Reviewerly/exHarmony huggingface dataset:
The Effects of Physical Activity-oriented Traditional Play on Prosocial Behavior of 4-year-old Children

본 연구는 신체활동 중심의 전통놀이가 만 4세 유아의 친사회적 행동에 미치는 효과를 검증하고 이를 교육 현장에 활용하는 데 목적이 있다. 연구 대상은 P시에 위치한 병설 유치원 두 곳에 재원 중인 만 4세 유아 36명이며 실험집단(남아 9명, 여아 9명)과 통제집단(남아 9명, 여아 9명)으로 선정하였다. 실험집단의 유아들에게는 신체활동 중심의 전통놀이 활동 13가지를 5주 동안 2∼3회씩 매회 40분간 실시하였고, 통제집단 유아들에게는 일상생활과 관련된 신체활동을 적용하였다. 유아의 친사회적 행동 변화을 알아보기 위해 활동 전과 후에 교사용 유아 친사회적 행동평가 검사를 실시한 후 SPSS 24.0으로 독립표본 t검증, 공변량분석(ANCOVA)을 실시하였다. 연구 결과, 신체활동 중심의 전통놀이는 유아들의 친사회적 행동을 증진시키는 것으로 나타났다. 또한, 전통놀이를 경험한 실험집단의 유아들은 친사회적 행동의 하위영역인 지도성, 도움주기, 의사소통, 주도적 배려, 접근 시도하기, 나누기, 감정이입 및 조절에서도 통제집단의 유아들에 비해 유의미하게 높은 수준을 보이는 것으로 나타났다. 이러한 연구 결과는 유아의 친사회적 행동을 증진시키기 위한 프로그램 개발에 있어 신체활동 중심의 전통놀이를 고려할 필요가 있음을 시사한다.This study aimed to examine the effects of physical activity-oriented traditional play on young children s prosocial behavior. The subjects were 36 four-year-old children from two kindergartens located in P city and were divided into an experimental group (N=18) and a control group (N=18). Only the experimental group participated in the 13 types of physical activity-oriented traditional play 2 to 3 times for five weeks for 40 minutes each time. Teachers of two groups evaluated children s prosocial behavior before and after the experiment using the Prosocial Behavior Scale for Young Children (PBSYC). The data was analyzed by independent t-test and ANCOVA using SPSS 24.0. The result showed that the experimental group showed higher levels of prosocial behavior compared with the control group. Children in the experimental group also showed higher levels in all the subscales of prosocial behavior, including leadership, being helpful, communication, concern, proximity, sharing, and empathy, than the control group children. These findings suggest that it is necessary to consider physical activity-oriented traditional play in developing programs to promote children s prosocial behavior.
Graph Neural Networks in Computer Vision

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Sound and Video examples from this issue 26(3)

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Custom Object Tracking

The chapter explains how to track moving and static objects in real time using downscaled picture details through measuring the period averaging background scene.
Interactions

An interactive visualization allows additional information to be presented when a user triggers actions through the mouse or keyboard. Roassal proposes a number of pluggable and extensible interactions, presented in this chapter.
Design and implementation of the algorithm for gender and face classification of face images based on convolutional neural network

Convolutional Neural Network (CNN) is a feedforward neural network suitable for large-scale image processing. CNN has been largely developed these years, it is primarily used to identify displacement, and it uses training to extract features from raw data to gain learning and judgment. Age and gender classification of face images is a kind of biometric technology that identifies people by extracting their biological features. This paper combines the convolutional neural network with the classification and recognition algorithms for the gender and age of the human face, uses the Adience dataset to train the network so as to realize the function of judging gender and estimating age on the Internet. With achieved AlexNet architecture using TensorFlow, the CNN initially completed the expected goals, and analyzed and evaluated the factors that affect network performance, and discussed the improvement methods. Using the face database to train the convolutional neural network, the network finally grasps the ability of face recognition of gender and age. The main problems to be solved are: the training of convolutional neural network data sets and the adjustment of parameters; the extraction and processing of information on face images that need to be identified; the application of convolutional neural networks to face recognition and age estimation. Specifically, it includes: constructing a reasonable convolutional neural network architecture; correctly inputting data and outputting corresponding results; processing and extracting effective information of the pictures.
Heart Smart

Innovative approaches are warranted to educate the public about the relationship between behavior and cardiovascular health as well as strategies to improve health. It was against the backdrop that the Heart Smart exhibition at the Miami Science Museum was developed. Heart Smart cards are dispensed only after visitors anonymously enter their age, gender, and ethnicity and indicate whether or not they consent to have their data used for research purposes. Heart Smart cards operate each of the interactive components independent of visitors’ involvement with the research project. The Heart Smart experience clearly illustrates that museum visitors are interested in research participation. A distinct advantage of the science Museum setting is that it allows researchers access to a large diverse pool of potential research participants. Such access would be impossible in conventional university-based research settings. The Heart Smart experience suggests that health researchers need to devise imaginative strategies to promote good heart health and improve the wellbeing of the community.
Data Acquisition

In the previous chapter, you learned the basics of using two Pandas data structures, namely, the series and the dataframe.
Effects of Home Training using Video Contents of Obese Middle-aged Women on Stress Enzyme, Obesity and Physiological Characteristics

The purpose of this study was to investigate the effects of stress enzymes, obesity, and physiological characteristics changes in obese middle-aged women by using video content exercise methods. Exercise using video content was 50 minutes a day for a total of 8 weeks, and the following conclusions were obtained. There was a significant difference between the groups in α-amylase, a stress enzyme, and there was an interaction effect between the measurement period × the group. In addition, as the result of the decrease in body weight in the degree of obesity, there was an interaction effect between the measurement period × the group. The body fat percentage showed a significant difference according to the measurement period, and there was an interaction effect between the measurement period × the group. There was no significant effect on BMI. In the change of physiological characteristics, TC showed an interaction effect between measurement period × group, and TG showed no significant effect. Therefore, fitness bag exercise using YouTube reduced stress enzymes in obese middle-aged women, improved obesity and showed positive changes in physiological characteristics. Even if middle-aged obese women cannot participate in the exercise center due to the recent corona virus, if their will and active participation are supported, they will be able to show the effect of exercise at home.
Data Types

In the previous chapter a lot of Java code was written, but when designing the class only the simplest data types were used: a few numeric ones and texts. In the JDK a lot of data types are declared for a multitude of purposes: for modelling calendar dates; for representing multiple types of numerics; and for manipulating texts, collections, files, database connections, and so on. Aside from JDK, there are libraries crated by other parties that provide even more functionality. The data types provided by the JDK are fundamental types, the bricks every Java application is built from. Depending on the type of application you are building, you might not need all of them. For example, I’ve never had the occasion to use the java.util.logging.Logger class. Most applications I have worked on were already set up by a different team when I came along, and they were using external libraries like Log4j, Logback, or logging abstractions like Slf4j.
Asymmetric anaphoric dependencies determine available readings for VP-ellipsis

Dalrymple et al. (1991) was a landmark contribution to the theory of ellipsis. In addition to providing an elegant semantic account of the interaction between ellipsis and quantification, it demonstrates how strict and sloppy readings can be generated without having to posit an ambiguity between bound and free pronouns in antecedent clauses. A weakness of the theory, however, is its lack of representational sensitivity to choice of referential form: the fact that pronouns and names are represented the same way causes the account to overgenerate sloppy readings in some cases. In this chapter, Kehler discusses a set of examples that provide adequacy criteria for theories of ellipsis with respect to their treatment of anaphoric dependencies. These cases reveal that a more generalized notion of dependency needs to be represented beyond the more limited notion captured by syntactic binding relations, including dependencies that cross clause boundaries and that involve eventualities. A provisional account is offered that captures these cases.
Policy Learning for Visually Conditioned Tactile Manipulation

Recent work on robot learning with visual observations has shown great success in solving many manipulation tasks. While visual observations contain rich information about the environment and the robot, they can be unreliable in the presence of visual noise or occlusions. In these cases, we can leverage tactile observations generated by the interaction between the robot and the environment. In this paper, we propose a framework for learning manipulation policies that fuse visual and tactile feedback. The control problems considered in this work are to localize a gripper with respect to the environment image and navigate to desired states. Our method uses a learned Bayes filter to estimate the state of a gripper by conditioning the tactile observations on the environment image. We use deep reinforcement learning for solving the localization and navigation problems provided with the belief of the gripper’s state and the environment image. We compare our method against two baselines where the agent uses tactile observation directly with a recurrent neural network or uses a point estimate of the state instead of the full belief state. We also transfer the policies to the real world and validate them on a physical robot.
Getting Started with NumPy

In the previous chapter, you learned the basics of the Python programming language and the scientific Python ecosystem. You also learned how to run simple Python programs in interactive web-based notebooks with Jupyter. We will continue using Jupyter Notebook for the majority of demonstrations in the rest of the chapters in the book.
Using Agile for Infrastructure Operations

In this chapter, we will detail a step-by-step approach for adopting agile for infrastructure operations in an enterprise. The topics that will be covered in this chapter are as follows:
3. Teacher Practices of Application of Learning Analytics as a Metacognitive Tool. Case Study Research

The research described in this book searches for the answers on how learners learn in todays open and networked learning environments and how learners, educators, institutions, and researchers can best support this process. There is sufficient data available on virtual learning environments, provided by learning analytics, on student and teacher behaviour and performance, but there is no common practice among teachers in higher education for using this data to improve the learning and teaching process. Learning analytics and data may inform and improve open and online learning from the point of view of teacher and learner awareness about their behaviour and their learning and teaching methods. The idea of describing learning analytics as a metacognitive tool, suggesting a development of metacognitive decision-making skills in teacher education, and focusing on learning design in higher education by using data from learning analytics served as the main focus of this research. The aim of the research was to create the model of application of learning analytics method as a metacognitive tool to enhance student success. The aim of the research was reached through theoretical and empirical objectives, namely: describing the learning analytics method as a metacognitive tool; revealing teacher metacognitive practices
Estimation of Abnormal Event Occurrence Time Based on Upstream and Downstream Multi-Source Data

Following the occurrence of abnormal events on expressways, the estimation of time is critical for the reasonable control of traffic. Due to the influence of the detection cycle of the detection equipment and the delay of the detection algorithm, the detection time of many events has a certain delay relative to real occurrence time. This paper estimates the occurrence time of abnormal events by combining microwave detector data, toll data and manually recorded data. In this paper, the travel time of the road section based on toll data is estimated. Then, the event detection algorithm for the large detection cycle is designed to get the detection time closer to the real occurrence time. Finally, the detection time is modified by travel time. The experimental results show that the time estimation method based on travel time correction is reasonable and effective.
DETERMINING THE CONTENT OF TEACHING FUTURE COMPUTER SCIENCE TEACHERS OBJECT-ORIENTED PROGRAMMING USING INFOGRAPHICS

The article considers the issue of teaching object-oriented programming courses for future teachers of computer science and the content of the course. The authors substantiate the role and importance of teaching object-oriented programming in the training of future teachers of computer science. The main idea of ​​this work is the use of infographics in the teaching of object-oriented programming. As a result of the analysis of foreign experience, literary sources, the authors identified the main problems of teaching object-oriented programming, as well as considered the work of various scientists who offer different methods and techniques of teaching OOP.
Leap for quantum advantage in optical and superconducting systems

Two different quantum computers – one using light and the other using superconducting circuits – have performed calculations beyond the capability of conventional computers.
Introduction

Computers are a formidable extension of the human brain: a computer liberates us from performing boring and repetitive tasks. Data visualization is a wonderful field where computers nicely complement what the brain excels at.
DTW-based Motion Matching System in Consumer Shopping Interest Analysis

This work proposes a Dynamic Time Warping (DTW)-based motion matching system in consumer shopping interest analysis. The inertial measurement unit (IMU) is utilized to record the movement of customers’ hands and products, and the classification algorithm based on the sliding window algorithm is implemented to make a connection between products and customers. Furthermore, this work achieves high accuracy in motion matching performance and displays the shopping list of the proposed system wearer's interest.
The influence of information culture on the formation of the image of a superhero of the XXI century

The purpose of the article is to investigate the influence of information culture on the formation of a superhero image of the XXI century. The research methodology includes such methods as analysis, synthesis, and systems approach, which makes it possible to trace and determine the vector of influence of information culture and digital processes taking place in connection with the informatization of society, on the transformation of the image of a superhero. The scientific novelty lies in the fact that virtual and augmented reality in the popularization of Ukrainian superheroes acts as a phenomenon that is considered not only as a result of interaction with people but also as an artifact of the new information era; the peculiarities of becoming a national hero as the basis of self-identification of modern Ukrainian society in the context of the specifics of information and communication technologies, are analyzed. Conclusions. Information culture is considered as a sphere of culture associated with the functioning of information in society and the formation of information qualities of a person. However, the phenomenon of the influence of information culture on the formation of the hero's image through the basis of society's self-identification in the modern dimension still remains unexplored. On a personal level, a person is surrounded by images, contradictory and disproportionate, and begins to simply consume the symbols and images of newly created superheroes. The structure of information culture includes a worldview component that provides motivation for information training of the individual; knowledge of the information environment, the laws of its operation, the ability to navigate in information flows. The information level of modern man is determined by his information culture, and the information culture of the individual, as a culture in general, reflects the active creative activity of man, and, accordingly, the development of man himself as a subject of this activity.
Sandbox

The Sandbox is a demarcated, carefully cordoned off space which allows consumers to test and use your APIs to get a feel for how they function. Of all the technical challenges, achievements, and breakthroughs over the lifespan of our API Marketplace, it was a revamp of the humble Sandbox which proved to be the tipping point for me to write this book. Our initial Sandbox strategy was relatively simple and catered for a specific spectrum of API products. As the platform grew, matured, and evolved, this construct and approach remained unchanged. In much the same way that a Jitterbug or Charleston step may function in today’s dance era, it just seemed out of place. The team had recognized for some time that the approach needed a serious overhaul, but the priority was always bumped down in favor of other “more important” deliverables.
Comparison of Structure Reduction, Pruning, and Knowledge Distillation for Lightning of Deep Learning

We compare three approaches of structure reduction, pruning, and knowledge distillation for lightning of a deep learning network. Structure reduction eliminates a set of layers of the model, but pruning deletes filters within a layer. Knowledge distillation effectively learns a small student model from a large teacher model using KL Divergence. Therefore, it has a similar effect of reduction of the model. The above three methods for lightning are rarely compared to each other in terms of performance. To compare these approaches for network reduction problem, we investigate the accuracy and flops of the methods on CIFAR10 and CIFAR100 data for ResNet models. A systematic analysis for the fundamental orientations and differences of each method is supplemented.
Minimizing Overloads of Critical Tasks Using Machine Learning in CPS by Extending Resources

With all the growing variety of solutions plus industries as well as nuclear, substance, aerospace, as well as auto sectors to come down with cyber-physical Systems (CPSs), methods remain now actuality seriously loaded. CPSs includes varied dangerous jobs that stand protection dangerous (1) that is high or perhaps non-protection crucial (2) that is low. For conventional job arranging, nearly almost on the current arranging algorithms offer terrible functionality for high criticality jobs, if the method suffers from overburden as well as doesn't present explicit splitting up with various criticality duties to make the most of utilizing cloud online resources. Below, a framework is proposed by us to plan the mixed criticality duties by examining the deadlines of theirs as well as delivery occasions that use the overall presentation of similar handling done by OpenMP (Open Multi-Processing). The suggested agenda presents a piece of ML-based estimate for a job unloading within the area of cloud. Furthermore, it clarifies to perform the nominated variety of low dangerous things within the area of cloud even though the extraordinary serious jobs are operated over the regional CPUs over the method clog. Consequently, the high criticality jobs fulfil almost all the deadlines of theirs and also the method accomplishes a tremendous enhancement within the general delivery period as well as much better throughput. Additionally, the investigational outcomes using OpenMP present the usefulness of utilizing the subdivided arranging during a worldwide arranging technique upon multiprocessor methods to accomplish the works isolation.
On the Translation of Chinese Ethnic Classics: Values, Problems and New Thinking

This commentary mainly points out the values and problems of the translation of Chinese ethnic classics by using the literature method. The conclusions are: Chinese ethnic classics are the essence and core of traditional Chinese culture, the translation and dissemination of Chinese ethnic classics is the impetus for inter-cultural communication, and even a kind of “literary diplomacy” and “cultural diplomacy,” which is the business card of the Chinese ethnic culture to the outside world. In view of the current problems such as low volume, poor quality in translated Chinese ethnic classics, and indirect-faithfulness in translation, this commentary with theoretical study makes some new thinking from the five aspects: translation talent, translation principle, communication method, communication effect, and sustainable research, which is expected to provide reference for the translation and dissemination of ethnic classics in the world.
Advanced Applications in Graph Neural Networks

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Collaborative Film Language Analysis in the Networked Information Era

This article explores new approaches to film analysis made possible through collaborations among film and media scholars, information scientists, and computer scientists. It examines in particular strategies for developing the field of digital film analysis through the creation of a film language ontology, improvements in machine learning in relation to film language, and academic crowdsourcing. It considers the role of a specific knowledge platform, Kinolab, in relation to more traditional forms of film analysis, contextualising the application of digital methodologies within the broader study of film language and challenges of film analysis.
Digital Entrepreneurship and Blockchain

Blockchain technology, originally the basis of the Bitcoin cryptocurrency, has received great attention from both academics and practitioners in the last decade. The consequent rise of interest in blockchain applications by different industries as well as public sector organizations has been complemented by questions and research on the impact of blockchain on organizations’ business models. Blockchain is also considered a source of innovation opportunities and challenges for entrepreneurs. Therefore, this chapter explores its potential for digital entrepreneurs, by first introducing the main elements making up the technology and then discussing eight companies that apply blockchain in different sectors, thus providing insights for new ventures. The chapter aims to give an essential understanding of blockchain’s advantages for digital entrepreneurs as well as insights that could inspire potential future applications of this technology for value creation and innovation in different sectors.