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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： He, Yuwen Wang, Wei Wu, Wanyu Jiang, Kui Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology China School of Computer Science and Technology Harbin Institute of Technology China

ISBN: (纸本)157735897X

Lens flares arise from light reflection and refraction within sensor arrays, whose diverse types include glow, veiling glare, reflective flare and so on. Existing methods are specialized for one specific type only, and overlook the simultaneous occurrence of multiple typed lens flares, which is common in the real-world, e.g. coexistence of glow and displacement reflections from the same light source. These co-occurring lens flares cannot be effectively resolved by the simple combination of individual flare removal methods, since these coexisting flares originates from the same light source and are generated simultaneously within the same sensor array, exhibit a complex interdependence rather than simple additive relation. To model this interdependent flares’ relationship, our Nighttime Lens Flare Formation model is the first attempt to learn the intrinsic physical relationship between flares on the imaging plane. Building on this physical model, we introduce a solution to this joint flare removal task named Self-supervised Generation-based Lens Flare Removal Network (SGLFR-Net), which is self-supervised without pre-training. Specifically, the nighttime glow is detangled in PSF Rendering Network(PSFR-Net) based on PSF Rendering Prior, while the reflective flare is modelled in Texture Prior Based Reflection Flare Removal Network (TPRR-Net). Empirical evaluations demonstrate the effectiveness of the proposed method in both joint and individual glare removal tasks. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Luminescent devices

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Spatiotemporal distance embedded hybrid ant colony algorithm for a kind of vehicle routing problem with constraints

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Frontiers of information Technology & Electronic Engineering 2023年第7期24卷 1062-1079页

作者： Zhenhui FENG Renbin XIAO School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Institute of Artificial Intelligence Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Information Processing and Intelligent Control Ministry of EducationWuhan 430074China

We investigate a kind of vehicle routing problem with constraints(VRPC)in the car-sharing mobility environment,where the problem is based on user orders,and each order has a reservation time limit and two location point transitions,origin and *** is a typical extended vehicle routing problem(VRP)with both time and space *** consider the VRPC problem characteristics and establish a vehicle scheduling model to minimize operating costs and maximize user(or passenger)*** solve the scheduling model more accurately,a spatiotemporal distance representation function is defined based on the temporal and spatial properties of the customer,and a spatiotemporal distance embedded hybrid ant colony algorithm(HACA-ST)is *** algorithm can be divided into two ***,through spatiotemporal clustering,the spatiotemporal distance between users is the main measure used to classify customers in categories,which helps provide heuristic information for problem ***,an improved ant colony algorithm(ACO)is proposed to optimize the solution by combining a labor division strategy and the spatiotemporal distance function to obtain the final scheduling *** analysis is carried out based on existing data sets and simulated urban *** with other heuristic algorithms,HACA-ST reduces the length of the shortest route by 2%–14%in benchmark *** VRPC testing instances,concerning the combined cost,HACA-ST has competitive cost compared to existing VRP-related ***,we provide two actual urban scenarios to further verify the effectiveness of the proposed algorithm.

关键词： Vehicle routing problem with constraints(VRPC) Spatiotemporal distance function Labor division strategy Ant colony algorithm(ACO)

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Autonomous Navigation for Mobile Robots with Weakly-Supervised Segmentation Network

Autonomous Navigation for Mobile Robots with Weakly-Supervis...

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IEEE Conference on Vehicular Technology (VTC)

作者： Peinan Huang Jialun Li Jianping He Dept. of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665454698

This paper investigates autonomous navigation for mobile robots with a low-cost monocular camera. The main challenge lies in: i) how to accurately detect prior unseen obstacles and acquire obstacles position from monocular images without depth information, and ii) how to get the constraints for path planning to generate safe and stable path for the robot. To accurately locate surrounding obstacles using only a monocular camera, we adopt a weakly-supervised semantic segmentation network trained from LIDAR data and perform inverse perspective transformation based on ground plane constraint. Meanwhile, to reduce segmentation noise, we establish a probability occupancy map based on the distance between robot and obstacles. For path generations, we present a novel search-and-optimization based planning approach to get boundary constraints in Frenet frame and generate stable local path with consecutive image inputs. In the simulation, segmentation Intersection over Union (IoU) of the drivable area achieves more than 99% and the average mapping accuracy is less than 10cm, showing feasibility and robustness of our navigation scheme.

关键词： Training Navigation Semantic segmentation Robot vision systems Cameras Path planning Stability analysis

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BEYOND CORRECTNESS: BENCHMARKING MULTIDIMENSIONAL CODE GENERATION FOR LARGE LANGUAGE MODELS

arXiv

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arXiv 2024年

作者： Zheng, Jiasheng Cao, Boxi Ma, Zhengzhao Pan, Ruotong Lin, Hongyu Lu, Yaojie Han, Xianpei Sun, Le Chinese Information Processing Laboratory China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Key Laboratory of System Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

In recent years, researchers have proposed numerous benchmarks to evaluate the impressive coding capabilities of large language models (LLMs). However, current benchmarks primarily assess the accuracy of LLM-generated code, while neglecting other critical dimensions that also significantly impact code quality in real-world development. Moreover, relying exclusively on correctness as the guiding metric renders LLMs susceptible to data contamination. Therefore, this paper proposes the RACE benchmark, which comprehensively evaluates the quality of code generated by LLMs across 4 dimensions: Readability, mAintainability, Correctness, and Efficiency. Specifically, considering the demand-dependent nature of dimensions beyond correctness, we design various types of user requirements for each dimension to assess the model’s ability to generate correct code that also meets user demands. We analyze 28 representative LLMs based on RACE and find that: 1) current correctness-centric benchmarks fail to capture the multifaceted requirements of code in real-world scenarios, while RACE provides a comprehensive evaluation that reveals the defects of LLMs across multiple dimensions;2) the RACE benchmark serves as an effective tool for resisting the risk of data contamination;3) even the most advanced code LLMs still encounter significant challenges in customized requirements involving complex instructions;4) most LLMs exhibit an inherent preference for specific coding style. These findings highlight the need for a multidimensional evaluation of code LLMs, emphasizing metrics beyond correctness for real-world applications. Future efforts should aim to develop novel learning algorithms to enhance code generation under varied constraints and improve coverage and usability for diverse user needs1 Copyright © 2024, The Authors. All rights reserved.

关键词： Risk perception

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Jointly Learning Time-Structure-History Graph Embedding for Temporal Knowledge Graph Reasoning

Jointly Learning Time-Structure-History Graph Embedding for ...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Hao Duan Haoyu Jin Kang Chen Shaochong Du Tao Fang Hong Huo Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

The Temporal Knowledge Graph(TKG) reasoning is an imperative task for various applications of TKG. However, reasoning over TKGs which aims to predict future facts has been less explored. Intuitively, entities and relations in TKG change differently over time, and the variations are different. It also can be observed that what happens in the past may affect the future. Apart from these, structure information that exists in the neighborhood of a given entity in a KG has been proven to be important. Inspired by these, a novel graph embedding method for TKG reasoning, called time-structure-history graph embedding (TSHGE), is proposed in this paper. TSHGE consists of three progressive learning units. The first time information learning unit employs a novel time-aware mechanism to encode the time influence on entities and relations. Then a relation-aware GAT (Graph Attention Network) is used in the structure information learning unit to model the 1-hop neighborhoods of all entities in a KG at each timestamp in TKG. Finally, the history information learning unit utilizes GRU (Gated Recurrent Unit) to learn history information from various facts. Then the ultimate embedding representations of entities and relations can be obtained for the prediction of future facts. The evaluations on three public TKG datasets have demonstrated the effectiveness and superiority of TSHGE for predicting future facts.

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A Unified Framework for Verification of Observational Properties for Partially-Observed Discrete-Event systems

arXiv

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arXiv 2022年

作者： Zhao, Jianing Yin, Xiang Li, Shaoyuan Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing the Ministry of Education of China Shanghai200240 China

In this paper, we investigate property verification problems in partially-observed discrete-event systems (DES). Particularly, we are interested in verifying observational properties that are related to the information-flow of the system. Observational properties considered here include diagnosability, predictability, detectability and opacity, which have drawn considerable attentions in the literature. However, in contrast to existing results, where different verification procedures are developed for different properties case-by-case, in this work, we provide a unified framework for verifying all these properties by reducing each of them as an instance of HyperLTL model checking. Our approach is based on the construction of a Kripke structure that effectively captures the issue of unobservability as well as the finite string semantics in partially-observed DES so that HyperLTL model checking techniques can be suitably applied. Then for each observational property considered, we explicitly provide the HyperLTL formula to be checked over the Kripke structure for the purpose of verification. Our approach is uniform in the sense that all different properties can be verified with the same model checking engine. Furthermore, our unified framework also brings new insights for classifying observational properties for partially-observed DES in terms of their verification complexity. Copyright © 2022, The Authors. All rights reserved.

关键词： Discrete event simulation

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Robust sliding model predictive control with disturbance compensation in application to AUV pitch-axis motion

Robust sliding model predictive control with disturbance com...

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第34届中国控制与决策会议

作者： Jiuwu Hui Jingqi Yuan State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment Department of Automation and the Key Laboratory of System Control and Information Processing/Ministry of EducationShanghai Jiao Tong University

Constraints on the control input and system states as well as uncertain disturbances are the practical challenges in many motion control *** this paper,a disturbance observer(DO) with two-step disturbance compensation algorithm is proposed to deal with disturbances and enhance the robustness of the controller,while a discrete sliding mode predictive control(DSMPC) scheme is designed to handle saturation constraints on the control input and system states with the application to an autonomous underwater vehicle(AUV).The DSMPC combines the model predictive control(MPC) with the discrete sliding mode control(DSMC) using linear matrix inequalities *** stability of the proposed DSMPC are proved via Lyapunov stability ***,simulation results are presented to illustrate the effectiveness of the whole control scheme.

关键词： Disturbance observer Two-step compensation algorithm Discrete sliding mode predictive control Inequality constraints and AUV pitch-axis motion control

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Clinical characteristics and outcomes of hospitalized kidney transplant recipients with COVID-19 infection in China during the Omicron wave:a single-center cohort study

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2024年第6期25卷 529-540页

作者： Duo LV Xishao XIE Qinyun YANG Zhimin CHEN Guangjun LIU Wenhan PENG Rending WANG Hongfeng HUANG Jianghua CHEN Jianyong WU Department of Clinical Pharmacy the First Affiliated HospitalZhejiang University School of MedicineHangzhou 310003China Zhejiang Provincial Key Laboratory for Drug Evaluation and Clinical Research Hangzhou 310003China Kidney Disease Center the First Affiliated HospitalZhejiang University School of MedicineHangzhou 310003China Key Laboratory of Kidney Disease Prevention and Control Technology Zhejiang ProvinceHangzhou 310003China Institute of Nephrology Zhejiang UniversityHangzhou 310003China Zhejiang Clinical Research Center of Kidney and Urinary System Disease Hangzhou 310003China The Third Grade Laboratory under the National State Administration of Traditional Chinese MedicineHangzhou 310003China Information Center the First Affiliated HospitalZhejiang University School of MedicineHangzhou 310003China

Background:Following the short-term outbreak of coronavirus disease 2019(COVID-19)in December 2022 in China,clinical data on kidney transplant recipients(KTRs)with COVID-19 are ***:We conducted a single-center retrospective study to describe the clinical features,complications,and mortality rates of hospitalized KTRs infected with COVID-19 between Dec.16,2022 and Jan.31,*** patients were followed up until Mar.31,***:A total of 324 KTRs with COVID-19 were *** median age was 49 *** median time between the onset of symptoms and admission was 13 ***,azvudine,and nirmatrelvir/ritonavir were administered to 67(20.7%),11(3.4%),and 148(45.7%)patients,***-nine(9.0%)patients were treated with more than one antiviral ***-eight(14.8%)patients were treated with tocilizumab and 53(16.4%)patients received baricitinib *** acute kidney injury(AKI)occurred in 81(25.0%)patients and 39(12.0%)patients were admitted to intensive care *** infections were observed in 55(17.0%)***(15.4%)patients lost their *** 28-d mortality rate of patients was 9.0%and 42(13.0%)patients died by the end of *** Cox regression analysis identified that cerebrovascular disease,AKI incidence,interleukin(IL)-6 level of>6.8 pg/mL,daily dose of corticosteroids of>50 mg,and fungal infection were all associated with an increased risk of death for hospitalized ***:Our findings demonstrate that hospitalized KTRs with COVID-19 are at high risk of *** administration of immunomodulators or the late application of antiviral drugs does not improve patient survival,while higher doses of corticosteroids may increase the death risk.

关键词： Coronavirus disease 2019(COVID-19) Kidney transplant Hospitalization Mortality

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Optimal Multi-Robot Path Planning for Cyclic Tasks using Petri Nets

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IFAC-PapersOnLine 2022年第28期55卷 9-15页

作者： Peng Lv Guangqing Luo Xiang Yin Ziyue Ma Shaoyuan Li Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai 200240 China School of Electro-Mechanical Engineering Xidian University Xi'an 710071 China

In this paper, we investigate the problem of optimal multi-robot path planning for a cyclic task represented by a particular type of linear-temporal logic (LTL) formulae. Specifically, the team of robot needs to fulfill a given LTL formula and at the same time, accomplishes some particular tasks infinitely often. To avoid the state-space explosion when the number of robot increases, we use Petri nets to model the team of multi-robot. Our goal is to find an optimal infinite sequence in the prefix-suffix form for each robot such that the average cost per task is minimized. We propose an efficient planning method based on the notion of basis reachability graph (BRG), which is a compact representation of the reachability space of the PN. We demonstrate the computational efficiency of our method through illustrative examples.

关键词： Petri Nets Linear Temporal Logic Multi-Robot systems Task Planning

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Trailer Tag Hitch: An Automatic Reverse Hanging system Using Fiducial Markers 7th

Trailer Tag Hitch: An Automatic Reverse Hanging System Using...

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7th International Conference on Cognitive systems and information processing, ICCSIP 2022

作者： Lu, Dongxi Yuan, Wei Lian, Chaochun Yao, Yongchun Cai, Yan Yang, Ming Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China University of Michigan - Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China SAIC-GM-Wuling Automobile Co. Ltd. Guangxi Liuzhou545007 China

ISBN: (纸本)9789819906161

Unmanned tractor-trailer vehicles are widely used in factory transportation scenarios. However, the trailer hitching process is still manually operated. The automatic trailer hitching is the precondition of fully unmanned logistics. Existing auto hitching methods directly detect the trailer or coupler features, making them hard to generalize and deploy to various types of trailers and couplers. To address this problem, this paper proposes a trailer hitch system using fiducial markers. The system is divided into two modules: hitch coupler pose estimation and visual servoing. An algorithm based on AprilTag detection is used for hitch coupler pose estimation. The pose messages guide the tractor to reverse to the trailer. An algorithm based on decoupled lateral-longitudinal control is used for visual servoing. The proposed system is experimented on 4 different tractor-trailer vehicles with 254 tests under various conditions. Large scale test condition variations include initial position and orientation, light illumination, indoor/outdoor scenario, and fiducial marker damage. Overall success rate of 95% shows that the proposed system is robust to environment variation and different kinds of trailers. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Light trailers

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