检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Mellet, Julien Berra, Andrea Marcellini, Salvatore Soto, Miguel Ángel Trujillo Heredia, Guillermo Ruggiero, Fabio Lippiello, Vincenzo PRISMA Lab Department of Electrical Engineering and Information Technology University of Naples Federico II Naples Italy CATEC Advanced Center for Aerospace Technologies Seville Spain GRVC Robotics Vision and Control Group School of Engineering University of Seville Seville Spain

Fully actuated aerial robot proved their superiority for Aerial Physical Interaction (APhI) over the past years. This work proposes a minimal setup for aerial telemanipulation, enhancing accessibility of these technologies. The design and the control of a 6-Degrees of Freedom (DoF) joystick with 4-DoF haptic feedback is detailed. It is the first haptic device with standard Remote controller (RC) form factor for APhI. By miniaturizing haptic device, it enhances RC with the sense of touch, increasing physical awareness. The goal is to give operators an extra sense, other than vision and sound, to help to perform safe APhI. To the best of the authors knowledge, this is the first teleoperation system able to decouple each single axis input command. On the omnidirectional quadrotor, by reducing the number of components with a new design, we aim a simplified maintenance, and improved force and thrust to weight ratio. Open-sourced physic based simulation and successful preliminary flight tests highlighted the tool as promising for future APhI applications. © 2024, CC BY-NC-ND.

关键词： Omnidirectional antennas

来源：评论

学校读者我要写书评

暂无评论

Design and Application of a One-Stop Mobile Application Sharing Platform for Steel Enterprises 42

Design and Application of a One-Stop Mobile Application Shar...

引用

42nd Chinese control Conference, CCC 2023

作者： Chen, Xinzhe Chen, Luefeng Hu, Jie Yang, Qingfeng Wu, Min Pedrycz, Witold School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada

ISBN: (纸本)9789887581543

As China's steel production accounts for an increasing share of the world's output, the intelligent transformation of the steel industry is becoming increasingly urgent. To address issues such as low levels of mobile informationization in steel enterprises and the lack of an industry-specific mobile application platform, it is of great significance to establish a shared mobile application platform for the steel industry. In this paper, the requirements of the platform were analyzed, and the platform's functions were designed. The software design of the platform was then carried out, and the entire mobile application sharing platform was developed, effectively improving the production management efficiency of steel enterprises. The results indicate that the platform can effectively meet the needs of steel enterprises and has significant engineering significance. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Informatization

来源：评论

学校读者我要写书评

暂无评论

A Modified Dempster Shafer Approach to Classification in Surgical Skill Assessment

A Modified Dempster Shafer Approach to Classification in Sur...

引用

Iranian Conference on electrical engineering (ICEE)

作者： Arash Iranfar Mohammad Soleymannejad Behzad Moshiri Hamid D. Taghirad School of Electrical and Computer Engineering University College of Engineering University of Tehran Tehran Iran Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran

Artificial intelligence systems are usually implemented either using machine learning or expert systems. Machine learning methods are usually more accurate and applicable to a broader range of applications. Expert systems, on the other hand, require much less data for training and generate more comprehensible results. These characteristics are typically desired in the fields of surgery and medicine because there isn't much data available. In order to give a machine's decisions a deeper level of semantics, it is also advantageous to incorporate a doctor's expertise into it. Furthermore, it is safer to understand the reasoning behind a machine's choices. In this paper, a Dempster-Shafer Theory (DST) based expert system is suggested for the task of surgical training skill assessment. An interval-based probabilistic feature analysis was applied to the data to assign values to the mass functions. Zhang's rule of combination was applied to handle the conflicting evidence in the prediction phase. The performance of the proposed method was compared to another DST classifier, SVM, and XGBoost. Our method outperforms SVM and other DST classifiers, but it is not as precise as XGBoost. By reducing the size of the dataset, the added benefit of using an expert system as opposed to a machine learning method was explored further. The performance of the suggested method is not adversely affected by the size of the dataset, whereas the XGBoost classifier is.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Physics-guided Inverse Design for SiPh Mode Manipulation

Physics-guided Inverse Design for SiPh Mode Manipulation

引用

Photonics in Switching and Computing, PSC 2021

作者： Masnad, Mahadi Grinberg, Yuri Xu, Dan-Xia Liboiron-Ladouceur, Odile Electrical and Computer Engineering Department McGill University Montral Canada Digital Technologies Research Center Ottawa Canada Advanced Electronics and Photonics Research Center National Research Council Ottawa Canada

Physics-guided formulation leads to more efficient inverse designs at lower computation costs. We validate this design approach with the performance analysis of mode converters and mode division multiplexers having ef...

ISBN: (纸本)9781557528209

关键词：

来源：评论

学校读者我要写书评

暂无评论

Recognition of driver's distraction based on facial thermal videos by deep learning

Recognition of driver's distraction based on facial thermal ...

引用

Asilomar Conference on Signals, Systems & computers

作者： Poorya Aghaomidi Zahra Bahmani Amin Mohammdian Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Research Center for development of Advanced Technologies Tehran Iran

Distraction detection is an effective method for providing drivers' safety. Facial thermal video was used as a non-contact measurement for distraction detection. In the first step, a novel method that employed self-supervised learning was used for face tracking of thermal videos. Two auxiliary tasks including gender and rotation detection were designed. A deep neural network was trained to simultaneously solve these two problems in a multi-task manner. Then, the trained model was fine-tuned for the purpose of face tracking with a few labeled frames. In the final stage, distraction was detected by a CNN-RNN network. The pre-trained InceptionV3 network was used to extract the features of the frames, followed by gated recurrent unit layers to aid in the classification. Our model achieved 100% and 98.46% accuracy for gender detection and rotation detection respectively. The proposed face tracker outperformed the classical image processing methods for thermal face tracking. Moreover, our system had an accuracy of 91.68% in identifying the presence or absence of a distraction factor. The proposed non-contact distraction detection system is the first method that extracted features by deep learning model from the whole area of the face. This model will be more valuable in practical applications.

关键词： Deep learning Thermal factors Face recognition Neural networks Transfer learning Self-supervised learning Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Editorial:Special Topic on Federated Learning for IoT and Edge Computing

引用

ZTE Communications 2022年第3期20卷 1-2页

作者： PAN Yi CUI Laizhong CAI Zhipeng LI Wei Faculty of Computer Science and Control Engineering at Shenzhen Institute of Advanced Technology Chinese Academy of SciencesChina the Academy of the United Nations Sciences and Technology Organization Ukrainian Academy of Engineering Sciences American Institute for Medical and Biological Engineering Institute of Engineering Technology the College of Computer Science and Software Engineering at Shenzhen University China Department of Computer Science and the College of Business at Georgia State University USA the Center for Distributed and High Performance Computing School of Computer ScienceThe University of Sydney the Australia-China Joint Research Center on Energy Informatics and Demand Response Technologies

Recent years have witnessed the proliferation of Internet of Things(IoT),in which billions of devices are connected to the Internet,generating an overwhelming amount of *** is challenging and infeasible to transfer an... 详细信息

关键词： cloud generating data.

来源：评论

学校读者我要写书评

暂无评论

Hidden multi-dimensional modulation side channels in quantum protocols

arXiv

引用

arXiv 2024年

作者： Gnanapandithan, Amita Qian, Li Lo, Hoi-Kwong Department of Electrical and Computer Engineering University of Toronto Toronto Canada Center for Quantum Information and Quantum Control University of Toronto Toronto Canada Quantum Bridge Technologies Inc. 108 College St. Toronto Canada

Quantum protocols including quantum key distribution and blind quantum computing often require the preparation of quantum states of known dimensions. Here, we show that, rather surprisingly, hidden multi-dimensional modulation is often performed by practical devices. This violates the dimensional assumption in quantum protocols, thus creating side channels and security loopholes. Our work has important impacts on the security of quantum cryptographic protocols. © 2024, CC BY.

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Anomaly Detection Based on Principle of Justifiable Granularity and Probability Density Estimation

Anomaly Detection Based on Principle of Justifiable Granular...

引用

2023 China Automation Congress, CAC 2023

作者： Du, Sheng Ma, Xian Li, Xiang Wu, Min Cao, Weihua Pedrycz, Witold School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Istanbul Sariyer Turkey

ISBN: (纸本)9798350303759

Anomaly detection is essential to ensure the safety of industrial processes. This paper presents an anomaly detection approach based on the probability density estimation and principle of justifiable granularity. First, time series data are transformed into a two-dimensional information granule by the principle of justifiable granularity. Then, the test statistic is constructed, and the probability density and cumulative distribution functions of the test statistic are calculated. Next, the confidence level determines the test threshold. Finally, the time series data of a key parameter in the sintering process is used as a case study. The experimental result demonstrates that the proposed approach can detect abnormal time series data effectively, providing an accurate and effective solution for detecting time series anomalies in industrial processes. © 2023 IEEE.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

CNL-ResUnet: A novel deep learning architecture for stroke image segmentation

CNL-ResUnet: A novel deep learning architecture for stroke i...

引用

International Conference on advanced technologies for Signal and Image Processing (ATSIP)

作者： Nesrine Jazzar Besma Mabrouk Ali Douik Networked Objects Control and Communication Systems National Engineering School of Sousse University of Sousse Tunisia National Engineering School of Sfax University of Sfax Tunisia Department of Electrical and Computer Engineering Advanced Technologies for Medicine and Signals ATMS National Engineers School Sfax University Tunisia Networked Objects Control and Communication Systems National Engineering School Sousse Tunisia

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

Segmentation of stroke lesions holds significant importance in enabling timely diagnosis and subsequent treatment by medical professionals. Automating this process presents technical challenges given the diverse appearance and evolving nature of lesions, discrepancies among medical experts, limited dataset availability, and the necessity for multiple MRI modalities for comprehensive imaging. This research presents an innovative method called CNL-ResUNet, specifically designed for 2D stroke image segmentation. CNL-ResUNet ingeniously incorporates residual blocks into its architecture, capitalizing on their innate capacity to facilitate seamless information flow across layers, thereby empowering the network to efficiently distill complex patterns from sparse datasets. It integrates customized skip connections to reduce semantic disparities between the encoder and decoder layers. Additionally, the architecture incorporates an innovative Classifier and Localizer (CNL) module, providing supplementary classification and localization insights with enhanced accuracy. By combining these insights with the segmentation results, CNL-ResUNet adeptly reduces the occurrence of false positives and false negatives. To evaluate the model’s performance, experiments were conducted utilizing the SISS dataset from the Ischemic Stroke Lesion Segmentation Challenge 2015. The outcomes from these experiments highlight the superiority of our approach, revealing significant qualitative and quantitative improvements across standard evaluation metrics like the Dice coefficient and Accuracy. Our proposed network demonstrates potential for advancing automated tools in stroke segmentation.

关键词： Deep learning Training Image segmentation Accuracy Semantics Stroke (medical condition) Robustness

来源：评论

学校读者我要写书评

暂无评论

LanCOPE: Language-Guided Category-Level Object Pose Estimation from a Single RGB Image

引用

IEEE Robotics and Automation Letters 2025年第7期10卷 7555-7562页

作者： Yang, Hui Sun, Wei Liu, Jian Zheng, Jin Dai, Zhenqi Mian, Ajmal Hunan University National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha 410082 China Central South University School of Architecture and Art Changsha 410082 China The University of Western Australia Department of Computer Science and Software Engineering 6009 WA Australia

Monocular RGB-based category-level object pose estimation is more practical and cost-effective for robotics. However, existing methods do not fully exploit the rich semantic and contextual information in multimodal data (e.g. language) that provides additional object attributes to guide the model in extracting category features more reliably. We propose a language-guided category-level object pose estimation method (LanCOPE), taking a single RGB image as input. Our method uses DINOv2 to recover depth from a single RGB image and converts it into point cloud to perceive the object's geometry. We then introduce language descriptions for the RGB image, estimated point cloud and overall scene to better guide the point cloud encoder and image encoder in learning category features. We develop a cross-modal differential perception feature fusion network to fuse multimodal features. This network employs a differential perception module to eliminate redundant information across different modalities, highlighting signifcant semantic differences and similarities. Furthermore, it uses a cross-attention mechanism to fuse the semantic information of the language and vision features, improving the overall perception. Finally, we design a denoising network based on the skip fusion transformer to recover the object pose accurately. Extensive experiments on REAL275 and Wild6D datasets show that LanCOPE achieves state-of-the-art performance. Our code is available at LanCOPE. © 2016 IEEE.

关键词： category-level object pose estimation languag RGB image

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：