Reviewerly/exHarmony huggingface dataset:
Powtoon as Digital Learning Media in Academic Writing Class: Students’ Perspective and Challenges

Facing the post-Covid-19 pandemic, teachers need to enhance technology in their teaching and learning process, especially in delivering the materials for the students. As digital natives, students are familiar with technology, and it makes them excited in learning English materials. Academic writing materials are complex because it involves expressing ideas carefully elaborated, and well-supported, logically sequenced, rigorously reasoned, and tightly stitched together. Powtoon is one of the solutions to make the materials more interesting and understandable for the students in academic writing class. This study aims to know the students’ perspectives and challenges about the use of Powtoon as digital learning media to improve writing skills. The subjects are 37 students in English Department in one of the state universities in Indonesia. The method is qualitative by using questionnaire, interview, and documentation. It is found that the students have positive perceptions (76.92%) on the use of Powtoon as digital learning media to improve writing skills. Hence, Powtoon is recommended as digital learning media to improve the students’ writing skills. However, the motion of the animation could distract student's concentration in understanding the materials. Apart from that, students still need to ask directly to the teacher if they have not really understood about the materials presented using Powtoon.
Étude Comparative de la Réalisation de la Liaison et de ‎L’enchaînement par des Locuteurs Natifs du Français et ‎des Apprenants Jordaniens

Objectives: The aim of this study is to examine and evaluate the ‎phenomena of liaison and enchaînement (linking) in ‎French as pronounced by Jordanian Arabic-speaking students and native speakers of French. Methods: The research compares the liaison and enchaînement in the pronunciation of students and French speakers. It aims to verify whether learners have the same performance and to highlight, where appropriate, the deviation in their pronunciation. In view of the results, we suggest appropriate remedies to the difficulties that were detected. Results: The results of the research reveal the lack of mastery and incompetence of Jordanian students to syllabify the French sentences. This is manifested through the pronunciation of the prohibited liaison, a low pronunciation rate of obligatory liaison and the non-linking of the liaison and coalescence consonants. Conclusions: The study recommends that it is important teach the liaison and enchaînement in the early stages of teaching French as a foreign language by employing a variety of strategies to address these challenges
Code-Switching Patterns of Senior High School Students and Teachers in the Technical Vocational and Livelihood (TVL) Shops And Language Classes: Basis for Intervention

This study looked into the code-switching patterns of the students and teachers of Isabela School of Arts and Trades Senior High School in the Technical Vocational and Livelihood (TVL) shops and language classes as a basis for intervention in classroom instruction. The study used the descriptive research design. Respondents of the study were five teachers of Technical Drafting, Bartending, Bread and Pastry Production (BPP) and Oral Communication and 105 students in the City Division of Ilagan during the School Year 2019-2020. The instruments used were questionnaire and unstructured interview. Based on the findings of the study, code switching is prevalent in classroom instruction and the most commonly used type is intrasentential. Students’ use of code switching is due to many reasons foremost of which is difficulty driven. This means that they lack the ease to transmit messages in the target language thus they code switch. Secondly, they code switch in consideration of the various linguistic backgrounds of the interlocutors as well as to promote solidarity with them. Lastly, they resort to code switching when they put emphasis more on the meaning or communicative intentions and stress out a point over the language itself. Sex does not influence the type of students’ code switching but it is affected by their age, language spoken and specialization.
Analysis of the Model of Organizational, Methodological and Personnel Support of Educational Activities in Russian Language in the Peopleʼs Republic of China

Russian language centers, including centers of Open education in Russian language and Russian language teaching, in the Peopleʼs Republic of China are analyzed in the article. The study of the functioning of the Russian language centers established at different times in the PRC revealed a number of problems that need to be solved. These include the lack of information promotion of education centers in Russian in the media, non-systemic financing of projects, the implementation of the centersʼ activities mainly on the basis of educational organizations in the PRC, the absence of a single governing body that controls and coordinates the activities of the centers, the shortage of Russian language teachers, the need to update methodological materials. The authors outline possible ways to solve problems aimed at improving the efficiency of existing Russian language centers in China and the centers that are in the process of establishing. The article also suggests a draft model of organizational, methodological and personnel support of educational activities in the Russian language in the Peopleʼs Republic of China, including various modules: regulatory, managerial (personnel), organizational and methodological, material and technical, financial and economic, psychological and pedagogical.
EFFECT OF KNOWLEDGE MANAGEMENT (KM) ON ORGANIZATION PERFORMANCE IN NIGERIAN MANUFACTURING SECTOR

This study aims to investigate the effect of knowledge management on organizational performance in Nigeria manufacturing sector. The research employed primary data sources, with a sample size of two hundred and twenty (220) completed and returned questionnaires. The collected cross-sectional data were analyzed using descriptive statistics, multiple regression, and correlation coefficients, indicating that the overall regression model was appropriate. The finding shows that knowledge creation has a significant effect on organization performance in Nigeria manufacturing sector and it was also revealed that knowledge sharing has a significant effect on organization performance in Nigeria manufacturing sector. The study concluded that knowledge management is considered a crucial factor for the competitiveness of organizations in the current business environment. As a recommendation, organizations are advised to establish knowledge-sharing platforms such as databases, intranets, and training activities to facilitate efficient knowledge sharing among staff and different divisions within the organization.
Development of Visual-Motor Functions in Children Early and Junior Preschool Ages for the Purpose of Prevention of Dyscalculia

The article offers analyzed results of an experimental study that involved children of early and junior preschool age performing tasks of a diagnostic technique that allows identifying in preschoolers of this age category the level of formation of visual-motor functions, the development of which is necessary when forming elementary mathematical concepts in preschoolers. Analysis of the results allowed us to conclude that it is necessary to create conditions for a subject-specific developmental environment, the interaction of specialists, teachers and parents in psychological and pedagogical work on the development of visual-motor functions and the prevention of dyscalculia in preschool age. The article defines the concept of “dyscalculia” and emphasizes the need to create and implement the most effective technologies for correctional work on the formation and development of visual-motor functions in the system of psychological and pedagogical work aimed at preventing dyscalculia in children of this age category.
Privacy-Enhancing Data Aggregation for Big Data Analytics

Data utility and data privacy are serious issues that must be considered when datasets are utilized in big data analytics such that they are traded off. That is, the datasets have high data utility and often have high risks in terms of privacy violation issues. To balance the data utility and the data privacy in datasets when they are provided to utilize in big data analytics, several privacy preservation models have been proposed, e.g., k-Anonymity, l-Diversity, t-Closeness, Anatomy, k-Likeness, and (lp1, . . . , lpn)-Privacy. Unfortunately, these privacy preservation models are highly complex data models and still have data utility issues that must be addressed. To rid these vulnerabilities of these models, a new privacy preservation model is proposed in this work. It is based on aggregate query answers that can guarantee the confidence of the range and the number of values that can be re-identified. Furthermore, we show that the proposed model is more effcient and effective in big data analytics by using extensive experiments.
Nonnegative/Binary matrix factorization for image classification using quantum annealing

Classical computing has borne witness to the development of machine learning. The integration of quantum technology into this mix will lead to unimaginable benefits and be regarded as a giant leap forward in mankind's ability to compute. Demonstrating the benefits of this integration now becomes essential. With the advance of quantum computing, several machine-learning techniques have been proposed that use quantum annealing. In this study, we implement a matrix factorization method using quantum annealing for image classification and compare the performance with traditional machine-learning methods. Nonnegative/binary matrix factorization (NBMF) was originally introduced as a generative model, and we propose a multiclass classification model as an application. We extract the features of handwritten digit images using NBMF and apply them to solve the classification problem. Our findings show that when the amount of data, features, and epochs is small, the accuracy of models trained by NBMF is superior to classical machine-learning methods, such as neural networks. Moreover, we found that training models using a quantum annealing solver significantly reduces computation time. Under certain conditions, there is a benefit to using quantum annealing technology with machine learning.
CHRISTIAN SUBJECTS AND SYMBOLIC IMAGES OF SCIENTIFIC DISCOVERIES IN A REALISTIC PICTURE: THE RELATIONSHIP BETWEEN SCIENCE AND ART

The article deals with the influence of scientific discoveries on the artistic practices of fine arts. We propose a hypothesis about the influence of a new view on the realistic picture by society and artists, as on a visual narrative and narrative practice with a system of semiotic signs and symbols of new realities of natural scientific knowledge of the late Late Middle Ages, the beginning of the New Age in Europe. In this paradigm of scientific discoveries, new proposals for the symbolism of traditional Christian subjects were formed. Was this new symbolic system in the works we are discussing uniquely readable to contemporaries? Probably yes. For those of them who were the customer of easel and monumental paintings, all signs and symbols indicating scientific discoveries were understandable and acceptable in translating into the language of symbols of traditional Christian plots of paintings. We offer a brief overview of the field of poetics of creating a picture from the point of view of realistic exhaustion and reflection
Performance Improvement of Generative Adversarial Networks to Generate Digital Color Images of Skin Diseases

The main task of creating new digital images of different skin diseases is to increase the resolution of the specific textures and colors of each skin disease. In this paper, the performance of generative adversarial networks has been optimized to generate multicolor and histological color digital images of a variety of skin diseases (melanoma, birthmarks, and basal cell carcinomas). Two architectures for generative adversarial networks were built using two models: the first is a model for generating new images of dermatology through training processes, and the second is a discrimination model whose main task is to identify the generated digital images as either real or fake. The gray wolf swarm algorithm and the whale swarm algorithm were relied on to generate values ​​that improve the performance of GANs and insert them into the generator instead of random values, which in turn worked to reduce the loss values ​​for the generated images. Loss values ​​were adopted as a measure of optimizations for each epoch, and the fastest access time to actual digital images for each skin disease was adopted. Before the optimization operations, 50% accurate images of skin diseases were obtained; after the optimization operations, 98% accurate images of skin diseases were obtained.
Blockchain-enabled Pharmaceutical Supply Chain under Uncertain Demand: Cost Prediction through the Tuning of Evolutionary Supervised Learning

This paper provides a new multi-function Blockchain Technology-enabled Pharmaceutical Supply Chain (BT-enabled PSC) mathematical cost model, including PSC costs, BT costs, and uncertain demand fluctuations. The purpose of this study is to find the most appropriate algorithm(s) with minimum prediction errors to predict the costs of the BT-enabled PSC model. This paper also aims to determine the importance and cost of each component of the multi-function model. To reach these goals, we combined four Supervised Learning algorithms (KNN, DT, SVM, and NB) with two Evolutionary Computation algorithms (HS and PSO) after data generation. Each component of the multi-function model has its own importance, and we applied the Feature Weighting approach to analyse their importance. Next, four performance metrics evaluated the multi-function model, and the Total Ranking Score determined predictive algorithms with high reliability. The results indicate the HS-NB and PSO-NB algorithms perform better than the other six algorithms in predicting the costs of the multi-function model with small errors. The findings also show that the Raw Materials cost has a stronger influence on the model than the other components. This study also introduces the components of the multi-function BT-enabled PSC model.
Application of the modal design method for discrete systems

Works considering modal synthesis and using polynomial decomposition of transfer functions of object and controller models are considered mainly for continuous automatic control systems. At the same time, in some cases, it is necessary to consider systems of a discrete type. An example of the synthesis of an automatic control system for an accurate positioning of a table driven by a direct-drive motor is given. Such systems provide accurate positioning in the processes of manufacturing and processing of parts. They are used in various fields of industry: medical, aerospace, automotive and others. In particular, the above model of the precise positioning table is used for packaging semiconductor elements. A feature of this example is the representation of the transfer function of the object model in a discrete form and the presence of four-cycle delay links in it. In addition, this model is unstable due to the presence of poles lying on the stability boundary in it. As a synthesis method, a modal method is used, using a polynomial decomposition of the transfer function of the model of the control object and controller. An approach is also demonstrated that makes it possible to reduce the number of calculations in the synthesis of regulators by reducing the order of the transfer function of the considered object model and reducing the number of unknown parameters of the regulator. At the same time, a regulator is obtained that differs from the original one. Various options for choosing the desired poles of the transfer function of a closed system are analyzed. The choice of the desired poles is carried out in favor of reducing the amount of overshoot of the system relative to the transients of the system with the initial choice of poles.
Mythologization of Time in the Contemporary Media Landscape

The peer-reviewed collective monograph explores the mythologization of time in modern media environments. Philosophers from Lipetsk (A.G. Ivanov, A.A. Linchenko, I.P. Polyakova) and Saratov (S.V. Tikhonova, D.S. Artamonov) consider theoretical and methodological aspects of the mythological understanding of time, analyze time frames in the media environment, use different philosophical approaches in the study of “strange time”. Attention is also paid to practical aspects of time management in everyday life, peculiarities of time mythologization in computer games, digital history, Internet memes and media projects. The specifics of time representation in British TV series and interactive cinema, as well as its manifestations in musical works, also come into the focus of scientific interest. In general, the monograph is a comprehensive study of the mythological dimension of time in the context of contemporary media environment.&#x0D; The instant mythologization of time in media space implies a rejection of the modernist idea of a straightforward flow of time and a return to ancient ideas about the cyclical nature of time periods. A clear temporal sequence of past-present-future is denied and it is argued that events are not necessarily subject to temporal logic. These trends arise from the use of new digital and media technologies that allow ordinary people to experience archaic notions of time in everyday life.
Prostate Cancer Classification Based on Histopathological Images

Prostate cancer is a significant health concern, ranking as the third most common cancer in Malaysian men, with increasing incidence in Asia. The importance of automating the prostate cancer classification process lies in its potential to significantly improve diagnostic accuracy, reduce subjectivity, and enhance overall efficiency compared to the manual approach. The objective of this thesis is two-fold: firstly, to effectively enhance and segment crucial features in the images to aid in the classification process, and secondly, to implement a binary classification task that indicates the presence or absence of malignant tissue on histopathology images. The study compares the performance of two image enhancement approaches, stain normalization with adaptive histogram equalization (AHE) and sharpening, and stain normalization with traditional histogram equalization (HE) and sharpening. Additionally, three machine learning models, namely SVM, DenseNet121, and InceptionResNetV2, are implemented and evaluated for prostate cancer binary classification. The findings reveal that AHE contributes to better contrast enhancement and image quality preservation. Moreover, the InceptionResNetV2 model demonstrates superior performance in terms of accuracy (97.25%), sensitivity (97.5%), specificity (97.5%), and area under the curve (AUC) (97.5%).
DEVELOPMENT OF RESEARCH SKILLS OF FUTURE FOREIGN LANGUAGE TEACHERS THROUGH READING ACADEMIC TEXTS

The relevance of the survey in the article is stipulated with the fact that research skills formed by reading scientific literature conduce to the enhancement of cognitive activity, independence and research personality of students, aimed at studying and cognition of new knowledge in the research process. The analysis of scientific literature and the collection of the necessary material is an essential part of any research; therefore, determining the ways of developing research skills through reading academic texts is an urgent problem. Nowadays the competitiveness of an advanced pro is defined not just by his tall capabilities within the proficient field, but also by the acquisition of research skills that are necessary for a graduate of the digital century. Searching for new strategies contributes to ensuring the quality of professional training of future foreign language teachers. Mastering research skills is a factor in refining the quality of professional training of future foreign language teachers and it is an essential condition for the current stage of development of higher pedagogical education. At the initial stage, any investigation commences with the scrutiny of the literature that contains a numerous quantity of academic texts on the topic of the research. However, students feel difficulties during working with specific and academic information. For instance: misconception of the general meaning of the scientific text, storage of vocabulary, incapability to analyze and summarize information, etc. In order to overcome these problems, we should teach students how to work with academic literature using a set of exercises for developing research skills. Research skills are considered as the acquisition of new knowledge, the selection of new material, analysis, generalization, and acquiring of any information on the research topic. The purpose of the survey in this article is to develop students’ research skills using a set of exercises based on reading academic texts. Keywords: research skills, components of research skills, informational component, the cognitive component, theoretical-cognitive component, academic texts, intensive reading, scanning reading, skimming reading, extensive reading, a set of exercises.
Model Analisis Incident Management pada Layanan Teknologi Informasi Berdasarkan Framework Information Technology Infrastructure Library V3

Information Technology (IT) services are services developed by service provider organizations for customers. Service provider organizations in implementing IT services have a goal to ensure IT systems remain in good condition to avoid incidents. Incidents are unexpected interruptions and reductions in the quality of IT services. Therefore, when an incident occurs in IT services, it is necessary to recover as quickly as possible or it is called incident management. Incident management is very important for service provider organizations, because if incidents are not managed and analyzed carefully then these incidents will recur. On this basis, a study was conducted to develop an IT service incident management analysis model based on the Information Technology Infrastructure Library (ITIL) V3 which aims to serve as a guide in analyzing and making recommendations for incident management. This model uses case studies in the PPTI section at Dinamika University. This model produces three stages including the incident data collection stage which produces IT service incident data. The incident management analysis stage produces a gap analysis, while the recommendation stage produces recommendations for improvement.