Reviewerly/exHarmony huggingface dataset:
B A Case Study of Dyslexic Student Learning English as a Foreign Language

Dyslexia is a particular learning impairment also known as reading and writing disability. Despite average intelligence it is characterized by a challenge with reading and writing. Dyslectics are affected with different degrees. Dyslexia has a neurological and family history basis. This study aims to highlight both the existence of this condition among students and the teachers' unawareness of this kind of learning difficulty. The study is conducted on a 13-year-old dyslexic girl. A general estimation of the case was carried out by first, an evaluation of the social and academic status of the girl's family, and second, using dyslexia screeners with some of the reading and writing tests to examine the nature of her disability. It was concluded that there are students in Kurdistan who have Dyslexia, without teachers and parents be aware of it. Dyslexia requires early intervention by teachers and parents alike to mitigate its effect on the process of learning. There is also an urgent need for an early diagnosis program of Dyslexia in the Kurdistan region so that teachers can identify dyslexic students and not blame them and their parents for their learning difficulties.
Intelligent Bio-Inspired Whale Optimization Algorithm for Color Image based Segmentation

Color image segmentation is widely used methods for searching of homogeneous regions to classify them into various groups. Clustering is one technique that is used for this purpose. Clustering algorithms have drawbacks such as the finding of optimum centers within a cluster and the trapping in local optima. Even though inspired meta-heuristic algorithms have been adopted to enhance the clustering performance, some algorithms still need improvements. Whale optimization algorithm (WOA) is recognized to be enough competition with common meta-heuristic algorithms, where it has an ability to obtain a global optimal solution and avoid local optima. In this paper, a new method for color image based segmentation is proposed based on using whale optimization algorithm in clustering. The proposed method is called the whale color image based segmentation (WhCIbS). It was used to divide the color image into a predefined number of clusters. The input image in RGB color space was converted into L*a*b color space. Comparison of the proposed WhCIbS method was performed with the wolf color image based segmentation, cuckoo color image based segmentation, bat color image based segmentation, and k-means color image based segmentation over four benchmark color images. Experimental results demonstrated that the proposed WhCIbS had higher value of PSNR and lower value of RMSR in most cases compared to other methods.
A Study on Comparing the Perception between Librarians and Users about Libraries' Value

Purpose - This study comprehensively draws a conclusion using factors of economic, social, and educational value and performed a survey on librarians and users to compare and analyze the difference in perception between the two groups. The result of this study will encourage librarians in the field of libraries and enable students and general users to value the existence of libraries more highly and to invigorate their use of libraries.  Design/Methodology/Approach - The details of the research procedure were as follows: First, literature relevant to the libraries' value was comprehensively analyzed to draw out the factors of libraries' value accordingly. Second, a survey was developed to investigate the perception of libraries' value and the target of the survey was selected to perform online and offline surveys.  Third, the differences in perception between groups of librarians and the user group were compared, and further methods to expand the libraries' value were discussed. Findings - First, Libraries had the social value not only on research and personal learning but also on establishment and vitalization of communities, provision of opportunities to share ideas between local residents and create something new, and provision of recreation to improve the residents’ capability. Second, both groups evaluated the libraries’ educational role and function relatively highly. In particular, the librarians scored very high for the items that the libraries’ educational role was expanding, the libraries were a part of the educational system, and the libraries’ value on reading and literacy was great, and the  users thought that libraries had an value because they were a part of education and the educational system. Third, economic value part also obtained relatively lower scores than other values; the mean of the librarian group was 3.46 and the user group was 3.43. Among the economic values, the librarian group scored the highest for the area of economic value for local communities, and the greatest scores were given to manpower development by the users. Originality/Value - The libraries’ values or impacts had been claimed by a number of researchers in the field of library and information science and libraries. There, however, was no research that comprehensively investigated items such as the libraries’ economic, social, and educational values. This study was undertaken to compare the perception of users and librarians regarding the values. This study indicated that most of the librarians more highly valued the libraries than the user group, but that users also valued the libraries more than the mean. URL:  http://ijkcdt.net/xml/14414/14414.pdf
The Role of Forming a Management Model in Educational Organizations

The theory of modern school management is developed as part of the general theory of social institutions management. Very important changes are expected in the system of financing and management of education in accordance with modern requirements. The object and subject of management is a person. The article states that the basic principles and regularities of the management process are generally reflected in all public structures. However, when managing any organization at the request of the manager, the management model is applied to this organization and its staff. And modern management models differ in creating conditions for employees. Accordingly, the author considers the importance and relevance of forming their own management model in relation to the organization of education. The author analyzes the management models of various foreign countries, factors that determine the national management model and formulates their main ideas.
TT-RecS: The Taxonomic Trace Recommender System

Traditional trace links are established directly between source and target artefacts. This requires that the target artefact exists when the trace is established. We introduce the concept of indirect trace links between a source artefact and a knowledge organization structure, e.g. a taxonomy. This allows the creation of links (we call them taxonomic traces) before target artefacts are created. To gauge the viability of this concept and approach, we developed a prototype, TT-RecS, that allows to create such trace links either manually or with the help of a recommender system.
Improvement of Teaching-Learning-Based-Optimization

Teaching-Learning-Based-Optimization is an optimization algorithm that simulates the teaching process. In the standard Teaching-Learning-Based-Optimization there are some problems such as precocity and low optimization accuracy. Through daily discovery, students’ learning effect is better when there are exercise lessons than when there are no exercise lessons. Students who study toward teacher on one’s own learn better than students who do not. Therefore, this paper proposes a teaching mode that combines exercise lessons and one-to-one to improve the Teaching-Learning-Based-Optimization.
Shouted Speech Compensation for Speaker Verification Robust to Vocal Effort Conditions

The performance of speaker verification systems degrades when vocal effort conditions between enrollment and test (e.g., shouted vs. normal speech) are different.This is a potential situation in non-cooperative speaker verification tasks.In this paper, we present a study on different methods for linear compensation of embeddings making use of Gaussian mixture models to cluster shouted and normal speech domains.These compensation techniques are borrowed from the area of robustness for automatic speech recognition and, in this work, we apply them to compensate the mismatch between shouted and normal conditions in speaker verification.Before compensation, shouted condition is automatically detected by means of logistic regression.The process is computationally light and it is performed in the back-end of an x-vector system.Experimental results show that applying the proposed approach in the presence of vocal effort mismatch yields up to 13.8% equal error rate relative improvement with respect to a system that applies neither shouted speech detection nor compensation.
Application of Machine Learning in Computer Vision and Cancer Bioinformatics

Abstract This article focuses on some of the problems of machine learning in computer vision and cancer bioinformatics.Separately, in computer vision, this paper adopts the method based on machine learning to study the face recognition, natural environment image classification, Static Image Behavior Recognition Algorithm;In the bioinformatics, questions relating to the classification of subtypes and stages of breast cancer are explored.
Hermit: A Novel Approach for Dynamic Load Balancing in Cloud Computing

Cloud computing is the recent trend in computing paradigms. It is widely being used by different communities due to its abundant opportunities as resources or services. The cloud hosts a variety of web applications and provides services on a pay-per-use basis. It has many computing issues related to server management, response time, content delivery, etc. As the number of users is raised alarmingly in the cloud, so to balance their need the load balancing has turned to be a major issue in cloud computing. It is one of the challenging tasks to schedule the load in this distributed environment. Hence, it is one of the prominent areas of research and development. In this paper, we have analyzed different metaheuristic algorithms and proposed a novel meta-heuristic algorithm for load balancing in the cloud computing environment. We have evaluated the performance of the algorithm with other competitive schemes such as Tabu Search, Simulated Annealing, Particle Swarm Optimization, and Genetic Algorithm, etc., in different measures like waiting time and turnaround time. The proposed approach outperforms existing schemes.
Problems and Prospects for the Development of Professional Pedagogical Activity in the Context of IT Penetration into Education

All this speaks of the need to improve the theoretical and methodological provisions and practical recommendations of professional and pedagogical training of university teachers in the conditions of informatization of education.
Randomized double and triple Kaczmarz for solving extended normal equations

The randomized Kaczmarz algorithm has received considerable attention recently because of its simplicity, speed, and the ability to approximately solve large-scale linear systems of equations. In this paper we propose randomized double and triple Kaczmarz algorithms to solve extended normal equations of the form $\bf A^\top Ax=A^\top b-c$. The proposed algorithms avoid forming $\bf A^\top A$ explicitly and work for {\it arbitrary} $\mbf A\in\mbbr^{m\times n}$ (full rank or rank deficient, $m\geq n$ or $m<n$). {\it Tight} upper bounds showing exponential convergence in the mean square sense of the proposed algorithms are presented and numerical experiments are given to illustrate the theoretical results.
Thesis Supervisor Recommendation with Representative Content and Information Retrieval

Background: In higher education in Indonesia, students are often required to complete a thesis under the supervision of one or more lecturers. Allocating a supervisor is not an easy task as the thesis topic should match a prospective supervisor’s field of expertise.Objective: This study aims to develop a thesis supervisor recommender system with representative content and information retrieval. The system accepts a student thesis proposal and replies with a list of potential supervisors in a descending order based on the relevancy between the prospective supervisor’s academic publications and the proposal.Methods: Unique to this, supervisor profiles are taken from previous academic publications. For scalability, the current research uses the information retrieval concept with a cosine similarity and a vector space model.Results: According to the accuracy and mean average precision (MAP), grouping supervisor candidates based on their broad expertise is effective in matching a potential supervisor with a student. Lowercasing is effective in improving the accuracy. Considering only top ten most frequent words for each lecturer’s profile is useful for the MAP.Conclusion:An arguably effective thesis supervisor recommender system with representative content and information retrieval is proposed.
Despeckling of SAR Images Using Shrinkage of Two-Dimensional Discrete Orthonormal S-Transform

Speckles are inherent to SAR. They hide and undermine several relevant information contained in the SAR images. In this paper, a despeckling algorithm using the shrinkage of two-dimensional discrete orthonormal S-transform (2D-DOST) coefficients in the transform domain along with shock filter is proposed. Also, an attempt has been made as a post-processing step to preserve the edges and other details while removing the speckle. The proposed strategy involves decomposing the SAR image into low and high-frequency components and processing them separately. A shock filter is used to smooth out the small variations in low-frequency components, and the high-frequency components are treated with a shrinkage of 2D-DOST coefficients. The edges, for enhancement, are detected using a ratio-based edge detection algorithm. The proposed method is tested, verified, and compared with some well-known models on C-band and X-band SAR images. A detailed experimental analysis is illustrated.
A Vocabulary Costruction Method based on Difference between Source Document and Summary for Neural Summarization Model

Pointer-generator, which is the one of the strong baselines in neural summarization models, generates summaries by selecting words from a set of words (output vocabulary) and words in source documents. A conventional method for constructing output vocabulary collects highly frequent words in summaries of training data. However, highly frequent words in summaries could be usually a high possibility to be frequent in source documents. Thus, an output vocabulary constructed by the conventional method is redundant for pointer-generator because pointergenerator can copy words in source documents. We propose a vocabulary construction method that selects words included in each summary but not included in its source text of each pair. Experimental results on CNN/Daily Mail corpus and NEWSROOM corpus showed that our method contributes to improved ROUGE scores while obtaining high ratios of generating novel words that do not occur in source documents.
TPR (TOTAL PHYSICAL RESPONSE) METHOD ON TEACHING ENGLISH TO EARLY CHILDHOOD

&lt;p&gt;&lt;em&gt;This training is carried out to provide knowledge and skills to PAUD teachers in implementing English language &lt;/em&gt;&lt;em&gt;l&lt;/em&gt;&lt;em&gt;earning for early childhood. The subjects of the training were 30 Kindergarten (Kindergarten) and PAUD teachers of Bendosari kindergarten. The training is carried out in 3 stages, namely: (1) strengthening of materials related to the TPR (Total Physical Response) method in early childhood learning; (2) implementation of the TPR (Total Physical Response) method in learning aged children; and (3) evaluation of the material for the TPR (Total Physical Response) method in learning children. Training on the application of the TPR (Total Physical Response) method in learning English for early childhood can improve the understanding, abilities and skills of Kindergarten and PAUD teachers in the District, Sukoharjo Regency in compiling, developing, and implementing English learning using the TPR (Total Physical Response) method. Where the deepening of the material for each training stage reaches 90%. This is evidenced by the results of practice and the implications of each material. Kindergarten and PAUD teachers in Bendosari Subdistrict, Sukoharjo Regency can develop themes and materials, create and use media, choose English vocabulary according to themes and materials, and apply English learning using the TPR (Total Physical Response) method.&lt;/em&gt;&lt;/p&gt;
Multi-Type Classification Comparison of Mammogram Abnormalities

Cancer is a life-threatening disease which reduces the lifespan of humans. If the disease is treated early, the lifespan can be extended. This paper provides a useful method for detecting the abnormalities in the mammograms. The proposed method uses four phases such as pre-processing, segmentation, feature extraction and classification. In the pre-processing phase, median filter is utilized to enhance the quality of an image. The pre-processed image is then segmented by fuzzy C means (FCM). Three different features such as Gaussian–Hermite moments (GHM), Jacobi moments and pseudo Zernike moments (PZM) are extracted from the segmented image. Finally, extreme learning machine (ELM) classifier identifies the normal, malignant and benign kinds of cancer. This method is compared with four different classifiers. The proposed method is tested on mammographic image analysis society (MIAS) dataset and the performance is evaluated against several analogous approaches in terms of accuracy, sensitivity and specificity. The proposed approach substantially provides the best result.
REM: Visualizing the Ripple Effect on Dependencies Using Metrics of Health

In recent years, free and open source software (FOSS) components have become common dependencies in the development of software, both open source and proprietary. As the complexity of software increases, so does the number of components they depend upon; in addition, components are also depending on other components. Thus, their dependency graphs are growing in size and complexity. One of the current challenges in software development is that it is not trivial to know the full dependency graph of an application. Developers are usually aware of the direct dependencies their application requires, but might not be fully aware of the dependencies that those dependencies require (the transitive dependencies). Unfortunately, transitive dependencies can break any software application; therefore, project developers need tools, methods and visualizations to inspect the health of these transitive dependencies and their potential impact.In this work, we propose the Ripple Effect of Metrics (REM) dependency graphs, a visualization of dependency graphs that leverages metrics of the health of dependencies. The two main features of REM dependency graph are: first, to display, and potentially summarize, the full dependency graph of an application based on the health of each of its dependencies; and second, to evaluate the ripple effect of potentially risky dependencies on the rest of the dependency graph. The REM helps application developers inspect the health of all of its dependencies, and also the impact that some of these dependencies might have. By showcasing two examples of popular NPM JavaScript application, we demonstrate that the combination of the ripple effect on the dependency graph using health metrics activity can be beneficial to developers. The advantages of REM graphs are: 1) the metric of health annotation is useful for evaluating the health of dependencies, and 2) the ripple effect of a vulnerability provides an easy method to identify potential risk in a dependency chain and 3) the summarizing mechanisms of the REM help reduce the size and complexity of the large dependency graphs, while focusing in specific aspects of the health of the dependency graph.
A Comparative Study on Quality Characteristics in Designing Educational Applications

Traditional learning methods have significantly changed with the adaptation of modern technologies. Teachers and students have become more interested to build their knowledge when exploring learning materials using various devices and applications. ISO/IEC 25010:2011 and ISO 9241-11:2008 are referred to regarding five quality characteristics in designing educational applications. This paper reports the comparative study that investigates the quality characteristics in existing educational applications by applying the Kirkpatrick Model, which comprises four logical levels in the educational process. The investigation of the quality characteristics involved four types of online educational applications. The analysis shows that more than half (56.66%) of the compared characteristics were not found in the selected educational applications. Thus, the study concludes that the compared educational applications remain to have issues if software developers or software engineers do not consider the five quality characteristics, which include user interface aesthetics, appropriateness recognisability, understandability, effectiveness and satisfaction from the users’ perspectives.
The xx205 System for the VoxCeleb Speaker Recognition Challenge 2020

This report describes the systems submitted to the first and second tracks of the VoxCeleb Speaker Recognition Challenge (VoxSRC) 2020, which ranked second in both tracks. Three key points of the system pipeline are explored: (1) investigating multiple CNN architectures including ResNet, Res2Net and dual path network (DPN) to extract the x-vectors, (2) using a composite angular margin softmax loss to train the speaker models, and (3) applying score normalization and system fusion to boost the performance. Measured on the VoxSRC-20 Eval set, the best submitted systems achieve an EER of $3.808\%$ and a MinDCF of $0.1958$ in the close-condition track 1, and an EER of $3.798\%$ and a MinDCF of $0.1942$ in the open-condition track 2, respectively.
Mineralogy of precious metals in ores of the Yubileinoe porphyry gold deposit (Kazakhstan)

Gold and silver mineralogy is studied in ores of the Yubileinoe porphyry gold deposit (Kazakhstan). Native gold is the major gold mineral. Its fneness varies from 970‰ in magnetite-hematite assemblage to 733–860‰ in pyrite-chalcopyrite assemblage. Silver occurs as admixture in native gold and, occasionally, as silver telluride. Native gold is associated with bi and Pb minerals: rucklidgeite, galenaclaustalite, and tetradymite-kawazulite. According to chlorite geothermometry, the Au, Ag and bi minerals precipitated at temperatures of 250-230 °С. These features are typical of the porphyry gold deposits worldwide. Figures 5. Tables 3. References 17.
Universal functions for linear functions depending on two variables

Abstract We consider universal function’s construction for classes of sums of two arguments modulo 2. We constructed functions with optimal domain cardinality O (log n ).