检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Conde, Pedro Lopes, Rui L. Premebida, Cristiano Institute os Systems and Robotics Department Of Electrical and Computer Engineering University of Coimbra Portugal Critical Software S.A. Portugal

The proliferation of Deep Neural Networks has resulted in machine learning systems becoming increasingly more present in various real-world applications. Consequently, there is a growing demand for highly reliable models in many domains, making the problem of uncertainty calibration pivotal when considering the future of deep learning. This is especially true when considering object detection systems, that are commonly present in safety-critical applications such as autonomous driving, robotics and medical diagnosis. For this reason, this work presents a novel theoretical and practical framework to evaluate object detection systems in the context of uncertainty calibration. This encompasses a new comprehensive formulation of this concept through distinct formal definitions, and also three novel evaluation metrics derived from such theoretical foundation. The robustness of the proposed uncertainty calibration metrics is shown through a series of representative experiments. Copyright © 2023, The Authors. All rights reserved.

关键词： Calibration

来源：评论

学校读者我要写书评

暂无评论

Logarithmically Quantized Distributed Optimization over Dynamic Multi-Agent Networks

arXiv

引用

arXiv 2024年

作者： Doostmohammadian, Mohammadreza Pequito, Sérgio Mechatronics Department Faculty of Mechanical Engineering Semnan University Semnan Iran Department of Electrical and Computer Engineering Institute for Systems and Robotics Instituto Superior Técnico University of Lisbon Portugal

Distributed optimization finds many applications in machine learning, signal processing, and control systems. In these real-world applications, the constraints of communication networks, particularly limited bandwidth, necessitate implementing quantization techniques. In this paper, we propose distributed optimization dynamics over multi-agent networks subject to logarithmically quantized data transmission. Under this condition, data exchange benefits from representing smaller values with more bits and larger values with fewer bits. As compared to uniform quantization, this allows for higher precision in representing near-optimal values and more accuracy of the distributed optimization algorithm. The proposed optimization dynamics comprise a primary state variable converging to the optimizer and an auxiliary variable tracking the objective function's gradient. Our setting accommodates dynamic network topologies, resulting in a hybrid system requiring convergence analysis using matrix perturbation theory and eigenspectrumanalysis. © 2024, CC BY.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Designing assessment processes using the student involvement method by WTCAi system 22

Designing assessment processes using the student involvement...

引用

2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics, SAMI 2024

作者： Karl, Eva Nagy, Eniko Molnar, Gyorgy Varkerti Primary School Varpalota Hungary Gyr Hungary Institute of Cyberphysical Systems Obuda University Antal Bejczy Center for Intelligent Robotics John von Neumann Faculty Budapest Hungary Obuda University Kando Kalman Faculty of Electrical Engineering Budapest Hungary Szechenyi University Janos Csere Apaczai Faculty Gyr Hungary

ISBN: (纸本)9798350317206

The quality assurance of education and training is of paramount importance, and the monitoring, assessment and evaluation process is indispensable for this purpose. A key determinant of the effectiveness of education is assessment, which serves not only to measure performance but also to support the learning process. The process of assessment and evaluation must take into account the diverse needs and abilities of students. Differentiated assessment supports individual learning paths and personal development. Assessment must be objective and valid, but it can achieve its deeper developmental purpose when personalized. Our research aims to enhance pedagogical assessment efficiency by developing a machine learning-supported assessment system. The research focuses on developing STEM skills and analyzes children's questions to understand their interests and needs better. During the research, we observe the characteristics of questions posed by children and develop a machine learning algorithm that helps provide suggestions to educators for creating assessment questions. Based on the data, we identify children's areas of interest and the difficulty level of questions. According to the research results, children's questions can significantly differ from question sets prepared by educators, suggesting that children's diverse perspectives and interests should be given even greater consideration in teaching. The research also raises further directions for development. It aims to use machine learning to understand better the diverse ways of thinking and differences in expression among children, thereby making education and assessment more effective. This can contribute significantly to the efficiency and effectiveness of the teaching-learning process. © 2024 IEEE.

关键词： Quality assurance

来源：评论

学校读者我要写书评

暂无评论

TReCiM: Lower Power and Temperature-Resilient Multibit 2FeFET-1T Compute-in-Memory Design 24

TReCiM: Lower Power and Temperature-Resilient Multibit 2FeFE...

引用

43rd International Conference on Computer-Aided Design, ICCAD 2024

作者： Zhou, Yifei Kämpfe, Thomas Ni, Kai Amrouch, Hussam Zhuo, Cheng Yin, Xunzhao Zhejiang University Hangzhou China Fraunhofer IPMS Dresden Germany Department of Electrical Engineering University of Notre Dame Notre Dame United States Technical University of Munich TUM School of Computation Information and Technology Munich Institute of Robotics and Machine Intelligence Munich Germany Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province China

ISBN: (纸本)9798400710773

Compute-in-memory (CiM) emerges as a promising solution to solve hardware challenges in artificial intelligence (AI) and the Internet of Things (IoT), particularly addressing the"memory wall" issue. By utilizing nonvolatile memory (NVM) devices in a crossbar structure, CiM efficiently accelerates multiply-accumulate (MAC) computations, the crucial operations in neural networks and other AI models. Among various NVM devices, Ferroelectric FET (FeFET) is particularly appealing for ultra-low-power CiM arrays due to its CMOS compatibility, voltage-driven write/read mechanisms and high ION/IOFF ratio. Moreover, subthreshold-operated FeFETs, which operate at scaling voltages in the subthreshold region, can further minimize the power consumption of CiM array. However, subthreshold-FeFETs are susceptible to temperature drift, resulting in computation accuracy degradation. Existing solutions exhibit weak temperature resilience at larger array size and only support 1-bit. In this paper, we propose TReCiM, an ultra-low-power temperature-resilient multibit 2FeFET-1T CiM design that reliably performs MAC operations in the subthreshold-FeFET region with temperature ranging from 0°C to 85°C at scale. We benchmark our design using NeuroSim framework in the context of VGG-8 neural network architecture running the CIFAR-10 dataset. Benchmarking results suggest that when considering temperature drift impact, our proposed TReCiM array achieves 91.31% accuracy, with 1.86% accuracy improvement compared to existing 1-bit 2T-1FeFET CiM array. Furthermore, our proposed design achieves 48.03 TOPS/W energy efficiency at system level, comparable to existing designs with smaller technology feature sizes. © 2024 Copyright is held by the owner/author(s).

关键词： MISFET devices

来源：评论

学校读者我要写书评

暂无评论

Development and Optimization of a WebGL-Based Mechanical Model Simulation Platform 4th

Development and Optimization of a WebGL-Based Mechanical Mod...

引用

4th International Conference on Mechanical Design and Simulation, MDS 2024

作者： Wang, Xintong Tian, Hao Fang, Jingzhe Zhang, Hualiang Zhang, Tao Software College Shenyang University of Technology Liaoning Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9789819778867

The need for mechanical model simulation platforms is growing as a result of the ongoing advancements in digital technology and the mechanical manufacturing sector. The application scope and efficacy of simulation platforms are severely limited by the issue of sluggish rendering performance, which frequently arises when obtaining high-quality rendering. When drawing high demand mechanical models, a lot of processing power is frequently needed, which makes real-time rendering speed unsatisfactory for practical purposes. In order to achieve real-time rendering and simulation of 3D robots, this experiment built and implemented a WebGL-based 3D simulation platform. Additionally, the simulation platform can be optimized by increasing frame rate and rendering speed without sacrificing rendering effect by building a mixed bounding box. © The Author(s) 2025.

关键词： Digital elevation model

来源：评论

学校读者我要写书评

暂无评论

A Safe Control Architecture Based on Robust Model Predictive Control for Autonomous Driving

A Safe Control Architecture Based on Robust Model Predictive...

引用

2022 American Control Conference, ACC 2022

作者： Nezami, Maryam Nguyen, Ngoc Thinh Mannel, Georg Abbas, Hossam Seddik Schildbach, Georg University of Lübeck Institute for Electrical Engineering in Medicine Lübeck Germany University of Lübeck Institute for Robotics and Cognitive Systems Lübeck Germany Fraunhofer Imte Fraunhofer Research Institution for Individualized and CellBased Medical Engineering Lübeck Germany

ISBN: (数字)9781665451963

ISBN: (纸本)9781665451963

This paper proposes a Robust Safe Control Architecture (RSCA) for safe-decision making. The system to be controlled is a vehicle in the presence of bounded disturbances. The RSCA consists of two parts: a Supervisor MPC and a Controller MPC. Both the Supervisor and the Controller are tube MPCs (TMPCs). The Supervisor MPC provides a safety certificate for an operating controller and a backup control input in every step. After an unsafe action by the operating controller is predicted, the Controller MPC takes over the system. In this paper, a method for the computation of a terminal set is proposed, which is robust against changes in the road curvature and forces the vehicle to reach a safe reference. Moreover, two important proofs are provided in this paper. First, it is shown that the backup control input is safe to be applied to the system to lead the vehicle to a safe state. Next, the recursive feasibility of the RSCA is proven. By simulating some obstacle avoidance scenarios, the effectiveness of the proposed RSCA is confirmed. © 2022 American Automatic Control Council.

关键词： Controllers

来源：评论

学校读者我要写书评

暂无评论

Robot Embodied Dynamic Tactile Perception of Liquid in Containers 23

Robot Embodied Dynamic Tactile Perception of Liquid in Conta...

引用

23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024

作者： Xu, Yingtian Ma, Yichen Lin, Waner Sun, Zhenglong Zhang, Tianwei Wang, Ziya The Chinese Univ of Hong Kong School of Science and Engineering Shenzhen518172 China Shenzhen University Key Laboratory of Optoelectronic Devices and Systems Ministry of Education School of Physics and Optoelectronic Engineering Shenzhen518060 China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Department of Micro-Nano Electronics Shanghai200240 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518129 China

ISBN: (纸本)9798350373578

Humans perceive objects and environments actively and dynamically using tactile sensing facilitated by the skin. However, due to the gap in sensing capabilities between electronic skin and human skin, it remains a challenge for robots to achieve intricate tactile perception. For example, the task of liquid properties estimation within containers, demands sensing and comprehension of complex dynamic tactile signals during contact. This paper introduces a novel tactile fingertip inspired by human skin enabling both static tactile sensing facilitated by a layer of porous piezoresistive elastomer and dynamic tactile sensing enabled by condenser microphones. A data-driven methodology is employed to analyze liquids through multimodal signals devoid of physical modelling. The proposed robotic system engages in shaking various bottles filled with different volumes of water, allowing the tactile fingertip to detect changes in grasping force caused by shaking and small vibrations caused by the collision of the container with liquid. Five machine learning models trained on these tactile signals are analyzed and compared. Experimental results demonstrate the proficiency of the tactile system in distinguishing liquid fill percentages across bottles of different shapes and capacities with a remarkable accuracy of 98%. This paper holds promise for advancing the embodied intelligence of robots, enhancing their ability to perceive mixed tactile signals dynamically, thereby facilitating tasks such as liquid estimation and other intricate tactile operations in environments like kitchens and hospitals. © 2024 IEEE.

关键词： Bottles

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

Rapid Maintenance based improved design for omnidirectional controlled wheels for VirtuSphere system

Rapid Maintenance based improved design for omnidirectional ...

引用

International Symposium for Design and Technology of Electronics Packages (SIITME)

作者： Lidia Cristina Bazavan Horatiu Roibu Daniela Coman Stefan Irinel Cismaru Anca Petrisor Nicu George Bizdoaca Mechatronics and Robotics Department Faculty of Automation Computers and Electronics University of Craiova Craiova Romania Engineering and Management of the Technological Systems Department Faculty of Mechanics University of Craiova Craiova Romania Electrical Energy and Aerospace Engineering Department Faculty of Electrical Engineering University of Craiova Craiova Romania

Designing for rapid maintenance requires an approach whereby the replacement of rapidly wearing sub-assemblies can be easily replaced while ensuring that the degree of wear can be tracked in real-time if possible. The redesign of the movement system of the Virtusfera platform by the authors previously led to an omnidirectional platform with increased integration facilities in virtual environments. The article presents two solutions for redesigning some subsystems that make up the new experimentally validated solution, presenting at the same time the study based on which the subsystems with the lowest reliability were identified and a proposal for a real-time tracking solution for those subsystems. Numerical simulations of the two solutions are presented, and conclusions and directions are formulated regarding the practical implementation of these subsystems based on the concept of design based on rapid maintenance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An in-Contact Robotic System for the Process of Desoldering PCB Components

arXiv

引用

arXiv 2024年

作者： Santos, Silvia Marques, Lino Neto, Pedro Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra3030-290 Portugal University of Coimbra CEMMPRE ARISE Department of Mechanical Engineering Coimbra3030-788 Portugal

The disposal and recycling of electronic waste (e-waste) poses a significant global challenge. The disassembly of components is a crucial step in achieving an efficient recycling process, avoiding destructive methods. While manual disassembly remains the norm due to the diversity and complexity of components, there is a growing interest in automating the process to enhance efficiency and reduce labor costs. This study endeavors to automate the desoldering process and the extraction of components from printed circuit boards (PCBs) by implementing a robotic solution. The proposed strategy encompasses multiple phases, one of which involves the precise contact of the developed robotic tool with the components on the PCB. The tool was designed to exert a controlled force on the PCB component, thereby efficiently desoldering it from the board. Results demonstrate the feasibility of achieving a high success rate in removing PCB components, including the ones from mobile phones. The desoldering success rate observed is approximately 100% for the larger components. © 2024, CC BY.

关键词： Printed circuit boards

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：