Reviewerly/exHarmony huggingface dataset:
EQUIPRIME FUZZY GRAPH OF A NEARRING WITH RESPECT TO A LEVEL IDEAL

In this paper, we introduce an equiprime fuzzy graph of a nearring with respect to the level ideal of a fuzzy ideal. We interrelate graph theoretical properties of the graph and ideal theoretical properties of nearring. We show that the properties like vertex cut, connectedness of the graph depend on the properties of the fuzzy ideal. We define ideal symmetry of the graph and find conditions for the graph to be ideal symmetric. If the fuzzy ideal is equiprime then we show that the level set induces a fuzzy clique. We find conditions required for the level set to be the vertex cover of the graph. We find interrelation between equiprime fuzzy graph and fuzzy graph of nearring with respect to level ideal. We study properties of the graph under neaaring homomorphism. We prove that the connectedness of the graph in homomorphic image depends on properties of ideal. We obtain conditions required for homomorphic image of an equiprime fuzzy ideal to be an equiprime fuzzy ideal.
Methodology of semi-supervised algorithm selection for classification problems

The paper concerns the problem of selecting an appropriate semi-supervised learning algorithm based on validating assumptions that the algorithm is based on for the particular dataset. This enables the selection of the fittest algorithm to achieve the best possible model accuracy. In this paper, we provide an overview of four primary semi-supervised assumptions, introduce the definition of metrics used to evaluate the assumption, provide a taxonomy of common semi-supervised algorithms and assumptions based on, and evaluate the proposed methodology on the synthetic too-moons dataset. The results indicate prospects of improving methodologies further by refining and introducing new metrics.
Term dependency extraction using rule-based Bayesian Network for medical image retrieval

Text-Based Medical Image Retrieval (TBMIR) has been known to be successful in retrieving medical images with textual descriptions. Usually, these descriptions are very brief and cannot express the whole visual content of the image in words, hence negatively affect the retrieval performance. One of the solutions offered in the literature is to form a Bayesian Network thesaurus taking advantage of some medical terms extracted from the image datasets. Despite the interestingness of this solution, it is not efficient as it is highly related to the co-occurrence measure, the layer arrangement and the arc directions. A significant drawback of the co-occurrence measure is the generation of a lot of uninteresting co-occurring terms. Several studies applied the association rules mining and its measures to discover the correlation between the terms. In this paper, we propose a new efficient association Rule Based Bayesian Network (R2BN) model for TBMIR using updated medically-dependent features (MDF) based on Unified Medical Language System (UMLS). The MDF are a set of medical terms that refers to the imaging modalities, the image color, the searched object dimension, etc. The proposed model presents the association rules mined from MDF in the form of Bayesian Network model. Then, it exploits the association rule measures (support, confidence, and lift) to prune the Bayesian Network model for efficient computation. The proposed R2BN model is combined with a literature probabilistic model to predict the relevance of an image to a given query. Experiments are carried out with ImageCLEF medical retrieval task collections from 2009 to 2013. Results show that our proposed model enhances significantly the image retrieval accuracy compared to the state-of-the-art retrieval models.
SOCIAL MEDIA AS AN IMPACT FACTOR ON IRAQI LEARNERS OF EFL

Brand value, client loyalty, and corporate execution can all profit from social media. The time of social systems administration, contention, and innovation has arrived. At this moment, the whole planet looks like a sign country. Youthful people can utilize social networking platforms to investigate their inclinations and interface with other people who have comparative ones. Social media technologies arrive in a wide assortment of configurations, for example, papers, online conversation sheets, websites, wikis, social organizations, digital broadcasts, pictures, and recordings. Innovations incorporate, however, are not restricted to publishing content to a blog, photograph sharing, wall posting, and music sharing. The present Facebook innovation seems to assume a considerable part in the social existence of countless individuals. It is becoming a critical type of correspondence that might fill instructive needs. Various studies have investigated the utilization of different advancements in educating and learning, especially in concentrating on foreign languages. Very few researchers have unequivocally based on how web-based entertainment affects language learning. This study wanted to survey the ability and supportiveness of web-based entertainment in jargon learning. In this manner, it could remarkably affect how individuals learn and show different languages.
Teachers’ Beliefs for Using Phonics to Develop Kindergarten School Students’ Reading

This study can further initiate valuable implications for teachers’ belief on how teachers’ performers with pedagogic competence and knowledge in teaching english by using phonics to develop students reading skills, to find the teachers’ specific beliefs for teaching reading using phonics in kindergarten school. Considering beliefs can’t be seen or quantified directly, researchers searched for several effective data gathering approaches to discover teachers' belief. The researcher used a qualitative case study to investigate to address the research objectives about teachers’ beliefs about using phonics to develop Kindergarten School students’ reading. The researcher discovers that the teachers’ belief comprises of information, experience, prespective, assumption, truth, and perception regarding teaching english observations. In actuality, the teacher's belief teaches not only information but also the teacher's own viewpoint. Three factors reflect a teacher's belief in teaching using phonics: knowledge about teaching reading using phonics, teachers’ behavior about teaching reading and the creation of conditions and environments. The researcher suggest that the principal provide some training or workshops for teachers to aid them in properly executing the lessons. It help improve students' reading since they are exposed to a positive learning environment.
Removing non-nuclei information from histopathological images: A preprocessing step towards improving nuclei segmentation methods

Disease interpretation by computer-aided diagnosis systems in digital pathology depends on reliable detection and segmentation of nuclei in hematoxylin and eosin (HE) images. These 2 tasks are challenging since appearance of both cell nuclei and background structures are very variable. This paper presents a method to improve nuclei detection and segmentation in HE images by removing tiles that only contain background information. The method divides each image into smaller patches and uses their projection to the noiselet space to capture different spatial features from non-nuclei background and nuclei structures. The noiselet features are clustered by a K-means algorithm and the resultant partition, defined by the cluster centroids, is herein named the noiselet code-book. A part of an image, a tile, is divided into patches and represented by the histogram of occurrences of the projected patches in the noiselet code-book. Finally, with these histograms, a classifier learns to differentiate between nuclei and non-nuclei tiles. By applying a conventional watershed-marked method to detect and segment nuclei, evaluation consisted in comparing pure watershed method against denoising-plus-watershed in an open database with 8 different types of tissues. The averaged F-score of nuclei detection improved from 0.830 to 0.86 and the dice score after segmentation increased from 0.701 to 0.723.
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Cataloging Virtual Reality Programs: Making the Future Searchable

While virtual reality (VR) programs are not new, only in recent years have libraries made these systems available for their patrons. Along with the VR systems, more and more programs are being released. These programs range from educational to entertainment. This paper discusses a project created at Mississippi State University Libraries to catalog their purchased VR programs and make them searchable to students and researchers via the OPAC.
Client-Centric Concept in Higher Education: Russian and International Experience of Implementation

The client-centric concept, which originated in the 1980s, has been implemented in the last decade in specific digital projects at the national and global level. Russia has fully embraced the new technological trend and is creating new types of digital services in different segments of the social space. The purpose of the article is to consider the stages of implementation of client-centric principles in global and Russian practice. The main emphasis is placed on the information superservice "University Admission Online" introduced in Russia and its counterparts in other countries of the world. The analysis showed that Russia has already passed the main stages of formation of such digital platforms and is in the group of the leading countries of the new initiative. International experience shows that the nearest analogues of Russian superservice have been created under the patronage of the state in Sweden and Germany. At the same time, the article shows that private global services in the higher education market already operate today – the Australian and the Anglo-Chinese initiatives, respectively. The question of expanding the digitalization of the Russian higher education market through the launch of global services in the framework of public-private partnerships is discussed.
An IMM-SRHCKF tracking algorithm with doppler information

To improve the tracking accuracy of manoeuvring targets, this paper introduces the Doppler information and the square-root high-degree cubature Kalman filter (SRHCKF) into the interacting multiple model (IMM) algorithm, then proposes an IMM-D-SRHCKF algorithm. The algorithm uses Doppler measurements to achieve an improvement in tracking accuracy. At the same time, adaptive state transition probabilities and dimensionality reduction by rounding off zero-weighted cubature nodes are incorporated to increase computational efficiency. Experimental results show that the tracking error of the proposed algorithm is 79.13% and 78.32% lower than that of the IMM-UKF and IMM-CKF without Doppler information, respectively, and 41.35% and 27.41% lower than that of the IMM-D-UKF and IMM-D-CKF with Doppler information, respectively, and the proposed algorithm also have pretty robustness in different scenarios.
Learning Generalized Hybrid Proximity Representation for Image Recognition

Recently, deep metric learning techniques received attentions, as the learned distance representations are useful to capture the similarity relationship among samples and further improve the performance of various of supervised or unsupervised learning tasks. We propose a novel supervised metric learning method that can learn the distance metrics in both geometric and probabilistic space for image recognition. In contrast to the previous metric learning methods which usually focus on learning the distance metrics in Euclidean space, our proposed method is able to learn better distance representation in a hybrid approach. To achieve this, we proposed a Generalized Hybrid Metric Loss (GHM-Loss) to learn the general hybrid proximity features from the image data by controlling the trade-off between geometric proximity and probabilistic proximity. To evaluate the effectiveness of our method, we first provide theoretical derivations and proofs of the proposed loss function, then we perform extensive experiments on two public datasets to show the advantage of our method compared to other state-of-the-art metric learning methods.
Multi-prior Driven Network for RGB-D Salient Object Detection

Most existing RGB-D salient object detection (SOD) methods rely on high-quality depth images. However, their performance is limited when processing low-quality depth maps. This paper exploits more complementary image priors to guide the model to learn on variable depth maps, and a novel multi-prior driven network called MPDNet is proposed for RGB-D SOD. MPDNet utilizes four processing pipelines to process RGB images and other priors, which include an RGB image processing pipeline, a depth map processing pipeline, a fine-grained and gradient prior processing pipeline, and an edge learning pipeline. Specifically, fine-grained and gradient priors are input to the same processing pipeline. For the depth maps, fine-grained and gradient priors, a prior channel attention module utilizes the channel attention mechanism to filter noises and highlights the salient cues. The RGB image processing pipeline uses a multi-feature progressive enhancement module to fuse and enhance features from depth maps. And a multi-feature prediction decoder decodes initial salient masks. In the edge learning pipeline, edge prior serves as an edge label and is captured by an edge capture module. Finally, the clear salient masks are obtained by fusing the salient information from the four pipelines. The experimental results on six benchmarks indicate that the proposed method outperforms thirteen state-of-the-art methods in six evaluation metrics.
Psychological training as positive thinking forming method in educational establishment

The development of positive thinking is an important factor for the effectiveness of firefighters’ and rescuers’ activities and professional health. For this reason we use some developments of positive psychology in the learning process, for example, training positive thinking formation. The purpose of the study was to determine the possibilities of psychological training for forming and developing positive thinking among cadets. The subject, object, hypothesis, tasks and methods of the research were defined, and as a result, the advantages of psychological training were identified. Thus, its practical orientation allowed the participants not only to discuss techniques and algorithms of work, but also to evaluate their effectiveness in practice.
MODERN PEDAGOGICAL UNIVERSITY AS A CENTRE FOR THE DEVELOPMENT OF SCIENTIFIC AND EDUCATIONAL INNOVATIONS

The article discusses the traditions and scientific and educational potential of Lugansk State Pedagogical University for the development of a model of a modern pedagogical university, where scientific and educational innovations dominate, continuous education is carried out in the formula: pre-university, university and postgraduate education, conditions are created for a phased and qualitative transformation of scientific and educational potential which was formed in the previous period within the framework of national programs and federal projects for the development of science and education in the Russian Federation.
Augmented Reality For Learning 3D Geometry

This research shows the outcomes of using augmented reality (AR) in the learning of descriptive geometry in elementary school students. In current times, we are aware that technological tools are widely used in the education sector as they are very interesting and engaging for students. Augmented reality is one such technology that has proved to be very useful in education. AR can make difficult concepts easier to understand. In this paper, we are presenting an AR-based android application called ‘Learn Geometry with AR’ for school students. This application provides a user-friendly interface, AR view of different solids, and details about these solids, as it provides all the information related to the solid in one place it clears all the concepts of the students very effectively. In addition, there is a quiz section to evaluate the students' learning that can be linked to an app. It is concluded that the use of an AR-based application significantly improves learning aspects of descriptive geometry.
Effective Reduction of Power Consumption with Thermo Electric Module (TEM) and Wireless Sensor Nodes using Embedded System

A computer system that serves a specific purpose inside a larger mechanical or electrical system is known as an embedded system. Embedded systems sometimes have to deal with real-time computing restrictions. Because embedded systems are designed to carry out just certain functions, design engineers are able to optimize them to cut down on the size and cost of the product while simultaneously improving its dependability and performance. Effective in-field detection and real-time management of malfunctioning Thermo Electric Modules (TEM) are essential components of the thermoelectric production system and must be present for the purpose of maximizing energy productivity (TEGs). According to the measurement criteria of faulty TEMs developed for series- parallel-connected TEM arrays and the control scheme based on TEM -oriented switches, autonomous and dispersed sensor nodes are proposed in this study to perform wireless TEM management. These nodes are designed to carry out wireless TEM management according to the series-parallel-connected TEM arrays' measurement standards for faulty TEMs.
An Improved Analysis of Plastic Recycling Model for Industrial Waste Management System using Blockchain Technology

Plastic bags have become a daily use item in today's human life. Businesses have a habit of putting any item they buy in plastic bags. These plastic bags are thrown away after use. These bags end up in the trash If that is not the case. It does not decompose even when buried in soil. Rather than trying to destroy these pockets of immortality, we should try to avoid them. In these protests, some countries have completely avoided plastic bags. Although many countries have advised their citizens to avoid plastic bags, they have not banned their production. Due to this invisible trend, the use of plastic bags continues. 0 micron weight, restricted to plastic bags smaller than 8 by 12 inches. But because the government authorities are not interested in implementing this ban, the encroachment of plastic bags is increasing day by day across the country. Due to this, charitable organizations working for the welfare of animals filed a public interest petition in the Supreme Court. Accepting this for hearing, the court said that the misuse of plastic bags is dangerous not only to livestock but also to the future generations, which should be banned completely or the manufacturers should recycle the plastic bags.
Music Education of Feeling for the Construction of Emotion

많은 연구에서 감정은 지식처럼 뇌의 의식적인 인지 작용을 통해 개념으로서 구성된다는 것이 밝혀지고 있다. 음악교육에서는 감정과 관련하여 일찍이 느낌의 교육이 강조되어 왔는데, 느낌은 감정의 종류 중 하나이며 감정을 구성하는 기초 요소로 알려져 있다. 본 연구는 음악을 대상으로 감정을 효과적으로 구성하기 위해 음악교육에서 이러한 느낌이 어떻게 다루어져야 하는지 그 방법을 모색하는 데에 목적을 두었다. 이를 위해, 감정과 감정의 구성, 느낌과 그 표현에 대하여 다양한 문헌을 고찰해 보았고, 이를 기반으로 감정을 구성하는 느낌의 음악교육 방법을 탐색하였다. 연구 결과로서 느낌을 크게 정동적 느낌, 개념적 느낌, 지성적 느낌으로 나누고, 개념적 느낌은 다시 감각적 개념, 음악적 개념, 감정적 개념, 명제적 개념으로 분류하였다. 감정 구성을 위한 느낌의 음악교육을 위해 우선 느낌의 자유로운 표현활동을 제안하였고, 분류한 각 느낌에 대한 자세한 설명과 그 표현하는 방법 등을 사례와 함께 제시하였다. 음악교육에서 이러한 표현 활동들은 학습자가 대상인 음악에 대하여 다양한 느낌과 음악적 요소들을 통찰하고, 감정을 구성할 수 있는 매우 효과적인 방법이 될 수 있을 것으로 기대한다.Many studies have revealed that emotions, like knowledge, are constructed as concepts through conscious cognitive processes in the brain. In music education, the education of feeling has been emphasized early on, and feeling is one of the types of emotions and is known as a basic element that composes emotions. The purpose of this study was to find out how to deal with these feelings in music education in order to effectively construct emotions in music. To this end, I reviewed various literature on emotions and construction of emotions, feelings and their expressions, and based on this, I studied the music education method of feeling that construct emotions. As a result of the study, feelings were largely divided into affective feelings, conceptual feelings, and intellectual feelings, and conceptual feelings were further classified into sensory concepts, musical concepts, emotional concepts, and propositional concepts. For the music education of feeling for the construction of emotion, first of all, free expression activities of feeling were proposed, and a detailed explanation of each classified feeling and how to express it were presented along with examples. In music education, these expressive activities are expected to be a very effective way for learners to gain insight into various feelings and musical elements of music, and to construct emotions.
Research on Improvement and Optimization of A* Algorithm in Robot Path Planning

With the development of science and technology, the research on robots has attracted more and more attention. In many cases, robots are used to perform some tasks instead of people. In the process of robot movement, path planning technology is the most important, and path planning algorithm is the core of path planning technology. A* algorithm is one of the commonly used algorithms in the field of path planning. This paper improves the traditional A* algorithm based on A* algorithm and combined with the actual requirements of this work. The penalty term of velocity change is added to the cost function of the traditional A* algorithm, and the pathfinding strategy of the algorithm is changed. The improved algorithm can be considered more comprehensively in path planning, so as to plan a path that takes the shortest time to execute a task.