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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Tabacaru, Gigi Moldovanu, Simona Barbu, Marian 'Dunarea de Jos' University of Galati Faculty of Automation Computers Electrical Engineering and Electronics Department of Automatic Control and Electrical Engineering Romania 'Dunarea de Jos' University of Galati Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Romania Dunarea de Jos University of Galati The Modelling & Simulation Laboratory Galati800008 Romania

ISBN: (纸本)9798350395440

In this work, an attempt is made for the first time to use the measurement pattern generated by morphological transformation quantified by Hausdorff fractal dimension (HFD) and classified with ensemble learning based on bagging. The proposed work uses three morphological transformations for image preprocessing: hit-and-miss transform (HMT), white (WHT), and black top-hat (BHT). The pattern texture of US breast images is described by extracting the HFD from the regions of interest (ROI) after the ultrasound (US) images have been preprocessed. The main objective of this study was achieved by comparatively analyzing the classification performance of features using the Random Forest (RF), Extra Trees (ET) classifier, and bagging ensemble method based on XGBoot classifier. In presented study, the XGBoost classifier and BHT image processing method give an accuracy of 89.8% in a binary classification, benign versus malignant breast cancer. © 2024 IEEE.

关键词： Fractal dimension

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Detection of UAV Target Based on Continuous Radon Transform and Matched Filtering Process for Passive Bistatic Radar

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Journal of Beijing Institute of technology 2024年第1期33卷 9-18页

作者： Luo Zuo Yuefei Yan Jun Wang Xin Sang Yan Wang Dongming Ge Lihao Ping Zhihai Wang Congsi Wang Guangzhou Institute of Technology Xidian UniversityGuangzhou 510555China National Laboratory of Radar Signal Processing Xidian UniversityXi’an710071China School of Information and Control Engineering Xi’an University of Architecture and TechnologyXi’anShaanxi 710055China CETC Wuhu Diamond Aircraft Manufacturing Co. LtdWuhuAnhui 241000China Beijing Space Vehicle General Design Department Beijing 100094China CETC No.38 Research Institute Hefei 230088China

Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target *** paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic *** not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.

关键词： passive bistatic radar unmanned aerial vehicle long-time coherent integration Radon-matched filtering process

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Improved Proximal Policy Optimization Algorithm for Multi-objective Disassembly Line Balancing Considering Hazardous Tasks 21

Improved Proximal Policy Optimization Algorithm for Multi-ob...

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21st International Conference on Networking, Sensing and control, ICNSC 2024

作者： Guo, Zeyu Guo, Xiwang Wang, Jiacun Qin, Shujin Qi, Liang Kang, Qi Liaoning Petrochemical University Information and Control Engineering Fushun China Monmouth University Computer Science and Software Eng. Wes Long BranchNJ United States Shangqiu Normal University Economics and Management Shangqiu China Shandong Technology University Computer Science Department Qingdao China New Jersey Institute of Technology Electrical and Computer Engineering Newark United States

ISBN: (纸本)9798350365221

As disassembly lines evolve, keeping workers safe from all potential dangers has become paramount. This work proposes an improved approach, Proximal Policy Optimization for Disassembly Line(PPO-DL), to address Multi-objective Dis-assembly Line Balancing Problem(MDLBP) that integrates task switching time and hazardous tasks. The MDLBP model aims to optimize disassembly net profit, balance workstation utilization, and mitigate penalties from hazardous tasks. The proposed PPO-DL modifies the action space of PPO to accommodate MD LBP characteristics, ensuring efficient learning by restricting actions to valid ranges through action masking. Comparative experiments with PPO, Q-learning, and A2C demonstrate PPO-DL's superiority in finding near-optimal solutions across various scenarios. © 2024 IEEE.

关键词： Assembly machines

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Structured light analogy of quantum squeezed states

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Light(Science & Applications) 2024年第12期13卷 3139-3150页

作者： Zhaoyang Wang Ziyu Zhan Anton N.Vetlugin Jun-Yu Ou Qiang Liu Yijie Shen Xing Fu Department of Precision Instrument Tsinghua UniversityBeijing 100084China State Key Laboratory of Precision Space-Time Information Sensing Technology Beijing 100084China Key Laboratory of Photonic Control Technology(Tsinghua University) Ministry of EducationBeijing 100084China Centre for Disruptive Photonic Technologies School of Physical and Mathematical Sciences&The Photonics InstituteNanyang Technological UniversitySingapore 63737ISingapore School of Physics and Astronomy University of SouthamptonSouthamptonUK School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore

Quantum optics has advanced our understanding of the nature of light and enabled applications far beyond what is possible with classical *** unique capabilities of quantum light have inspired the migration of some conceptual ideas to the realm of classical optics,focusing on replicating and exploiting non-trivial quantum states of discretevariable ***,we further develop this paradigm by building the analogy of quantum squeezed states using classical structured *** have found that the mechanism of squeezing,responsible for beating the standard quantum limit in quantum optics,allows for overcoming the“standard spatial limit”in classical optics:the light beam can be“squeezed”along one of the transverse directions in real space(at the expense of its enlargement along the orthogonal direction),where its width becomes smaller than that of the corresponding fundamental Gaussian *** show that classical squeezing enables nearly sub-diffraction and superoscillatory light focusing,which is also accompanied by the nanoscale phase gradient of the size in the order ofλ/100(λ/1000),demonstrated in the experiment(simulations).Crucially,the squeezing mechanism allows for continuous tuning of both features by varying the squeezing parameter,thus providing distinctive flexibility for optical microscopy and metrology beyond the diffraction limit and suggesting further exploration of classical analogies of quantum effects.

关键词： quantum optics analogy

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Carbon-Aware Computing in a Network of Data Centers: A Hierarchical Game-Theoretic Approach

Carbon-Aware Computing in a Network of Data Centers: A Hiera...

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European control Conference (ECC)

作者： Enno Breukelman Sophie Hall Giuseppe Belgioioso Florian Dörfler Division of Decision and Control Systems KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden Department of Electrical Engineering and Information Technology Automatic Control Laboratory ETH Zurich Zürich Switzerland

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Over the past decade, the continuous surge in cloud computing demand has intensified data center workloads, leading to significant carbon emissions and driving the need for improving their efficiency and sustainability. This paper focuses on the optimal allocation problem of batch compute loads with temporal and spatial flexibility across a global network of data centers. We propose a bilevel game-theoretic solution approach that captures the inherent hierarchical relationship between supervisory control objectives, such as carbon reduction and peak shaving, and operational objectives, such as priority-aware scheduling. Numerical simulations with real carbon intensity data demonstrate that the proposed approach success-fully reduces carbon emissions while simultaneously ensuring operational reliability and priority-aware scheduling.

关键词： Data centers Processor scheduling Computational modeling Carbon dioxide Games Supervisory control Resource management

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Finite-Time Sideslip Differentiator-Based LOS Guidance for Robust Path Following of Snake Robots

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 239-253页

作者： Yang Xiu Dongfang Li Miaomiao Zhang Hongbin Deng Rob Law Yun Huang Edmond Q.Wu Xin Xu the School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China the School of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Antai College of Economics&Management Shanghai Jiao Tong UniversityShanghai 200240China the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China the Asia-Pacific Academy of Economics and Management University of MacaoMacao 999078China the Department of Decision Science Macao University of Science and TechnologyMacao 999078China the Department of Automation Shanghai Jiao Tong Universityand also with the Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai 200240China the College of Mechatronics and Automation National University of Defense TechnologyChangsha 410073China IEEE

This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS)guidance method for robust path following of snake ***,finite-time stable sideslip differentiator and adaptive LOS guidance method are proposed to counteract sideslip drift caused by cross-track *** proposed differentiator can accurately observe the cross-track error and sideslip angle for snake robots to avoid errors caused by calculating sideslip angle *** our method,the designed piecewise auxiliary function guarantees the finite-time stability of position ***,for the case of external disturbances and state constraints,a Barrier Lyapunov functionbased backstepping adaptive path following controller is presented to improve the robot’s *** uniform ultimate boundedness of the closed-loop system is proved by analyzing ***,a gait frequency adjustment-based virtual velocity control input is derived to achieve the exponential convergence of the tangential *** last,the availability and superiority of this work are shown through simulation and experiment results.

关键词： Line-of-sight(LOS) path following sideslip snake robot

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An Improved Object Detection Algorithm for UAV Images Based on Orthogonal Channel Attention Mechanism and Triple Feature Encoder

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IET Image Processing 2025年第1期19卷

作者： Wang, Wenfeng Wang, Chaomin Lei, Sheng Xie, Min Gui, Binbin Dong, Fang School of Information Engineering Nanchang Institute of Technology Nanchang China Jiangxi Province Key Laboratory of Smart Water Conservancy Nanchang Institute of Technology Nanchang China Flood Control Information Center Jiangxi Provincial Department of Water Resources Nanchang China

Object detection in Unmanned Aerial Vehicle (UAV) imagery plays an important role in many fields. However, UAV images usually exhibit characteristics different from those of natural images, such as complex scenes, dense small targets, and significant variations in target scales, which pose considerable challenges for object detection tasks. To address these issues, this paper presents a novel object detection algorithm for UAV images based on YOLOv8 (referred to as OATF-YOLO). First, an orthogonal channel attention mechanism is added to the backbone network to imporve the algorithm's ability to extract features and clear up any confusion between features in the foreground and background. Second, a triple feature encoder and a scale sequence feature fusion module are integrated into the neck network to bolster the algorithm's multi-scale feature fusion capability, thereby mitigating the impact of substantial differences in target scales. Finally, an inner factor is introduced into the loss function to further upgrade the robustness and detection accuracy of the algorithm. Experimental results on the VisDrone2019-DET dataset indicate that the proposed algorithm significantly outperforms the baseline model. On the validation set, the OATF-YOLO algorithm achieves a precision of 59.1%, a recall of 40.5%, an mAP50 of 42.5%, and an mAP50:95 of 25.8%. These values represent improvements of 3.8%, 3.0%, 4.1%, and 3.3%, respectively. Similarly, on the test set, the OATF-YOLO algorithm achieves a precision of 52.3%, a recall of 34.7%, an mAP50 of 33.4%, and an mAP50:95 of 19.1%, reflecting enhancements of 4.0%, 3.3%, 4.0%, and 2.6%, respectively. To further validate the model's robustness and scalability, experiments are conducted on the NWPU-VHR10 dataset, and OATF-YOLO also achieves excellent performance. Furthermore, compared to several classical object detection algorithms, OATF-YOLO demonstrates superior detection performance on both datasets and indicates that it is bette

关键词： Unmanned aerial vehicles (UAV)

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Successive statistical iterative reconstruction, 3D-filtering and region growing methods for high-quality 3D visualization of cone-beam CT image 2022

Successive statistical iterative reconstruction, 3D-filterin...

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7th International Conference on Multimedia and Image Processing, ICMIP 2022

作者： Dong, Jian Zhang, Siyuan Yang, Xiaoxia Zhang, Jingyu Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology Tianjin300222 China Department of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9781450387408

Our study is to improve the accuracy of bone morphology depicted in dental cone-beam computed tomography (CBCT) images. First, successive statistical iterative reconstruction was used to reduce unavoidable streak artefacts. Then 3-dimentional filtering (Gaussian-Laplacian filter) and region growing methods were examined to present clear bone morphology. CBCT examinations were performed with the following principal exposure parameters: I-mode, FOV 10cm in diameter, 120 kV, 15 mA, 0.2 mm slice thickness, and exposure time of 10s. Ordered subset-expectation maximization (OS-EM) algorithm was applied for unavoidable streak artefact reduction. 3D Laplacian sharpening to images preprocessed by Gaussian smoothing was sequentially tested. Region growing method with dilation and erosion was used to segment maxillofacial tissue. Streak artefact induced by metallic prosthetic appliances was reduced by applying successive iterative OS-EM algorithm. Multi-planar reconstruction (MPR) images at left side molar plane and mid-sagittal plane were presented to validate effect of OS-EM algorithm and 3D Gaussian-Laplacian filter. Maxillofacial tissue was segmented and presented to show the effect of region growing method. Streak artefact reducing method, 3D filtering method for image smoothing and sharpening, and region growing method with dilation and erosion were effective to improve accuracy of bone morphology in dental CBCT images. © 2022 ACM.

关键词： Image reconstruction

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Explainable Artificial Intelligence Solution for Online Retail

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Computers, Materials & Continua 2022年第6期71卷 4425-4442页

作者： Kumail Javaid Ayesha Siddiqa Syed Abbas Zilqurnain Naqvi Allah Ditta Muhammad Ahsan M.A.Khan Tariq Mahmood Muhammad Adnan Khan Department of Computer Science University of South AsiaLahore54000Pakistan Department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54000Pakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Division of Science and Technology University of EducationLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea

Artificial intelligence(AI)and machine learning(ML)help in making predictions and businesses to make key decisions that are beneficial for *** the case of the online shopping business,it’s very important to find trends in the data and get knowledge of features that helps drive the success of the *** this research,a dataset of 12,330 records of customers has been analyzedwho visited an online shoppingwebsite over a period of one *** main objective of this research is to find features that are relevant in terms of correctly predicting the purchasing decisions made by visiting customers and build ML models which could make correct predictions on unseen data in the *** permutation feature importance approach has been used to get the importance of features according to the output variable(Revenue).Five ML models i.e.,decision tree(DT),random forest(RF),extra tree(ET)classifier,Neural networks(NN),and Logistic regression(LR)have been used to make predictions on the unseen data in the *** performance of each model has been discussed in detail using performance measurement techniques such as accuracy score,precision,recall,F1 score,and ROC-AUC *** model is the bestmodel among all five chosen based on accuracy score of 90%and F1 score of 79%followed by extra tree ***,our study indicates that RF model can be used by online retailing businesses for predicting consumer buying *** research also reveals the importance of page value as a key feature for capturing online purchasing *** may give a clue to future businesses who can focus on this specific feature and can find key factors behind page value success which in turn will help the online shopping business.

关键词： Explainable artificial intelligence online retail neural network random forest regression

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Remotely controllable Data Self-Destruction for Privacy-Preserving Sensitive Data Services 25

Remotely Controllable Data Self-Destruction for Privacy-Pres...

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25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Zhou, Chengxin Xue, Xianbin Riad, Khaled Zhu, Yan Chu, William Cheng-Chung School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China North Navigation Control Technology Co. Ltd. Beijing China College of Computer Science and Information Technology King Faisal University Saudi Arabia Tunghai University Department of Computer Science Taichung Taiwan

ISBN: (纸本)9798350330014

This paper address a comprehensive solution to address data privacy and security challenges in data science, providing secure self-destruction of sensitive data, confidentiality through encryption, and flexible control over message destruction. Based on outsourcing cloud data services, we introduce a cloud retrograde storage (CRS) system for privacy-preserving self-destruction of sensitive data. The CRS is based on a frequently colliding hash table and recycle pool, and supports remote time, count, and range control. Hereby, we provide a remotely controllable mechanism for the prompt destruction of inactive messages against digital forensics without reducing the availability of services. The method used in the CRS involves storing messages in a recycle pool, where they are automatically erased at the end of their validity period or after being viewed by all recipients. The system also incorporates encryption and decryption processes to ensure confidentiality. The result of performance evaluation shows that the CRS effectively handles the destruction of messages and provides secure data removal from storage pools. The experiments demonstrate the efficiency and practicality of the CRS for large-scale data services. © 2023 IEEE.

关键词： Sensitive data

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