Reviewerly/exHarmony huggingface dataset:
Approach to Implementation of Configuration Process for Adaptive Software Systems based on Ontologies

Analysis of scientific research on the development of adaptive and self-adaptive software systems is conducted. It is established that the use of machine learning methods and feedback diagrams is an effective way to design and develop adaptive software. It is determined that the existing methods do not fully provide the possibility of dynamic changes and expansion of functional and graphic characteristics. The software adaptation process is designed based on the ontological model using the semantic decision-making mechanism. The proposed method allows us to dynamically determine the necessary system characteristics and perform software adaptation. Modification process takes into account the information about currently active device based on data about the needs and requirements of the user. Using the results of designing an abstract approach to software configuration modification, an experimental study of the speed of generating optimal system settings is conducted. According to the results of the experiment, it is established that the new method demonstrates 20% better indicators of the speed of generating software settings compared to classical approaches.
Computer-assisted school experiments as a method for improvement of students’ knowledge in mechanics and atomic/molecular physics in secondary school

We investigate the possibility to improve the effectiveness of school teaching in physics by means of introducing a partially computer-based learning experiment. More specifically, we focused on the preparation and implementation of laboratory exercises in the fields of "Mechanics" and "Atomic/molecular physics" according to the educational content in physics in secondary schools in Bulgaria. The laboratory practicum which we offer for implementation was performed by a small group of 10-th grade (16-year old) students and we present the results as a case study. The pre- and post-practice survey identified areas where significant improvement was observed, as well as some that require additional approaches to overcome difficulties. The results of the research confirm the formulated hypothesis and give reason to claim that the use of a physical experiment in physics education leads to improving the understanding of the basic concepts in the field of mechanics and atomic/molecular physics; improving skills for working with certain devices and computer programs; creating a better understanding of scientific experiment and its relationship to the physical theory.
Research on Pedestrian Multi-Object Tracking Network Based on Multi-Order Semantic Fusion

Aiming at the problem of insufficient tracking accuracy caused by object occlusion in the process of multi-object tracking, this paper proposes a multi-order semantic fusion pedestrian multi-object tracking network. Firstly, the feature pyramid attention module is used in the backbone network to enlarge the receptive field and obtain more abundant feature information to improve the detection accuracy of different scale objects. Secondly, a size-aware module is integrated into the pedestrian re-identification branch network to fuse semantic features from different resolutions and extract more basic pedestrian features, thereby improving the tracking accuracy. Finally, the detection head is reconstructed and the small object detection layer is fused to make the proposed network adapt to objects of different sizes. Experiments on the MOT16 and MOT17 datasets show that the multi-object tracking accuracy of the proposed network reaches 75.4% (MOT16) and 74.3% (MOT17), which effectively deals with the problem of low tracking accuracy caused by occlusion in the field of autonomous driving, and achieves good tracking results. The network proposed in this paper improves the tracking accuracy of pedestrians and provides a basis for further practical applications.
A zero‐watermarking technique based on i‐vector model for audio copyright protection

Abstract Audio zero‐watermarking is a promising technology for audio copyright protection. It does not modify the content of the original carrier and has good imperceptibility. Considering that i‐vector model can map audio signals of different lengths into a vector space of fixed length, which has good robustness against desynchronization attacks, a robust audio zero‐watermarking technique based on i‐vector model is proposed here. The proposed scheme extracts the i‐vector of the input signal to identify its inherent stability features and then generates a key by XOR operation on the watermark and encoded feature sequences. Experimental results show that this scheme can effectively resist common attacks and desynchronization attacks.
Dysarthric Speech Characterization and Classification Based on Affinity Propagation

Millions of people are estimated to suffer from speech impairments originating from various causes, including neurological disorders, brain damage, and physical conditions. Dysarthric speech is hard to recognize and understand because of its enormous variability and low intelligibility rate. In today’s high-tech environment, speech recognition system has achieved more than 95% accuracy, from which dysarthric speakers are far behind and excluded from the state of art escapade. In this paper, we propose a model to narrow down this gap and help them to get recognized by deep feature analysis and informative feature extraction techniques to get a better characterization of dysarthric speech. Linear Prediction Cepstral Coefficient (LPCC) is used as a feature extraction technique and a pre-clustering-based algorithm, Affinity Propagation (AP), is used to select the best features for a speaker based on the locality of the speech signal. SVM is used to verify the selection of features. UASpeech digit dataset is used for the experiment, and the result is consistent. A significant amount of data is required to build a conventional speech recognition system, but some fields, like medically challenged speech recognition, lack sufficient data, that’s why some optimized or alternate techniques are used.
Digital Competencies in University Students through Educational Innovations: A Review of the Current Literature

Technological advances have had a significant impact on education, leading to increased attention on the development of digital skills in university students. The objective of this article was to conduct a review of current literature related to educational innovations aimed at promoting digital competencies in university students, in order to identify current approaches and provide a comprehensive and updated insight into the topic. This research is qualitative, applied, and bibliographic in nature, with a descriptive scope, under a non-experimental, cross-sectional design that employs the analytical-synthetic method. The main findings highlight that educational software, educational platforms, and social networks can be valuable tools that benefit students in their learning and acquisition of competencies in various fields, as long as they are used responsibly, critically, and as a complement to face-to-face teaching.
The integration of technology in university teachers following the TPACK Model

The objective of this research focused on identifying the level of technological integration that university professors of the Faculty of Accounting and Administration of Autonomous University of Sinaloa, México, possess, based on the TPACK model during their teaching practice. The results were determined using the criterion of mean frequencies (M), where the low level of conceptual knowledge corresponds to M£2.3, for an intermediate level M&gt;2.3 and M£3.6 and for the high-level M&gt;3.6. These findings showed that the teachers were, in general, above the mean in the seven dimensions of knowledge that make up the model (M=3.6). The data reflected that the teachers were at a high conceptual level of technological integration due to their level of knowledge. It was shown that the hypothesis is true, since the teaching activities that promote learning are related to the level of technological integration following the TPACK model. Future lines of research may include direct observation of educational practices in the classroom to advance towards greater scientific knowledge about the integration of technological tools in the design and development of teaching activities with technology.
Evaluating the applicability of hardware trust anchors for automotive applications

The automotive trend towards autonomous driving and advanced connected services increases both complexity of the vehicle internal network and the connections to its environment. This introduced complexity further broadens the vehicle cyberattack surface. As mitigation strategy, state-of-the-art security mechanisms utilize so-called hardware trust anchors (HTAs) to protect security-sensitive data and processes in shielded locations that are isolated utilizing hardware security mechanisms. However, there is a variety of different HTAs with different functionality and security guarantees and there is currently no work done that compares and evaluates them against current and emerging automotive requirements. In this work, we evaluate the applicability of various HTAs to secure modern as well as upcoming future automotive applications. For this, we analyze and evaluate HTAs that are already established in the automotive field as well as promising HTAs from other domains. We extend our preliminary work [1] by increasing the range of the analyzed HTAs with solutions that are feasible for the most resource constrained automotive controllers and technologies that become feasible to be utilized by the introduction of high-performance controllers in future automotive architectures. We assess the different HTAs based on the evaluation criteria and in accordance to automotive requirements.
Educational computing to assess decision-making learning in university students

This paper describes a study related to the learning of decision-making heuristics such as preference matrix, break-even point and decision tree from the perspective of using a computational tool. With their respective algorithms, a virtual learning environment through a mobile application (app) aimed at Engineering students was developed. To answer the research questions posed in this report, an empirical study was conducted to assess the effectiveness, efficiency and cost in solving decision-making problems with and without the use of the app. The results in this study suggest that the use of the app in learning decision-making skills facilitates the mathematical process for students, and that by using critical thinking competence, they can make assertive and accurate decisions considering different alternatives.
Community Data Curation Curriculum Development

This poster presents the preliminary findings of the two-year project, Community Data Curation Competency, which aims to extend the current understanding of data curation competencies in the context of community data, engage with strategic stakeholders (educators, practitioners, community organizations) in the process of curriculum design, and design a data curation pilot curriculum to fulfill the current gaps in data curation education to include community data curation competencies.
Education Policies for the Integration of ICT in the Mexican National Education System

The objective of this article is to present an analysis of research and studies from the decade between 2012 and 2021 on education policies for the integration of information and communication technologies (ICT) in the Mexican national education system. Using a qualitative document analysis methodology, it was found that the reviewed works are based on the guidelines proposed by international organizations regarding the use of technology in innovative pedagogical processes. It is concluded that it is essential to continue researching this topic in order to understand how technology is transforming teaching and learning processes, and to identify the progress made and proposals to improve its integration in the national education system.
The Study Program Selection System: Integrated Analytical Hierarchy Process (AHP) and Technique For Others Preference by Similarity to Ideal Solution (TOPSIS) Approach

The study program selection in several high schools or madrasah aliyah (MA) in Riau province is conducted manually. The initial survey found that the study program is commonly chosen by following the friend’s preference and parents’ option instead of their knowledge capability and desire. As a reflection, many students fail to adhere to the school subjects, obtain unsatisfactory results, and even change their study program. Therefore, this paper aims to assist students in altering the appropriate study program by considering students' capabilities, talents and interests by developing a multi-criteria decision support system (DSS). This DSS employs the integrated AHP approach for criteria weighting and TOPSIS for ranking alternatives. Herein, seventy students' data from grade ten MAN 2 Kuantan Singingi grows into this case study. The automation system analysis is executed through the web base DSS system using PHP programming language and MySQL database. As a result, AHP calculates the significance values of the criterion whereby the student interest score values at 0.34, academic report, potential academic test, physiological test, Pre-Test/Post-Test, interview scores, and teacher recommendation scores at 0.21, 0.14, 0.11, 0.09, 0.06, and 0.05, respectively. Subsequently, TOPSIS ranks the students according to the assessment and criteria weighting based on the standard requirement of study program in Mathematics and Science program (MIPA) and Social Science program (IIS). The DSS study program selection application has been tested using the Blackbox and User Acceptance Test (UAT) methods. Both of these approaches indicate that this application is functionally approved and capable of aiding the users in the optimal study program selection, with 81.9% agreement. In a nutshell, this DSS has successfully recommended the optimum study program per the students’ talents, interests, and capabilities and provided the direction development of students’ expertise area for the next level of education.
Improving Learning Abilities Using AI-Based Education Systems

AI is transforming the traditional education system globally. The traditional education system based on historical paradigms has a very feeble scope for creating an interactive environment for the specialized students. AI is providing an innovative, diverse, and impactful roadmap in education system to improve the teaching-learning experience not only for teachers but also for students with special needs. AI with its interactive tools has improved the overall educational system by creating enormous opportunities for specialized students. AI-assisted tools such as live chatbots, class dictating software, verbal command-based eBooks, adaptive personalized tutors, image-based learning, and many more have accelerated the teaching-learning experience. Implication of these tools in the education system inculcate critical thinking and improve student engagement in the various teaching activities. The authors have reviewed the impact of AI in transforming the educational system from traditional to AI-assisted modern educational systems.
Problems of cataloging and research of rare books (based on Persian books)

Қолжазбалар мен сирек кітаптарды зерттеуде каталогтардың алатын орны орасан зор. Каталогтарды құрастыру әрі жауапты әрі уақыт талап ететін ұзақ процесс. Қолжаба немесе сирек кітаптардың каталогын құрастырушыға қойылатын талаптар көп, атап айтқанда қолжазбатану саласынан басқа тіл, тарих, дін, әдебиет, философия және т.с.с. бірқатар пәндерді жақсы меңгеруі тиіс. Одан да маңыздысы осы білімін каталог жасау барысында тиімді қолдана білуі қажет. Қолжазбалар мен сирек кездесетін кітаптар Қазақстанның барлық аймақтарында сақталған. Мақалада ҚР Ұлттық кітапханасы мен Орталық ғылыми кітапхана қорларында сақталған сирек кездесетін парсы тіліндегі кітаптардың тарихы, каталогқа енуі және зерттелуі қарастырылады. Ұлттық кітапхана мен Орталық ғылыми кітапхананың сирек қорларында сақталған парсы тіліндегі кітаптар кеңес дәуірінде аз зерттелген. Қазақстан Республикасы тәуелсіздігін алғаннан кейін де арнайы маман жетіспеушілігінен біршама уақыт сирек кітаптар зерттелмей келген. Сол себепті қолжазбалар мен сирек кітаптарды каталогқа енгізу және кітап тарихын зерттеу жұмыстары соңғы жылдары қолға алына бастаған. Мақалада &nbsp;аты аталған екі кітапхананың сирек қорларында сақталған парсы тіліндегі сирек кездесетін кітаптардың каталогқа енуі мен оларды зерттеу мәселелері жан-жақты зерделенеді. Зерттеу барысында каталог құрастыруға қатысты әдістер, атап айтқанда классификациялау, мәтінтану, кодикологиялық әдіс, хронологиялық және библиографиялық зерттеу әдістері қолданылды. Сонымен қатар кеңес ғалымдары, батыс және ирандық ғалымдардың тәжірибесі мен әдістеріне сүйендік. Зерттеу нәтижесінде парсы тіліндегі сирек кездесетін кітаптардың нақты саны, тақырыптық ерекшеліктері және қазақ интелектуалды өмірінен алатын орны анықталды. Парсы тілінің түрлі медреселерде оқытылғаны мен қазақ қоғамында парсы тілін үйренуге деген қызығушылықтың тарихы тереңде жатқандығы нақты мысалдармен ұсынылды. Парсы тіліндегі сирек кездесетін кітаптар тақырыптарға, баспаларға және жарық көрген елдеріне қарай топтастырылып, осы кітаптардың кітапханаға келіп түсу тарихына қатысты мәліметтер берілді.
Generalization of Renyi’s Entropy and its Application in Source Coding

In this paper, we introduce a new generalization of Renyis entropy β(P) and the most important feature of this generalized entropy Rαβ (P) is that it derives most important entropies that are well known and influence information theory and applied mathematics. Some significant properties of Rαβ (P) has been undertaken in this article. In addition, we introduce a new generalized exponentiated mean codeword length Lβα (P) in this article then determine how Rβα (P) and Lβα (P) are related in terms of source coding theorem.
Noise Removal From Movies by Using Hybrid Smooth Algorithms

Hybrid algorithms are increasingly being employed to reduce noise from videos and images. In this study, new hybrid method was used to eliminate noise from movies by first converting the movies to frames, then the frames to images which the suggested algorithm has been applied. This study aims to create the most noise-free, closest-possible copies of the original movie images in order to produce the purest movie possible. Two traditional images noise removal algorithms were integrated into the suggested algorithm. That is to say, Median filter and the conservative smoothing filter (max &amp;min) algorithms were implemented sequentially by utilizing Matlab software version (2016R).The outcomes of this research improve the proposed algorithm's efficacy when compared to the behavior of currently applied existing algorithms for removing noise from images. In order to evaluate our process in this study, a movie with more than 300 frames was used. Frame models were chosen, and the algorithms were then applied to the frame images. The results show that the proposed hybrid algorithm performed much better than the median and conservative smoothing algorithms in all of the selected frames while tested statically by utilizing both criteria Root Mean Square Error (RMSe) and Normalization Correlation Coefficient (NCC) values which improve the hybrid algorithm the best for removing noise from sample frames.
The Level of Friendship among Al-Israa University Students in the light of Some Variables

This study aimed to find out the level of friendship among the students of Al-Israa University in the Jordanian society, which is attributed to gender and academic qualification, and to achieve the objectives of the study, a questionnaire was prepared to measure the level of friendship among the students of Al-Israa University, and its validity and stability were confirmed, and it was applied to a sample of (361) male and female students, from the bachelor's and master's level at Israa University in Jordan. After using the arithmetic means, standard deviations and t-test, the results of the study revealed that the level of friendship among Al-Israa University students was high, and there are no statistical differences due to the variables of gender and academic qualification in the level of friendship among Al-Israa University students.
The Role Of Peer Assessment Model With A Web Platform In Participation And Learning Achievement Of Students

Technological innovations have led to the widespread use of web-based peer evaluation as an alternative formative assessment strategy. This assessment method has significant potential benefits for the education of the student population (Chien, Hwang, &amp; Jong, 2020). A web-based peer evaluation system and a method for team improvement were developed in order to allow the rapid administration of the assessment, stimulate the provision of quality feedback, and construct effective team operations (Friedrich, 2019). However, very few teachers really put into practice peer evaluations that are completely anonymous. When implementing web-based peer assessment systems, both students and instructors will have obligations. The teachers often have a considerable impact on the outcomes of the usual classroom assessments (Liu, Li, &amp; Zhang, 2017). The finding of this study suggests that there is a wider gap between the evaluations that males and females have of themselves based on their own self-assessments and the evaluations that the lecturer has of them based on their own evaluations. One of the many possible explanations for this phenomenon is that individuals often have a more favourable perception of their own intellect than females. The aim of this article is to provide evidence on the role of the Peer Assessment Model with A Web Platform in participation and learning. A total of fifty reputable publications were searched out; however, only five were proved to have a high level of authenticity and relevancy with the topic.
A Tax Regulatory Framework for Cryptographic Assets

We propose to develop a novel regulatory framework for taxing cryptographic assets. Most tax systems apply the realization principle for taxing cryptographic assets even though such a deferral is regressive, increases capital inequality, decreases governmental tax receipts, and incentivizes taxpayers not to sell or exchange their cryptographic assets and avoid being taxed on any such capital appreciation along with concealing such assets since the taxpayer is not subject to any reporting obligations. The application of the realization principle is clearly unjustifiable in this context, and in order to depart from it, a novel tax framework has to be adopted.
Deep Learning Multi-view Paradigm to Forecast Medical Spending on Patients

Healthcare providers, accountable care management, and capitated medical payment adjustment all benefit from accurate patient spending predictions. A large amount of medical domain knowledge is required, and the models based on linear regression are only somewhat effective in predicting the future. Based on historical claims data, this research provides a multi-view deep learning system for forecasting individual healthcare expenditures in the future. With our multi-view method, we are able to model heterogeneous data, such as patient demographics, medical codes, medicine usages, and facility use, effectively and efficiently. We used a real-world dataset of more than 450,000 pediatric patients to perform predicting tasks. For estimating medical costs, our suggested strategy surpasses all other methods. These results contribute to greater healthcare prevention and accountability.