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27th International Conference on Pattern Recognition, ICPR 2024

作者： Zheng, Xiaolong Wang, Jianming Xiao, Zhitao Sun, Yukuan School of Software Tiangong University Tianjin China Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems Tiangong University Tianjin China Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems Tiangong University Tianjin China Center for Engineering Intership and Training Tiangong University Tianjin China

ISBN: (纸本)9783031781063

Graph Neural Networks (GNNs) have shown great potential in visual tasks, yet they face challenges in effectively constructing and processing graphs. Vision GNN (ViG) was developed to tackle these issues by segmenting images into patches treated as nodes, with edges formed by connecting the nearest semantic neighbors. However, relying solely on semantic information for graph construction confines itself to a dispersed distribution of object neighbors, leading to inadequate graph processing. To address this issue, we propose Vision DualGNN(VDG), a novel dual graph neural network architecture that leverages both spatial and semantic information to construct and process graph representation of images. We apply a node encoder that transforms image patches into expressive node features. Additionally, we implement a dual-stream GNN that operates on both a spatial graph and a semantic graph. The spatial graph serves as a constraint for the semantic graph, enhancing the node features with spatial awareness. To verify the validity of our architecture, we have conducted our experiments on the ImageNet and CIFAR-100 datasets. And achieved state-of-the-art performance compared to other baseline models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： dualgnn graph convolution semantic graph spatial graph

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F-IKOS: An Abstract Interpretation-based Static Analyzer for Fortran Programs 12

F-IKOS: An Abstract Interpretation-based Static Analyzer for...

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12th International Workshop on Quantitative Approaches to software Quality, QuASoQ 2024

作者： Zou, Sheng Chen, Liqian Fan, Guangsheng Huang, Renjie Yin, Banghu College of Computer Science and Technology National University of Defense Technology Changsha410073 China State Key Laboratory of Complex & Critical Software Environment Changsha410073 China College of Systems Engineering National University of Defense Technology Changsha410073 China

The Fortran programming language is widely utilized in numerical computation and scientific computing. Fortran programs are prone to potential runtime errors related to numerical properties due to the large number of numerical operations. In this paper, we present F-IKOS, an abstract interpretation-based static analyzer for Fortran programs on top of IKOS, which soundly handles floating-point types in Fortran programs. Firstly, we translate Fortran programs to LLVM IR using compiler front-end Flang. After that, we extend IKOS to support sound floating-point analysis and then employ it to analyze the translated LLVM IR. Particularly, when analyzing floating-point types in programs, we first abstract floating-point expressions into real-number expressions with interval coefficients, and then linearize these expressions into real-number expressions with scalar coefficients. These linear expressions are subsequently handled by abstract domains originally designed for real-number types to produce sound analysis results. We have conducted experiments on representative Fortran programs to show the efficiency and effectiveness of F-IKOS. The experimental results are encouraging: F-IKOS soundly analyzes runtime errors in complex programs, outperforming other analyzers. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： FORTRAN (programming language)

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Policy Extraction and Optimization with Access Logs for Attribute-based Access Control

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第3期8卷 932-947页

作者： Sun, Wei Li, Long Hu, Ying School of Computer and Information Technology Xinyang Normal University Xinyang464000 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China Department of Electric Engineering Pacific Gas and Electric Company San Ramon94583 United States

The policy engineering technology based on attribute-based access control is commonly used to derive rules from the existing authorization information such as access logs. However, most conventional methods extract rules that do not support negative attribute expressions, and there are numerous redundant and inaccurate rules. This study proposes a novel policy-engineering method to extract and optimize the ABAC policy based on access logs. First, to enhance the policy interpretability while reducing the engineering scale, the clustering technology is utilized to partition access logs into different rule clusters, and an algorithm is presented to extract effective rules supporting both the positive and negative attribute conditions. Second, to guarantee the policy quality, an optimization algorithm is proposed to repeatedly correct the extracted rules according to different policy categories, which improves the policy accuracy and reduces the complexity of the policy engineering. Last, the evaluation criteria of the policy quality are presented based on principles of the correctness and conciseness, and the efficiency and effective-ness of the proposal are demonstrated through experiments. The experimental results show that compared to the existing studies, the proposed method not only enhances the policy interpretability but also guarantees the policy quality. © 2023, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Authorization

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Some New Methods to Generate Short Addition Chains

IACR Transactions on Cryptographic Hardware and Embedded Sys...

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IACR Transactions on Cryptographic Hardware and Embedded Systems 2023年第2期2023卷 270-285页

作者： Ding, Yuanchao Guo, Hua Guan, Yewei Song, Hutao Zhang, Xiyong Liu, Jianwei School of Cyber Science and Technology Beihang University Beijing China State Key Laboratory of Cryptology P.O. Box Beijing China State Key Laboratory of Software Development Environment Beihang University Beijing China Beijing Institute of Satellite Information Engineering Beijing China

Modular exponentiation and scalar multiplication are important operations in most public-key cryptosystems, and their efficient computation is essential to cryptosystems. The shortest addition chain is one of the most important mathematical concepts to realize the optimization of computation. However, finding a shortest addition chain of length r is generally regarded as an NP-hard problem, whose time complexity is comparable to O(r!). This paper proposes some novel methods to generate short addition chains. We firstly present a Simplified Power-tree method by deeply deleting the power-tree whose time complexity is reduced to O(r2). In this paper, a Cross Window method and its variant are introduced by improving the Window method. The Cross Window method uses the cross correlation to deal with the windows and its pre-computation is optimized by a new Addition Sequence Algorithm. The theoretical analysis is conducted to show the correctness and effectiveness. Meanwhile, our experiments show that the new methods can obtain shorter addition chains compared to the existing methods. The Cross Window method with the Addition Sequence algorithm can attain 44.74% and 9.51% reduction of the addition chain length, in the best case, compared to the Binary method and the Window method respectively. © 2023, Ruhr-University of Bochum. All rights reserved.

关键词： Optimization

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Design of PMCW Millimeter Wave Radar Algorithms on an Embedded DSP 16

Design of PMCW Millimeter Wave Radar Algorithms on an Embedd...

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16th International Conference on Signal Processing Systems, ICSPS 2024

作者： Zhao, Jinghao Liu, Qiuming Tan, Bin School of Software engineering Jiangxi University of Science and Technology Nanchang China Nanchang Key laboratory of Virtual Digital Factory and Cultural Communications Nanchang China Jiangxi Provincial Key Laboratory of Electronic Data Control and Forensics China School of Electronics and Information Engineering Jinggangshan University Ji’an China

ISBN: (纸本)9781510689251

The rapid advancements in autonomous driving technology necessitate the extensive deployment of automotive radars operating within the 77-81 GHz millimeter-wave band in the forthcoming years. In contrast to earlier Frequency Modulated Continuous Wave (FMCW) radars, Phase-Modulated Continuous Wave (PMCW) radars exhibit notable improvements in processing speed and flexibility, offering superior range and velocity resolution. These enhancements are critical for the precise detection and interpretation of dynamic and complex traffic scenarios. This paper initially presents the simulation and testing of algorithms for range and speed measurement using single-input single-output (SISO) PMCW millimeter-wave radar. Building upon these results, further simulations incorporating multi-input multi-output (MIMO) systems utilizing Hadamard codes are conducted to augment PMCW radar performance. The final phase of this study involves implementing the relevant signal processing algorithms on a custom-developed digital signal processor (DSP) named SWIFT. Experimental findings demonstrate that PMCW radar significantly mitigates multipath effects and clutter, maintaining high performance in complex environments. Furthermore, the algorithms executed on the DSP meet the anticipated performance standards. The proposed methodology not only validates the theoretical framework but also establishes a foundation for future hardware implementation. © 2025 SPIE.

关键词： Automotive radar

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Container-based data-intensive application scheduling in hybrid cloud-edge collaborative environment

Container-based data-intensive application scheduling in hyb...

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作者： Tang, Bing Luo, Jincheng Zhang, Jiaming School of Computer Science and Engineering Hunan University of Science and Technology Hunan Xiangtan China Hunan Key Laboratory for Service Computing and Novel Software Technology Hunan University of Science and Technology Hunan Xiangtan China School of Information and Communication Engineering Guangzhou Maritime University Guangdong Guangzhou China School of Information Engineering Wuhan University of Technology Hubei Wuhan China

Container virtualization technology represented by Docker has been widely used in the industry due to its advantages of lightweight, fast deployment, and easy portability. It can bring convenience to system deployment, operation, and maintenance. This article considers the implementation of AI-based IoT applications based on Docker and container technology in a cloud-edge collaborative environment. Three typical data-intensive applications, preprocessing, training, and inference in machine learning, are deployed using Docker containers. For these three types of tasks, this article proposes a container-based data-intensive application scheduling framework. Using an attribute-based data-driven method, a new scheduling approach considering multiple weighting factors is proposed, which is called DICS-OPT. The cloud nodes and edge nodes are scored and sorted uniformly. The container is scheduled to the node with the highest score, and then the task data is transmitted to the node to execute the task. NSGA-III-based genetic algorithm has been proposed to search for the optimal weighting factors. This article introduces the implementation of the prototype system and builds a cloud-edge collaborative testbed consisting of Raspberry Pis and PCs. The performance evaluation results indicates that the proposed scheduling approach outperforms existing approaches. Compared with existing approaches, DICS-OPT improves the average edge resource utilization by 10.05% to 69.04%, and saves the cloud resource cost by 16.02% to 36.68%. © 2023 John Wiley & Sons Ltd.

关键词： Edge computing

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Joint Optimization Clearing of Electro-hydrogen Coupling System for New Energy Consumption 4

Joint Optimization Clearing of Electro-hydrogen Coupling Sys...

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4th International Conference on Intelligent Power and Systems, ICIPS 2024

作者： Yang, Fan Wu, Hao Peng, Chen Wang, Weijie Zhang, Yajian Shanghai University School of Mechatronic Engineering and Automation China Sichuan University of Science & Engineering Artificial Intelligence Key Laboratory of Sichuan Province Yibin China Xuchang Xuji Software Technology Co. Ltd Xuchang China

ISBN: (纸本)9798331532765

In this study, a joint optimization clearing model of electro-hydrogen coupling system considering the uncertain output of new energy in electricity spot market has been proposed. Firstly, Monte-Carlo sampling and scenario reduction technologies are used to address real-time market price uncertainty. Secondly, a Cournot equilibrium model is constructed to maximize the profit of each market participant. Then, the nonlinear complementary method is used to solve the equilibrium results. Case studies have demonstrated that by optimizing the strategy of the electro-hydrogen coupling system and virtual bidding simultaneously. Meanwhile, the price gap between the day-ahead market and the real-time market can be effectively reduced, and the price of the electricity market can be more stable and reasonable. © 2024 IEEE.

关键词： Commerce

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TransRec++:Translation-based sequential recommendation with heterogeneous feedback

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Frontiers of Computer Science 2022年第2期16卷 190-192页

作者： Zhuo-Xin ZHAN Ming-Kai HE Wei-Ke PAN Zhong MING National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen 518060China College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China

1 Introduction Nowadays,recommender systems are widely used because of the information overload problem on the *** are a variety of feedback in recommender systems,such as explicit feedback,implicit feedback,sequential feedback,*** them,modeling of heterogeneous sequential feedback,which contains not only different types of feedback such as examinations and purchases but also the sequential information,is an emerging and important problem receiving more and more *** sequential feedback is relatively easy to be collected in a deployed system and is also able to provide more information than the homogeneous feedback,which is thus expected to be helpful in improving the recommendation accuracy.

关键词： feedback recommendation sequential

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Robust Classification of Similar Yoga Poses based on Grouping and Hierarchical Inference 6

Robust Classification of Similar Yoga Poses based on Groupin...

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6th International Conference on Multimedia Analysis and Pattern Recognition, MAPR 2023

作者： Huynh, Huu-Phuc Nguyen, Duc-Hung Nguyen, Thanh Thao-Ly Nguyen, Mai-Vinh Nguyen, Quang-Thuc University of Science VNU-HCM Vietnam National University Faculty of Information Technology and Software Engineering Laboratory Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350327410

The COVID-19 pandemic has had a negative impact on people's health, leading to an increased demand for self-improvement methods, such as Yoga. However, practicing Yoga without guidance is challenging due to the complexity of poses and the risk of injury. The authors propose a new method for classifying Yoga poses from images to address this issue. Although previous studies have achieved up to 99.33% accuracy, they involve only 3 classes, only a fraction of the 82 poses in the Yoga-82 dataset used in this study. We enhance a pre-trained DenseNet121 and achieve an accuracy of 88.89%, higher than the method by Verma ***. at CVPR workshop 2020, which reached 79.31%. Although data for training is just a subset of Yoga82 dataset, the model has less complexity, about 10 million parameters. Moreover, using a customized DenseNet121 model as a baseline, the authors enhanced its accuracy by incorporating a hierarchical structure and grouping data. Then, the authors proposed two methods, XGBoost and YOLOv5, working on parent labels to improve the accuracy of similar-looking poses and get a total accuracy of 87.33%. The approaches demonstrated in this paper could be applied to other sports or physical actions, indicating their potential for broader use. © 2023 IEEE.

关键词： COVID-19

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An Approach for Performance Calculation of AVS/RS in Multi-floor Workshop 3rd

An Approach for Performance Calculation of AVS/RS in Multi-f...

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3rd International Conference on Smart Manufacturing, Industrial and Logistics engineering, SMILE 2023 and the 7th Asian Conference of Management Science and Applications, ACMSA 2023

作者： Liu, Xiaopeng Wu, Cuiying Zhang, Baolin Xi, An Chen, Xuanrui Ministry of Industry and Information Technology Key Laboratory of Industrial Software Engineering Application Technology China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou510619 China School of Computer and Information Engineering Hanshan Normal University Guangdong Chaozhou521041 China

ISBN: (纸本)9789819701933

Warehouse management is an important part of the production process. As a result of the development of technology, more and more companies tend to use automated logistics technologies such as AVS/RS to handle the internal logistics of the production system. Especially in multi-floor workshops, the production process on each floor are connected with each other through AVS/RS. It is becoming more and more important to study the integration process of AVS/RS and multi-floor workshop production process. In this paper, an integrated queuing network model of multi-floor workshop and AVS/RS was established, and a calculation method of system performance index was proposed. The accuracy and efficiency of the proposed method are demonstrated by comparing the results with simulations from numerical experiments. The work of this article can provide a basis for the design of autonomous vehicle storage and retrieve systems in multi-floor workshop, and the calculation method can be used as the support of WMS technology base. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Floors

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