检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Zhang, Xiaorui Zhang, Wenzheng Sun, Wei Song, Aiguo Xu, Tong Engineering Research Center of Digital Forensics Ministry of Education Jiangsu Engineering Center of Network Monitoring School of Computer and Software Nanjing University of Information Science & Technology Nanjing210044 China Wuxi Research Institute Nanjing University of Information Science & Technology Wuxi214100 China School of Automation Nanjing University of Information Science & Technology Nanjing210044 China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and Control School of Instrument Science and Engineering Southeast University Nanjing210096 China University of Southern California Los AngelesCA United States

Flexible tissue modeling plays an important role in the field of telemedicine. It is related to whether the soft tissue deformation process can be accurately, real-time and vividly simulated during surgery. However, most existing models lack the unique biological characteristics. To solve this problem, a high-fidelity virtual liver model incorporating biological characteristics, such as the viscoelastic, anisotropic and nonlinear biological characteristics, is proposed based on the finite element model. When simulating the resection of diseased livers, the model undergoes a plastic deformation process where the model loses elasticity due to excessive deformation, but does not reach the cutting fracture threshold. To improve the fidelity of the liver model, this study is the first to introduce the viscoplasticity of biological tissues to the liver model. The 3DMax2020 and OpenGL4.6 were used to build a liver surgery simulation platform, and the PHANTOM OMNI manual controller was used to sense the feedback force during the operation. The proposed model was verified from three aspects of accuracy, fidelity and real-time performance. The experimental results show that the proposed virtual liver model can enhance visual perception ability, improve deformation accuracy and fidelity. © 2023, The Authors. All rights reserved.

关键词： Simulation platform

来源：评论

学校读者我要写书评

暂无评论

SoybeanNet: Transformer-Based Convolutional Neural Network for Soybean Pod Counting from Unmanned Aerial Vehicle (UAV) Images

arXiv

引用

arXiv 2023年

作者： Li, Jiajia Magar, Raju Thada Chen, Dong Lin, Feng Wang, Dechun Yin, Xiang Zhuang, Weichao Li, Zhaojian Department of Electrical and Computer Engineering Michigan State University East LansingMI United States Department of Plant Soil and Microbial Sciences Michigan State University East LansingMI United States Environmental Institute Link Lab University of Virginia CharlottesvilleVA United States Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China School of Mechanical Engineering Southeast University Nanjing China Department of Mechanical Engineering Michigan State University East LansingMI48824 United States

Soybean is a critical source of food, protein and oil, and thus has received extensive research aimed at enhancing their yield, refining cultivation practices, and advancing soybean breeding techniques. Within this context, soybean pod counting plays an essential role in understanding and optimizing production. Despite recent advancements, the development of a robust pod-counting algorithm capable of performing effectively in real-field conditions remains a significant challenge This paper presents a pioneering work of accurate soybean pod counting utilizing unmanned aerial vehicle (UAV) images captured from actual soybean fields in Michigan, USA. Specifically, this paper presents SoybeanNet, a novel point-based counting network that harnesses powerful transformer backbones for simultaneous soybean pod counting and localization with high accuracy. In addition, a new dataset of UAV-acquired images for soybean pod counting was created and open-sourced, consisting of 113 drone images with more than 260k manually annotated soybean pods captured under natural lighting conditions. Through comprehensive evaluations, SoybeanNet demonstrates superior performance over five state-of-the-art approaches when tested on the collected images. Remarkably, SoybeanNet achieves a counting accuracy of 84.51% when tested on the testing dataset, attesting to its efficacy in real-world scenarios. The publication also provides both the source code (https://***/JiajiaLi04/Soybean-Pod-Counting-from-UAV-Images) and the labeled soybean dataset (https://***/datasets/jiajiali/uav-based-soybean-pod-images), offering a valuable resource for future research endeavors in soybean pod counting and related fields. © 2023, CC BY-NC-SA.

关键词： Statistical tests

来源：评论

学校读者我要写书评

暂无评论

Driving on Highway by Using Reinforcement Learning with CNN and LSTM Networks

Driving on Highway by Using Reinforcement Learning with CNN ...

引用

IEEE International Conference on Intelligent Engineering Systems (INES)

作者： László Szőke Szilárd Aradi Tamás Bécsi Péter Gáspár Department of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics H-1111 Budapest Hungary Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences H-1111 Budapest Hungary

ISBN: (数字)9781728110592

ISBN: (纸本)9781728110608

This work presents a powerful and intelligent driver agent, designed to operate in a preset highway situation using Policy Gradient Reinforcement Learning (RL) agent. Our goal is to create an agent that is capable of navigating safely in changing highway traffic and successfully accomplish to get through the defined section keeping the reference speed. Meanwhile, creating a state representation that is capable of extracting information from images based on the actual highway situation. The algorithm uses Convolutional Neural Network (CNN) with Long-Short Term Memory (LSTM) layers as a function approximator for the agent with discrete action space on the control level, e.g., acceleration and lane change. Simulation of Urban MObility (SUMO), an open-source microscopic traffic simulator is chosen as our simulation environment. It is integrated with an open interface to interact with the agent in real-time. The agent can learn from numerous driving and highway situations that are created and fed to it. The representation becomes more general by randomizing and customizing the behavior of the other road users in the simulation, thus the experience of the agent can be much more diverse. The article briefly describes the modeling environment, the details on the learning agent, and the rewarding scheme. After evaluating the experiences gained from the training, some further plans and optimization ideas are briefed.

关键词： Road transportation Learning (artificial intelligence) Vehicles Training Neural networks Aerospace electronics Acceleration

来源：评论

学校读者我要写书评

暂无评论

A New LMI-Based controller Design Method for Uncertain Differential Repetitive Processes 1

引用

20th Polish control Conference, PCC 2020

作者： Maniarski, Robert Paszke, Wojciech Rogers, Eric Institute of Control and Computation Engineering University of Zielona Góra Szafrana 2 Zielona Góra65-516 Poland Institute of Automation Electronic and Electrical Engineering University of Zielona Góra Szafrana 2 Zielona Góra65-516 Poland School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

ISBN: (数字)9783030509361

ISBN: (纸本)9783030509354

The paper develops new results on stability analysis and control law design for differential linear repetitive processes. These results are based on new dilated LMI characterizations for stability along the pass where auxiliary slack variables with full structure are employed. This provides additional flexibility to the solution. The results are also easily extended to processes with norm-bounded uncertainties. It is also shown that the generalized Kalman-Yakubovich-Popov lemma can be used to obtain stability and controller design procedures in which performance specifications are imposed over finite frequency ranges. Sufficient conditions for the existence of a robust controller in this setting are established. Finally, a simulation example is given to illustrate the merits of the new design. © 2020, Springer Nature Switzerland AG.

关键词： Linear matrix inequalities

来源：评论

学校读者我要写书评

暂无评论

MODELING AND FUZZY control OF PERMANENT MAGNET SYNCHRONOUS MOTORS

MODELING AND FUZZY CONTROL OF PERMANENT MAGNET SYNCHRONOUS M...

引用

The 10th International Conference on Power Electronics, Machines and Drives (PEMD 2020)

作者： D.-K. Jukić T. Varga T. Benšić V. J. Štil M. Barukčić Automation and Control Institute TU Wien Vienna Austria Faculty of Electrical Engineering Computer Science and Information Technology Osijek Josip Juraj Strossmayer University of Osijek Osijek Croatia

This paper deals with Permanent Magnet Synchronous Motor modeling and control. The derived nonlinear dq model is a combination of Finite Element Method simulation data with the classical dq model. The so derived model keeps the precision of the Finite Element Method simulations and also the fast execution times of the dq model. The Finite Element Method data is included in the dq model using Artificial Neural Networks. The derived model is also used for controller design. The chosen controller is a PI like Fuzzy Logic controller, which is tuned using Genetic Algorithm optimization. The Permanent Magnet Synchronous Motor with Fuzzy Logic controller operation is tested using Real-Time (Model-in-the-Loop) simulations.

关键词： fuzzy control finite element analysis genetic algorithms neural nets permanent magnet motors machine control synchronous motors nonlinear control systems PI control electric machine analysis computing

来源：评论

学校读者我要写书评

暂无评论

A Visual-Inertial Vehicle Navigation System Based Line Feature

A Visual-Inertial Vehicle Navigation System Based Line Featu...

引用

Artificial Intelligence and Electromechanical automation (AIEA), International Conference on

作者： Xingxing Guang Yanbin Gao Pan Liu Guangchun Li Ningbo Li Henry Leung College of Automation Harbin Engineering University Harbin China Department of Electrical and Computer Engineering University of Calgary Calgary Canada Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (数字)9781728182889

ISBN: (纸本)9781728182896

In this paper, an integrated navigation system based on visual and inertial sensors for vehicles is proposed to solve the low accuracy position estimation problem caused by the unavailability signal of GNSS. In the proposed method, the visual sensor provides not only the attitude information by visual attitude method but also the motion information by visual odometer algorithm. Because the visual information is used in two separate ways, the proposed integrated navigation method has better robustness in dynamic conditions. It is verified by experiments in dynamic conditions. The experimental results show that the attitude errors of the proposed method can be reduced an order of magnitude than the previous visual attitude aided inertial navigation systems. For position estimation, the proposed method can improve the accuracy, stability, and reliability of the vehicle navigation system.

关键词： inertial integrated navigation dynamic line feature representation visual odometer vehicle navigation Vehicle navigation vehicle navigation systems Visualization position estimation Inertial navigation systems inertia sensor Navigation systems visual information Global Navigation Satellite System Attitude

来源：评论

学校读者我要写书评

暂无评论

Interpretable classification of epileptic EEG signals using ALIF decomposition and attention-augmented cascaded deep neural networks

引用

Applied Soft Computing 2025年 180卷

作者： Wei Zeng Minglin Zhang Liangmin Shan Yang Chen Zuoyong Li Shaoyi Du School of Physics and Mechanical and Electrical Engineering Longyan University Longyan 364012 PR China School of Mechanical Engineering and Automation Fuzhou University Fuzhou 350116 PR China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou 350121 PR China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an 710049 PR China

Epilepsy is a chronic neurological disorder characterized by recurrent seizures. Accurate diagnosis and effective monitoring require the precise classification of electroencephalogram (EEG) signals. In this study, we introduce a novel approach that combines Adaptive Local Iterative Filtering (ALIF) for signal decomposition with an attention-enhanced cascaded deep neural network (CDNN) architecture. The ALIF algorithm decomposes EEG signals into intrinsic mode functions (IMFs) that capture inherent oscillatory components. These IMFs are processed by the CDNN, which operates in two stages: a feature extraction module and a classification module. In the feature extraction stage, a SEblock channel attention mechanism dynamically prioritizes significant features within the IMFs. The classification stage employs a hybrid CNN-LSTM architecture that effectively captures both spatial and temporal dependencies. To enhance interpretability, the SHapley Additive exPlanations (SHAP) framework is incorporated to provide insights into the model’s decision-making process, while Gradient-weighted Class Activation Mapping (Grad-CAM) visualizes the most discriminative regions in the input data. Rigorously validated using 10-fold cross-validation on the Bonn and EEG Epilepsy databases, the proposed methodology achieved an exceptional classification accuracy of 100%, with sensitivity, specificity, and F1-scores exceeding 99% across various scenarios. The integration of SHAP and Grad-CAM not only elucidates the model’s decision processes but also contributes to a more interpretable and reliable system for epileptic EEG signal classification. This synergistic combination of advanced signal processing, deep learning, and interpretability techniques holds significant potential to enhance epilepsy diagnosis and strengthen trust in clinical decision support systems.

关键词： ALIF decomposition Cascaded deep neural networks Epileptic EEG signals SEBlock attention mechanism

来源：评论

学校读者我要写书评

暂无评论

Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach

arXiv

引用

arXiv 2022年

作者： Li, Yang Wei, Xinhao Li, Yuanzheng Dong, Zhaoyang Shahidehpour, Mohammad The Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China The School of Artifcial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The Electrical and Computer Engineering Department Illinois Institute of Technology ChicagoIL60616 United States The ECE Department The King Abdulaziz University Saudi Arabia

As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one of the top-priority cyber-related issues and has received increasing attention in recent years. However, so far little attention has been paid to privacy preservation issues in the detection of FDIAs in smart grids. Inspired by federated learning, a FDIA detection method based on secure federated deep learning is proposed in this paper by combining Transformer, federated learning and Paillier cryptosystem. The Transformer, as a detector deployed in edge nodes, delves deep into the connection between individual electrical quantities by using its multi-head self-attention mechanism. By using federated learning framework, our approach utilizes the data from all nodes to collaboratively train a detection model while preserving data privacy by keeping the data locally during training. To improve the security of federated learning, a secure federated learning scheme is designed by combing Paillier cryptosystem with federated learning. Through extensive experiments on the IEEE 14-bus and 118-bus test systems, the effectiveness and superiority of the proposed method are verified. Copyright © 2022, The Authors. All rights reserved.

关键词： Smart power grids

来源：评论

学校读者我要写书评

暂无评论

Acceleration Command based Visual Servoing with Artificial Induced Time-Delay 19

Acceleration Command based Visual Servoing with Artificial I...

引用

Proceedings of the 2019 4th International Conference on Advances in Robotics

作者： Madhu Yadav Chimmula Kishore Indra Narayan Kar Sumantra Dutta Roy Control & Automation Group Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi India Computer Technology Group Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi India

ISBN: (纸本)9781450366502

The tracking of an object using visual feedback by controlling the camera motion is known as Visual Servoing. In general most of visual servoing techniques use camera velocity as control input. In this paper, camera acceleration is used for deriving the control law. The use of acceleration input can accomplish smoother operating trajectory. However, this controller requires the first order feature measurement which may not be available. In this paper, to circumvent the issue, a time-delayed approximation is used for the non-measurable system states. The controller parameters are obtained from the stability analysis of the closed-loop time-delay system using Lyapunov-Razumikhin approach. The implemented controller is able to track the desired feature smoothly. These results establish a complementary approach to the existing acceleration-based augmented controller design.

关键词： Acceleration input

来源：评论

学校读者我要写书评

暂无评论

Scalable robustness of interconnected systems subject to structural changes

arXiv

引用

arXiv 2020年

作者： Knorn, Steffi Besselink, Bart Institute of Automation Engineering Otto-von-Guericke University Magdeburg Germany Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence Jan C. Willems Centre for Systems and Control University of Groningen Netherlands

This paper studies the robustness of large-scale interconnected systems with respect to external disturbances, focussing on their scalability properties. Specifically, a notion of scalability is introduced that asks for these robustness properties to remain unchanged under a structural change of the system, such as the addition/removal of a subsystem or a change in the interconnection structure. Both necessary and sufficient conditions, in terms of the interconnection structure and edge weights, are given under which elementary structural changes are scalable. The results are illustrated through a simple *** Codes 93A15 (Primary), Copyright © 2020, The Authors. All rights reserved.

关键词： Large scale systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：