Reviewerly/exHarmony huggingface dataset:
Criteria, Indicators and Levels of Research of Future Teachers' Readiness for Organization of Dialogic Teaching for Primary School Students

The article substantiates the necessity to study the criterion-content and level structure regarding the formation of readiness of future elementary school teachers to organize dialogic teaching. While creating the program of the experimental work the author has taken into account the basic postulations of psychological and pedagogical science, concerning the problem of the readiness of future specialists to organize dialogic teaching, professionalism of activity and communication and dialogic pedagogical communication. The article offers indicative criteria for studying the readiness of future elementary school teachers to organize dialogic teaching of students: need-motivational, cognitive, social-communicative, reflexive-value and operational-activity, as well as indicators of their detection. The levels of readiness of future elementary school teachers to organize dialogic training are determined - high, medium and low. The author presents the results of the empirical study of the state of students' readiness for dialogic teaching of primary school students according to the need-motivational criterion. The results of diagnostics of future teachers' motivation of achievement, understanding of their motivational structure of dialogic teaching, internal motivation of their readiness for self-development, resistance to external influences (in particular, results of ranking by the degree of importance of motives of future pedagogical professional activity) are presented. It is proved that the introduction into the process of training of primary school teachers of the author’s model allows to change substantially the motivation of future specialists for future professional activity.
Real-time processing for light field imaging using an FPGA-based approach

Light field cameras can capture both angular and spatial information of light, from which depth estimation and refocusing is made possible. One main drawback of these cameras is that the instantaneous capturing is followed by complex post-processing algorithms for phase-space deconvolution to finally obtain multi-focused images. Nowadays these time consuming algorithms are implemented in software and carried out offline outside the camera itself. These cameras usually consist of a microlens array located between the main lens of the camera and the sensor. The calibration of these microlenses is one decisive step in the post-processing of the captured image. In this paper we present the newest findings on an FPGA-based on-the-fly calibration implementation and architectural concepts for efficient post-processing on the same hardware platform, targeting real-time performance of 4D video content.
Professional Self-Development of a Teacher of a Higher Education Institution: Interdisciplinary Aspect

This article deals with the urgent problem of teacher’s professional self-development at a higher educational institution, based on normative and acmeological aspects. In the process of achieving this goal – which is the study of the peculiarities of professional self-development in the terms of Ukrainian higher education in its cultural and historical context – the analysis of such problems, as the transformation of forms of consciousness into educational interactions; professional archetype of a teacher; the transformation of the content of professional self-development, was conducted. The given problem has practical meaning. It means that there are a number of objective factors, which influence the essence of a teacher's professional self-development, as a process, connected with the concept of lifelong education, and turn it into a component of the creation of professional identity. We came to the following conclusions: firstly, concerning the dual nature of professional and personal identity (real and imaginary, virtual), which is objectified in the cultural and educational space of the university; secondly, studying the peculiarities of the teacher's self-development,special attention should be paid to appropriate archetypes as culturally conditioned generalized patterns; thirdly, a change in the type of teacher’s professional self-development is caused by both the transformation of the character of the person’s identity and the change of archetype
Meta-Path based Text Feature Enrichment Using Knowledge Graph

Text feature representation is an important and fundamental problem widely studied in many text analysis tasks such as text classification. However, most of the existing methods on text feature extraction focus on text itself, for example, bag-of-words (BOW). In this work, we propose to make use of Knowledge Graphs (KGs) to enrich text representation in a novel HIN perspective. There are two main challenges due to the complexity of KGs. First, how to address the ambiguity when mapping the entities in a text to a KG. Second, how to incorporate the relations of entities in the same document, which indicate the intra-document semantics. To solve these problems, we present a novel Meta-Path Based Text Feature Enrichment (MeTEN) method. The MeTEN can effectively map nouns or noun phrases in a text to entities in a KG, and effectively discover their relations represented by meta paths in the KG through a novel bi-directional meta path generation algorithm. Extensive experiments on real-world datasets demonstrate that MeTEN can effectively enrich text feature and thus improve text classification.
Non-contact motion estimation using image correlation

Non-contact motion measurement technique was applied to estimate motion of local regions in hand movement. An optical flow technique, based on tracing the pixel level image intensity, and thresholding was applied to obtain displacement parameters. A square subset of reference image was created from the object and correlated to the subsequent images obtained during motion. The technique is applicable in estimating the nano and meso-scale pixel motion.
Impact of the Council of Europe Guidelines on Electronic Evidence in Civil and Administrative Law

On 30 January 2019 the Council of Europe adopted guidelines on electronic evidence in civil and administrative law (hereinafter “the Guidelines”). The article summarizes and analyses this soft law instrument and explains why its creation is important for the proper administration of justice and how it addresses and reflects technological developments, new business models and evolving case-law. Several conclusions have been identified regarding how use of the Guidelines will address current practical problems for courts and attorneys while maintaining full compliance with important principles like the right to a fair trial, protection of private life and national laws of the member states.
ENGLISH INSTRUCTIONAL MATERIALS FOR THE INTEGRATED ISLAMIC ELEMENTARY SCHOOL (SDIT)

The global trend to include English program in the early years of primary education in recent years has given ascend to the need for experienced teachers who was teaching English to young learners. There are kind of instructional materials for teaching English to the young learners. However, not all of instructional materials can be used effectively and appropriately in the classroom especially in an integrated Islamic school which is adopted and combined both government curriculum and integrated Islamic curriculum. Therefore, this research aims in investigating kind of instructional materials that generally used by the English teacher and the impacts of using instructional materials toward the learning environment. Further, the researcher also described the challenges of English teachers in adopting the instructional materials at integrated Islamic elementary school. To reach the aims, a descriptive qualitative study design is conducted towards the participants: seven English teachers from different integrated Islamic elementary schools in Central Java. The research employed questionnaire and interview to obtain the deeper data. The findings of the research are expected to provide an overview for English teacher in choosing the appropriate instructional materials with any considerations since they can motivate the young learners in learning English as a foreign language especially at the integrated Islamic elementary school.
A robust and Adaptable Method for Moving the Mouse Cursor Based on Eye Gazing Technique

with the growing number of computer devices and the increasing time we spent on interacting with such devices, we started to get a new techniques to ease the use of these devices and increase interaction efficiency. Eye gazing techniques allow the user to move the mouse pointer using his eyes. It also helps adults and children with cerebral palsy, spinal cord injuries, brain injuries, Amyotrophic lateral sclerosis, multiple sclerosis and brainstem strokes. The objectives were achieved using a trained Haar classifier for the face Detection in addition to the gradient theory for pupil detection. Also there was a use of OpenCV library that provides a wide variety of functions that were also used to achieve the overall objectives. We experienced several methods forface detection and eye center localization and compare it with the suggested method in terms of accuracy and robustness.
Android-based Attendance System using QR Code and Fingerprint Features

Smartphones acts as a companion to people all over the world. It provides numerous benefits to its users. Smartphones can be used within the academic institution to manage student's attendance. There are different methods to maintain attendance such as biometrics. This paper aims to develop the android based attendance system for students using QR code and fingerprint feature. A decoding algorithm is used to verify QR code and fingerprint extraction and matching techniques is used. This system mainly reduces time for taking attendance and saves the lecturing time.
Strong eventual consistency of the collaborative editing framework WOOT

Abstract Commutative Replicated Data Types (CRDTs) are a promising new class of data structures for large-scale shared mutable content in applications that only require eventual consistency. The WithOut Operational Transforms (WOOT) framework is the first CRDT for collaborative text editing introduced by Oster et al. (In: Conference on Computer Supported Cooperative Work (CSCW). ACM, New York, pp 259–268, 2006a). Its eventual consistency property was verified only for a bounded model to date. While the consistency of many other previously published CRDTs had been shown immediately with their publication, the property for WOOT remained open for 14 years. We use a novel approach identifying a previously unknown sort-key based protocol that simulates the WOOT framework to show its consistency. We formalize the proof using the Isabelle/HOL proof assistant to machine-check its correctness.
A Novel Clustering Algorithm for Faster Passive Sensor Measurement Association

This paper proposes a novel clustering algorithm for static passive sensor measurement association. The algorithm clusters line of sight (LOS) measurements based on the valid solutions of pairwise triangulation between measurements of different sensors. Each valid triangulation solution will give a range value along the LOS as possible target location. Clusters are formed based on the pairwise distance between these range values. The criteria for the validity of a triangulation solution and cluster formation depend on the measurement noise of sensors and geometry of possible target and sensor locations. Intensity of space intersection and association cost of each cluster are used to select association solutions among available clusters. Several algorithms for passive sensor measurement association exist in literature like S-D assignment, Seq(2-D), So-D+Seq(2-D) and algorithms based on intensity of space intersection, however, they are still cumbersome to be implemented in real time. An effort has been made through this novel algorithm to reduce computation time for a feasible real time implementation.
Design Foundations for Emotional Game Characters

Recent Computer Role Playing Games such as Bethesda’s The Elder Scrolls V: Skyrim and Nintendo’s The Legend of Zelda: Breath of the Wild, have entranced us with their expansive, complex worlds. However, the Non-Player Characters (NPCs) in these games remain stale and lackluster outside of scripted events. This is, in part, because game engines generally do not simulate emotions in their NPCs while they wander in the world. Wouldn't these games be much more interesting, potentially even more re-playable, if NPCs reacted more appropriately to the situations they find themselves in?To be able to do this, designers need an engine that models emotion, based on inputs available in the game world and from other designer-defined character elements such as personality, goals, and mood. A full-fledged cognitive architecture could fulfill this task, but it would likely be much too inefficient for use in a real-time environment like a game.There are many psychological models of emotion but only a few have been explored for video game applications. A game requires an emotion engine which generates believable results to enhance NPC agency and player engagement. Unlike AI agents and simulations of cognitive psychology theories, an emotion engine for games does not need to be correct or even justifiable. This enables the exploration of a variety of emotion theories that have not been actively considered for games. One such theory is Plutchik's psychoevolutionary synthesis. He proposes a method of organizing emotions into a cone, where the intensity of an emotion increases as one moves up the sides. It also postulates that primary emotions in the model can be arranged in opposing pairs and that other emotions can be composed from the primary emotions and their intensities. This allows for greater flexibility in the number and type of emotions to include, whereas most models that have been used before define a closed set of emotion types—a serious constraint on designer's freedom. A second theory, Lazarus's cognitive appraisal, better describes emotion elicitation and behaviour selection, and appears to integrate well with Plutchik's work.An emotion engine based on simplified versions of psychoevolutionary synthesis and cognitive appraisal is an understudied approach towards emotional NPCs. Together with readily identifiable elements of emotion processing, such as attention and action selection, an engine can be designed and customized to meet the needs of game designers with minimal impact on computational resources.We will present an overview of some existing cognitive architectures and emotion engines followed by a description of key elements in psychoevolutionary synthesis and cognitive appraisal. Next we list some requirements for an emotion engine for NPCs and how our selected emotion theories meet them. Finally, we propose a design and a collection of game-oriented test scenarios to illustrate how our design handles various facets of NPC emotional responses.
An Overview on Automatic Speaker Verification System Techniques

Automatic Speaker Verification (ASV) is a widely used voice-based biometric system. Like every other biometric system, ASV is also vulnerable to malicious attacks. Replay attacks in ASV systems are a greater threat compared to other attacks. Many types of research have been conducted to find the countermeasures for the replay attacks. Feature extraction and classification are the two fundamental processes of speaker verification. A wide variety of features and classifiers were implemented in the past studies to check their performances. The feature extraction methods discussed in this paper are Mel-Frequency Cepstral Coefficients (MFCC), Linear Prediction Coefficients (LPC), Linear Prediction Cepstral Coefficients (LPCC), Discrete Wavelet Transform (DWT) and Perceptual Linear Prediction (PLP). Some of the classifiers that are discussed are Gaussian Mixture Model (GMM), Gaussian Mixture Model-Universal Background Model (GMM-UBM), Hidden Markov Model (HMM), Support Vector Machine (SVM), Dynamic Time Wrapping (DTW) and deep learning networks like Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). This paper intends to focus on the various attacks in the ASV system along with these two fundamentals of the system.
Topic Based Machine Learning Summarizer

The study develops a summarizer relying on domain-based corpus to enhance classification. Three contributions are brought forth: (1) summarization is extended to a context of spotting a text on food insecurity; (2) use of suitable corpus to promote topical summarization; and (3) shows that extractive summarization considered less effective can be dependable in some situations. These study aspirations were experimented on a task of a human identifying whether an article is on food insecurity or not. Findings showed that a human could still label an article correctly at 98% of Area Under the Curve (AUC) after applying the summarization compared to random classifier performance of 74%. By summarizing the articles, it becomes easy to identify and track conversations on food insecurity in the articles. Trends of these conversations can inform food relief agencies on appropriate actions as dictated by prevailing circumstances. Future work considers blending this summarization with Machine Learning Classification to enhance performance.
Imager assessment by classification of geometric primitives

A large variety of image quality metrics has been proposed within the last decades. The majority of these metrics has been investigated only for single image degradations like noise, blur and compression on limited sets of domain-specific images. For assessing imager performance, however, a task-specific evaluation of captured imagers with user-defined content seems, in general, more appropriate than using such metrics. This paper presents an approach to image quality assessment of camera data by comparison of classification rates of models individually trained to solve simple classification tasks on images containing single geometric primitives. Examples of considered tasks are triangle orientation discrimination or the determination of number of line pairs for bar targets. In order to make models more robust against image degradations typically occurring in real cameras, data augmentation is applied on pristine imagery of geometric primitives in the training phase. Pristine imagery is impaired by a variety of simulated image degradations, e.g. Gaussian noise, salt and pepper noise for defective pixels, Gaussian and motion blur, perspective image distortion. The trained models are then applied to real camera images and classification rates are calculated for geo- metric primitives of different sizes, contrasts and center positions. For task-related performance ranking, these classification rates could be compared for multiple cameras or camera settings. An advantage of this approach is that the amount of training data is practically inexhaustible due to artificial imagery and applied image degradations, which makes it easy to counteract model over fitting by increasing the number of considered realizations of image degradations applied to the imagery and hence increasing the variability of training data.
Multi-Font Arabic Isolated Character Recognition Using Combining Machine Learning Classifiers

Nowadays, optical character recognition is one of the most successful automatic pattern recognition applications. Many works have been done regarding the identification of Latin and Chinese characters. However, the reason for having few investigations for the recognition of Arabic characters is the complexity and difficulty of Arabic characters identification compared to the others. In the current work, we investigate combining multiple machine learning algorithms for multi-font Arabic isolated characters recognition, where imperfect and dimensionally variable input charactersare faced. To the best of our knowledge, there is no such work yet available in this regard. Experimental results show that combined multiple classifiers can outperform each individual classifier produces by itself. The current findings are encouraging and opens the door for further research tasks in this direction.
Lamprophyres and mineralization of the Koytash ore field (Southern Tien Shan)

Research subject . The Koytash ore field is located in the potentially productive Au, Ag, W, Mo, Ti, Fe, Cu, Pb, Zn and REE North Nuratau mineralisation zone of Tien Shan. The authors undertook a study of the composition of dikes breaking through the Paleozoic ore-bearing formations, as well as their petro- and ore-generating role in the formation of the Koytash-Ugat sulphide-rare-metal (W, Mo, Fe) specialised mineralisation. Materials and methods . A study of rock and mineral composition was performed at the Institute of Geology and Geophysics named after Kh.M. Abdullaev. The content of petrogenic and rare elements in rocks and sulphides was determined by ICP-MS using an ICPE-9000 mass-spec trometer in the Central Laboratory of the State Committee for Geology of the Republic of Uzbekistan. The chemical analysis of minerals was performed using a Jeol-8800Rh electronic microanalyser at the Institute of Geology and Geophysics named after Kh.M. Abdullaev. The micrographs of transparent sections were obtained using Nikon Optiphot 2 Pol and Polam R-311 microscopes. Results and conclusions . The conducted study showed that, in terms of their structure, the Koytash ore field dike formations can be regarded as lamprophyres. In terms of their chemical composition, these formations are mafic and intermediate rocks of the subalkaline series. It was found that the composition of lamprophyre dikes correlates with the size of the erosion section. Their melanocratic varieties are confined to the southern part of the intrusion (absolute elevations are 1000–1200 m), and leucocratic – to the northern (about 1900 m). This is assumed to be the result of crystallization differentiation of a single initial melt. The dikes of the Koytash ore field lamprophyres break through not only sulphide-rare-metal bodies of the Koytash-Ugat strip, but also skarn and carbonate rocks and, in turn, are broken through by quartz-polymetallic ore-bearing veins, which testifies to their inter-ore character.
MOBILE-BASED ONLINE EXAM APPLICATIONS USING PROBLEM WEIGHT CLASSIFICATION TECHNIQUES, GROUPING AND RANDOMIZING

Education is an agenda for designing the country's development. Implementation in the field of education is a joint responsibility of both the government and the community, educational institutions are one that plays an important role in the ongoing learning process activities one of which is the examination activities. The test is an evaluation of the learning process to obtain learning outcomes as a form of achievement recognition or completion in an educational unit. The test is still cheating, it is triggered by the lack of confidence in working on the exam questions and the same type of exam questions will provide an opportunity to chat and work together. The author aims to provide a solution in the form of the application of online-based online test applications using question weight classification techniques, grouping and randomization. This mobile-based online exam application was developed using the waterfall model. The results obtained from research on this mobile-based exam application has features to prevent screen capture or screenshots, prevent video recording or video recorder and prevent switching applications that can run multiplatform on Android and iOS. This application has been through the process of testing the user and distributing questionnaires to determine the feasibility of using the weight classification technique with a percentage of 80% so it is suitable for use in examination activities.