physical violence. Despite this law,the number of femicides increases daily. In 2015, the Map of Violence estimatedthe number of femicides at 4.8% per 100,000 women – one murder every 90 minutesand 5 beatings every 2 minutes – which placed Brazil in fifth place. The documentshowed that we had with the rise of the extreme right spreading patriarchal andsexist propaganda, a 30% increase in acts of violence against women is expected.However, states of violence and psychological violence caused by abusive relati-onships are not counted in these data. Within social media, there are countlesssemioses that denounce violence and abuse, which could be used as evidence incourt, and even to prevent deaths. This article analyzes discursive stylistic markspresent in WhatsApp messages exchanged between a victim of femicide and herbest female friend – that indicate a state of violence, possible physical and psy-chological violence – in a case which had wide national repercussion. We useDiscourse Analysis applied in a forensic linguistics context to discuss the crime ofhomicide, using as theoretical support van Dijk (2012), Charaudeau (2001), Cano(2012), and Sousa Silva and Coulthard (2016). The analysis raises interesting lin-guistic issues such as the concepts of “context” that evidence constant situationsof state of violence within the interaction process.
GML_DT: A Novel Graded Multi-label Decision Tree Classifier

The goal of Graded Multi-label Classification (GMLC) is to assign a degree of membership or relevance of a class label to each data point.As opposed to multi-label classification tasks which can only predict whether a class label is relevant or not.The graded multi-label setting generalizes the multi-label paradigm to allow a prediction on a gradual scale.This is in agreement with practical real-world applications where the labels differ in matter of level relevance.In this paper, we propose a novel decision tree classifier (GML_DT) that is adapted to the graded multi-label setting.It fully models the label dependencies, which sets it apart from the transformation-based approaches in the literature, and increases its performance.Furthermore, our approach yields comprehensive and interpretable rules that efficiently predict all the degrees of memberships of the class labels at once.To demonstrate the model's effectiveness, we tested it on real-world graded multilabel datasets and compared it against a baseline transformationbased decision tree classifier.To assess its predictive performance, we conducted an experimental study with different evaluation metrics from the literature.Analysis of the results shows that our approach has a clear advantage across the utilized performance measures.
Image-based Positioning Technology: The Research, Development and Demonstration

ディジタルトランフォーメーションにおいては,われわれが存在するフィジカル空間とデータを処理する仮想のサイバー空間の間で情報を収集し還元することで新たな価値を生み出している.その際フィジカル空間での正確な位置と姿勢は,空間を密に紐づける重要な情報になる.そこでわれわれは精度に優れ姿勢も推定可能な画像に基づく測位手法(VPS: Visual Positioning System/Service)の研究開発を行ってきた.提案する局所特徴の方式は,天気や時間による日照変化に頑健で正確な3D点群地図を生成し,位置姿勢推定精度を向上する.また,その技術を基に開発したVPSシステムは,日照変化や類似構造が多い室内や屋外でも動作し,屋内では約8cm,屋外でも約46cmの推定精度を実現した.また本システムを活用した一般者向けの実証実験も行っており,技術の改善に加え新たな体験を生み出す活動にも取り組んでいる.
Local and International Factors Affecting Participation of Tanzanian Small and Medium Enterprises in Market Opportunity Brought by the African Growth and Opportunity Act (AGOA)

The study aimed at assessing local and international factors that affect participation of Tanzanian Small and Medium enterprises in market opportunity brought by African Growth and Opportunity Act (AGOA). The study focussed on Tanzania local SMEs engaged in garments and textiles, handicrafts, leather goods, footwear and agro-processing subsectors. The study utilized mixed approach methods and involved a total of 129 respondents. Questionnaire and interview were the main tools for data collection. Information was collected from the owners and marketers of SMEs located in Dar es Salaam, the officials of Ministry of Industry and Trade as well as the Tanzania Ministry of foreign Affairs and East Africa Cooperation. Quantitative data was analysed using SPSS software and qualitative data was examined using MAXQDA software. Findings revealed that both local and international related factors were inhibiting Tanzanian SMEs from engaging in the AGOA market. Such factors have been narrated in this paper and recommendations have been given in order to increase engagement of Tanzanian SMEs in the AGOA market.
Current Balancing Random Body Bias in FDSOI Cryptosystems as a Countermeasure to Leakage Power Analysis Attacks

This paper identifies vulnerabilities to recently proposed countermeasures to leakage power analysis attacks in FDSOI systems based on the application of a random body bias. The vulnerabilities are analyzed and the relative difficulty to obtain the secret key, once the vulnerabilities are taken into account, are compared to the original proposals. A new countermeasure, based on a new body bias scheme, is then proposed. The new countermeasure is based on the equalization of asymmetries in static power consumption dependent on data being stored in registers implemented in FDSOI technology. The countermeasure’s effectiveness is theoretically established through the development of a power model based on technological parameters, and further reinforced through numerical simulations of a dummy cryptosystem implementing part of an AES encrypting round.
Design and Validation of an Instrument to Measure Educational Innovations in Primary and Pre-Primary Schools

The creation and implementation of innovation proposals in education can provide a new key towards sustainable development. We are aware that schools perform very different innovations but often, with very low levels of impact and dissemination in their community. There are not many studies that describe, put a value on, categorize or analyse the innovations. This study sought to gain insight into the ICT innovations produced in Spanish primary and pre-primary schools. A quantitative approach based on a questionnaire was used to collect the data, named MANEDUIN, completed by 86 teachers selected by stratified random sampling (public - private, rural - urban). The reliability and the construct-related validity was evaluated from the questionnaire and the validity of content decided by means of experts’ judgment. Our findings point to a good consistency in the questionnaire (Cronbach’s Alpha: 0.848). The descriptive statistics and the analysis were made by factorial categories. The results of the factorial analysis confirm the dimensions proposed in the design of the questionnaire in the categories of the factors included in the innovation (social cohesion, interaction with the community, technologies, and success), the innovative schools and their characteristics, the topic and the type of innovation (on resources, direction, materials and time), as well as the obstacles to the innovation. This paper concludes that the questionnaire MANEDUIN is a valid and reliable tool to measure the management of schools’ innovations.
Improving Synonym Recommendation Using Sentence Context

Traditional synonym recommendations often include ill-suited suggestions for writer's specific contexts.We propose a simple approach for contextual synonym recommendation by combining existing human-curated thesauri, e.g.WordNet, with pre-trained language models.We evaluate our technique by curating a set of word-sentence pairs balanced across corpora and parts of speech, then annotating each word-sentence pair with the contextually appropriate set of synonyms.We found that basic language model approaches have higher precision.Approaches leveraging sentence context have higher recall.Overall, the latter contextual approach had the highest F-score.
Editors’ Introduction: Best Papers from the 18th International Conference on Cognitive Modeling

The International Conference on Cognitive Modeling brings together researchers from around the world whose main goal is to build computational systems that reflect the internal processes of the mind. In this issue, we present the four best representative papers on this work from our 18th meeting, ICCM 2020, which was also the first meeting to be held virtually. Two of these papers develop novel techniques for building larger and more complex models using Reinforcement Learning and Learning By Instruction, respectively. The other two show how cognitive models connect to neuroscience, drawing on details of the hippocampus and cerebellum to constrain and explain the cognitive processes involved in memory and conditioning.
Gender Classification from Facial Images

Gender is one striking feature that human can deduce effortlessly when looking at a face. Here, we try to classify the gender (male or female) based on the face images. The first part of this paper presents a review of different methods/approaches used for gender recognition. We present a comparative analysis for gender recognition using PCA, 2dPCA and its variants. Finally, we develop an iterative model using 2dPCA which updates itself when new samples are encountered. This model is expected to be fruitful in real-life situation as it can learn when it comes across new test samples. We consider CFD, CUHK, ORL and Yale facial data-sets for our experiments.
Interpretation Strategies of Contemporary Musical and Theatrical Art: Trends, Factors

Relevance of the study. The modern interpretive content main tendencies of the European and Ukrainian musical and theatrical art were analyzed. Forms of interpretation being were considered in the coordinates of the “composer-listener-performer” triad in the aspect of its correspondence to its time artistic intentions. The scientific novelty of the study is in the analysis of innovative projects most of which are not adapted to musicology and in the formulation of trends and factors of modern musical art’s interpretive policy. Main objective of the study is to determine the specifics and factors of the modern interpretations of a musical and theatrical art. Methodology. The following methods have been adapted: the interpretive — in relation to the analyzed opera projects; the hermeneutic-semantic — for the purpose of identify the interpreted works’ intonation-image specificity; the comparative — to juxtaposition the “interpretive behavior” of one work in different performance versions; the intonation-dramaturgical analysis — to study the specifics and factors of works’ interpretive versions. Results and conclusions. The modern interpretive reality initiates the emergence of radically new and the consolidation of existing non-standard trends in the work’s representation. These are: the instrumental performing theatricalization, significant expansion of the improvisation’s zone, abandonment of the opera genre canons with an emphasis on synthetic genres of performative nature and the use of bold audio, scenographic, color and light effects. The modern interpretative main trends are the actualization, the alienation and the emergence of working remote versions, the encroachment on the textual and intonational essence of a known work by adding the new material (the integral opus or the fragmentary inlay), the emergence of modern composer’s alternative role which is a co-author of a new hybrid product thanks to the connection to the work of the past. Findings of the research. The specifics and factors of work’s variant-interpretive realization are analytically argued. The main factors are the genre-intonation specificity, the synthetic and intertextual nature, the complexity and synergy of text semantic intentions, the recipient’s culturalhistorical awareness, the socio-cultural intentions’ balance of the author and his artistic will performers, the degree of text openness, the context. Prospects for further exploration in this direction. The following research areas are needed: 1) the development of new methods and terminological apparatus suitable for the modern artifacts’ analysis; 2) the analytical base’s expansion due to: a) the further accumulation of examples, b) the scientific adaptation of various genres’ works.
Learning to Rank-based Approach for Movie Search by Keyword Query and Example Query

This paper proposes a method for ranking movies by keyword queries and examples using machine learning techniques that analyze actual data from the online movie review site. Existing search methods cannot rank movies in “surprising order” for the keyword query “surprising.” People and critics created many “My best surprising movies” rankings on the web. Our proposed method uses a LambdaMART, one of the mainstream Learning to Rank techniques, to learn these personalized rankings and sort the movies through the viewpoint represented by a given query. To accept more complex information needs, we diverted the learning results to a search-by-example algorithm that enables users to input examples, such as “surprising movies like The Usual Suspects or Fight Club.” The experiment using the personal ranking data from the personal content curation service in Yahoo! Movies Japan suggests two findings: direct learning of personal ranking does not improve search performance, and the search-by-example-based application increases user satisfaction.
Preliminary Biometrics of ECG Signal Based on Temporal Organization through the Implementation of a Multilayer Perceptron Neural Network

The attributes of the ECG signal signifying the unique electrical properties of the heart offer the opportunity to expand the realm of biometrics, which pertains the identification of an individual based on physical characteristics.The temporal organization of the ECG signal offers a basis for composing a machine learning feature set.The four attributes of the feature set are derived through software automation enabled by Python.These four attributes are the temporal differential of the P wave maximum and T wave maximum relative to the R wave maximum and the Q wave minimum and S wave minimum relative to the R wave maximum.The multilayer perceptron neural network was applied and evaluated in terms of classification accuracy and time to develop the model.Superior performance was achieved with respect to a reduced feature set considering only the temporal differential of the P wave maximum and T wave maximum relative to the R wave maximum by comparison to all four attributes applied to the feature set and the temporal differential of the Q wave minimum and S wave minimum relative to the R wave maximum.With these preliminary findings and the advent of portable and wearable devices for the acquisition of the ECG signal, the temporal organization of the ECG signal offers robust potential for the field of biometrics.
Students’ Attitudes and Perception of Achievement in Reading Comprehension

This study aimed to investigate the students’ attitudes and perception of reading comprehension. Participants were fourth, fifth and sixth-grade students selected using random purposive sampling from three different classes in a public school (n=80) in Betong. This research using an explanatory mixed-method also aimed to determine whether students’ attitudes and perception significantly affect their reading comprehension. The data was gathered using Elementary Reading Attitude Survey (ERAS) developed by McKenna and Kear, 1990, interview questions and the analysis on students’ performance in reading comprehension. The research findings showed no strong relationship between students’ attitudes and perception towards reading would affect their achievement in reading comprehension because students’ attitudes and perceptions are affected mainly by other factors.