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SSRN 2023年

作者： Cammarata, Antonio Dašić, Miljan Nicolini, Paolo Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Technicka 2 Prague16627 Czech Republic Scientific Computing Laboratory Center for the Study of Complex Systems Institute of Physics Belgrade University of Belgrade Pregrevica 118 Belgrade11080 Serbia Institute of Physics Czech Academy of Sciences Na Slovance 2 Prague18200 Czech Republic

We here present the Normal Dynamics technique, which provides a way to integrate the Newton's equations of motion by sampling the reciprocal space. We discuss the sampling strategy and show how it is capable to produce dynamical trajectories at the ab initio level on an ordinary desktop computer. The reciprocal space sampling allows to i) obtain a systematic improvement of the results accuracy and a fine control of the computational load, and ii) account for distortions realized across large atomic distances without the use of large unit cells. We present three case studies: the first two are aimed to show the capabilities of the method while in the latter we investigate on the characterization of Raman spectra at different temperatures in MoS2/MX2 transition metal dichalcogenide heterostructures. Finally, we discuss how the sampling procedure is general and can be used to simulate periodic, semiperiodic and finite systems such as crystals, slabs, nanoclusters or molecules. © 2023, The Authors. All rights reserved.

关键词： Equations of motion

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Teeth Segmentation from Bite-Wing X-Ray Images by Integrating Nested Dual UNet with Swin Transformers

Teeth Segmentation from Bite-Wing X-Ray Images by Integratin...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Yubo Li Yibin Tian Zhiyuan Zhang Xueyang Zhang Bingran Du Zhi Zeng School of Computer and Information Science Chongqing Normal University Chongqing CN College of Mechatronics and Control Engineering Shenzhen University Shenzhen CN Litemaze Technology Shenzhen CN School of Computing and Information Systems Singapore Management University Singapore SG Department of Stomatology Shunde Hospital Southern Medical University (The First People's Hospital of Shunde) Foshan CN

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In medical practice, the precision of image segmentation is crucial for diagnosis and treatment evaluations. Specifically, in dentistry, accurate teeth segmentation from bite-wing images is important for automatic and objective evaluations of root canal treatments. This study introduces $\text{Swin}-\mathrm{U}^{2} \text{Net}$ , a model merging the nested dual UNet with residual U-block and Swin Transformers. It combines the local feature extraction capability of the former and the global attention and context understanding of the latter. It has been evaluated for tooth root segmentation using 500 bite-wing dental x-ray images obtained from a root canal treatment clinic. It achieved the best segmentation outcome in terms of Intersection over Union (IOU) and the third best result in terms of Dice Similarity Coefficient (DSC) with the second least amount of network parameters among six UNet-like models, thus it is effective and efficient.

关键词： Image segmentation Irrigation Accuracy Merging Teeth Transformers Feature extraction Dentistry X-ray imaging Medical diagnostic imaging

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Research on fault diagnosis method and application of gas turbine based on acoustic imaging technology

Research on fault diagnosis method and application of gas tu...

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CSAA/IET International Conference on Aircraft Utility Systems (AUS 2024)

作者： Wen Yan Mingliang Hu Fei Wen Peipei Guo Ziang Guo AVIC Shanghai Aviation Measurement & Control Technology Research Institute Shanghai 201601 People's Republic of China Xi'an Aeronautics Computing Technique Research Institute AVIC Xi'an 710068 People's Republic of China Department of Electronics College of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 People's Republic of China

ISBN: (数字)9781837242108

Gas turbine health management is of great significant for enhancing flight safety and reducing maintenance costs. Based on the architecture of gas turbine fault identification system, a multi-arm spiral microphone array with high positioning accuracy, high beam resolution, and strong anti-interference capability is designed in this paper with simulation and experiment. On this basis, by utilizing multi-channel acoustic digital acquisition and analysis equipment, high-precision, wide dynamic range, and high-real-time acquisition of audio data from the combustion chamber of gas turbines are achieved. An audio data analysis strategy based on feature extraction and an autoencoder network construction strategy are proposed, fulfilling the imaging of audio data from the combustion chamber of gas turbines, which can effectively identify gas turbine faults. Experiments conducted on the platform of the multi-arm spiral microphone array indecates that the proposed fault detection strategy has an accuracy rate of over 98%. This is of great theoretical significance and practical value for enhancing the level of gas turbine fault detection, and improving the performance, reliability, and lifespan of gas turbine systems.

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Research on Reconstruction of CT Images Based on AA-R2Unet in Inferior Mesenteric Artery Classification 7th

Research on Reconstruction of CT Images Based on AA-R2Unet i...

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7th International Conference on Life System Modeling and Simulation, LSMS 2021, and 7th International Conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2021

作者： Xu, Peixia Wang, Meirong Han, Yu Chen, Jinghao Zhu, YuanFan Zhang, Kun He, Bosheng School of Electrical Engineering Nantong University Nantong China Department of Radiology The Second Affiliated Hospital of Nantong University Nantong China Nantong Key Laboratory of Intelligent Medicine Innovation and Transformation Nantong China Nantong Key Laboratory of Intelligent Control and Intelligent Computing Nantong China School of Management Science and Engineering ChongqingTechnology and Business University Chongqing China

ISBN: (纸本)9789811672064

In the process of colorectal cancer surgery, dispute on whether to retain the left colonic artery continues to this day. The classification of the inferior mesenteric artery has instructional significance for clinic which has been proved. Therefore, realizing relative position among vessels is an essential step for the diagnosis and therapy of colorectal cancer disease. The method of 3D reconstruction based on CT sequence images in hospital is time-consuming and laborious. In this paper, we propose a kind of AA-R2Unet based on Unet to realize automatic segmentation of the inferior mesenteric artery. We use attention augment rather than the convolution to achieve the global feature, stacking predictions with 2D features to achieve the function of 3D visualization. The improved Focal Loss function we proposed focuses more on our target vessel. AA-R2Uet achieved a per case precision of 93.34%, recall of 90.28%, and 90.06% of F1 score. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Diagnosis

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Remanufacturing Scheme Design for Used Parts Based on Incomplete Information Reconstruction

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Chinese Journal of Mechanical engineering 2020年第3期33卷 72-85页

作者： Wenhao Huang Zhigang Jiang Teng Wang Yan Wang Xiaoli Hu Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science&TechnologyWuhan 430081China Key Laboratory of Metallurgical Equipment and Control Technology Wuhan University of Science&TechnologyWuhan 430081China Department of Computing Engineering and MathematicsUniversity of BrightonBrighton BN24GJUK School of Mechanical Engineering Shanghai Dianji UniversityShanghai 201306China.

The different conditions of use of a component result in a variety of damage ***,excluding differences in shape and size,used parts show a high degree of uncertainty regarding failure characteristics,quality conditions,and remaining life,which seriously affects the efficiency of a remanufacturing scheme *** to address this problem,a remanufacturing scheme design method based on the reconstruction of incomplete information of used parts is ***,the remaining life of the reconstructed model is predicted by finite element analysis,and the demand for the next life cycle is ***,the scanned 3D damage point cloud data are registered with the original point cloud data using the integral iterative method to construct a missing point cloud model to achieve the restoration of geometric ***,according to reverse engineering and laser cladding remanufacturing,the tool remanufacturing process path can be generated by the tool contact point path section line ***,the proposed method is adopted for turbine blades to evaluate the effectiveness and feasibility of the proposed *** study proposes a remanufacturing scheme design method based on the incomplete reconstruction of used part information to solve the uncertain and highly personalized problems in remanufacturing.

关键词： Remanufacturing Incomplete information Unit-step integration iteration method

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Deep Learning-Based Object Pose Estimation: A Comprehensive Survey

arXiv

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arXiv 2024年

作者： Liu, Jian Sun, Wei Yang, Hui Zeng, Zhiwen Liu, Chongpei Zheng, Jin Liu, Xingyu Rahmani, Hossein Sebe, Nicu Mian, Ajmal The National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China The School of Architecture and Art Central South University Changsha410082 China The Department of Automation Tsinghua University Beijing100084 China The School of Computing and Communications Lancaster University LA1 4YW United Kingdom The Department of Information Engineering and Computer Science University of Trento Trento38123 Italy The Department of Computer Science The University of Western Australia WA6009 Australia

Object pose estimation is a fundamental computer vision problem with broad applications in augmented reality and robotics. Over the past decade, deep learning models, due to their superior accuracy and robustness, have increasingly supplanted conventional algorithms reliant on engineered point pair features. Nevertheless, several challenges persist in contemporary methods, including their dependency on labeled training data, model compactness, robustness under challenging conditions, and their ability to generalize to novel unseen objects. A recent survey discussing the progress made on different aspects of this area, outstanding challenges, and promising future directions, is missing. To fill this gap, we discuss the recent advances in deep learning-based object pose estimation, covering all three formulations of the problem, i.e., instance-level, category-level, and unseen object pose estimation. Our survey also covers multiple input data modalities, degrees-of-freedom of output poses, object properties, and downstream tasks, providing the readers with a holistic understanding of this field. Additionally, it discusses training paradigms of different domains, inference modes, application areas, evaluation metrics, and benchmark datasets, as well as reports the performance of current state-of-the-art methods on these benchmarks, thereby facilitating the readers in selecting the most suitable method for their application. Finally, the survey identifies key challenges, reviews the prevailing trends along with their pros and cons, and identifies promising directions for future research. We also keep tracing the latest works at Awesome-Object-Pose-Estimation. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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Research on CT Image Grading of Superior Mesenteric Artery Based on AA Res-Unet 7th

Research on CT Image Grading of Superior Mesenteric Artery B...

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7th International Conference on Life System Modeling and Simulation, LSMS 2021, and 7th International Conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2021

作者： Han, Yu Chen, Jinghao Xu, Peixia Wang, Meirong Zhu, YuanFan Zhang, Kun He, Bosheng School of Electrical Engineering Nantong University Nantong China Department of Radiology The Second Affiliated Hospital of Nantong University Nantong China Nantong Key Laboratory of Intelligent Medicine Innovation and Transformation Nantong China Nantong Key Laboratory of Intelligent Control and Intelligent Computing Nantong China School of Management Science and Engineering ChongqingTechnology and Business University Chongqing China

ISBN: (纸本)9789811672064

In recent years, the incidence of Crohn’s disease (CD) is on the rise, which calls for more accurate and less invasive diagnostic tools. Crohn’s disease usually need to be confirmed by colonoscopy, and this paper puts forward a network model AA Res-Unet based on the fundamental Unet, can realize automatic of superior mesenteric artery CT image segmentation, and further to realize the automatic grading function, help doctors by observing the superior mesenteric artery features, early diagnosis of disease. Image segmentation achieved a per case precision of 98.76%, recall of 98.00%, and 98.34% of F1 score. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Image segmentation

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Proximal-like algorithms for equilibrium seeking in mixed-integer Nash equilibrium problems

Proximal-like algorithms for equilibrium seeking in mixed-in...

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IEEE Conference on Decision and control

作者： Filippo Fabiani Barbara Franci Simone Sagratella Martin Schmidt Mathias Staudigl Department of Engineering Science University of Oxford United Kingdom IMT School for Advanced Studies Lucca Lucca Italy Department of Advanced Computing Sciences Maastricht University Maastricht The Netherlands Department of Computer Control and Management Engineering Antonio Ruberti (DIAG) Sapienza University of Rome Rome Italy Department of Mathematics at Trier University Universitätsring 15 54296 Trier Germany

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

We consider potential games with mixed-integer variables, for which we propose two distributed, proximallike equilibrium seeking algorithms. Specifically, we focus on two scenarios: i) the underlying game is generalized ordinal and the agents update through iterations by choosing an exact optimal strategy; ii) the game admits an exact potential and the agents adopt approximated optimal responses. By exploiting the properties of integer-compatible regularization functions used as penalty terms, we show that both algorithms converge to either an exact or an ϵ-approximate equilibrium. We corroborate our findings on a numerical instance of a Cournot oligopoly model.

关键词： Computational modeling Measurement uncertainty Stochastic processes Games Approximation algorithms Nash equilibrium Cost function

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High-Gain Like Observer Design for Nonlinear Systems Applied to Vehicle Motion Estimation

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IFAC-PapersOnLine 2023年第2期56卷 5673-5678页

作者： H. Bessafa C. Delattre Z. Belkhatir A. Zemouche R. Rajamani Université de Lorraine CRAN CNRS UMR 7039 54400 Cosnes et Romain France School of Electronics and Computer Science University of Southampton University Road Southampton SO17 1BJ UK Faculty of Computing Engineering and Media De Montfort University The Gateway Leicester LE1 9BH UK Laboratory for Innovations in Sensing Estimation and Control Department of Mechanical Engineering University of Minnesota Minneapolis USA

This work investigates the problem of state estimation for nonlinear triangular systems having additional output measurements. The main objective of this paper is to propose observer design strategies that account for the available additional information, which is difficult to consider using the standard high-gain observer methodology. To deal with this challenge, we propose a novel observer design method to handle the additional output measurements. This method can be thought of as an extension of the standard high-gain observer by introducing a weighting matrix as a tuning parameter, which uses both the high-gain methodology and the LPV/LMI technique. The proposed approach was applied to a nonlinear longitudinal dynamic model that uses extra measurement information, in addition to the measured longitudinal position of the vehicle.

关键词： Observer design High-gain observer LPV/LMI observer Autonomous Vehicles Longitudinal dynamic model

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Hamiltonian Learning using Machine Learning Models Trained with Continuous Measurements

arXiv

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arXiv 2024年

作者： Tucker, Kris Rege, Amit Kiran Smith, Conor Monteleoni, Claire Albash, Tameem Department of Applied Math University of Colorado Boulder United States Department of Computer Science University of Colorado Boulder United States Center for Quantum Information and Control University of New Mexico University of New Mexico AlbuquerqueNM United States Department of Electrical and Computer Engineering University of New Mexico AlbuquerqueNM United States INRIA Centre de Recherche de Paris France Center for Computing Research Sandia National Laboratories AlbuquerqueNM87185 United States

We build upon recent work on using Machine Learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervised learning where the weak measurement training record can be labeled with known Hamiltonian parameters, and (2) unsupervised learning where no labels are available. The first has the advantage of not requiring an explicit representation of the quantum state, thus potentially scaling very favorably to a larger number of qubits. The second requires the implementation of a physical model to map the Hamiltonian parameters to a measurement record, which we implement using an integrator of the physical model with a recurrent neural network to provide a model-free correction at every time step to account for small effects not captured by the physical model. We test our construction on a system of two qubits and demonstrate accurate prediction of multiple physical parameters in both the supervised and unsupervised contexts. We demonstrate that the model benefits from larger training sets establishing that it is in fact "learning," and we show robustness to errors in the assumed physical model by achieving accurate parameter estimation in the presence of unanticipated single particle relaxation. © 2024, CC BY.

关键词： Qubits

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