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2nd International Conference on Image Processing, computer Vision and Machine Learning, ICICML 2023

作者： Zhang, Ji Chen, Zhihao Ge, Yiyuan Yu, Mingxin Beijing Information Science and Technology University School of Instrument Science and Opto-Electronics Engineering Beijing China Beijing Information Science and Technology University Computer School Beijing China Jilin University Department of Software Engineering Changchun China

ISBN: (纸本)9798350331417

This paper introduces an innovative and efficient multi-scale Vision Transformer (ViT) for the task of image classification. The proposed model leverages the inherent power of transformer architecture and combines it with the concept of multi-scale processing generally used in convolutional neural networks (CNNs). The work aims to address the limitations of conventional ViTs which typically operate at a single scale, hence overlooking the hierarchical structure in visual data. The multi-scale ViT enhances classification performance by processing image features at different scales, effectively capturing both low-level and high-level semantic information. Extensive experimental results demonstrate the superior performance of the proposed model over standard ViTs and other state-of-the-art image classification methods, signifying the effectiveness of the multi-scale approach. This research opens new avenues for incorporating scale-variance in transformer-based models for improved performance in vision tasks. © 2023 IEEE.

关键词： Classification Convolutional neural networks Multi-scale Vision Transformer

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Demystifying Mobile Extended Reality in Web Browsers: How Far Can We Go? 23

Demystifying Mobile Extended Reality in Web Browsers: How Fa...

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2023 World Wide Web Conference, WWW 2023

作者： Bi, Weichen Ma, Yun Tian, Deyu Yang, Qi Zhang, Mingtao Jing, Xiang School of Computer Science Peking University Beijing China Institute for Artificial Intelligence Peking University Beijing China School of Computer Science and Engineering University of New South Wales Australia School of Software and Microelectronics Peking University Beijing China

ISBN: (纸本)9781450394161

Mobile extended reality (XR) has developed rapidly in recent years. Compared with the app-based XR, XR in web browsers has the advantages of being lightweight and cross-platform, providing users with a pervasive experience. Therefore, many frameworks are emerging to support the development of XR in web browsers. However, little has been known about how well these frameworks perform and how complex XR apps modern web browsers can support on mobile devices. To fill the knowledge gap, in this paper, we conduct an empirical study of mobile XR in web browsers. We select seven most popular web-based XR frameworks and investigate their runtime performance, including 3D rendering, camera capturing, and real-world understanding. We find that current frameworks have the potential to further enhance their performance by increasing GPU utilization or improving computing parallelism. Besides, for 3D scenes with good rendering performance, developers can feel free to add camera capturing with little influence on performance to support augmented reality (AR) and mixed reality (MR) applications. Based on our findings, we draw several practical implications to provide better XR support in web browsers. © 2023 ACM.

关键词： Web browsers

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Saving The Elf: Immersive VR Experience Utilizing Multiple Relaxing Approaches

Saving The Elf: Immersive VR Experience Utilizing Multiple R...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Nie, Cheng Ding, Ding Wu, Jinhao Yang, Xu Ou, Ronghuang Du, Wei College of Software Engineering Southeast University Nanjing China Southeast University Computer Experimental Teaching Center Nanjing China School of Computer Science and Engineering Southeast University Nanjing China School of Artificial Intelligence Southeast University Nanjing China School of Public Health Southeast University Nanjing China

ISBN: (纸本)9781665410205

The global prevalence of anxiety has seen a significant increase in the past few years. Anxiety, if left untreated, can lead to various detrimental effects, such as sleep disturbances, excessive fear, and even suicidal tendencies. Traditional face-to-face therapies have been employed to address this issue;however, their effectiveness is limited by time and space constraints, particularly during the COVID-19 pandemic. As a result, computer-based systems have emerged as a potential solution. However, most existing relaxation systems rely on a single method and have unnatural interactions, leading to a lack of variety and engagement. To overcome these limitations, this study proposes a virtual reality (VR) relaxation system that combines various relaxation techniques, a captivating storyline and natural interactions to enhance the user experience. To assess the effectiveness of the proposed system, a pilot study was conducted with 36 participants. The study utilized a between-subjects design, dividing the participants into three groups: a control group, a progressive muscular relaxation group, and a virtual reality relaxation group. The findings revealed that the virtual reality relaxation system significantly reduced anxiety levels among the participants. Importantly, this effect was observed to persist even after a period of time and was found to be more effective than using only one relaxation method in the long term. Moreover, the performance of our system is close to that of commercial systems. © 2024 IEEE.

关键词： Virtual environments

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Point-Multipoint Communication Scheduling in Industrial Internet: A Quick Survey 11

Point-Multipoint Communication Scheduling in Industrial Inte...

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11th International Conference on Advanced Cloud and Big Data, CBD 2023

作者： Chen, Yufeng Jiang, Ping Qu, Yida Wu, Mengqi Luo, Lu Yang, Ming Lu, Wenqian Southeast University School of Computer Science and Engineering School of Software Nanjing China China Telecom Nanjing Branch Nanjing China China Telecom Beijing China

ISBN: (纸本)9798350345346

The industrial Internet represents a significant innovation merging Internet technologies, big data, artificial intelligence, and advanced manufacturing, which is characterized by high technological and commercial value. Industrial communication systems need to satisfy precision manufacturing, including the expansive connections and tight requirements such as real time, determinism, and reliability. Hence, an efficient communication scheduling mechanism is essential. In contrast to conventional separate point-to-point (P2P) scheduling, point-to-multipoint multicasting and multipoint-to-point data aggregation are proven to be more effective in alleviating network congestion, enhancing throughput, and improving efficiency in the context of the ubiquitous point-to-multipoint communication in the industrial Internet. This paper focuses on communication in intra-datacenter and inter-datacenter subject to industrial quality of service (QoS) demands. Initially, we introduce a mathematic model for network and point-to-multipoint communication requests. Subsequently, we provide a comprehensive analysis of multicast route selection and traffic rate allocation algorithms that are deadline-aware and delay-aware. Additionally, we discuss the benefits of in-network data aggregation, including insights into aggregation pathways and aggregator placement algorithms, which are valuable for reference in data transfer scheduling in the industrial Internet. © 2023 IEEE.

关键词： Multicasting

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Research on performance optimization of virtual data space across WAN

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Frontiers of computer science 2024年第6期18卷 167-187页

作者： Jiantong HUO Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China

For the high-performance computing in a WAN environment,the geographical locations of national supercomputing centers are scattered and the network topology is complex,so it is difficult to form a unified view of *** aggregate the widely dispersed storage resources of national supercomputing centers in China,we have previously proposed a global virtual data space named GVDS in the project of“High Performance Computing Virtual Data Space”,a part of the National Key Research and Development Program of *** GVDS enables large-scale applications of the high-performance computing to run efficiently across ***,the applications running on the GVDS are often data-intensive,requiring large amounts of data from multiple supercomputing centers across *** this regard,the GVDS suffers from performance bottlenecks in data migration and access across *** solve the above-mentioned problem,this paper proposes a performance optimization framework of GVDS including the multitask-oriented data migration method and the request access-aware IO proxy resource allocation *** a WAN environment,the framework proposed in this paper can make an efficient migration decision based on the amount of migrated data and the number of multiple data sources,guaranteeing lower average migration latency when multiple data migration tasks are running in *** addition,it can ensure that the thread resource of the IO proxy node is fairly allocated among different types of requests(the IO proxy is a module of GVDS),so as to improve the application’s performance across *** experimental results show that the framework can effectively reduce the average data access delay of GVDS while improving the performance of the application greatly.

关键词： storage aggregation across WANs large-scale applications GVDS data migration allocation of IO proxy resource

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Investigating the Impact of Bug Dependencies on Bug-Fixing Time Prediction 17

Investigating the Impact of Bug Dependencies on Bug-Fixing T...

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17th ACM/IEEE International Symposium on Empirical software engineering and Measurement, ESEM 2023

作者： Li, Chenglin Zhao, Yangyang Yang, Yibiao Zhou, Yuming Nie, Liming Ding, Zuohua School of Computer Science and Technology Zhejiang Sci-Tech University Hangzhou China Nanjing University State Key Lab for Novel Software Technology Nanjing China School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781665452236

Background: Bug dependencies refer to the link relationships between bugs and related issues, which are commonly observed in software evolution. It has been found that bugs with bug dependencies often take longer time to be resolved than other bugs without any dependencies. Despite the potential impact of bug dependencies on bug-fixing time, previous studies use traditional metrics without considering bug dependencies to build bug-fixing time prediction models. As a result, there is currently little empirical evidence to support the use of bug dependencies in improving prediction accuracy. Aims: We aim to conduct a comprehensive empirical study to investigate the value of considering bug dependencies for bug-fixing time prediction. Method: We define a set of bug dependency metrics based on bug dependencies. We first investigate the correlation between bug dependency metrics and bug-fixing time to investigate whether bugs with more complex dependencies are more time-consuming to be fixed. Next, we employ principal component analysis to study whether bug dependency metrics capture additional dimensions of a bug compared to traditional metrics. Finally, we build multivariate prediction models to explore whether considering bug dependencies can improve the effectiveness of bug-fixing time prediction. Results: The experimental results suggest that: (1) bugs with more complex dependencies require more time to be fixed;(2) bug dependency metrics are complementary to traditional metrics;(3) considering bug dependencies can improve the effectiveness of bug-fixing time prediction. Conclusions: These findings highlight the importance of considering bug dependencies in bug-fixing time prediction, and provide valuable insights into the potential impact of bug dependencies on software development processes. © 2023 IEEE.

关键词： Principal component analysis

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VITS-Based Singing Voice Conversion System with DSPGAN Post-Processing for SVCC2023

VITS-Based Singing Voice Conversion System with DSPGAN Post-...

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2023 IEEE Automatic Speech Recognition and Understanding Workshop, ASRU 2023

作者： Zhou, Yiquan Chen, Meng Lei, Yi Zhu, Jihua Zhao, Weifeng Xi'an Jiaotong University School of Software Engineering Xi'an China School of Computer Science Xi'an China Tencent Music Entertainment Lyra Lab Shenzhen China

ISBN: (纸本)9798350306897

This paper presents the T02 team's system for the Singing Voice Conversion Challenge 2023 (SVCC2023). Our system entails a VITS-based SVC model, incorporating three modules: a feature extractor, a voice converter, and a postprocessor. Specifically, the feature extractor provides F0 contours and extracts speaker-independent linguistic content from the input singing voice by leveraging a HuBERT model. The voice converter is employed to recompose the speaker timbre, F0, and linguistic content to generate the waveform of the target speaker. Besides, to further improve the audio quality, a fine-tuned DSPGAN vocoder is introduced to resynthesise the waveform. Given the limited target speaker data, we utilize a two-stage training strategy to adapt the base model to the target speaker. During model adaptation, several tricks, such as data augmentation and joint training with auxiliary singer data, are involved. Official challenge results show that our system achieves superior performance, especially in the cross-domain task, ranking 1st and 2nd in naturalness and similarity, respectively. Further ablation justifies the effectiveness of our system design. © 2023 IEEE.

关键词： Linguistics

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General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action

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engineering 2024年第2期33卷 63-76页

作者： Heye Huang Yicong Liu Jinxin Liu Qisong Yang Jianqiang Wang David Abbink Arkady Zgonnikov School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China Department of Cognitive Robotics Faculty of MechanicalMaritime and Materials Engineering(3mE)Delft University of TechnologyDelft 2628Netherlands Department of Software Technology Faculty of Electrical EngineeringMathematics and Computer ScienceDelft University of TechnologyDelft 2628Netherlands Xi’an Institute of High-Technology Xi’an 710051China

This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and ***,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road *** coordinates are then transformed to achieve the curvature continuity of the generated *** the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate ***,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and *** simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic ***,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.

关键词： Autonomous vehicle Trajectory planning Multi-performance objectives Principle of least action

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A Neural Architecture Search Method with Multi-Dimensional Correlation Representation for Fault Diagnosis 9

A Neural Architecture Search Method with Multi-Dimensional C...

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9th IEEE Smart World Congress, SWC 2023

作者： Liu, Yumeng Wang, Tingqi Zheng, Xu Tian, Ling Wang, Hongan Institute of Software Chinese Academy of Sciences Beijing Key Laboratory of Human-Computer Interaction Beijing China University of Chinese Academy of Sciences School of Computer Science and Technology Beijing China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China

ISBN: (纸本)9798350319804

As deep learning has become more widely used for fault diagnosis, the shortcomings of model transferability and human model design costs are growing increasingly evident. The current work has tackled each of these two issues. Domain adaptation methods can provide transportability by mapping data to a common domain. For the consumption of manually constructed networks, Neural Architecture Search (NAS) is an intelligent solution that automatically select the ideal network structure. Unfortunately, there is little work to connect these two methodologies in fault diagnosis. Furthermore, these approaches are incapable in extracting internal correlations from instrumental signal data. In this paper, we propose a transferrable NAS fault diagnosis method, which maximizes savings in manual costs. We also integrate graph neural networks (GNN) in a stepwise manner into the NAS and domain adaptation to provide a multi-dimension correlation representation. Firstly, we structure the signal data into graph based on temporal relationships. Then, NAS designs automatically for selecting the optimal network structure and useful features. In NAS, graph encoder of GNN is used to establish internal relationships. Finally, domain adaptation provides transferability. At the same time, GNN's weights in domain adaptation help to further mine data internal associations. We tested our method on two publicly available datasets and performed comparisons. The experimental results show the proposed method has superior performance. © 2023 IEEE.

关键词： Domain Adaptation Fault Diagnosis Graph Neural Network Neural Architecture Search

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An Online Integrated Development Environment for Automated Programming Assessment Systems 17

An Online Integrated Development Environment for Automated P...

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17th International Conference on computer Supported Education, CSEDU 2025

作者： Frankford, Eduard Crazzolara, Daniel Vierhauser, Michael Meißner, Niklas Krusche, Stephan Breu, Ruth University of Innsbruck Department of Computer Science Austria University of Stuttgart Institute of Software Engineering Germany Technical University of Munich School of Computation Information and Technology Germany

ISBN: (纸本)9789897587467

The increasing demand for programmers has led to a surge in participants in programming courses, making it increasingly challenging for instructors to assess student code manually. As a result, automated programming assessment systems (APASs) have been developed to streamline this process. These APASs support lecturers by managing and evaluating student programming exercises at scale. However, these tools often do not provide feature-rich online editors compared to their traditional integrated development environments (IDEs) counterparts. This absence of key features, such as syntax highlighting and autocompletion, can negatively impact the learning experience, as these tools are crucial for effective coding practice. To address this gap, this research contributes to the field of programming education by extracting and defining requirements for an online IDE in an educational context and presenting a prototypical implementation of an open-source solution for a scalable and secure online IDE. The usability of the new online IDE was assessed using the Technology Acceptance Model (TAM), gathering feedback from 27 first-year students through a structured survey. In addition to these qualitative insights, quantitative measures such as memory (RAM) usage were evaluated to determine the efficiency and scalability of the tool under varying usage conditions. Copyright © 2025 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Teaching

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