Reviewerly/exHarmony huggingface dataset:
THEORETICAL FOUNDATIONS OF THE USE OF LEGO-TECHNOLOGIES IN THE NUS

For the formation of key mathematical competences in elementary school, it is important to use LEGO technologies, which involve modeling choice situations, conducting dialogue, free exchange of ideas, etc. The use of such technologies in mathematics lessons in elementary school contributes to the creation of an educational environment in which social competence is formed, the worldview and coherent speech of students develops, and the child’s character is formed. The purpose of the article is to reveal the main aspects of the use of LEGO technologies in mathematics lessons in elementary school in the conditions of the New Ukrainian School. Originality consists in establishing the main approaches to the effective implementation of LEGO technologies as a condition for the formation of key mathematical competencies in primary school in the conditions of the New Ukrainian School. A complex of the following methods was used during the research: theoretical – generalization, systematization, theoretical modeling, specification, comparison, analysis, synthesis; empirical – observation, analysis of the results of students’ activities, conversations. Working with LEGO will help to expand knowledge and form correct ideas about the surrounding world, architecture, transport and landscape. In addition, it promotes the development of attention, memory and creative thinking of primary school students. Using LEGO also helps to build dialogic speaking skills, expand vocabulary and the ability to work in groups, communicate and be tolerant of each other. Working with the LEGO constructor also contributes to the creation of a friendly atmosphere in the classroom. Well-organized work with a LEGO constructor has great potential: it helps to develop certain qualities – perseverance, mutual respect, accuracy, patience, develops creative thinking. The use of LEGO technologies can be useful in providing a more interactive approach to learning, which allows students to become more involved in the learning process and increase their motivation to learn mathematics. Thanks to the possibility of construction, students can make their own discovery and research, which contributes to the development of creative thinking and self-confidence. Thus, the use of LEGO can be very useful for developing mathematical skills and preparing students for further study of more complex mathematical concepts. The introduction of LEGO technologies in mathematics classes activates the development of logical thinking, such mental functions as analysis, synthesis, the establishment of patterns by students of education and the identification of relevant analogies, will contribute to learning and the development of the ability to make decisions and evaluate their correctness with the help of modeling real situations based on development mathematical apparatus. It makes sense to direct further research in the direction of studying the organizational and pedagogical conditions of effective use of LEGO technology in the educational process of primary school.
IMPLEMENTATION OF MOBILE LEARNING IN THE EDUCATIONAL PROCESS

This article reveals the content of mobile learning and substantiates the current trends in the use of modern information technologies in the educational process. The main priority of a modern developed country and its development strategy is to improve the level of education, which is characterized by the effective introduction of modern technologies into the educational process. At the stage of development of modern technologies and the situation in our country, mobile learning began to be widely used. Mobile learning is one of the strategies in education that directs the capabilities of mobile phones to the ability to become an assistant to the learner when needed. One of the advantages of mobile learning is that the learner can study regardless of place and time. Also, this form of education provides more opportunities to get an education, achieve a high level of socialization, develop communication and life skills, as well as the ability to work in a team. Since mobility is one of the characteristic features of modern society, which, along with the development of technology, is improving and developing at a fairly fast pace, then mobile learning is one of the promising and interesting areas of research, namely its introduction into the educational process. Therefore, at this stage, the search for new approaches in the organization of the educational process and the development of didactic and methodical materials for the implementation of mobile learning is of particular relevance. The use of mobile learning in modern conditions, the relevance and lack of awareness of the chosen problem, its theoretical and practical significance determined the choice of the research topic. Research and analyze the peculiarities of the implementation of mobile learning in the educational process and develop methodical approaches to conducting classes in a mobile format. Since the current level of information technology development opens up new perspectives for the use of mobile applications in the educational process, expanding opportunities with the help of mobile learning, the modern teacher must create such an educational environment that allows access to educational materials at any time and in any place, provide maximum flexibility, convenience, efficiency regardless of place and time. Therefore, mobile learning is another high step towards human development, and technology is our future, which can affect the high development of humanity.
Review of Parameter Tuning Methods for Nature-Inspired Algorithms

Almost all optimization algorithms have algorithm-dependent parameters, and the setting of such parameter values can largely influence the behaviour of the algorithm under consideration. Thus, proper parameter tuning should be carried out to ensure the algorithm used for optimization may perform well and can be sufficiently robust for solving different types of optimization problems. This chapter reviews some of the main methods for parameter tuning and then highlights the important issues concerning the latest development in parameter tuning. A few open problems are also discussed with some recommendations for future research.
Determining the Eligibility of Livestock Assistance using the Weighted Aggregated Sum Product Assessment Method

Livestock is a part of the agricultural sector in Indonesia's national development which aims to increase the income and welfare of farmers and ranchers. This is evidenced by the growth rate which is always positive and the contribution which tends to increase, one of which is the Agam Regency Animal Husbandry Service. In providing assistance, the Livestock Service Office of Agam Regency, in providing assistance, livestock assistance is often not on target and the livestock assistance that is given is not properly managed because often groups of farmers or livestock after receiving assistance after being checked again, the livestock that are given are not well cared for. In providing livestock assistance, it is still being carried out by using a manual process, namely the Agam Regency Animal Husbandry Service in providing assistance does not use a special calculation method such as using the scientific method. The implementation of the Decision Support System in this study uses the Weighted Aggregated Sum Product Assessment (WASPAS) method, which is a combination method of the WP method and the SAW method. The WASPAS method is expected to provide better results in assisting the determination of decision support systems. Then the best solution will be made to help make a decision to determine the feasibility of livestock assistance using the Weighted Aggregated Sum Product Assessment (WASPAS) method. The results of this study that get the highest ranking is Breeder 4 with a preference value of 0.84. This research also produces a decision support system that can analyze the right assistance to be given to farmers so that farmers can receive assistance according to the problems they face.
Analysis of Home Appliances Functional Failure on Certainty Factor-Based Engineering ACS

Technological developments are currently experiencing very rapid changes along with human needs that are increasingly numerous and complex. Not only in the fields of health, education, agriculture, and so forth. However, the electronics industry has also been affected by the development of this technology. The production of household electronic devices or home appliances that combine sophistication of technology and modern designs has emerged and is much in demand by the public, one of which is the refrigerator. Even with the development of this technology, it does not mean that the refrigerator can function properly forever if it is used continuously. Because the refrigerator requires maintenance and repair if there is damage. In diagnosing damage to a 2-door no frost home appliances refrigerator, limitations in information, knowledge, and experience from the public and technicians cause delays in recognizing the damage that has occurred, which also affects decision-making in handling it. Then a system will be formed using an expert system computer program with the Certainty Factor method. The Certainty Factor method is a method for accommodating statements from an expert in their delivery. where a website-based expert system is created that can be used without any space and time limitations to help new technicians and the public. The result of testing this method is the resulting accuracy rate of more than 90% of the data&#x0D; has been tested so that it can assist technicians in diagnosing damage to the no frost 2 door refrigerator
Customer experience discovery model based on sentiment analysis and machine learning method

Exploiting customer insights plays a key role in the long-term development strategy of every business, which strongly supports them in building trust with customers and enhancing competitive advantages. Especially in the period of rapid growth of technology, as there is a significant increase in online users, all the interactions and comments become more important in extracting valuable insights into customer behaviours and emotions. Our research aims to conduct sentiment analysis on comments in mobile commerce apps , then classify them into positive or negative sentiment, based on a hybrid approach that combines supervised machine learning methods and natural language processing techniques; at the same time, evaluating the model performance through the Confusion Matrix to ensure the reliability of the results. The study experimented on a proposed model with 04 machine learning methods including Naive Bayes, SVM, Random Forest and Logistic Regression on more than 935,000 comments collected from 04 popular mobile commerce apps in Vietnam (Tiki, Shopee, Lazada and Sendo). The experiment categorised positive and negative views with high accuracies of 91%, expressed by reports and charts that reflect customer trends and feelings. Moreover, the study also brings new and deeper perspectives on customer behaviours, assisting administrators to detect the strengths and weaknesses of services and apps, thereby improving user experience. Based on the research results, E-commerce businesses can analyse market trends and explore customers' needs and interests to develop effective product and service development strategies.
SOSIALISASI PENINGKATAN KOMPETENSI PEMBELAJARAN MATA KULIAH AKUNTANSI MASA PANDEMI COVID 19 TERHADAP MAHASISWA/I DI WILAYAH JABODETABEK

This research analyses development of e learning facility with Online sytem Of Accounting .Improving the quality and learning quality of accounting courses is one of the efforts made to improve student competence.this study aims to better understand the online lecture learning system by using an integrated online system in financial accounting and management accounting courses in increasing skills and knowledge for students in the Greater Jakarta area and surrounding areas.This qualitative descriptive study uses the content method with 20 respondents and the results of long distance interviews from student representatives in the Greater Jakarta Area.It is hoped that this researchwill result in an increase in quality and competence on post pandemic Covid 19 to students in e learning process online integration system.The limitation of this research is the impact of elearningonline system of financial accounting and management accounting subject.The contribution of this research is that business Financial accounting and business administration’s student in Accounting majoring are able to maintain skill and knowledge
PELATIHAN PENERAPAN MODEL PEMBELAJARAN KOOPERATIF BERBANTUAN KANCING GEMERINCING

Teachers as educators are expected to help students improve their knowledge. Therefore, it is necessary for teachers to know the application of learning models, especially in mathematics, which is one of the important subjects in the field of education. Many teachers use conventional learning models. It is less effective and boring for students. One of the learning models that are considered very good to be applied is the cooperative learning model assisted by jingling buttons. Through community service activities in class VII SMP HKBP Lubuk Pakam, the learning model was applied. The form of activity is carried out with lectures and practice. The result is that teachers and students understand the application of the jingling button-based learning model and the students are also seen to be active and enthusiastic in learning, even trying hard to answer the math problems given correctly and quickly until the buttons obtained by the group run out.
IMPLEMENTASI TEKNOLOGI MIXED REALITY SEBAGAI INOVASI STRATEGI PEMBELAJARAN SISTEM PEMBANGKIT TENAGA LISTRIK ENERGI BARU TERBARUKAN

&#x0D; &#x0D; &#x0D; &#x0D; Abstract: In an era that is completely digital, Information and Communication Technology (ICT) is very influential in many aspects of life, not to mention in the field of education, especially in universities. Along with the existence of an independent campus policy from the ministry of education, many universities are trying to harmonize appropriate learning methods. This can support the needs of superior human resources from higher education, so that the existence of ICT-based learning methods that present reality in a learning atmosphere is very important to design an appropriate visualization strategy. One of the ICTs that presents reality in a learning atmosphere that can be applied to the education sector is Mixed Reality (MR), which is a combination of Virtual Reality and Augmented Reality. This research will be conducted using research and development methods, where data collection will be carried out first and the selection of learning materials and end with the implementation and dissimilation. The benefits of applying this learning method are expected to create a learning environment that is closer to reality and establishes student independence in learning. The output of this research is the creation of MR-based learning materials at SMK TI Muhammadiyah Cikampek.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D;
The Driving Forces for the Involvement of Higher Learning Institution’s Students in Cybercrime Acts. A Case of Selected Higher Learning Institutions in Tanzania

This study investigates the extent and driving forces of cybercrime acts among students in higher learning institutions. The research digs into common cybercrime involvement and explores potential motives driving students' engagement in such illicit activities. A mixed-methods approach was adopted, involving online surveys and interviews with 308 samples size from a population of 1500 participants from selected higher learning institutions in Tanzania. Institutions involved in this study included Collage of Business Education (CBE), Dar es Salaam Institute of Technology (DIT), Institute of Finance Management (IFM) and Tanzania Institute of Accountancy (TIA). The findings revealed that digital piracy, hacking, computer viruses, spam mailing, computer-related forgery, and cyberbullying were prevalent forms of cybercrime among the participants. Significant associations were identified between cybercrime involvement and factors such as social-economic status, technological changes, peer influence, lack of awareness of cybercrime, individual traits, and internet usage contributing to students' involvement in cybercrime. In light of these findings, the study recommends implementing comprehensive educational programs, strengthening institutional cybersecurity, promoting positive peer influence, enhancing collaboration with law enforcement, and integrating ethical training into the curriculum. These efforts will foster a safe and responsible digital environment within higher learning institutions, protecting students from cybercrime risks and promoting ethical digital citizenship.
Combining GAN with reverse correlation to construct personalized facial expressions

Recent deep-learning techniques have made it possible to manipulate facial expressions in digital photographs or videos, however, these techniques still lack fine and personalized ways to control their creation. Moreover, current technologies are highly dependent on large labeled databases, which limits the range and complexity of expressions that can be modeled. Thus, these technologies cannot deal with non-basic emotions. In this paper, we propose a novel interdisciplinary approach combining the Generative Adversarial Network (GAN) with a technique inspired by cognitive sciences, psychophysical reverse correlation. Reverse correlation is a data-driven method able to extract an observer's 'mental representation' of what a given facial expression should look like. Our approach can generate 1) personalized facial expression prototypes, 2) of basic emotions, and non-basic emotions that are not available in existing databases, and 3) without the need for expertise. Personalized prototypes obtained with reverse correlation can then be applied to manipulate facial expressions. In addition, our system challenges the universality of facial expression prototypes by proposing the concepts of dominant and complementary action units to describe facial expression prototypes. The evaluations we conducted on a limited number of emotions validate the effectiveness of our proposed method. The code is available at https://github.com/yansen0508/Mental-Deep-Reverse-Engineering.
Over-the-Air Computation Aided Federated Learning with the Aggregation of Normalized Gradient

Over-the-air computation is a communication-efficient solution for federated learning (FL). In such a system, iterative procedure is performed: Local gradient of private loss function is updated, amplified and then transmitted by every mobile device; the server receives the aggregated gradient all-at-once, generates and then broadcasts updated model parameters to every mobile device. In terms of amplification factor selection, most related works suppose the local gradient's maximal norm always happens although it actually fluctuates over iterations, which may degrade convergence performance. To circumvent this problem, we propose to turn local gradient to be normalized one before amplifying it. Under our proposed method, when the loss function is smooth, we prove our proposed method can converge to stationary point at sub-linear rate. In case of smooth and strongly convex loss function, we prove our proposed method can achieve minimal training loss at linear rate with any small positive tolerance. Moreover, a tradeoff between convergence rate and the tolerance is discovered. To speedup convergence, problems optimizing system parameters are also formulated for above two cases. Although being non-convex, optimal solution with polynomial complexity of the formulated problems are derived. Experimental results show our proposed method can outperform benchmark methods on convergence performance.
A comprehensive study of spike and slab shrinkage priors for structurally sparse Bayesian neural networks

Network complexity and computational efficiency have become increasingly significant aspects of deep learning. Sparse deep learning addresses these challenges by recovering a sparse representation of the underlying target function by reducing heavily over-parameterized deep neural networks. Specifically, deep neural architectures compressed via structured sparsity (e.g. node sparsity) provide low latency inference, higher data throughput, and reduced energy consumption. In this paper, we explore two well-established shrinkage techniques, Lasso and Horseshoe, for model compression in Bayesian neural networks. To this end, we propose structurally sparse Bayesian neural networks which systematically prune excessive nodes with (i) Spike-and-Slab Group Lasso (SS-GL), and (ii) Spike-and-Slab Group Horseshoe (SS-GHS) priors, and develop computationally tractable variational inference including continuous relaxation of Bernoulli variables. We establish the contraction rates of the variational posterior of our proposed models as a function of the network topology, layer-wise node cardinalities, and bounds on the network weights. We empirically demonstrate the competitive performance of our models compared to the baseline models in prediction accuracy, model compression, and inference latency.
Efficient collision avoidance for autonomous vehicles in polygonal domains

This research focuses on trajectory planning problems for autonomous vehicles utilizing numerical optimal control techniques. The study reformulates the constrained optimization problem into a nonlinear programming problem, incorporating explicit collision avoidance constraints. We present three novel, exact formulations to describe collision constraints. The first formulation is derived from a proposition concerning the separation of a point and a convex set. We prove the separating proposition through De Morgan's laws. Then, leveraging the hyperplane separation theorem we propose two efficient reformulations. Compared with the existing dual formulations and the first formulation, they significantly reduce the number of auxiliary variables to be optimized and inequality constraints within the nonlinear programming problem. Finally, the efficacy of the proposed formulations is demonstrated in the context of typical autonomous parking scenarios compared with state of the art. For generality, we design three initial guesses to assess the computational effort required for convergence to solutions when using the different collision formulations. The results illustrate that the scheme employing De Morgan's laws performs equally well with those utilizing dual formulations, while the other two schemes based on hyperplane separation theorem exhibit the added benefit of requiring lower computational resources.
Connected components of the topological surgery graph of a unicellular collection

A unicellular collection on a surface is a collection of curves whose complement is a single disk. There is a natural surgery operation on unicellular collections, endowing the set of such with a graph structure where the edge relation is given by surgery. Here we determine the connected components of this graph, showing that they are enumerated by a certain homological "surgery invariant". Our approach is group-theoretic and proceeds by understanding the action of the mapping class group on unicellular collections. In the course of our arguments, we determine simple generating sets for the stabilizer in the mapping class group of a mod-$2$ homology class, which may be of independent interest.