Reviewerly/exHarmony huggingface dataset:
CONDITIONS ON FORMING UNIVERSAL SYMBOLIC LEARNING ACTIVITIES IN ELEMENTARY SCHOOL STUDENTS DURING CONSTRUCTION AND PERFORMANCE OF MULTI-PURPOSE CLASS ASSIGNMENTS

Рассматривается проблема формирования у младших школьников метапредметных результатов, в частности универсального учебного действия моделирования, являющегося в обновленном Стандарте начального общего образования системообразующим для всех метапредметных результатов. Дана характеристика знаково-символических умений, формируемых у младших школьников. Приведены элементы учебного содержания, подлежащего моделированию в начальной школе (понятия, действия, процессы, учебные задачи), описана специфика работы по их моделированию в практической деятельности педагога. Выделены содержательные и организационно-технологические условия, при которых формирование у младших школьников знаково-символических универсальных учебных действий будет наиболее эффективно. The problem under review is formation of metadisciplinary results in elementary school students, most notably universal learning activity of modeling, which is considered by the renewed Federal Educational Standard for the elementary general education to be the basis for all metadisciplinary results. The symbolic skills of elementary school students are given an assessment. The reference is provided for the elements of the educational subjects for elementary school (concepts, actions, processes, teaching objectives, complete assignments), as well as for their practical application by the elementary school teacher. The formation of symbolic universal learning activities in the elementary school students, as well as the action of modeling, is to be performed during the completion of the multipurpose educational assignments, which have the increased didactic and methodical potential with metadisciplinary and subject-specific components. Performance of such learning activities by elementary school students results in discipline-related results, but also will form the universal learning activities of various types. Because the symbolic activities serve as a framework for all the universal learning activities, the assignments that pertain to the modeling activity are thus far the most impactful in the didactic sense, as their performance by the elementary school students trains the ability to plan further activities, perform them according to that plan, as well as the ability to perform all the types of logical universal learning activities. Inclusion of additional activities (testing, appraisal, communicative) will also promote formation of a broad spectrum of multidisciplinary results. The specification is provided for the organizational, technical and subject-related conditions that boost efficiency of the formation of the universal learning activities in the elementary school students.
Topic modeling and sentiment analysis about Mandalika on social media using the latent Dirichlet allocation method

The rapid and widespread dissemination of information currently affects the tourism sector. One tourist area that is quite widely discussed is the Mandalika Circuit. Twitter is one platform that provides comments related to the Mandalika Circuit. The amount of information related to the Mandalika Circuit is currently not being utilized properly by managers (government or private). It causes many topics related to the Mandalika Circuit that are currently trending, and public sentiment regarding the Mandalika Circuit is unknown to the government or private sector. Ignorance can result in delays in decision making which can harm the manager. To overcome this problem, research on sentiment analysis and topic modeling related to the Mandalika Circuit was carried out. The sentiment analysis method used is SVM and for modeling using LDA. Based on the results of the sentiment analysis, 1500 tweets were obtained before doing the pre-processing process, thus getting a dataset of 500 tweets divided into 398 positive and 102 negative tweets. So it can be concluded that more Twitter users give positive than negative responses to the Mandalika Circuit. The test results show that the SVM algorithm can classify sentiment toward the Mandalika Circuit well, as indicated by the measurement of the performance of the SVM algorithm, namely 87% accuracy, 77% precision, 84.81% recall, and 98.52% specificity. These results also show that the F1 Score compares the average precision and recall, which is weighted at 80.72%.
Review methods for clock skew measurement

Clock skew is the deviation of the clock from the true time, which makes it an important role in time information. Clock skew is unavoidable and causes each clock to run at a different speed, so there is a very slight difference between them, but it can still be observed properly. The known properties of clock skew make it potential research for many experts, such as Paxson, Aoki, and Huang. To produce a more accurate clock skew measurement, this study uses the ant colony optimization method by adopting the behavior of an ant colony in searching for food by choosing the path with the shortest route, which will become the cluster offset as a material for measuring clock skew. Ant colony optimization method has the most potential to be adapted in clock skew measurement because the cluster offset is not affected by the upper and the bottom outliers to produce an accurate clock skew measurement.
ANALYSIS OF THE PROBLEMS OF FORMING UNIVERSITY STUDENTS’ MOTIVATION IN THE MODERN HIGHER EDUCATION SYSTEM

Reducing the motivational activity of university students is a rather important factor hindering efficiency of education. In the article, the authors investigate the reasons that prevent the formation of a stable motivation among students by conducting research. The data obtained indicate the presence of initial motivation to study at a university, but in the course of training, most of the respondents lose it. As a result of the analysis the authors come to the conclusion that in order to form a stable students’ motivation, a set of measures is needed that affect all its main factors.
FORMATION OF FLEXIBLE SKILLS AMONG STUDENTS THROUGH PROJECT ACTIVITIES

The article describes the methodology of project activities for the development of flexible skills. The authors of the article point out the advantages of the method and give an example of its application. The described tool is proposed to be used in the educational process for the preparation of competitive university graduates.
Comparison of cognitive strength and weaknesses between visually impaired children and non-visually impaired children

Visually impaired children experience limitation in learning and identifying the world. There has yet to be an intelligence measuring instrument tailor made to accommodate their limitations. Therefore, this study aims explore strengths and weaknesses of visually impaired children compared to non-visually impaired children in standard intelligence test as a pilot study for constructing intelligence test that is tailor made for visually impaired children. This research is a quantitative approach using WISC-R as the research instrumenrs. The data was analyzed using Mann-Whitney U Test. This study found a significant difficulty experienced by visually impaired children in performance subtest. Further, no significant difference in verbal IQ was found between visually impaired children and non-visually impaired children. The results of this study are expected to be the basis for developing intelligence measuring tools for visually impaired children in the future.
Dialogic Reading to Promote the Underprivileged Pre-School Children's Expressive Language Ability

Background: &#x0D; Children from low socioeconomic backgrounds in Indonesia have been facing challenges in terms of their literacy and language development. One of the possible reasons is that they are not used to receiving meaningful early reading interventions such as shared reading during their pre-school attendance. This phenomenon has brought to light the urgency of having an early intervention, which can accommodate the very diverse linguistic and cultural context of Indonesia- a multilingual and multicultural country.&#x0D; Methodology: &#x0D; This study employed an explanatory sequential mixed-method research design. The first phase was conducted in a quantitative one-group pre-experiment with pre-and post-test design. The second phase of this research was carried out in a qualitative case study through classroom observation and informal interviews with the teacher and the children.&#x0D; Findings: &#x0D; The findings of MLU calculation showed that for the pre-test, the mean score was 2.35, the median was 2.20 and the standard deviation was 0.53. Meanwhile, for the post-test, the mean score was 3.72, the median was 3.18 and the standard deviation was 1.38. The qualitative phase explored two main aspects, namely the implementation of dialogic reading activity by the teacher and the teacher as well as childrenâ€™s opinions regarding the dialogic reading activity.&#x0D; Conclusion: &#x0D; This current study has offered an insight that dialogic reading activity could be well implemented by the teacher in a typical Indonesian pre-school setting. The dialogic reading activity was also found to contribute significantly to the development of childrenâ€™s expressive language ability.&#x0D; Originality: &#x0D; The findings of this study have indicated dialogic reading potentials in terms of promoting childrenâ€™s language development and just as importantly, sparking childrenâ€™s joy of reading since their early years of formal education. Therefore, it is suggested that early childhood educators and parents work hand in hand to incorporate dialogic reading activity into their daily literacy practices at schools as well as at home.
Clipping-Based Post Training 8-Bit Quantization of Convolution Neural Networks for Object Detection

Fueled by the development of deep neural networks, breakthroughs have been achieved in plenty of computer vision problems, such as image classification, segmentation, and object detection. These models usually have handers and millions of parameters, which makes them both computational and memory expensive. Motivated by this, this paper proposes a post-training quantization method based on the clipping operation for neural network compression. By quantizing parameters of a model to 8-bit using our proposed methods, its memory consumption is reduced, its computational speed is increased, and its performance is maintained. This method exploits the clipping operation during training so that it saves a large computational cost during quantization. After training, this method quantizes the parameters to 8-bit based on the clipping value. In addition, a fully connected layer compression is conducted using singular value decomposition (SVD), and a novel loss function term is leveraged to further diminish the performance drop caused by quantization. The proposed method is validated on two widely used models, Yolo V3 and Faster R-CNN, for object detection on the PASCAL VOC, COCO, and ImageNet datasets. Performances show it effectively reduces the storage consumption at 18.84% and accelerates the model at 381%, meanwhile avoiding the performance drop (drop &lt; 0.02% in VOC).
Extracting Factual Information about the Pandemic from Open Internet Sources

A large number of different source data is needed for multi-agent models of the spread of infectious diseases. Most of them are not directly accessible. Therefore, one of the key problems to design such models is the development of tools for obtaining data from various sources. This article presents approaches that allow to extract the values of the parameters of the functioning of the simulated society and statistical data on the development of the pandemic from text messages published in the Internet. The proposed method and software implementation provide intelligent search of open source information in the Internet and process of unstructured data. The data collected this way used to set up parameters of mathematical model, which provides ability to study various scenarios and predict progress of the epidemic in concrete regions. The emphasis of the proposed approach is placed on two main technologies. The first is the use of regular expressions. The second is analysis using machine learning methods. The use of the regular expression method allows for high-speed text processing, but its applicability is limited by a strong dependence on the context. Machine learning allows to adapt the information context of the message, but at the same time there is a relatively large amount of time spent on analysis. To improve the accuracy of the analysis and to level the shortcomings of each of these approaches, ways of combining these technologies are proposed. The article presents the obtained results of optimization of algorithms for obtaining the necessary data.
Novel Transfer Learning Attitude for Automatic Video Captioning Using Deep Learning Models

Objectives: To generate the captions for the videos with less time complexity and high accuracy and also to create captions for each input video frame with particular timestamps.It will be utilized in the crime branch and hearingimpaired people will learn about the happenings of the video fruitfully.Methods: The proposed approach experiments with Transfer learning techniques.Modified Inception v3 and Resnet 50 networks are designed to compare the results.The standard MSVD Dataset is utilized to demonstrate the architectures.The performances are compared with the standard performance metrics.Findings: The inception v3 model works better than the Resnet 50 architecture for video captioning tasks.It provides the best accuracy at 99.83% with captions for the given input videos than Resnet 50 model.The MSVD dataset is more suitable for the demonstration of the video captioning task.Novelty:The two proposed models are modified based on the working of the video captioning tasks.The aggregation of some layers boosts the performance of the models more than ordinary models.
Algebraic properties of HTC-identifiable graphs

In this paper, we explore some algebraic properties of linear structural equation modelsthat can be represented by an HTC-identifiable graph. In particular, we prove that all mixedgraphs are HTC-identifiable if and only if all the regression coefficients can be recovered fromthe covariance matrix using straightforward linear algebra operations. We also find a set ofpolynomials that generates the ideal that encompasses all the equality constraints of the modelon the cone of positive definite matrices. We further prove that this set of polynomials are theminimal generators of said ideal for a subset of HTC-identifiable graphs.
Sharding-Based Proof-of-Stake Blockchain Protocols: Key Components &amp;amp; Probabilistic Security Analysis

Blockchain technology has been gaining great interest from a variety of sectors including healthcare, supply chain, and cryptocurrencies. However, Blockchain suffers from its limited ability to scale (i.e. low throughput and high latency). Several solutions have been proposed to tackle this. In particular, sharding proved that it is one of the most promising solutions to Blockchain’s scalability issue. Sharding can be divided into two major categories: (1) Sharding-based Proof-of-Work (PoW) Blockchain protocols, and (2) Sharding-based Proof-of-Stake (PoS) Blockchain protocols. The two categories achieve good performances (i.e. good throughput with a reasonable latency), but raise security issues. This article focuses on the second category. In this paper, we start by introducing the key components of sharding-based PoS Blockchain protocols. Then, we briefly introduce two consensus mechanisms, namely PoS and practical Byzantine Fault Tolerance (pBFT), and discuss their use and limitations in the context of sharding-based Blockchain protocols. Next, we provide a probabilistic model to analyze the security of these protocols. More specifically, we compute the probability of committing a faulty block and measure the security by computing the number of years to fail. Finally, we evaluate the effectiveness of the proposed model via numerical analysis.
J -Wmyh Mobile Game-Based Learning Application

Nowadays, game-based education has been developed to attract students' interest.Modern Jawi script's spelling, based on the "Daftar Kata Bahasa Melayu (DKBM): Rumi-Sebutan-Jawi" dictionary, uses the same approach.The current platform for Jawi education lacks sufficient gamification elements to attract the younger generation.Therefore, this research aims to apply gamification elements to develop a mobile-based game-based learning application of Jawi: Warisan Melayu Yang Hilang (J-WMYH) through a digital platform.This mobile gamebased learning would target the younger generation to pique their interest in learning modern Jawi.This application will help the youth to practice reading and recognizing Modern Jawi script.The methodology adopted is Rapid Application Development (RAD) which consists of four processes: i) Analysis and Quick Design, ii) prototype cycle, iii) Testing and iv) Deployment.A few gamification elements were embedded, and mobile game-based learning was developed using ShoeBox and Flutter.Based on the functionality test, we found that J-WMYH can function as targeted and suitable for enhancing knowledge.
TEKNOLOGI AUGMENTED REALITY UNTUK ALAT PERAGA PEMBELAJARAN ANAK

Augmented technology is generally only used for games and here I am trying to research an application to recognize letters and numbers based on augmented reality. Where children can learn to recognize letters and numbers with 3D screen animations. This technology combines the real world and the virtual world. To overcome this problem, the author makes an application of augmented reality technology for android-based teaching aids for children. This study aims to make it easier for children to recognize letters and numbers with an attractive and easy-to-use animated display. The data collection process in designing this system uses a marker-based tracking method. The result of this research is an application that implements augmented reality technology using a marker-based tracking method which is designed to help students get information and education about the introduction of flat shapes in elementary schools.
Kesulitan Belajar Peserta Didik di SD Muhammadiyah 1 Marapalam Padang

This research is motivated by students who have not been able to overcome learning difficulties at SD Muhammadiyah 1 Marapalam Padang. The purpose of this study is to describe the difficulties in learning to read, write and count.This research use desciptive qualitative approach. The instruments used in the research are observation, interviews and documentation of the cases seen. The technique used in data processing is through data reduction, data presentation and drawing conclusions. Techniques for data validity, trustworthiness, transferability, reliability. The results of this study indicate that students who have learning difficulties are: 1. Students' learning difficulties in reading occur because students do not repeat lessons at home such as reading, students experience poor vision and hearing. 2 Students' learning difficulties in writing occur because students do not practice writing at home and have blurred vision and 3. Students' learning difficulties in counting occur because of doubts in recognizing mathematical symbols and lack of practice at home. Based on the results of the study, it is recommended for parents to pay more attention to students at home so that learning difficulties experienced by students can be overcome.
Reflexes of the pandemic on personal physical training in southern Brazil

Objective: to analyze the impact of the COVID-19 pandemic on the routine of Personal Trainers (PTs) in southern Brazil. Methods: by invitation on social networks, 79 PTs (38 women; 41 men; aged 20 to 69 years) answered a questionnaire available on Google Forms during the months of April and May/2020, with questions about characterization, professional performance and physical exercise routine. Results: There was a decrease in clients both for less experienced PTs (92%) and for those with longer experience (68%); the most used digital technology used for training was WhatsApp (81%); most of the PTs (79%) believe that the intensity of virtual training is much lower, but that the method will continue to be used after the pandemic period. Conclusion: social isolation imposed by the pandemic impacted in a negative manner the work of PTs, reducing clients, forcing the use of remote methodologies and altering the PTs' physical exercise routine.
Corporate Culture in the Educational Environment of the University

educational organization should be based on the interaction of all subjects of the educational process. It is known that an important role in the formation of a general, socio-psychological climate in the process of socio-professional adaptation of a person is influenced by pedagogical work at the university, which solves a number of fundamental and important tasks, such as the formation of a civil position of a person based on the spiritual and moral values of students who have positive motivation for educational activities. In addition, corporate culture is the most important component of the culture of human interaction in professional activities. The author analyzes the study on the example of the “Dorzhi Banzarov Buryat State University” Pedagogical Institute in Ulan-Ude. The experiment involved 64 students with a bachelor’s degree, from I–IV full-time courses, studying in the areas of training “Psychological and pedagogical education” and “Pedagogical education”. This paper substantiates and presents the diagnostics of the study of students’ corporate culture. Among the research methods, the following were used: the test “Self-assessment of the parameters of the image of a business person” (an adapted version of the method of M. Spillane), the test of Ch. Sishora to determine the index of group cohesion, a questionnaire on the level of development of reflexivity (A. V. Karpov). The results based on the conducted surveys of respondents, which allowed us to determine the process of forming the corporate culture of students in the educational environment of the university are described by the author. The data obtained in this way have been confirmed and formed the basis for future studies of the process of forming a student’s corporate culture in the educational environment of the university. Keywords: students, socio-psychological climate, cohesion, communication, educational process
Joint Optimization–Encryption Model Based on Auto Encoder Neural Network, Variable-Length Dynamic S-Box and New Stream Encryption

The openness of the Internet makes information transmission prone to the risk of illegal eavesdropping, and data security and user privacy protection have become one of the key research hotspots. Aiming to solve the problem that a single encryption method cannot provide comprehensive security guarantees and the traditional one-time pad encryption method consumes a large amount of secure channel resource, this paper innovatively proposes a variable-length dynamic S-box and a cross-mapping sequence-based new type of stream encryption, and an improved method of synchronizing keys during a one-time pad transmission. On this basis, this paper innovatively proposes a joint optimization–encryption model based on the auto encoder neural network, variable-length dynamic S-box and new stream encryption. Finally, taking the optical fiber transmission as an example, the simulation results show that the joint optimization–encryption model proposed in this paper can save security channel resources and effectively resist common security attacks in the process of high-speed information transmission.