Reviewerly/exHarmony huggingface dataset:
The Analysis of the Influence of Information Environment on the Efficiency of Training Future Masters for Research Activity

The article presents the results of research on the problem of training future masters of humanities for research activity under the conditions of the information environment. The authors reviewed scientific literature, determined the mainstreams of the future masters’ training for research activities, and the dynamics of their readiness for these activities, studied the influence of the information environment of higher educational institutions on the level of the development for research activities. They also developed the provisions for methodological recommendations. The information environment is understood as the possibility to obtain the necessary data, evidence, hypotheses, theories, etc. Much attention is paid to ensuring the quality of professional training through the introduction of stagewise higher education, the formation of the future masters’ professional mobility under the labour market conditions. Based on the review of psychological and pedagogical literature, we determined the pedagogical conditions for the development of future masters' readiness for research activities: ensuring the future masters’ training within the modern information environment; formation of the future masters’ motivation for research activities in the information environment; introduction of a competent approach into the future masters of humanities training; ensuring the integration of academic subjects in the future masters’ training for research activity. Based on the results of the study, we determined the main tasks of further research. The authors confirmed the reliability of the research results by the Student’s t-test and Fisher’s F-test.
Road and Vehicles Detection System Using HSV Color Space for Autonomous Vehicle

Nowadays, an a utonomous vehicle is one of the fastest-growing technologies. In its movements, the autonomous vehicle requires a good navigation system to run on the specified lane. One sensor that is often used in navigation systems is the camera. However, this camera is constrained by the process and its reading, especially to detect roads that are suitable for the vehicle's position. Thus, t his research was conducted to detect the road and distance of nearby objects using the HSV color space method. From the test results, this research succeeded in detecting roads with an accuracy of 78.012 %, and an accuracy of 80% for the safe/unsafe area detection . The results also showed that the method achieved an accuracy of 80% and 74.76% for object detection and object distance detection , respectively. The results of this research implied that the HSV method was quite good with fairly high accuracy to detect roads and vehicles.
Application of Big Data Analytics in Detection of Suspected Thieves in Local Trains

Huge records accumulated through computerized admission assortment (AFC) structures give chances to perusing every close to home visiting practices and aggregate portability designs in city areas. Existing investigations on AFC realities have customarily fixated on making sense of travelers' movement styles. In any case, we innovatively utilized such information for distinguishing pickpocket suspects. Halting pickpockets inside the open travel gadget has been basic for improving traveler pleasure and open assurance. In any case, in work out, it is testing to recognize hoodlums from standard travelers. In this paper, we built up a speculate discovery and observation gadget, that can see pickpocket presumes dependent on their step by step travel records. In particular, we originally separated various gainful capacities from every traveler's step by step exercises inside the travel device. At that point, we adopted a -step strategy that abuses the qualities of unaided anomaly identification and regulated class models to select hoodlums, who by and large hotshot atypical visiting practices. Test results built up the adequacy of our methodology. We likewise advanced a model contraption for capacity utilizes with the guide of security representatives.
Linguistic Features Of Gender Differences In Blog Communication

Virtual communication space possesses various features, such as subjectivity of information, interactivity, hypertextuality, global nature, creativity, anonymity and fragmented structure as well as involvement of the reader into a dialogue, a combination of different types of discourse, similar speech patterns of communication, free choice of language and specific computer ethics.The present article reveals that a blog post is a unique genre of virtual communication that can used in many formats.It is characterized by peculiar structure, linguo-stylistic means, and ways of constructing personal identity.Blog posts cover a wide range of topical issues and events that occur in modern fashion, sports, music, art and entertainment and are widely discussed by bloggers.Researchers distinguish both gender similarities and differences in English-speaking blogosphere.Gender differences in virtual communication depend on the communication settings, type of discourse and the time parameter.At this stage of the study, the analysis reveals that in female blogs the self-expression strategy is actualized by various tactics, which are in their turn, realized by the lexical and syntactical means, such as evaluative epithets with the positive connotation, the abundant use of intensifiers, lexical approximators, metaphors, comparisons, elliptical sentences, modal verbs, and emphatic constructions.In male blogs the self-description as well as the selfexpression strategies are realized by jargon words and terms, slang and taboo words, logical comparisons and simile, idiomatic expressions and contracted word forms as well as interjections.
Vehicle Detection, Tracking and Counting Using Gaussian Mixture Model and Optical Flow

Vehicle detection, tracking, and counting play a significant role in traffic surveillance and are principle applications of the Intelligent Transport System (ITS). Traffic congestion and accidents can be prevented with an adequate solution to problems. In this paper, we implemented different image processing techniques to detect and track the moving vehicle from the videos captured by a stationary camera and count the total number of vehicles passed by. The proposed approach consists of an optical flow method with a Gaussian mixture model (GMM) to obtain an absolute shape of particular moving objects which improves the detection performance of moving targets.
Soft Skills Development In Teaching Business Interaction

The article deals with the problem of subject’s soft skills development and aims at proving the potential of the process of teaching business interaction in it. The necessity of studying this question arose from the changes in the labour market which have been happening for the last two decades. Literature analysis and knowledge synthesis allowed specifying the notion of soft skills and clarifying the range of the most important ones in professional activity. The potential of teaching business interaction lies in interactive and project methods contributing to the development of communicative-interactive, analytical, reflexive and time-management skills, critical thinking via actualization of pair and group work in collaborative interactive activity. The main unit of teaching business interaction is a business communicative-interactive task. Being the basis of any interactive learning method, challenging interactive tasks provide the subject’s soft skills development through taking multiple decisions on various problems in real and modeled situations. Communicative-interactive tasks can be different according to their aim, complexity, number of participants, content and conditions. The further research can be done on finding out the most effective interactive methods for developing soft skills and ways to measure them; designing a set of interactive challenges aimed at subject’s soft skills development in teaching business English.
DEEP LEARNING BASED OPTICAL FLOW ESTIMATION FOR CHANGE DETECTION: A CASE STUDY IN INDONESIA EARTHQUAKE

Abstract. Real-time change detection and analysis of natural disasters is of great importance to emergency response and disaster rescue. Recently, a number of video satellites that can record the whole process of natural disasters have been launched. These satellites capture high resolution video image sequences and provide researchers with a large number of image frames, which allows for the implementation of a rapid disaster procedure change detection approach based on deep learning. In this paper, pixel change in image sequences is estimated by optical flow based on FlowNet 2.0 for quick change detection in natural disasters. Experiments are carried out by using image frames from Digital Globe WorldView in Indonesia Earthquake took place on Sept. 28, 2018. In order to test the efficiency of FlowNet 2.0 on natural disaster dataset, 7 state-of-the-art optical flow estimation methods are compared. The experimental results show that FlowNet 2.0 is not only robust to large displacements but small displacements in natural disaster dataset. Two evaluation indicators: Root Mean Square Error (RMSE) and Mean Value are used to record the accuracy. For estimation error of RMSE, FlowNet 2.0 achieves 0.30 and 0.11 pixels in horizontal and vertical direction, respectively. The error in horizontal error is similar to other algorithms but the value in vertical direction is significantly lower than them. And the Mean Value are 1.50 and 0.09 pixels in horizontal and vertical direction, which are most close to the ground truth comparing to other algorithms. Combining the superiority of computing time, the paper proves that only the approach based on FlowNet 2.0 is able to achieve real-time change detection with higher accuracy in the case of natural disasters.
PRACTICAL USE OF OFF-THE-SHELF VIRTUAL REALITY FOR DISTANCE EDUCATION - A LOOK AT THE FEASIBILITY OF NON-EXPERT USE

As the potential value of online learning and distance education becomes increasingly clear (considering, e.g., global health and climate change) we are motivated to push for practical use of emerging technologies at an accelerated pace, to further facilitate rich and flexible distance education.While the pedagogical value of lectures has been often questioned, it remains a common method of instruction, making them relevant to investigate within digitalisation.Virtual Reality (VR) affords valuable embodied experiences and is currently at a point where it is within reach for non-experts, but may require considerable additional effort.By focusing on the use of off-the-shelf hardware and software to give virtual lectures, a larger number of educators can start experimenting within their comfort zone.The purpose of the current paper is to contribute to the acceleration of this process by describing challenges encountered in such an attempt to quickly employ readily available VR technology to give a lecture in VR.Is it possible for educators without previous expertise in VR to start using this technology now?What factors can be considered to make the experience positive to both educators and students?The setup of the VR lecture in this case study had the lecturer entering a virtual environment remotely (from another city) using the free VR application Bigscreen with students and three observing coteachers entering the same environment being co-located in one physical room.The study was performed as an action research intervention, and the results were documented with ethnographic observations and a focus group.Some issues encountered may be avoided or minimized by raising awareness beforehand and additional preparation.Based on the present study, technical and ethical recommendations are given for which issues should be prioritized and how they may be dealt with, regardless of the educators' level of expertise, to be able to successfully conduct a VR lecture.
The Problem Of Constructing Linguistic Patterns For Detecting ‘Precedent’ Texts (In Headlines)

The given article follows the author's research in automated indexation of 'precedent' texts in newspaper headlines.The previous work describes the first three stages of the research delineating the corpus for analysis and the survey to reveal general recognition of the precedent texts.As the original text (precedent pretext) is transformed by the headline's author its recognizing may be found hard, which was shown by the results of stage three.Thus the fourth stage, described in the given article, aims at outlining the borders of morphological/syntactical alternations of the original text that distinguish between recognition and non-recognition (very rare cases of recognition) of this precedent text disguised in the headline.The research was conducted through the survey.The questionnaire contains headlines with precedent texts of different origin: slogans, proverbs, book titles, etc.The assignment was to recognize and comment upon the precedent text in the transformed samples that included both existing headlines from the newspapers as well as the ones created by the author according to typical models of precedent text transformations, which were obtained from the analysis of the previously collected corpus.The results show most productive (in terms of recognition) ways of transforming precedent texts into headlines that can serve as a basis for constructing linguistic patterns that will further on help create automatic search and indexation of precedent linguistic phenomena in the massive of media texts.The search and indexation will be based on the general principles and regularities of understanding and recognition of precedent texts.
PERSUASIVE STRATEGIES USED IN BURGER KING’S INSTAGRAM POSTS CAPTION

Burger King is the one of the most successful fast food restaurant in the world. According to Wikipedia, there are 17,796 locations of Burger King all over the world in 2018. Burger King also has its Instagram account. Now this account has been followed by 1,6 million people and has posted 938 posts. That statistic shows that Burger King is active in social media especially in Instagram platform. The writer see the indication of the using of Persuasive Strategies because in promoting their product. In this research the writer wants to know the persuasive strategies that applied in Burger King’s Instagram post caption and the most used strategy. This research applied Qualitative Method as research method. This research has two findings, first, there are 13 strategies that appear in Burger King’s Instagram post caption they are, Anecdote, Assonance, Cliché, Connotation, Evidence, Everyday/Colloquial Language, Hyperbole, Imagery, Inclusive Language, Pun, Repetition, Rhetorical Question, and Simile. Second, the most used strategy is Everyday/Colloquial Language.
English teachers’ methods in teaching reading comprehension of procedure text

This study focuses on English teachers’ methods in teaching reading comprehension of procedure text. The main purpose of this study is to describe the methods used by English teachers and reveal the strengths and weaknesses of those methods used for teaching reading comprehension of procedure texts. The research was a qualitative case study. The participants of this research were two English teachers at one of junior high schools in Semarang in the academic year of 2019/2020. In collecting data, several data collection instruments were used, including: interview, observation guideline and document analysis checklist. The findings showed that English teachers planned the teaching materials and strategies in advance. They also used various methods in teaching reading of procedure text. Both teachers almost used the same methods which were audio-visual method, scaffolding, grammar-translation method, and project-based learning. The difference was in the step of the strategy implementation. In addition, the findings showed that the most appropriate method in teaching reading comprehension was grammar-translation method since it helped students comprehend the procedure text. There were several students who still had a hard time following the lessons. Teachers are supposed to make sure that all students have understood the whole text or not and they should observe the students’ situation and needs so that the teaching and learning is contextual.
Tracking Emotions through Facial Expressions in Online Education Systems Based on Transient Emotion Peak

Two types of students' performance evaluation mechanisms are called formative and summative.To have good results at the summative evaluation, the students must have frequent constructive feedback throughout a course.It is not an easy task for a teacher to give frequent feedback.As a solution for that, online tests can be introduced with feedback.A constructive feedback should consist of three features, i.e.Appreciation, Advice and Evaluation.When incorporating the appreciation in a feedback in an online education system, the emotions can be analysed to appreciate the student' effort.The most feasible way to analyze the emotions is through the facial expressions in an online system.However, there should be a systematic way to track the emotions based on each question, while the students are answering.This research proposes a time interval based on the transient emotion peak considering the time taken to read a question as the stimulus activity to cause an emotional change, to capture the emotional changes.A series of photographs were captured by using a webcam for each question and analysed the emotions by using MSemotion-API.At the end, a single photograph was selected based on this time, tracking the most different emotion out of the series.A video recording was taken simultaneously, and it was analysed by a psychiatrist and kept as the benchmark dataset.At the end, a cross validation test was done based on the output of API and the benchmark dataset and was noticed that this has given a good result.
AN APPLICATION OF CHORAL READING STRATEGY IN ENGLISH LANGUAGE LESSONS IN ECONOMIC TEXT TO INCREASING READING SKILLS FOR THE STUDENT GRADE XI STATE VOCATIONAL SCHOOL 2 MEDAN

The objectives of this study are: (1) to determine the application of Choral Reading learning strategies relating to texts relating to Economics in learning English; (2) to determine the effectiveness of the application of choral reading learning strategies in English learning to students' reading skills. This type of research is Classroom Action Research which consists of two cycles. Subjects in the study were students of class XI with a total of 30 students. Data collection techniques that will be used are observation, documentation, and testing. The qualitative data analysis technique is by doing reflection notes, the thoughts that arise when observing, and are the results of the process of comparing, linking, or linking the data displayed with previous data. The results of this class action research showed an increase in initial ability compared to cycle 1, namely students who completed in cycle 1 numbered 15 students or 50.00%. From the results of the second cycle, it can be written that students who have completed are 24 students from 30 students or 80.00%. From cycle 1 to cycle 2 there was a 30% increase. This proves that the use of Choral Reading learning strategies is very effective.
GEOMETRIC DISTORTION OF HISTORICAL IMAGES FOR 3D VISUALIZATION

Abstract. Archivists, historians and national mapping agencies, among others, are archiving large datasets of historical photographs. Nevertheless, the capturing devices used to acquire these images possessed a diversity of effects that influenced the quality of the final resulting picture, e.g. geometric distortion, chromatic aberration, depth of field variation, etc. This paper examines singularly the topic of geometric distortion for a co-visualization of historical photos within a 3D model of the photographed scene. A distortion function of an image is ordinarily estimated only on the image domain by adjusting its parameters to observations of point correspondences. This mathematical function may exhibit overfits, oscillations or may not be well defined outside of this domain. The contribution of this work is the description of a distortion model defined on the whole undistorted image plane. We extrapolate the distortion estimated only on the image domain and then transfer this distortion information to the view of the 3D scene. This enables to look at the scene through an estimated camera and zoom out to see the context around the original photograph with a well-defined and behaved distortion. These findings may be a significant addition to the overall purpose of creating innovative ways to examine and visualize old photographs.
Constructing Innovation and Entrepreneurship Education System for the Cultivation of Innovative Talents in Computer Major

To build an innovative and new industrialized country, it is necessary to continuously and deeply promote the reform of innovation and entrepreneurship education in colleges and universities of our country in order to train a large number of computer professionals with innovative spirit and entrepreneurial ability for our country.This article focuses on the overall ideas and specific methods of constructing the innovation and entrepreneurship education system in computer major.
DELINEATION AND CONSTRUCTION OF 2D GEOMETRIES BY FREEHAND DRAWING AND GEOMETRIC REASONING

Abstract. The creation of accurate and consistent line drawings is the subject of various applications. Prominent examples are the delineation of human-made objects in aerial images and the construction of technical line drawings, flow-charts, or diagrams. Interactive solutions usually restrict the user’s interaction during the design process to enforce geometric relations such as orthogonality or incidence. To avoid the time-consuming selection of operational modes, a freehand approach is desirable using strokes as the only user input. In this case, the construction principles have to be inferred automatically by geometric reasoning with uncertain observations. We present and discuss the corresponding methods in the context of educational technology. By introducing and utilizing a user-friendly software tool, we offer a hands-on approach to explore the feasibility and usability of the procedure. The experiments comprise the polygonal approximation of 2D shapes, theorem proving, and the construction of human-made figures.
ADAPTABLE AUTOREGRESSIVE MOVING AVERAGE FILTER TRIGGERING CONVOLUTIONAL NEURAL NETWORKS FOR CHOREOGRAPHIC MODELING

Abstract. Choreographic modeling, that is identification of key choreographic primitives, is a significant element for Intangible Cultural Heritage (ICH) performing art modeling. Recently, deep learning architectures, such as LSTM and CNN, have been utilized for choreographic identification and modeling. However, such approaches present sensitivity to capturing errors and fail to model the dynamic characteristics of a dance, since they assume a stationarity between the input-output data. To address these limitations, in this paper, we introduce an AutoRegressive Moving Average (ARMA) filter into a conventional CNN model; this means that the classification output feeds back to the input layer, improving overall classification accuracy. In addition, an adaptive implementation algorithm is introduced, exploiting a first-order Taylor series expansion, to update network response in order to fit dance dynamic characteristics. This way, the network parameters (e.g., weights) are dynamically modified improving overall classification accuracy. Experimental results on real-life dance sequences indicate the out-performance of the proposed approach with respect to conventional deep learning mechanisms.