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2nd IEEE International Conference on computer Vision and Machine Intelligence, CVMI 2023

作者： Tsugawa, Seizan Toma, Takao Oshiro, Shiho Wada, Tomohisa University of the Ryukyus Computer Science and Intelligent Systems Program Okinawa Japan Magna Design Net Inc Okinawa Japan University of the Ryukyus Information Technology Center Okinawa Japan University of the Ryukyus Area of Computer Science and Intelligent Systems Dept. of Engineering Okinawa Japan

ISBN: (纸本)9798350305142

This paper proposed Scalability in Autoencoder-based Orthogonal Frequency Division Multiplexing(OFDM) communication system. In the previous research, only the comparison between IEEE802.11a and Autoencoder by the conventional OFDM communication system was performed, and it was proved that the communication system created by Autoencoder exceeded the performance of the conventional system. Therefore, in this paper, it uses IEEE802.11n and compare whether it can be improved by expanding the bandwidth and using ***802.11n standard has an FFT length of 128, a subcarrier number of 114 (108 for data), and modulation schemes of Quadrature Phase Shift Keying(QPSK), 16 Quadrature Amplitude Modulation (16QAM). The GI length is 800ns and the symbol length is 4000ns. In the simulation, a computer simulation was performed using a conventional OFDM communication system and a communication system generated by Autoencoder. Assuming that the simulation environment had an Signal-to-Noise Ratio (SNR) of 0 to 30 and an amplitude r of 0.0 to 1.0, the Symbol Error Rate (SER) status for each SNR was output. As a result of computer simulation, QPSK converged at SNR 27 at IEEE 802.11a, but was able to reduce SER overwhelmingly to SNR 12 at IEEE 802.11n. Also, in 16QAM the convergence at r=0.0 is the same as for SNR22 , but in IEEE 802.11a it does not converge after r=0.6, but in IEEE 802.11n it does not converge only at r=0.9 and r=1.0. As a future task, it will use IEEE802.11ac, which enables communication speeds several times faster than IEEE802.11n, examine whether it is possible to further improve accuracy. And it will continue our research to correspond MIMO communication. © 2023 IEEE.

关键词： Orthogonal frequency division multiplexing

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Pseudo-label Assisted Optimization of Multi-branch Network for Cross-domain Person Re-identification 20

Pseudo-label Assisted Optimization of Multi-branch Network f...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Wang, Zhengyang Guo, Shuxiang Shang, Xue Ye, Xiufen Harbin Engineering University College of Intelligent Systems Science and Engineering Harbin China National University of Singapore Department of Electrical and Computer Engineering Singapore Beijing Institute of Technology School of Life Science Beijing China

ISBN: (纸本)9798350320831

Person re-identification plays an important role in the field of robot intelligence perception and public safety. Its main task is to identify person targets under cross-camera. However, the domain diversity between different datasets poses a clear challenge for adapting a model trained on one dataset to another. Currently, person re-identification methods based on domain adaptive learning and pseudo-label have made good progress on this problem. Unfortunately, inferior pseudo-labels and source domain noise affect the performance. In order to improve the quality of generated pseudo-labels and enhance the feature representation capability of the model, we propose a pseudo-label assisted optimization of a multi-branch person re-identification method. The multi-branch network is able to extract and represent more effective global and local features, and the generated pseudo-labels are optimized by using cosine similarity and DBSCAN clustering on the feature vectors, thus improving the consistency of the supervised information to enhance the cross-domain recognition performance. We also use a loss function combining cross-entropy loss and triplet loss to make the best feature learning. Experiments show that our method performs well in the Market-to-Duke and Duke-to-Market cross-domain recognition tasks. © 2023 IEEE.

关键词： intelligent robots

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Methods for Predictive Performance Improvement of Deep Learning systems for Aerial Building Roof Detection with Multispectral Images

Methods for Predictive Performance Improvement of Deep Learn...

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2023 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement systems and Applications, CIVEMSA 2023

作者： Churi, A. Megherbi, D.B. University of Massachusetts Center for Human/Machine Intelligence Networking Distributed Systems Department of Electrical and Computer Engineering LowellMA United States

ISBN: (纸本)9781665434454

In this paper, we present a dilated convolutional neural network-based deep learning system for the challenging problem of building accurate roof pixel detection from city aerial multispectral images in the visible and infrared spectral bands. The proposed system uses an automatic spectral band selection strategy and an automatic histogram-based threshold-finding method to improve the network's prediction accuracy performance. Current existing systems train a single model on all the cities of interest data at once. These systems also usually use only RGB bands and avoid post-processing of the predicted images for increased prediction accuracies. In this paper, we present the following solutions to these object detection challenges, 1) we propose and implement a separate model for each city dataset, 2) we propose an optimal band selection strategy to choose the most informative visible-infrared bands from multispectral images, 3) we propose an adaptive and automatic histogram-based optimal threshold finding technique for building roof object segmentation. Our results show that having a separate model for each city rather than only one model for all the combined cities increases the system's performance by 20.77% in building roof pixel prediction in any of the cities considered. We show that our system also has a 35.6% increase in F1 score compared to its state-of-The-Art counterpart, the winning implementation of the SpaceNet building detection national challenge, which took place in 2017. © 2023 IEEE.

关键词： Object recognition

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Random suppression of ECG artifacts using a NLSRLMMN-based cascaded noise canceller 58

Random suppression of ECG artifacts using a NLSRLMMN-based c...

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58th Asilomar Conference on Signals, systems and computers, ACSSC 2024

作者： Faiz, Mohammed Mujahid Ulla Zerguine, Azzedine Kale, Izzet Presidency University Department of Electrical and Computer Engineering Karnataka Bengaluru560064 India Interdisciplinary Research Center for Communication Systems and Sensing Kfupm Electrical Engineering Department Dhahran31261 Saudi Arabia Department of Computer Science and Engineering LondonW1W 6UW United Kingdom

ISBN: (纸本)9798350354058

Normally, the electrocardiogram (ECG) signal artifacts are removed in a particular sequence starting with baseline wander removal at the beginning. In this work, a methodology has been proposed using a novel algorithm called the Normalized Leaky Sign Regressor Least Mean Mixed Norm (NLSRLMMN) algorithm to remove multiple ECG artifacts such as baseline wander, motion artifacts, muscle artifacts, and power line interference randomly without following a particular sequence. Through rigorous simulations we have shown that if we remove multiple ECG artifacts randomly using our proposed approach then an improvement in signal to noise ratio and mean square error is observed as opposed to a conventional method that employs the Least Mean Square (LMS) algorithm in all the cascaded adaptive noise canceller stages. © 2024 IEEE.

关键词： Mean square error

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Powering Inaccessible IoT Devices Through a WPT-enabled Sustainable UAV Network

Powering Inaccessible IoT Devices Through a WPT-enabled Sust...

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2023 IEEE INFOCOM Conference on computer Communications Workshops, INFOCOM WKSHPS 2023

作者： Mekikis, Prodromos-Vasileios Bouzinis, Pavlos Mitsiou, Nikos Tegos, Sotiris Papanikolaou, Vasilis Tyrovolas, Dimitrios Diamantoulakis, Panagiotis Karagiannidis, George K. Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki Greece Cyber Security Systems and Applied AI Research Center Lebanon

ISBN: (纸本)9781665494274

Powering Internet of Things (IoT) devices in hard to reach or hazardous locations could be prohibitive in terms of cost and safety. In this work, we demonstrate a thorough solution that tackles this problem using a network of unmanned aerial vehicles (UAVs) with wireless power transfer (WPT) capabilities. Given the large-scale IoT deployments of the future and the energy needs of the UAVs, we consider an infrastructure of charging stations for the UAVs that allow an uninterrupted and flexible UAV deployment based on the current energy needs of the IoT devices. Then, we exhibit an orchestrator that communicates with the entire infrastructure and handles the UAV traffic and energy decisions, as well as the digital representation and interaction of the network with the user. © 2023 IEEE.

关键词： User interfaces

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Periodic event-triggered impulsive control for a class of uncertain nonlinear systems

Periodic event-triggered impulsive control for a class of un...

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第43届中国控制会议

作者： Feng Shu Min Li Yuanyuan Li Jinnan Luo Center for Intelligent Complex Systems College of Electrical EngineeringSouthwest Minzu University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Addressed in this note is the periodic event-triggered impulsive control for a class of uncertain nonlinear *** reducing the impulsive control cost,periodic event-triggered(PET) impulsive control strategy is widely used to generate the impulsive instants. However,this strategy is often adopted for linear systems or nonlinear systems with certain *** extending the result to nonlinear systems with large uncertainties,a sliding variable-based PET impulsive controller and a PET mechanism are co-designed. Then,a gain scaling technique is introduced to solve the uncertainties in the considered *** is proved that all the system states can converge to the origin asymptotically. Finally,an example is provided to show the effectiveness of the proposed method.

关键词： Impulsive control periodic event-triggered strategy uncertain nonlinear systems

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Linear Active Disturbance Rejection Control with a Fractional-Order Integral Action

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computers, Materials & Continua 2022年第11期73卷 3057-3079页

作者： Maâmar Bettayeb Rachid Mansouri Ubaid M.Al-Saggaf Abdulrahman U.Alsaggaf Mohammed Moinuddin Electrical Engineering Department University of SharjahUnited Arab Emirates L2CSP Laboratory University Mouloud Mammeri of Tizi-OuzouAlgeria Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddahSaudi Arabia Electricaland Computer Engineering Department King Abdulaziz UniversityJeddahSaudi Arabia

Linear active disturbance rejection control(LADRC)is a powerful control structure thanks to its performance in uncertainties,internal and external disturbances estimation and *** extended state observer(ESO)based controller is the key to the LADRC *** this article,the LADRC scheme combined with a fractional-order integral action(FOILADRC)is proposed to improve the robustness of the standard *** the robust closed-loop Bode’s ideal transfer function(BITF),an appropriate pole placement method is proposed to design the set-point tracking controller of the FOI-LADRC *** simulations and experimental results on a cart-pendulum system will illustrate the effectiveness of the proposed FOI-LADRC scheme for the disturbance rejection,the set-point tracking and the improved *** illustrate the LADRC control schemes and to verify the performance of the proposed FOI-LADRC,compared to the standard LADRC and IOI-LADRC structures,two tests will be carried ***,simulation tests on an academic example will be presented to show the effect of the different parameters of the control law on the performance of the closed-loop ***,these three control structures are implemented on an experimental test bench,the cart-pendulum system,to show their efficiency and to show the superiority of the proposed method compared to the two other structures.

关键词： Fractional calculus active disturbance rejection control pole placement cart-pendulum system robust control

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Investigation on Structures of Axial Gap Type Magnetic Multiple Spur Gear for In-Wheel Motor System of Electric Vehicle

Investigation on Structures of Axial Gap Type Magnetic Multi...

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2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023

作者： Kamijo, Taiga Aiso, Kohei Akatsu, Kan Aoyama, Yasuaki Shibaura Institute of Technology Electrical Engineering and Computer Science Tokyo Japan Shibaura Institute of Technology Department of Electrical Engineering Tokyo Japan Yokohama National University Division of Intelligent Systems Engineering Department of Faculty of Engineering Yokohama Japan Center for Technology Innovation - Materials Hitachi Ltd. Research & Development Group Ibaraki Japan

ISBN: (纸本)9798350314274

A novel drive system using Magnetic Multiple Spur Gear (MMSG) and multiple high-speed motors is characterized by small size, lightweight, and high efficiency even at high-speed region, it is expected to apply to in-wheel motor systems. However, there is a risk of contact between the rotors when applied to in-wheel motor system. In this study, a novel axial-gap MMSG is proposed to solve this problem, stabilize the air gap between the high-speed and low-speed rotors, and effectively utilize the magnets, and its performance is evaluated by finite element analysis. © 2023 IEEE.

关键词： Electric vehicles

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Coupling Mobile Brain Imaging and Virtual Reality Omnidirectional Treadmill to Explore Attenuated Situational Awareness during Distracted Walking

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IEEE Transactions on Cognitive and Developmental systems 2024年第3期16卷 1063-1076页

作者： Chuang, Chun-Hsiang Chiu, Tsai-Feng Hsu, Hao-Che Lin, Shih-Syun National Tsing Hua University Research Center for Education and Mind Sciences College of Education The Institute of Information Systems and Applications College of Electrical Engineering and Computer Science Hsinchu300 Taiwan National Tsing Hua University Research Center for Education and Mind Sciences Hsinchu300 Taiwan National Yang Ming Chiao Tung University Department of Computer Science Hsinchu300193 Taiwan National Taiwan Ocean University Department of Computer Science and Engineering Keelung20224 Taiwan

Walking while engaging in distracting activities affects our perception of changes happening on the road, leading to exposure to hazardous conditions. This study aimed to evidence that pedestrians who become distracted when absorbed in their smartphones fail to maintain situational awareness. Thirty-six recruited participants performed a psychomotor vigilance task and a wayfinding task designed to simulate a multitasking scenario;meanwhile, an auditory oddball paradigm presented to participants tested their situational awareness of an external stimulus. The experiment was conducted in virtual reality (VR) environment with an omnidirectional treadmill. Participant's behavioral and electroencephalographic (EEG) responses were measured and analyzed using a newly proposed brain network measure, phase locking distance (PLD), to capture multitasking-associated couplings between brain regions. The current study supports the notion that multitasking can lead to diminished behavioral performance and changes in walking patterns. Despite the increased interregional brain connectivity, which may be an adaptive response to heightened cognitive demands, the associated reduction in event-related EEG activity suggests competition for neural resources during multitasking. Moreover, the observed EEG activities could indicate additional information processing capacity limitations and provide evidence of decreased situational awareness during multitasking, thereby increasing susceptibility to potentially hazardous situations. © 2016 IEEE.

关键词： Electroencephalography

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Condition Monitoring and Maintenance Management with Grid-Connected Renewable Energy systems

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computers, Materials & Continua 2022年第8期72卷 3999-4017页

作者： Md.Mottahir Alam Ahteshamul Haque Mohammed Ali Khan Nebras M.Sobahi Ibrahim Mustafa Mehedi Asif Irshad Khan Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah 21589Saudi Arabia Advance Power Electronics Research Lab Department of Electrical EngineeringJamia Millia IslamiaNew Delhi 110025India Department of Electrical Power Engineering Faculty of Electrical Engineering and CommunicationBrno University of TechnologyBrno 61600Czech Republic Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah 21589Saudi Arabia Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia

The shift towards the renewable energy market for carbon-neutral power generation has encouraged different governments to come up with a plan of *** with the endorsement of renewable energy for harsh environmental conditions like sand dust and snow,monitoring and maintenance are a few of the prime *** problems were addressed widely in the literature,but most of the research has drawbacks due to long detection time,and high misclassification *** to overcome these drawbacks,and to develop an accurate monitoring approach,this paper is motivated toward the understanding of primary failure concerning a grid-connected photovoltaic(PV)system and highlighted along with a brief overview on existing fault detection *** on the drawback a data-driven machine learning approach has been used for the identification of fault and indicating the maintenance unit regarding the operation and maintenance ***,the system was tested with a 4 kWp grid-connected PV system,and a decision tree-based algorithm was developed for the identification of a *** results identified 94.7%training accuracy and 14000 observations/sec prediction speed for the trained classifier and improved the reliability of fault detection nature of the grid-connected PV operation.

关键词： Fault detection machine learning fault ride through

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