Reviewerly/exHarmony huggingface dataset:
РЕФЕРЕНЦИЯ И ЕЕ СВЯЗУЮЩИЙ ПОТЕНЦИАЛ В БЛОГОВОМ ТЕКСТЕ

DOI 10.18522/1995-0640-2021-1-100-111Reference as a logical-semantic category is implemented in the blog text based on a variety of lexical and grammatical means (personal, demonstrative and possessive pronouns, definite article, nominative phrases). At the same time, we consistently differentiate the functional and formal level of analysis (connectivity relations – means of expressing connectivity). The conceptual difference between the functional category and the formal implementation of this category reveals some implications that are important for our study. First, the noun or nominative phrase that acts as a segment of the propositional stimulus message is repeatedly replaced by a certain range of formal (and contextual) anaphoric means. Responding to this message, the interlocutor constructs a mental representation of the relationship of formal or contextual connectivity between the antecedent and the substitute. At the same time, the connectivity tool performs a specific referential function in the mental map of blog communication participants. If the referential interdependence between the antecedent and the substitute becomes contextual, the blogger and respondents identify the similarity of the concepts manifested by these components of the stimulus and reaction, establish not only formal equivalence, but also semantic and pragmatic similarity of the conceptual meanings of the associated language units.In the developed blog, there is a contextual relationship between the indicators of connectivity of thematically correlated constituents and the pragmatic consistency of messages of participants in computermediated communication. In the blogosphere, lexical and grammatical tools that function in an anaphoric or cataphoric function are endowed with such semantics that acquire relevant meaning for the interlocutors only taking into account the previous or subsequent messages. These messages, in turn, turn out to be the context against which these units are identified and interpreted by the blogger and respondents. The relationship of connectedness is manifested not so much in the blog text, but at the moment of perception by the interlocutors of each other’s discursive works. The category of connectedness is a value proportional to the communicative ability of the interlocutors to compare and coordinate the semantics of discursive elements, taking into account the referential schemes activated in their minds.Keywords: blog text, linking tools, reference, background knowledge, context.
Employment of alternative therapies as a way to minimize tensions and emotions generated by COVID-19

INTRODUCTION: The pandemic triggered by the SARS-CoV-2 virus, which causes COVID-19, is directly interfering in people's lives, negatively affecting their physical, emotional and psychological health. Linked to this, social distance increases the damage, as it requires a new lifestyle and the absence of family and friends. Therefore, in order to reduce stress, anxiety, fear, several measures can be adopted as an alternative method. AIM: To approach the use of alternative therapies as a way to minimize tensions and emotions generated by COVID-19. MATERIAL AND METHODS: This is a systematic review based on articles indexed in the “Biblioteca Virtual em Saude (BVS)” [Virtual Health Library (VHL)], using as descriptors: “alternative therapies”, “tensions” and “COVID-19”. Inclusion criteria were used: full text, in Portuguese, published between 2019 and 2020. The sample consisted of 8 articles. RESULTS: In the context of the pandemic, all people are subjected to various pressures and changes in habits, which implies the need for care, both physically, emotionally, mentally and spiritually. It is essential to try to maintain the global balance of health, even though everyone is threatened by the lethality of a virus until then uncontrollable, SARS-CoV-2. Alternative, energetic or holistic therapies, such as yoga and meditation, allow a more complete understanding of the human being, as an interconnected organism, a whole, and not fragmented, which is dealing with an invisible threat, living under the pressure from a challenging sentimental charge. Alternative therapies value and recognize inner subjectivity, emotions and thoughts that can affect the health of the body. Despite they are often viewed with suspicion, it is a complementary health care tool. In this sense, they are recommended by the World Health Organization (WHO) and the Ministry of Health (MS). In addition, the “Sistema Unico de Saude (SUS)” [Unified Health System (UHS)] defines them as integrative and complementary practices (PICs), which do not replace traditional treatment, but are indicated as supplementary, adding to the state of health. CONCLUSION: Currently, the world scenario points to a future catastrophe in mental health, evidenced after the period of the pandemic. This fact deserves to be taken into account and prioritized by the public authorities, so that the negative consequences on the mental health of the population in the medium and long term can be minimized. Thus, investment in alternative therapies, as well as adequate health care, are mechanisms that prove to be valuable for facing the current pandemic.
Machine Learning-Based Approach for Arabic Dialect Identification

This paper describes our systems submitted to the Second Nuanced Arabic Dialect Identification Shared Task (NADI 2021). Dialect identification is the task of automatically detecting the source variety of a given text or speech segment. There are four subtasks, two subtasks for country-level identification and the other two subtasks for province-level identification. The data in this task covers a total of 100 provinces from all 21 Arab countries and come from the Twitter domain. The proposed systems depend on five machine-learning approaches namely Complement Naive Bayes, Support Vector Machine, Decision Tree, Logistic Regression and Random Forest Classifiers. F1 macro-averaged score of Naive Bayes classifier outperformed all other classifiers for development and test data.
Моделирование производительности солнечных концентраторных модулей на основе алгоритмов искусственных нейронных сетей

Since the performance of solar power plants is quite variable, the dependence of production on weather conditions significantly increases the need for accurate forecasting. At present, the formation of a new approach to the development of predictive models of the performance of solar power plants based on artificial neural network algorithms is acquiring special relevance. The advantages of artificial neural networks in forecasting, such as the ability to learn and take into account a set of parameters that are not in a functional connection, make it possible to successfully use them in the development of models of the performance of solar power plants. The analysis of existing developments is carried out and promising areas of application of artificial intelligence algorithms in solar energy are determined. To simulate the performance of a solar concentrator module, a two-layer artificial neural network with sigmoid hidden neurons and linear output neurons has been developed. The developed performance model of a solar concentrator module based on an artificial neural network makes it possible, with a significant approximation, to determine the thermal efficiency of a solar module depending on various external conditions and operating parameters.
Developing an Audiobook for Listening Courseware

This study aims to develop an audiobook for learning listening to students. This research was conducted using the Borg &amp; Gall development method, with several adjustments for research needs. The research stages carried out were (1) preliminary studies, (2) planning, (3) product development, (4) product validation, (5) first stage revision, (6) product testing, (7) second stage revision, and (8) dissemination. Some innovations are integrated into this book that was developed. This innovation is in the form of integrating theory and lis-tening to various types of texts, from conversational texts to narrative texts. The product developed is listening courseware, which is present-ed in a flash application. The results showed that the products devel-oped were in accordance with the student needs and could increase student independence. The results of validation tests and trials show that the product developed is feasible to be implemented with an aver-age percentage of the assessment results of 90.71%.
cs_english@LT-EDI-EACL2021: Hope Speech Detection Based On Fine-tuning ALBERT Model

This paper mainly introduces the relevant content of the task “Hope Speech Detection for Equality, Diversity, and Inclusion at LT-EDI 2021-EACL 2021”. A total of three language datasets were provided, and we chose the English dataset to complete this task. The specific task objective is to classify the given speech into ‘Hope speech’, ‘Not Hope speech’, and ‘Not in intended language’. In terms of method, we use fine-tuned ALBERT and K fold cross-validation to accomplish this task. In the end, we achieved a good result in the rank list of the task result, and the final F1 score was 0.93, tying for first place. However, we will continue to try to improve methods to get better results in future work.
THE CALCULATION SYSTEM OF NUMBER OF PEOPLE IN A ROOM BASED ON HUMAN DETECTION USING HAAR-CASCADE CLASSIFIER

Data of number of people in the room, calculations are usually carried out by assigning someone to oversee a room. In this final project, a system for calculating the number of people in the room is designed with image processing based on human detection that can be used in rooms, both for commercial applications and for security. This system uses Raspberry Pi device that already has an image processing method Haar-Cascade Classifier. Input data is in the form of video taken directly via webcam to be captured into a frame so that it can be used as a input the Haar-Cascade Classifier method and perform the counting process will be sent to the Antares platform. The system design has been tested with five scenarios. Scenario 1 the effect of the distance of the object, scenario 2 the effect of the pose of the object, scenario 3 the effect of the amount the object in the frame, scenario 4 affects the scale factor and scenario 5 measurement computation time. Scenarios 1 to 3 will do the best configuration for minimum neighbour. The system gets the best accuracy of 98,5% when the object distance 4 meters, the best accuracy of 96,6% when the object is facing forward and accuracy the best is 97,7% when the object in the frame is more than two objects with the best configuration use the minimum neighbour 5. Scenario 4 gets accuracy the best is 76,2% when using the scale factor 1.1. Scenario 5 gets the average computation time of the system is under one second, meaning the detection process done pretty fast.
Caveat Usor: Surveillance Capitalism as Epistemic Inequality

Epistemic rights are the cause of which privacy is the effect. The wholesale destruction of privacy during the first two decades of the digital century is the consequence of the unilateral nullification of elemental epistemic rights, as the leading surveillance capitalist corporations established unrivaled dominance over the totality of the world’s information now rendered in digital format. This political and human rights contest has been obfuscated to the point of invisibility, despite the fact that its outcome will define the moral and political milieu of our information civilization.The distribution of epistemic rights determines the degree of epistemic inequality, defined as unequal access to learning imposed by hidden mechanisms of information capture, production, analysis, and control. It is best exemplified in the fast-growing abyss between what people can know and what can be known about them. This new axis of social inequality does not reflect what we can earn but rather what we can learn. It represents a focal shift in social ordering from ownership of “the means of production” to ownership of “the production of meaning,” from the division of labor to the division of learning.Asymmetries of knowledge feed the progress of instrumentarian power as exclusive knowledge is translated through the networked layer of digital instrumentation to produce new capabilities of behavioral actuation at scale – influencing, tuning, herding, and modifying human behavior toward others’ commercial -- and political-- ends. The division of learning is both the ascendant principle of social order in the twenty-first century and already hostage to surveillance capital’s privileged position, empowered by its self-authorized ownership of human-generated data and its exclusive command of analysis and prediction capabilities. The result: Caveat usor.These conditions are best understood as the unauthorized privatization of the division of learning in society. Just as Durkheim warned of the subversion of the division of labor by the powerful forces of industrial capital a century ago, today’s successful prosecution of information warfare by surveillance capital against citizen-users exerts private power over the definitive principle of social order in our time. Epistemic inequality is the signature deformation of this epoch, as the pathologies of the division of learning infect society and undermine democracy. How do surveillance capitalists defend their dominance? What responses are required? Finally, the citizens’ paradox: Democracy is the ultimate target of this epistemic poison and its only antidote.
Toward the Effectiveness of Teaching Descriptive Text at Junior High School

Teaching descriptive text for oral and written competences has been quite phenomenal in Junior High School level since students’ had very limited access or competence in the target language. Therefore, using Information Gap Technique, several indicators of speaking skills were expected to be explored in the case of students at Grade Eight in Solok West Sumatera. The purpose of this research was to determine whether or not Information Gap Technique gave significant effects to students’ speaking skills. Using clustering random  sampling,  thirty-two  students  from  class VIII.2. and other 32 students of VIII1 became the experimental and control class. Data were collected by using speaking test and analyzed by using Statistical Product and Service Solution (SPSS) procedures. T-test was used to analyze the students’ post-test score. The data were analyzed by using simple regression (df .05). The result of this research showed that mean scores of students’ speaking in experimental class was 65,81 higher than those of control class (58.15). While, t- calculate (8.3) was also bigger than t-table (1.669). Statistically, it showed that teaching speaking by using Information Gap Technique gave significant effects to students’ speaking skill.
Power grid fault detection method based on cloud platform and improved isolated forest

In order to avoid equipment failures that may occur during power generation and transportation, real-time fault detection and diagnosis are required. Based on the cloud computing architecture, this paper proposes a fault detection method suitable for the power grid cloud platform. The method first improved the isolated forest model. After that, a power grid cloud platform was built, which was divided into three layers. The field layer collects the data generated by the various monitoring systems at the equipment layer and uploads it to the cloud center layer after data preprocessing; The cloud center layer uses the previously stored data to parallelize and iteratively train the improved isolated forest model, and the trained model can classify the faults that occur. Finally, the accuracy of the method is proved through experiments.
Risk-based security: from theory to practice

Risk-based security is a concept introduced to provide security checks without inconveniencing travelers that are being checked with unqualified scrutiny checks while maintaining the same level of security with current check point practices without compromising security standards. Furthermore, risk-based security, as a means of improving travelers’ experience at check points is expected to reduce queueing and waiting times while improving at the same travelers’ experience during checks. Several projects have been funded by the European Commission to investigate the concept of risk-based security and develop the means and technology required to implement it. This paper discusses and analyses the concept of riskbased security, the inherent competing mechanism between risk assessment, screening time and level of security, and means to implement risk-based security based on anomaly detection using deep learning and artificial intelligence (AI) methods. This paper summarizes work that has been carried out in the project FLYSEC [2] and continues in the projects TRESSPASS ]3], D4FLY and SAFETY4RAIL (see Acknowledgments), and has previously been published in [13], [7], [8].
The Effect of Learning Motivation, Learning Facilities, and Teacher Teaching Skills on Student Learning Interests

This study aims to determine whether there is an influence of learning motivation, learning facilities, and teaching skills of teachers on student learning interest. This research was conducted for two months from three April to June 2020. The research method used was a survey method with a regression approach to the population in this study were students and high school students from various educational institutions. The population in this study is a random population of 200 respondents. The technique used in data collection is using SPSS Statistics version 22 and using Amos 23, the test carried out is the test requirements test, the classic assumption test, and the hypothesis test. Researchers also tested the EFA, CFA, and SEM. Of the five hypotheses carried out, three were accepted and two were rejected.
Perancangan Sistem Evaluasi Online Dengan Fitur Link Login Instant Menggunakan Model Waterfall

The Covid-19 pandemic that has hit the world has an impact on the implementation of an online learning system for all levels of education. For the purposes of student evaluation, of course, an online evaluation system is needed. At the basic education level, the online evaluation system must be specially designed by prioritizing the ease of students accessing and carrying out evaluations. Therefore, research is needed to design an online evaluation system that is easy to use and flexible. This study aims to design an online evaluation system that can be accessed by students by simply clicking a link. So students do not need to create an account and use it to access teacher evaluations. The expected result of this research is a system that makes it very easy, especially for students at the basic education level so that all students can follow all evaluations given by the teachers easily and flexibly. Unified Modeling Language is used to make the design, while the method for system development used is the waterfall model.
GENERAL ASPECTS OF BIBLIOGRAPHY IN THE CONDITIONS OF THE INFORMATION SOCIETY

The article is devoted to the study of the general aspects of bibliographic activity in the information society. At the same time, the essence of bibliography is explained from a terminological, scientifictheoretical, methodological and conceptual point of view. The general interpretation of bibliography in this regard explains two main conceptual directions: bibliographers and documentarians. As a result of research in this area, it becomes clear that bibliography as a whole is a field of human activity and is considered as a system.
The Effect of Learning Facilities, Teacher Competence, and Family Environment on Learning Motivation

The motivation of a student to want to learn is sometimes erratic and strongly influenced by several factors. This study aims to determine whether there is an influence of learning facilities, teacher competence, and family environment on learning motivation possessed by students. The research was conducted for three months, starting from April to June 2020. The research method used a survey method with a regression approach with the population in this study were high school and equivalent students as well as students from various universities, totaling 211 respondents. Data collection using literature and questionnaire techniques. Data were analyzed using SPSS Statistics version 25 and using Amos, with linear regression analysis. The results show that each variable has an unequal effect. This result can be said that learning motivation that exists in students is influenced by learning facilities, teacher competence, and family environment. According to this study, learning facilities are variables that greatly affect learning motivation compared to teacher competency and family environment variables.
Provides a Hybrid Method of Analyzing News Databases Using RapidMine Case Study: Persian News Texts

One of the most widely used approaches in the management of Web-based systems, use the online agency and Data related to them . Online web agency, like the heart of a community and is one of the most critical information resources in a society. The importance of this topic in the news military organizations will be doubled. So having a right way and a unique conceptual approach to analyze and categorize the resources, Can provide numerous benefits and assistance to decision-makers within the organization, especially military organizations in carrying out decisions. In this study, firstly we contribute to the study and understanding of the concepts of data mining methods. Secondly, analysis of different methods of text processing must be done from different perspectives So as to identify the positive strategies and strengths of a variety of methods and The Finally, the analysis of news database, so as to uncover information hidden in the data and how to use it. Keywords: Data mining, text mining, News Database, Mixed-Method.