Reviewerly/exHarmony huggingface dataset:
On Western Experience of Student Research Activity Organization and on Opportunities for Its Improvement at Baikal State University

The purpose of this paper is to define main disadvantages of current system of research activity at Russian universities, on the basis of analyzing valuable western experience, highlighting the research course content at American universities, as well as considering the biggest drawbacks of national university courses and propose some practical solutions. This paper examines main features of American-based Research Methods courses taught at graduate level, by analyzing their structure, requirements, practice-based assignments, and other aspects. We also provide in-depth analysis of how student research activity is organized within undergraduate system of Russian education, by assessing its main characteristics and challenges. We demonstrate that the main challenge faced by Russian educators is that undergraduate (bachelor / specialist) programs at Russian universities do not provide any core curriculum Research Methods courses while having research paper as the main graduation requirement. We argue that early-on introduction of a specially designated research design course will be to a great advantage for our students as it will establish solid foundation for student research work at sophomore and senior levels. Therefore, we recommend that a basic Research Methods course should be included as a required course at Baikal State University for the majors with term research projects and final graduation research papers.
English through the use of smartphone apps as motivation for students from the School of Tourism and Gastronomy

With students spending up to 20% of their in-class time texting, emailing, and checking social media, it is no wonder the problem about smartphones in the classroom arises. This article presents results of a piece of research focused on the analysis and reflection of the smartphone applications used with higher education students in order to provide, as well as to improve, their results in departmental exams while they are studying English at a professional level.&#x0D; The study took place over one semester of a curricular English course where smartphone applications were carefully selected and integrated into the current didactic units of the standardized institutional English program, with the purpose of finding, in the school of tourism and gastronomy, not only a solution, but a different approach to turning the problem into part of an updated methodology for the foreign language classroom. &#x0D; The results of this research are expected to have a significant impact on the improvement of the methodology used by teachers at all the schools on our institutional English program with the effect that, once the teachers begin to implement the systematic use of smart phone applications in the delivery of their lessons, learners will hopefully perceive the English course as more relevant and meaningful and be motivated to achieve the expected results.
Locality Sensitive Hashing for Efficient Similar Polygon Retrieval

Locality Sensitive Hashing (LSH) is an effective method of indexing a set of items to support efficient nearest neighbors queries in high-dimensional spaces. The basic idea of LSH is that similar items should produce hash collisions with higher probability than dissimilar items. We study LSH for (not necessarily convex) polygons, and use it to give efficient data structures for similar shape retrieval. Arkin et al. represent polygons by their "turning function" - a function which follows the angle between the polygon's tangent and the $ x $-axis while traversing the perimeter of the polygon. They define the distance between polygons to be variations of the $ L_p $ (for $p=1,2$) distance between their turning functions. This metric is invariant under translation, rotation and scaling (and the selection of the initial point on the perimeter) and therefore models well the intuitive notion of shape resemblance. We develop and analyze LSH near neighbor data structures for several variations of the $ L_p $ distance for functions (for $p=1,2$). By applying our schemes to the turning functions of a collection of polygons we obtain efficient near neighbor LSH-based structures for polygons. To tune our structures to turning functions of polygons, we prove some new properties of these turning functions that may be of independent interest. As part of our analysis, we address the following problem which is of independent interest. Find the vertical translation of a function $ f $ that is closest in $ L_1 $ distance to a function $ g $. We prove tight bounds on the approximation guarantee obtained by the translation which is equal to the difference between the averages of $ g $ and $ f $.
Automatic Historical Feature Generation through Tree-based Method in Ads Prediction

Historical features are important in ads click-through rate (CTR) prediction, because they account for past engagements between users and ads. In this paper, we study how to efficiently construct historical features through counting features. The key challenge of such problem lies in how to automatically identify counting keys. We propose a tree-based method for counting key selection. The intuition is that a decision tree naturally provides various combinations of features, which could be used as counting key candidate. In order to select personalized counting features, we train one decision tree model per user, and the counting keys are selected across different users with a frequency-based importance measure. To validate the effectiveness of proposed solution, we conduct large scale experiments on Twitter video advertising data. In both online learning and offline training settings, the automatically identified counting features outperform the manually curated counting features.
The Application of Think Pair Share Learning Model to Increase Student Activity and Learning Outcomes

This research aims to improve student activity and learning outcomes through the application of the Think Pair Share learning model. This type of research is classroom action research (CAR). The subjects of this research were students of class VII MTs. Nurul Islam Ranuyoso. The data collection methods used was test, observation, interview and documentation methods. This research was conducted in two cycles, namely cycle I and cycle II. Based on the results of the research conducted, it was obtained data related to student activity in the first cycle of 63% and the second cycle of 87%. Then for the completeness of student learning outcomes before the research was 36.6%, in the first cycle it was 54.5%, and in the second cycle it was 82%. Based on the results obtained, it can be concluded that the application of the Think Pair Share learning model can increase student activity and learning outcomes. Keywords: think pair share, activity, learning outcomes
Evaluation in the social sciences, a student perspective

Learning assessment has been widely addressed by theorists and researchers; however, most of them have focused their attention on the relationship between teaching and assessment, leaving student participation behind. Therefore, the objective of this research is precisely to interpret the perceptions that students have regarding the assessment of their learning in the area of social sciences. The research is of a mixed type, not experimental, with a descriptive and narrative design in the qualitative area. The results in the perception of assessment indicate that 1.7% consider it adequate, 95.4% not very adequate and 2.9% inadequate; in the cognitive dimension 4.6% adequate, 92.5% not very adequate and 2.9% inadequate; in the procedural dimension 1.2% adequate, 82.1% not very adequate and 16.7% inadequate, and in the attitudinal dimension 12.4% adequate, 83.9% inadequate and 3.7% inadequate. These students’ perceptions are conclusive, so therefore, their role, opinion and perception about evaluation should be taken into consideration, since they are the main actors in the education system. In this sense, teachers should reflect on and improve their form of assessment and place emphasis on ensuring that students understand how they will be assessed and change their perception of assessment. Finally, students should actively participate in planning and modifying pedagogical documents in order to meet their needs and contribute to strengthening the teaching-learning process.
Key indicators of the economic activity of educational institutions: modeling and prospects

The results of activities in the field of education appear in the form of service and, as a rule, do not have a clearly expressed material form. The measurement of the economic activity of educational institutions requires a clear definition of the main categories and values necessary for its calculation. It is necessary to evaluate the economic activity and the rationality of the cost of resources for any purpose based on certain criteria. The article analyses the scientific literature on the problem of determining indicators of the economic activity of educational institutions. Based on an expert survey, the principles of building a system of indicators characterizing economic activity at a university have been defined, analytical support for the assessment of economic activity of university departments has been developed, and the sequence of determining the economic rating of departments of a higher education institution on the basis of the performance indicator has been presented.
DESCRIPTIVE STUDY OF STUDENTS CRITICAL READING SKILLS IN NARRATIVE TEXTS

The objective of this study is to know whether the student's response and finding strategies that are used in teaching reading especially critical reading skills in narrative texts. The research problem is how students respond and what are strategies used by students to critical reading skills in narrative texts. The qualitative approach was applied in this study with a case study as the research design using observation and interview guidelines as instrument research. In this research, subject observation consists of 17 students and the subject interview consists of 5 students that have been choosy from the result observation was given. Based on the results of the observation and interview, the researcher could conclude that student respond and strategy was using student in study critical reading skills in the narrative text was good. This result indicates that the narrative text was effective to increase the understanding of the reading skills of students in predicting, synthesizing, and evaluating a text. Through the student's response, the student knows and understands critical reading in narrative text, but they still lack in using critical reading to found a message in the story. Besides that, the student's strategy found that students knew strategy in critical reading like predicting, questioning, clarifying, and summarizing narrative text. It can be concluded that students could easier to understand the content and purpose of narrative text. As a result, it can help students in learning to critical reading in the text narrative that their knowledge skills read can increase.
Document Level NMT of Low-Resource Languages with Backtranslation.

This paper describes our system submission to WMT20 shared task on similar language translation. We examined the use of documentlevel neural machine translation (NMT) systems for low-resource, similar language pair Marathi−Hindi. Our system is an extension of state-of-the-art Transformer architecture with hierarchical attention networks to incorporate contextual information. Since, NMT requires large amount of parallel data which is not available for this task, our approach is focused on utilizing monolingual data with back translation to train our models. Our experiments reveal that document-level NMT can be a reasonable alternative to sentence-level NMT for improving translation quality of low resourced languages even when used with synthetic data.
Protuberancy State Recognition in Human Visual System

The human visual system (HVS) seeks toward select relevant region in the direction of level rear method attempts. visual concentration effort to guess the essential region of films or imagery observed through an individual eye. Such representations, are functioned to areas similar to workstation work, MPEG conventions, and an eminence evaluation. while numerous models are expected, only some of them be pertinent enroute for high dynamic range (HDR) picture substance, in addition to no effort has been completed for HDR visualization. Furthermore, the disadvantage inside the obtainable form is with the intention, they couldn't reproduce the uniqueness of HVS beneath the extensive shining array established in HDR substance. This paper gets the better of these troubles by the process approach to represent the bottom-up visual saliency for HDR input through merge spatial and temporal image features. An examine of a human eye ball movement information make sure the efficiency of the proposed model. Evaluation using 3 well-known quantitative metrics show that the proposed model significantly gets better predictions of visual concentration for HDR substance.
Teachers' Computer and internet Literacy

Today, it is necessary for each individual to obtain the abilities of using modern computer techniques in order to lead an independent and creative professional and social life. The area of Teachers' Computer and Internet Literacy in Slovenia hasn’t been researched much yet. We have come out of the research problem that despite fostering ICT and EU investment in digital literacy of teachers, they are still not enough qualified for the use of ICT. In this article we have written the results from a research of teachers’ computer and internet Literacy. In theoretical part, we have presented the observation of different kinds of literacy in EU and initiatives to increase Computer and internet Literacy. In the empirical part of work, we have concentrated on the research of Computer and Internet Literacy of teachers at primary schools. In the survey that we have done among primary school teachers, we have compared the obtained data from the survey with Eurostat data. The analysed data was whit the programme for statistical analysis, statistically analysed. At the end of our work, we set guidelines for further research with a new method.
Order Embeddings from Merged Ontologies using Sketching

We give a simple, low resource method to produce order embeddings from ontologies. Such embeddings map words to vectors so that order relations on the words, such as hypernymy/hyponymy, are represented in a direct way. Our method uses sketching techniques, in particular countsketch, for dimensionality reduction. We also study methods to merge ontologies, in particular those in medical domains, so that order relations are preserved. We give computational results for medical ontologies and for wordnet, showing that our merging techniques are effective and our embedding yields an accurate representation in both generic and specialised domains.
Review of Forbidden Configurations in Discrete Geometry by David Eppstein

In 1930, the mathematician Esther Klein observed that any five points in the plane in general position (i.e., no three points forming a line) contain four points forming a convex quadrilateral. This innocentsounding discovery led to major lines of research in discrete geometry. Klein's friends Paul Erdős and George Szekeres generalized this theorem, and also conjectured that 2k-2 + 1 points (again in general position) would be enough to force a convex k-gon to exist. The resolution of this conjecture became known as the "happy ending problem," because Klein and Szekeres ended up getting married. The unhappy side is that it has, to date, not been completely solved, although a recent breakthrough of Suk made significant progress. This both mathematically and personally charming little story is a great beginning for this elegant book about discrete geometry. It typifies the type of problems that are studied throughout, and also captures the spirit of curiosity that drives such studies. The book covers many problems that lie at the intersection of three fields: discrete geometry, algorithms and computational complexity.
Fuzzy C-Means Clustering Algorithm For Grouping Health Care Centers On Diarrhea Disease

In Indonesia, public health services at the city or district level are carried out by regional public hospitals or “puskesmas” (health care centers), especially in Banyuwangi regency, East Java, Indonesia that has 45 health care centers spread throughout the villages. This research focused on the deaths of babies caused by diarrhea diseases, which are the second leading cause of death among children younger than 5 years globally. All of the health care centers need to be divided into 3 groups to find out which health care centers have the least, most moderate, and many diarrhea sufferers. Fuzzy C-Means algorithm is used to overcome this problem. The result from this research shown that 2 health care centers have the smallest member of diarrhea sufferers, 14 health care centers have a medium member of diarrhea sufferers, and the rest have a large number of diarrhea sufferers. From the result of this study, it can be a reference for the health department center in dealing with diarrheal diseases, accordingly, the infant mortality rate due to diarrheal diseases can be lowered to health care centers that have high diarrhea sufferers.
Rare earth elements and stable sulphur (δ34s) isotope of baryte mineralization in Liji Area, Northern Benue trough, northeastern Nigeria

The Liji area lithologically consists of inliers of granite and pegmatite members of the Pan-African granitoids surrounded by Cretaceous sedimentary deposits of Bima, Yolde, Pindiga and Gombe Formations. Epigenetic fracture-filling baryte mineralization hosted by granite, pegmatite and Bima Sandstone were delineated, sampled and analyzed for rare-earth elements (REEs) and stable sulphur isotope geochemistry. The REEs of the distal (unaltered) rocks indicated normal values (26.15-36.81 ppm) before mineralization was marked by enrichment of light rare-earth elements (LREEs) (27.94 ppm) relative to the heavy rare-earth elements (HREEs) (5.34 ppm) and negative Eu anomalies typical of calc-alkaline granites of Pan-African age. The baryte separates were marked by enriched LREEs and depleted HREEs with pronounced positive Eu anomalies indicating the invasion and consequent deposition of baryte-rich hydrothermal fluid under oxidizing conditions in the N-S and E-W striking fractures. Stable sulphur isotope of the baryte gives values that ranged from 18.3 - 19.8o/oo CDT indicating that the source of sulphur is from ocean water and not from magmatic, fresh water and connate water sources from the nearby granite, pegmatite and sandstone.&#x0D; Keywords: Baryte, Mineralization, Hydrothermal, Liji, REE, Sulphur-Isotope.
Introduction of Information Business Course in the Content of the Computer Science Program

In today's rapidly changing world of innovative technologies, it is necessary to search for means of modernization of educational process, where along with implementation and constant improvement of new technologies and software it is also important to update the content of education system as well.The modern and developing education institution requires experts in the various related fields.First, it is necessary to know the modern innovative technologies; second, to employ these technologies in various sectors and activities.With regard to the above, the content of education programs with respect to the development of the promising areas should be revised these days.The given article analyses the development of educational content in computer science of Kazakhstan, determines the theoretical basis, development and practical realization of introducing the content of computer science in secondary school.The authors of this article introduced information business in the course of computer science with an aim to develop the content of computer science discipline by introducing elements of information business.The content and structure of training in the fundamentals of information business was introduced in the educational process as a separate elective course and as a fragment of general education computer science course.
Head Posture Recognition Based on Newton-Raphson Method

In the research of flight simulator, the head posture recognition of pilot is very important. The accuracy of head posture recognition directly affects the quality of flight simulation. In this paper, a head posture recognition method is proposed for Flight Training Simulation. Firstly, the development process and working principle of Helmet Mounted Sight (HMS) are deeply studied, then the principle of Newton-Raphson method is introduced, after that the head posture recognition method based on Newton-Raphson method is proposed. Finally, the hardware design and software workflow of head posture recognition system are given. The simulation result shows that the method has high efficiency and accuracy and is suitable for head pose recognition.
A Framework for Fast Scalable BNN Inference using Googlenet and Transfer Learning

Efficient and accurate object detection in video and image analysis is one of the major beneficiaries of the advancement in computer vision systems with the help of deep learning. With the aid of deep learning, more powerful tools evolved, which are capable to learn high-level and deeper features and thus can overcome the existing problems in traditional architectures of object detection algorithms. The work in this thesis aims to achieve high accuracy in object detection with good real-time performance. In the area of computer vision, a lot of research is going into the area of detection and processing of visual information, by improving the existing algorithms. The binarized neural network has shown high performance in various vision tasks such as image classification, object detection, and semantic segmentation. The Modified National Institute of Standards and Technology database (MNIST), Canadian Institute for Advanced Research (CIFAR), and Street View House Numbers (SVHN) datasets are used which is implemented using a pre-trained convolutional neural network (CNN) that is 22 layers deep. Supervised learning is used in the work, which classifies the particular dataset with the proper structure of the model. In still images, to improve accuracy, Googlenet is used. The final layer of the Googlenet is replaced with the transfer learning to improve the accuracy of the Googlenet. At the same time, the accuracy in moving images can be maintained by transfer learning techniques. Hardware is the main backbone for any model to obtain faster results with a large number of datasets. Here, Nvidia Jetson Nano is used which is a graphics processing unit (GPU), that can handle a large number of computations in the process of object detection. Results show that the accuracy of objects detected by the transfer learning method is more when compared to the existing methods.