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Energy-aware Integrated Scheduling for Container Terminals with Conflict-free AGVs

Journal of Systems Science and Systems engineering 2023年第4期32卷 413-443页

作者： Zhaolin Zhong Yiyun Guo Jihui Zhang Shengxiang Yang Institute of Complexity Science School of AutomationQingdao UniversityQingdao266071China Shandong Key Laboratory of Industrial Control Technology Qingdao266071China Qingdao Port International Company Ltd.Qingdao266011China Institute of Artificial Intelligence School of Computer Science and InformaticsDe Montfort UniversityLeicesterLE19BHUK

For automated container terminals,the effective integrated scheduling of different kinds of equipment such as quay cranes(QCs),automated guided vehicles(AGVs),and yard cranes(YCs)is of great significance in reducing energy consumption and achieving sustainable *** at the joint scheduling of AGVs and YCs with consideration of conflict-free path planning for AGVs as well as capacity constraints on AGV-mate which is also called buffer bracket in blocks,a mixed integer programming model is established to minimize the energy consumption of AGVs and YCs for the given loading/unloading task.A solution method based on a novel bi-level genetic algorithm(BGA),in which the outer and the inner layer search the optimal dispatching strategy for QCs and YCs,respectively,is *** validity of the model and the algorithm is verified by simulation experiments,which take the Port of Qingdao as an example and the performance under different conflicting resolution strategies is *** results show that,for the given task,the proposed solution to conflict-free path and the schedule provided by the algorithm can complete the task with minimum energy consumption without loss of AGVs utilization,and the number of AGV-mates should be adjusted according to the task rather than keeping *** results indicate that our proposed approach could efficiently find solutions within 6%optimality *** consumption is dropped by an average of 15%.

关键词： Automated container terminal conflict-free routing energy saving improved genetic algorithm

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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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2024 International Conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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Power amplifier circuit defect detection based on improved Patch SVDD

Power amplifier circuit defect detection based on improved P...

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作者： Xie, Zhonghui Kong, Wa Zhou, Xinyu Zhang, Wence Zhong, Yujie Xia, Jing School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace Jiangsu University Zhenjiang China Department of Electronic Information Engineering Hong Kong Polytechnic University Hong Kong

In the manufacturing process of power amplifier (PA), various defects on the circuit surface will seriously affect the circuit performance and its operation. To solve the above problems, this article proposes a circuit defect detection method based on improved patch-based support vector data description algorithm (Patch SVDD), which uses contrastive learning to enhance the feature extraction ability of neural network. An image calibration algorithm is used for calibration preprocessing to enhance the robustness of the model. The Euclidean distance between a query image patch and its nearest normal patch is defined to be an anomaly score. For verification, three defects in the PA circuit, including components missing, solder contamination and component orientation dislocation, were detected. The experimental results show that, compared with conventional method, the area under receiver operating characteristic (AUROC) of the improved anomaly detection model increased from 90.1% to 95.1%, which improves the detection accuracy effectively. © 2023 John Wiley & Sons Ltd.

关键词： Anomaly detection

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Knowledge-driven inverse diffusion prediction algorithm for flexible job shop scheduling problem considering transportation resources and multiple breakdowns

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Swarm and Evolutionary Computation 2025年 96卷

作者： Wang, Cong Wei, Lixin Sun, Hao Hu, Ziyu Hebei Key Laboratory of Industrial Computer Control Engineering Yanshan University Qinhuangdao Hebei066004 China School of Electrical Engineering Yanshan University Qinhuangdao Hebei066004 China

The complex coupling between transportation and production poses significant challenges for scheduling algorithms, particularly in dynamic environments where contingencies are frequent. The traditional Flexible Job Shop Scheduling Problem (FJSP) does not fully account for these factors. Therefore, a two-stage knowledge-driven inverse diffusion prediction algorithm (TKIDP) is proposed for FJSP with transportation resources and multiple breakdowns (MBFJSPT). In the first phase, TKIDP operates in a static environment and aims to minimize the makespan and load imbalance, thereby reducing the risk of machine breakdowns. When a machine breakdown occurs, TKIDP enters a rescheduling phase and minimizes total energy consumption as an additional objective. An inverse diffusion prediction strategy is proposed to address the occurrence of multiple machine breakdowns. By learning from optimization processes of historical breakdowns, the proposed strategy identifies potential evolutionary patterns and predicts the evolutionary trends of future breakdowns. A similarity measure based on mutual entropy is introduced to select the most relevant historical breakdowns for learning. This method enhances prediction accuracy. To further improve exploration and exploitation capabilities, an adaptive competitive reconfiguration strategy is proposed. This strategy incorporates multiple deletion and reconstruction operators to guide the algorithm toward the optimal solution. To verify the effectiveness of MBFJSPT, a dedicated MB test set is constructed. On the MB1-18 test, TKIDP is compared with five other algorithms. Based on the Inverted generational distance (IGD), hypervolume (HV), and relative deviation (RD) metrics, TKIDP achieves the best results on 15, 18, and 18 out of the 18 test instances, respectively. © 2025 Elsevier B.V.

关键词： Multiobjective optimization

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Occurrence, partition behavior, source and ecological risk assessment of nitro-PAHs in the sediment and water of Taige Canal, China

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Journal of Environmental Sciences 2023年第2期124卷 782-793页

作者： Jijie Kong Tao Ma Xiaoyu Cao Weidi Li Fengxiao Zhu Huan He Cheng Sun Shaogui Yang Shiyin Li Qiming Xian School of Environment Nanjing Normal UniversityNanjing 210023China School of Geography Nanjing Normal UniversityNanjing 210023China The State Key Laboratory of Pollution Control and Resource Reuse School of the EnvironmentNanjing UniversityNanjing 210023China Fujian Provincial Key laboratory of Eco-Industrial Green Technology College of Ecological and Resource EngineeringWuyi UniversityWuyishan 354300China Nanjing Institute of Environmental Sciences Ministry of Ecology and EnvironmentNanjing 210042China

Nitrated polycyclic aromatic hydrocarbons(NPAHs)are widespread organic pollutants that possess carcinogenic and mutagenic properties,so they may pose a risk to the environment and human *** this study,the concentrations of 15 NPAHs and 16 polycyclic aromatic hydrocarbons(PAHs)in 30 surface water samples and 26 sediment samples were measured in 2018 from the Taige Canal,one of the main rivers flowing into Taihu Lake,*** total NPAH concentrations in water and sediment ranged from 14.7 to 235 ng/L and 22.9 to 96.5 ng/g dw,respectively.9-nitrophenanthrene(nd–76.3 ng/L)was the dominant compound in surface water,while 2+3-nitrofluoranthene(1.73–18.1 ng/g dw)dominated in *** PAHs,concentration ranging from 1,097 to 2,981 ng/L and 1,089 to 4,489 ng/g dw in surface water and sediment,*** was a strong positive correlation between the log octanol-water partition coefficient(Kow)and log sediment-water partition coefficient due to hydrophobic *** fugacity fraction value increased with the decrease of log Kow,and chrysene was transferred from water into *** residual NPAHs in surface water and sediment of the Taige Canal have partial *** engine and coal combustion emissions were probably the principal sources of NPAHs in surface water and *** results of ecological risk assessment showed that some NPAHs inwater(e.g,1-nitropyrene and 6-nitrochrysene)and sediment(e.g.,2-nitrobiphenyl,5-nitroacenaphthene,9-nitrophenanthrene and 2+3-nitrofluoranthene)had moderate ecological risks,which should be of concern.

关键词： Nitrated polycyclic aromatic hydrocarbons(NPAHs) Occurrence Partition behavior Source apportionment Ecological risk assessment

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A Copyright Authentication Method Balancing Watermark Robustness and Data Distortion 26

A Copyright Authentication Method Balancing Watermark Robust...

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26th International Conference on computer Supported Cooperative Work in Design, CSCWD 2023

作者： Wang, Chundong Li, Yue Tianjin University of Technology Tianjin300384 China National Engineering Laboratory for Virus Prevention and Control Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education Tianjin China

ISBN: (纸本)9798350331684

Database watermarking plays an irreplaceable role in copyright authentication and data integrity protection, but the robustness of the watermark and the resulting data distortion are a pair of contradictory objects that cannot be ignored. To solve this problem, a reversible database watermarking method, named IGADEW, is proposed to balance the relationship between them. The biggest difference from previous research is that IGADEW synthesizes the optimization objects and obtain various parameters through genetic algorithm (GA). Second, the fitness function considers the weights of robustness and distortion, aiming to find the optimal balance between the two. IGADEW uses the Hash-based Message Authentication Code (HMAC) algorithm to encrypt the experimental parameters and uses the primary key hash algorithm for data grouping, both to ensure robustness. And the data distortion is limited with the help of threshold constraints. Finally, experiments using the UCI dataset demonstrate the effectiveness of IGADEW. Experimental results show that, compared with existing methods, IGADEW is more robust against common attacks, with lower data distortion. © 2023 IEEE.

关键词： Copyrights

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

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

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2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

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

ISBN: (纸本)9798350378658

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. © 2024 IEEE.

关键词： Radiation hazards

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Detection method of river industrial pollution events based on background model prediction using three-dimensional fluorescence

Detection method of river industrial pollution events based ...

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第34届中国过程控制会议

作者： Qiuhao Zhang Jie Yu Jiegen Shi Fangjia Xue Pingjie Huang Dibo Hou Hongjian Zhang Key Laboratory of Industrial Control Technology Department of Control Science and EngineeringZhejiang University

The use of three-dimensional fluorescence spectroscopy for anomaly detection of urban river water quality can protect the water environment from exogenous pollution especially organic pollutant,and has great potential for ***,the detection methods face challenges from scenarios of pollution in low concentration,similar spectral distinguish,fluctuation in water background,*** paper proposed a detection method based on water background model prediction feature extraction method which is suitable for the above ***,a spectroscopy preprocessing method for anomaly detection in river scenes is applied to delete the scattering ***,alternating residual trilinearization is used to establish a river water spectroscopy model to predict the trend of water quality *** the frequency domain features of potential fluorescence peaks are extracted from the residual spectrum for classification to identify abnormal organic *** results show that the method proposed in this paper can effectively extract the fluorescence characteristics of pollutants in low concentration pollutant scene,overlapping pollutant fluorescence peaks with background fluorescence peaks scene and river water background fluctuation scene,thus achieving accurate anomaly detection results.

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A comprehensive survey of visible infrared person re-identification from an application perspective

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Multimedia Tools and Applications 2024年第42期83卷 90243-90270页

作者： Chang, Hua Xu, Xin Liu, Wei Lu, Lingyi Li, Weigang School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan430065 China School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

Person re-identification (ReID) is a significant issue in computer vision, aiming to match the same pedestrian across various cameras. Recent research on this issue has successfully reached a satisfactory performance level in the daytime scenario. However, the performance of ReID in low illumination scenarios suffers a dramatic degradation due to the insufficient personal information captured by visible cameras in low or no light scenarios. To address this challenge, the adoption of novel camera technologies for more effective pedestrian data is imperative. Owing to the constraints of distance and usage scenarios in deploying depth cameras, practical infrared cameras are frequently utilized, spurring research in visible infrared person re-identification (VI-ReID). Significant progress has been made in the field of VI-ReID in recent years, but only a few reviews have categorized this problem based on methodology. This article offers a novel perspective by classifying VI-ReID according to application scenarios. Following our categorization scheme, the main advancements in deep learning for VI-ReID over the past five years have been grouped into three categories as follows: retrieval of infrared images using visible images (V→IR), retrieval of visible images using infrared images (IR→V), and joint retrieval of infrared and visible images (V→IR and IR→V). Next, this survey outlines the available datasets and evaluation metrics. After that, we categorize diverse methodologies under the proposed classification and assess their performance metrics across common datasets. Finally, we present two prospective avenues for future research in this domain, informed by the current state of advancement. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Infrared imaging

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On convergence of covariance matrix of empirical Bayes hyper-parameter estimator

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control Theory and Technology 2024年第2期22卷 149-162页

作者： Yue Ju Biqiang Mu Tianshi Chen School of Data Science and Shenzhen Research Institute of Big Data The Chinese University of Hong KongShenzhenShenzhen518172GuangdongChina Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technology10044StockholmSweden Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and System ScienceChinese Academy of SciencesBeijing100190China

Regularized system identification has become the research frontier of system identification in the past *** related core subject is to study the convergence properties of various hyper-parameter estimators as the sample size goes to *** this paper,we consider one commonly used hyper-parameter estimator,the empirical Bayes(EB).Its convergence in distribution has been studied,and the explicit expression of the covariance matrix of its limiting distribution has been ***,what we are truly interested in are factors contained in the covariance matrix of the EB hyper-parameter estimator,and then,the convergence of its covariance matrix to that of its limiting distribution is *** general,the convergence in distribution of a sequence of random variables does not necessarily guarantee the convergence of its covariance ***,the derivation of such convergence is a necessary complement to our theoretical analysis about factors that influence the convergence properties of the EB hyper-parameter *** this paper,we consider the regularized finite impulse response(FIR)model estimation with deterministic inputs,and show that the covariance matrix of the EB hyper-parameter estimator converges to that of its limiting ***,we run numerical simulations to demonstrate the efficacy of ourtheoretical results.

关键词： Regularized system identification Hyper-parameter estimator Empirical Bayes Convergence of covariance matrix

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