Reviewerly/exHarmony huggingface dataset:
Effects on mathematics achievement,Interest, and Mathematical Attitudes based on Small group cooperative learning by ability

Objectives The purpose of this study was to find ways for students to improve their overall mathematics achievement, interest, and mathematical attitude toward math learning through small group cooperative learning by ability. Methods The study was conducted on 58 students in 2 classes in the 2nd grade of 00 Humanities High School. OO High School is located in OO Metropolitan City. Two classes were selected based on the results of the midterm exam in the first semester of the first grade. Class 1 was divided into an experimental group and another class 1 was divided into a comparative group. From April 29 to July 9, 2022, 13 classes were conducted for about 2 months. The experimental group (33 students) was a class that was taught by cooperative learning of small groups by ability, and the comparative group (33 students) was a class that was taught based on traditional textbooks centered on explanatory expressions. Results Through this study, the following results were obtained. First, in this study, learning contents for each unit were set and activity papers were used for small group cooperative learning by ability. By applying this to the class, it was possible to improve mathematics achievement, interest, and mathematical attitude. Second, classes using small group cooperative learning by ability were more effective in mathematics achievement, interest, and mathematical attitude compared to traditional textbook-oriented classes centered on narrative for top, middle, and bottom students. Third, in classes using small group cooperative learning by ability, they were also interested in lower-level students excluded from general mathematics classes, and actively participated and improved the level of mathematics achievement. Conclusions In conclusion, the experimental group that used small group cooperative learning by ability had significant differences in mathematics achievement, interest, and mathematical attitude than the comparative group.
Analysis of Practical Arts(Technology &amp; Home economics) Curriculum of Elementary and Middle School in 2022 in China

Objectives The study was analyzing the Practical Arts(Technology &amp; Home economics) Curriculum of Elementary and Middle School in the revised national curriculum of China in 2022, hoping to get enlightenment from the Arts(Technology &amp; Home economics) education in China. Methods The content analysis of literature study method for this study was used. Results This paper analyzes the changes of Practical Arts(Technology &amp; Home economics) curriculum in China, the overall composition of the revised Practical Arts(Technology &amp; Home economics) curriculum documents of Elementary and Middle School in 2022 and various parts of the text. Finally, through the comparison of Practical Arts(Technology &amp; Home economics) Curriculum of Elementary and Middle School in 2022 between South Korea and China, the enlightenment is drawn. Conclusions First, The compilation and operation of Practical Arts(Technology &amp; Home economics) Curriculum of Elementary and Middle School in China is centered on the hierarchy, cohesion and coherence of its nature, goal and content system. Second, the goal of Practical Arts(Technology &amp; Home economics) Curriculum of Elementary and Middle School in China is to cultivate knowledge, skills and attitudes about labor(technology), and it also emphasizes starting from the professional and ideological levels. Thirdly, the content system of Practical Arts(Technology &amp; Home economics) Curriculum of Elementary and Middle School in China is “daily life labor”, “productive labor” and “service labor” based on Marx's labor theory of value. Fourth, the teaching and learning methods of Practical Arts (Technology and Home economics) Curriculum of Elementary and Middle School in China are based on experience activities called “Lao Dong Zhou” and labor projects. Fifthly, the evaluation of Practical Arts(Technology &amp; Home economics) Curriculum of Elementary and Middle School in China takes into account the development level of learners, and is carried out in grades (groups) around the core literacy of subject.
Children's Experiences in Augmented Reality (AR) Music Activities

Objectives This study aims to examine children’s experiences in augmented reality(AR) music activities and the values in early childhood education through exploring five-year-old children’s responses by AR music with smart device apps. Methods A total of 20 five-year-old children and a teacher are participated in this study. The researcher observed the participating children’s music activities twice a week for three months in the kindergarten. Data collection included recorded videos of children’s music activities, filed note for observation, interviews with teacher. The following findings were drawn by analyzing recorded materials and inductively categorizing the contents of collected materials. Results First, children showed curiosity in the process of experiencing augmented reality (AR) music and smart devices, and experienced augmented reality (AR) music with characters and sounds. Second, it was found that children experienced music with various senses and perceived it aesthetically through AR music; that is, they were meeting AR while simultaneously feeling music with sight, hearing, and body. Third, children were expanding into another world of convergence through music, connecting augmented reality with reality. Conclusions These results were able to explore the meaning of the experience when the child meets AR music. This study is to put its value in that it can be used as basic data to present desirable direction of education to young children living in the digital age.
Exploration of the University Students’ Educational Needs for the Competencies Required for the Project Based Learning

Objectives The purpose of this study was to understand the university students’ educational needs for the competencies required for the project based learning in order to provide implications for the teaching strategy. Methods To this end, a project performance competency test was administered to 120 university students in the metropolitan area. The Importance, performance, Borich index, and IPA matrix analysis were performed on the 49 items of the five competencies: creative problem solving, inquiry/research and analysis, project management, collaboration, presentation and report writing. Results The results were as follows. It was found that the performance of all items was lower than their importance. A total of 11 items were classified as ‘Concentrate here’ area, with high importance but low performance. These included 2 items in creative problem-solving competencies, 2 items in inquiry/research and analysis competencies, 1 item in project management competencies, and 6 items in presentation and report writing competencies which showed the highest number among the competencies. There was no item of ‘Concentrate here’ area in the collaboration competencies. 11 items were ranked within the 1st to 14th positions based on the educational needs according to the Borich index. 3 items of the top rankings were excluded from ‘Concentrate here’ area, 2 items falling into the ‘low-priority’ area and 1 item into the ‘Keep up the good work’ area. Conclusions Based on the results, pedagogical implications were derived for designing and implementing project based learning for university students, focusing on field handling ability, innovation, thinking skills, crisis management and leadership.
A Study on the Development of Evaluation Tools for School Culture and Arts Education to Establish a Performance Management System for School Arts Instructor Support Business

Objectives The purpose of this study is to develop an evaluation tool to assist in the mutual evaluation of the participants in the school arts teacher support project, namely arts instructors, operating schools, and local operating agencies, in order to establish a quality management system for school cultural arts education and contribute to enhancing the cultural arts education capabilities of those who participate in each school's cultural arts education. Methods Based on previous studies, a draft of the questions was developed and FGI, written review, and survey were conducted with 31 experts related to culture and arts education to revise and supplement the evaluation items to confirm the validity. Results First, questions for each subject of art instructors, school teachers, and beneficiary students were produced to evaluate art instructors, and consisted of self-reflection questions, art expertise (observation, understanding/creation, and appreciation), educational expertise (class progress, student management), instructor competency (instructor literacy, cooperation with teachers), and comprehensive satisfaction evaluation. In addition, additional questions were produced for cooperation in the operating school to collect opinions from art instructors. Second, it was developed by dividing it into art instructors and teachers in charge for the evaluation of local operating institutions, and both art instructors and teachers developed evaluation questions in five areas: administrative support, competency support, business support, civil complaint management, guidance, and promotion. Conclusions Through the final development of the arts teacher and local operating agency evaluation items, this study contributes to the establishment of a capacity management system for school cultural arts education quality management, provides important criteria that must be sustained or improved in the field of school cultural arts education, and helps enhance the cultural arts capabilities of each participant in the school arts education, including arts instructors, operating schools, and local operating agencies.
Analysis of Middle School Students’ Self-directed Project Implementation Experience

자기주도 프로젝트가 학생들의 자기주도성을 높이는 데 효과가 있는 것으로 알려져 있으나, 이를 수행하는 학생들의 경험을 생생하게 밝힌 선행연구는 아직 부족하다. 이에 이 연구는 자기주도 프로젝트를 수행한 중학생들을 대상으로 혼합연구 방법으로 자기주도 학습력의 변화와 함께, 학생들의 프로젝트 수행 경험 및 인식을 살펴보고자 하였다. 이를 위해 자유학기제와 동아리 활동을 통해 자기주도 프로젝트를 수행한 B중학교 1~3학년 112명으로부터 두 번에 걸쳐 수집한 자료를 대응표본 t 검증방법으로 분석하였고, 이들 중 8명을 선발하여 초점집단면접을 실시하였다. 연구결과, 이전에 자기주도 프로젝트를 수행해 본 경험이 있는 2학년만이 자기주도 학습력에서 초인지, 인지 사고, 자기효능감에서 긍정적인 변화를 보고하였다. 또한, 학생들은 처음 이 프로젝트를 접하였을 때는 막막함과 내･외적 갈등을 경험하였으나 프로젝트 수행과정에서 부딪히는 여러 문제에 대해 스스로 해결해가는 방법을 모색하고 필요할 때 최소한의 수준에서 교사의 지원을 요청하는 등 적극적이고 능동적인 학습자의 모습을 나타내었다. 이 연구 결과는 시행착오를 겪더라도 학생들이 나름의 방법을 찾을 수 있는 자기주도 학습 기회가 학교에서 충분히 주어진다면 이들의 자기주도성을 높이는 데 도움이 됨을 확인할 수 있었다.Although self-directed projects are known to be effective in increasing students’ self-directed learning, there is still a lack of previous studies that vividly reveal the experiences of students who perform them. The study aimed to investigate the changes in self-directed learning ability through self-directed projects in middle school students and examine the experience of implementing these projects. To investigate the change in self-directed learning ability, the data was collected twice from 112 students in grades 1 to 3 of B middle school and analyzed using the paired-samples t -test. The students carried out self-directed projects through the free semester system and club activities. Eight of them were then selected, and focus group interviews were conducted to gain an in-depth understanding of their experiences with self-directed project implementation. As a result, only second-graders who had previously carried out self-directed projects reported positive changes in meta-cognition, cognitive thinking, and self-efficacy in self-directed learning. The students reported experiencing a sense of confusion first and internal and external conflicts during the project’s execution. However, they learned how to solve problems on their own and, when necessary, sought minimal support from teachers, demonstrating their active and proactive approach to learning. Based on these results, we suggest that self-directed learning ability can change when students are given enough time to explore their own approaches through trial and error in schools.
Value iteration for streaming data on a continuous space with gradient method in an RKHS

The classical theory of reinforcement learning focused on the tabular setting when states and actions are finite, or for linear representation of the value function in a finite-dimensional approximation. Establishing theory on general continuous state and action space requires a careful treatment of complexity theory of appropriately chosen function spaces and the iterative update of the value function when stochastic gradient descent (SGD) is used. For the classical prediction problem in reinforcement learning based on i.i.d. streaming data in the framework of reproducing kernel Hilbert spaces, we establish polynomial sample complexity taking into account the smoothness of the value function. In particular, we prove that the gradient descent algorithm efficiently computes the value function with appropriately chosen step sizes, with a convergence rate that can be close to 1/N, which is the best possible rate for parametric SGD. The advantages of using the gradient descent algorithm include its computational convenience and it can naturally deal with streaming data.
American Sign Language Recognition and Generation : A CNN-based Approach

Although not a global language, sign language is an essential tool for the deaf community. Communication between these communities and hearing population is severely hampered by this, as human-based interpretation can be both costly and time-consuming. In this paper, we present a real-time American Sign Language (ASL) generation and recognition system that makes use of Convolutional Neural Networks and deep learning (CNNs). Despite differences in lighting, skin tones, and backdrops, our technology is capable of correctly identifying and generating ASL signs. We trained our model on a large dataset of ASL signs in order to obtain a high level of accuracy. Our findings show that, with accuracy rates of 98.53% and 98.84%, respectively, our system achieves high accuracy rates in both training and validation. Our approach uses the advantages of CNNs to accomplish quick and precise recognition of individual letters and words, making it particularly effective for sign fingerspelling recognition. We believe that our technology has the ability to transform communication between the hearing community and the deaf and hard-of-hearing communities by providing a dependable and cost-effective way of sign language interpretation. Our method could help people who use sign language communicate more easily and live better in a range of environments, including schools, hospitals, and public places.
CRIME PREDICTION BASED ON PERSON-WEAPONS RELATION USING DEEP LEARNING TECHNIQUES

Crime Scene detection predict the chances of happening the crime without any involvement of human intervention is always the crucial task in the field of artificial intelligence.In this paper crime forecasting based on the weapon detection and tracking with the person can help investigator to understand the sequence of action took place during the crime.The images are manually annotated, which is a process where an expert goes through each images and mark the position and class of object within the image.Object detection and classification algorithms provides the necessary ground to verify data for the algorithms.The models like SSD, YOLO and Faster RCNN are used for weapons detection and mediapipe library is used to generate the human body datapoints and calculate the relation between weapons with the human.The maximum accuracy of Faster RCNN with mediapipe library is 93%.
Analysis of Human Diseases using Artificial Neural Network and Blockchain Technology

With the development of engineering technology and artificial neural network which mimic human brain neural networks, are being using in medical diagnosis for various human diseases. The purpose of this paper is to investigate and study various diseases using neural network and blockchain technology used in medical diagnosis. Emerging technologies like artificial Neural Network and Blockchain Technology are revolutionizing the existing healthcare infrastructure, which is a difficult task to securely and accurately forecast different diseases in Human being. Blockchain and ML are providing the best solutions to gather information while predicting and securing human disease. This study provides comprehensive reviews on different Artificial Neural Network techniques, Radial Basis Function (RBF), Generalized Regression Neural Network (GRNN), Support Vector Machine (SVM), Feedforward Backprogation Neural Network (FFBP), Convolutional Neural Network (CNN), in order to predict various human diseases. Artificial Neural Network, in addition to its strengths, may assist in overcoming many of the restrictions that Blockchain Technology base systems used in medical diagnosis of various diseases. These two technologies when combined can produce high performing and valuable solutions. In this manuscript, Blockchain Technology and how machine learning skills can be combined with a blockchain based systems are studied.
New preprint explores tracing data reuse and citations

In our digital era, scientists are certainly sharing and reusing open data. Yet it remains unclear how widespread data reuse and citation practices are within academic disciplines, and why scientists cite—or do not cite—data in their research work. In a recent preprint from the Meaningful Data Counts project, Kathleen Gregory (postdoctoral researcher at the University of Vienna and University of Ottawa) and fellow ScholCommLab members—Anton Boudreau Ninkov, Chantal Ripp, Emma Roblin,...
Владельцы личных библиотек и книжная культура Туркестанского края на рубеже XIX - XX веков

The article is devoted to the owners of personal libraries in the Turkestan region at the turn of the XIX – early XX centuries, who made a significant contribution to the foundation of the Turkestan Public Library and development of book culture in general. The purpose of the article is to consider peculiarities of book culture as well as the owners’ personalities, history of the formation of their personal libraries, the repertoire and the degree of their study. Information about personal libraries and their owners is pro-vided on materials from the collections of rare books and manuscripts of the National Library of Uzbeki-stan and the Fundamental Library of the Academy of Sciences of the Republic of Uzbekistan. The author considers Russian personal libraries as an important element of the national and regional book culture of the region.
PRILOG UNIVERZITETSKOJ NASTAVI KNjIŽEVNOG PREVOĐENjA S ITALIJANSKOG NA SRPSKI: O ISKUSTVIMA U RADU S NOVIM PRAKTIKUMOM

Translation competence, although important as a practical outcome of the second language acquisition process and a fundamental prerequisite for entering the job market, seems to be unfairly neglected in terms of the availability of printed instructional materials supporting its development. In such context and aiming to contribute to teaching translation from Italian to Serbian at the university level, a new workbook was created – Praktikum za vežbe prevođenja sa italijanskog na srpski jezik (Ceković 2018), intended for Serbian-speaking students of the Ital- ian language and literature at intermediate-advanced level of competence. This paper aims to describe some of the procedures used in the creation of the workbook as well as to illustrate its use in the classroom. The workbook is not only designed for literary translation but also as a source for reading exercises, text interpretation and contrastive Italian-Serbian analysis.
Automatic Identification of Kinematic Diagrams with Computer Vision

Abstract In this work, a computer vision algorithm for the detection and recognition of 2D kinematic diagrams, both from paper schemes and digital files, was developed. Furthermore, it runs even with hand-made diagrams, which can be correctly identified. The algorithm is mainly based on the use of the free computer vision library OpenCV, being able to identify each element of the kinematic diagram, its connection with the other elements and store its pixels, which will allow in future research the implementation of motion in the sketches themselves. Allowed elements are revolute, prismatic, fixed, cylindrical and rigid joints and rigid bars. The main applications of this work are focused on the teaching world, communication of ideas in a quickly and graphical way and for fast and preliminary designs of new mechanisms as people can draw the diagram in a Tablet or paper and simulate it in real time, avoiding the necessity to learn how to operate a specialized simulation software and the time it takes to prepare the virtual model and obtain its results.
Maneuvering Target Tracking

The system model of target tracking is composed of a measurement model and a motion model. As mentioned in the introduction of Chap. 2 , the measurement uncertainty is a major challenge faced by target tracking. In fact, there is another important problem.
Single Target Tracking Algorithms

Target tracking refers to the process during which the number and states of targets are jointly estimated based on uncertain measurements. Measurement uncertainty includes noise pollution, clutter interference, detection uncertainty, and data association uncertainty.
Target Tracking for Doppler Radars

The previous chapter extended the standard RFS-based target tracking algorithms from the perspective of the motion model, and from the beginning of this chapter to Chap. 12 , the standard RFS-based target tracking algorithms will be extended from the perspective of the measurement model.
SIMULATION-BASED OPTIMIZATION OF PATH PLANNING FOR CAMERA-EQUIPPED UAV CONSIDERING CONSTRUCTION ACTIVITIES

Automated progress monitoring of construction sites using cameras has been proposed in recent years.However, collecting images or videos using fixed or pan-tilt-zoom cameras is still limited by the inability to adapt to the dynamic construction environment.Therefore, considerable attention has been paid to using camera-equipped unmanned aerial vehicles (CE-UAVs), which provide mobility to the camera over the construction site.Previous studies in this area proposed methods for capturing the as-built BIM model by using structure from motion (SFM).However, data collection of construction activities of workers and equipment using CE-UAVs has not been discussed before.This paper proposes a method to perform simulation-based optimization of path planning for CE-UAVs to allow automated and effective data collection of construction activities based on a high 4D-LOD as-planned BIM, which includes a detailed micro-schedule and the corresponding workspaces.This method can identify the most informative views of the workspaces and the optimal path for data capturing.The proposed method considers the following requirements and constraints: (1) The fields of view should be optimized to cover the areas of interest and to ensure visibility of the targets considering occlusions according to the 4D BIM model; (2) The path of the UAV should be optimized to allow the data collection from multiple dynamic targets over a large construction site considering the location of activities on the site at specific times and their importance level while reducing the travel cost; and (3) The data collection should consider the requirements for computer vision processes.A case study is developed to demonstrate the feasibility of the proposed method.