Reviewerly/exHarmony huggingface dataset:
The influence of pedagogical reflection on design educational and professional plans of future teachers.

The article analyzes the level of formation of pedagogical reflection among graduates studying the pedagogical specialties, and also generalizes the nature of the influence of pedagogical reflection on the educational and professional plans of future teachers after receiving a diploma. In the study, the author considers pedagogical reflection as a prestart state of a specialist, embodied in meta-competence, which allows one to assess one’s professional knowledge and skills as sufficient or insufficient to work in the acquired specialty. As a part of the study, a vision of the nature and structure of the phenomenon of pedagogical reflection founded on a competency-based approach was formed. The algorithm was proposed for assessing the level of formation of pedagogical reflection among graduates based on the use of factor analysis. The algorithm was tested on data from a questionnaire survey conducted in 2023 by the Voluntary Research Center of the Russian Academy of Sciences (RAS) among graduates studying to become teachers in the Vologda region. As a result of testing, it was revealed that after receiving a diploma, graduates with critical reflection more often than others want to connect their lives with work at school and see the future of their children in the teaching profession. Graduates with moderate and weak reflection are less likely to design appropriate plans. In the course of further generalization, a procedural model of the influence of pedagogical reflection on the professional development of a university graduate was developed. The scientific novelty of the study lies in the new perspective of posing the question of pedagogical reflection as a factor in educational and professional choice; the author’s methodology for summarizing the level of formation of professional reflection within the framework of factor analysis; a conceptual model that describes the influence of reflection on the professional development of a graduate, focusing on “soft” mechanisms that can be used to solve personnel problems in the education system. The article proposes a set of approaches to solving the problems of training reflective teachers, which can be introduced into management practice.
Digital Content Management Using Non-Fungible Tokens and the Interplanetary File System

Non-fungible tokens (NFTs) are digital identifiers containing metadata, such as token number, title, content, and image URL, and are linked to digital assets, which are characterized by the fact that, unlike conventional virtual assets, they have their own unique value and cannot be replaced. NFTs cannot be deleted or forged; therefore, they can be used to authenticate the ownership of digital assets. The metadata of the NFTs are uploaded to the interplanetary file system (IPFS), which is a distributed file system, and converted into unique content identifiers (CIDs) that are stored on the blockchain. Digital content (DC) is divided into multiple pieces; it also has its own unique value and is distributed and stored using the IPFS. This study built an NFT-based IPFS testbed and experimented with the process of generating unique values for DC divided into three groups and sharing them. The results confirmed that each DC had a unique hash value and no duplicates existed.
Edutuber and Gender in STEM

The gender gap in the field of STEM (Science, Technology, Engineering and Mathematics) is nothing new. Recent research warns of this through programs and initiatives that use Information and Communication Technology (ICT) as a resource to reduce this gap. However, new questions and some areas of concern are arising out of the mass use of digital repositories. The possibility of consuming and producing video (prosumers) in these digital ecosystems brings to light the prejudices and stereotypes in these fields through their content. Considering the YouTube repository, this research analyses the edutubers on 81 STEM channels from a gender perspective in 190 immersions. Through a critical approach, oriented towards change for social transformation, an exploratory and descriptive paper has been written. It employs a mixed quantitative–qualitative method. The results are described in the form of four descriptive grids about edutuber environments where an evident gender gap in the STEM edutubers can be observed, and guidelines are subsequently outlined to attempt to eliminate it. It is concluded that the educational resources offered by YouTube are popular and have a significant impact on the young population, but these resources inherit past behaviours that also entail a new risk associated with the use of ICT.
Radar-SR3: A Weather Radar Image Super-Resolution Generation Model Based on SR3

To solve the problems of the current deep learning radar extrapolation model consuming many resources and the final prediction result lacking details, a weather radar image super-resolution weather model based on SR3 (super-resolution via image restoration and recognition) for radar images is proposed. This model uses a diffusion model to super-resolve weather radar images to generate high-definition images and optimizes the performance of the U-Net denoising network on the basis of SR3 to further improve image quality. The model receives high-resolution images with Gaussian noise added and performs channel splicing with low-resolution images for conditional generation. The experimental results showed that the introduction of the diffusion model significantly improved the spatial resolution of weather radar images, providing new technical means for applications in related fields; when the amplification factor was 8, Radar-SR3, compared with the image super-resolution model based on the generative adversarial network (SRGAN) and the bicubic interpolation algorithm, the peak signal-to-noise ratio (PSNR) increased by 146% and 52% on average. According to this model, it is possible to train radar extrapolation models with limited computing resources with high-resolution images.
CLOVER: Contrastive Learning for Onboard Vision-Enabled Robotics

Current deep-learning models employed by the planetary science community are constrained by a dearth of annotated training data for planetary images. Current models also frequently suffer from inductive bias due to domain shifts when using the same model on data obtained from different spacecraft or different time periods. Moreover, power and compute constraints preclude state-of-the-art vision models from being implemented on robotic spacecraft. In this research, we propose a self-supervised learning (SSL) framework that leverages contrastive learning techniques to improve upon state-of-the-art performance on several published Mars computer vision benchmarks. Our SSL framework enables models to be trained using fewer labels, generalize well to different tasks, and achieve higher computational efficiency. Results on published Mars computer vision benchmarks show that contrastive pretraining outperforms plain supervised learning by 2–10%. We further investigate the importance of dataset heterogeneity in mixed-domain contrastive pretraining. Using self-supervised distillation, we were also able to train a compact ResNet-18 student model to achieve better accuracy than its ResNet-152 teacher model while having 5.2 times fewer parameters. We expect that these SSL techniques will be relevant to the planning of future robotic missions, and remote sensing identification of target destinations with high scientific value.
Application of Kahoot Game Application Based Assessment in Class Discussion Learning Model Action to Improve Students' Arabic Learning Outcomes

The more advanced the times, the more sophisticated the development of technology. No exception to the technology that should be utilized as much as possible by educators in teaching and learning activities in the classroom. possible by educators in teaching and learning activities in the classroom. One of them is of which is that educators can apply the Kahoot application as an assessment tool for learning in the classroom as an effort to create a learning atmosphere so that learning in the classroom as an effort to create a conducive learning atmosphere and conducive and save time in the process of assessing student learning outcomes.This research aims to overcome the problems that occur in the classroom during teaching and learning activities. classroom when teaching and learning activities take place as an action taken to improve students' learning outcomes. to improve the learning outcomes of Arabic language of class X students by applying Kahoot game-based assessment in the action model. Kahoot game-based assessment in the action of Class Discussion learning model. This research uses the Classroom Action Research (PTK) method which was implemented in SMA Muhammadiyah 25 Setiabudi Pamulang, South Tangerang. This research was conducted in two cycles. First, the pre-cycle stage and cycle 1 in its implementation using the Classroom Discussion learning model which learning model consisting of 5 phases (Clarifying the purpose and estabilishing the set, Focusing the Discussion, Controlling the Discussion, Ending the Discussion). Discussion, Controlling Discussion, Ending Discussion, Debriefing)The results of the study found that students' Arabic language learning outcomes The pre-cycle stage to the cycle 1 stage. the completeness of student learning outcomes only reached 47% while the cycle 1 stage the completeness of student learning outcomes has increased. Motivation of students to learn and foster the spirit of challenged students to participate in classroom learning activities
Perceived Intelligence of Artificially Intelligent Assistants for Travel: Scale Development and Validation

This study developed a perceived intelligence scale for artificially intelligent (AI) assistants and investigated its impact on users’ travel-related behavioral intentions. A four-stage study with a mixed-methods design was conducted. Study 1 identified three dimensions and 26 initial items through a systematic literature review, interviews, and focus group discussions. Study 2 used exploratory factor analysis to refine the items. Through composite confirmatory analysis, Study 3 confirmed an 18-item and three-dimensional scale (conversational intelligence, information quality, anthropomorphism). Study 4 established the scale’s predictive validity in travelers’ intentions to use AI assistants to search for travel information and make travel bookings. This research made the first attempt to identify factors shaping users’ perceptions of AI assistant intelligence, extending the understanding of human-AI interaction and AI technology adoption in the travel sector. Furthermore, it provides actionable recommendations for the travel industry and AI developers when designing and deploying AI assistant services.
Using Virtual Reality Interventions to Promote Social and Emotional Learning for Children and Adolescents: A Systematic Review and Meta-Analysis

This study provides a comprehensive review of the application of virtual reality (VR) in social and emotional learning (SEL) for children and adolescents over the past decade (January 2013–May 2023), with a specific interest in the relations between their technological and instructional design features. A search in Web of Science resulted in 32 relevant articles that were then manually screened. Coding analysis was conducted from four perspectives: participant characteristics, research design, technological features, and instructional design. The analysis provides insights into the VR literature regarding publication trends, target populations, technological features, instructional scenarios, and tasks. To test the effectiveness of VR interventions for promoting SEL, a meta-analysis was also conducted, which revealed an overall medium effect size and significant moderating effects of SEL disorder type and instructional task. Finally, based on the research results, the practical implications of and future research directions for applying VR in SEL were discussed.
Increasing Student Collaboration Through the Scramble Type Cooperative Learning Model in Elementary School

Purpose of the study: Learning that prioritizes one-way interaction in class causes the learning process to become less interesting so that students easily get bored when participating in learning activities. This research aims to increase student cooperation through the Scramble type cooperative learning model in class III students at State Elementary School 187/1 Muara Bulian.&#x0D; Methodology: This research is classroom action research which consists of two cycles, where the data taken is in the form of observation data, through student collaboration observation sheets. This research was carried out in 4 stages, namely the planning, implementation, observation and reflection stages. During the teaching and learning process, learning activities apply the Scramble type cooperative learning model.&#x0D; Main Findings: The research results show that the application of the Scramble type cooperative learning model can increase student cooperation in social studies subjects. Based on the observation sheet, student collaboration shows an increase with the percentage of student collaboration being 69% in the good category in cycle I and 84% in the very good category in cycle II. Based on the research findings, it can be concluded that student cooperation in social studies learning for class III students at State Elementary School 187/I Muara Bulian can increase after implementing the Scramble type cooperative learning model.&#x0D; Novelty/Originality of this study: This research shows a significant increase in student collaboration after implementing this learning model. These findings indicate that the Scramble type cooperative learning model is effective in encouraging student cooperation and making the learning process more interesting for them. Thus, this research contributes to the development of learning methods that are more interactive and actively involve students.
Attitude Determination of Photovoltaic Device by Means of Differential Absorption Imaging

Future wireless power transmission will cover power levels up to kilowatts or more and transmission distances up to the scale of kilometers. With its narrow beam divergence angle, optical wireless power transmission (OWPT) is a promising candidate for such system implementations. In the operation of OWPT, it is necessary to estimate the position, direction (azimuth, elevation), and attitude of the target photovoltaic device before the power supply. The authors have proposed the detection of targets using differential absorption imaging and positioning with a combination of stereo imagery. In the positioning by stereo imagery, a condition regarding the consistency of the left and right images can be defined. This corresponds to the certain value of the exposure time of the image sensor, and this depends on the target’s attitude angle. In this paper, we discuss target attitude estimation using this minimum exposure time at which the integrity measure converges. A physical model was derived under general conditions of target position and experimental configuration. Target attitudes were estimated within an error range of 10 to 15 degrees in approximately 60 degrees range. On the other hand, there is an attitude estimation method based on the apparent size of the target. When using this method to estimate the attitude angle, errors are significantly large for specular and diffuse mixed targets like the PV. The method proposed in this paper is a robust attitude estimation method for the photovoltaic device in OWPT.
On the Design of Multi-Party Reversible Data Hiding over Ciphered Overexposed Images

Multi-party reversible data hiding over ciphered images (MRDH-CI) has high restorability since the image is split into multiple ciphered images by secret sharing. However, the MRDH-CI methods either fail to produce satisfied results, or only work well for conventional images. This paper introduces a multi-party reversible data-hiding approach over ciphered overexposed images. First, the pixels of the overexposed images are decomposed into two parts, each of which can be used for secret sharing. Then, the decomposed overexposed images are converted into multiple ciphered overexposed images by using a modified secret sharing method, in which the differences of the ciphered overexposed images are retained. The symmetry of the difference retaining makes the secret data conceal within the ciphered overexposed images such that the marked ciphered overexposed images can be created. Finally, by collecting sufficient marked ciphered overexposed images, it is possible to symmetrically reconstruct the concealed data and primitive overexposed image. Experimental results illustrate that the presented method can efficiently deal with overexposed images while maintaining a low computational overhead.
SyDog-Video: A Synthetic Dog Video Dataset for Temporal Pose Estimation

Abstract We aim to estimate the pose of dogs from videos using a temporal deep learning model as this can result in more accurate pose predictions when temporary occlusions or substantial movements occur. Generally, deep learning models require a lot of data to perform well. To our knowledge, public pose datasets containing videos of dogs are non existent. To solve this problem, and avoid manually labelling videos as it can take a lot of time, we generated a synthetic dataset containing 500 videos of dogs performing different actions using Unity3D. Diversity is achieved by randomising parameters such as lighting, backgrounds, camera parameters and the dog’s appearance and pose. We evaluate the quality of our synthetic dataset by assessing the model’s capacity to generalise to real data. Usually, networks trained on synthetic data perform poorly when evaluated on real data, this is due to the domain gap. As there was still a domain gap after improving the quality of the synthetic dataset and inserting diversity, we bridged the domain gap by applying 2 different methods: fine-tuning and using a mixed dataset to train the network. Additionally, we compare the model pre-trained on synthetic data with models pre-trained on a real-world animal pose datasets. We demonstrate that using the synthetic dataset is beneficial for training models with (small) real-world datasets. Furthermore, we show that pre-training the model with the synthetic dataset is the go to choice rather than pre-training on real-world datasets for solving the pose estimation task from videos of dogs.
Demand Mechanism, Information Barriers, and Comprehensive Approaches for the Development of Rural Education in the Context of Educational Digitalization

Amidst the contemporary digital era, the push for digital technology utilization, the genuine need for equitable high-quality education, and the rigorous digital literacy standards present both vast opportunities and challenges for rural education. Yet, rural education grapples with hurdles like the urban-rural digital gap, a deficiency in digital skills, inadequate infrastructure, and deep-seated teaching ideologies. Given these circumstances, channeling superior educational resources to foster urban-rural synergy, holistically elevating digital acumen among rural educators and pupils, fortifying the rural digital foundation, and reshaping traditional pedagogical perspectives stand out as potent strategies for rural educational advancement.
Intellectual Property Protection of data: Chinese Practice and related reflection

The era of big data has arrived, and data has become an extremely important distribution factor in the current society. What kind of rights data belongs to is still unclear and is still under exploration, but the effective protection of data is imminent, which profoundly affects the development of science and technology and the vitality of the market. Due to the characteristics and value attributes of data itself, protecting data through intellectual property protection is a topic worthy of in-depth study.There are lots of different methods around the globe trying to solve the problem,and China has also promoted its own solution--Registration.This passage discusses the new practice China adopted recently,and is wishing to draw some inspirations from the different measures taken in the four different experimental units launched in China.
Measures in Rural Education in China

This paper focuses on the issues of rural education development in China. Education is the cornerstone of development. As a populous and developing country, China pays great attention to education issues. The Chinese government and people have made many directional efforts for the development of education, but there are still many regional, cultural, and linguistic problems in the practical stages of policy implementation due to China's vast territory. Especially in the aspect of rural education, there are still many problems, and the revival of rural education also promotes the development of rural revitalization. This paper analyzes and introduces the current education environment and the problems of uneven education resources based on various education policies in China today, and proposes solutions to rural education problems, including localized curriculum setting for rural education, directed training for rural teachers, organic integration of new media and education, and the creation of spatial awareness in rural education.
On the Innovation Strategy of Higher Vocational Physical Education Under the Guidance of Vocational Education

For higher vocational colleges, because it is the place to cultivate "professional" talents, vocational education guidance is inevitable in teaching activities, so as to improve students' Vocational Competitiveness and make students' ability development more in line with work needs. But for the physical education work, due to the lack of attention of higher vocational colleges, there are many deficiencies in the process of carrying out educational activities. The most important thing is that there is no "localization" treatment in higher vocational colleges, blindly learning from the physical education curriculum of ordinary high school, without highlighting the guidance of vocational education, which can not provide effective help for students' career development. In this article, we will focus on the reform of physical education in Higher Vocational Colleges under the guidance of vocational education, and put forward some feasible optimization and innovation strategies on the basis of fully considering the professional needs and the development of students.
A Study of English Teaching Differences Between China and The United States

According to the existing literature, the analysis of the teaching content, teaching method and assessment model in China and the United States has the same trend: Scholars generally believe that compared with the English language teaching system in China, the methods of English language education in the United States are more diverse, the educational goals are more realistic to life, and the evaluation criteria are more comprehensive. The factors cause this difference is worth investigating. This paper evaluates the applicability of these views in today's world through a questionnaire survey. Specifically, this paper attempts to assess whether the similarities and differences that scholars have found between the English language teaching systems in China and the United States still exist today or whether the development trends between the English language teaching systems of the two countries are trending in the same direction today. The study surveyed Chinese students in the U.S. - a target group with dual English learning experiences in China and the U.S. The results of the paper show that the effectiveness and applicability of the English teaching systems of the two countries need to be discussed in the cultural environment of the two countries, and there is no one-sided argument that either system is better.