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Experimental results on FMCW radar based Human Recognition using only Doppler information

Experimental results on FMCW radar based Human Recognition u...

International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology, ECTI-CON

作者： Patipon Petchtone Denchai Worasawate Tiwat Pongthavornkamol Kazuhiko Fukawa Yuyuan Chang Department of Electrical Engineering Faculty of Engineering Kasetsart University Bangkok Thailand National Electronic and Computer Technology Center National Science and Technology Development Agency Pathum Thani Thailand School of Engineering Tokyo Institute of Technology Tokyo Japan

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

The demand of indoor human identification systems that prioritize privacy has led to an increased interest in wireless sensing devices such as radar. Several studies have identified distinctive characteristics of human movement that cause Doppler signatures, which can be used for subject identification. Following them, this paper proposes an alternative machine learning approach for human identification, which uses only Doppler information from each subject by using FMCW radar. Experimental results in the two-subject scenarios show that the proposed method can achieve an accuracy of 96.2% (±1.1%) when data for both training and verification are obtained from the same scenarios, while an accuracy of 67.0% (±2.8 % ) can be achieved when data for the verification are obtained from different scenarios

关键词： Wireless communication Training Wireless sensor networks Privacy Accuracy Doppler radar Telecommunications

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A Low-power High-gain Inverter Stacking Amplifier with Rail-to-Rail Output 3

A Low-power High-gain Inverter Stacking Amplifier with Rail-...

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3rd IEEE International Conference on Design and Test of Integrated Micro and Nano-Systems, DTS 2021

作者： Shad, Erwin H. T. Moeinfard, Tania Molinas, Marta Ytterdal, Trond Faculty of Information Technology and Electrical Engineering Engineering Cybernetics Trondheim Norway York University Faculty of Electrical Engineering and Computer Science Toronto Canada Faculty of Information Technology and Electrical Engineering Electronic Systems Trondheim Norway

ISBN: (纸本)9780738132631

In this article, a rail-to-rail low-power amplifier is presented based on stacking inverter-based amplifiers. The output voltages of each inverter-based amplifier are converted to a current and then mirrored to the output so that a rail-to-rail output is achieved. Besides, extensive simulations have been carried out to show the effect of drain-source voltage on the intrinsic gain of a transistor. Based on these simulations, a minimum supply voltage is chosen to achieve high open-loop gain and low closed-loop gain error. All the simulations are carried out in a commercially available 0.18 μm CMOS technology. The proposed amplifier achieves 88 dB open-loop gain. It is exploited in a capacitively-coupled amplifier structure. The closed-loop gain is 40 dB in the bandwidth of 0.1 Hz to 10 kHz when the power consumption is 0.54 μW at a 1.2 V supply voltage. The total input-referred noise is 4.7 μVrms in the whole bandwidth. The proposed neural amplifier achieved 0.02 SEF in the bandwidth from 200 Hz to 10 kHz. The proposed amplifier achieved a rail-to-rail output swing while the SEF is among the best reported SEF in the literature. Besides, to show the robustness of the proposed structure in the presence of process and mismatch variation, 500 Monte Carlo simulations are carried out. The PSRR and CMRR mean values are 89 dB and 68 dB, respectively. Finally, the proposed neural amplifier area consumption is 0.03 mm2 without pads. © 2021 IEEE.

关键词： Bandwidth

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MetaCon: Revitalizing Internet Congestion Control with Meta-Reinforcement Learning

MetaCon: Revitalizing Internet Congestion Control with Meta-...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： He Bai Hui Li Jianming Que Minglong Zhang Peter Han Joo Chong Kalupahana Liyanage Kushan Sudheera Xinyuan Pei School of Electronic and Computer Engineering Peking University Shenzhen China School of Computer Science Fuyao University of Science and Technology Fuzhou China Department of Electrical and Computer Engineering Mississippi State University Starkville USA School of Engineering Computer and Mathematical Sciences Auckland University of Technology Auckland New Zealand Department of Electrical and Information Engineering Faculty of Engineering University of Ruhuna Sri Lanka

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Effective congestion control algorithms (CCAs) are crucial for the smooth operation of Internet communication infrastructure. CCAs adjust transmission rates based on congestion signals, optimizing resource utilization and user experience. However, existing studies, both rule-based and learning-based CCAs, often struggle with generalization and underperform when deployed in real-world environments. When applied to unseen network conditions, hand-crafted schemes or pre-trained models may experience significant performance degradation. To address this challenge, we propose MetaCon, a novel adaptive Internet congestion control approach based on meta-reinforcement learning. MetaCon leverages knowledge learned from prior scenarios to quickly adapt to new environments. Experimental results show that MetaCon outperforms existing algorithms by exhibiting superior generalization and achieving better transmission performance across a wide variety of network conditions.

关键词： Degradation Adaptation models Signal processing algorithms Signal processing User experience Acoustics Internet Resource management Speech processing

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Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s

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computers, Materials & Continua 2022年第2期70卷 2761-2775页

作者： Abdul Hanan Ashraf Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry Awais Mahmood Muhammad Attique Mohamed Habib Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer Science HITEC UniversityTaxila47080Pakistan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Faculty of Engineering Port Said UniversityPort Fuad CityEgypt

In recent years,the number of Gun-related incidents has crossed over 250,000 per year and over 85%of the existing 1 billion firearms are in civilian hands,manual monitoring has not proven effective in detecting *** is why an automated weapon detection system is *** automated convolutional neural networks(CNN)weapon detection systems have been proposed in the past to generate good ***,These techniques have high computation overhead and are slow to provide real-time detection which is essential for the weapon detection *** models have a high rate of false negatives because they often fail to detect the guns due to the low quality and visibility issues of surveillance *** research work aims to minimize the rate of false negatives and false positives in weapon detection while keeping the speed of detection as a key *** proposed framework is based on You Only Look Once(YOLO)and Area of Interest(AOI).Initially,themodels take pre-processed frames where the background is removed by the use of the Gaussian blur *** proposed architecture will be assessed through various performance parameters such as False Negative,False Positive,precision,recall rate,and F1 *** results of this research work make it clear that due to YOLO-v5s high recall rate and speed of detection are *** reached 0.010 s per frame compared to the 0.17 s of the Faster *** is promising to be used in the field of security and weapon detection.

关键词： Video surveillance weapon detection you only look once convolutional neural networks

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Comparison of Algebraic Reconstruction Technique Methods and Generative Adversarial Network in Image Reconstruction of Magnetic Induction Tomography (MIT)

Comparison of Algebraic Reconstruction Technique Methods and...

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2021 International Conference on Biomedical engineering, ICoBE 2021

作者： Lubis, A.J. Nasir, N.F. Mohd Zakaria, Z. Jusoh, M. Azizan, M.M. Zakaria, M.Z. Kazim, M.N.F.M. Rahman, S. Faculty of Engineering and Computer Science Universitas Harapan Medan Medan Indonesia Computer Engineering Program Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Biomedical Electronic Engineering Program Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Universiti Malaysia Perlis Perlis Malaysia Department of Electrical and Electronic Department Faculty of Engineering and Built Environment Universiti Sains Islam Malaysia Negeri Sembilan Malaysia Faculty of Mechanical Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Mechatronic Engineering Program Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Perlis Malaysia

Magnetic induction tomography (MIT) is a technique used for imaging electromagnetic properties of objects using eddy current effects. The non-linear characteristics had led to more difficulties with its solution especially in dealing with low conductivity imaging materials such as biological tissues. Two methods that could be applied for MIT image processing which is the Generative Adversarial Network (GAN) and the Algebraic Reconstruction Technique (ART). ART is widely used in the industry due to its ability to improve the quality of the reconstructed image at a high scanning speed. GAN is an intelligent method which would be able to carry out the training process. In the GAN method, the MIT principle is used to find the optimum global conductivity distribution and it is described as a training process and later, reconstructed by a generator. The output is an approximate reconstruction of the distribution's internal conductivity image. Then, the results were compared with the previous traditional algorithm, namely the regularization algorithm of BPNN and Tikhonov Regularization method. It turned out that GAN had able to adjust the non-linear relationship between input and output. GAN was also able to solve non-linear problems that cannot be solved in the previous traditional algorithms, namely Back Propagation Neural Network (BPNN) and Tikhonov Regularization method. There are several other intelligent algorithms such as CNN (Convolution Neural Network) and K-NN (K-Nearest Neighbor), but such algorithms have not been able to produce the expected image quality. Thus, further study is still needed for the improvement of the image quality. The expected result in this study is the comparison of these two techniques, namely ART and GAN to get the best results on the image reconstruction using MIT. Thus, it is shown that GAN is a better candidate for this purpose. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Generative adversarial networks

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Multi-dimensional Resource Allocation in HAP-assisted UAV Wireless Networks for IoRT Data Collection

Multi-dimensional Resource Allocation in HAP-assisted UAV Wi...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Hui Zhao Xinran Zhang Weilong Chen Xiaobin Xu Li Wang Zheng Chang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science Beijing University of Posts and Telecommunications Beijing China Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In this paper, we propose a multi-dimensional resource allocation scheme for Internet of Remote Things (IoRT) data collection in a high altitude platform (HAP)-assisted unmanned aerial vehicle (UAV) network. Considering the quality of service (QoS) requirements of delay-sensitive IoRT data, we propose a UAV-HAP double relay data transmission mode to reduce the transmission delay for delay-sensitive data. Since the resources of the UAV are limited, we jointly optimize communications, computing and storage resources to maximize the utility of the considered system. Due to the high dimensionality of the solution space, we design a Twin Delayed Deep Deterministic policy gradient-based multi-dimensional resource allocation (TD3-MDRA) algorithm to find the optimal resource allocation strategy. Extensive simulation results are presented to demonstrate the superior performance of TD3-MDRA for IoRT data collection with delay and resource constraints.

关键词： Wireless networks Simulation Quality of service Data collection Autonomous aerial vehicles Delays Telecommunication computing Internet Resource management Relays

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An Achievable and Analytic Solution to Information Bottleneck for Gaussian Mixtures

An Achievable and Analytic Solution to Information Bottlenec...

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IEEE International Symposium on Information Theory

作者： Yi Song Kai Wan Zhenyu Liao Hao Xu Giuseppe Caire Shlomo Shamai Faculty of Electrical Engineering and Computer Science Technical University of Berlin Berlin Germany School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China Department of Electronic and Electrical Engineering University College London London UK Department of Electrical and Computer Engineering Technion-Israel Institute of Technology Haifa Israel

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

In this paper, we consider a remote source coding problem with binary phase shift keying (BPSK) modulation sources, where observations are corrupted by additive white Gaussian noise (AWGN). An intermediate node, such as a relay, receives these observations and performs further compression to find the optimal trade-off between complexity and relevance. This problem can be formulated as an information bottleneck (IB) problem with Bernoulli sources and Gaussian mixture observations, for which no closed-form solution is known. To address this challenge, we propose a unified achievable scheme that employs three different compression strategies for intermediate node processing, i.e., two-level quantization, multi-level deterministic quantization, and soft quantization with tanh function. Comparative analyses with existing methods, such as the Blahut-Arimoto (BA) algorithm and the Information Dropout approach, are performed through numerical evaluations. The proposed analytic scheme is observed to consistently approach the (numerically) optimal performance over a range of signal-to-noise ratios (SNRs), confirming its effectiveness in the considered setting.

关键词： Quantization (signal) Closed-form solutions AWGN Phase modulation Source coding Approximation algorithms Binary phase shift keying

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WAEI: An Intelligent Chatbot for Helping Fighting the Pandemic Infodemic

WAEI: An Intelligent Chatbot for Helping Fighting the Pandem...

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Emerging Technologies for Dependable Internet of Things (ICETI), International Conference on

作者： Yahya Almurtadha Mukhtar Ghaleb Mohamed Ahmed Alomari Ibrahim Ahmed Al-Balatah Faculty of Computers and Information Technology University of Tabuk Tabuk Saudi Arabia Faculty of Computing and Information Technology University of Bisha Bisha Saudia Arabia Faculty of Technology & Electronic and Computer Engineering (FTKEK) Universiti Teknikal Malaysia Melaka Melaka Malaysia Faculty of Science and Engineering Al-Hikma University Sana’a Yemen

ISBN: (数字)9798331533557

ISBN: (纸本)9798331533564

The World Health Organization (WHO) began warning of a possible upcoming epidemic called monkeypox, while humanity is still suffering from the consequences of the latest epidemic. In addition to various health issues caused by the Covid-19 pandemic, an "infodemic" accompanied the virus that led to the spread of many fake news about the virus and possible medication treatments. This fake news led to the emergence of huge mass panic causing stress and anxiety and might lead to death. This paper proposes an intelligent Chatbot called WAEI (Arabic term means awareness in English) to increase the awareness of pandemic risks, methods of prevention, and precautionary measures. WAEI fight the infodemic by producing responses based on its knowledgebase that was formed from credible sources, namely the WHO. The Chatbot uses Natural Language Understanding (NLU) to infer its responses. 308 volunteers evaluated the proposed chatbot. The volunteers’ responses were statistically analyzed to measure whether the Chatbot is resourceful, coherent, and achieves user satisfaction. Precision, recall and F1 metrics shows improvement in accuracy, which reach 83% accuracy in responding to users’ inquiry. WAEI is of great value and has been proposed at the right time for the health sectors as it gives a good experience in using technology and smart systems to quickly handle infodemic effectively by providing necessary awareness for any potential foreseen diseases.

关键词： Measurement Accuracy Pandemics Prevention and mitigation Anxiety disorders Organizations Chatbots Smart systems Internet of Things Fake news

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Investigation of The Performance Impact of Active Layer Parameter Variations on Inverted Perovskite Solar Cells Using GPVDM

Investigation of The Performance Impact of Active Layer Para...

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IEEE Regional Symposium on Micro and Nanoelectronics (RSM)

作者： A. M. A. Aziz S. Muniandy M. I. Idris Z. A. F. M. Napiah Z. B. Zamani N. B. Norddin M. Rashid Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka (UTeM) Malaysia Micro and Nano Electronic Research Group (MiNE) Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka (UTeM) Malaysia Faculty of Electrical & Electronic Engineering Technology Universiti Teknikal Malaysia Melaka (UTeM) Malaysia School of Physics Universiti Sains Malaysia (USM) Malaysia

This research explores the performance of inverted perovskite solar cells (IPSC) using the General-purpose Photovoltaic Device Model (GPVDM) software. Alternatively, inorganic p-type semiconductors, especially NiOx which is the most widely used HTL, can provide intrinsically higher stability and exhibit lower cost than organic polymer-based HTL. The device structure in the simulation comprises ITO/NiOx/MAPbI3/C60/BCP/Ag. Various factors, including layer thickness, electrical parameters, absorption coefficient and refractive index of each layer, can influence the simulated IPSC's performance. GPVDM provides a comprehensive simulation platform to investigate the impact of these factors on the power conversion efficiency (PCE) of IPSCs. The simulation results from GPVDM exhibit a remarkable match and good agreement with achieving efficiencies of 17.35% and 17.57%. To optimize the results, two cases are analyzed and compared. Notably in Case 2, which employs experimental data for α and n from earlier research, outperforms the preceding journal with an efficiency of 18.23% compared to 17.57%. These simulation findings serve as a valuable guide for the fabrication of IPSCs utilizing NiOx, BCP, and C60 as active layers, offering insights into enhancing their performance.

关键词：

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Lag Synchronization and Lag H∞ Synchronization for Multiweighted Coupled Reaction-Diffusion Neural Networks Suffering Topology Attacks

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IEEE Transactions on Control of Network Systems 2025年

作者： Wang, Jin-Liang Zhao, Xin-Yu Ren, Shun-Yan Huang, Tingwen Tiangong University Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems School of Computer Science and Technology Tianjin300387 China Tiangong University School of Electronics & Information Engineering Tianjin300387 China University of Electronic Science and Technology of China School of Mechanical and Electrical Engineering Chengdu611731 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

This paper mainly discusses two kinds of coupled reaction-diffusion neural networks (CRNN) under topology attacks, that is, the cases with multistate couplings and with multiple spatial-diffusion couplings. On one hand, by adopting state feedback control scheme, the problem of the lag synchronization for the multistate coupled CRNN is addressed. Moreover, the influences of external disturbances for the lag synchronization of the CRNN with multistate couplings are also taken into consideration. On the other hand, several lag and lag H∞ synchronization conditions for CRNN with multiple spatial-diffusion couplings are derived under the help of the Kronecker product and the state feedback control method. Finally, two numerical examples are provided to verify the correctness of the derived criteria. © 2014 IEEE.

关键词： State feedback

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