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Variable petri nets for mobility

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arXiv 2021年

作者： Ding, Zhijun Yang, Ru Cui, Puwen Zhou, MengChu Jiang, Changjun Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China Department of Computer Science and Technology Tongji University Shanghai201804 China Institute of Systems Engineering Macau University of Science and Technology Macau999078 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

Mobile computing systems, service-based systems and some other systems with mobile interacting components have recently received much attention. However, because of their characteristics such as mobility and disconnection, it is difficult to model and analyze them by using a structure-fixed model. This work proposes a new Petri net model called Variable Petri Net (VPN) for modeling and analyzing these systems. The definition, firing rule, and related analysis technology of VPN are introduced in detail. In a VPN, the possible interaction interfaces are abstracted as a new kind of places called virtual places, and the occurrences of (dis)connections are described by new functions, which makes it appropriate to describe the component collaboration in systems and realize the scalability and pluggability of systems. Moreover, to overcome the shortcoming that markings cannot reflect link capability of a system, VPNs add a constraint function along with a marking to represent a complete system configuration. Several examples are used to demonstrate the newly proposed model and method. Copyright © 2021, The Authors. All rights reserved.

关键词： Embedded systems

Modeling and analysis of three properties of mobile interactive systems based on variable Petri nets

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arXiv 2021年

作者： Yang, Ru Ding, Zhijun Jiang, Changjun Zhou, MengChu The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University The Department of Computer Science and Technology Tongji University Shanghai201804 China The Institute of Systems Engineering Macau University of Science and Technology 999078 China The Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

Due to the mobility and frequent disconnections, the correctness of mobile interaction systems, such as mobile robot systems and mobile payment systems, are often difficult to analyze. This paper introduces three critical properties of systems, called system connectivity, interaction soundness and data validity, and presents a related modeling and analysis method, based on a kind of Petri nets called VPN. For a given system, a model including component nets and interaction structure nets is constructed by using VPNs. The component net describes the internal process of each component, while the interaction structure net reflects the dynamic interaction between components. Based on this model, three properties are defined and analyzed. The case study of a practical mobile payment system shows the effectiveness of the proposed method. Copyright © 2021, The Authors. All rights reserved.

关键词： Petri nets

Follow Everything: A Leader-Following and Obstacle Avoidance Framework with Goal-Aware Adaptation

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arXiv 2025年

作者： Zhang, Qianyi Ma, Shijian Liu, Boyi Liu, Jingtai Jiao, Jianhao Kanoulas, Dimitrios Institute of Robotics and Automatic Information System Nankai University Tianjin300350 China Electrical and Computer Engineering Department Hong Kong University of Science and Technology China Centre for Data Science University of Macau China Department of Computer Science University College London United Kingdom

Robust and flexible leader-following is a critical capability for robots to integrate into human society. While existing methods struggle to generalize to leaders of arbitrary form and often fail when the leader temporarily leaves the robot’s field of view, this work introduces a unified framework addressing both challenges. First, traditional detection models are replaced with a segmentation model, allowing the leader to be anything. To enhance recognition robustness, a distance frame buffer is implemented that stores leader embeddings at multiple distances, accounting for the unique characteristics of leader-following tasks. Second, a goal-aware adaptation mechanism is designed to govern robot planning states based on the leader’s visibility and motion, complemented by a graph-based planner that generates candidate trajectories for each state, ensuring efficient following with obstacle avoidance. Simulations and real-world experiments with a legged robot follower and various leaders (human, ground robot, UAV, legged robot, stop sign) in both indoor and outdoor environments show competitive improvements in follow success rate, reduced visual loss duration, lower collision rate, and decreased leader-follower distance. Visit the website for the video and code. © 2025, CC BY.

关键词： Motion planning

A Novel Structure and Route Algorithm for Hybrid DCN Network Based on ExCCC-DCN

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A Novel Structure and Route Algorithm for Hybrid DCN Network...

Internet of Things and Intelligent Applications (ITIA), International Conference on

作者： Yujie Zhang Zhijie Han Yunfei Song School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China School of Computer and Information Engineering Henan University Kaifeng China System Engineering Institute Macau University of Science and Technology Macao China

ISBN: (数字)9781728193014

ISBN: (纸本)9781728193021

With the rapid development of data center network (DCN) technology, researchers have cleverly combined wireless connection and wired DCN to form a new structure, hybrid data center network (HDCN). Exchanged Cube-Connected Cycles (ExCCC) has high scalability and relatively low construction cost and operation energy consumption, which is very suitable for the deployment of large-scale data center. In this paper a novel hybrid ExCCC-DCN structure is proposed by combining the communication characteristics of 60GHz millimeter-wave technology. The transformed hybrid network not only inherits the original structural characteristics of ExCCC-DCN structure, but also effectively reduces the network data traffic and improves the network throughput. We divide the hybrid ExCCC-DCN into several units (pods), and propose a new cluster-based multicast routing algorithm. Comparative experiments prove that the algorithm can effectively reduce the number of multicast links and improve the data throughput during multicast communication when constructing a multicast tree.

关键词： Wireless communication Data centers Millimeter wave technology Millimeter wave communication Servers Routing Multicast algorithms

Meta-heuristic and MILP for Solving Urban Traffic Signal Control

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Meta-heuristic and MILP for Solving Urban Traffic Signal Con...

International Conference on Industrial engineering and systems Management (IESM)

作者： Kaizhou Gao Naiqi Wu Ren Wang School of Computer Liaocheng University Liaocheng China Macau Institute of System Engineering Macau University of Science and Technology Macau China

This paper studies the urban traffic light control problem. A model is proposed to describe the problem as an urban traffic light scheduling problem (UTLSP). The objective is to minimize total delay time of all vehicles in a fixed time window. To overcome the potentially high computational complexity involved in UTLSP, an improved artificial bee colony (IABC) algorithm, is proposed. Extensive computational experiments are carried out using sixteen instances. The IABC algorithm is compared to several meta-heuristics and standard solvers of the mixed integer linear programming (MILP) problem such as CPLEX. The comparisons and discussions show the competitiveness of IABC for solving UTLSP.

关键词： Task analysis Electroencephalography Electrodes Covariance matrices Feature extraction Speech recognition

Cross-receptive Focused Inference Network for Lightweight Image Super-Resolution

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arXiv 2022年

作者： Li, Wenjie Li, Juncheng Gao, Guangwei Deng, Weihong Zhou, Jiantao Yang, Jian Qi, Guo-Jun The Intelligent Visual Information Perception Laboratory Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210046 China The Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China The School of Communication and Information Engineering Shanghai University Shanghai200444 China Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing210094 China The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China The State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science Faculty of Science and Technology University of Macau 999078 China The School of Computer Science and Technology Nanjing University of Science and Technology Nanjing210094 China The Research Center for Industries of the Future The School of Engineering Westlake University Hangzhou310024 China OPPO Research SeattleWA98101 United States

Recently, Transformer-based methods have shown impressive performance in single image super-resolution (SISR) tasks due to the ability of global feature extraction. However, the capabilities of Transformers that need to incorporate contextual information to extract features dynamically are neglected. To address this issue, we propose a lightweight Cross-receptive Focused Inference Network (CFIN) that consists of a cascade of CT Blocks mixed with CNN and Transformer. Specifically, in the CT block, we first propose a CNN-based Cross-Scale Information Aggregation Module (CIAM) to enable the model to better focus on potentially helpful information to improve the efficiency of the Transformer phase. Then, we design a novel Cross-receptive Field Guided Transformer (CFGT) to enable the selection of contextual information required for reconstruction by using a modulated convolutional kernel that understands the current semantic information and exploits the information interaction within different self-attention. Extensive experiments have shown that our proposed CFIN can effectively reconstruct images using contextual information, and it can strike a good balance between computational cost and model performance as an efficient model. Source codes will be available at https://***/IVIPLab/CFIN. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study

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The Lancet Digital Health 2025年第5期7卷 100868页

作者： Meng, Ziyao Guan, Zhouyu Yu, Shujie Wu, Yilan Zhao, Yaoning Shen, Jie Lim, Cynthia Ciwei Chen, Tingli Yang, Dawei Ran, An Ran He, Feng Hamzah, Haslina Singh, Sarkaaj Abd Raof, Anis Syazwani Lee-Boey, Jian Wen Samuel Lim, Soo-Kun Sun, Xufang Ge, Shuwang Xu, Gang Su, Hua Cheng, Yang Lu, Feng Liao, Xiaofei Jin, Hai Deng, Chenxin Ruan, Lei Zhang, Cuntai Wu, Chan Dai, Rongping Jin, Yixiao Wang, Wenxiao Li, Tingyao Liu, Ruhan Li, Jiajia Shu, Jia Lu, Yuwei Wang, Xiangning Wu, Qiang Qin, Yiming Tang, Jin Sheng, Xiaohua Jiao, Qiong Yang, Xiaokang Guo, Minyi McKay, Gareth J Hogg, Ruth E Liew, Gerald Chee, Evelyn Yi Lyn Hsu, Wynne Lee, Mong Li Szeto, Simon Luk, Andrea O Y Chan, Juliana C N Cheung, Carol Y Tan, Gavin Siew Wei Tham, Yih-Chung Cheng, Ching-Yu Sabanayagam, Charumathi Lim, Lee-Ling Jia, Weiping Li, Huating Sheng, Bin Wong, Tien Yin Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Institute for Proactive Healthcare Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Centre for Diabetes Shanghai Key Laboratory of Diabetes Mellitus Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Beijing Tsinghua Changgung Hospital Eye Center School of Clinical Medicine Tsinghua Medicine Tsinghua University Beijing China Medical Records and Statistics Office Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Renal Medicine Singapore General Hospital SingHealth-Duke Academic Medical Centre Singapore Singapore Department of Ophthalmology Shanghai Health and Medical Center Wuxi China Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong Hong Kong Special Administrative Region China Singapore Eye Research Institute Singapore National Eye Centre Singapore Department of Medicine Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia Department of Ophthalmology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Hubei Wuhan China Department of Nephrology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Nephrology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Ophthalmology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China National Engineering Research Centre for Big Dat

Background: Improving the accessibility of screening diabetic kidney disease (DKD) and differentiating isolated diabetic nephropathy from non-diabetic kidney disease (NDKD) are two major challenges in the field of diabetes care. We aimed to develop and validate an artificial intelligence (AI) deep learning system to detect DKD and isolated diabetic nephropathy from retinal fundus images. Methods: In this population-based study, we developed a retinal image-based AI-deep learning system, DeepDKD, pretrained using 734 084 retinal fundus images. First, for DKD detection, we used 486 312 retinal images from 121 578 participants in the Shanghai Integrated Diabetes Prevention and Care system for development and internal validation, and ten multi-ethnic datasets from China, Singapore, Malaysia, Australia, and the UK (65 406 participants) for external validation. Second, to differentiate isolated diabetic nephropathy from NDKD, we used 1068 retinal images from 267 participants for development and internal validation, and three multi-ethnic datasets from China, Malaysia, and the UK (244 participants) for external validation. Finally, we conducted two proof-of-concept studies: a prospective real-world study with 3 months' follow-up to evaluate the effectiveness of DeepDKD in screening DKD;and a longitudinal analysis of the effectiveness of DeepDKD in differentiating isolated diabetic nephropathy from NDKD on renal function changes with 4·6 years' follow-up. Findings: For detecting DKD, DeepDKD achieved an area under the receiver operating characteristic curve (AUC) of 0·842 (95% CI 0·838–0·846) on the internal validation dataset and AUCs of 0·791–0·826 across external validation datasets. For differentiating isolated diabetic nephropathy from NDKD, DeepDKD achieved an AUC of 0·906 (0·825–0·966) on the internal validation dataset and AUCs of 0·733–0·844 across external validation datasets. In the prospective study, compared with the metadata model, DeepDKD could detect DKD wit

关键词： Deep learning

Enterotypes in the landscape of gut microbial community composition (vol 3, pg 8, 2017)

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NATURE MICROBIOLOGY 2018年第3期3卷 388-388页

作者： Costea, Paul I. Hildebrand, Falk Arumugam, Manimozhiyan Backhed, Fredrik Blaser, Martin J. Bushman, Frederic D. de Vos, Willem M. Ehrlich, S. Dusko Fraser, Claire M. Hattori, Masahira Huttenhower, Curtis Jeffery, Ian B. Knights, Dan Lewis, James D. Ley, Ruth E. Ochman, Howard O'Toole, Paul W. Quince, Christopher Relman, David A. Shanahan, Fergus Sunagawa, Shinichi Wang, Jun Weinstock, George M. Wu, Gary D. Zeller, Georg Zhao, Liping Raes, Jeroen Knight, Rob Bork, Peer European Molecular Biology Laboratory Heidelberg Germany. VIB Center for Microbiology VIB Belgium. Laboratory of Microbiology Vrije Universiteit Brussel Brussels Belgium. The Novo Nordisk Foundation Center for Basic Metabolic Research Faculty of Health and Medical Sciences University of Copenhagen Copenhagen Denmark. Wallenberg Laboratory Department of Molecular and Clinical Medicine Institute of Medicine Sahlgrenska Academy University of Gothenburg Gothenburg Sweden. Novo Nordisk Foundation Center for Basic Metabolic Research Section for Metabolic Receptology and Enteroendocrinology Faculty of Health Sciences University of Copenhagen Copenhagen Denmark. New York University Langone Medical Center New York NY USA. Department of Microbiology Perelman School of Medicine at the University of Pennsylvania Philadelphia PA USA. RPU Immunobiology Department of Bacteriology & Immunology University of Helsinki Helsinki Finland. Laboratory of Microbiology Wageningen University Wageningen The Netherlands. Metagenopolis Institut National de la Recherche Agronomique Jouy en Josas France. King's College London Centre for Host-Microbiome Interactions Dental Institute Central Office Guy's Hospital London UK. Institute for Genome Sciences at the University of Maryland School of Medicine Baltimore MD USA. Graduate School of Advanced Science and Engineering Waseda University Tokyo Japan. Department of Biostatistics Harvard School of Public Health Boston MA USA. APC Microbiome Institute University College Cork Cork Ireland. Biotechnology Institute University of Minnesota Saint Paul MN USA. Department of Computer Science and Engineering University of Minnesota Minneapolis MN USA. Center for Clinical Epidemiology and Biostatistics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. MPI Department of Microbiome Science Tübingen Germany. Department of Integrative Biology University of Texas Austin TX USA. Warwick Medical School University

Population stratification is a useful approach for a better understanding of complex biological problems in human health and wellbeing. The proposal that such stratification applies to the human gut microbiome, in the form of distinct community composition types termed enterotypes, has been met with both excitement and controversy. In view of accumulated data and re-analyses since the original work, we revisit the concept of enterotypes, discuss different methods of dividing up the landscape of possible microbiome configurations, and put these concepts into functional, ecological and medical contexts. As enterotypes are of use in describing the gut microbial community landscape and may become relevant in clinical practice, we aim to reconcile differing views and encourage a balanced application of the concept.

关键词： Community composition landscapes

Response Policies to Process Module Failure in Single-Arm Cluster Tools Subject to Wafer Residency Time Constraints

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Response Policies to Process Module Failure in Single-Arm Cl...

作者： Qiao, Yan Pan, Chun-Rong Wu, Nai-Qi Zhou, Mengchu Department of Industrial Engineering School of Electro-Mechanical Engineering Guangdong University of Technology Guangzhou510006 China School of Mechatronics and Electrical Engineering Jiangxi University of Science and Technology Ganzhou341000 China Institute of Systems Engineering Macau University of Science and Technology Taipa China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102-1982 United States

In semiconductor manufacturing, wafer residency time constraints make the scheduling problem of cluster tools complicated. A process module (PM) in cluster tools is prone to failure. It is crucial to deal with any such failure in a proper and timely manner. If there are feasible periodic schedules in operating a cluster tool before and after a PM failure, it is desired to make it operate continuously when such a failure occurs. However, due to wafer residency time constraints, it is highly challenging to control a tool such that it can be correctly transferred from a feasible schedule before failure to another after it. To solve this problem, a Petri net model is developed to describe the dynamic behavior of a single-arm cluster tool and failure response policies are proposed. The proposed policies are formulated via simple control laws for their easy implementation. Examples are given to show them. © 2015 IEEE.

关键词： Scheduling