检索结果-内蒙古大学图书馆

7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023

作者： Xiao, Feng Sun, Sijia Wang, Xiaoyu State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9789819733392

The formation control problem of second-order nonholonomic systems formulated by a force-balance equation is investigated with network communication constraints. A novel event-triggered mechanism based on polynomial interpolation predictive models is presented. To address the stabilization obstacles imposed by the nonholonomic constraints, persistently exciting (PE) functions are utilized to design the distributed control protocols. Under the designed event-triggered mechanism, the system does not exhibit Zeno behavior. Sufficient conditions for second-order nonholonomic systems to achieve stable formation are obtained based on Barbalat’s lemma. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed results. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Distributed parameter control systems

来源：评论

学校读者我要写书评

暂无评论

CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

引用

computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood Ul Haq Muhammad Athar Javed Sethi Najib Ben Aoun Ala Saleh Alluhaidan Sadique Ahmad Zahid farid Department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and Information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan Department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, COMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the COMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

OSAP‐Loss:Efficient optimization of average precision via involving samples after positive ones towards remote sensing image retrieval

引用

CAAI Transactions on Intelligence Technology 2023年第4期8卷 1191-1212页

作者： Xin Yuan Xin Xu Xiao Wang Kai Zhang Liang Liao Zheng Wang Chia‐Wen Lin School of Computer Science and Technology Wuhan University of Science and TechnologyWuhanChina Hubei Province Key Laboratory of Intelligent Information Processing and Real‐time Industrial System Wuhan University of Science and TechnologyWuhanChina Nanyang Technological University SingaporeSingapore School of Computer Science Wuhan UniversityWuhanChina Department of Electrical Engineering Industrial Technology Research InstituteNational Tsing Hua UniversityHsinchuChina

In existing remote sensing image retrieval(RSIR)datasets,the number of images among different classes varies dramatically,which leads to a severe class imbalance *** studies propose to train the model with the ranking‐based metric(e.g.,average precision[AP]),because AP is robust to class ***,current AP‐based methods overlook an important issue:only optimising samples ranking before each positive sample,which is limited by the definition of AP and is prone to local *** achieve global optimisation of AP,a novel method,namely Optimising Samples after positive ones&AP loss(OSAP‐Loss)is proposed in this ***,a novel superior ranking function is designed to make the AP loss differentiable while providing a tighter upper ***,a novel loss called Optimising Samples after Positive ones(OSP)loss is proposed to involve all positive and negative samples ranking after each positive one and to provide a more flexible optimisation strategy for each ***,a graphics processing unit memory‐free mechanism is developed to thoroughly address the non‐decomposability of AP *** experimental results on RSIR as well as conventional image retrieval datasets show the superiority and competitive performance of OSAP‐Loss compared to the state‐of‐the‐art.

关键词： computer vision image retrieval metric learning

来源：评论

学校读者我要写书评

暂无评论

Deep Conditional Generative Adversarial Networks for Efficient Channel Estimation in AmBC systems

IEEE Transactions on Machine Learning in Communications and ...

引用

IEEE Transactions on Machine Learning in Communications and Networking 2024年 2卷 805-822页

作者： Zargari, Shayan Tellambura, Chintha Maaref, Amine Li, Geoffrey Ye University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Huawei Canada Ottawa Wireless Advanced System Competency Centre OttawaONK2K 3J1 Canada Imperial College London School of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom

In ambient backscatter communication (AmBC), battery-free devices (tags) harvest energy from ambient radio frequency (RF) signals and communicate with readers. Although reliable channel estimation (CE) is critical, classical pilot-based estimators tend to perform poorly. To address this challenge, we treat CE as a denoising problem using conditional generative adversarial networks (CGANs). A three-dimensional (3D) denoising block leverages spatial and temporal characteristics of pilot signals, considering both real and imaginary components of channel matrices. The proposed CGAN estimator is extensively evaluated against traditional estimators like minimum mean-squared error (MMSE), least squares (LS), convolutional neural network (CNN), CNN-based deep residual learning denoiser (CRLD), and blind estimation. Simulation results show 82% gain of the proposed estimator over CRLD and MMSE estimators at an SNR of 5 dB. Moreover, it has advanced learning capabilities and accurately replicates complex channel characteristics. © 2023 CCBY.

关键词： Channel estimation

来源：评论

学校读者我要写书评

暂无评论

Data-driven Robust State Estimation Through Off-line Learning and On-line Matching

引用

Journal of Modern Power systems and Clean Energy 2021年第4期9卷 897-909页

作者： Yanbo Chen Hao Chen Yang Jiao Jin Ma Yuzhang Lin State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Electrical&Electronic EngineeringNorth China Electric Power UniversityBeijing 102206China School of Electrical and Information Engineering University of SydneySydney 2006Australia Department of Electrical and Computer Engineering University of MassachusettsLowellMA 01852USA

To overcome the shortcomings of model-driven state estimation methods, this paper proposes a data-driven robust state estimation (DDSE) method through off-line learning and on-line matching. At the off-line learning stage, a linear regression equation is presented by clustering historical data from supervisory control and data acquisition (SCADA), which provides a guarantee for solving the over-learning problem of the existing DDSE methods;then a novel robust state estimation method that can be transformed into quadratic programming (QP) models is proposed to obtain the mapping relationship between the measurements and the state variables (MRBMS). The proposed QP models can well solve the problem of collinearity in historical data. Furthermore, the off-line learning stage is greatly accelerated from three aspects including reducing historical categories, constructing tree retrieval structure for known topologies, and using sensitivity analysis when solving QP models. At the on-line matching stage, by quickly matching the current snapshot with the historical ones, the corresponding MRBMS can be obtained, and then the estimation values of the state variables can be obtained. Simulations demonstrate that the proposed DDSE method has obvious advantages in terms of suppressing over-learning problems, dealing with collinearity problems, robustness, and computation efficiency.

关键词： Robust state estimation historical snapshot off-line learning on-line matching collinearity

来源：评论

学校读者我要写书评

暂无评论

Integrated Device for Controllable Droplet Generation and Detection on Open Array Chip 16th

Integrated Device for Controllable Droplet Generation and De...

引用

16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Zhou, Zijian Wang, Jie Li, Yuxin Zhou, Jia Du, Lin School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai200433 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200433 China State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai200433 China

ISBN: (纸本)9789819965007

The open array chip is an incredibly valuable tool for analyzing single molecule levels. Its efficiency, speed, compatibility, and precision make it an essential part of this process. However, efficient sample addition has become a significant challenge in the development of open array chips due to the coupling of the solid-liquid interface and the need for high-precision control. To address this challenge, we have developed an integrated adding sample device using technology of generates and detects controllable droplets array based on an open array chip with a biomimetic structure. This device combines a microfluidic chip, image detection, and smear speed regulation. We have studied the factors that affect the efficiency of sample loading, such as the number, speed and fluctuation of smears, and microwell size. The experiments have shown that the open array chip with the microwell’s diameter of 350 µm can generate arrays of ~470/cm2 ~8 nL droplets, significantly reducing controlled speed fluctuation errors by7.24% and volume fluctuation errors by 24% compared to traditional manual ways. The device has also displayed excellent performance on chips with microwell diameters of 120, 350, 700, and 1300 µm, respectively, with a notable first-time success rate of up to 91% on chips with microwell diameters of 120 µm. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Microfluidic chips

来源：评论

学校读者我要写书评

暂无评论

Real-time Safety Helmet-wearing Detection Based on Improved YOLOv5

引用

computer systems Science & engineering 2022年第12期43卷 1219-1230页

作者： Yanman Li Jun Zhang Yang Hu Yingnan Zhao Yi Cao NARI Nanjing Control System Ltd. Nanjing210032China School of Computer Nanjing University of Information Science&TechnologyNanjing210044China Department of Electrical and computer Engineering University of WindsorWindsorN9B 3P4Canada

Safety helmet-wearing detection is an essential part of the intelligentmonitoring system. To improve the speed and accuracy of detection, especiallysmall targets and occluded objects, it presents a novel and efficient detectormodel. The underlying core algorithm of this model adopts the YOLOv5 (YouOnly Look Once version 5) network with the best comprehensive detection performance. It is improved by adding an attention mechanism, a CIoU (CompleteIntersection Over Union) Loss function, and the Mish activation function. First,it applies the attention mechanism in the feature extraction. The network can learnthe weight of each channel independently and enhance the information dissemination between features. Second, it adopts CIoU loss function to achieve accuratebounding box regression. Third, it utilizes Mish activation function to improvedetection accuracy and generalization ability. It builds a safety helmet-wearingdetection data set containing more than 10,000 images collected from the Internetfor preprocessing. On the self-made helmet wearing test data set, the averageaccuracy of the helmet detection of the proposed algorithm is 96.7%, which is1.9% higher than that of the YOLOv5 algorithm. It meets the accuracy requirements of the helmet-wearing detection under construction scenarios.

关键词： Safety helmet wearing detection object detection deep learning YOLOv5 Attention Mechanism

来源：评论

学校读者我要写书评

暂无评论

Developing Engagement in the Learning Management system Supported by Learning Analytics

引用

computer systems Science & engineering 2022年第7期42卷 335-350页

作者： Suraya Hamid Shahrul Nizam Ismail Muzaffar Hamzah Asad W.Malik Department of Information System Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala LumpurMalaysia Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Department of Computing School of Electrical Engineering and Computer Science(SEECS)National University of Sciences and Technology(NUST)IslamabadPakistan

Learning analytics is an emerging technique of analysing student par-ticipation and *** recent COVID-19 pandemic has signiﬁcantly increased the role of learning management systems(LMSs).LMSs previously only complemented face-to-face teaching,something which has not been possible between 2019 to *** date,the existing body of literature on LMSs has not analysed learning in the context of the pandemic,where an LMS serves as the only interface between students and ***,productive results will remain elusive if the key factors that contribute towards engaging students in learning are notﬁrst identiﬁ***,this study aimed to perform an exten-sive literature review with which to design and develop a student engagement model for holistic involvement in an *** required data was collected from an LMS that is currently utilised by a local Malaysian *** model was validated by a panel of experts as well as discussions with *** is our hope that the result of this study will help other institutions of higher learning determine factors of low engagement in their respective LMSs.

关键词： Engagement analysis learning analytics learning management system student engagement

来源：评论

学校读者我要写书评

暂无评论

A Compact Electro-tactile system for Braille Display 46

A Compact Electro-tactile System for Braille Display

引用

46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Chu, Po-Hsun Chen, Hai-Yin Chou, Lin Chen, Yu-Ching Tsai, Kun-Ju Liao, Yu-Te National Yang Ming Chiao Tung University School of Medicine Taiwan National Yang Ming Chiao Tung University Institute of Electrical and Computer Engineering Taiwan Industrial Technology Research Insitute Electronic and Optoelectronic System Research Laboratories Taiwan

ISBN: (纸本)9798350371499

Tactile displays have gained significant attention, particularly in the medical field for their application in Braille for the visually impaired. Traditional Braille embossing systems face limitations in terms of device size and complexity due to mechanical stimulation. Therefore, electro-tactile displays have emerged as a promising solution for implementing Braille. Our study presents a compact electro-tactile device with built-in electrodes, which is used to determine optimized stimulation parameters. We conducted tests on both polarity and intensity, culminating in a Braille number examination using 0.8mA, 1ms anodal stimulation. The results showed an average accuracy of 64.3% in seven participants, and three of them achieved over 90%. © 2024 IEEE.

关键词： Tactile reading aids

来源：评论

学校读者我要写书评

暂无评论

Light Fidelity and Internet of Things for Medical Applications 4

Light Fidelity and Internet of Things for Medical Applicatio...

引用

4th International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2024

作者： Adi, Puput Dani Prasetyo Sariningrum, Ros Rahmatullah, Rizky Novita, Hessy Situngkir, Tiar Lina Adji, Priyo Hartono Lusiastuti, Angela Mariana Wibowo, Antonia Rahayu Rosaria Prastiyono, Yudi Adiprabowo, Tjahjo Yassir, Muhammad Maulana, Fairuz Iqbal Department of Telecommunication Bandung Indonesia Veterinary Research Center Bandung Indonesia Singaperbangsa University Faculty of Economics Department of Management Karawang Indonesia Bandung Indonesia Langlangbuana University Faculty of Engineering Department of Electrical Engineering Bandung Indonesia Institut Teknologi Dan Bisnis Nobel Department of System and Information System Makassar Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350376111

This study focuses on transmitting data utilizing medical sensors that are vital for patients in hospitals and other settings. In this situation, Light Fidelity refers to transmitting medical sensor data or other data comprising the Transmitter (Tx) and the Receiver (Rx). If the Light Fidelity Principle is used, the Transmitter transmits LEDs or light to the Receiver. At the same time, the Receiver contains a receiver or light detection component known as the Light Dependent Resistor (LDR);using programming and this basic working principle, data can be sent from the LED Transmitter to the LDR Receiver using C++ Programming and its Library to send Medical sensor data. Sensors can include pulse sensors, like in prior research, and additional sensors such as SPO2 or blood pressure sensors. For medical data, a modest bit rate is sufficient, but LiFi applications can be created in such a way that they can be hybridized with WiFi and other RF devices such as LoRa and the Internet of Things. © 2024 IEEE.

关键词： C++ (programming language)

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：