检索结果-内蒙古大学图书馆

2nd IEEE International Conference on Image Processing and computer Applications, ICIPCA 2024

作者： Su, Shuzhi Xu, Mengjie Chen, Jian Zhu, Yanmin School of Computer Science and Engineering Anhui University of Science & Technology Anhui Huainan232001 China School of Mechanical and Electrical Engineering Anhui University of Science & Technology Anhui Huainan232001 China

ISBN: (纸本)9798350360240

Fault diagnosis is difficult to determine intrinsic locality relationships of multi-modal fault data. Aiming at the issue, we propose a novel cross-modal hyperbolic subspace fault diagnosis method. In the method, we construct a cross-modal hyperbolic subspace learning model by integrating local correlation theory and hyperbolic space learning, and the model can solve the local distortion of the Euclidean space manifolds. Besides, we derive analytical solutions of the model by means of Lagrange multiplier, and the cross-modal fault features with good class separability can be obtained by space projection. Experiments on the Paderborn dataset shows the effectiveness of our method in cross-modal fault diagnosis. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Precision autofocus in optical microscopy with liquid lenses controlled by deep reinforcement learning

引用

Microsystems & Nanoengineering 2024年第6期10卷 559-571页

作者： Jing Zhang Yong-feng Fu Hao Shen Quan Liu Li-ning Sun Li-guo Chen School of Mechanical and Electrical Engineering Soochow UniversityNo.8 Jixue RoadSuzhou CityJiangsu 215000China School of Computer Science and Technology Soochow UniversityNo.333 Ganjiang East RoadSuzhou CityJiangsu 215006China

Microscopic imaging is a critical tool in scientific research,biomedical studies,and engineering applications,with an urgent need for system miniaturization and rapid,precision autofocus ***,traditional microscopes and autofocus methods face hardware limitations and slow software speeds in achieving this *** response,this paper proposes the implementation of an adaptive Liquid Lens Microscope System utilizing Deep Reinforcement Learning-based Autofocus(DRLAF).The proposed study employs a custom-made liquid lens with a rapid zoom response,which is treated as an“agent.”Raw images are utilized as the“state”,with voltage adjustments representing the“actions.”Deep reinforcement learning is employed to learn the focusing strategy directly from captured images,achieving end-to-end *** contrast to methodologies that rely exclusively on sharpness assessment as a model’s labels or inputs,our approach involved the development of a targeted reward function,which has proven to markedly enhance the performance in microscope autofocus *** explored various action group design methods and improved the microscope autofocus speed to an average of 3.15 time ***,parallel“state”dataset lists with random sampling training are proposed which enhances the model’s adaptability to unknown samples,thereby improving its generalization *** experimental results demonstrate that the proposed liquid lens microscope with DRLAF exhibits high robustness,achieving a 79%increase in speed compared to traditional search algorithms,a 97.2%success rate,and enhanced generalization compared to other deep learning methods.

关键词： Deep hardware generalization

来源：评论

学校读者我要写书评

暂无评论

Assessing the stiffness of intact bone marrow with non-contact optical coherence elastography 12

Assessing the stiffness of intact bone marrow with non-conta...

引用

Optical Elastography and Tissue Biomechanics XII 2025

作者： Singh, Amandeep Singh, Manmohan Aglyamov, Salavat R. Mayerich, David Larin, Kirill V. Department of Biomedical Engineering University of Houston TX77204 United States Department of Mechanical and Aerospace Engineering University of Houston TX77204 United States Department of Electrical and Computer Engineering University of Houston TX77204 United States

ISBN: (纸本)9781510683907

Bone marrow plays an important role in regulating immunity for homeostasis and controlling stromal cell trafficking. Bone marrow cells are sustained by the framework of connective tissues that preserve the mechanical and functional integrity of the tissue. Optical coherence elastography (OCE) is a potential method to measure the biomechanical properties of bone marrow with high spatio-temporal resolution. In this work, we demonstrate the quantification of wave speed at different locations along the diaphysis of mice femur samples using non-contact air-coupled ultrasound OCE (ACUS-OCE). The preliminary results from the current approach show that the ACUS-OCE can characterize the mechanical stiffness of intact bone marrow and can be used for minimally invasive and ex vivo clinical applications. © 2025 SPIE.

关键词： Bone

来源：评论

学校读者我要写书评

暂无评论

Graph Convolutional Networks for Lithium-Ion Battery Health Estimation 10

Graph Convolutional Networks for Lithium-Ion Battery Health ...

引用

10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia

作者： He, Yuxin Deng, Zhongwei Nie, Wenhao Jiang, Chunlin University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu611731 China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China

ISBN: (纸本)9798350351330

Assessing the state of health (SOH) is essential for guaranteeing the safety and maintenance of lithium-ion batteries (LIBs). Nevertheless, due to the complex operating conditions, accurately estimating the capacity of LIBs is challenging. This study proposes a data-driven approach leveraging graph convolutional networks (GCN) to estimate the SOH of LIBs by utilizing multiple voltage segments. Then, the extracted voltage sequence is input into a graph generation layer(GGL), which transforms traditional sequential data into graph structured data. Finally, aggregating features from multiple nodes, and battery SOH estimation is achieved through a multi-layer perceptron. The efficacy of this approach in estimating battery SOH is validated using the MIT-Stanford dataset. Based on the results, the GCN method is able to achieve a high accuracy of 0.41% MAE and 0.63% RMSE, representing a substantial improvement over alternative methods. © 2024 IEEE.

关键词： Lithium-ion batteries

来源：评论

学校读者我要写书评

暂无评论

Need for Artificial Neural Networks in today’s world 4th

Need for Artificial Neural Networks in today’s world

引用

4th Annual International Conference on Data science, Machine Learning and Blockchain Technology, AICDMB 2023

作者： Siddesh Kumar, N.M. Promod Kumar, B.M. Haloor, Bheem Kumar Haran, Pranadhi Manoj Gowda, K.S. Hemashree, S.S. Department of Mechanical Engineering PES College of Engineering Mandya India Department of Computer Science and Engineering PES College of Engineering Mandya India Department of Electrical and Engineering PES College of Engineering Mandya India Department of Information Science and Engineering PES PES College of Engineering Mandya India

ISBN: (纸本)9781032426853

Artificial Neural Networks (ANNs) are widely used in various fields due to their versatile applications. They are capable of handling complex functions and can adapt to new conditions. Their applications range from data interpretation, drug design, pattern recognition, text translation, credit card fraud detection, medical diagnosis and more. ANNs have become an essential tool in today’s world due to their ability to interpret large amounts of data, making them crucial in fields such as medical diagnosis and credit card fraud detection. The versatility of ANNs makes them applicable in many different industries and continues to contribute to their growing popularity. The current work focuses on exploring the wide range of applications of ANNs and their significance in our world today. © 2024 The Author(s).

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Lightweight and Roubust Key Agreement for Securing IIoT-Driven Flexible Manufacturing Systems

引用

IEEE Internet of Things Journal 2025年第11期12卷 17197-17209页

作者： Hammad, Muhammad Badshah, Akhtar Almeer, Mohammed A. Waqas, Muhammad Song, Houbing Chen, Sheng Han, Zhu GIK Institute of Engineering Sciences and Technology Faculty of Mechanical Engineering Topi23640 Pakistan University of Malakand Department of Software Engineering Dir Lower18800 Pakistan University of Bahrain Computer Engineering Department College of Information Technology 32038 Bahrain University of Greenwich Faculty of Engineering and Science Centre for Sustainable Cybersecurity United Kingdom Edith Cowan University School of Engineering PerthWA6027 Australia Department of Information Systems BaltimoreMD United States University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

The ever-evolving Internet of Things (IoT) has ushered in a new era of intelligent manufacturing across multiple industries. However, the security and privacy of real-time data transmitted over the public channel of the industrial IoT (IIoT) remain formidable challenges. Existing lightweight protocols often omit one or more critical security features, such as anonymity and untraceability, and are susceptible to threats like desynchronization attacks. Additionally, they struggle to achieve an optimal balance between robust security and performance efficiency. To bridge these gaps, we introduce a new lightweight key agreement security scheme that guarantees secure access to the IIoT-enabled flexible manufacturing system (FMS). The strength of our scheme lies in its utilization of the authenticated encryption with associative data (AEAD) primitive, AEGIS, along with hash functions and physical unclonable functions, which secure the IIoT ecosystem. Additionally, our scheme offers flexibility in the form of the addition of new machines, password updates, and revocation in cases of theft or loss. A comprehensive security analysis demonstrates the efficacy of the proposed scheme in thwarting various attacks. The formal analysis, based on the Real-Or-Random (RoR) model, ensures session key indistinguishability, while the informal analysis highlights its resilience against known attacks. The comparative assessment demonstrate that the proposed scheme consistently outperforms the benchmark schemes across multiple dimensions, including security and functionality features, computational and communication overheads, and runtime efficiency. Specifically, the proposed scheme achieves peak performance enhancements of 77.55%, 44.73%, and 69.6% in computational overhead, runtime overhead, and communication overhead, respectively, underscoring its substantial performance advantages. © 2025 IEEE.

关键词： Flexible manufacturing systems

来源：评论

学校读者我要写书评

暂无评论

Extended Reality and Digital Twin in the Oil and Gas Pipeline Industry: A Systematic Review on Applications, Trends, and Future Directions 23

Extended Reality and Digital Twin in the Oil and Gas Pipelin...

引用

23rd IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2024

作者： Sarvesh, Muskan Kang, Ryan Nam, Hyeongil Park, Simon Hugo, Ron Maurer, Frank Kim, Kangsoo University of Calgary Department of Electrical and Software Engineering Canada University of Calgary Department of Mechanical and Manufacturing Engineering Canada University of Calgary Department of Computer Science Canada

ISBN: (纸本)9798331516475

Immersive and simulation technologies, such as Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), and Digital Twins (DTs), have proven effective in enhancing decision-making, streamlining operations, and improving safety through intuitive visualizations. Unsurprisingly, the oil and gas (O&G) pipeline industry is increasingly turning to these technologies to tackle complex construction and resource management challenges. This paper reviews the applications, benefits, and future trends of these technologies, focusing on integration and emerging trends in monitoring, training, maintenance, and testing. It identifies potential gaps, offers guidance for future research, and emphasizes adapting to technological evolution, providing insights to improve system reliability and sustainability in O&G pipeline operations using immersion and simulation methods. © 2024 IEEE.

关键词： Gas pipelines

来源：评论

学校读者我要写书评

暂无评论

Vibration analysis of elastically supported sandwich beam with damaged core and functionally graded face sheets

引用

Steel and Composite Structures 2025年第1期54卷 71-83页

作者： Wang, Lulu Mohsin, Hasan F. Bains, Pardeep Singh Sharma, Rohit Bohlooli, Nasrin College of Mechanical and Electrical Engineering Guangdong University of Science and Technology Guangdong Dongguan523083 China Computer Techniques Engineering Department Faculty of Information Technology Imam Ja’afar Al-Sadiq University Baghdad10011 Iraq Computer Technical Engineering Department College of Technical Engineering The Islamic University Najaf54001 Iraq University Karnataka Bengaluru560069 India Department of Mechanical Engineering Vivekananda Global University Rajasthan Jaipur303012 India School of Engineering and Technology Shobhit University Uttar Pradesh Gangoh247341 India Department of Mechanical Engineering Arka Jain University Jharkhand Jamshedpur831001 India Nabi Data Science & Computational Intelligence Research Co. Tehran Iran

This paper presents the influence of carbon nanotubes (CNTs) waviness, aspect ratio and damaged core on the vibrational behavior of functionally graded nanocomposite sandwich beams resting on two-parameter elastic foundations. The distributions of CNTs are considered functionally graded (FG) or uniform along the thickness of upper and bottom layers of the sandwich beam and their mechanical properties are estimated by an extended rule of mixture. In this study, the classical theory concerning the mechanical efficiency of a matrix embedding finite length fibers has been modified by introducing the tube-to-tube random contact, which explicitly accounts for the progressive reduction of the tubes’ effective aspect ratio as the filler content increases. A damage model is introduced to provide an analytical description of an irreversible rheological process that causes the decay of the mechanical properties, in terms of engineering constants. An isotropic damage is considered for the core of the sandwich beams. The equations of motion are derived based on Timoshenko beam theory and employing Hamilton’s principle. The problem is modeled using a semi-analytical approach composed of generalized differential quadrature method (GDQM) and series solution adopted to solve the equations of motion. Detailed parametric studies are carried out to investigate the mechanical behavior of these multi-layered structures depending on the damage features, through-the-thickness distribution and boundary conditions. Also, the effects of carbon nanotubes (CNTs) waviness, CNT aspect ratio, Winkler foundation modulus, shear elastic foundation modulus and geometrical conditions on the vibrational behavior of the sandwich structure are studied. © 2025 Techno-Press, Ltd.

关键词： Aspect ratio

来源：评论

学校读者我要写书评

暂无评论

OPTIMIZING DESIGN AND CONTROL OF RUNNING ROBOTS ABSTRACTED AS A TORQUE DRIVEN SPRING LOADED INVERTED PENDULUM

OPTIMIZING DESIGN AND CONTROL OF RUNNING ROBOTS ABSTRACTED A...

引用

ASME 2024 International Design engineering Technical Conferences and computers and Information in engineering Conference, IDETC-CIE 2024

作者： Truax, Reed Liu, Feng Chowdhury, Souma Pierre, Ryan St. Department of Mechanical and Aerospace Engineering University at Buffalo BuffaloNY14228 United States Department of Computer Science and Engineering University at Buffalo BuffaloNY14228 United States

ISBN: (纸本)9780791888377

Legged locomotion shows promise for running in complex, unstructured environments. Designing such legged robots requires considering heterogeneous, multi-domain constraints and variables, from mechanical hardware and geometry choices to controller profiles. However, very few formal or systematic (as opposed to ad hoc) design formulations and frameworks exist to identify feasible and robust running platforms, especially at the small (sub 500 g) scale. This critical gap in running legged robot design is addressed here by abstracting the motion of legged robots through a torque driven spring-loaded inverted pendulum (TD-SLIP) model, and deriving constraints that result in stable cyclic forward locomotion in the presence of system noise. Synthetic noise is added to the initial state in candidate design evaluation to simulate accumulated errors in an open-loop control. The design space was defined in terms of morphological parameters, such as the leg properties and system mass, actuator selection, and an open loop voltage profile. These attributes were optimized with a well-known particle swarm optimization solver that can handle mixed-discrete variables. Two separate case studies minimized the difference in touchdown angle from stride to stride and the actuation energy, respectively. Both cases resulted in legged robot designs with relatively repeatable and stable dynamics, while presenting distinct geometry and controller profile choices. Copyright © 2024 by ASME.

关键词： Inverted pendulum

来源：评论

学校读者我要写书评

暂无评论

Fault detection based on multiple features clustering and unsupervised scoring for lithium-ion battery packs 10

Fault detection based on multiple features clustering and un...

引用

10th IEEE International Power Electronics and Motion Control Conference, IPEMC 2024 ECCE Asia

作者： Nie, Wenhao Deng, Zhongwei He, Yuxin Jiang, Chunlin University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu611731 China Chongqing University College of Mechanical and Vehicle Engineering Chongqing400044 China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China

ISBN: (纸本)9798350351330

Battery fault diagnosis is critical to ensure the safe and reliable operation of electric vehicles and energy storage systems. Entropy value can represent the degree of chaos and disorder of the system, the improved entropy value algorithm has been applied by many researchers to the field of fault diagnosis of lithium-ion batteries. However, the use of Shannon entropy for battery cell fault detection has some limitations and drawbacks, such as sensitivity to noise, limited feature representation and lack of adaptability. To address these limitations, a novel approach that incorporates Shannon entropy with other relevant features through clustering algorithm is proposed in this study. By applying a sliding time window to iteratively score the clustering results, this study transforms the traditional classification problem into an unsupervised scoring problem. The results demonstrate that the clustering algorithm based on multiple features outperforms the standalone Shannon entropy algorithm in terms of accuracy and time in diagnosing individual cell faults. © 2024 IEEE.

关键词： Failure analysis

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：