Reviewerly/exHarmony huggingface dataset:
Education and Value Re-Ordering of Nigerian Youths in a Multicultural Society

The paper examined the challenges associated with values re-ordering of Nigerian youths in a multicultural society. The researcher employed the philosophical methods of critical reflections, analysis and speculation. Data were sourced from secondary data such as print materials, online journals and articles. The paper is relevant to stakeholders in education, namely, Government, Ministry of Education at various levels, Educationists, Teachers, Managers and Planners of school as well as Parents. Given the numerous contemporary issues in a multicultural Nigerian society, it is the position of the researcher that values should be re- evaluated and re-ordered. Such necessary steps would help savage the Nigerian youths from total collapse inspite of the significant progress in science and technology. Moreso this will offer Nigerian youths right ethical foundation for education.
DISTANCE LEARNING EXPERIENCE IN GEORGIA UNIVERSITIES

The covid-19 pandemic has put the higher education system of Georgia in front of serious challenges. Universities have had to quickly adapt to distance learning methods. Two years of distance learning experience has shown that this method of learning has its advantages and disadvantages. The description of these parties in the paper is based on the personal experience of the author's academic activity.
Increasing Exercise Workload Degrades The Precision Of Rapid Eye Movements

PURPOSE: Exercise involves rapidly changing and unpredictable visual environments. To be safe and successful in sports, rapid eye movements (saccades) must accurately locate targets of interest. The physiological effects of acute exercise on the kinematics of saccades are currently unexplored. METHODS: To test if exercise intensity is a mediating factor in oculomotor control, twenty-five participants completed an incremental workload cycle ergometry protocols composed of 4-minute stages. Relative exercise intensity was determined via expired air analysis, with saccadic eye movements recorded between 40% - 90% VO2max via infrared oculography cameras mounted within virtual reality goggles. RESULTS: Several saccadic kinematic variables scaled linearly with exercise intensity. From 40% to 90% of VO2max, both peak saccade velocity and amplitude significantly increased by 86 ± 27 o/s (p < 0.01) and 2.2 ± 0.8 o (p < 0.01), respectively. Participants' eyes therefore moved quicker and less accurately as workload increased. The latency saccades did not change significantly during the exercise protocol. A follow-up experiment assessed visuospatial attention across the same range of exercise intensities to confirm that alterations in eye kinematics were not attributable to changes in attention. CONCLUSIONS: Our novel approach to assessing oculomotor function during exercise reveals that the precision of eye movements degrades as exercise intensity increases. At the higher intensities, participants gazed beyond the visual target (dot). The magnitude of the exercise- increased displacement of the eyes exceeded foveal vision (the central area of vision where eyesight is sharpest). These findings suggest that the intensity of exercise can alter oculomotor function to the point where visual acuity may be impaired. The precision of saccadic eye movements is degraded during strenuous exercise, to an extent that could prevent effective scanning of a dynamic visual environment. These findings might have implications for safety and performance in sports where surroundings rapidly change in an unpredictable manner.
IMPLEMENTATION OF PROJECT ACTIVITIES AS THE PRIORITY OF PROVIDING CONTINUING EDUCATION

The practical aspects of project activities are analyzed. The main paradigms of the organization of the psychological-pedagogical process of project activities were analyzed, which made it possible to identify the principle positions of it in the fied of inclusion education. The attention is focused on the importance and necessity of studying and providing the best practices of foreign countries in the context of higher education. The key parameters are determined and the pedagogical conditions for the construction of the system of professional training of specialists in the fied of inclusion education are characterized.
Genetic Factors Causing the Prevalence of Anemia in Young Girls and Stunting in Toddlers: A Systematic Literature Review

The prevalence of anemia in adolescents at the national level is still considered quite high. Several factors are associated with the incidence of anemia in female adolescents, namely energy intake, protein intake, iron intake, vitamin C intake, tea or coffee drinking habits, investment in worms, knowledge, education and type of parental occupation, family income, and menstrual patterns as well as genetics. Stunting is also still a problem in Indonesia due to insufficient nutritional intake for quite a long time. Stunting occurs when the fetus is still in the womb and only appears when the child is two years old. anemia caused by malnutrition at an early age increases infant and child mortality. anemia in young women and also stunting in children is very dangerous. Where the purpose of research is to explain Genetic Factors Causing the Prevalence of Anemia in Young Girls and Stunting in Toddlers. A review is conducted on the state-of-the-art methods using the preferred reporting items for reviews and meta-analyses (PRISMA) guidelines. We review literature from several publications and analyze genetic factors that cause the prevalence of anemia in young women. The prevalence of anemia among young women is also caused by genetic factors. Young women tend to experience anemia because during this period they experience growth and development. The risk of anemia increases with physiological shifts such as menstrual periods. To prevent anemia, the government has planned a program for the Prevention and Control of Iron Nutrition Anemia in women of childbearing age which aims to reduce the prevalence of iron deficiency anemia in high school and junior high school students.
Exploring English Information Packaging Constructions in Written and Spoken Language

Information structure refers to the relationship between sentence properties and the surrounding discourse: the legitimacy of the sentences may depend on what has been established by the immediately preceding sentences or phrases in the written and spoken language. Passive clauses, extraposition, the existential construction, the 'it'-cleft construction, pseudo-clefts, dislocation, and pre- and post-posing are described as non-canonical constructions. The paper is to characterize the syntactic differences between these constructions and their basic counterparts and to investigate the factors that encourage or discourage the use of one of these constructions as opposed to the more basic counterpart
Are we making progress in developing knowledge management strategies that support organizational performance?

Purpose The purpose of the present study is to establish the emerging trend of studies on knowledge management (KM) strategy from 2007 to 2021 and identify the most studied constructs, methodologies used and gaps, thereby suggesting future directions. Design/methodology/approach Guided by items on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, the study analyzed 46 articles published within the 15 years under review. Findings An upward trend in KM strategy studies published from 2007 to 2021 emerged, indicating researchers' growing interest in the topic. Further, the studies reaffirmed the essence of having a KM strategy alongside other functional strategies for an organization's outstanding performance. Key KM strategy antecedents were identified: resource availability, communication, business environment, stakeholder participation, organizational culture and incentives. The need to align the KM strategy and other functional strategies with the overall business strategy was also established as critical. Finally, gaps in study methodologies and extant literature were identified, leading to suggestions for future directions. Originality/value The study provides valuable insights regarding the emerging trend of studies on KM strategy over the 15 years, identification of methodologies used in the studies and the most studied constructs. To this effect, the study's uniqueness lies in the identified gaps and recommendations made for future research directions as it strives to bridge the identified gaps.
Enhancing Visual Feedback Control through Early Fusion Deep Learning

A visual servoing system is a type of control system used in robotics that employs visual feedback to guide the movement of a robot or a camera to achieve a desired task. This problem is addressed using deep models that receive a visual representation of the current and desired scene, to compute the control input. The focus is on early fusion, which consists of using additional information integrated into the neural input array. In this context, we discuss how ready-to-use information can be directly obtained from the current and desired scenes, to facilitate the learning process. Inspired by some of the most effective traditional visual servoing techniques, we introduce early fusion based on image moments and provide an extensive analysis of approaches based on image moments, region-based segmentation, and feature points. These techniques are applied stand-alone or in combination, to allow obtaining maps with different levels of detail. The role of the extra maps is experimentally investigated for scenes with different layouts. The results show that early fusion facilitates a more accurate approximation of the linear and angular camera velocities, in order to control the movement of a 6-degree-of-freedom robot from a current configuration to a desired one. The best results were obtained for the extra maps providing details of low and medium levels.
A lightweight weak semantic framework for cinematographic shot classification

Abstract Shot is one of the fundamental unit in the content structure of a film, which can provide insights into the film-director’s ideas. By analyzing the properties and types of shots, we can gain a better understanding of a film’s visual language. In this paper, we delve deeply into the task of shot type classification, proposing that utilizing multimodal video inputs can effectively improve the accuracy of the task, and that shot type classification is closely related to low-level spatiotemporal semantic features. To this end, we propose a Lightweight Weak Semantic Relevance Framework (LWSRNet) for classifying cinematographic shot types. Our framework comprises two modules: a Linear Modalities Fusion module (LMF Module) capable of fusing an arbitrary number of video modalities, and a Weak Semantic 3D-CNN based Feature Extraction Backbone (WSFE Module) for classifying shot movement and scale, respectively. Moreover, to support practical cinematographic analysis, we collect FullShots, a large film shot dataset containing 27K shots from 19 movies with professionally annotations for movement and scale information. Following experimental results validate the correctness of our proposed hypotheses, while our framework also outperforms previous methods in terms of accuracy with fewer parameters and computations, on both FullShots and MovieShots datasets. Our code is available at ( https://github.com/litchiar/ShotClassification ).
Efektivitas Games PowerPoint dalam Meningkatkan Hasil Belajar Pendidikan Agama Islam

Using a learning media adapted to the characteristics of students who like to play, designed through the application of PowerPoint presentations, is a solution for students' PAI learning outcomes. This research used a quasi-experimental design with a pretest-posttest control group design. The research sample consisted of 18 students: 9 in the experimental and 9 in the control classes. The research focused on student learning outcomes before and after using learning media based on PowerPoint games in third grade of SD Negeri 294 Lempa. The results showed that students' learning outcomes experienced an increase after using learning media based on PowerPoint games, as shown in the test results. The indicators can be seen from the pretest-posttest results. In the experimental class, the average pre-test score was 62.68, which increased to 81.1 after the post-test. In the control class, the pre-test score was 48.22 to an average of 50.66 after the post-test. The result of calculating the N-Gain Score for the experimental class was 59.40, which was categorized as quite effective, while the control class's N-Gain Score was 38.16, classified as ineffective.
Research on the Infiltration of Mathematical Culture in Class from the Perspective of Situated Cognition Theory

Mathematical culture contains mathematical ideas, methods, spirits, and their occurrence and evolution processes. Integrating mathematical culture into the mathematics class can develop students’ thinking and promote their comprehension of knowledge. The situated cognition theory helps students connect mathematical culture with real life. This paper analyzes the possibilities of integrating situated cognition theory with mathematical culture and explores the practical paths for such integration.
Improving Students' Listening Skill by Using Role-Play Method in the Material of Asking for and Giving Directions

A communication strategy that enables listeners to comprehend what is said is referred to as listening skills. This enables effective communication to be established as well. This research aimed to improve listening skills in class VII F students of SMPN 6 Semarang for the 2022/2023 academic year in learning English with the material "asking for and giving directions" using the role-playing method. The research design uses Kemmis and Mc. Taggart. This classroom action research was carried out in 2 cycles. The time used for each cycle is 2 meetings with 2 material presentation meetings, and at the end of the second meeting, a cycle evaluation is held. Each cycle has 4 stages: planning, action, observation, and reflection. The number of students involved in this study was 34 students. Data collection techniques using observation and questionnaires. Data were analyzed descriptively and presented in the form of tables and graphs. The results showed increased students' listening scores on the material "asking for and giving directions". Namely, in the first cycle, 32.35% of students were able to exceed the KKM, and then in the second cycle, it increased to 61.76% of students were able to exceed the KKM. Thus, the role-playing method can improve student learning outcomes in listening activities and "asking for and giving directions" for class VII F students of SMPN 6 Semarang.
The learning styles and their impact on the academic education of ecuadorian university students

The objective of this research was to learn about the influence of the use of learning styles in the virtual academic formation of ULEAM students, Extension El Carmen. To this end, the positivist paradigm was used through the quantitative approach, with correlational level field research. The study population was one thousand five hundred and two (1502) students, calculating a sample of three hundred and seven (307), which was extracted with 95% confidence criteria and 5% margin of error, taking two sections of each course at different levels, with the purpose of knowing different opinions from various groups. For the collection of data, the survey technique was used by means of a Likert-type questionnaire, and in this way process the data by using the SPSS version 25. The results obtained show that there is a strong positive correlation in the use of learning styles and the academic training of students. Likewise, it was determined that in the Basic Education career there is a good management of these learning styles, while those of other careers varied from medium to low.
Support vector machines implementation over integers modulo-M and Residue Number System

In low-power hardware implementations for classification algorithms, it is often essential to use physical resources efficiently. In this sense, the use of modulo-M integer operations instead of floating-point arithmetic, can lead to better performance, especially when M represents the dynamic range of an arithmetic block of the Residue Number System (RNS) [1,2]. Following this premise, this work is aiming to provide a methodology for implementing a classifier, specifically a Support Vector Machine (SVM) [3], using modulo-M integers and proposing a method for the use of Residue Number System.
LITERASI EKONOMI DALAM PANDANGAN FILSUF ADAM SMITH DAN KONTRIBUSINYA TERHADAP PENDIDIKAN

The purpose of this study is to determine economic literacy in the view of philosopher Adam Smith and its contribution to education. The research methodology used is a literature-based approach, which is based on books, notes, and summaries of previous research findings. The direct and indirect economic benefits of education, i.e. how it is viewed as an investment that yields long-term benefits. The notion of investing in education is developing rapidly, and it is increasingly widely accepted that the growth of the education sector is a necessary condition for the expansion of other development sectors in all countries.
FACILITATION OF VIRTUAL MEETINGS ON FINANCIAL AND ECONOMIC ISSUES

The essence of facilitation, its types and the secret of preparation for virtual collection are considered. The organizational issues of holding a facilitation session on financial and economic issues are revealed on the example of professional terminology. Proposals for the preparation of the discussion and improvement of its quality were made, which will help to reach consensus by the participants of the virtual meeting.
Investigating Students’ Difficulty in Understanding Idiomatic Expressions on EFL Classroom

This research was conducted to measure the student's ability to understand idiomatic expressions and to find out the student’s difficulty in understanding idiomatic expressions. This research uses the descriptive qualitative method as the research methodology. The population in this study is the fourth-semester students in the English education department, faculty of teacher, training, and education of Muhammadiyah University of Sidenreng Rappang, and the sample in this study is 29 students (4 male students and 25 female) fourth semester, English department, faculties of teacher, training, and education of Muhammadiyah University of Sidenreng Rappang. The data collection methods used in this research are written test, interview, and recorder. A written test was chosen to measure students'' ability to identify idiomatic expressions, interviews were used to find out the student’s difficulty in understanding idiomatic expressions, and the recorder were used to record the interview process and also as data documentation. The data obtained from the test will be processed with a scoring technique and the data obtained from the interview will be processed by the descriptive analysis method. As the result of the study, the written test shows that 2 students categorized on a very good level, 7 on Good, 5 on Average, 3 on Poor, and 3 on very poor, while the interview shows that as many as 62% of respondents have difficulty because they lack vocabulary, 19% of respondents have difficulty understanding idioms based on their language style, and 33% of respondents have difficulty understanding idioms.
Swarm Optimisation-Based Federated Learning for the Cyber Resilience of Internet of Things Systems Against Adversarial Attacks

Federated Learning (FL) is a paradigm of distributed machine learning that enables multiple devices or clients to work together in training a common model while keeping the privacy of individual data. However, FL has several issues such as slow convergence, communication overhead, and vulnerability to adversarial attacks, particularly in Industry 5 environments such as the Internet of Things (IoT) and its integration with traditional manufacturing processes. These challenges stem from the diverse and non-IID nature of data distributed across clients, which leads to slow convergence and increased communication rounds. This paper aims to address these challenges by proposing a grey wolf optimisation-based federated learning (GWOFL) approach for offering resilience in Industry 5.0 settings against adversarial attacks. The proposed approach decreases the number of communication rounds, reduces the payload between clients and the server, and withstands adversarial attacks simultaneously. It also reduces communication overhead and successfully defends against data poisoning attacks. Experimental results have revealed the efficiency of the proposed approach in overcoming the challenges of FL using the MNIST and CIFAR-10 datasets. The proposed approach converges faster, along with higher accuracy compared with the peer FL methods.
Hierarchical Attention-Based Age Estimation and Bias Analysis

In this work, we present a Deep Learning approach to estimate age from facial images. First, we introduce a novel attention-based approach to image augmentation-aggregation, which allows multiple image augmentations to be adaptively aggregated using a Transformer-Encoder. A hierarchical probabilistic regression model is then proposed that combines discrete probabilistic age estimates with an ensemble of regressors. Each regressor is adapted and trained to refine the probability estimate over a given age range. We show that our age estimation scheme outperforms current schemes and provides a new state-of-the-art age estimation accuracy when applied to the MORPH II and CACD datasets. We also present an analysis of the biases in the results of the state-of-the-art age estimates.
Positive-Unlabeled Learning With Label Distribution Alignment

Positive-Unlabeled (PU) data arise frequently in a wide range of fields such as medical diagnosis, anomaly analysis and personalized advertising. The absence of any known negative labels makes it very challenging to learn binary classifiers from such data. Many state-of-the-art methods reformulate the original classification risk with individual risks over positive and unlabeled data, and explicitly minimize the risk of classifying unlabeled data as negative. This, however, usually leads to classifiers with a bias toward negative predictions, i.e., they tend to recognize most unlabeled data as negative. In this paper, we propose a label distribution alignment formulation for PU learning to alleviate this issue. Specifically, we align the distribution of predicted labels with the ground-truth, which is constant for a given class prior. In this way, the proportion of samples predicted as negative is explicitly controlled from a global perspective, and thus the bias toward negative predictions could be intrinsically eliminated. On top of this, we further introduce the idea of functional margins to enhance the model's discriminability, and derive a margin-based learning framework named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Positive-Unlabeled learning with Label Distribution Alignment (PULDA)</i> . This framework is also combined with the class prior estimation process for practical scenarios, and theoretically supported by a generalization analysis. Moreover, a stochastic mini-batch optimization algorithm based on the exponential moving average strategy is tailored for this problem with a convergence guarantee. Finally, comprehensive empirical results demonstrate the effectiveness of the proposed method.