Reviewerly/exHarmony huggingface dataset:
Video synopsis method based on interaction determination using human pose estimation

Authors:
raw_author_name: Chenwu Wang
raw_affiliation_string: Xi’an University of Posts and Telecommunications, School of Modern Post, Xi’an, China
raw_author_name: Kaixuan Yang
raw_affiliation_string: Xi’an University of Posts and Telecommunications, School of Computer Science, Xi’an, China
raw_author_name: Pei Wang
raw_affiliation_string: Xi’an University of Posts and Telecommunications, School of Modern Post, Xi’an, China
raw_author_name: Zhixiang Zhu
raw_affiliation_string: Xi’an University of Posts and Telecommunications, School of Modern Post, Xi’an, China
raw_author_name: Lei Zhang
raw_affiliation_string: Xi’an University of Posts and Telecommunications, School of Computer Science, Xi’an, China
raw_author_name: Fudan Wang
raw_affiliation_string: Xi’an University of Posts and Telecommunications, School of Computer Science, Xi’an, China

Abstract: Video synopsis aims to condense long videos containing temporal redundancy into a more compact form by rearranging the active objects in the video. However, since each object in the video belongs to a different tube, moving the objects during the tube rearrangement process may disrupt the interaction relationship between the objects. To address this issue, we proposed a video synopsis optimization method based on interaction determination using human pose estimation. First, the inverse perspective mapping method is used to calculate the distance between objects from a bird’s-eye view. Then the body orientation is determined using the coordinates of human skeletal points obtained from the human pose estimation model. These two pieces of information are then combined to determine the interactions between objects. Second, the interaction energy cost term is introduced. By penalizing the cost term, the interactions between objects in the original video are preserved in the synopsis video. Finally, we propose a fusion optimization algorithm (FSOSA) that combines snake optimization and simulated annealing. FSOSA aims to minimize the energy cost function and achieve optimal tube rearrangement. Experimental results demonstrate that the proposed method effectively preserves the interactions between objects while improving the convergence speed.
A Method for Specifying Yoga Poses Based on Deep Learning, Utilizing OpenCV and Media Pipe Technologies

Authors:
raw_author_name: T Anuradha
raw_affiliation_string: Department of Information Technology, VR Siddhartha Engineering College, Vijayawada, Andhra Pradesh, India
raw_author_name: N. Krishnamoorthy
raw_affiliation_string: Department of Computer Science and Engineering, Kongu Engineering College, Perundurai, Erode, Tamilnadu, India
raw_author_name: C.S. Pavan Kumar
raw_affiliation_string: Department of Information Technology, VR Siddhartha Engineering College, Vijayawada, Andhra Pradesh, India
raw_author_name: L.V. Narasimha Prasad
raw_affiliation_string: Department of Computer Science and Engineering, Institute of Aeronautical Engineering, Hyderabad, Telangana, India
raw_author_name: Anilkumar Chunduru
raw_affiliation_string: Department of Information Technology, GMR Institute of Technology, Rajam, Srikakulam, Andhra Pradesh, India

Abstract: Yoga is a years discipline that calls for physical postures, mental focus, and deep breathing. Yoga practice can enhance stamina, power, serenity, flexibility, and well‐being. Yoga is currently a well-liked type of exercise worldwide. The foundation of yoga is good posture. Even though yoga offers many health advantages, poor posture can lead to issues including muscle sprains and pains. People have become more interested in working online than in person during the last few years. People who are accustomed to internet life and find it difficult to find the time to visit yoga studios benefit from our strategy. Using the web cameras in our system, the model categorizes the yoga poses, and the image is used as input. However, the media pipe library first skeletonizes that image. Utilizing a variety of deep learning models, the input obtained from the yoga postures is improved to improve the asana. The algorithms like VGG16 (Visual Geometric Group), VGG19, Convo2d, CNN.
Quality Enhancement with Frame-wise DLCNN using High Efficiency Video Coding in 5G Networks

Authors:
raw_author_name: M. Dharani
raw_affiliation_string: Department of ECE, Mohan Babu University, Tiruapthi, Andhra Pradesh, India
raw_author_name: Y Dasaratha Rami Reddy
raw_affiliation_string: Department of CSE, Chaitanya Bharathi Institute of Technology, Proddatur, AP, India

Abstract: In the present situation, applications related to multimedia are discovered to be comfortable with the use of video. The number of end consumers who use video continues to rise every day. People are presently searching for videos with better quality among the ones that are currently available there. This results in the launch and dissemination of HD (high definition) videos. Ultra high-definition (UHD) videos are becoming more and more popular as a result of this advancement and need. However, as video communication keeps expanding, there is an upsurge in network traffic because of the limited bandwidth, especially among smart cities. Different advancement codecs have been suggested to deal with the data stream to overcome this hazardous circumstance. However, the fact that modern UHD videos have huge amounts of data makes the available codecs even more complicated. UHD videos can be processed with the latest improvement codec, H.265/High-efficiency video coding (HEVC). Nevertheless, it is impacted by increased power consumption and intricate calculations. Limitations in the codec's functionality confine its use to specific applications, preventing its application in wireless, mobile, or portable settings. Hence, this research concentrates on implementing frame-level quality enhancement through a deep learning network known as FQE-Net. The deep learning convolutional neural network (DLCNN) is specifically crafted to manage films with resolutions up to 16K. Its primary objectives include reducing complexity, minimizing artifacts, enhancing the efficiency of the HEVC codec, and compacting energy consumption. To achieve superior efficiency, it is imperative to replace the DWT transforms within the HEVC codec with a DLCNN model. Additionally, incorporating the Content Block Search Algorithm for Motion Estimation and Compensation, alongside filtering techniques like Sample Adaptive Filter and Deblocking Filter, becomes essential. The simulation results showed that the suggested FQE-Net performed better than the conventional techniques.
DEVELOPMENT OF SERIAL IMAGE MEDIA IN THE FORM OF POP-UP E-BOOKS TO IMPROVE THE READING SKILLS OF CLASS I STUDENTS IN THE INDEPENDENT CURRICULUM

Authors:
raw_author_name: Fitria Sari
raw_affiliation_string: Universitas Dharmas Indonesia
raw_author_name: Amar Salahuddin
raw_affiliation_string: Universitas Dharmas Indonesia
raw_author_name: Eza Susanti
raw_affiliation_string: Universitas Dharmas Indonesia

Abstract: Media is a vehicle for transmitting learning information or transmitting messages. The word media comes from Latin, namely medius, which means middle, intermediary, or introduction. Media means an intermediary or messenger from the sender to the message recipient. The broad meaning is activities that can create conditions that enable students to acquire knowledge and attitudes. The aim of this research is to see whether the development of serial image media in the form of pop-up e-books can improve the reading skills of class I students in the independent curriculum. The type of research used in this research is research and development. Research and development (R&amp;D) is a type of research that focuses on products. The results of the research show that serial image media in the form of pop-up e-books is said to be very valid, where the average for validator material is 83% while for media experts it is 85%. Based on the results of the research and discussions that have been carried out, it can be concluded as follows. Pop-up book media that is suitable for reading for grade I elementary school students is a pop-up book that pays attention to aspects of the material that supports the content of the learning material and is in accordance with the characteristics of elementary school students.&#x0D;
How does AI create and recommend corresponding wallpapers based on the games played by users?

Authors:
raw_author_name: Zicheng Liu
raw_affiliation_string: Qingdao Academy
raw_author_name: Jiacheng Wang
raw_affiliation_string: Shanghai United International School Jiaoke Campus

Abstract: The purpose of this paper is to give a comprehensive review of the related work that has everything to do with creating a wallpaper in artificial intelligence (AI) technology. Firstly, deep learning and neural network are summarized, especially generative adversarial networks that aim to effective generate images. Then, User interest modeling is summarized and analyzed, which is a key point to figure out the preference of the players. Further, main ideas are given about the trends and directions of wallpaper generation by AI.
Research on autonomous mobile robot maze navigation problem based on Dijkstras algorithm

Authors:
raw_author_name: Qihan Wu
raw_affiliation_string: University of Birmingham

Abstract: In recent years, the field of autonomous mobile robotics has garnered significant attention due to its potential applications in various domains such as logistics, surveillance, and search and rescue operations. A crucial challenge in this area is the efficient navigation of robots within complex and dynamic environments, particularly when navigating through maze-like structures. The maze navigation problem involves finding optimal paths for robots to traverse from their initial positions to designated destinations while avoiding obstacles and making intelligent decisions to ensure timely and safe navigation. This study aims to investigate and apply Dijkstras algorithm to solve the maze navigation problem for autonomous mobile robots. By analyzing the navigation challenges faced by autonomous mobile robots in maze environments, a solution based on Dijkstras algorithm is proposed. In conclusion, this study contributes to the field of autonomous mobile robotics by proposing and evaluating the application of Dijkstras algorithm for maze navigation. The experimental results validate its potential to address the challenges of navigating intricate maze environments. However, it is acknowledged that further refinement and innovation are possible to continue improving the performance of autonomous mobile robots in maze navigation scenarios.
Multimodal human-computer interaction for virtual reality

Authors:
raw_author_name: Jiajun Tang
raw_affiliation_string: Shool of Advanced Technology Xi'an Jiaotong-liverpoor Unsiversity Suzhou, China
raw_author_name: Manni Gong
raw_affiliation_string: Wuhan Britain-China School
raw_author_name: Taojie Gao
raw_affiliation_string: Wuhan Britain- China School

Abstract: Virtual reality (VR) is an interactive simulation environment based on computer technology that enables users to immerse themselves in a virtual world. With the continuous advancement of technology, VR has shown great potential in various fields. This article aims to review the application of VR in different fields and its impact on society. First, this paper introduces VR's basic principles and technical characteristics. VR systems are usually composed of head-mounted display devices, trackers, joysticks, etc., enabling users to experience immersive virtual environments by simulating real-world perception and interaction. Secondly, this paper discusses the application of VR in the field of education. VR technology can provide an immersive learning experience, enabling students to personally participate in the course content, greatly enhancing the effect of learning. At the same time, VR can also simulate experimental scenes, train operational skills, etc., to provide students with more abundant and practical learning resources. Then, this paper introduces the application of VR in the medical field. VR can be used for rehabilitation training of patients, psychological treatment, and other aspects, effectively improving the quality and effect of medical services. In addition, this paper also discusses the application of VR in entertainment, tourism, and other fields. VR technology can bring users immersive gaming experience, virtual tourism, etc., and inject new vitality into the entertainment industry. In tourism, VR can provide tourists with an immersive sightseeing experience, so they can feel the distant scenery at home.
Analysis of -ary tree algorithms with successive interference cancellation

Authors:
raw_author_name: Yash Deshpande
raw_author_name: Cedomir Stefanović
raw_author_name: Wolfgang Kellerer

Abstract: Abstract We calculate the mean throughput, number of collisions, successes, and idle slots for random tree algorithms with successive interference cancellation. Except for the case of the throughput for the binary tree, all the results are new. We furthermore disprove the claim that only the binary tree maximizes throughput. Our method works with many observables and can be used as a blueprint for further analysis.
Impact of Dataset Scaling on Hierarchical Clustering: A Comparative Analysis of Distance-Based and Ratio-Based Methods

Authors:
raw_author_name: Ali Rashash R. Alzahrani

Abstract: In this study, the distance-based agglomerative hierarchical clustering techniques were compared to a ratio-based approach. Two real datasets, which were also used in a prior study by Roux (2018), were considered. Firstly, it was observed that the type of scaling applied to the datasets was found to affect the results of hierarchical clustering. Thus, various scaling methods were employed prior to implementing hierarchical clustering. Furthermore, two rank-based goodness-of-fit measures were used to evaluate the hierarchical clustering methods. In contrast to Roux (2018) findings, it was observed that the distance-based methods, such as Median linkage, Average linkage, and centroid linkage, performed better than the ratio-based method. The ratio-based methods also showed issues with branch crossing in the hierarchical clustering dendrogram. Consequently, this study illustrates that, with appropriate dataset scaling, the distance-based methods outperform ratio-based methods in terms of goodness-of-fit measures.
SiamFDA: feature dynamic activation siamese network for visual tracking

Authors:
raw_author_name: Jialiang Gu
raw_affiliation_string: Computer Science and Engineering, Sun Yat-sen University, Guangzhou, 510000, China
raw_author_name: Ying She
raw_affiliation_string: Computer Science and Engineering, Sun Yat-sen University, Guangzhou, 510000, China
raw_author_name: Yi Yang
raw_affiliation_string: Computer Science and Engineering, Sun Yat-sen University, Guangzhou, 510000, China

Abstract: Abstract In this paper, we present a novel anchor-free visual tracking framework, referred to as feature dynamic activation siamese network (SiamFDA), which addresses the issue of ignoring global spatial information in current Siamese network-based tracking algorithms. Our approach captures long-range dependencies between distant pixels in space, which enables robustness to unreliable regions. Additionally, we introduce a hierarchical feature selector that adaptively activates features at different layers, and an adaptive sample label assignment method to further improve tracking performance. Our extensive evaluations on six benchmark datasets, including VOT-2018, VOT-2019, GOT10k, LaSOT, OTB-2015, and OTB-2013, demonstrate that SiamFDA outperforms several state-of-the-art trackers in various challenging scenarios, with a real-time frame rate of 40 frames per second.
Content Modeling in Multi-Platform Multilingual Social Media Data

Authors:
raw_author_name: Vlad Barash

Abstract: An increase in the use of social media as the primary news source for the general population has created an ecosystem in which organic conversation commingles with inorganically seeded and amplified narratives, which can include public relations and marketing activity but also covert and malign influence operations. An efficient and easily understandable analysis of such data is important, as it allows relevant stakeholders to protect online communities and free discussion while better identifying activity and content that may violate social media platform terms of service. To accomplish this, we propose a method of large-scale social media data analysis, which allows for multilingual conversations to be analyzed in depth across any number of social media platforms simultaneously. Our method uses a text embedding model, i.e., a natural language processing model that holds semantic and contextual understandings of language. The model uses an “understanding” of language to represent posts as coordinates in a high-dimensional space, such that posts with similar meanings are assigned coordinates close together. We then cluster and analyze the posts to identify online topics of conversation existing across multiple social media platforms. We explicitly show how our method can be applied to four different datasets, three consisting of Chinese social media posts related to the Belt and Road Initiative and one relating to the Russia-Ukraine war, and we find politically-influenced conversations that contain misleading information relating to the Chinese government and the Russia-Ukraine war.
Penerapan Model Pembelajaran Berbasis Maslah Untuk Meningkatkan Hasil Belajar Siswa Kelas XI Pada Materi Hukum Pascal

Authors:
raw_author_name: None Herlina Usman
raw_affiliation_string: Universitas Negeri Jakarta

Abstract: Research on the problem based learning model on Pascal's law material aims to determine student learning outcomes in class XII. This research is classroom action research that uses Kurt Lewin's model or method. Kurt Lewin's classroom action research model consists of several stages, namely planning, action, observation and reflection. In this research, two cycles of research were carried out. Model based learning is often called problem based learning. By providing problems, it is hoped that students can be active in searching for and finding solutions to the problems given. With problem-based learning, educators try to invite students to be active in learning activities. Based on the results of data analysis, it was found that this learning experienced an increase in the percentage of learning completion and an increase in the class average. So the percentage of students who do not complete has decreased. The data results in cycle I showed that student learning completeness was 82.35% and in cycle II it rose to 88.48%. In cycle II the average student score was 76.47 and in cycle II the average student score rose to 85.25%. Meanwhile, the percentage of student failure to complete in cycle I was 17.65% and in cycle II it decreased to 11.52%. From the data results it can be concluded that the use of model based learning in Pascal's law material for class XII students can improve student learning outcomes.
An Analysis of Narratives on Vocational Consignment Education Experience of Students in General High Schools

Authors:
raw_author_name: Jun Ho Choi

Abstract: The purpose of this study is to understand in-depth the context of the situation and the subjective meaning composition in the selection of vocational consignment education, the life process, and the process of returning to school and adaptation after the interruption, focusing on the experience story that constitutes the personal and social life of students who experience vocational consignment education in general high schools. Therefore, this study examined the selection and life process of vocational consignment education and the process of returning to school and adaptation after the interruption of consignment education by using narrative analysis method for the stories directly dictated by students of vocational consignment education in general high schools. The results of this study are as follows: First, the choice of vocational consignment education for general high schools considers one's aptitude and talent, and the interaction with the surrounding people and the composition of one's meaning play a very important role in the difference of the choice decision. Next, in the career consignment education life of general high schools, it was found that there was a great psychological and emotional reward that strengthened career awareness by having a sense of accomplishment or confidence due to the pride of preparing for the desired job in accordance with the aptitude and talent of the students, the support of the teacher, and the learning success experience coming from the consignment curriculum. However, there was a case where students in the consignment educational institution did not form a sense of identity or belonging properly. In addition, psychological and cultural factors such as the burden and difficulty of acquiring practical training and certification, the sense of heterogeneity felt in the collective culture among the consignment education students, the difficulties in communication and exchanges with the consignment education participants, and the reconsideration of their interests and interests through consignment education and the turning of their career goals to college were the complex factors that determined their return to school after the interruption of consignment education.
Prolegomena about the cluster-network model organization of the educational system in musical academies of Ukraine

Authors:
raw_author_name: Olha Oleksiuk

Abstract: The article „Prolegomena about the cluster-network model organization of the educational system in the musical academies of Ukraine” discusses the complexity of higher musical education and the need for new scientific approaches to address the changing pedagogical reality. The authors propose a cluster-network model for organizing the educational system in musical academies, which is based on the following components: conceptual – tasks, methods, forms, means; axiological– values; psychological and pedagogical – mechanisms of learning values; organizational and management – management of elements of the educational structure. The cluster-network model aims to increase the competitiveness of the educational system by developing the students’ competencies that meet the requirements of the social order. It also emphasizes the importance of spirituality in education and the need for a holistic approach to human development. The authors argue that the ideal of human education is constantly changing, but the ability to correlate the concepts, ideas, and theories acquired during cognitive activity with an individual value system is a key indicator of successful education. The article highlights the importance of understanding the inner class and spiritual being of a person, as well as the need to implement some methods that contribute to penetrating into the phenomenological secrets of human consciousness for researching and revealing the most important mental structures of man. It also discusses the role of dialogue as a way of existing and coexisting- with the „other” in the communication process. The proposed model aims to address the challenges of the postmodern era, where the world is thought of as an open text not limited in its manifestations and interpretations. It emphasizes the importance of continuous education and the integration of knowledge from related disciplines to develop digital education and innovative work practices.