Reviewerly/exHarmony huggingface dataset:
Primary Educators Experts’ Validation of The Developed Mathematics Mobile Application to Enhance the Teaching of Mathematics in Nigeria Primary Schools

Mobile learning brought a great benefit to education through, training at any time; training at the place; learner-centered content; and development of teaching and learning. Smartphones and similar mobile devices have changed the way individuals interact with technology and with each other. To ascertain the usability of the instructional mobile application, it must be verified by experts in the area of the subject content. Hence, it is needed to determine the experts’ validation of the developed mathematics mobile application before it can be used for instructional purposes. Two instruments were used for the validation process: Primary Education Lecturers’ Rating Scale and Primary School Teachers’ Rating Scale. Percentage score and mean were used to answer research questions. The percentage score of the rating for the validation of the developed mathematics mobile application by the six Experts shows that the mobile application satisfied the required standard in the field of primary education. The developed mathematics mobile application has the potential to make teaching and learning basic mathematics easy and interesting. The study revealed that teachers can teach the concept of mathematics to primary school pupils either individually or collaboratively through effective utilization of the mobile application. It was recommended that primary educators should employ a mobile application strategy for teaching those abstract and difficult concepts in mathematics.
A research on students’ readiness for Education 4.0 program

Background/Objectives: The purpose of the study is to find out the factors affecting student readiness for education 4.0.Methods/Statistical analysis: Based on 361 samples, this quantitative research was conducted: reliability testing, exploratory factor analysis, correlation coefficients and linear regression.The result shows that there are four key factors affecting readiness including Self-regulation, Creativity, Upgrade and Attitude.Findings: The result of t-test shows that the group of students who had experienced online learning had higher readiness for the education 4.0 than the others.Improvements/Applications: The advantages that students realize when being involved in the 4.0 education system will help them greatly improve their skills and knowledge.
An Efficient Recommender System Technique in Social Networks Based on Association Rule Based Mining

A recommender system is an information filtering system that has become a buzzword in various areas of marketing and research such as movies, music, books, products and research articles. The main role of recommender systems is to guide users on a personal level to provide an optimum set of suggestions based on the users’ taste, explicit rating of items, his/her demographic and other related valuable information. In the past decade, several approaches have been discussed for recommendation of items to online users keeping in mind the accuracy of prediction, the cold-start problem and the problem of sparsity. However, most of these existing recommender system techniques have failed to define a proper recommendation model that can be well suited for any online social network and can consider majority of the limitations when modeling real-market recommendations. In this paper, we present a novel efficient recommender system technique RecGyp and many other standard commonly used existing prediction techniques and also perform experimental evaluations to make a comparative analysis among each technique. The experiments carried out on the MovieLens 100K and the Yahoo! Webscope Movie datasets demonstrate the superior nature of the proposed RecGyp technique in solving the scalability issue and accuracy of results for recommending items to users of a social network. In addition to the traditional similarity measurements evaluation, results are also provided for three evaluation metrics, Precision, Recall and ROC, to evaluate the accuracy of all the recommender system techniques.
The Kingsguard OS-level mitigation against cache side-channel attacks using runtime detection

Most of the mitigation techniques against access-driven cache side-channel attacks (CSCAs) are not very effective. This is mainly because most mitigation techniques usually protect against any given specific vulnerability of the system and do not take a system-wide approach. Moreover, they either completely remove or greatly reduce the performance benefits. Therefore, to find a security vs performance trade-off, we argue in favor of need-based protection in this paper, which will allow the operating system to apply mitigation only after successful detection of CSCAs. Thus, detection can serve as a first line of defense against such attacks. In this work, we propose a novel OS-level runtime detection-based mitigation mechanism, called the Kingsguard, against CSCAs in general-purpose operating systems. The proposed mechanism enhances the security and privacy capabilities of Linux as a proof of concept, and it can be widely used in commodity systems without any hardware modifications. We provide experimental validation by mitigating three state-of-the-art CSCAs on two different cryptosystems running under Linux. We have also provided results by analyzing the effect of the combination of multiple attacks running concurrently under variable system noise. Our results show that the Kingsguard can detect and mitigate known CSCAs with an accuracy of more than 99% and 95%, respectively.
An Optimal Limit Order Book Prediction Analysis Based on Deep Learning and Pigeon-Inspired Optimizer

Currently, In the system-driven electronic markets, stocks and futures contracts are traded based on the centralization of buy and sell orders in the boundary order book (LOB), as provides much more information about stocks than their prices, such as dynamics of the price and predictability of the next trading move.This paper proposes an optimal limit order book analysis for five stocks, including Amazon (AMZN), Apple (AAPL), Google (GOOG), Intel (INTC), and Microsoft (MSFT).It is based on deep learning and an enhanced pigeon-inspired (PIO) algorithm.The system reduces the dimentaionlty of LOB data sets by using a pigeon-inspired optimizer to determine the most significant features.The fitness function is used to evaluate the fitness value of each solution based on TPR and FPR and the feature count.The optimized LOB feature selection is evaluated using the Decision Tree (DT) classifier.A new deep neural network with high-frequency order series includes convolutional, dense layers and Inception units to predict future stock price movements (Submission, Cancellation, Deletion, Execution visible and hidden orders) in an extensive highfrequency LOB database that supports improving the operational performance of the trading process.The proposed model is evaluated using the LOB dataset, and the results show that the model performs better in predicting the different classes.The analysis of variance ANOVA supports the obtained results that test for the significant difference among the means of all items according to their event types.
Design of Webinar Information System for People with Hearing Impairments

This research aimed to design a webinar platform that can help the deaf understand information while attending online seminars using sign language interpreter features. That way, the deaf will have no difficulty understanding the material being delivered by the speaker. This research method used descriptive methods to describe the problems faced by deaf webinar participants, where the difficulty met when attending online seminars using webinar media. In general, webinar applications lack sign language interpreting features, confusing webinar participants with hearing loss in understanding what the speaker is talking about. This webinar platform can display sign language translators according to the sentences spoken by the speaker. These study results are expected to help create a webinar platform with features that make it easier for participants with hearing disabilities to understand the material quickly.
Evaluation of Multimedia User Interface Design Method for M-learning (MobLearn): A Comparative Study

The multimedia m-learning method (MobLearn method) is a holistic and functional method that includes the key steps, methods, and techniques for using multimedia to create m-learning interfaces.In this paper, the MobLearn process was evaluated by comparing it to one of the latest m-learning methods by Stanton and Ophoff (2013( which has the same function.A comparative case study was employed to examine the degree to which two m-learning approaches are similar in terms of interface architecture and their main characteristics, their differences and the primary function of features that occur in one of them but not in the other.Based on this comparative study, the final version of MobLearn method was introduced in two forms: high-level framework and method steps.In this version, the mapping strategies of m-learning were applied where the mapping techniques deal with a different set of information types and a large variety of media.Povzetek:
Designing English Education Game Application for Early Childhood

This research aims to design a game app design that can help increase children's interest in learning English. The research method used descriptive qualitative by looking at early childhood learning during this pandemic, especially learning English, with additional data from literature studies. The system development method uses the waterfall method consisting of five stages: Requirement Analysis, Design, Implementation, Testing, Maintenance, and object approach method with tools such as use case, activity diagram, and interface design to produce an orderly system. The design of the game application is named GUTHEWORDS. It is expected to help increase children's interest in learning English to guess vocabulary such as animal names and numbers in English to help improve teaching success by making the teaching method fun and interesting for children. Through the implementation of learning through this game, it is expected to make it easier for children to learn to read, remember and hear some vocabulary in English well, also expected to explore the potential, creativity, and interest of children in learning English.
A Qualitative Examination of the Iron Boomerang and Trends in Spectral Metrics across Iron Ore Deposits in Western Australia

There are two major types of iron ore deposits in the Pilbara Province of Western Australia—banded iron formation (BIF)-hosted iron ore deposits and bedded iron deposits (BID), respectively, named martite–goethite and martite–microplaty hematite and the channel iron deposits (CID). These deposits consist mainly of iron oxides such as magnetite, hematite and goethite; the latter have been subdivided into vitreous and ochreous goethite. Combining spectral scanning of diamond drill core, drill chips and pulps collected from these deposits provides a rapid and relatively inexpensive means of assessing the potential mineral makeup within a deposit to make informed qualitative decisions. Additionally, the full width half maximum (FWHM) of the 900 nm 6A1à4T1 crystal field absorption feature within the goethite-dominated region is shown to be related to the type of goethite, namely ochreous and vitreous. The assessment capabilities of the combined metrics are presented in a visual format named as the iron boomerang because of its distinctive manifold. This provides the identification of at least two spectral endmembers comprised of hematite and vitreous goethite, the identification of samples that are moving from a pure hematite to mixed hematite/goethite and lastly into a goethite-dominant-driven regime.
Psychomotor development of preschoolers with speech pathologies by means of art therapy techniques

The article examines the concepts of “psychomotorics” and “psychomotor development” and gives their characterization in preschoolers with speech pathologies, as well as analyzes art therapy technologies as an instrument for psychomotor development of children in this group. The goal of the study is to develop the organizational and methodical aspects of the psychomotor development of preschool children with speech pathologies by means of art therapy technologies. The research is founded on the general scientific research methods of analysis, synthesis, comparison, and generalization, as well as a pedagogical experiment (ascertaining, formative, and control) and empirical data analysis. The data obtained in the study are processed in Excel by mathematical statistics methods. The data obtained in the course of the study give evidence of the positive dynamic of the psychomotor development of preschoolers with speech pathologies after the experimental work with the use of art therapy technologies. Research data confirms that specially organized work with the use of art therapy technologies allows increasing the level of psychomotor development in children with speech impairments. The developed materials can be used by teachers of preschool educational organizations to improve the level of psychomotor development of preschoolers with speech pathologies by means of art therapy techniques.
Multi-style Training for South African Call Centre Audio

Mismatched data is a challenging problem for automatic speech recognition (ASR) systems. One of the most common techniques used to address mismatched data is multi-style training (MTR), a form of data augmentation that attempts to transform the training data to be more representative of the testing data; and to learn robust representations applicable to different conditions. This task can be very challenging if the test conditions are unknown. We explore the impact of different MTR styles on system performance when testing conditions are different from training conditions in the context of deep neural network hidden Markov model (DNN-HMM) ASR systems. A controlled environment is created using the LibriSpeech corpus, where we isolate the effect of different MTR styles on final system performance. We find that noise perturbation and encoding (including downsampling) are the most effective techniques to improve a system on noisy, encoded audio; with significant improvements observed if the training/testing mismatch is large. We evaluate our findings on a South African call centre dataset that contains noisy, WAV49-encoded audio: MTR provides consistent improvements on this set, but these improvements are very small, given the smaller than expected mismatch observed.
Super Resolution MRI Using Generative Adversarial Networks

This paper proposes a new frame for MRI Image Enhancement from a low-resolution (LR) image obtain from an early used MRI machine to generate a high-resolution (HR) MRI image. For this we use Generative Adversarial Networks, which have proven well in image recovery task. Here we simultaneously train two models which is Generative model that captures the data distribution in the LR MRI images, and a discriminative model that estimates the probability that a sample came from the training data rather than generator. For training generator, we have to maximize the probability of discriminator of making a mistake in comparing the fake image. For discriminator the adversarial loss uses least squares in order to stabilize the training and for generator the function is a combination of a least square adversarial loss and a content term based on mean square error and image gradient to improve the quality of generated images of MRI.
An Artificial Intelligence (AI) and Digital Services at King Saud University Libraries in COVID-19 Pandemic

This article presents the Artificial Intelligence (AI) applications and Digital Services (DS) used at King Saud University Libraries as a procedures to continue providing services during the COVID-19 pandemic, which were monitored based on the researcher’s knowledge of what is being done through his observation during this pandemic as a staff member of the Deanship of Library Affairs at King Saud University, in order for the experience of King Saud University libraries to be available for researchers and interested parties to view, benefit from, develop or change what must be changed in other universities libraries As the king Saud University’s Libraries continued to provide their services by employing possible artificial intelligence techniques, And by employment of digital services in the university libraries, while the Covid-19 pandemic has impeded the provision of many services which were provided in their natural form before the pandemic.
Emoticons as Self-Disclosure in Social Media and Its Meaning for People Who are Deaf

Disability, CBR and Inclusive Development aims to enhance knowledge in the field of disability and inclusive development, addressing the needs of practitioners, policy makers, DPOs and the scientific community.
Response of Junior High School Students About Online Learning of PJOK Lessons in The Time of The Covid-19 Pandemic

The purpose of this activity was to determine the responses of junior high school students to online learning of PJOK subjects during the covid 19 pandemic. This study used a qualitative descriptive method. Data collection techniques using online questionnaires. The questionnaire was distributed in the form of a google form link via WhatsApp Group. Observation respondents were 7th grade junior high school students as many as 20 students. The place where the observation was conducted was at SMPN 4 Bandung. Based on the results of student responses, most of the students gave a response that did not like the implementation of online learning of PJOK. Students' understanding of the material presented by the teacher during online learning is less understandable. Most of the student responses stated that online learning of PJOK was not fun because it was done alone at home and could not interact with teachers or friends, so students felt bored compared to offline learning PJOK. In overcoming the difficulties of online learning of PJOK, a more interactive online learning media is needed, so that the level of interaction between teachers and students online is the same as the level of student interaction offline.
THEORETICAL ISSUES OF FORMATION OF MORAL VALUES OF STUDENT YOUTH IN THE REALITIES OF TODAY

The article analyzes scientific research on the issue of forming the moral values of student youth in today’s realities through the prism of Ukraine’s European integration aspirations, proves the need for its comprehensive study due to the identified contradictions. The publication thoroughly explores the concepts of “value”, “morality”, “moral values”. Thus, the concept of “value” is analyzed through the prism of philosophical approaches. The above concept is also studied from the point of view of psychology, sociology and pedagogy. The authors define the main functions of morality, thoroughly analyze the concept of “moral values”, which is also considered from the standpoint of sociology, psychology and pedagogy. The article provides the author’s definition of the process of formation of moral values of student youth, which is considered as a process of rationing based on the internalization of primary values and goals by young people. The authors argue that the formation of moral values of student youth is a systemic process of development and self-development of the individual, and moral education is an integral part of education, which provides a relatively meaningful and purposeful cultivation in accordance with the specific goals, groups and organizations. The publication proves that the main focus of the teacher should be the formation of moral values, and the main goal - the development of the child’s personality, capable of conscious and responsible choice of behavior and actions in various life situations, without violating universal values. The article identifies the following main theoretical problems of formation of moral values of student youth: the problem of coordination of teachers and parents educational influences on student youth in the process of their socialization and individualization; filling the methods of formation of educational activities with appropriate moral content; functioning of interrelation and mutual influence of personal qualities of student’s youth which are in a stage of their formation; creation of an effective model of formation of moral values of student youth which will consider the sequence of development of various qualities of a person. The paper argues that the formation of moral values of student youth is not a common goal that can be achieved in a certain period of time by specific means. The result of this process should be the formed morality of the individual, which can be defined as the highest goal, which allows the existence of all other goals and is the basis of human activity itself. Thus, the formed morality of student youth can be considered not as a goal, but as an ideal - a regulatory principle and a scale for assessing their behavior.
Challenging Experience with Severe Complicated Malaria in the City of Dhaka

Malaria is a vector-borne febrile illness that requires an association of three factors- parasite, vector, andhost- to continue its life cycle. The physical and cultural environments, as rainfall, humidity, and temperaturepermitted Bangladesh to be a malaria-endemic area, where Plasmodium falciparum is the dominantparasite and accounts for 93% of the malaria cases in the country. Due to the high degree of severity of thedisease and about 15% of total annual deaths in Bangladesh, in the year of 1961, Malaria EradicationProgram (MEP) was introduced. NMEP caused a significant reduction in total malaria incidences, severityand deaths. Still 33.6% of the total population in Bangladesh is at risk of malaria and the majority of casesare reported in 13 endemic areas of 64 districts in the country. Above all, resurgence of malaria andtreatment resistant cases have become a burning issue to think about in recent years. Here, we presenttwo severe falciparum malaria cases that challenged us with the complicated nature of the disease inDhaka city, which is not listed as a malaria endemic zone of Bangladesh. J MEDICINE 2022; 23: 87-95
Designing e-Local Content of Teaching Materials for Extensive Reading Course: Lecturer’s Voice

This research focus on designing e-local content of teaching materials for extensive reading course: Lecturer’s voice. It applied R&amp;D based on ADDIE MODEL. ADDIE means Analysis, Design, Development, Implementation and Evaluation. Furthermore, Interview and questionnaire as the instrument of collecting data. The result of this research revealed that the lecturers interested to use this reading material for teaching extensive reading course. It is proved by the positive response given by the lecturer. From 19 distributed questions, 18 questions has Yes response (1). The percentage of the score 1 is 100%, and it categorized as excellent. Moreover, 1 question has No (0)response, and the category of score 0 is poor. Refers to the gathered score, the E-Local Content of teaching materials is feasible to use as the appropriate reading materials for teaching extensive reading course based on lecturer’s voice.