Reviewerly/exHarmony huggingface dataset:
OFFLINE YORÙBÁ HANDWRITTEN WORD RECOGNITION USING GEOMETRIC FEATURE EXTRACTION AND SUPPORT VECTOR MACHINE CLASSIFIER

Yorùbá language is one of the three main languages that is been spoken in Nigeria. It is a tonal language that carries an accent on the vowel alphabets. There are twenty-five (25) alphabets in Yorùbá language with one of the alphabets a digraph (GB). Due to the difficulty in typing handwritten Yorùbá documents, there is a need to develop a handwritten recognition system that can convert the handwritten texts to digital format. This study discusses the offline Yorùbá handwritten word recognition system (OYHWR) that recognizes Yorùbá uppercase alphabets. Handwritten characters and words were obtained from different writers using the paint application and M708 graphics tablets. The characters were used for training and the words were used for testing. Pre-processing was done on the images and the geometric features of the images were extracted using zoning and gradient-based feature extraction. Geometric features are the different line types that form a particular character such as the vertical, horizontal, and diagonal lines. The geometric features used are the number of horizontal lines, number of vertical lines, number of right diagonal lines, number of left diagonal lines, total length of all horizontal lines, total length of all vertical lines, total length of all right slanting lines, total length of all left-slanting lines and the area of the skeleton. The characters are divided into 9 zones and gradient feature extraction was used to extract the horizontal and vertical components and geometric features in each zone. The words were fed into the support vector machine classifier and the performance was evaluated based on recognition accuracy. Support vector machine is a two-class classifier, hence a multiclass SVM classifier least square support vector machine (LSSVM) was used for word recognition. The one vs one strategy and RBF kernel were used and the recognition accuracy obtained from the tested words ranges between 66.7%, 83.3%, 85.7%, 87.5%, and 100%. The low recognition rate for some of the words could be as a result of the similarity in the extracted features.
Development of Digital Competence of a Future Teacher in the Context of Informatization and Digitalization of Modern Teacher Education

The relevance of the research lies in fact that the digitalization of modern teacher education, according to the adopted national program “Digital Economy of the Russian Federation”, should ensure the preparation of highly qualified staff, who will be able to apply modern and advanced information technologies with a high level of digital skills and competencies, that correspond to social needs and the requirements of the digital economy. Based on these requirements, it becomes necessary to develop the digital competence of the future teacher, in particular, in the field of using augmented reality technologies in professional activities. The aim of the article is to create a technology developing digital competence of a future teacher and methods for using augmented reality tools for teaching physics. The main research methods are: studying the experience of Russian and foreign scientists connected with the problem of future physics teacher’s digital competence formation, questioning, conducting an experiment, which allows us to explore the process of using augmented reality technology as one of the components of digital competence formation. The article revealed that first-year graduate students, on the one hand, are interested in using augmented reality technology in the educational process. On the other hand, they do not have a sufficient level of knowledge and practical skills in this area. The digital competence formation technology for future physics teacher is developed. A technique for diagnosing of formation level of digital competence is proposed and its effectiveness is experimentally proven.
Improving Workload Estimation in Inexperienced Teams with Hybrid Agile Approach

SCRUM framework is an agile technique that is widely used by development teams in order deliver incremental value to customers and dynamically react to project needs. SCRUM framework might be adapted to conform the development team specificities. In the context of an industry project, we have found that an inexperienced development team frequently faced difficulties with estimating the time needed to complete tasks, which led to missed deadlines in most of the projects. Such problem hampers the risk management and degrades the relationship with the customer. Upon closer analysis, it was identified that the main reason to this issue was the team's inability to breaking down a larger task into smaller sub-tasks and associate a realistic workload to each part. Then, based on traditional techniques, a structured approach to workload estimation was introduced in the SCRUM planning meeting to leverage the team's estimation skill. This approach was implemented in two development projects and increased the accuracy in the estimate defined by the team, yielding realistic schedules and increasing technical visibility.
Sliding Mode Control for Interval Type-2 Fuzzy System Under Fading Channels

This paper addresses the problem of sliding mode control for discrete-time interval type-2 fuzzy system subject to fading channels. The multiplicative fading model is established for reflecting the fluctuation of the transmitted signals. Meanwhile, the membership function-dependent sliding function involves the fading coefficient. By using the membership functions depending on the fading signals, the mismatched interval type-2 fuzzy sliding mode controller is designed such that the state trajectories can be driven into the neighborhood of the specified sliding surface. Moreover, the closed-loop fuzzy system is ensured to be mean-square asymptotically stable. Finally, the proposed control scheme is verified by a numerical example.
Implementation of SQ3R Method in Improving the Students’ Basic Reading Skill

The SQ3R method is an increasingly popular and widely used reading method. This method is considered as a method of reading which is quite effective and can produce good understanding. SQ3R is a method of reading to find the main ideas and supporters of the main ideas also help the reader to remember longer. SQ3R is an excellent method for intensive and rational reading. This method is more appropriate for study needs. Because this method is designed according to levels that allow students to learn systematically, and efficiently. The study used qualitative approach by collecting data, arranged in a systematic, factual and accurate. This study used in-depth interviews, observations, and documentation. The results obtained from the implementation of the SQ3R method in improving reading skills at MI Uyunul Ulum Gayam Bojonegoro are good enough, that the SQ3R method can improve students' reading skills. It bocomes a sollution to build student creativity and also makes the students dare to advance in order to uphold the progress of the institution.
Introduction to Corpus Linguistics

Corpus linguistics started to develop as a separate discipline in the 1960s, although early examples of corpus analysis were available, and has flourished since the 1990s – hand in hand with the development of computational technology. In essence, corpus linguistics analyses the information about the frequencies of occurrence of linguistic features and the contexts of their use in language sampled in corpora, a perspective that is unique to corpus analysis. Quantitative techniques in corpus linguistics involve the counting of linguistically meaningful items, e.g. words, phrases and grammatical structures. To be able to systematically evaluate quantitative evidence, corpus linguistics relies on statistical procedures to collect and analyze the data. Corpus linguistics has the aspiration to be a scientific discipline hence it strives for the standardization of its procedures and calls for more methodological rigor and replication. General corpora can also be used as reference corpora in second language research representing the target use of linguistic features.
The Bases for Projecting Individual Educational Trajectories of Future Teachers

The implementation of the Federal State Educational Standard of Higher Education 3 ++ requires devising individual curricula for students with regard not only to the demands of the federal and regional labor markets, as well as of the academic community, but also to the educational needs and interests of students themselves. In our opinion, at a time of shortage of teaching staff, including the system of preschool education, the devising of individual curricula and related to their implementation individual educational trajectories of students will increase motivation for learning that provides them with the opportunity to purposefully choose an individual path of development and self-improvement.The aim of the given paper is to present the bases for projecting individual educational trajectories of future teachers of preschool organizations, consideration of which will create the most favorable conditions for motivation, self-management and self-development of students; will determine effective methods and technologies of their education by individual educational trajectories. The methodological framework for determining the bases for projecting future preschool teachers’ individual educational trajectories includes systematic and competency-based approaches. The key method of the research is the general scientific method of analysis of scientific pedagogical literature and regulatory documents in the field of higher and preschool education. To conduct pedagogical expertise of the bases for projecting individual educational trajectories, the method of group expert assessment is used. The presented bases for the projecting of future teachers’ individual educational trajectories comprise the consistency of the requirements of basic regulatory documents in the field of preschool education and provide a more comprehensive approach to the selection and contents of elective modules, as well as increase students’ motivation for learning and self-improvement in the professional field. The research materials can be useful for university administration and teachers while creating individual educational trajectories for bachelors who are professionally oriented on teaching in preschool establishments.
Chaotic Cryptosystem for Selective Encryption of Faces in Photographs

In this article, a safe communication system is proposed that implements one or more portable devices denominated SBC (single-board computers), with which photographs are taken and that later utilizes the OpenCV Library for the detection and identification of the faces that appear in them. Subsequently, it consults the information in a stored database, whether locally in SBC or in a remote server, to verify that the faces should be coded, and it encrypts these, implementing a new cryptosystem that executes mathematical models to generate chaotic orbits, one of which is used for application on two occasions the technique of diffusion with the purpose of carrying out a small change in one of the pixels of the image, generating very different cryptograms. In addition, in order to make a safer system, it implements other chaotic orbits during the technique of confusion. With the purpose of verifying the robustness of the encryption algorithm, a statistical analysis is performed employing histograms, horizontal, vertical, and diagonal correlation diagrams, entropy, number of pixel change rate (NPCR), unified average change intensity (UACI), sensitivity of the key, encryption quality analysis, and the avalanche effect. The cryptosystem is very robust in that it generates highly disordered cryptograms, supports differential attacks, and in addition is highly sensitive to changes in the pixels as well as in the encrypted keys.
Desiderata for Planning Systems in General-Purpose Service Robots

General-purpose service robots are expected to undertake a broad range of tasks at the request of users. Knowledge representation and planning systems are essential to flexible autonomous robots, but the field lacks a unified perspective on which features are essential for general-purpose service robots. Progress towards planning and reasoning for general-purpose service robots is hindered by differing assumptions about users, the environment, and the overall robot system. In this position paper, we propose desiderata for planning and reasoning systems to promote general-purpose service robots. Each proposed item draws on our experience with research on service robots in the office and home and on the demands of these environments. Our desiderata emphasize support for natural human-interfaces as well as for robust fallback methods when interactions with humans and the environment fail. We highlight relevant work towards these goals.
Starting with Django

“You can create a mobile app with no Swift at all?” my client asked me surprisingly. We were sitting at a coffee shop, and I was pitching an idea to use Python and Django for his mobile app. “Yes, that’s the idea,” replied I.
STUDENTS’ PERCEPTIONS OF ONLINE TEACHER AS RELATED TO MOTIVATION TO LEARN

The goal of this study was to examine the relationship between students’ motivation for learning in an online course and their perceptions regarding the teacher’s role. Participants were 520 undergraduate students in a teacher education college who took asynchronous online courses and responded to a closed-ended questionnaire about motivation for learning (Duncan & McKeachie ,2005) and perceptions of the teacher’s role (Lee, 2011). The findings reveal significant correlations between types of students' motivation and their perceptions of the teacher. Correlation analysis indicated a relationship between students’ type of motivation and their perceptions of the teacher’s role. For students with high levels of Task value, Extrinsic goal orientation and Intrinsic goal orientation, perception of the teacher include filling pedagogical, technical, affective, and differentiating roles. Students with high levels of self-efficacy and control of learning beliefs expect the teacher meet pedagogical and differentiating roles, and those with test anxiety – only affective and technological roles.To further focus the results, regression analysis was performed for each type of motivation. This analysis yielded additional differences regarding the perceptions that students had of their teachers according to the different types of motivation.The findings indicate that students’ perceptions of efficient and precise teaching differ in accordance with the type of motivation for pursuing an online course. In preparing courses, attention should be paid to these differences.Reports of high dropout rates from these courses are proof of the importance of this study, especially in the time of this writing, with the Covid-19 pandemic. References:[1] Duncan, T. G., & McKeachie, W. J. (2005). The making of the motivated strategies for learning questionnaire. Educational Psychologist, 40, 117-128.‏[2] Lee, D. Y. (2011). Korean and foreign students’ perceptions of the teacher’s role in a multicultural online learning environment in Korea. Education Technology Research and Development, 59, 913-935.
Transform a Physics Course in Middle School through Personalized Learning and Digital Platform

The article discusses the possibilities of forming and evaluating subject and meta-subject outcomes provided by the use of personalized learning and a digital platform.It demonstrates how the concept and structure of the platform influence the content and effectiveness of the educational course.Examples describe the use of learning analytics for assessing educational outcomes based on the analysis of data collected by the digital platform.The personalized learning tools aimed at formation of subject and meta-subject outcomes.The summary gives an overview of the results of the two years of experience in teaching physics at school with the use of the digital platform.
Latest Advances of Natural Language Processing and their Applications in Everyday life

Natural language processing (NLP) area of Artificial Intelligence (AI) has offered the scope to apply and integrate various other traditional AI fields. While the world was working on comparatively simpler aspects like constraint satisfaction and logical reasoning, the last decade saw a dramatic shift in the research. Now large-scale applications of statistical methods, such as machine learning and data mining are in the limelight. At the same time, the integration of this understanding with Computer Vision, a tech that deals with obtaining information from visual data through cameras will pave way to bring the AI enabled devices closer to a layman also. This paper gives an overview of implementation and trend analysis of such technology in Sales and ServiceSectors.
Opening Access, Closing the Knowledge Gap? The Right to Science and States’ Obligations to Regulate the Global Science System in the Digital Age

The Corona pandemic as never before shows the advantages of Open Science and Open Access (OA), understood as the unrestricted access to research data, software and publications over the internet. It might prove to become the final push for the long-predicted “access revolution” in the academic publishing system, completing the paradigm shift from a system based on subscriptions to one in which scientific publications are freely available for readers over the internet. This paradigm shift is already underway, with major research funding organisations at the national and international levels massively supporting it. The call for OA has now also been taken up by the Committee on Economic, Social and Cultural Rights, which in its recent General Comment No. 25 on the so-called “right to science” under Art. 15(1)(b) of the ICESCR explicitly asks states to promote OA. Following the line of argument of OA proponents, the Committee finds that OA is beneficial to scientific progress and furthermore a tool to bridge the “knowledge gap”. The aim of this paper is to examine the GC and its implications for the global academic publishing system in the digital age. Analysing and critically assessing the GC, which highlights that “benefitting” from science includes access to science as such and not only to its material outcomes, the paper argues that the added value of the GC, and indeed the independent meaning of the right to science which so far primarily was seen as an enabler for other social rights, lies in this dimension. However, when it comes to OA, the GC is not nuanced enough. Without closer scrutiny, it assumes that OA is generally beneficial to the right to science. This risks to give the human rights blessing to practices deemed highly problematic by many: The OA model which is about to become the global standard risks to benefit the already privileged, namely researchers and publishers in the Global North, further sidelining those at the margins. Rather than narrowing existing gaps, it risks to of further deepen them. A human rights approach to science, the paper concludes, needs to address these global connections and implications rather than to overlook them.
NEURO-FUZZY DATA MINING SYSTEM FOR IDENTIFYING E-COMMERCE RELATED THREATS

E-commerce is driven via Information Technology (IT) especially the web it mostly relies upon on innovative technologies that are facilitated by Electronic Data Interchange (EDI) and Electronic Payment over the web. Several researches have shown that e-commerce platforms are compromised by means of phishing and fraud attacks. This has necessitated trying to find innovative methodologies for defending e-commerce systems and users from the said threats. This research integrates Case Based Reasoning (CBR) and Adaptive Neuro-Fuzzy Inference System (ANFIS) to spot and categorise e-commerce websites transactions as legitimate or illegitimate by analyzing and evaluating some attributes. this may provide an invulnerable platforms for e-commerce users. The system, which was implemented on MATLAB, are often deployed on e-commerce systems and servers to watch e-commerce requests with the aim of identifying legitimate and illegitimate websites and transactions. The results of the implementation indicates that the machine is promising.
GESTURE RECOGNITION SYSTEM FOR NIGERIAN TRIBAL GREETING POSTURES USING SUPPORT VECTOR MACHINE

This paper presents the application of Gaussian blur filters and Support Vector Machine (SVM) techniques for greeting recognition among the Yoruba tribe of Nigeria. Existing efforts have considered different recognition gestures. However, tribal greeting postures or gestures recognition for the Nigerian geographical space has not been studied before. Some cultural gestures are not correctly identified by people of the same tribe, not to mention other people from different tribes, thereby posing a challenge of misinterpretation of meaning. Also, some cultural gestures are unknown to most people outside a tribe, which could also hinder human interaction; hence there is a need to automate the recognition of Nigerian tribal greeting gestures. This work hence develops a Gaussian Blur – SVM based system capable of recognizing the Yoruba tribe greeting postures for men and women. Videos of individuals performing various greeting gestures were collected and processed into image frames. The images were resized and a Gaussian blur filter was used to remove noise from them. This research used a moment-based feature extraction algorithm to extract shape features that were passed as input to SVM. SVM is exploited and trained to perform the greeting gesture recognition task to recognize two Nigerian tribe greeting postures. To confirm the robustness of the system, 20%, 25% and 30% of the dataset acquired from the preprocessed images were used to test the system. A recognition rate of 94% could be achieved when SVM is used, as shown by the result which invariably proves that the proposed method is efficient.
EFFICIENCY OF THE MODEL FOR FORMATION OF PROFESSIONAL-PEDAGOGICAL COMPETENCE FOR SPORTS ANIMATION ACTIVITY

Introduction: Thise article discusses the effectiveness of an educational model for students and postgraduates in acquiring vocational pedagogical competence for sports and animation activities in an educational environment.&#x0D; Study Objective: The authors are based on the Kirkpatrick assessment model. Presented are results that shall establish the degree of effectiveness of applications at the Pedagogical Faculty of Trakia University, Stara Zagora of the competency model of three indicators – degree of satisfaction from the training program, degree of acquiring of competence and learning outcomes.&#x0D; Methods: The methods of pedagogical research used are: questionnaire, didactic test, pedagogical observation, expert evaluation.&#x0D; Results: The results prove the effectiveness of the developed didactical model.
Elucidating the Physics of Nanophotonic Structures Through Explainable Machine Learning Algorithms

Explainable machine learning algorithms were applied to convolutional neural networks to reveal deeper insights into the properties of metamaterials, demonstrating new avenues for physics discovery and device optimization in optics and photonics.