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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Yan, Xufei Chen, Renliang Zhu, Shiqiang Xie, Anhuan Gu, Jason Research Center for Intelligent Robotics Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China National Key Laboratory of Science and Technology on Rotorcraft Aeromechanics College of Aeronautics Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

This paper investigates the optimal landing trajectory and control procedure when a helicopter undergoes autorotation due to tail rotor drive failure (TRDF), in which an optimal control methodology is proposed. First, a helicopter flight dynamics model with TRDF was developed. Then, the autorotation in TRDF was converted to be a nonlinear optimal control problem, solved by direct node collocation method and sequential quadratic programming algorithm. Finally, a model helicopter (Z11) with single main rotor and tail rotor was used to demonstrate the proposed approach. An optimal autorotation landing procedure in TRDF was determined accordingly. Results indicate that the airframe will immediately respond to the excess torque generated by the main rotor via yawing, sideslip and rolling when TRDF occurs. The pilot is recommended to shut down the engine and perform a series of critical operations to stabilize the violent yaw and roll movements. In addition, flight test data were used to validate the numerical simulations of autorotation landing. The proposed optimal control approach provides a useful tool to investigate helicopter TRDF autorotation landing procedure. © 2022 IEEE.

关键词： Helicopters

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Brain Tumor Classification and Segmentation Using Dual-Outputs for U-Net Architecture: O2U-Net

Brain Tumor Classification and Segmentation Using Dual-Outpu...

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21st International Conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2023

作者： Zargari, Seyed Aman Kia, Zahra Sadat Nickfarjam, Ali Mohammad Hieber, Daniel Holl, Felix Electrical Engineering Department Faculty of Electrical and Computer Engineering Semnan University Semnan Iran Department of Health Information Management and Technology School of Allied Medical Sciences Kashan University of Medical Science Kashan Iran Health Information Management Research Center Kashan University of Medical Science Kashan Iran Institute DigiHealth Neu-Ulm University of Applied Sciences Neu-Ulm Germany

ISBN: (纸本)9781643684000

We propose a modified version of the U-Net architecture for segmenting and classifying brain tumors, introducing another output between down- and up-sampling. Our proposed architecture utilizes two outputs, adding a classification output beside the segmentation output. The central idea is to use fully connected layers to classify each image before applying U-Net's up-sampling operations. This is achieved by utilizing the features extracted during the down-sampling procedure and combining them with fully connected layers for classification. Afterward, the segmented image is generated by U-Net's up-sampling process. Initial tests show competitive results against comparable models with 80.83%, 99.34%, and 77.39% for the dice coefficient, accuracy, and sensitivity, respectively. The tests were conducted on the well-established dataset from Nanfang Hospital, Guangzhou, China, and General Hospital, Tianjin Medical University, China, from 2005 to 2010 containing MRI images of 3064 brain tumors. © 2023 The authors and IOS Press.

关键词： Tumors

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Optimal Landing of Tilt-rotor Aircraft after Engine Failure Considering Pilot Inherent Limitations

Optimal Landing of Tilt-rotor Aircraft after Engine Failure ...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Yan, Xufei Chen, Renliang Zhu, Shiqiang Xie, Anhuan Gu, Jason Research Center for Intelligent Robotics Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China College of Aeronautics Nanjing University of Aeronautics and Astronautics National Key Laboratory of Science and Technology on Rotorcraft Aeromechanics Jiangsu Nanjing China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

An augmented longitudinal rigid-body model is developed with a set of algebra equations describing the controls in the cockpit and the differential equations describing the pilot inherent limitations. The landing procedure after one engine failure is formulated into a nonlinear optimal control problem. XV-15 tilt-rotor aircraft is taken as the sample for the demonstration of landing in one engine failure during short takeoff. The results show that the total power required, thrust coefficient, longitudinal flapping angle and optimal controls are more relatively gentle than the solutions without considering the pilot inherent limitations. Compared with the basic longitudinal rigid-body model, the optimal solutions involve more control information. © 2022 IEEE.

关键词： Differential equations

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Two-Stage High-Efficiency Encryption Key Update Scheme for LoRaWAN Based IoT Environment

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computers, Materials & Continua 2022年第10期73卷 547-562页

作者： Kun-Lin Tsai Li-Woei Chen Fang-Yie Leu Chuan-Tian Wu Department of Electrical Engineering Tunghai UniversityTaichung407Taiwan Research Center for Smart Sustainable Circular Economy Tunghai UniversityTaichung407Taiwan Department of Computer and Information Sciences Chinese Military AcademyKaohsiung830Taiwan Department of Computer Science Tunghai UniversityTaichung407Taiwan Emergency Response Management Center Industry-Academia Collaboration and University Extension DivisionMing-Chuan UniversityTaipei111Taiwan

Secure data communication is an essential requirement for an Internet of Things(IoT)*** in Industrial Internet of Things(IIoT)and Internet of Medical Things(IoMT)systems,when important data are hacked,it may induce property loss or life *** though many IoTrelated communication protocols are equipped with secure policies,they still have some security weaknesses in their IoT *** is one of the low power wide-area network protocols,and it adopts Advanced Encryption Standard(AES)to provide message integrity and ***,LoRaWAN’s encryption key update scheme can be further *** this paper,a Two-stage High-efficiency LoRaWAN encryption key Update Scheme(THUS for short)is proposed to update LoRaWAN’s root keys and session keys in a secure and efficient *** THUS consists of two stages,i.e.,the Root Key Update(RKU)stage and the Session Key Update(SKU)stage,and with different update frequencies,the RKU and SKU provide higher security level than the normal LoRaWAN specification does.A modified AES encryption/decryption process is also utilized in the THUS for enhancing the security of the *** security analyses demonstrate that the THUS not only protects important parameter during key update stages,but also satisfies confidentiality,integrity,and mutual ***,The THUS can further resist replay and eavesdropping attacks.

关键词： Key update AES LoRaWAN IoT security high efficiency

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Reactor Optimization Benchmark by Reinforcement Learning

arXiv

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arXiv 2024年

作者： Schwarcz, Deborah Schneider, Nadav Oren, Gal Steinitz, Uri Soreq Nuclear Research Center Israel Scientific Computing Center Nuclear Research Center Negev Israel Department of Electrical & Computer Engineering Ben-Gurion University Israel Department of Computer Science Technion - Israel Institute of Technology Israel

Neutronic calculations for reactors are a daunting task when using Monte Carlo (MC) methods. As high-performance computing has advanced, the simulation of a reactor is nowadays more readily done, but design and optimization with multiple parameters is still a computational challenge. MC transport simulations, coupled with machine learning techniques, offer promising avenues for enhancing the efficiency and effectiveness of nuclear reactor optimization. This paper introduces a novel benchmark problem within the OpenNeoMC framework designed specifically for reinforcement learning. The benchmark involves optimizing a unit cell of a research reactor with two varying parameters (fuel density and water spacing) to maximize neutron flux while maintaining reactor criticality. The test case features distinct local optima, representing different physical regimes, thus posing a challenge for learning algorithms. Through extensive simulations utilizing evolutionary and neuroevolutionary algorithms, we demonstrate the effectiveness of reinforcement learning in navigating complex optimization landscapes with strict constraints. Furthermore, we propose acceleration techniques within the OpenNeoMC framework, including model updating and cross-section usage by RAM utilization, to expedite simulation times. Our findings emphasize the importance of machine learning integration in reactor optimization and contribute to advancing methodologies for addressing intricate optimization challenges in nuclear engineering. The sources of this work are available at our GitHub repository: RLOpenNeoMC. © 2024, CC BY.

关键词： Reinforcement learning

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A Multi-task Transformer Architecture for Drone State Identification and Trajectory Prediction

A Multi-task Transformer Architecture for Drone State Identi...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Nicolas Souli Andreas Palamas Tania Panayiotou Panayiotis Kolios Georgios Ellinas Department of Electrical and Computer Engineering KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus Wiztech Group Limassol Cyprus Department of Computer Science KIOS Research and Innovation Center of Excellence University of Cyprus

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

With the proliferation of unmanned aerial vehicles in various applications ranging from delivery services to surveillance and rescue operations, an efficient drone state identification and trajectory prediction framework is becoming a mandate. This work introduces a novel multi-task learning framework that provides drone state identification and trajectory prediction enhancements with the use of a novel Transformer neural network architecture. The proposed system exploits the ability of Transformer models to handle sequential data, capturing more effectively than conventional models’ temporal dependencies and relations inherent to drone movement data. The proposed framework utilizes a dual-task learning approach, facilitating simultaneous prediction of drone state and trajectory and enhancing both tasks’ performance via shared feature learning. Extensive evaluations are conducted to validate the efficiency of the proposed framework, with two complementary datasets encompassing diverse drone movements and conditions. The results demonstrate significant improvement in terms of drone state identification and trajectory prediction performance compared to existing methods.

关键词： Neural networks computer architecture Transformers Multitasking Data models Trajectory Object recognition

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Experimental demonstration of a flexible-grid 1×(2×3)mode-and wavelength-selective switch using silicon microring resonators and counter-tapered couplers

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Chinese Optics Letters 2024年第1期22卷 52-58页

作者：孔德军鲁昊汪鹏君符强戴世勋陈伟伟王栎沣张波豪马凌霄李军戴庭舸杨建义 Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China College of Electrical and Electronic Engineering Wenzhou UniversityWenzhou 325035China College of Science and Technology Ningbo UniversityNingbo 315300China Laboratory of Infrared Materials and Devices The Research Institute of Advanced TechnologiesNingbo UniversityNingbo 315211China Department of Information Science and Electronics Engineering and Cyrus Tang Center for Sensor Materials and Applications Zhejiang UniversityHangzhou 310027China

A flexible-grid 1×(2×3)mode-and wavelength-selective switch which comprises counter-tapered couplers and silicon microring resonators has been proposed,optimized,and demonstrated experimentally in this *** carefully thermally tuning phase shifters and silicon microring resonators,mode and wavelength signals can be independently and flexibly conveyed to any one of the output ports,and different bandwidths can be generated as *** particle swarm optimization algorithm and finite difference time-domain method are employed to optimize structural parameters of the twomode(de)multiplexer and crossing *** bandwidth-tunable wavelength-selective optical router composed of12 microring resonators is studied by taking advantage of the transfer matrix *** results show that,for the fabricated module,cross talk less than-10.18 dB,an extinction ratio larger than 17.41 d B,an in-band ripple lower than0.79 dB,and a 3-dB bandwidth changing from 0.38 to 1.05 nm are obtained,as the wavelength-channel spacing is 0.40 *** corresponding response time is measured to be 13.64μs.

关键词： integrated optics optical waveguide mode-and wavelength-selective switch

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Unsupervised detection of Small Hyperreflective Features in Ultrahigh Resolution Optical Coherence Tomography

Unsupervised detection of Small Hyperreflective Features in ...

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Bildverarbeitung für die Medizin Workshop, BVM 2023

作者： Reimann, Marcel Won, Jungeun Takahashi, Hiroyuki Yaghy, Antonio Hwang, Yunchan Ploner, Stefan Lin, Junhong Girgis, Jessica Lam, Kenneth Chen, Siyu Waheed, Nadia K. Maier, Andreas Fujimoto, James G. Department of Electrical Engineering and Computer Science Research Laboratory of Electronics Massachusetts Institute of Technology United States Pattern Recognition Lab Friedrich-Alexander-Universität Erlangen-Nürnberg Germany New England Eye Center Tufts Medical Center United States

ISBN: (纸本)9783658416560

Recent advances in optical coherence tomography such as the development of high speed ultrahigh resolution scanners and corresponding signal processing techniques may reveal new potential biomarkers in retinal diseases. Newly visible features are, for example, small hyperreflective specks in age-related macular degeneration. Identifying these new markers is crucial to investigate potential association with disease progression and treatment outcomes. Therefore, it is necessary to reliably detect these features in 3D volumetric scans. Because manual labeling of entire volumes is infeasible a need for automatic detection arises. Labeled datasets are often not publicly available and there are usually large variations in scan protocols and scanner types. Thus, this work focuses on an unsupervised approach that is based on local peak-detection and random walker segmentation to detect small features on each B-scan of the volume. © 2023 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature.

关键词： Optical tomography

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FDAM: Filter-Dedicated Approximate Multiplier Design for Real-Time CNN Acceleration

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Nguyen, Kihwan Kim Xuan Truong Jeon, Dongsuk Lee, Hyuk-Jae Korea Republic of program Department of Electrical Engineering Seoul08826 Korea Republic of Inter-University Semiconductor Research Center Seoul National University Graduate School of Convergence Science and Technology Research Institute for Convergence Science Seoul08826 Korea Republic of Department of Electrical and Computer Engineering Seoul08826 Korea Republic of

Video super-resolution (VSR) is widely used in various high-definition applications, such as HDTVs and smartphones, requiring a dedicated upscaling technique for realtime full-HD generation. To reduce on-chip buffers for largesize output feature maps, a streaming VSR accelerator may employ an output stationary dataflow, leading to a large energy consumption caused by frequent filter switching. To mitigate this, we introduce a new filter-dedicated multiplier design for realtime VSR acceleration. We replace costly multipliers with adders, shifters, and multiplexers (MUXes), referred to as unified multiple constant multiplications (UMCM). The conventional UMCM, however, may incur considerable area/power overhead due to the unified topology constraint among different filter sets. To address this problem, we propose a new approximated MCM (AMCM) problem to relax the constraint and an approximate compatible graph synthesis (A-CGS) framework to efficiently solve AMCM by jointly searching for approximated filters and constructing a unified graph. Additionally, we suggest a lightweight finetuning method by freezing approximated filters and only finetuning biases, which can recover the original model’s accuracy within a few epochs. Experimental results with synthetic data demonstrate that AMCM reduces the area by up to 49.8%, 44.8%, and 40.3% when considering constant sets of 2, 4, and 8, respectively. Our designs with SR application achieve up to a 73.3% reduction in energy consumption. Experiments with the Set5 and Set14 datasets show that our model with bias correction achieves similar restoration performance compared to the eightbit models. © 1982-2012 IEEE.

关键词： Acceleration

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Optical polarized orthogonal matrix

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Photonics research 2025年第2期13卷 373-381页

作者： SHUJUN ZHENG JIAREN TAN XIANMIAO XU HONGJIE LIU YI YANG XIAO LIN XIAODI TAN Information Photonics Research Center College of Photonic and Electronic EngineeringFujian Normal UniversityFuzhou 350117China Department of Electrical and Computer Engineering Duke UniversityDurhamNorth Carolina 27708USA College of Photonic and Electronic Engineering Key Laboratory of Opto-Electronic Science and for Medicine of Ministry of EducationFujian Provincial Key Laboratory of Photonics TechnologyFujian Provincial Engineering Technology Research Center of Photoelectric Sensing ApplicationFujian Normal UniversityFuzhou 350117China

Multiplexing technology serves as an effective approach to increase both information storage and transmission ***,when exploring multiplexing methods across various dimensions,the polarization dimension encounters limitations stemming from the finite orthogonal *** that only two mutually orthogonal polarizations are identifiable on the basic Poincarésphere,this poses a hindrance to polarization *** overcome this challenge,we propose a construction method for the optical polarized orthogonal matrix(OPOM),which is not constrained by the number of orthogonal ***,we experimentally validate its application in high-dimensional multiplexing of polarization *** explore polarization holography technology,capable of recording amplitude,phase,and polarization,for the purpose of recording and selective reconstruction of polarization *** research reveals that,despite identical polarization states,multiple images can be independently manipulated within distinct polarization channels through orthogonal polarization combinations,owing to the orthogonal selectivity among information.

关键词： two mutually orthogonal polarizations optical polarized orthogonal matrix construction method multiplexing methods polarization dimension multiplexing orthogonal polarization combinations polarization holography

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