Reviewerly/exHarmony huggingface dataset:
The Paradigm of Corporate Governance in Universities: The Ground Research for Models of Education Modernization in the Republic of Uzbekistan

The article provides a comparative analysis of existing corporate governance models in developed countries in order to find an adaptive model for the republic. The realities of governance practice, the goals and challenges in Uzbekistan are considered. Further, an overview of the modern paradigms of university governance is made, in the context of using the experience of foreign universities for the possible implementation of corporate governance and proposed to use a conceptual approach based on the insider model of corporate governance of the university.
Developing Learners’ Spatial Thinking while Solving Geometrical Tasks with Elements of the Yakut Everyday Life and Architecture

The article examines the problem of developing 7th-9th-grade pupils’ spatial thinking by the example of the Sakha Republic (Yakutia). The authors emphasize that geometrical tasks with elements of the Yakut everyday life and architecture contribute to developing pupils’ spatial thinking. Inclusion of these tasks into the content of geometry teaching is considered within the framework of ethno-pedagogical space created on the basis of harmonization of ethnic and pedagogical components. Examples of tasks with elements of the Yakut everyday life and architecture that can be used as additional material at geometry lessons are provided.
PENERAPAN MODEL PEMBELAJARAN STUDENT TEAMS ACHIEVEMENT DIVISION (STAD) UNTUK MENINGKATKAN PRESTASI BELAJAR BAHASA INGGRIS

The purpose of this classroom action research is to improve students' learning achievement of English through learning model of STAD in grade IX-H students of Semester Gasal of SMP Negeri 2 Sukoharjo in the 2019/2020 school year.This research was conducted from July to December 2019 in SMP Negeri 2 Sukoharjo.The subjects of this study were students of class IX-H as many as 32 students.This research is a Classroom Action Research conducted in two cycles.Data collection techniques used documentation, observation, and written tests.Data collection tools are observation sheets, test items, and value list documents.Data analysis using comparative descriptive analysis is followed by reflection on each cycle consists of four steps, namely: (1) Planning, (2) Action Implementation, (3) Observation, and (4) Reflection.The results of
Third Workshop on Evaluation of Personalisation in Information Retrieval (WEPIR 2020)

The Third WEPIR 2020 workshop builds on the success of the first two WEPIR meetings held at CHIIR 2018 and CHIIR 2019. WEPIR 2020 again brings together researchers from different backgrounds interested in continuing to explore and advance the evaluation of personalisation in information retrieval. Similar to the first two workshops, WEPIR 2020 has a strong emphasis on active participation by workshop attendees. This was very successfully achieved in the first two workshops by the use of workshop breakout groups exploring topics related to personalisation and information retrieval, and the evaluation of personalisation in information retrieval in general, with subsequent report back to the workshop as a whole. However, a key difference for WEPIR 2020 is that while the first two workshops focused on developing and articulating principles and ideas relating general topics relating to these topics, identified as interesting and important by the attendees at the workshops, WEPIR 2020 focuses breakout discussion on a number of relevant specific use cases of the evaluation of personalisation in information retrieval. A use case is assigned to each breakout group with the plan being to have more than one group work on each use case. The task for each group is to identify specific relevant factors relating to the use case in terms of user activities, data to be collected, ethical issues, and evaluation metrics. Groups will make reports of their discussions to the assembled workshop in the final session with discussion of the alternative solutions relating to the same use case, and contrasting the issues raised by the different use cases. The overall goal of the workshop is to work towards developing a general set of principles and guidelines for addressing the evaluation of specific instances of the use of personalisation in information retrieval tasks. This is consistent with the activities and goals of the first two workshops, but represents a significant progression of the activities towards concrete outcomes of benefit to those exploring personalisation in search, the issues arising in its evaluation, and how researchers might go about tackling this in specific situations.
Research on Landfill Site Evaluation Index Based on Cloud Model

Abstract In order to solve the uncertainty, ambiguity and randomness in the closure evaluation of the municipal solid waste landfill in Dagang District of Tianjin, combined with the actual situation of saline-alkali land in the arid area, the cloud model was introduced to evaluate the landfill site closure and determine the filling. The site level of the burial field. The weight of each level of the evaluation index of the landfill and the score of each level of the index are obtained by the reverse cloud generator to obtain the corresponding cloud model, and each level of the index is qualitatively and quantitatively analyzed, and the cloud model is evaluated for the landfill. The evaluation results are presented and an improvement plan is proposed. The cloud model provides a new method for the closure of saline-alkali landfills in arid regions.
Image-Based Scene Representations for Head-Motion Parallax in 360° Panoramas

Creation and delivery of “RealVR” experiences essentially consists of the following four main steps: capture, processing, representation and rendering. In this chapter, we present, compare, and discuss two recent end-to-end approaches, Parallax360 by Luo et al. [9] and MegaParallax by Bertel et al. [3]. Both propose complete pipelines for RealVR content generation and novel-view synthesis with head-motion parallax for 360° environments. Parallax360 uses a robotic arm for capturing thousands of input views on the surface of a sphere. Based on precomputed disparity motion fields and pairwise optical flow, novel viewpoints are synthesized on the fly using flow-based blending of the nearest two to three input views which provides compelling head-motion parallax. MegaParallax proposes a pipeline for RealVR content generation and rendering that emphasizes casual, hand-held capturing. The approach introduces view-dependent flow-based blending to enable novel-view synthesis with head-motion parallax within a viewing area determined by the field of view of the input cameras and the capturing radius. We describe both methods and discuss their similarities and differences in corresponding steps in the RealVR pipeline and show selected results. The chapter ends by discussing advantages and disadvantages as well as outlining the most important limitations and future work.
Wearable Device for Restaurant Operational that Employs People with Hearing Impairment

Abstract Speed in serving consumers is one of the top priorities in restaurants. To provide fast and precise service, it needed a device that is able to help the operational system at restaurant. This research focus on creating a device that can help operational system at restaurant that can be controlled using the smartphone. The device is designed to combine several components that were merged into a wearable device. The result is wearable devices that can last 7 hours 34 minutes with 2 hours charging time, average operating distance 35.3 m, and 5% error glitch.
Methodical and Information Support of the Operational Personnel in the Training Management System of the ISS RS Simulator Complex.

The paper analyzes the functional structure of the training management system (TMS) of the ISS RS simulator complex from the viewpoint of engineering and technical support of training. It is shown that the methodical and informational support for the performance of the operational personnel is an element of the TMS and requires an improvement or development taking into account the tasks of controlling the simulator complex when preparing and conducting training.
CHAPTER 15. Proteomic Workflows with R/ R Markdown

This R Markdown document contains a brief introduction to R and R Markdown We explain the capabilities of these tools and their potential implementation together to process Mass Spectrometry data. Then, a simple step-by-step workflow processing of an 8-channel iTRAQ test dataset using the Trans-Proteomic Pipeline and finally a more advanced workflow is described as a template and step-by-step example solution of the 2016 iPRG study as well as an example of how to submit and share such solutions in an R Markdown document.
El 2000 visto desde el People’s Party

For a few years (1890-1896), the People's Party was the "third party" of the United States and it changed the rhetoric of the two major parties into which it "dissolved" (especially in the case of the Democratic Party represented by William Jennings Bryan in 1896).The aim of the article is to test the politicalnarrative background which includes, among other productions in 1888, the first edition of Looking Backward.
Realization of Competence-Based Approach in the System of Engineering-Pedagogical Staff Development

The study examines the projection of competence-based approach into the system of engineering-pedagogical staff development; and presented the design of the career enhancement programs of a new generation. It justified the transfer from the traditional structuring of subject-thematic content of pedagogical staff development to projecting a modular-competence content in the framework of the professional development model.
Music Gesture and the Correspondence of Lines: Collaborative Video Mediation and Methodology

Music Gesture can be thought of as being made up of dynamic, multisensorial lines. From this, the author draws from Ingold's “correspondence of lines” as a conception of music and a transformative compositional process, informing gestural line expressions and the development of notation systems for the body. The author outlines the technology he has developed for two compositions, involving a video scoring methodology and software that enables interactive video gestural sampling in a collaborative art music context. The author also engages with Ingold's concept of the “mesh,” as lines that overflow, and imagines how the mesh could be perceived through sensory modalities. This discourse of lines is contextualized through examples of absurdist instrumental pieces and corporeally based music.
Efficient sampling generation from explicit densities via Normalizing Flows

For many applications, such as computing the expected value of different magnitudes, sampling from a known probability density function, the target density, is crucial but challenging through the inverse transform. In these cases, rejection and importance sampling require suitable proposal densities, which can be evaluated and sampled from efficiently. We will present a method based on normalizing flows, proposing a solution for the common problem of exploding reverse Kullback-Leibler divergence due to the target density having values of 0 in regions of the flow transformation. The performance of the method will be demonstrated using a multi-mode complex density function.
Smartphone Information Extraction and Integration from Web

We present herein a solution to problems in data integration, which is a process of consolidating similar information from different sources, in which multiple data sources ensure data unification. One concept value may have different name values used in two different databases that are consistent and meaningful under the same concept. This conflict must be resolved for consistency as well as to reduce data errors. We extracted the specifications of a mobile phone and smartphone from several websites and created JSON middleware for mapping and synonyms for the specification of mobile phone data in the form of same word standardization. Schema matching plays an important role in combining different sources of information, which can find meaningful consistency between the components of the two schemas, and are then integrated into a new database that collects more mobile phones and smartphones, but reduces the duplication of data from the original database obtained from website data extraction. The application of the proposed method involves the mobile phone data integration problem of two integrated languages, namely, Thai and English, demonstrating efficiency in actual use.
Prediction of Software Effort Using Design Metrics: An Empirical Investigation

These days, prediction of effort in software project is the shove area for the researchers. The estimation of effort in software process is as essential as software product. Primarily, estimation models consist of relation between dependant and independent variable(s). The effectiveness of these models is to bring more accuracy to the work plan and reduce financial cost. The variables in these models may be considered as complexity, size, person per month, and other different software metrics. Most of these models only considered the static behaviour of the software product, in which the fixed value of the effort predicted at the starting of project. Hence, there is a need to formulate a methodology which considered the future changes in the software project for effort estimation. In this paper, a model has been formulated which can be use to make the prediction of software efforts with the help of software metrics, primarily design metrics, such as Depth of Inheritance Tree, Line of Code, Weighted Method per Class. The correlation between the metrics and effort is been shown with the help of regression model formulated in this paper. The model has been validated by the data set collected from the PROMISE repository.
Corpus stylistics in translation-oriented text analysis. Approaching the work of Denton Welch from a functionalist perspective

This article is an effort towards interpreting the findings of a corpus-based stylistic analysis of the short narrative “Sickert at St Peter’s” (1942), written by the English writer and painter Denton Welch (1915–1948), within the larger framework for translation-oriented text analysis presented by Christiane Nord in Textanalyse und Übersetzen (2009). The aim is to explore both the theoretical possibilities andthe practical applications of a corpus-based approach to the lexical analysis phase of Nord’s model from a literary translation perspective, in which style and word choice play a critical role. Once the statistical findings of the corpus-based analysis are presented, the 25 highest-ranking keywords in the text are analyzed in context. Translation briefs and literary translation in general are discussed, and a global pre-translational strategy for translating “Sickert at St Peter’s” is presented. By way of conclusion, it is argued that the method described promotes valuable insights for literary interpretation and serves as a practical aid in developing a pre-translational strategy for translating individual texts.
Analysis of Patients’ Reviews and Enhancing Services in Hospitals

Currently, when it comes to hospitals, a large amount of patients visit daily. If the feedbacks or reviews or opinions are not analyzed properly, it is bound to affect the business and reputation of hospitals. So it is necessary to analyze the reviews that the patients have about hospitals. We have proposed an approach for mining of feedbacks of patients which will be useful to find the common features in a hospital which can be +ve or −ve. We successfully generate the summary of the reviews and also classify the reviews with more than 80% accuracy with all the classifiers. ‘Majority vote’ which is the approach proposed by us proved to be more accurate than other classifiers.
Belief Propagation for Maximum Coverage on Weighted Bipartite Graph and Application to Text Summarization

We study text summarization from the viewpoint of maximum coverage problem. In graph theory, the task of text summarization is regarded as maximum coverage problem on bipartite graph with weighted nodes. In recent study, belief-propagation based algorithm for maximum coverage on unweighted graph was proposed using the idea of statistical mechanics. We generalize it to weighted graph for text summarization. Then we apply our algorithm to weighted biregular random graph for verification of maximum coverage performance. We also apply it to bipartite graph representing real document in open text dataset, and check the performance of text summarization. As a result, our algorithm exhibits better performance than greedy-type algorithm in some setting of text summarization.
Cancer Cell Prediction Using Machine Learning and Evolutionary Algorithms

Cancer is a disease that affects the global population indistinctly. It is considered the second cause of death in the world. Early detection can reduce cancer mortality. However, instruments and equipment for diagnostic are often expensive and insufficient. This makes doctor’s work becomes complex and often, cancer patients do not receive a diagnosis until the disease is advanced. Machine Learning (ML) has shown to be useful for classification and prediction problems but it faces some limitations. Mainly, because it depends on the quality of the information. Over the years, different mechanisms have been developed to solve them, but there is not any mechanism that eliminates all ML difficulties. Because of that, this area remains open to new promising discoveries and ideas. Evolutionary Algorithms (EAs) have demonstrated to be useful for solving optimization problems in a heuristic way. This chapter presents a comparative study related to the prediction of cancer cells based on Machine Learning and Evolutionary Algorithms. As well as, a brief introduction of machine learning and evolutionary technics is presented. Also, the procedures’ implementation and performance are described. The results obtained show that the AEs can support a ML method, guiding the learning process.
Ensemble Methods on Weak Classifiers for Improved Driver Distraction Detection

Distracted driving is the act of driving when engaged in other activities which takes the driver’s attention away from the road. It is one among the main causes of road accidents. Majority of these accidents occur because of momentary negligence, thus a driver monitoring system which executes and analyzes in real time is necessary. The required dataset will be prepared and this data will be utilised to train the neural network. The major areas of focus are extreme head poses, yawning detection, facial expressions, head nodding and hand movements that are indicators of distraction. Emphasis will also be given in exploring different ensemble methods for combining various existing models.
Design and Implementation of Human Safeguard Measure Using Separable Convolutional Neural Network Approach

Smart surveillance system is designed and developed to mitigate the occurrence of crime scenarios. Traditional image processing methods and deep learning approaches are used to identify the knife from camera feed. On identification of knife, the identity of person holding the knife is obtained using SSD ResNet CNN model. Also, an awareness alarm is generated by the system to caution the people in the surroundings. Experimental investigation clearly shows that the method of fine-tuned Xception deep learning model based on Separable Convolutional Neural Network (SCNN) with Logistic Regression (LR) classifier resulted in highest accuracy of 97.91% and precision rate of 0.98. Face detection is employed using a conditional face detection model based on SSD ResNet. The result obtained using deep learning approach is high compared to that of traditional image processing method. Real time implementation result shows that the model effectively detects the knife and identifies the person holding knife.
Dynamics of Fuzzy Argumentation Frameworks

Dung’s theory of abstract argumentation plays an incremental role in artificial intelligence. The research about the dynamics theory of argumentation efficiently identifies the justified arguments when arguments or attacks change. However, the dynamics theory is absent in fuzzy argumentation framework (FAF). We want to calculate the semantics of the updated FAF by partially reusing the semantics of the previous FAF. In this paper, we explore the dynamics theory in FAFs. First, we introduce all the changes of FAF, including not only the changes of arguments and attacks but also the increases or decreases of their fuzzy degrees. Thus, the changes in FAFs are more complicated than standard AF. Then by extending Liao’s division-based approach, we provide an efficient algorithm for computing some basic semantics. This algorithm conserves part of the semantics in the previous FAF. Thus, we can efficiently compute the belief degree to which arguments are justified.
Feature Learning for Effective Content-Based Image Retrieval

Increase in the use of mobile phones for scene capturing turns into the exponential increase in the size of digital libraries. Content-Based Image Retrieval (CBIR) is an effective solution to handle this enormous data. Most of the existing approaches are relied on the hand-crafted feature extraction for CBIR. These approaches could fail in large-scale databases. Thus, in this paper, we have proposed an end-to-end deep network for CBIR. Proposed network is characterized by the residual learning and thus does not undergoes the vanishing gradient problem. Performance of the proposed method has been evaluated on two benchmark databases namely Corel-10K and GHIM-10K with the help of two evaluation parameters i.e. recall and precision. Comparison with the state-of-the-art methods reveiles that proposed method outperforms existing methods by a large margin on all of the databases.
Suggestive techniques in music-performing training of future music art teachers: methodological aspect

The article deals with the use of suggestive techniques, which by influencing the conscious and subconscious sphere of future music arts teachers through the use of verbal and non-verbal, external and internal means of influence, will contribute to the disclosure of their inner potential, the development of creative thinking as well as the realization of their abilities into the practical activities. The author defines various spheres of the suggestive techniques use, in particular, in the process of future music teachers training and provides own interpretation of the concept of “suggestive technique in the music-performing training of future music teachers”. In addition, the author offers methodological developments aimed at conducting creative music-performing activities #x201C; suggestopedic self-training of self-regulation skills along with suggestopedic method of forming the skills in artistic interpretation of a musical work, which is presented as a chain of suggestopedic classes, where each stage corresponds to a certain interpretation phase. Furthermore, it is noted that the developed methodological toolkit with the complex involvement of suggestive techniques with a number of methods, tools and approaches to art education along with the varied application of these methods in the process of students’ professional training, methods of performing reliability formation and innovative methods, provides to carry out pedagogical influence on independence as well as performing activities effectively. Admittedly, the introduction of typical suggestopedic forms of classes (concert sessions, classes involving related arts, class performances, storytelling, play sessions) into the methodological toolbox brings additional aesthetic coloring into the interpretative processes, which, in combination with the globalization of the learning material, have led to the reconsidering of musical works artistic interpretation techniques on the whole.