检索结果-内蒙古大学图书馆

IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Venkatasubramanian Kalpathy Venkiteswaran Jurrien Bos Dimple Dannana Ali Sadeghi Department of Biomechanical Engineering University of Twente En-schede The Netherlands Faculty of Engineering Technology Surgical Robotics Laboratory University of Twente Faculty of Engineering Technology Soft Robotics Lab University of Twente

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Growing robots are a subset of continuum robots with the main distinctive feature the fact that material is added from the tip instead of from the base. Currently, growing robots rely primarily on material deposition through filament printing or eversion using pneumatic circuits which may be too bulky or unsafe for applications inside the human body. In this paper, a proof of concept for a novel growing robot mechanism is presented. A variable stiffness tube (VST) based on low melting point alloy (LMPA) is developed to act as the growing element and the direction of robot growth can be guided using magnetic fields. A prototype is built to test the concept and is evaluated through experiments. Effects of Joule heating on the temperature within the VST are studied, as well as the stiffness variation of the VST when the LMPA transitions from solid to metal phase. The magnetic interaction is modeled and a system of external system of magnets is developed to achieve wireless guidance of the robot head. The growing mechanism of the robot via magnetic actuation is demonstrated through benchtop experiments where it is guided through straight and curved paths.

关键词： Wireless communication Printing Metals Prototypes Medical services Pneumatic systems Solids Magnetic heads Magnets Robots

来源：评论

学校读者我要写书评

暂无评论

Experimental test rig for oil film thickness study 11

Experimental test rig for oil film thickness study

引用

Advanced Topics in Optoelectronics, Microelectronics, and Nanotechnologies XI 2022

作者： Cristian, Românu Ionuţ Ioan-Cozmin, Manolache-Rusu Ilie, Muscă Gavril, Ciornei Department of Mechanics and Technologies Mechanical Engineering Automotive and Robotics Faculty "Ștefan cel Mare" University of Suceava 13 University Street 720229 Romania

ISBN: (纸本)9781510660939

The paper presents some aspects regarding the conception and construction of an experimental test rig used for studies concerning friction phenomenon of threads immersed in oil, maintained in a state of motion with constant velocity. The structure of the experimental test rig, testing methodology, experimental results and the applicability of the experimental set-up were detailed. To validate the experimental equipment and method, the obtained values were correlated with those obtained analytically. A good correlation was found, which attests the applicability of the test rig and method. © 2023 SPIE.

关键词： Film thickness

来源：评论

学校读者我要写书评

暂无评论

Neuro-Evolution of Frequency Controllers in the Power-Electricity System Island

引用

IFAC-PapersOnLine 2024年第9期58卷 49-54页

作者： Filip Zúbek Martin Ernek Ivan Kenický Ivan Sekaj Institute of Robotics and Cybernetics Faculty of Electrical Engineering and Information Technology The Slovak University of Technology in Bratislava Slovakia

We present a methodology for designing frequency controllers in a power-electricity isolated island that is based on artificial neural networks (ANN). A less commonly employed machine learning approach based on neuro-evolution (NE) is proposed for learning the ANN, demonstrating its efficiency in dynamic system control. The power-electricity island consists of four water turbogenerators, two steam-gas cycle units, one nuclear unit, a distribution network, and consumers. The proposed architecture of neural controllers and the NE-based learning method, using a genetic algorithm, is described. The results are compared with commonly used PI controllers using different criteria functions. The comparison shows that the proposed approach achieves significantly better control performance compared to the conventional approach using PI controllers.

关键词： Artificial neural network continuous-time control frequency control genetic algorithm isolated island neuro-controller neuro-evolution PI controllers power-electricity system

来源：评论

学校读者我要写书评

暂无评论

MODELING OF THE AUTOMATIC TESTING PROCESS OF ELECTRONIC CONTROL UNITS IN THE AUTOMOTIVE INDUSTRY

International Journal of Mechatronics and Applied Mechanics

引用

International Journal of Mechatronics and Applied Mechanics 2022年第12期2022卷 148-155页

作者： Bogorin-Predescu, Adrian Țîțu, Aurel Mihail Niță, Nicoleta–Mădălina Domnariu, Victor-Leonard University Politehnica of Bucharest Faculty of Industrial Engineering and Robotics Splaiul Independenţei nr. 313 6th District Bucharest Romania "Lucian Blaga" University of Sibiu Faculty of Engineering Industrial Engineering and Management Department 10 Victoriei Street Sibiu550024 Romania

– The scientific paper presents an original contribution regarding the modelling of the automatic EOL (End of Line) testing process of the Electronic Control Units (ECU) in the production flow in the automotive industry, by implementing the parallel testing algorithm to reduce the processing time at the related process station. This modelling operation for optimization must be implemented without affecting the quality of the automated functional testing process and is necessary for the application of the Kanban method in the automotive production flow. The process modelling begins with the analysis of the traditional execution time for each ECU input or output pin and continues with the development of a parallel test algorithm in which the test time for a single ECU is substantially decreased. By reducing the processing time of a station in the production flow, in this case at the EOL test station, a significant improvement in the capacity of the assembly line is achieved, which translates into cost savings at the resource level. The last part of the paper highlights the results obtained from the modelling of the process in order to optimize it and presents our conclusions developed in this case study. © 2022, Cefin Publishing House. All rights reserved.

关键词： Automotive industry

来源：评论

学校读者我要写书评

暂无评论

Comparison of Deep Reinforcement Methods and Neuroevolution for Bipedal Walker Learning

Comparison of Deep Reinforcement Methods and Neuroevolution ...

引用

Cybernetics & Informatics (K&I)

作者： Oliver Halaš Filip Zúbek Ivan Sekaj Faculty of Electrical Engineering and Information Technology Institute of Robotics and Cybernetics Bratislava Slovakia

ISBN: (数字)9798331541811

ISBN: (纸本)9798331541828

This paper presents an in-depth comparison of deep reinforcement learning (DRL) methods and neuroevolutionary techniques for continuous control in robotic movement systems, using the Bipedal Walker environment as a testbed. We evaluate three prominent DRL algorithms: Advantage Actor-Critic (A2C), Twin Delayed Deep Deterministic Policy Gradient (TD3), and Proximal Policy Optimization (PPO), and NeuroEvolution of Augmenting Topologies (NEAT). The study benchmarks each algorithm under identical computational constraints, focusing on learning progress over a fixed training period and assessing performance on a set of unseen terrain configurations. Results reveal a trade-off between DRL methods’ robustness and NEAT’s structural flexibility, highlighting DRL’s edge in adaptability and reward maximization. This work contributes to a better understanding of each approach’s suitability for complex continuous control problems, offering insights that can guide method selection in robotics and control systems applications.

关键词： Training Legged locomotion Scalability Focusing Robustness Topology Time factors Robots Optimization Faces

来源：评论

学校读者我要写书评

暂无评论

The Application of Machine Learning in Sentiment Analysis of Social Media and E-commerce: A Review of Methods and Techniques

The Application of Machine Learning in Sentiment Analysis of...

引用

International Carpathian Control Conference (ICCC)

作者： Agata Nawrocka Marcin Nawrocki Andrzej Kot Marcin Słychan Department of Process Control Faculty of Mechanical Engineering and Robotics AGH University of Science and Technology Krakow Poland Departament of Mechinery Engineering and Transport Faculty of Mechanical Engineering and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (数字)9798331501273

ISBN: (纸本)9798331501280

The paper describes the application of machine learning for sentiment analysis in the context of social media and e-commerce. It presents a literature review and an overview of available sentiment analysis methods, such as sentiment classification, the use of lexicons, machine learning methods (e.g., SVM, decision trees), and word embedding techniques. Both traditional approaches and modern solutions based on deep learning are thoroughly *** the practical part of the thesis, sentiment analysis was conducted on data collected from social media platforms such as Twitter and Reddit. Various machine learning algorithms were utilized, and the model's behavior was analyzed based on different activation functions.

关键词： Deep learning Support vector machines Sentiment analysis Analytical models Recurrent neural networks Social networking (online) Text categorization Electronic commerce Systematic literature review Sorting

来源：评论

学校读者我要写书评

暂无评论

Retinal disorder diagnosis based on hybrid deep learning models

引用

Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

来源：评论

学校读者我要写书评

暂无评论

Smart Cities Using Artificial Intelligence (AI) and Blockchain in the Internet of Things (IoT) Era 1st

Smart Cities Using Artificial Intelligence (AI) and Blockcha...

引用

1st International Conference on Smart Environment and Green Technologies, ICSEGT 2024

作者： Al-Turjman, Fadi Salama, Ramiz Sadikoglu, Gunay Artificial Intelligence Engineering Dept. AI and Robotics Institute Near East University Nicosia Mersin Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Kyrenia Mersin Turkey Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Mersin Turkey Near East University Nicosia Mersin Turkey

ISBN: (纸本)9783031815638

Around the world, modern cities are changing dramatically in order to install smart infrastructure, provide smart services to residents, improve accessibility for vulnerable populations, and provide a clean, sustainable, and secure environment. Numerous initiatives that address significant issues with urban transportation, health, water management, energy conservation, housing, safety, and accessibility are centered on the adoption of new technologies. To overcome these obstacles and enhance the resourcefulness, sustainability, and security of cities, it is imperative to embrace new and creative technologies, especially in light of the advancements in communication and sensor technology over the past few decades. This article gives a summary of the metropolitan issues that smart urban communities are now experiencing. It investigates how edge AI and blockchain, two recent technological innovations, might revolutionize urban intelligence. It also examines significant research initiatives in these two crucial areas of today’s smart cities, along with a variety of applications for edge AI and blockchain in smart energy and transportation. It discusses numerous uses of blockchain in the context of secure vehicle-to-vehicle trade and communication, along with a range of methods for processing speed detection, counting, and identification to lessen traffic congestion. The purpose of this review article is to set the stage for next research on applying blockchain technology and edge artificial intelligence to smarter city applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Sustainable city

来源：评论

学校读者我要写书评

暂无评论

Estimating the Capacitance of a Dielectric Elastomer Generator Using Selected Measurement Methods

Estimating the Capacitance of a Dielectric Elastomer Generat...

引用

International Carpathian Control Conference (ICCC)

作者： Wojciech Sikora Faculty of Mechanical Engineering and Robotics AGH University of Krakow Krakow Poland

ISBN: (数字)9798350350708

ISBN: (纸本)9798350350715

Generators based on dielectric elastomers have the potential to convert mechanical energy into electrical energy. The amount of energy that can be converted depends on the range of change in capacitance due to mechanical deformation. To estimate the amount of energy that can be generated, it is necessary to determine the capacitance of the generator for a given range of deformation and operating voltage levels. This estimate is close to the theoretical value because it neglects losses and charge leakage that typically occur in electrical circuits during energy harvesting. This information is useful in the design and prototyping process of the generator as it allows for the separation of the mechanical (construction) and electrical (harvesting circuit) components of the generator. It is possible to avoid direct measurements of generator performance using a harvesting circuit that operates at high voltages, up to 1kV or more. This paper presents the results of capacitance measurements of uniaxial generator subjected to cyclic stretching using selected methods.

关键词： Deformation Circuits High-voltage techniques Capacitance Dielectric elastomers Generators Dielectric measurement

来源：评论

学校读者我要写书评

暂无评论

SIS: Seam-Informed Strategy for T-Shirt Unfolding

引用

IEEE robotics and Automation Letters 2025年第7期10卷 7342-7349页

作者： Huang, Xuzhao Seino, Akira Tokuda, Fuyuki Kobayashi, Akinari Chen, Dayuan Hirata, Yasuhisa Tien, Norman C. Kosuge, Kazuhiro The University of Hong Kong JC STEM Lab of Robotics for Soft Materials Department of Electrical and Electronic Engineering Faculty of Engineering Hong Kong Centre for Transformative Garment Production Hong Kong Tohoku University Department of Robotics Graduate School of Engineering Japan The University of Hong Kong Department of Electrical and Electronic Engineering Faculty of Engineering Hong Kong

Seams are information-rich components of garments. The presence of different types of seams and their combinations helps to select grasping points for garment handling. In this paper, we propose a new Seam-Informed Strategy (SIS) for finding actions for handling a garment, such as grasping and unfolding a T-shirt. Candidates for a pair of grasping points for a dual-arm manipulator system are extracted using the proposed Seam Feature Extraction Method (SFEM). A pair of grasping points for the robot system is selected by the proposed Decision Matrix Iteration Method (DMIM). The decision matrix is first computed by multiple human demonstrations and updated by the robot execution results to improve the grasping and unfolding performance of the robot. Note that the proposed scheme is trained on real data without relying on simulation. Experimental results demonstrate the effectiveness and generalization ability of the proposed strategy. © 2016 IEEE.

关键词： Intelligent robots

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：