Reviewerly/exHarmony huggingface dataset:
The Power of Politeness Strategies in EFL Student-Teacher Interaction: Teacher’s Gender Perspective

The nature of student-teacher interaction is often influenced by the teachers’ actions and utterances. In fact, student-teacher interaction could be felt like either threatening or enjoyable. Teachers’ politeness will result in enjoyable student-teacher interaction. Very few studies about politeness on the teachers’ gender perspectives have been conducted. Therefore, this study is aimed to investigate the kinds of politeness strategies used by male and female teachers in powering EFL classroom, and to elaborate how the power of politeness strategies run the EFL student-teacher interaction. The participants are several teachers and students who conduct the English Intensive Course Program in an undergraduate university. Many students-teacher interactions using English are found in those course program, since the courses require the classroom participants to communicate in English. This research followed qualitative research design and used observation to collect data. Applying Brown and Levinson’s theory of politeness, the results show that politeness strategies bring a lively and friendly atmosphere during the classroom interaction. Specifically for female teachers who mostly use positive politeness strategy, they build more interaction with the student rather male teachers. Positive politeness strategy focused on the students’ positive face by expressing the number of utterances that want to be listened to by the students. It keeps students to have willingness to communicate so that the student-teacher interaction in EFL classroom can be maximized.
Face Age Estimation and the Other-race Effect

Age estimation is an automated method of predicting human age from 2-D facial feature representations.The majority of studies carried out in this research area use the FG-NET and MORPH 2 databases to train and test developed systems, which are lacking in black-face content.Most age frauds are perpetuated in the sub-Saharan African region due to the unavailability of an official database and unregistered births in the rural areas.The issues of unverified age in the region made it possible for under-age voters, under-age drivers, and the engagement of over-aged sportsmen.The other-race effect could reduce the performance of face recognition techniques, which could make techniques that work for white faces underperform when deployed for use in the predominately black face region.This study examines the other-race effect on face-based age estimation by analyzing the accuracy of an age estimation system trained with predominantly black faces against the same age estimation system trained with predominately white faces.The developed age estimation system uses a genetic algorithmartificial neural network classifier and local binary pattern for texture and shape feature extraction.A total of 170 black faces were used for system testing.The result showed that the age estimation system trained with the predominantly black face database (GA-ANN-AES-855) outperformed the system trained with predominantly white faces (GA-ANN-AES-255) on testing with the aforementioned black face samples.The results obtained from the simulation were further subjected to inferential statistics, which established that the improvement in the correct classification rate was statistically significant.Hence, the otherrace effect affects face-based age estimation systems.
Network Forensic on Web-based Applications using Network Forensic Development Life Cycle Method

It is important to note computer network security.At any point, a web server can be attacked.There are many types of attacks that can be carried out by attackers.One type of attack that is often carried out is a Distributed Denisal of Service (DDOS) attack.Distributed Denial of Service (DDOS) attacks are one type of attack that attackers frequently use to increase traffic to the point where the server cannot handle client requests and may even cause the server to fail.To limit the likelihood of an attack, a network security system able to detect attacks is required.Snort is a software program that is capable of detecting an attack in real time by executing a rule that produces a log file containing information about network activity.Additionally, it is used to conduct network forensic analysis using the Network Forensics Development Life Cycle (NFDLC) method, which is a branch of digital forensic science concerned with the steps necessary to discover evidence of attacks originating from log files.The analysis method is comprised of the following stages: Initiations, Acquisition, Implementation, Operations, and Disposition.According to the findings of the research, Snort's Intrusion Detection System (IDS) is capable of detecting DDOS attacks on web servers.Based on the analysis of the log files using wireshark, there are 3 IP addresses, who tried to commit crimes against the web server.From the results of the DDOS attack analysis, it can be used as digital evidence from the results of network forensic investigations.
Applying probability theory to neural networks

Using mathematical models to create an image of the human brain reproduction of machines by artificial intelligence.An artificial neural network consists of three components: input layer, hidden layers, output layer.Also, in the center of the neural network is the loss function.Which minimizes errors known as: quadratic, cross-entropy, AdaBoost, Kullback distance.Loss function should not depend on the activation values of the neural network.
USE OF DIGITAL TECHNOLOGIES IN THE EDUCATIONAL ENVIRONMENT OF HIGHER EDUCATION: OFFLINE AND ONLINE LEARNING

The article is devoted to the up-to-date problem of introduction of digital technologies by their integration in higher education teaching and learning for the purpose of formation of the independent, responsible, socially active personality. The specifics of mastering digital competence, which today is an integral component of students’ training, and due to the use of digital technologies provides future professionals with relevant knowledge, forms their ability to adequately use digital information and work in a dynamic environment. The features of the use of digital technologies in the professional offline/online activities of future specialists are discussed; the overall positive impact of use of technologies in students learning process and outcomes aimed to promote students’ active engagement and participation in the learning process inside and outside the classroom id admitted. The data also revealed digital technologies to support more transmissive ways of teaching, facilitating students individually to access, share and publish information, and significantly lesser used to promote collaborative and cooperative learning. The potential benefits of digital technologies in the classroom are revealed and can be taken to mean digital processing systems that encourage active learning, knowledge construction, inquiry, and exploration, and which also allow for remote communication as well as data sharing to take place between teachers and/or learners in different physical classroom locations. Theoretical aspects of the research are substantiated; the main intensifiers of transformation processes in education are determined; six levels of digital competence development are characterized in accordance with the specifics of professional tasks, type and level of educational training. The concepts of "digital competence", "digital technologies", "digitalization" are disclosed. The effectiveness of using digital technologies in order to increase the efficiency of practical training of future professionals in higher education institutions is substantiated. The most widespread digital technologies are singled out and systematized into taxonomy in the context of formation of digital competence of future specialists.
Efektivitas Penggunaan Aplikasi Google Classroom dalam Meningkatkan Kualitas Pembelajaran PAI Mahasiswa IAIN Curup pada Masa Pandemi Covid-19

To avoid the spread of Covid-19, the learning process is carried out through online method, including IAIN Curup. Since April 2020 IAIN Curup has been implementing online learning. During online learning, the lecturers use various online applications to support the learning process so that it can run well. The purpose of this study is to discover how the effectiveness of using Google Classroom application to improve learning quality of IAIN Curup students during the Covid-19 pandemic. This research used qualitative approach, data analysis used qualitative analysis methods by using non-statistical techniques. Reserach data were collected from interviews, observation and documentation. This research shows that the effectiveness of learning by using Google Classroom is quietly effective by using strategies in the form of assignments and observations, problem-based learning models and field experiences, evaluation in the form of questions and product creation. Google classroom has several advantages such as: easy to use, saves mobile data, collects tasks precisely and saves storage memory. Meanwhile, the disadvantage is that communication is not well established
The Sonority Dispersion Principle in Albanian

An important pattern that is based on the sonority relationship is the Sonority Dispersion Principle (SDP) formulated by Clements (1990). This principle can serve as the basis for classifying syllable types in terms of relative complexity. The notion “dispersion in sonority” clearly defined within a demisyllable. According to this principle, the sonority slop from the onset to the syllable nucleus is maximized and from the nucleus to the coda is minimized. The purpose of this paper is to provide some data on the Albanian language by dividing the sounds within the demisyllable, by analyzing the combinations of sounds in the onset and in the coda. According to SDP, in Albanian the optimal syllable structure with 2 elements is C[stop]V, while among the optimal structures with 3 elements, the types C[stop]VC[glide], C[stop]C[liquid]V, C[stop]C[nasal]V and C[fricative]C[liquid]V predominate. The analyzed data are important and serve to deeply recognize the characteristics of phonological system of Albanian and can also serve for its approach to typological level.
Automatic Facial Mask Rule Violation Detection using Keras &amp; Tensorflow to Limit COVID-19

Abstract: COVID-19 is a pandemic disease that spread by itself coming in the contact of people. It was initially started from China and now it has been spread all over the world and many casualties have been occurred. Social distancing commonly known as physical distancing is a non-pharmaceutical approach through which it can be reduced. But social distancing only works when people started wearing mask because it can spread by sneezing even having distance among people. So wearing mask is mandatory to stop spreading this virus at its possible extent. In this paper, it has been intended to identify the people who are wearing mask or not. By the help of CCTV camera it can be recognized at the entrance of various public places such as mall, airport, railway station, mart and many more. If facial mask can be recognized effectively with high level of accuracy then it can become mandatory for people who are violating the rules. The proposed system uses Keras and Tensorflow model for identifying whether people are following the rule or not. Tensorflow is a deep learning methodology through which facial mask can be detected with all kind of situations. Proposed system is able to classify whether a person wear a mask or not, it is also able to identify whether people incorrectly wearing mask i.e. partial wearing. It is mandatory to identify whether people are properly using the mask or not. System identify this kind of situation and classified them accordingly. System uses hybrid technique by combining two algorithms i.e. keras and tensorflow. By combining both the systems it can be identified more precisely to identify the rule violations. Keywords: COVID-19, Facial Mask, Convolutional Neural Network, Classifiers, Machine Learning, Image Processing, Pattern Recognition.
Creating University Students’ Civic-minded Culture by Analyzing Russian Feature Films

The article discusses the following research areas in the context of educating university students for civic engagement based on the material of Russian feature films:-analysing patriotic feature films, historical dramas and war films about the exploits of Russian people, films about love and self-sacrifice for the Motherland;-analysing Russian feature films about real heroes and their exploits, as well as films about heroic deeds committed by ordinary people in peacetime, films about public and official duties;-analysing film images of famous Russian historical personalities in Russian and foreign feature films;-analysing feature films about love for the "small" homeland, about professional and civic responsibility;-analysing film images of national heroes or famous citizens of various professions who contributed to the development of Russia, its culture, science, art, sports, etc.;-a comparative analysis of Russian and foreign film adaptations of classic Russian literary works, a critical analysis of national stereotypes in Russian and foreign feature films;-a critical analysis of antisocial images in feature films in order to form correct models of social and civic consciousness and behaviour among university students;-film education of youth based on social film dramas.
DEEP FLOW: an embodied materiality of dance, technology, and bodily experience

In this research article, I argue that Deep Flow is an embodied materiality that may be experienced by exploring performative phenomenologies, entwining two different sets of research practice: phenomenological methodologies and artistic practice. In Deep Flow the practitioner entangles phenomenological methodologies, methods and research practices performatively such as embodied dance practice, the felt senses, drawings, verbal feedback and their analyses in relation to biometric data, from an embodied heart rate monitor. By looking inwardly, the practitioner experiences embodied phenomena and reveals these experiences in artistic practices in relation to the worlding in which they find themselves. These outcomes are considered as being differing materialities, flowing and converging through relational and phenomenological practice, Deep Flow and through this they become embodied by the practitioner, where new forms of embodied materialities emerge. I argue that in my practice, this is an experiential state, Deep Flow, where all human and non-human elements of the dance practice flow and course through the practitioner as an embodied materiality.
STUDENT RESILIENCE IN THE MANAGEMENT OF TECHNOLOGY IN TIMES OF THE PANDEMIC

&#x0D; &#x0D; &#x0D; Introduction. The present article aims to develop a cross-sectional, non-experimental quantitative research that allows knowing the level of resilience and its factors in the management of technology during the time of the pandemic in secondary school students belonging to EI 1255 Walter Peñaloza Ramella, from the Self-managed Community of Huaycán, located in the district of Ate, city of Lima - Peru. Materials and methods. The study involved 187 students between the ages of 14 and 18, the Wagnild &amp; Young Resilience Scale was used, the Peruvian version, adapted by Gómez (2019), which includes Factor I: Personal competence and Factor II: Self-acceptance. Results. 50.3% of the students present a level of resilience between high and very high. Conclusion: Students with more knowledge in the management of Tics, 150 (80.21%) in reference to those with less information 37 (19.8%) at the Factor I level, digital natives tend to trust their ability to respond and adapt to achieve their goals and at Factor II level they are flexible, persistent and remain calm in the face of acquired skills despite adversity.&#x0D; &#x0D; &#x0D;
The Implementation of Scientific Approach in English Teaching Practice

This study explores the challenges in implementing the scientific approach perceived by the EFL pre-service teachers and investigates the EFL pre-service teachers' strategies to overcome the challenges.This research applied a descriptive qualitative design with the in-depth interview as the data collection method.This study was conducted at the English Language Education Department (ELED) at a private university in Yogyakarta with 5 EFL pre-service teachers who employed the scientific approach in their teaching practices when doing their internship program as the participants.This research found that the EFL pre-service teachers faced some challenges in implementing the stages of the scientific approach.These challenges were the challenge in asking the students to ask questions, maintaining the students' focus in gathering information, asking the students to have a discussion, and enhancing the students' self-confidence to share the conclusion of their discussion.However, there were some strategies that these EFL pre-service teachers applied to overcome these challenges.The strategies were helping the students to make questions, monitoring the students in gathering information, monitoring the students in doing the discussion, and building the students' self-confidence.
MONITORING FEATURES OF THE CLIENT PART OF MOBILE APPLICATIONS

This paper considers the features of monitoring the client part of mobile applications. The main parameters of the process of information transfer from the end user to specialized monitoring systems are highlighted. The possibilities of modern systems for collecting, processing and visualizing user data are analyzed. The structure of a standard approach to monitoring user data for mobile applications has been developed. The principle of linearity of step-by-step collection and processing of information was used to develop the structure. The possibilities of forecasting the main long-term collection of user data are analyzed. The list of modern systems of client monitoring, and also their possibilities of interaction is formed. The advantages and disadvantages of these systems are considered.
MULTI-INSTANCE LEARNING FOR RHETORIC STRUCTURE PARSING

It would be helpful to consider various topic-independent features: syntax, semantics, and discourserelations between text fragments to accurately detect texts containing elements of hatred or enmity.Unfortunately, methods for identifying discourse relations in the texts of social networks are poorlydeveloped. The paper considers the task of classification of discourse relations between two parts ofthe text. The RST Discourse Treebank dataset (LDC2002T07) is used to assess the performance of themethods. Since the size of this dataset is too small for training large language models, the work uses amodel-pre fitting approach. Model pre-fitting is performed on a Reddit user comment dataset. Textsfrom this dataset are labeled automatically. Since automatic labeling is less accurate than manualmarking, we use the multiple-instance learning (MIL) method to train models. A distinctive feature ofmodern language models is the large number of parameters. Using several models at different levels ofsuch a text analyzer requires a lot of resources. Therefore, for the analyzer to work, it is necessary touse high-performance or distributed computing. The use of desktop grid systems can attract andcombine computing resources to solve this type of problem.
The main aspects of modernization of the higher education system in the perception of students and teachers: a sociological analysis

Introduction. The Rome Conference of Ministers of Science and Higher Education set a new direction for the implementation of key commitments necessary for the full functioning of the European Higher Education Area. As a participant in the Bologna process, Russia is rapidly increasing the pace of modernization in the higher education system, which actualizes the need to analyze the results and consequences of the ongoing reforms. The research purpose is to identify the specifics of perception of the main aspects of the modernization process by students and teachers as key agents in the provision and consumption of educational services. Materials and methods. During the study, a questionnaire survey was conducted among first-to-fifth year students (N=300) and teachers (N=100) of the Volgograd Institute of Management, a branch of the Russian Academy of National Economy and Public Administration. Results. The research results demonstrate an ambiguous attitude towards the ongoing reforms. 39.3% of the surveyed students and 37.8% of the teachers support the transition to a two-tier higher education system, 28.6% of the students and 44.4% of the teachers do not approve of it. The main risk of the reform relates to the loss of the quality of education when changing the field of study and a student’s obligation to obtain a master’s degree in order to be in demand in the labor market. The transition to a modular-rating training system is perceived positively by more than a third of the surveyed students and teachers. Negative consequences of the reform affected teachers to a greater extent: an increase in time costs and the risk of error when completing modules with teaching materials. The transition to the credit system as a tool for the development of academic mobility is supported by 62% of the surveyed teachers and 39.9% of the students. The contradictory attitude to stimulating the change of universities is associated with the risks of student adaptation and stereotyped education as the consequences of reforms. Conclusions. Based on the research results, the authors come to the conclusion that to overcome the ambiguous attitude towards the ongoing reforms, it is important to develop and implement measures to highlight the current modernization directions, goals and results: at meetings of the Academic Council or through teaching and student exchanges at the regional and international level. Also, the identified problems can be compensated by the intensification of advanced training courses taken by teachers to use the tools of work against the backdrop of new tasks, the development of a regulatory framework that regulates the transition between levels of education and measures to prevent the risks of students’ adaptation when changing universities.
Lantern to the Underworld - Following User Actions Using Bing URL Parameters When Child Exploitation Terms Are Suggested by the Search Engine

During a 2016 criminal investigation overseen by the authors, a discovery was made that the Bing search engine was suggesting search terms known to be associated with child exploitation materials.This was in response to a non-contraband search by a subject, leading to increasingly explicit suggestions.This information led to the discovery that, with a user's browser history files, the specific actions taken by a user could be isolated and tracked using Bing's own unique URL parameters.While the suggestion of contraband terms by the Bing search engine has since ceased, there has been little to no research conducted on analyzing a user's browser activity in order to determine their specific actions behind the keyboard through the use of these unique URL parameters.The purpose of this paper is to document Bing's URL parameters related to image searches (specifically the FORM parameter) in order to detail how a user's actions during searching may be determined by an analyst.The authors also provide a new tool for creating a timeline of Bing image search events when an analyst possesses a user's browser history files.