检索结果-内蒙古大学图书馆

Optimizing Steering Angle Predictive Convolutional Neural Network for Autonomous Car

Computers, Materials & Continua 2022年第5期71卷 2285-2302页

作者： Hajira Saleem Faisal Riaz Asadullah Shaikh Khairan Rajab Adel Rajab Muhammad Akram Mana Saleh Al Reshan Control Automotive and Robotics Lab Affiliated lab of National Center of Robotics and Automation(NCRA HEC Pakistan)and with the Department of Computer Science and Information TechnologyMirpur University of Science and Technology(MUST)Mirpur Azad Kashmir10250Pakistan College of Computer Science and Information System Najran UniversityNajran61441Saudi Arabia College of Computer Science and Engineering University of South FloridaTampa33620United States

Deep learning techniques,particularly convolutional neural networks(CNNs),have exhibited remarkable performance in solving visionrelated problems,especially in unpredictable,dynamic,and challenging *** autonomous vehicles,imitation-learning-based steering angle prediction is viable due to the visual imagery comprehension of *** this regard,globally,researchers are currently focusing on the architectural design and optimization of the hyperparameters of CNNs to achieve the best *** has proven the superiority of metaheuristic algorithms over the manual-tuning of ***,to the best of our knowledge,these techniques are yet to be applied to address the problem of imitationlearning-based steering angle ***,in this study,we examine the application of the bat algorithm and particle swarm optimization algorithm for the optimization of the CNN model and its hyperparameters,which are employed to solve the steering angle prediction *** validate the performance of each hyperparameters’set and architectural parameters’set,we utilized the Udacity steering angle dataset and obtained the best results at the following hyperparameter set:optimizer,Adagrad;learning rate,0.0052;and nonlinear activation function,exponential linear *** per our findings,we determined that the deep learning models show better results but require more training epochs and time as compared to shallower *** show the superiority of our approach in optimizing CNNs through metaheuristic algorithms as compared with the manual-tuning *** testing was also performed using the model trained with the optimal architecture,which we developed using our approach.

关键词： Bat algorithm convolutional neural network hyperparameters metaheuristic optimization algorithm steering angle prediction

来源：评论

学校读者我要写书评

暂无评论

Research on geomembrane leakage detection method based on quadruped robot

Research on geomembrane leakage detection method based on qu...

引用

2024 China automation Congress, CAC 2024

作者： Zhang, Pengcheng Hu, Ningning Wang, Xiao Xi, Qingbiao Zhao, Haohao Wu, Xingchen Qin, Linfeng Yuan, Dongli Investigation & Testing Research Institute Shanghai Investigation Design & Research Institute Co. Ltd. Shanghai China System Department 2 Xi'an ASN Technology Group Co. Ltd Xi'an China School of Electronic and Control Engineering Chang'an University Xi'an China School of Automation Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9798350368604

Aiming at the problem of leakage detection of seepage control geomembranes in landfills, a fully autonomous dipole method detection system based on a quadruped robot equipped with a dipole sensor is designed. The feasibility and superiority of using a quadruped robot are analyzed on the basis of the detection principle of the dipole method. Due to the problems existing in the process of upgrading the artificial static detection to autonomous dynamic detection, a dynamic detection method based on a quadruped robot is designed while the structure construction of the dipole method on the quadruped robot is completed. The experimental results show that the efficiency of geomembrane leakage detection can be improved with detection system method employed in this paper. © 2024 IEEE.

关键词： Geomembranes

来源：评论

学校读者我要写书评

暂无评论

Resilient Distributed Parameter Estimation in Sensor Networks

Resilient Distributed Parameter Estimation in Sensor Network...

引用

American Control Conference (ACC)

作者： Jiaqi Yan Kuo Li Hideaki Ishii Department of Computer Science Tokyo Institute of Technology Japan Department of Automation Center for Intelligent and Networked System BNRist Tsinghua University P.R. China

In this paper, we study the problem of parameter estimation in a sensor network, where the measurements and updates of some sensors might be arbitrarily manipulated by adversaries. Despite the presence of such misbehaviors, normally behaving sensors make successive observations of an unknown d-dimensional vector parameter and aim to infer its true value by cooperating with their neighbors over a directed communication graph. To this end, by leveraging the so-called dynamic regressor extension and mixing procedure, we transform the problem of estimating the vector parameter to that of estimating d scalar ones. For each of the scalar problem, we propose a resilient combine-then-adapt diffusion algorithm, where each normal sensor performs a resilient combination to discard the suspicious estimates in its neighborhood and to fuse the remaining values, alongside an adaptation step to process its streaming observations. With a low computational cost, this estimator guarantees that each normal sensor exponentially infers the true parameter even if some of them are not sufficiently excited.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Novel Unsupervised MRI Synthetic CT Image Generation Framework with Registration Network

引用

Computers, Materials & Continua 2023年第11期77卷 2271-2287页

作者： Liwei Deng Henan Sun Jing Wang Sijuan Huang Xin Yang Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration School of AutomationHarbin University of Science and TechnologyHarbin150080China Institute for Brain Research and Rehabilitation South China Normal UniversityGuangzhou510631China Department of Radiation Oncology Sun Yat-sen University Cancer CenterState Key Laboratory of Oncology in South ChinaCollaborative Innovation Center for Cancer MedicineGuangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and TherapyGuangzhou510060China

In recent years,radiotherapy based only on Magnetic Resonance(MR)images has become a hot spot for radiotherapy planning research in the current medical ***,functional computed tomography(CT)is still needed for dose calculation in the *** deep-learning approaches to synthesized CT images from MR images have raised much research interest,making radiotherapy based only on MR images *** this paper,we proposed a novel unsupervised image synthesis framework with registration *** paper aims to enforce the constraints between the reconstructed image and the input image by registering the reconstructed image with the input image and registering the cycle-consistent image with the input ***,this paper added ConvNeXt blocks to the network and used large kernel convolutional layers to improve the network’s ability to extract *** research used the collected head and neck data of 180 patients with nasopharyngeal carcinoma to experiment and evaluate the training model with four evaluation *** the same time,this research made a quantitative comparison of several commonly used model *** evaluate the model performance in four evaluation metrics which achieve Mean Absolute Error(MAE),Root Mean Square Error(RMSE),Peak Signal-to-Noise Ratio(PSNR),and Structural Similarity(SSIM)are 18.55±1.44,86.91±4.31,33.45±0.74 and 0.960±0.005,*** with other methods,MAE decreased by 2.17,RMSE decreased by 7.82,PSNR increased by 0.76,and SSIM increased by *** results show that the model proposed in this paper outperforms other methods in the quality of image *** work in this paper is of guiding significance to the study of MR-only radiotherapy planning.

关键词： MRI-CT image synthesis variational auto-encoder medical image translation MRI-only based radiotherapy

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Safe Controller Synthesis for Deterministic systems: A Posteriori Method With Validation Tests

Data-Driven Safe Controller Synthesis for Deterministic Syst...

引用

IEEE Conference on Decision and Control

作者： Yu Chen Chao Shang Xiaolin Huang Xiang Yin Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Department of Automation Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China

In this work, we investigate the data-driven safe control synthesis problem for unknown dynamic systems. We first formulate the safety synthesis problem as a robust convex program (RCP) based on notion of control barrier function. To resolve the issue of unknown system dynamic, we follow the existing approach by converting the RCP to a scenario convex program (SCP) by randomly collecting finite samples of system trajectory. However, to improve the sample efficiency to achieve a desired confidence bound, we provide a new posteriori method with validation tests. Specifically, after collecting a set of data for the SCP, we further collect another set of independent validate data as posterior information to test the obtained solution. We derive a new overall confidence bound for the safety of the controller that connects the original sample data, the support constraints, and the validation data. The efficiency of the proposed approach is illustrated by a case study of room temperature control. We show that, compared with existing methods, the proposed approach can significantly reduce the required number of sample data to achieve a desired confidence bound.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Explore the dominant factor in prime editing via a view of DNA processing

引用

Synthetic and systems Biotechnology 2023年第3期8卷 371-377页

作者： Zhimeng Xu Dacheng Ma Houzhen Su Xiaodong Jia Yinqing Li Yinying Lu Zhen Xie MOE Key Laboratory of Bioinformatics and Bioinformatics Division Center for Synthetic and System BiologyDepartment of AutomationBeijing National Research Center for Information Science and TechnologyTsinghua UniversityBeijing100084China Research Center for Biological Computation Zhejiang LaboratoryHangzhou311100China Comprehensive Liver Cancer Centre The Fifth Medical Center of PLA General HospitalBeijingChina School of Pharmaceutical Sciences IDG/McGovern Institute for Brain ResearchTsinghua UniversityBeijingChina

Prime editing is a revolutionary gene-editing method that is capable of introducing insertions,deletions and base substitutions into the ***,the editing efficiency of Prime Editor(PE)is limited by the DNA repair ***,we show that overexpression of the flap structure-specific endonuclease 1(FEN1)and the DNA ligase 1(LIG1)increases the efficiency of prime editing,which is similar to the dominant negative mutL homolog 1(MLH1dn).In addition,MLH1 is still the dominant factor over FEN1 and LIG1 in prime *** results help to further understand the relationship of proteins involved in prime editing and envisage future directions for the development of PE.

关键词： process. prime directions

来源：评论

学校读者我要写书评

暂无评论

Integrated Dual Static Var Compensators to Reduce Railway Power Quality Conditioner Volt-ampere Rating in Co-phase V/v Traction system

Integrated Dual Static Var Compensators to Reduce Railway Po...

引用

Power Electronic and Drive systems and Technologies Conference (PEDSTC)

作者： Mohammad Habibolahzadeh Alireza Jalilian Department of Electrical Engineering Iran University of Science and Technology Tehran Iran Department of Electrical Engineering Centre of Excellence for Power System Automation and Operation Iran University of Science and Technology Tehran Iran

This paper proposes a V/v co-phase supply system structure consisting of dual Static Var Compensators (SVCs) connected in parallel with a Railway static Power Quality Conditioner (RPC). Dual SVCs play a crucial function in this configuration by compensating load and grid reactive powers, while the role of the RPC is limited to balancing active currents through the two output phases of the V/v transformer. Analysis of the RPC operating region shows that the RPC's compensation currents and dc-link voltage are more modest than those of the conventional design. Also included is a theoretical approach to matching converter output impedances. The comprehensive equations of the PQ instantaneous power theory are given, which are used in either present or traditional schemes. This design eliminates the need for passive filters by providing a control system specifically for suppressing harmonics caused by loads and SVCs. The RPC volt-ampere rating is also affected by load power factors, which may be lowered to as high as 43%. Therefore, the affordable design raises RPC adoption.

关键词： Reactive power Passive filters Impedance matching Power quality Harmonic analysis Transformers Rail transportation

来源：评论

学校读者我要写书评

暂无评论

Fault Diagnosis of Aero-Engine Bearings in Comprehensive Noise Environments Based on Multi-Scale Convolution Networks

Fault Diagnosis of Aero-Engine Bearings in Comprehensive Noi...

引用

International Symposium on system and Software Reliability (ISSSR)

作者： HongBo Ran JianXin Zhang JinHua Mi School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Department of SRM Design Shanghai Space Propulsion Technology Research Institute Shanghai China Center for System Reliability and Safety University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798331501242

ISBN: (纸本)9798331501259

For aero-engines operating in harsh environments, the presence of substantial noise poses challenges to effective fault diagnosis, a multi-scale attention residual network (MCRN) is proposed. Firstly, time-frequency images are obtained by short-time Fourier transform of the raw vibration signals. Secondly, multi-scale convolution is applied to feature extraction from the time-frequency images, and channel attention mechanism is employed to suppress irrelevant channels. Simultaneously, a spatial attention mechanism is employed to filter out useless spatial features. While considering the presence of noise interference, the concept of noise as an interval is proposed and injected into the signal. Lastly, the requirement of certain prior knowledge for interval noise determination is acknowledged, and an approach considering comprehensive noise injection is proposed. Through a series of comparative experiments, it is found that the MCRN proposed in this study can maintain a high accuracy rate and high robustness, which makes it suitable for applications in actual complex working conditions.

关键词： Fault diagnosis Time-frequency analysis Attention mechanisms Convolution Noise Feature extraction Robustness Aircraft propulsion Engines Residual neural networks

来源：评论

学校读者我要写书评

暂无评论

Node Importance Estimation Leveraging LLMs for Semantic Augmentation in Knowledge Graphs

arXiv

引用

arXiv 2024年

作者： Lin, Xinyu Zhang, Tianyu Hou, Chengbin Wang, Jinbao Xue, Jianye Lv, Hairong School of Computing and Artificial Intelligence Fuyao University of Science and Technology Fuzhou China Department of Automation Tsinghua University Beijing China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China

Node Importance Estimation (NIE) is a task that quantifies the importance of node in a graph. Recent research has investigated to exploit various information from Knowledge Graphs (KGs) to estimate node importance scores. However, the semantic information in KGs could be insufficient, missing, and inaccurate, which would limit the performance of existing NIE models. To address these issues, we leverage Large Language Models (LLMs) for semantic augmentation thanks to the LLMs’ extra knowledge and ability of integrating knowledge from both LLMs and KGs. To this end, we propose the LLMs Empowered Node Importance Estimation (LENIE) method to enhance the semantic information in KGs for better supporting NIE tasks. To our best knowledge, this is the first work incorporating LLMs into NIE. Specifically, LENIE employs a novel clustering-based triplet sampling strategy to extract diverse knowledge of a node sampled from the given KG. After that, LENIE adopts the node-specific adaptive prompts to integrate the sampled triplets and the original node descriptions, which are then fed into LLMs for generating richer and more precise augmented node descriptions. These augmented descriptions finally initialize node embeddings for boosting the downstream NIE model performance. Extensive experiments demonstrate LENIE’s effectiveness in addressing semantic deficiencies in KGs, enabling more informative semantic augmentation and enhancing existing NIE models to achieve the state-of-the-art performance. The source code of LENIE is freely available at https://***/XinyuLin-FZ/LENIE. Copyright © 2024, The Authors. All rights reserved.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Fault Diagnosis of Mechanical Transmission Components with Siam-GNN Under Few-Shot Noisy Conditions

Fault Diagnosis of Mechanical Transmission Components with S...

引用

International Symposium on system and Software Reliability (ISSSR)

作者： Zhiguo Wang Shengjie Yin Jinhua Mi School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Department of SRM Design Shanghai Space Propulsion Technology Research Institute Shanghai China Center for System Reliability and Safety University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798331501242

ISBN: (纸本)9798331501259

Fault diagnosis of mechanical transmission components is challenged by limited fault samples and noise interference. Deep learning methods often overlook the implicit topological relationships between samples. Graph neural networks (GNNs) efficiently aggregate feature information of neighboring nodes based on the dependencies and topological relationships among samples, demonstrating strong reasoning capabilities. However, determining node adjacency via K-nearest neighbor (KNN) in traditional GNNs can lead to node misconnections under few-shot conditions with noise interference, resulting in erroneous feature aggregation. Therefore, this paper proposes an inductive fault diagnosis method based on a Siamese Graph neural network (Siam-GNN). Firstly, this paper introduces the Siamese network to determine node adjacency relationships innovatively, optimizing the quality of association graph by increasing distances between nodes of the same category and decreasing distances between nodes of different categories. Subsequently, the classic contrastive loss function is improved to enhance the robustness under noisy conditions. Finally, ablation and comparative experiments are conducted on rolling bearings and planetary gearboxes based on the proposed fault diagnosis method, demonstrating the proposed method's stronger robustness, higher diagnostic accuracy and good generalization performance across both types of transmission components.

关键词： Fault diagnosis Accuracy Noise Rolling bearings Interference Nearest neighbor methods Graph neural networks Robustness Noise measurement Security

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：