检索结果-内蒙古大学图书馆

11th International Conference on Information Technology, computer and electrical engineering, ICITACEE 2024

作者： Meutia, Ernita Dewi Arnia, Fitri Nasaruddin Muharar, Rusdha Oktiana, Maulisa Saddami, Khairun School of Engineering Universitas Syiah Kuala Department of Electrical and Computer Engineering Banda Aceh Indonesia Universitas Syiah Kuala Department of Electrical and Computer Engineering Banda Aceh Indonesia

ISBN: (纸本)9798350389289

Cross-spectral face recognition (CSFR), particularly in the Near Infra-Red (NIR) and visual (VIS) spectrum, presents challenges due to differences in illumination and sensor characteristics. NIR sensors are commonly used in practical applications, such as in nighttime outdoor surveillance systems, due to their ability to capture images in low light conditions and at various standoff distances. This study proposes a simple CSFR method that combines deep learning techniques with photometric normalization using Homomorphic Filtering (HF) to identify subjects in NIR images across different standoff distances. Both NIR and VIS images are filtered to mitigate illumination discrepancies. A deep convolutional neural network (CNN) model is employed to automatically extract discriminative deep features from the normalized images of both spectrums. Four deep CNN models of ResNet-50, DenseNet, EfficientNet, and MobileNetV2 are tested. The performance of the models in feature extraction for CSFR is evaluated on the LDHF (Long Distance Heterogeneous Face) database. The Hamming distance metric is employed to match NIR probe images with VIS gallery images. The experimental findings, expressed in recognition rate RR, demonstrate the effectiveness of the approach in enhancing CSFR accuracy, with MobileNetV2 achieving the highest accuracy of 90% for a short standoff. In addition, HF improves image quality, enhancing the deep learning model's ability to discern image characteristics. © 2024 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Driver Assistance System for Stress Recognition by Handcrafted Feature Extraction and Convolutional Neural Network 20

Driver Assistance System for Stress Recognition by Handcraft...

引用

20th CSI International Symposium on Artificial Intelligence and Signal Processing, AISP 2024

作者： Vaezi, Mahtab Nasri, Mehdi Azimifar, Farhad Mosleh, Mahdi Branch Department of Biomedical Engineering Isfahan Iran Islamic Azad University Khomeinishahr Branch Department of Biomedical Engineering Isfahan Iran Branch Department of Computer Engineering Isfahan Iran

ISBN: (纸本)9798350383942

Stress is one of the emotional states that cause disruption in decision-making, that's why stress while driving can be dangerous. Identification of stress in drivers by smart algorithms and timely warning can prevent traffic accidents. In the proposed method to provide a stress detection driver assistance system, the feature vector is used as convolutional neural network input, which makes the training of the network stable in repeated repetitions, improves the weight update, and increases the classification accuracy. The drivedb database contains biosignals such as the ECG of drivers in city driving and in our proposed method, the ECG of this database is used. By using the proposed method, three stress states were identified with 93.6% accuracy, which has increased classification accuracy compared to similar methods. © 2024 IEEE.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Enhanced Overcoupled Plasmonic Resonators for Biomolecular Detection 38

Machine Learning-Enhanced Overcoupled Plasmonic Resonators f...

引用

38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Li, Dongxiao Zhou, Hong Ren, Zhihao Xu, Cheng Lee, Chengkuo National University of Singapore Department of Electrical & Computer Engineering Singapore

ISBN: (纸本)9798331508890

Plasmonic biosensors offer a unique opportunity to precisely control light-matter coupling in surface-enhanced infrared absorption (SEIRA) spectroscopy. However, the broadband nature of infrared spectra and the complex molecular information pose challenges in detecting and distinguishing biomolecules. Here, we propose the design of an overcoupled plasmonic resonator with ultrasensitive (7.25%/nm) and ultrabroadband (1000-3333 cm-1) sensing capabilities. These features allow the resonator to enhance multiple molecular fingerprint vibrations with high sensitivity. To further unlock the sensor's potential, machine learning is employed, achieving 100% accuracy in identifying five biomolecules based on rich vibrational data. With outstanding sensing performance and molecular recognition capabilities, the machine-learning-enhanced overcoupled resonator paves the way for broader SEIRA applications. © 2025 IEEE.

关键词： Infrared absorption

来源：评论

学校读者我要写书评

暂无评论

Digital Twin Enabled Runtime Verification for Autonomous Mobile Robots under Uncertainty 28

Digital Twin Enabled Runtime Verification for Autonomous Mob...

引用

28th IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications, DS-RT 2024

作者： Betzer, Joakim Schack Boudjadar, Jalil Frasheri, Mirgita Talasila, Prasad Aarhus University Department of Electrical and Computer Engineering Denmark

ISBN: (纸本)9798331527211

As autonomous robots increasingly navigate complex and unpredictable environments, ensuring their reliable behavior under uncertainty becomes a critical challenge. This paper introduces a Digital Twin as a service approach to enable runtime monitoring and verification of an autonomous mobile robot and mitigate the impact posed by uncertainty in the deployment environment. The safety and performance properties are specified and synthesized as runtime monitors using TeSSLa. The integration of the executable digital twin, via the MQTT protocol, enables continuous monitoring and validation of the robot's behavior in real-time. We explore different sources of uncertainties and analyze their impact on the robot safety and performance. Equipped with high computation resources, the cloud-located digital twin serves as a watch-dog model to estimate the actual state, checking the consistency of the robot's actuations and approving or denying such actuations depending on the safety and performance properties. The experimental analysis demonstrated high efficiency of the proposed approach in ensuring the reliability and robustness of the autonomous robot behavior in uncertain environments by securing high alignment between the actual and expected speeds where the difference is reduced by up to 41% compared to the default robot navigation control. © 2024 IEEE.

关键词： Mobile robots

来源：评论

学校读者我要写书评

暂无评论

Light-induced Magnetic Field in Graphene

Light-induced Magnetic Field in Graphene

引用

2024 Photonics North, PN 2024

作者： Abedi, S. Majedi, A.H. Department of Electrical and Computer Engineering University of Waterloo Canada

ISBN: (纸本)9798350366365

Through the application of the inverse Faraday effect (IFE), graphene can exhibit an optically-generated DC magnetization due to the nonlinear response of its orbital angular momentum to circularly polarized light. By providing a single-particle quantum mechanical model of this optomagnetic effect, we derive a non-perturbative analytical expression for magnetization based on dressed states of quasi-electrons in the Dirac region. Optical rotatory power is computed through gyroelectric birefringence where we predict measurable polarization rotation angles under moderate and intense optical radiation. © 2024 IEEE.

关键词： Faraday effect

来源：评论

学校读者我要写书评

暂无评论

CPT:A Configurable Predictability Testbed for DNN Inference in AVs

引用

Tsinghua Science and Technology 2025年第1期30卷 87-99页

作者： Liangkai Liu Yanzhi Wang Weisong Shi Department of Computer and Information Science University of DelawareNewarkDE 19713USA Department of Electrical&Computer Engineering Northeastern UniversityBostonMA 02115USA

Predictability is an essential challenge for autonomous vehicles(AVs)’*** neural networks have been widely deployed in the AV’s perception ***,it is still an open question on how to guarantee the perception predictability for AV because there are millions of deep neural networks(DNNs)model combinations and system configurations when deploying DNNs in *** paper proposes configurable predictability testbed(CPT),a configurable testbed for quantifying the predictability in AV’s perception *** provides flexible configurations of the perception pipeline on data,DNN models,fusion policy,scheduling policies,and predictability *** top of CPT,the researchers can profile and optimize the predictability issue caused by different application and system *** has been open-sourced at:https://***/Torreskai0722/CPT.

关键词： predictability deep neural network autonomous driving

来源：评论

学校读者我要写书评

暂无评论

MODELING OF AN E-DELIBERATION SYSTEM A REWARDING MECHANISM FOR ENHANCING CITIZENS’ INVOLVEMENT 21

MODELING OF AN E-DELIBERATION SYSTEM A REWARDING MECHANISM F...

引用

21st International Conference on Applied Computing 2024, AC 2024 and 23rd International Conference on WWW/Internet 2024, ICWI 2024

作者： Tsakanikas, Vassilis Triantafyllou, Vassilis Electrical & Computer Engineering Department University of Peloponnese Greece

ISBN: (纸本)9789898704627

This study presents a novel e-deliberation model that incorporates a rewarding mechanism to enhance citizen engagement and improve the quality of deliberative processes. The model simulates interactions between citizens and proposals, focusing on how costs and rewards influence citizen behavior. Through rigorous mathematical formulation and simulation, we demonstrate that the implementation of a rewarding mechanism significantly increases the number of comments posted by citizens. By adjusting parameters to provide substantial rewards for valuable contributions and reducing participation costs, we observed enhanced engagement and more dynamic interactions. The findings suggest that a well-calibrated reward structure can sustain long-term participation and prevent disengagement. Future work will involve empirical validation of the model using real-world data collected an e-deliberation system (PODS), which will further refine and validate the model's applicability in practical e-deliberation scenarios. © 2024 Proceedings of the International Conferences on Applied Computing and WWW/Internet 2024. All rights reserved.

关键词： Digital elevation model

来源：评论

学校读者我要写书评

暂无评论

A Wirelessly Powered, Battery-less, Miniaturized Microchip for Implantable Biopotential-Monitoring Applications

引用

IEEE Sensors Journal 2025年第11期25卷 19545-19554页

作者： Jang, Jaeeun Habibagahi, Iman Mathews, Roshan P. Gwak, Wonseop Rahmani, Hamed Babakhani, Aydin Kwangwoon University School of Semiconductor Systems Engineering Seoul Korea Republic of University of California at Los Angeles Department of Electrical Engineering Los AngelesCA90095 United States New York University Department of Electrical and Computer Engineering BrooklynNY11201 United States

This paper presents a low-power, battery-less biopotential-recording integrated circuit (IC) designed for implantable leadless cardiac monitoring applications, addressing the full autonomy based on wireless energy harvesting and closed-loop control. A key technical feature is the closed-loop capability with integration of a dual-band radio frequency (RF) energy harvester and communication system utilizing industrial, scientific, and medical (ISM) bands at 40.68 MHz for downlink and 915 MHz for uplink, ensuring efficient wireless power transfer and robust bi-directional data communication. The RF harvester achieves a peak conversion efficiency exceeding 40%, a critical design challenge in maintaining consistent performance under variable power conditions. Also, proposed IC overcomes the need for a local oscillator by utilizing an externally provided clock, reducing system complexity and power consumption. Operating with a clock frequency of 100 kHz, the IC consumes only 8.8 μW, a major achievement in energy efficiency for wireless, battery-less systems. Fabricated in a 180 nm complementary metal-oxide-semiconductor (CMOS) process, the IC successfully demonstrates cardiac signal measurement and heart rate extraction under a fully battery-less environment with air medium, providing a promising solution for next-generation leadless cardiac monitoring systems. © 2001-2012 IEEE.

关键词： Inductive power transmission

来源：评论

学校读者我要写书评

暂无评论

A 500 kHz Wide Output LLC-T Resonant Converter With Narrow Frequency Range, Reduced Circulating Energy, and Low Voltage Stress

引用

IEEE Transactions on Power Electronics 2025年第8期40卷 11749-11762页

作者： Hou, Zhengming Jiao, Dong Lai, Jih-Sheng Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering BlacksburgVA24061 United States

The resonant converters are promising topologies for the electric vehicle charging applications due to the soft switching feature. However, the conventional LLC resonant converter regulates the wide output voltage through a wide frequency range, which leads to low efficiency with large circulating energy and the difficulty of the resonant tank optimization. This article proposes a novel LLC-T resonant converter, which parallels an auxiliary transformer with the LC resonant tank for the wide output applications. The proposed LLC-T resonant converter narrows the frequency range with less circulating energy, lower voltage stress on the resonant capacitor, and smaller flux linkage in the resonant inductor compared to the conventional LLC resonant converter. Meanwhile, the zero-voltage switching turn-on is maintained throughout the wide output voltage range and load range. Furthermore, a precise time-domain based analysis and the design methodology are proposed. A 500-kHz, 1.35 kW, 400 V input 250 V-450 V output prototype is built to verify the concepts of the proposed topology and demonstrates a 97.82% peak efficiency. © 1986-2012 IEEE.

关键词： Resonant converters

来源：评论

学校读者我要写书评

暂无评论

Transform Kernel Selection for Blended Intra Prediction

Transform Kernel Selection for Blended Intra Prediction

引用

2025 International Workshop on Advanced Imaging Technology, IWAIT 2025

作者： Cheon, Muho Pai, Hongkwon Jeon, Byeungwoo Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

ISBN: (数字)9781510688131

ISBN: (纸本)9781510688124

In this paper, we investigate an explicit transform selection method that merges transform sets of the two intra prediction modes used for predictor blending, aimed at the new blending intra prediction (BIP) tools (i.e., DIMD, TIMD, OBIC) for the enhanced compression beyond VVC *** existing multiple transform selection (MTS) mechanism in ECM is designed based on the characteristics of regular intra prediction modes, which differ from those of BIP ***, applying the existing selection method of multiple transform set to BIP modes is *** proposed method merges multiple transform sets corresponding to the two intra prediction modes used for predictor generation and makes it possible for a decoder to decide which transform kernel pair to use without explicit *** enables the use of more diverse transform kernel *** results show performance improvements of -0.01%, 0.00%, and 0.01% for the Y, Cb, and Cr components, respectively, compared to the ECM 13.0 test model under the All Intra (AI) *** results emphasize clear need for an improved MTS scheme tailored to BIP tools as well. © 2024 SPIE.

关键词： Image compression

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：