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检索条件"机构=Systems and Software Development Laboratory"

共 221 条记录，以下是11-20 订阅

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Diving into Continual Ultra-fine-grained Visual Categorization

Diving into Continual Ultra-fine-grained Visual Categorizati...

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2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023

作者： Zhang, Pengcheng Yu, Xiaohan Bai, Xiao Zheng, Jin Wu, Xiaoyu Gao, Yongsheng Beihang University School of Computer Science and Engineering State Key Laboratory of Software Development Environment Jiangxi Research Institute Beijing China Griffith University Institute for Integrated and Intelligent Systems Nathan4111 Australia

ISBN: (纸本)9798350382204

Recent advance in ultra-fine-grained visual categorization (ultra-FGVC) has significantly boosted the capability of deep neural networks for ultra-FGVC tasks. However, building models for continually learning to recognize increasing ultra-fine-grained categories is still under-explored. This limits the application of ultra-FGVC techniques in real-world production. To this, we take the first attempt for continual ultra-FGVC. By evaluating existing continual learning methods on the constructed continual ultra-FGVC benchmark, we observe that the main bottleneck lies in the limited model plasticity for incrementally adapting to new tasks. This can be caused by excessive anti-forgetting constraints as the difficult ultra-FGVC task requires substantial update of parameters, and over-fitting on early tasks given that the ultra-fine-grained categories are with very few training samples. To tackle these problems, we propose a joint self-supervised learning and prompting model. The prompt-based continual learning framework offers proper anti-forgetting operation by fixed pretrained vision transformer and adaptive prompt selection. By jointly optimizing the learnable prompts with an adversarial self-supervised loss, the over-fitting on each continual learning task is mitigated. Extensive experiments demonstrate that the proposed method outperforms existing continual learning methods on the challenging continual ultra-FGVC problem. © 2023 IEEE.

关键词： Deep neural networks

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The Power of Age-based Reward in Fresh Information Acquisition 42

The Power of Age-based Reward in Fresh Information Acquisiti...

引用

42nd IEEE International Conference on Computer Communications, INFOCOM 2023

作者： Wang, Zhiyuan Meng, Qingkai Zhang, Shan Luo, Hongbin Beihang University School of Computer Science and Engineering Beijing China Beihang University State Key Laboratory of Virtual Reality Technology and Systems China Beihang University Institute of Artificial Intelligence Beijing China State Key Laboratory of Software Development Environment China

ISBN: (纸本)9798350334142

Many Internet platforms collect fresh information of various points of interest (PoIs) relying on users who happen to be nearby the PoIs. The platform will offer reward to incentivize users and compensate their costs incurred from information acquisition. In practice, the user cost (and its distribution) is hidden to the platform, thus it is challenging to determine the optimal reward. In this paper, we investigate how the platform dynamically rewards the users, aiming to jointly reduce the age of information (AoI) and the operational expenditure (OpEx). Due to the hidden cost distribution, this is an online non-convex learning problem with partial feedback. To overcome the challenge, we first design an age-based rewarding scheme, which decouples the OpEx from the unknown cost distribution and enables the platform to accurately control its OpEx. We then take advantage of the age-based rewarding scheme and propose an exponentially discretizing and learning (EDAL) policy for platform operation. We prove that the EDAL policy performs asymptotically as well as the optimal decision (derived based on the cost distribution). Simulation results show that the age-based rewarding scheme protects the platform's OpEx from the influence of the user characteristics, and verify the asymptotic optimality of the EDAL policy. © 2023 IEEE.

关键词： Simulation platform

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Research on Energy-Saving Optimization of Different Formation Configurations Based on Four Catamarans 30th

Research on Energy-Saving Optimization of Different Formatio...

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30th International Conference on Computational and Experimental Engineering and Sciences, ICCES 2024

作者： Jiang, Bo Liang, Xu Wang, Longkan Zhang, Zhifan Wang, Yuemei State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment School of Naval Architecture Engineering Dalian University of Technology Dalian116024 China CSSC Systems Engineering Research Institute Beijing100080 China China Ship Research and Development Academy Beijing100192 China

ISBN: (纸本)9783031687747

Nowadays, sailing in formation has been the major trend with the rise of unmanned ships. In the past, research about unmanned catamaran formation were more focused on algorithmic control, but the changes in hydrodynamic performance and energy are often overlooked. In nature, various collective behaviors indicate that followers would obtain significant energy consumption from beneficial interaction in certain formation configurations. Based on the previous research, the high-speed catamaran delft-372 was chosen as the basic numerical model in this paper. Four ship’s formation configurations (tandem, "trimaran", and rectangle formations) are proposed to analyze the influence on the hydrodynamic performance of each ship, based on the Reynolds Averaged Navier-Stokes (RANS) method in combination with the Shear Stress Transport (SST) k-ω turbulence model. Through comparative analysis, it can be seen that the resistance and motion of the following ships have been optimized under specific formation configurations, but the impact of various formation configurations is quite different. In terms of single ship’s energy preservation, the last following ship of "trimaran" formation has the best performance. For the whole, tandem formation is the optimal fleet configuration. In conclusion, the hydrodynamic performance of four catamarans in different formation configurations has been studied, which can provide some reference significance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Drag reduction

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Smart Contract Service Optimization in Blockchain-Cloud Collaborative Computing 24

Smart Contract Service Optimization in Blockchain-Cloud Coll...

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24th IEEE International Conference on Mobile Data Management, MDM 2023

作者： Wan, Ji Hu, Kai Li, Jie Su, Hao Wu, Qingshun Li, Mingyuan Feng, Libo Pan, Yan Beihang University State Key Laboratory of Software Development Environment Beijing China Beihang Yunnan Innovation Institute Yunnan Key Laboratory of Blockchain Application Technology Kunming China Zhengzhou University School of Computer and Artificial Intelligence Zhengzhou China The First Affiliated Hospital of Zhengzhou University Zhengzhou China Yunnan University National Pilot School of Software Kunming China China Industrial Control Systems Cyber Emergency Response Team Institute of Software Beijing China

ISBN: (纸本)9798350341010

Smart contract is a trusted service provided on the blockchain, while cloud service is a traditional service mode with a large number of resources. The combination of the blockchain and cloud service is of great significance to the trusted expansion of services and the access to services inside and outside the blockchain. In this paper, we study the smart contract extension service in blockchain-cloud collaborative computing. The service module decoupling method of smart contract is proposed, and the parallel execution algorithm of smart contract service is designed, which improves the execution efficiency of smart contract service. Finally, this paper designs a secure data interaction method of smart contract and cloud service, which helps to maintain the data consistency between cloud computing and blockchain. The experimental results show that the proposed method can save at most 42.13% of the running time, and it can promote the data consistency between the cloud service and the blockchain. © 2023 IEEE.

关键词： Smart contract

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Tightly-Coupled Lidar-Based Lifelong Mapping using Wheels and a MEMS Gyroscope for Mobile Robots in Dynamic Environment 24

Tightly-Coupled Lidar-Based Lifelong Mapping using Wheels an...

引用

3rd International Symposium on Robotics, Artificial Intelligence and Information Engineering, RAIIE 2024

作者： Hu, Lizhi Chen, Huilin Li, Xiang Lu, Wei Zhao, Yifan Hu, Songyu Navigation and Localization Algorithm Department Zhejiang HuaRay Technology Co. Lt. Hangzhou China Software Research and Development Center Zhejiang HuaRay Technology Co. Lt. Hangzhou China State Key Laboratory of Fluid Power and Mechatronic Systems College of Mechanical Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9798400718311

Localization and mapping technology of mobile robots is important in production and warehousing. The changing warehousing environment always result in poor accuracy and robustness of the mobile robot's localization. It is necessary to detect the degree of environmental changes and update the map. This paper proposes a novel lifelong mapping method fusing measurements from the lidar, wheels and a MEMS gyroscope, which can create a reliable map corresponding to the current working environment. Firstly, we use the wheels and gyroscopes measures for pre-integration to provide relative motion constraints, while integrating wheels and gyroscopes to provide initial pose for lidar matching. We also establish lidar odometry by submaps to provide another type of relative motion constraints. The absolute constraints are obtained by matching the lidar measurements with prior map. These three types of constraints are optimized in a factor graph. At the same time, during the process of updating the map, detect newly added artificial markers such as reflective columns or strips, and update them into the map timely. Then, in order to delete redundant lidar data keyframes for building map, we propose a determine redundancy method based on submaps. Finally, we propose a method for calculating the degree of map changes, which can update the map timely. Experimental results prove that our method can establish higher quality maps, optimize lidar external parameters timely during the mapping process, delete redundant lidar keyframes more efficiently, and update the current environmental map more accurately and timely. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Gyroscopes

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How to Route CUBIC and BBR Packets in Space

How to Route CUBIC and BBR Packets in Space

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International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Shuo Huang Zhiyuan Wang Wenhao Lu Kai Shen Jiayi Zhang Shan Zhang Hongbin Luo School of Computer Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beijing China State Key Laboratory of Software Development Environment Beijing China

ISBN: (数字)9783903176652

ISBN: (纸本)9798331508722

Low-earth-orbit satellite constellation (e.g., Starlink) is becoming the indispensable component of future Internet. Due to the mobility nature, ground-satellite links (GSLs) and inter-satellite links (ISLs) are not as stable as the fiber links of wired Internet. Consequently, end-to-end TCP connections traversing the LEO constellation will suffer from packet loss and latency variation caused by GSL handover and ISL failure. However, typical congestion control algorithms (e.g., loss-based CUBIC and bandwidth-estimated BBR) rely on these feedbacks to detect congestion in wired Internet. This leads to performance degradation for CUBIC/BBR in LEO satellite networks. In this paper, we propose a Default-and-Backup Routing (DB-R) mechanism to enhance the performance of CUBIC/BBR in LEO satellite networks. Specifically, DB-R leverages default routing to address the packet loss caused by frequent GSL handover. Moreover, DB- R utilizes backup routing to eliminate the packet loss caused by occasional ISL failure. Overall, DB-R only incurs negligible control overhead, but can effectively improve the performance of CUBIC and BBR in LEO satellite networks. We implement DB-R in Linux kernel and evaluate its performance based on OpenSN (i.e., an open-source libarary for emulating LEO satellite networks). Results show that our DB-R mechanism can improve the average throughput of CUBIC (and BBR, respectively) by up to 37 % (and 18 %, respectively) compared with classic OSPF.

关键词： Satellites Linux Wireless networks Low earth orbit satellites Packet loss Handover Routing Throughput Internet Kernel

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GAN-based EEG Forecasting for Attaining Driving Operations

GAN-based EEG Forecasting for Attaining Driving Operations

引用

IEEE Symposium on Intelligent Vehicle

作者： Kenichi Takasaki Yuka Sasaki Shoichiro Watanabe Yasutaka Nishimura Mari Abe Tokyo Software & Systems Development Laboratory IBM Japan Ltd. Tokyo Japan Product Engineering MODE Inc. Tokyo Japan

In the domain of connected vehicles or advanced driver assistance systems, electroencephalogram (EEG) data is measured in vehicles and used for applications in driver safety. These analysis modules are designed to detect abnormal driver states such as drowsiness, fatigue, and dangerous driving by using EEG data in real-time on edge devices since these conditions reflect a driver’s current cognitive state. However, there are few approaches to forecasting EEG data to prevent dangerous driving in advance using recent deep learning techniques. In this paper, we propose a novel generative adversarial network (W-GAN) which aims to forecast EEGs as a multivariate multi-step times series data. It consists of dilated causal convolutional layers to maintain EEG characteristics. We also propose a new performance measure reflecting the reproducibility of frequency components which confirms the feasibility of the forecasted EEG data. We conducted an experiment to evaluate our proposed model using EEG analysis research data. In the experiment, it was shown that our model outperformed several deep learning models in reproducibility of both EEG waveform and frequency components.

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Load-Aware Hierarchical Information-Centric Routing for Large-Scale LEO Satellite Networks

Load-Aware Hierarchical Information-Centric Routing for Larg...

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IEEE Conference on Wireless Communications and Networking

作者： Fei Yan Zhiyuan Wang Shan Zhang Qingkai Meng Hongbin Luo School of Computer Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beijing China State Key Laboratory of Software Development Environment Beijing China Institute of Artificial Intelligence Beihang University Beijing China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

The emerging large-scale low earth orbit (LEO) constellation is expected to provide global Internet services. However, large-scale satellite networks meet the challenges of topology dynamics and continuous traffic variation. This paper proposes LoHi, a Load-aware Hierarchical Information-centric (LoHi) Routing Protocol based on constellation Partitioning and logic path identifier (PID), to address the above challenges. Specifically, LoHi divides a constellation into satellite groups and only keeps track of the inter-satellite link (ISL) state within each group instead of the entire constellation, stabilizing global routing. Moreover, LoHi adopts the PID to denote the logic connectivity of adjacent satellite groups, which corresponds to multiple physical ISLs. Accordingly, the hierarchical multipath routing is calculated based on the inner-group and inter-group connectivity information. Furthermore, LoHi adjusts forwarding decisions according to the real-time traffic load on the ISL and group-level inter-group paths to reduce packet drop and queuing delay in a hierarchical pattern. Packet-level experiment results show that LoHi achieves a higher packet delivery ratio than the state-of-the-art mechanisms (up to 132.12%).

关键词： Satellites Web and internet services Low earth orbit satellites Telecommunication traffic Routing Throughput Routing protocols

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software fault localization based on eigenvector centrality in complex network theory

Software fault localization based on eigenvector centrality ...

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IEEE International Conference on software Quality, Reliability and Security Companion (QRS-C)

作者： Wentao Wu Shihai Wang Yuanxun Shao Wandong Xie School of Reliability and Systems Engineering Beihang University Beijing China Science and Technology on Reliability and Environmental Engineering Laboratory China State Key Laboratory of Software Development Environment China Aerospace Science and Engineering Network Information development CO. LTD Beijing China Information Center of China North Industries Group Corporation Beijing China

ISBN: (数字)9798350365658

ISBN: (纸本)9798350365665

software debugging plays a crucial role in fault localization tasks, and spectrum-based fault localization (SBFL) is a hot topic in software automation debugging research. However, existing SBFL technologies are generally limited by tie within ranks, where a large number of elements share the same suspiciousness, which in turn severely limits the performance of SBFL. To this end, we propose an SBFL model based on eigenvector centrality (FLEC). This algorithm first utilizes the statement coverage information in the program spectrum to construct a statement network, and adopts the correlation between statements as edge weights. Then, FLEC takes statement suspiciousness as node weight. On this basis, the algorithm utilizes the eigenvector centrality to calculate the weighted suspiciousness of each statement while considering both node importance and correlation between nodes. Finally, FLEC conducted experimental validation on 3 datasets of Defects4J, and the results showed an average improvement of 10.7% in ACC@N compared to the optimal baseline.

关键词： Location awareness Correlation software algorithms software quality Debugging Complex networks Reliability engineering software reliability Security software debugging

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Computer-Vision-Based Non-Contact Paste Concentration Measurement*

Computer-Vision-Based Non-Contact Paste Concentration Measur...

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Automation in Manufacturing, Transportation and Logistics (ICaMaL), International Conference on

作者： Tailin Liang Zhaolin Yuan State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing China Department of Industrial and Systems Engineering Research Institute of Advanced Manufacturing The Hong Kong Polytechnic University Hong Kong China

ISBN: (数字)9798350378658

ISBN: (纸本)9798350378665

For monitoring the paste concentration, existing techniques, such as ultrasonic concentration meters and neutron meters, suffer from radiation hazards and low precision in high concentrations. This paper proposes a novel non-contact concentration measurement method based on deep learning. With the dataset collected by preparing the paste with different concentrations and taking photographs from the paste surface, a convolutional neural network is trained to extract the features from images and predict the concentration. The experiments indicate that the measurement accuracy is close to 88.79 % for the manual stirring paste dataset and 91.42 % for the automatic stirring paste dataset, which are sufficient in industrial applications. As a substitution of traditional concentration measurement instruments, the proposed vision-based concentration measurement method is non-contact and its accuracy is sufficient in industrial applications.

关键词： Meters Deep learning Accuracy Ultrasonic variables measurement Transportation Manuals Feature extraction Surface texture Convolutional neural networks Surface treatment

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