Reviewerly/exHarmony huggingface dataset:
DBN-Based Fingerspelling Recognition Approach using Feature fusion

Abstract Sign language recognition offers effective and precise approach of recognizing gestures or postures. In this work, a vision-based framework is presented for recognizing fingerspelling alphabets and a comparison is conducted to show the efficiency of feature fusion. Fused features and Deep Belief Network are used in the proposed framework. In the experiments stage, a comparison between the fused features and the individual ones is performed by using two public fingerspelling datasets. Experiment results show the improvement of the feature fusion.
SPECIFICS OF VISUALIZATION OF STUDY MATERIAL WITH AUGMENTED REALITY WHILE STUDYING NATURAL SCIENCES

Augmented reality (AR) gives the ability to visualize an object (atoms and molecules, their interference, circuits of the devices, technological processes, etc.) as much as possible, meaning to convert a 2D image to 3D, as well as “make it alive”. The objective of the work is development of a mobile application designed for reproduction of study material in natural sciences using Augmented Reality. The main task is the selection and creation of 3D-study demonstration material and video data of practical works and laboratory experiments, according to the current programs in physics, chemistry, biology for secondary education establishments, which can be used by the teacher and pupils to prepare an effective performance. Two methods of augmented reality implementation were combined for maximal visualization of the study material. The first one is using 3D-images, which made the 2D-images of handbooks “alive”, converting them into 3D, with animation ability; the second one is reproduction of the developed video material on mobile devices by “connecting” them with individual markers for any practical or laboratory work. A mobile application for reproduction of video data in natural sciences provides the pupil with an ability to find out about the safety regulations before the work performance, chemicals and equipment, necessary for its performance and with the course of work in video. Pictures of laboratory work elements were chosen for the mobile app; they were created on “Vuforia” platform, realized in software as augmented reality objects with a multiplatform instrument for development of two- and three-dimensional applications, named “Unity 3D”. Implementation of augmented reality objects will increase the level of data memorization as a result of interactivity of its image in 3D, will give the opportunity the modern teacher to explain a big volume of theory fast and understandable, update the demonstration of study material, and for the pupils to memorize it effectively, will improve the critical thinking, boost motivation for study and will give the ability to gain some skills while performing the experiment.
An Efficient Novel Algorithm for Positioning a Concrete Boom Pump

Robots are used in many fields as they have remarkable benefits. Some of these benefits are robots precision, high productivity, time-saving and the ability to work in harsh working environments. The boom of the Concrete Boom Pump (CBP) is one of serial robot arm forms, and it is used in the field of construction. The boom base positioning is crucial since it is essential to accomplish the tasks efficiently. The boom base positions are determined according to the operator experience which consumes effort and time and consequently operation cost. Boom base positions could be determined using an automated method to save operation time. The proposed algorithm determines the boom base positions depending on the position of the concrete pouring points. The results show the ability of the proposed algorithm to determine the CBP base positions with high efficiency over other methods. Moreover, the proposed method shows low processing time than others.
Toward the Automatic Correction of Short Answer Questions

The manual correction for short answer questions is a tedious and time consuming task. This issue leads to the importance of having automatic correction systems for short answer questions. Thus this paper proposes three different approaches for correcting short answer questions. One of them is NLP-based while the others are machine learning based approaches. The three approaches are tested and compared across another two short answer correction systems that are evaluated on the same dataset. Results show that the proposed approaches outperform others that are evaluated on the same dataset.
Extracurricular activities for the subject «life safety» as a way of forming personal ULA in students of 7th grade

The article considers the questions of personal ULA development in students of 7th grade, through the organization of extracurricular activities in the framework of the subject «life safety». In the course of classes such activities as: game, research, creative, competitions, creative tasks promoting effective adaptation to the environment conditions are offered.
Approach to Association and Classification Rules Visualization

The results obtained from the use of Data Mining methods are not always convenient for human perception. In a set of associative or classification rules, in mathematical formulas, it is quite difficult for a person to quickly and easily find new and useful knowledge for him. In this regard, there is a need to create visual images of Data Mining models in a form that is convenient for human perception. In this paper the options for visualization of models of associative and classification rules are described. In each case, the advantages and disadvantages are identified, and the models visualization options are selected that have the most convenient form of presenting the results for human perception, the best in terms of presenting the information that the user may need for further analysis and decision making.
A Regression Prediction Model Based on Incremental Iteration for Big Industrial Data

The existence of a large number of data sets produced in the industry increases the need for algorithms that efficiently use resources such as storage space and computational efficiency. One of the challenges that machine learning currently faces is how to handle incremental data, especially in the case where the previous round of data has the same part of data with the current round of data. The shortcomings of existing big industrial data regression prediction models are: (1) there is a large amount of redundancy between batch data; (2) for some iterations, not every element in the working set generated by a single iteration needs to re-participate in the next iteration; In this paper, we introduce a machine learning regression algorithm based on incremental iteration. The overall goal is to reduce memory usage and optimise the computational efficiency of curve fitting in order to achieve high performance when the algorithm occurs on a large data set. The experimental results show that: (1) provides a faster regression prediction algorithm, which significantly improves the calculation efficiency and its cost; (2) provides a method of storage, which saves storage space; The proposed concepts and algorithms combine typical industrial application scenarios with advanced artificial intelligence and have the potential to accelerate the implementation of Industry 4.0.
Design of Answer-Grabbing Devices Based on Labview

Abstract Answer-grabbing devices are widely used in various TV programs, competitions and other fields. At present, with the increasing demand for fairness in competition, higher requirements have been put forward for answer-grabbing devices, such as higher sensitivity, better reliability, more powerful functions and so on. To meet this requirement, this paper designs a answer-grabbing devices based on Labview, which consists of answer-grabbing module, display module, compere button module and control module. Through design of front panel and program, debugging and operation, the functions of answer-grabbing device, as timing, scoring and zero clearing are finally realized. Experiments show that the system has high reliability, sensitivity and multiple functions.
ROBOTICS FOR EDUCATION. ASPECTS OF TRAINING PRE-SERVICE TEACHERS OF INFORMATICS

The current article deals with the urgent problems of introducing such educational discipline as "Educational robotics" into the curriculum of educational institutions. The article also considers the necessity of special training of pre-service teachers of informatics for teaching educational robotics at school and inclusion of a number of specialized educational disciplines, such as "Educational Informatics", "Robotics", "Hardware programming of microcontrollers" into their professional training. Moreover, the text of the article depicts the results of the diagnostic experiment started in 2013 on the basis of the South Ukrainian National Pedagogical University named after K. D. Ushynsky (Odessa, Ukraine) within the framework of the discipline "Programming of microcontrollers". The aforementioned course is taught for students of full-time and parttime studying in the specialty "Secondary Education (Computer Science)". The article highlights the positive aspects of the influence of teaching educational robotics at school and during professional training of pre-service teachers of informatics. In addition, the text highlights the experience of participating in the "Build Your Own AVR JTAG ICE Clone" project, which had been devoted to the study of the AVR JTAG controller. In the framework of the project participants were asked to explore the possibility of simplifying the architecture of this controller. While working on project implementation, we were given the task of making it easier to create an in-circuit debugger. The results of participation in this project were extended and continued in the framework of scientific degree work of students in the scientific direction "014 Secondary Education (Informatics)". According to the goals and objectives of the international project, taking into account the experience of working on the project "Build Your Own AVR JTAG ICE clone", the experience of cooperation with the NANITES Group and taking into account own pedagogical and methodological experience in accordance with the training needs and market demand in the framework of MoPED: Modernization of Pedagogical Higher Education by Innovative Teaching Instruments 586098-EPP-1-2017-1-UA-EPPKA2-CBHE-JP implementation we have created a program of educational discipline "Educational Robotics" which structure is described in the article.
Improving Universal Language Model Fine-Tuning using Attention Mechanism

Inductive transfer learning is widespread in computer vision applications. However, in natural language processing (NLP) applications is still an under-explored area. The most common transfer learning method in NLP is the use of pre-trained word embeddings. The Universal Language Model Fine-Tuning (ULMFiT) is a recent approach which proposes to train a language model and transfer its knowledge to a final classifier. During the classification step, ULMFiT uses a max and average pooling layer to select the useful information of an embedding sequence. We propose to replace max and average pooling layers with a soft attention mechanism. The goal is to learn the most important information of the embedding sequence rather than assuming that they are max and average values. We evaluate the proposed approach in six datasets and achieve the best performance in all of them against literature approaches.
Problems of management theory development in educational publications (incisive analysis on the basis of I.V. Ponkin's tutorial «Theory of public administration»)

The article is devoted to the problems of management theory development in educational publications. The author emphasizes that today one of the problems of various educational publications is a formal approach to their preparation and provision of educational material. I.V. Ponkin's tutorial «Theory of public administration» was used as the basis of the analysis. The author comes to the conclusion that at the present time there is a need to prepare and give such a tutorial on management, which would be based on the scientific positions of the management theory and create a basis for graduates in the formation of their managerial competencies in accordance with the Federal state educational standards of higher education and professional standards.
Beyond Word for Word: Fact Guided Training for Neural Data-to-Document Generation

Recent end-to-end encoder-decoder neural models for data-to-text generation can produce fluent and seemingly informative texts despite these models disregard the traditional content selection and surface realization architecture. However, texts generated by such neural models are often missing important facts and contradict the input data, particularly in generation of long texts. To address these issues, we propose a Fact Guided Training (FGT) model to improve both content selection and surface realization by leveraging an information extraction (IE) system. The IE system extracts facts mentioned in reference data and generates texts which provide fact-guided signals. First, a content selection loss is designed to penalize content deviation between generated texts and their references. Moreover, with the selection of proper content for generation, a consistency verification mechanism is designed to inspect fact discrepancy between generated texts and their corresponding input data. The consistency signal is non-differentiable and is optimized via reinforcement learning. Experimental results on a recent challenging dataset ROTOWIRE show our proposed model outperforms neural encoder-decoder models in both automatic and human evaluations.
Assessing the Reading Competence Needs of Senior High School Students in National Examination: Teachers’ Perspective

The focus of this research is to asses the Reading competence needs of senior high school students in English National Examination (ENE) based on teachers’ perspective. The background in conducting this research mainly because of two things. The first one is the importance of curriculum evaluation behind the Needs Analysis itself. The second one is the importance of the certain preparation for strengthening English material to face the incoming English National Examination. Both of these backgrounds are equally important for students and teachers at once. This study is carried out with the objectives to answer the problems, that is to know what do 12 grader senior high school students’ needs in order to have English Reading competence of National Examination based on teachers’ perspective. The next objective is to find out what kinds of effort do teachers make to fulfil those needs. The last objective is to discover what obstacles are faced by teachers in order to fulfill those needs. All of these questions are framed within the scope of the teacher's perspective. The data of this research, included some questionnaires. This research already debriefed 5 English teachers who teach grade 12. They are from MGMP or English Teacher Forum of senior high schools in Boyolali Regency, Central Java Province, Indonesia. They were involved in filling out the questionnaire &amp;amp; also interview where the results were used as the main data in this study. The final findings in this study include the fact that: (1) the basic needs of students in reading competence are the mastership in Reading comprehension, the mastery of sufficient and adequate vocabulary and also high motivation in learning, (2) the teachers then made several programs to meet the needs of the students by providing additional Reading material and adding vocabulary, implementing Computer Based National Examination Simulation, Increasing awareness and motivation of students in reading English texts, Applying group discussion and student mentoring, Inserting speaking material in Reading learning, &amp;amp; makingEnglish Modules (3) students' instant habits in usinggadget, the inconsistency between the compulsory in12th grade curriculum and the material that must be taught by the teacher in the National Exam preparation class, lack of English teacher curriculum,books from the government are poor in content, low motivation &amp;amp; concentration of students in English lessons in the classroom, and low vocabulary mastery of studentsare the main obstacles that are facedby teachers in their efforts to increase students Reading competence in ENE.
Development of the Complex Algorithm for Web Pages Classification to Detection Inappropriate Information on the Internet

The paper is devoted to the investigation of web pages classification algorithms for protection against inappropriate information on the Internet. The approach for combining of classification algorithms based on different aspects of the source data and different machine learning methods is proposed. The experiments results of this approach application for website classification is presented.
An Effective approach of Data Migration from Private to Public cloud using E-LSB with Improvisation Technique

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Amazing Science Festival in National Institute of Technology, Kure College

Our school event termed “Amazing Science Festival” in National Institute of Technology, Kure College, was reported. This event ran from 2013 to provide experiences for the fun of science activities and the real thrill for manufacturing to many citizens, especially small children by communicating with our students. This event currently got big in Kure area because the number participants is drastically increased to be about 1000 by collaboration with “Incubation Work”, which is one of the PBL education curriculum starting from 2015. The achievement and the brief overview are shown in this paper.
Probabilistic Margin-Aware Multi-Label Feature Selection by Preserving Spatial Consistency

Multi-label feature selection focuses on constructing a reduced feature space for discriminating multi-label instances. In consideration of the complex structures of label and feature spaces, a critical issue that explicitly determines selection performance is how to induce consistent information from both spaces to steer feature selection. Existing approaches tackle this issue in various spatial-aware views, without sufficient consideration of the negative effects of irrelevant features and imbalanced neighbors on inferring space structure. Inspired by the superiority of margin theory in assessing reliable space structure, we approach multi-label feature selection in the learning framework of preserving label-feature space consistency through probabilistic margin in this paper. In contrast to existing approaches, our model assesses the weighted margin based on the probabilistic nearest neighbors, and preserves consistent margin information in label and feature spaces. In this manner, label-feature space consistency is elegantly achieved, which conduces to effectively capturing discriminative features suitable for multi-label learning tasks and eliminating noisy features. Experimental results on multi-label data sets demonstrate the encouraging performance of the proposed model.
Towards a Faster Incremental Packrat Parser

This work is an extension to the research done by Dubroy and Warth [1] on incremental packrat parsing. It attempts to further decrease the parse time of the incremental parser using two techniques from experimental algorithmics: algorithm and code tuning. Two modifications were introduced to the original incremental packrat parser: reduction of copy operations, and the use of an array of overlapping entries. Initial results showed that there is a significant difference between the parse times of the original parser (μ = 15.64ms, σ = 69.29ms) and the modified parser (μ = 4.60ms, σ = 69.53ms), with a t-score of t(890)=52.26 and a p -value of 9.41 ×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-274</sup> . This means that faster parse times are achieved when using the modified parser.
Mathematical Model of the Oculomotor System

Mathematical modeling of eye movement contributes to the learning of the oculomotor system and the development of technologies for device control. We propose in the present article a representative model of the different movements and rotation of the eye (adduction, abduction, elevation and descent) taking into account the anatomical properties of the extraocular muscles, strength-elongation relationship, and the action of the agonist muscles and antagonists. An easy to understand model is presented that allows the analysis of applied forces in muscle contraction, the conversion of length of elongation (or shortening) of the muscle, which generates rotation of the eye, and the vector interpretation of the direction in the space of towards where the eye directs the sight. In addition, an interface was made that allows the user to vary the Force applied to the extraocular muscles and obtain the spatial movement of the eye, with the anatomical and physiological considerations of the oculomotor system. The proposed model allows a simplified understanding, compared to other models, of the physiology of the oculomotor system, and its implementation in computational simulation systems results in faster executions with lower computational cost. The implementation of the proposed model will serve in the future in the control of devices or development of technologies that depend on eye movements or that imitate these movements.
Development Route of Power Grid Enterprises Based on New Electricity Reform

The paper believes that the introduction of the new electricity reform program has an important impact on the development of power grid enterprises, and the power grid enterprises need to re-comb and locate in the development path. First, it sorts out for Chinese the electricity reform program and the reform of the core ideas over the years, focuses on the interpretation of the core elements of this reform, sorts out the important issues associated with the development of power grid enterprises, combining the development path problem of power grid enterprises. We should optimize the investment, assets, innovation and cost control in order to improve the profitability of grid enterprises in the new situation.