Reviewerly/exHarmony huggingface dataset:
Social and Psychological Characteristics of Individual Freedom Space

The article is devoted to the analysis of social and psychological characteristics of individual freedom space. The concept of freedom, in terms of socio-psychological processes, is represented by three basic vectors: Forms of interpersonal interaction (community - society); Degree of probability (arbitrariness - given); The principle of social processes development (naturalness - artificiality). According to certain vectors, freedom finds its manifestation as: a natural process, which has many possibilities for deployment and is realized in a horizontal direction of interpersonal interaction. It is noted, that freedom is lost: in the process of institutionalization of organizational forms; with appearing of formalism, legitimacy, normative features, regulation; in the presence of hierarchy, subordination and vertical relationships in the group. It has been found out, that according to the vector, form of interpersonal interaction, freedom is mostly present in communities, which are united by a network principle. Civic organizations, communities, associations provide an opportunity for self-expression of the individual, since there is no dictate of group norms. According to this vector, freedom can be analyzed, not as an organization from community to society, but as a way of interaction of feelings, thoughts, actions, ways of thinking. It has been analyzed that according to the vector, the development of social processes, freedom is observed in everything, which is natural. It is a space of natural experiences, feelings and states, any artificiality and control is a sign of lack of freedom. It has been shown that according to the probability vector, freedom is manifested in the processes, where an arbitrary scenario is observed. This is a space for goal setting, building up one’s own activities. According to each vector, the degree of probability of freedom is analyzed.
Implementation of Essence Practice into Azure DevOps Server System

Nowadays one of the important issues in software engineering is the question of creating business effective software development methods. The Essence language which was created by the SEMAT initiative makes it possible to have a common foundation and comparation tool for very different software development processes. However, the use of Essence is mostly focused on describing software development methods in their general form. In this work we propose a way to use Essence and its supporting tools to transform abstract practice into the Azure DevOps Server system entities and rules. To do this we firstly consider how relations from abstract level of Essence language trans­form into a specific practice by describing entities and relations between them. Then we demonstrate how a practice described in the Essence language should work using typical software project management system features. Then we look thorough different Azure DevOps Server features which allow to modify and upgrade systems. Finally, we describe how to modify an Azure DevOps Server system to support import of Essence practices and methods. To conclude, we consider in this paper a general description of Essence, what differs the abstract level of Essence from an Essence practice, what must be done to implement an Essence practice to any project management system, and describe our modification of the Azure DevOps Server.
New Orthogonal Binary Sequences Using Quotient Rings Z/&amp;lt;i&amp;gt;n&amp;lt;/i&amp;gt;Z Where &amp;lt;i&amp;gt;n&amp;lt;/i&amp;gt; Is a Multiple of Some Prime Numbers

Orthogonal Sequences (as M-Sequences, Walsh Sequences,…) are used widely at the forward links of communication channels to mix the information on connecting to and at the backward links of these channels to sift through this information is transmitted to reach the receivers this information in a correct form, especially in the pilot channels, the Sync channels, and the Traffic channel.This research is useful to generate new sets of orthogonal sequences (with the bigger lengths and the bigger minimum distance that assists to increase secrecy of these information and increase the possibility of correcting mistakes resulting in the channels of communication) from quotient rings Z/nZ, where Z is the integers and n is not of the form p m, where p is prime, replacing each event number by zero and each odd number by one, also, the increase in the natural number does not necessarily lead to an increase in the size of the biggest orthogonal set in the corresponding quotient ring.The length of any sequence in a biggest orthogonal set in the quotient ring Z/nZ is n and the minimum distance is between (n-3)/2 and (n-1)/2 and the sequences can be used as keywords or passwords for secret messages.
DEVELOPING ENGLISH READING MATERIALS FOR THE EIGHTH GRADE STUDENTS OF MTs AL-HAMID BANJARMASIN

Reading is one of the skill that important to learn. By reading, students will get new knowledge from books, newspaper, magazine, even social media. In this era, many students have problems in understanding and confuse to learn reading text. To reach the goal of reading lesson, the students need the English reading material which are relevant. Good materials are needed in this research. It can be effort for the students to makes their reading ability better. By developing good materials, students will expected to be more active in the learning process and make the students interested in the reading lesson. This design of this research is Research and Development (R&D). The participants were the eighth grade students of MTs Al-Hamid. This research adapted the model from Dick and Carey with some modification. The steps in the modified research procedures were conducting the needs analysis, writing the course grid, developing the materials, getting the expert judgment, and writing the final draft of the materials. There were two types of data: the quantitative and qualitative data. The quantitative data were the students’ needs analysis and the expert judgment which were collected by using questionnaires, while the qualitative data were the expert opinion about the materials. The result of needs analysis shows that the students preferred to communicate in daily activity, and also in the intermediate level. Besides, the students have difficulties in recognizing particular meaning of the text. The students preferred to have topic about holiday and family. Meanwhile, the length of the text are about 100 – 150 words. Most of students want the activity of answering optional question. The students preferred reading in the classroom and do the activity individually. The students want the teacher to guide and correct student’s work while teaching and learning. Meanwhile the students preferred to be active learner. The result from expert judgment shows that the main value from each chapters of the appropriateness of content is 4, appropriateness of language is 4, and appropriateness of graphic is 4. All of those values are in range ≥ 3.28 that means “very good”. Meanwhile, the main value of the appropriateness of presentation is 3.5 and in the range ≥ 3.28 that means “very good”. Based on the result, the materials categorized appropriate.
Kannada Dialect Classification Using CNN

Kannada is one of the prominent languages spoken in southern India. Since the Kannada is a lingua franca and spoken by more than 70 million people, it is evident to have dialects. In this paper, we identified five major dialectal regions in Karnataka state. An attempt is made to classify these five dialects from sentence-level utterances. Sentences are segmented from continuous speech automatically by using spectral centroid and short term energy features. Mel frequency cepstral coefficient (MFCC) features are extracted from these sentence units. These features are used to train the convolutional neural networks (CNN). Along with MFCCs, shifted delta and double delta coefficients are also attempted to train the CNN model. The proposed CNN based dialect recognition system is also tested with internationally known standard Intonation Variation in English (IViE) dataset. The CNN model has resulted in better performance. It is observed that the use of one convolution layer and three fully connected layers balances computational complexity and results in better accuracy with both Kannada and English datasets.
Evaluasi Utilitas Bangunan Pada GKB UNISSULA

&lt;p&gt;&lt;em&gt; In the construction of multi-storey buildings, every aspect must be considered in accordance with the rules set out in the Act. Article 7 Paragraph 3 of Law 28/02 states that building construction must meet four aspects, namely safety, health, comfort, and convenience. To support the realization of these aspects, it is necessary to have a building utility. The Joint Lecture Building (GKB) of Sultan Agung Islamic University in Semarang, is a building that has 10 floors and is a busy building because it is used by several faculties, such as the PGSD Faculty, Language Faculty, Communication Faculty, and Nursing Faculty. In the operation of the GKB building, there are several complaints that occur in the GKB such as electricity that often goes out, some rooms have less lighting / dark, queues of elevator users are piling up and visually, the GKB building has the potential of being struck by lightning because it has high above average.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Seeing these conditions, the authors conducted a study to evaluate the reliability of buildings based on the utility of the building with methods that have been used in other studies, namely the scoring method that is based on visual inspection and by adding measurement methods, and calculations. From these results found the reliability value of the GKB building on the criterion of health scores got a score of 81, the health and comfort criteria scored 99, the ease criterion scored a score of 98. So the reliability of the GKB building got a score of 92 and was included in the unfit category.&lt;/em&gt;&lt;/p&gt;
FORMATION OF READYNESS OF FUTURE TEACHERS OF INFORMATICS FOR PROFESSIONAL ACTIVITY

The article substantiates that the readiness of future computer science teachers for professional activities is a complex formation, internal potential and is determined by interest in the field of computer science education, and is the result of qualification, manifested in the ability to competently perform tasks and responsibilities, flexibly adapt to dynamic working conditions, to solve complex specialized problems and practical problems in general secondary education institutions. In the descriptions of ability we mean «ability to act», as the ability to effectively use the formed competencies in the design and reproduction of professional actions of teachers and educational and cognitive activities of students at both reproductive and creative levels. Emphasis is placed on combining competency-oriented education with activity, personal and other scientific approaches, focusing the training of future computer science teachers on the learning outcomes of the relevant educational program. Other conditions for the formation of professional readiness are: the fundamentalization of education and its combination with practical training; rethinking the content of education in favor of interdisciplinary integration of knowledge; awareness of readiness both as a prerequisite for professional activity and as a result of this activity. The content of motivational, cognitive, operational, personal, reflexive components of students’ readiness for pedagogical activity at the motivational-orientational, cognitive-activity, practical-reflexive stages is clarified. An analysis of the results of a survey of students to determine their own level of readiness for professional activity, which indicates the feasibility of focusing on this phenomenon in higher education and especially when studying the disciplines of the professional cycle.
Analyzing the Performance of Graph Neural Networks with Pipe Parallelism

Many interesting datasets ubiquitous in machine learning and deep learning can be described via graphs. As the scale and complexity of graph-structured datasets increase, such as in expansive social networks, protein folding, chemical interaction networks, and material phase transitions, improving the efficiency of the machine learning techniques applied to these is crucial. In this study, we focus on Graph Neural Networks (GNN) that have found great success in tasks such as node or edge classification and link prediction. However, standard GNN models have scaling limits due to necessary recursive calculations performed through dense graph relationships that lead to memory and runtime bottlenecks. While new approaches for processing larger networks are needed to advance graph techniques, and several have been proposed, we study how GNNs could be parallelized using existing tools and frameworks that are known to be successful in the deep learning community. In particular, we investigate applying pipeline parallelism to GNN models with GPipe, introduced by Google in 2018.
On an equivalence between regular ordered Γ-semigroups and regular ordered semigroups

Abstract In this paper, we develop a technique which enables us to obtain several results from the theory of Γ-semigroups as logical implications of their semigroup theoretical analogues.
Ontognoseological Meaning of Anthropic Principle and Issue of Reasonable Reality

The purpose of the study is to attain apodictically reliable criteria for understanding reasonable reality from the standpoint of the anthropic principle. The article offers a concept of one-to-one correspondence between classical understanding of reasonable reality and two versions of the anthropic principle. Limits of system-formation regarding the issue of unity of being and thinking are set. Scientific novelty of the research lies in transforming graduation and stratification of aporetics into the doctrine of “double eternity” according to the distinction theory. The attained results have revealed the system-forming function of opposition between anamnesis and hysteresis from the standpoint of the anthropic principle in the context of ontognoseological essentialism.
Using the methods of probability theory analyzing logs of electronic infromation systems

Proper level of logging in various information systems and log analysis play a key role in achieving the desired level of security.The aim of the present study on one hand is to provide an overview of the known applications of mathematical statistical tools and methods in the field of information security, and, on the other hand, to demonstrate the applicability of probability theory in analysis of log files of IT systems through a specific example.Starting from the basic concepts of the topic, and the most important and relevant concepts related to logging, log analysis and statistics are discussed. After that comes a brief overview of the previous researches on the topic.Finally, a possible use of random variables and theoretical probability distributions in the analysis of logs of various IT systems is described. The raison d’etre of the method is verified through a real-world example.
Exploiting WordNet Synset and Hypernym Representations for Answer Selection.

Answer selection (AS) is an important subtask of document-based question answering (DQA). In this task, the candidate answers come from the same document, and each answer sentence is semantically related to the given question, which makes it more challenging to select the true answer. WordNet provides powerful knowledge about concepts and their semantic relations so we employ WordNet to enrich the abilities of paraphrasing and reasoning of the network-based question answering model. Specifically, we exploit the synset and hypernym concepts to enrich the word representation and incorporate the similarity scores of two concepts that share the synset or hypernym relations into the attention mechanism. The proposed WordNet-enhanced hierarchical model (WEHM) consists of four modules, including WordNet-enhanced word representation, sentence encoding, WordNet-enhanced attention mechanism, and hierarchical document encoding. Extensive experiments on the public WikiQA and SelQA datasets demonstrate that our proposed model significantly improves the baseline system and outperforms all existing state-of-the-art methods by a large margin.
Research on Talent Training Mode of Applied Big Data Specialty in Higher Vocational Colleges

With the rapid development of science and technology, now we have come to the era of big data. At present, big data technology has gradually penetrated into people's lives, and penetrated into all areas of life. With the rapid development of big data technology, the society also needs corresponding talents. Therefore, the major vocational colleges and universities should comply with the development of the times, and strive to cultivate technical application-oriented talents. Colleges and universities are in the process of continuous practice and exploration. First, the university should make efforts to analyze the development of big data industry; second, the university needs to discuss and study the difficulties faced by the relevant majors of big data; third, the cultivation of big data professionals needs to establish a complete mode, and put forward relevant strategies to give the university professional construction Reference.
Empirical Probability Distributions with Unknown Number of Components

Gaussian mixture modelWe consider the estimation of empirical probability distributions, both discrete and continuous.We focus on deriving formulas to estimate number of categories for the discrete distribution, when the number of categories is hidden, and the means and methods to estimate the number of components in the Gaussian mixture model representing a probability density function given implicitly in terms of its realizations.To reach the stated goals, we solve certain combinatorial problems for discrete distribution and develop methods to compute the expected Kullback-Leibler divergence for Gaussians.The last mentioned result is needed to develop the theory of continuous distributions.Sample applications and an extensive numerical study are given.
Scientific Visualization System on a Chip with Tangible User Interface

This paper is devoted to the development of the ontology-driven standalone scientific visualization station based on a single-board microcomputer with custom tangible user interface. Such a station can be used as a powerful demonstration tool in various scenarios including interactive museum exhibitions. According to the approach proposed, the particular instance of a software scientific visualization system is generated automatically by a high-level platform SciVi that was been developed earlier. Previously, ontology-driven software generation mechanisms within SciVi were tested on the firmware generation for the microcontroller units. Currently we present a generalization of this technique to the case of systems on chips like Raspberry Pi or Orange Pi. Data preprocessing and rendering capabilities of SciVi are reused without modifications from the previous stages of development, while the new mechanisms of taking into account the specifics of systems on chips software and hardware organization are introduced via extending the appropriate SciVi ontologies. The generalized technique is tested in practice by creating a set of interactive museum items for the “Transmutations” exhibition within Kidsmuseum, branch of Perm Regional Museum.
Research on the Application of Mobile Learning to College English Listening Teaching-- A Case Study on Shanbay Listening APP

In order to verify the effect of mobile learning assisting college English listening teaching, this study guided students to conduct a one-semester teaching experiment on the platform of Shanbay Listening APP, collected students’punching times and CET-4 scores, and conducted a questionnaire survey on students. Research shows that the frequency of punching in the Shanbay Listening APP is positively correlated with CET-4 scores, and students have a high degree of recognition of mobile learning, but their perseverance and self-control are not enough to persist in learning, which requires teachers to guide and supervise them.
ANALISIS FRASA VERBA PADA TEKS BERITA BBC.COM BERJUDUL â€œPILKADA 2020 DI TENGAH PANDEMI COVID-19: MASA KAMPANYE DIMULAI, CARA TATAP MUKA TETAP DINILAI PALING EFEKTIFâ€

Phrases are often found in text in a sentence, which is in the bbc.com news text entitled Pilkada 2020 in the Middle of the Covid-19 Pandemic: The Campaign Period begins, Face-to-Face Remaining is considered the Most Effective The research objective was to analyze verb phrases, namely verb phrases modified, coordinative, and apologetic. The research method uses descriptive qualitative methods, with reading, note-taking, and substitution techniques, then the analysis of the research data this time uses the split method. From the research results obtained data of 11 verb phrases. With the results of this verb phrase analysis, more detailed research on verb phrase analysis can be carried out.
THEORETICAL AND METHODOLOGICAL ASPECTS OF UNDERSTANDING OF THE SYSTEM OBJECT IN DESIGN

The article is devoted to the analysis of the system object from the point of view of design from design, sociocultural and philosophical positions. The authors systematize the definitions of a system object of design proposed in the 1960–1980s by theorists and practitioners, art historians, cultural experts and philosophers from different countries, including Russia, which allows a comprehensive understanding of the phenomenon of design culture. This article is devoted to the characteristic properties of the system object in design. They were considered and analyzed on the example of the «Absheron» design-program when designing of agricultural village). This concept was developed at the All-Union Scientific Research Institute of Technical Aesthetics (VNIITE) in 1983. Using the same example, the features of the approach to designing a system object in design was observed not only as a separate product, but as a sociocultural situation that constantly changes at each design stage.
Improving The Quality Of Education Management With Big Data Processing Technology

In modern educational institution management systems, big data technologies are almost never used, although the interest for this kind of information and its processing is highly relevant today.The use of big data technologies in other areas gives a qualitative increase in the efficiency of systems, for example: medicine, economics, banking, city administration systems, etc.The examples of successful applications of big data technologies in student assistance systems at universities show that the use of big data technologies in the field of education will improve the process of managing education in educational institutions.As an example, the authors consider methods of scheduling using automated school scheduling systems.The systems for scheduling are created, however they may not include all information about the organization and management of educational process in a school or university.However, without the use of big data technologies, it is impossible to take into account all the special cases in each particular school, which complicates the learning process and the process of its managing.