Reviewerly/exHarmony huggingface dataset:
DEFINING THE PHENOMENON OF CREATIVITY IN PEDAGOGICAL THEORY AND PRACTICE

The article is devoted to the construction of a definition of the phenomenon of creativity of future teachers, using the essence of the scope and content of the concepts, generic relations and specific features of the concept of ″creativity of the future teacher″, rules for defining the concept, etc., since the socio-economic situation puts forward new requirements for the process of training future specialists in institutions of higher education. We associate this with the fact that acquiring only subject knowledge in modern society does not make graduates competitive on the labor market. And that is why the New Ukrainian School requires creative, creative teachers of the modern generation. Today, the development of creativity of future specialists in the educational process of pedagogical higher education institutions due to the lack of flexible plans, programs, textbooks, insufficient use of innovative technologies occurs spontaneously, does not encourage students to professional creativity and reorients the components of the current educational system on the basis of modern concepts extremely slowly. It is established that modern psychological and pedagogical science considers this concept in various aspects (general foundations of creativity, mechanisms of creative thinking, creativity as a type of intellectual behavior, ″self-actualization″ in connection with creativity, the special nature of the motivation of creative activity, reflection of creativity and creative productivity at scientific employees, etc. Some methodological inaccuracies and improprieties during the modeling of various processes in educational activity, caused by differences in the interpretation of the concept of creativity in philosophical, scientific, methodical and psychological-pedagogical literature, are outlined. In addition, the publication presents a critical analysis of a significant number of approaches to the formulation of the definitions of the concepts ″creativity″, ″teacher's creativity″, ″creativity of future teachers″, etc. Key words: definition, creativity, pedagogical university, future teachers, gender relations.
ACTIVATION OF METHODOLOGICAL WORK ON THE DEVELOPMENT OF PROFESSIONAL SPEECH COMPETENCE OF PRESCHOOL EDUCATION TEACHERS

The article highlights the issue of intensification of methodical work on the development of professional speech competence of preschool teachers. Based on the analysis of psychological literature, it was found that a lot of scientific research and practical innovations are devoted to the problem of methodical work in various educational institutions. The scientists revealed the peculiarities of the organization of methodical work in educational institutions of different levels, characterized the effectiveness of various practical experiences on the activation of methodical work in preschool education institutions; the content and forms of innovations in the activation of methodical work of educators were revealed. Researchers see the meaning of methodical work in the selection of the most rational methods of teaching and raising children by increasing the level of general didactic and methodical preparation of the teacher for organizing and conducting educational work; exchange of experience between members of the pedagogical team, identification and promotion of advanced pedagogical experience The analysis of purposeful observation of the professional speech activity of educators in organized conditions in online classes, conversations, questionnaires, analysis of the products of the methodical work of educators, documentation of educational material allows us to state that there is no systematic, purposeful nature of planning speech classes for teaching preschoolers to write stories thoughts. The author applied forms of intensification of methodical work on the development of professional speech competence of preschool teachers. Among them are the following: interactive sketches, a moment of empathy, the game-competition «Quote Disputes», the intellectual game-competition «Two Tents», a pedagogical polylogue, a methodical capsule of an educator, an interactive game, a club form «Salon of Errors», a problem table, a creative sheet, methodological ring, panorama of creative works, modeling, seminar-presentation «School of Renewal», interactive interaction «Pedagogical Carousel», compiling a cloud of tags «Describe, tell, think», case model «Using visualization techniques in the process of teaching children of the older group to compose a story reflection», simulation game «Content characteristics of a story-reflection». We see the prospect of further research in the substantiation of the criteria for the activation of methodical work in preschool education institutions; development of didactic and technological foundations of information support for the activation of methodical work on the development of professional speech competence of preschool teachers using modern computer technologies. Key words: activation of methodical work, teachers of preschool education institution, forms of methodical work.
DESIGNING A VIRTUAL LABORATORY FOR DEVELOPING ISLAMIC JOURNALISM

Improvement of student skills can be pursued one of them with practicum activities. Journalism practicum can help students acquire the skills needed by the media industry, such as skills as journalists, editors and layouters. However, from its inception the UINSU KPI Study Program never had a laboratory, especially for online journalism courses. Therefore, the aim of this research is to design a virtual laboratory in the form of a news portal and online magazine as a practicum facility for KPI UINSU students. This research method is Research and Development which starts from problem identification to the manufacture of the final product in the form of news portals and online magazines. The results showed that the design of this virtual laboratory was feasible according to experts and received a positive response from students where most of the students stated that this virtual laboratory helped them to practice journalism needed in the media industry.
COVID-19 and Malaria Parasite Detection and Classification by Bins Approach with Statistical Moments Using Machine Learning

This work introduces the novelty as an application of histogram-based bins approach with statistical moments for detecting and classifying malaria using blood smear images into parasitized and uninfected cell images and the rising disease of COVID-19/Normal lung images.Proposed algorithms greatly vary as compared to the previous work.This work aims to improve accuracy in detection and classification and reduce feature vector dimensionality.It focuses on detailed image contents extracted into 8 bins by considering the significance of the R, G, and B color component relationship in the formation of each pixel.The texture features are represented by the first four moments for each of the three colors separately.This leads to the generation of 12 features vectors, each of size 8 components for each image in the database.Feature dimensionality reduction is achieved by applying different feature selection techniques to obtain desired optimum feature space.The comprehensive feature analysis presented here identifies many useful findings in order to validate the contribution of each image content uniquely in detection and classification.The proposed approach experimented with two image datasets: the malaria dataset obtained from the National Library of Medicine (NLM) and the lung image dataset acquired from the Radiography Database from Kaggle.The performance of work presented here is evaluated and compared with previous work with the same set of parameters, namely precision, recall, F1 score, and the AUC.We have achieved and improved the performances compared to previous work and also achieved better results even for the COVID-19 dataset.
A High-Density EEG Study Investigating the Neural Correlates of Continuity Editing Theory in VR Films

This paper presents a cognitive psychology experiment to explore the differences between 2D and virtual reality (VR) film editing techniques. We recruited sixteen volunteers to view a range of different display modes and edit types of experimental material. An electroencephalogram (EEG) was recorded simultaneously while the participants watched. Subjective results showed that the VR mode reflects higher load scores, particularly in the effort dimension. Different editing types have no effect on subjective immersion scores. The VR mode elicited stronger EEG energy, with differences concentrated in the occipital, parietal, and central regions. On the basis of this, visual evoked potential (VEP) analyses were conducted, and the results indicated that VR mode triggered greater spatial attention, while editing in 2D mode induced stronger semantic updating and active understanding. Furthermore, we found that while the effect of different edit types in both display modes is similar, cross-axis editing triggered greater cognitive violations than continuity editing, which could serve as scientific theoretical support for the development of future VR film editing techniques.
Publication Trends from STEAM in Education from Scopus Database: Bibliometric Analysis

The objective of this study is to shed light on the domain of STEAM education research by employing a three-pronged strategy. This article provides a bibliometric analysis of STEAM education literature by focusing on three major research questions (RQs): RQ1. How has research on STEAM education progressed? RQ2. Who is the most influential in STEAM education research? RQ3. Which affiliations and countries are contributing to STEAM in education? This study combines quantitative analysis with descriptive methods. The evolution of STEAM education and the pattern of publishing found in Scopus, which is determined by research connections, research themes, and scientific journals, are of interest to researchers. Throughout this research, the Bibliometrix R-tool and the BiblioShiny software packages were utilized, one at a time, for data analysis, reduction, visualization, and mapping, respectively. In response to RQ1, this study found the Annual Growth Rate to be 24.19%. This finding is based on the trend of publications in STEAM in Education. The results indicate that there has been an increase in the number of journal articles devoted to this subject, which are frequently disseminated. The second question this research aims to answer is which areas of STEAM education research have the most influence. While Piperopoulos P has the top spot for the most globally mentioned documents, Perignat E holds the top spot for the most locally cited papers. In the meantime, Herro D is a writer who has contributed to the study done in the field of STEAM education. As for RQ3, it can be noted that Jeju National University and the Korea National University of Education are the top two campuses in the world regarding STEAM in Education research publications, both of which are located in South Korea.
Advances in monolingual and crosslingual automatic disability annotation in Spanish

Abstract Background Unlike diseases, automatic recognition of disabilities has not received the same attention in the area of medical NLP. Progress in this direction is hampered by obstacles like the lack of annotated corpus. Neural architectures learn to translate sequences from spontaneous representations into their corresponding standard representations given a set of samples. The aim of this paper is to present the last advances in monolingual (Spanish) and crosslingual (from English to Spanish and vice versa) automatic disability annotation. The task consists of identifying disability mentions in medical texts written in Spanish within a collection of abstracts from journal papers related to the biomedical domain. Results In order to carry out the task, we have combined deep learning models that use different embedding granularities for sequence to sequence tagging with a simple acronym and abbreviation detection module to boost the coverage. Conclusions Our monolingual experiments demonstrate that a good combination of different word embedding representations provide better results than single representations, significantly outperforming the state of the art in disability annotation in Spanish. Additionally, we have experimented crosslingual transfer (zero-shot) for disability annotation between English and Spanish with interesting results that might help overcoming the data scarcity bottleneck, specially significant for the disabilities.
CPSS using Dynamic Spectrum Accessibility on the Blockchain over Non-Real-Time Data

Abstract: Due to being dependent on wireless transmission through various devices for big data sharing in Cyber-PhysicalSocial Systems (CPSSs), radio spectrum resources are seriously in limited availability. Despite the fact that license-free access to the spectrum offers a great deal of promise to reduce the developing shortage of spectrum resources, competition for spectrum is more fierce due to the laxer access regulations. A dynamic cycle of "competition-verification-synchronization-competition" may be introduced by a blockchain technology to address this problem of competition. In this study, we offer a general architecture for managing license-free spectrum resources in CPSSs using blockchain and smart contracts. We precisely partition the spectrum of a local cell into numerous channels, each of which is equivalent to a blockchain. Next, we propose a blockchain-KM protocol that could expedite transaction processing while maintaining a generic blockchain's core features. Users of the Blockchain-KM protocol must mine or lease wireless spectrum, and the entire private chain is transformed into a multi-ring blockchain. In contrast to the conventional mining method, the prize in our mining process includes both a spectrum access licence and virtual currency. Once a miner has secured a permit for spectrum access, it will use the permit to send messages through wireless networks. If a miner decides not to send messages, it may sell its permit at auction. During the auction, we provide a virtual currency called Xcoin for trading spectrums or other items.
Health Care Data Privacy Using the Slicing Technique

Abstract: Data security is essential because it protects an organization's information from fraud, hackers, and even identity theft. To safeguard the security of its information, any business that aspires to run efficiently must have a data protection plan. Data security becomes increasingly crucial as the amount of data created or stored grows. Data leaks and cyberattacks can have disastrous repercussions.
Machine Learning Algorithm for Toxic Comments Analysis

Abstract: Online comments that are toxic tend to drive other users away from a discussion because they are nasty, abusive, or irrational. The risk of online bullying and harassment limits people from expressing opposing views, which has an impact on the free exchange of ideas. Sites fail to properly promote discussions, which forces many communities to restrict or disable user comments. In order to analyze the toxicity as accurately as possible, this paper will carefully evaluate the prevalence of online harassment. In order to solve the text classification problem and determine the optimal machine learning algorithm based on our assessment metrics for the categorization of harmful comments, we will employ six machine learning algorithms and apply them to our data. We will work to accurately assess the toxicity to reduce its negative consequences, which will encourage organizations to take the necessary action.
A rational decision-making approach based on Bayesian network and BDI model for autonomous driving system

The safety of decision-making in Autonomous Driving Systems (ADSs) is a challenging issue, which is very important for ADS development. As a highly acceptable decision method, Bayesian Network (BN) has attracted more and more attention, therefore, its decision confidence and robustness have also become a focus. Since BN is a form of reasoning based on probability, for the decision results with low confidence (that is, the probability values of several optional decision actions have a small difference), when the data is slightly disturbed, it is likely to change, resulting in serious consequences such as car crash. To generate safe decision-making, we innovatively propose a rational Bayesian network decision-making approach based on BDI model. It helps to improve the decision confidence of the traditional BN. BDI model is a well-known theory of inferencing agents' mental states (belief, desire and intention). We use it to guide the decision-making process of Bayesian network. According to the domain knowledge of ADS, we introduce and design rule-based intention inference for the decision agent to build a Bayesian network with BDI-layer. And for other uncertain agents in the environment, we utilize LSTM model to predict their intentions and provide scenario information for the construction of the above network. To sum up, we propose a rational decision-making approach based on Bayesian network guided by BDI model. Our novel approach makes the traditional Bayesian network decision more humanized and improves the confidence of decision results. Finally, we take the lane-change and overtaking scenario as an example to illustrate our approach in detail and demonstrate the effectiveness in improving decision confidence.
Handwritten Text Recognition and Conversion to Speech

Abstract: Handwritten text recognition and conversion to speech is a complex task that involves multiple stages and technologies. The process begins with image processing, where the handwritten text is captured and pre-processed to enhance its quality and remove any noise. The next step is to perform optical character recognition (OCR), which involves recognizing individual characters in the text and converting them into a digital form that can be processed by a computer. Once the text has been digitized, it is processed by natural language processing (NLP) algorithms to identify and extract relevant information, such as dates, names, and numbers. The final step is to convert the digitized text into speech using text-to-speech (TTS) technology. This involves synthesizing a spoken language representation of the text, typically using machine learning algorithms to model the pronunciation and rhythm of human speech. Overall, handwritten text recognition and conversion to speech is a challenging task that requires a combination of image processing, OCR, NLP, and TTS technologies. However, advances in these fields have made it possible to create systems that can accurately recognize and convert handwritten text into speech with high levels of accuracy
Adapting Zeroth Order Algorithms for Comparison-Based Optimization

Comparison-Based Optimization (CBO) is an optimization paradigm that assumes only very limited access to the objective function f (x).Despite the growing relevance of CBO to real-world applications, this field has received little attention as compared to the adjacent field of Zeroth-Order Optimization (ZOO).In this work we propose a relatively simple method for converting ZOO algorithms to CBO algorithms, thus greatly enlarging the pool of known algorithms for CBO.Via PyCUTEst, we benchmarked these algorithms against a suite of unconstrained problems.We then used hyperparameter tuning to determine optimal values of the parameters of certain algorithms, and utilized visualization tools such as heat maps and line graphs for purposes of interpretation.
Analisa Efektivitas Metode Octave Allegro dan Fmea Dalam Penilaian Risiko Aset Informasi Pada Institusi Pendidikan Tinggi

The current rapid development of technology allows all tertiary institutions to utilize information systems to support their operations, such as the Surabaya ABC Institute of Technology. Through the Central Information System Unit (PSI), the ABC Surabaya Institute of Technology can develop and manage ICT (Information and Communication Technology) so that it can easily manage various kinds of data and information. However, it should be noted that currently digital information is an important asset that needs to be protected from various kinds of adverse risks. But unfortunately the application of information asset risk management at the Surabaya ABC Institute of Technology has not been implemented properly. From these problems, the researcher aims to find out the process of managing the security of information assets in tertiary institutions through a risk assessment of the information assets they have. To achieve this goal the research method used refers to the Octave Allegro framework and the FMEA method is used to assess the risk of information assets. The results of this study indicate that the ABC Institute of Technology has 11 important assets which are divided into 5 categories, namely: Data, Hardware, Network, Software, People. Of the eleven assets, six of them have a high level of risk. From these findings it can be concluded that universities also need to manage information security. These results also indicate that the method used by researchers is very helpful in determining the risk of the value of information assets owned by the ABC Surabaya Institute of Technology. So that the combination of the Octave Allegro method with the FMEA method is very effective in helping organizations carry out information security management.
An alternative word embedding approach for knowledge representation in online consumers’ reviews

ÖzPurchasing decisions in e-commerce shopping websites are highly influenced by online reviews.Although online reviews contain finegrained consumers' opinions that reflect their preferences towards products; an important challenge, is that the number of online reviews can be very huge for fast and effective analysis.Hence, discovering the thematic structure of documents plays an important role in analyzing online reviews.The proposed system in this paper aims to discover the main consumer interests in online reviews on Turkish e-commerce websites.For this aim, a novel hybrid method combining Latent Dirichlet Allocation (LDA) and word2vec is proposed.Finally, we compare the performance of our work with those of several state-of-theart baselines on 7 datasets collected from well-known Turkish ecommerce websites.The experimental results show how our proposed approach was able to provide significantly improved performance over baselines.Besides, our method enables us to discover very specific topics complying with consumer interests.