Reviewerly/exHarmony huggingface dataset:
Means of speech characteristics of the stage image in the context of decoding the signal space contemporary performances

The purpose of the article is to identify the features of speech characteristics in the context of the disclosure of the plot-content aspect of the performance of postmodern aesthetics. Methodology. A typological and systematic method is used to study the creative mechanisms of the actor's creation of the speech characteristic of the image in the context of the peculiarities of the aesthetics of postmodernism; cognitive method, thanks to which theoretical positions in the field of language psychology and speech therapy are extrapolated to the field of theatrical art; method oftheoretical generalization, etc. Scientific novelty. The influence of postmodernist theater tendencies on the process of the actor's voice work on the creation of the image – the development and implementation of speech features of the character; the peculiarities of the process of decoding the sign system of a modern production on the basis of the interpretation of the speech characteristic of the images created by the actors are analyzed. Conclusions. The verbal characteristic of the image contributes to the actor's representation of certain internal characteristics of the character, his emotional state, deep reaction to events and/or actions of other characters, changes in lifestyle and worldview, etc., and in the context of postmodern aesthetics, when stage texts double coding" – a complex phenomenon of postmodernism, artistic and aesthetic means of which in theatrical art is a synthesis of different languages and codes of literature and philosophy in a holistic hypertext of performance, contribute to the understanding and comprehension of semantic aspects of theatrical production. The actor's use of elements of speech characteristic contributes to the expansion of his professional speech competence, the diversity of speech sound of the stage word. The components of speech characteristics can act as expressive means that reveal important aspects of the character; the necessary form of revealing the internal content of the stage image; an important element of the psychophysical structure of the role; an artistic technique that enhances the expressive possibilities of the stage word, and, accordingly, helps to form verbal symbolic means of expressing the artistic meanings of the performance. In our opinion, for the organic process of forming the stage image in general and the speech characteristics of the character in particular, the actor must not only expand his attention, observation, and ability to understand and comprehend the psychological and social causes of human behavior, but also deepen knowledge of psycholinguistics and speech therapy. Because only the organic combination of these factors contributes to the design of optimal stage speech, which corresponds to the concept of each specific performance.
Competence-based fuzzy skill functions

Fuzzy skill functions connect knowledge states at the performance level with latent cognitive abilities at the competence level. Given that there may exist precedence relations among skills, the main idea of this study is trying to develop fuzzy competence structures restricted on the fuzzy sets of skills that are likely to occur. We consider the knowledge structures determined by fuzzy skill functions and fuzzy competence structures. More precisely, disjunctive fuzzy skill functions delineate knowledge spaces if the fuzzy competence structures are union-closed, while conjunctive fuzzy skill functions delineate simple closure spaces if the fuzzy competence structures are intersection-closed. In general, competence-based fuzzy skill function delineates knowledge structures depending on the effective competence states. Correspondingly, we build algorithms that delineate knowledge structures via competence-based fuzzy skill functions. In the courses of these algorithms, one does not need to list all fuzzy competence states of fuzzy competence structures.
The application of bidirectional gated recurrent unit neural network in biomedical event trigger identification

Biomedical event extraction aims to extract structured biomedical events from unstructured mass biomedical literature, describing fine-grained biomedical relationships between events and biological entities. Biomedical event extraction reduces human effort and provides support for constructing a relevant database of disease diagnosis. Trigger word and argument are two components of a biomedical event. The trigger word refers to the word or phrase that triggers the event, and its type determines the type of the event. In contrast, argument refers to the event's participant, which can be a biological entity or another event. The current biomedical event extraction system uses the phased approach, with trigger word identification being the first step of the phased method. In this paper, an extended version of the recurrent neural network, i.e., the bidirectional gated recurrent unit (Bi-GRU) neural network, is utilized, to conduct the biomedical event trigger identification task. Specifically, the inputted word sequence tensor first passes through an embedding module including a word embedding layer and an entity-type label embedding layer to obtain the concatenated token representations for each sentence. Then, the token representations are fed into a Bi-GRU module to acquire the contextual encoding, which is used to conduct the trigger word identification task. The experiment is based on the MLEE dataset, a commonly used biomedical event extraction dataset. The experiment result shows that the proposed model can achieve some comparable performances with Precision 79.62%, Recall 78.64%, and F-score 78.82%
Information Fusion and Its Intelligent Sensing for Learning Intervention Model of Educational Big Data

With the continuous development of science and technology, a large number of devices containing high technology began to appear in people’s lives. With the popularity of big data, it not only drives the development of the whole information industry in society but also leads to different degrees of innovation and development in the reform industry worldwide. The purpose of this paper is to study how to use information fusion and its intelligent sensing technology to play an active role in the education industry, to help students identify problems in the learning process, to give timely intervention and guidance, and to help students complete their learning tasks with high quality. This paper proposes to use information fusion and its intelligent sensing technology to take advantage of learning analytics to collect, organize, analyze, and guide the learning data generated by students in the learning process and then to generate interventions that can have an impact on learning and improve learning methods for students. The experimental results of this paper show that after the learning intervention, the students’ frequency in discussion and communication was 72 in the first four weeks and reached 300 after the intervention, and the learning resources changed from 95 to 370 after the learning intervention, which is very significant progress.
Logging in Python

In the last chapter, you became acquainted with a unit test framework, Selenium. This chapter is a change of pace and you learn about a related topic, logging.
DEVELOPMENT AND IMPLEMENTATION OF A REAL-TIME SEDIMENT DISASTER ALERT SYSTEM

For flooding, visual information of rising water levels can signal the timing of residents' evacuation.For impending sediment disasters, however, the state of the groundwater level or soil moisture content in a slope's soil layer cannot be visually confirmed.Therefore, the authors developed a sediment disaster alert system, in part using a color-coded chart that signals evacuation urgency -an "evacuation switch".The system uses a slope's real-time rainfall observation as input data and performs real-time stability analysis based on rainwater runoff and infiltration simulations.In Nishikatsura Town, Yamanashi Prefecture, Japan, a slope designated as a mountain stream from which debris flow is likely to occur was selected as the target.The simulation model was constructed based on results of soil exploration and soil testing.The website for a sediment disaster alert system was developed by combining the rainfall observation system and the simulation.To provide the evacuation switch for residents, this website expresses risk of sediment disasters not by a safety factor but by a chart showing the current groundwater level with respect to the groundwater level at which the slope becomes unstable and collapses.
Knowledge Sharing, Individualism, Collectivism and Organizational Innovative Behaviour in the Public Health Organizations

&lt;p&gt;The purpose of this paper is to investigate that either individualists or collectivists employees are more innovative in the public sector concerning knowledge sharing and organizational culture. The study adopted quantitative research technique and data was collected through an online survey. We collected data from a field study of 480 employees working in Pakistan's two major public health institutions to test the study's hypotheses. The study adopted a hierarchical linear regression model to test the hypothesis. Our results show that there is a significant positive influence of organizational-based knowledge sharing, individual-based knowledge sharing, collectivism, and individualism on organizational innovative behavior in the organizations. Furthermore, this study also found a significant positive impact of collectivism and individualism as moderators on organizational innovative behavior. Finally, this study concluded that collectivism has a higher positive impact on organizational innovative behavior in comparison to individualism. &lt;/p&gt;
Relations between metacognitive processes and differences in framing effect performance

In this paper we discuss the link between risky decisions and regret, uncertainty about choice and willing to change the chosen option. We used a classic and modified versions of “Asian disease” task. The modification consisted in adding a series of side effects to the sure option to decrease it's the preferability. An attempt to replicate framing effect, action effect and its inversion in certain and uncertain decision-makers was made. The estimation of utility through integration of information about alternatives and role of metacognitive processes in choice are discussed. Accordingly to results the uncertain decision-makers tend to feel regret about choosing safe option in loss domain. Action effect and its inversion were not found. The inversion of framing-effect in uncertain decision-makers in loss domain was shown. In conclusion, the absence of framing effect in loss domain can be explained by strong the differences between certain and uncertain decision-makers.
Association Rule Mining Algorithms for Big Data using RDD-ECLAT Algorithms

Abstract The revolution in technology for storing and processing big data leads to data intensive computing as a new paradigm. To find the valuable and precise big data knowledge, efficient and scalable data mining techniques are required. In data mining, different techniques are applied depending on the kind of knowledge to be mined. Association rules are generated from the frequent itemsets computed by frequent itemset mining (FIM) algorithms. The problem of designing scalable and efficient frequent itemset mining algorithms on the Spark RDD framework. The research done in this thesis aims to improve the performance (in terms of execution time) of the existing Spark-based frequent itemset mining algorithms and efficiently re-design other frequent itemset mining algorithms on Spark. The particular problem of interest is re-designing the Eclat algorithm in the distributed computing environment of the Spark. The paper proposes and implements a parallel Eclat algorithm using the Spark RDD architecture, dubbed RDD-Eclat. EclatV1 is the earliest version, followed by EclatV2, EclatV3, EclatV4, and EclatV5. Each version is the consequence of a different technique and heuristic being applied to the preceding variant. Following EclatV1, the filtered transaction technique is used, followed by heuristics for equivalence class partitioning in EclatV4 and EclatV5. EclatV2 and EclatV3 are slightly different algorithmically, as are EclatV4 and EclatV5. Experiments on synthetic and real-world datasets.
An Early Alert System for Software Vulnerabilities based on Vulnerability Repositories and Social Networks

The huge amount of information regarding software vulnerabilities, the multiple and heterogeneous information sources, and the lack of awareness about the dangers of software vulnerabilities, exacerbates the risks of security threats being materialized. In this complex context, this paper approaches the problem of managing early alerts for software vulnerablities by leveraging existing vulnerability information found in vulnerability repositories and social networks. To this end, we propose a solution based on techniques that stem from automated retrieval of information about vulneratilities from the above sources, userdefined preferences regarding their technological environment and intelligent vulnerability tagging. Our user studies reveal the feasibility of our approach as a tool for managing early alerts regarding software vulnerabilities and keeping security professionals aware of them.
A Concept Attainment Model Using Cloud-Based Mobile Learning to Enhance the Mathematical Conceptual Knowledge of Undergraduate Students

The COVID-19 situation has affected the instructional process, with both students and instructors having to adapt to the conditions that have emerged. The inclusion of online tools as part of teaching and learning is imperative, especially in mathematics courses, in order to provide knowledge and to create a learning environment as close as possible to face-to-face learning. This study focuses on the mathematical conceptual knowledge of undergraduate students using a concept attainment model. This consists of a three-phase learning process involving the presentation of information and conceptualization, a conceptual comprehension test, and an analysis of thinking strategy. It also features the implementation of cloud-based mobile learning features, including cloud learning devices, cloud learning services, and cloud learning environments as the components of the proposed instruction model. The model was evaluated by experts before being used to investigate the mathematical conceptual knowledge of undergraduate students and how pre-test scores differ from post-test scores. Descriptive statistics and t-test were used to analyze the data. The results revealed that the overall scores for the suitability of the model indicate that this approach is most suitable, and that students learning through a concept attainment model using cloud-based mobile learning obtain a higher post-test score in mathematical conceptual knowledge compared to their pre-test score, at a level of .05 statistical significance. The framework of this study can be useful for mathematics instructors or others educators when it comes to applying it in order to develop students in mathematics contexts.
In defense of the self-reference quantifier S??. Approximation by dynamic systems

Arguments in defense of introducing the self-referencing quantifier S and its approximation on dynamical systems are consistently presented.The case of classical logic is described in detail.Generated 3-valued truth tables that match the corresponding Priest tables [5].In the process of constructing 4-valued truth tables, two more truth values were revealed that did not coincide with the original ones.Therefore, the closed tables turned out to be 6-valued.De Morgan's law confirmed in 6-valued truth tables.
HIGHER EDUCATION IN UKRAINE IN THE CONVENTION OF THE COVID-19 PANDEMIC: NEW CHALLENGES AND PROSPECTS

The article is devoted to the analysis of the problems of introduction of distance learning in higher educational institutions of Ukraine. The article presents the results of an anonymous survey of research and teaching staff and students of higher education institutions on the use of distance learning technologies in the conditions of national quarantine, conducted by the State Education Quality Service of Ukraine. According to the results of the survey, conclusions were made about the degree of effectiveness and further prospects for the introduction of new teaching methods in a pandemic.&#x0D; In order to identify achievements, possible difficulties and determine the main trends in the further development of distance technologies, the State Service for the Quality of Education of Ukraine conducted an anonymous survey of scientific and pedagogical workers and students of higher education institutions on the use of distance learning technologies in conditions of national quarantine. The survey was conducted from 23.04. to 05.05.2020. 28 391 respondents took part in the survey - 22367 students and 6024 scientific and pedagogical workers.&#x0D; As a result of the research, conclusions were drawn that the distance learning technologies in Ukraine and in the world are rapidly developing and are a promising tool for the provision of educational services.&#x0D; Thus, the introduction of quarantine during the COVID-19 coronavirus pandemic revealed not only new problems in higher education in Ukraine, but also new challenges and opportunities for higher education institutions from three points of view: for students, this is an experience of self-discipline and self-education; for teachers - the use of new methods and tools of distance learning; for structural divisions of universities, this is practical testing of the technical capabilities of distance learning; defining a clear distance learning strategy, where students not only gain knowledge, but also cooperate with teachers in a feedback mode; awareness of the need to quickly master the volume of home education.
Informational influence: concept and evolution in modern scientific idea

postgraduate student, Department of Information, Library and Archival Affairs, Kharkiv State Academy of Culture, Kharkiv, Ukraine&#x0D; INFORMATIONAL INFLUENCE: CONCEPT AND EVOLUTION IN MODERN SCIENTIFIC IDEA&#x0D; The purpose of this paper is to provide an analysis of the concept of “informational impact”, its evolution in scientific idea, as well as methodological aspects of the development of information technology in the context of their connection with the phenomenon of the information impact.&#x0D; The methodology. The work studies this issue by examining the basic methods and principles of information studies.&#x0D; The results. The concept of “informational influence” can be represented as a form of influencing the consciousness of the individual, carried out using the media resource in order to change the formed assessments, opinions, beliefs, values ​​for further transformation of its behavioral response to events. Not enough attention is paid to the informational influence as a phenomenon in the works of the scientists, because it is considered as an integral part of other definitions, and not as a separate phenomenon. It is important to note that the concept of “informational impact” as a phenomenon is almost not considered in scientific works. Most often, informational influence was an integral part of other definitions, rather than a separate process. Thus, this problem has not been considered comprehensively, and it needs additional attention of the scientific community.&#x0D; Informational influence, as well as the use of media resources in modern conditions are becoming an integral part of socio-political conflicts. The media and the phenomenon of informational influence itself is a tool for both the emergence and resolution of conflict situations. The conclusion about global informatization and formation of high-tech information infrastructure, and also about importance of consideration of information influence as one of tools of manipulative technologies is made.&#x0D; The scientific novelty. The author’s definition of the concept of “informational influence” is formulated, as well as its place as a tool of manipulative possibilities are analyzed, and also the questions of manipulative possibilities of mass media and communication are considered.&#x0D; The practical significance lies in the analysis of scientific and theoretical views of this matter. The phenomenon of informational influence in the context of information warfare and manipulations is considered.
Popular Scientific Book for Children “Peoples of Russia” as a Historical Source

Peoples of Russia" is a series of ethnographic stories for children.This article analyzes the first issue of the series entitled "Deserts of the North and their nomadic inhabitants" by N. A. Aleksandrov.The book was published in 1898 and was not reprinted during the Soviet and post-Soviet times.It was also not subjected to a scientific description, while the work contains valuable historical material on the ethnography of Russia.In a form that is generally accessible for perception, N. A. Aleksandrov systematizes the historical and ethnographic material about the peoples inhabiting the North of Russia in the XIX century.The purpose of the study is to consider the image of these peoples, to study their ethnic-forming markers, from the standpoint of which the peoples are presented in the source.The research was carried out on the basis of the analysis of six ethnographic stories and the contents of the "Interpreter" section.Source analysis has become the main research method.As a result of the study, ethno-forming markers of such historical peoples of the north of Russia as the Lapps, Samoyeds, Ostyaks, Yukagirs, Chukchi, and Koryaks were identified.Ethnographic markers are manifested through the description of the appearance of members of peoples, their way of life, beliefs, traditions, rituals, social structure, economic situation, interethnic relations, in particular with Russians.It demonstrates not only the territorial remoteness of peoples from civilization, but also the decisive role of the natural and climatic conditions of the North in the formation of the culture of peoples.The systematization of historical data based on the analysis of the first issue of the "Peoples of Russia" publication substantially supplements the available information regarding the processes that took place among the northern peoples of Russia in the XIX century.
A personal credit forecasting method based on improved isolation random forest

In recent years, due to the development of financial business and the Internet, personal credit business has become the focus of financial enterprises and the public. With the development of artificial intelligence technology, data-driven methods have been widely used in personal credit forecasting. However, due to potentially incorrect personal information about consumers, or possible errors in the collection of data, the credit system has some abnormal data in its database, which may lead to a decrease in the accuracy of the forecast. Furthermore, traditional machine learning methods ignore the influence of outliers on the model. In this paper, an improved isolation random forest model is proposed for personal credit forecasting. First, an isolation forest is used to isolate anomalous data to reduce the misguidance of the model. Compared with the general anomaly detection algorithm, the isolated forest does not need to make assumptions about the distribution of data and can effectively detect anomalies in the data. Then, the random forest is applied to build personal credit models based on the clean data. Compared with other methods, finally the accuracy of the proposed method is at least 6.57% higher, even under the interference of strong noise.