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German Microwave Conference

作者： Andrej Lavrič Boštjan Batagelj Marco A. Antoniades Faculty of Electrical Engineering University of Ljubljana Slovenia Department of Electrical Computer & Biomedical Engineering Toronto Metropolitan University Canada

ISBN: (数字)9783982039749

ISBN: (纸本)9798331521790

A simple method for the design of a continuously tunable phase shifter based on a negative-refractive-index transmission line (NRI-TL) metamaterial without the need for variable inductors is presented. The employed λ/4 transformer solution consists of only three varactor diodes and three corresponding bias resistors, which greatly simplify the design and lower the cost of the phase-shifting stage. A single unit cell of the phase shifter prototype exhibits a total phase shift of 60° over 4V at 2.4GHz and a fractional bandwidth of 37% with insertion loss of only 0.5dB. Some of the drawbacks are also discussed.

关键词： Varactors Phased arrays Resistors Power transmission lines Prototypes Phase transformers Insertion loss Microwave theory and techniques Metamaterials Inductors

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New Hybrid IoT LoRaWAN/IRC Sensors:SMARTWater Metering System

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computers, Materials & Continua 2022年第6期71卷 5201-5217页

作者： Vlastimil Slany Petr Koudelka Eva Krcalova Jan Jobbagy Lukas Danys Rene Jaros Zdenek Slanina Michal Prauzek Radek Martinek Mendel University in Brno Faculty of AgrisciencesDepartment of AgriculturalFood and Environmental Engineering61300BrnoCzechia Slovak University of Agriculture in Nitra Faculty of EngineeringDepartment of Machines and Production Biosystems94976NitraSlovakia VSB-Technical University of Ostrava Faculty of Electrical Engineering and Computer ScienceDepartment of Cybernetics and Biomedical Engineering70800Ostrava-PorubaCzechia

The massive development of internet of things(IoT)technologies is gaining momentum across all areas of their possible deployment—spanning from Industry 4.0 to eHealth,smart city,agriculture or waste *** ongoing development is further pushed forward by the gradual deployment of 5G *** 5G capable smart devices,it will be possible to transfer more data with shorter latency thereby resulting in exciting new use cases such as Massive ***-IoT(low-power wide area network-LPWAN)enables improved network coverage,long device operational lifetime and a high density of *** all the advantages of massive-IoT technology,there are certain cases where the original concept cannot be *** them are dangerous explosive environments or issues caused by subsurface deployment(operation during winter months or dense greenery).This article presents the concept of a hybrid solution of IoT LoRaWAN(long range wide area network)/IRC-VLC(infrared communication,visible light communication)technology,which combines advantages of both technologies according to the deployment scenario.

关键词： IRC/VLC LoRaWAN LPWAN massive IoT smart metering

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Automated classification of renal tumors on ultrasound images using deep neural network 9

Automated classification of renal tumors on ultrasound image...

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9th International Conference on Intelligent Informatics and biomedical Sciences, ICIIBMS 2024

作者： Wu, Wei-Chieh Chiang, Te-Mei Tsai, Zhi-Ren Asia University Program in Artificial Intelligence College of Information and Electrical Engineering Taichung City Taiwan Asia University Hospital Department of Radiation Oncology Taichung City Taiwan Asia University Department of Computer Science & Information Engineering Taiwan

ISBN: (纸本)9798350363043

Kidney cancer is one of the most common cancers worldwide. The major types of malignant renal tumors are renal cell carcinoma and urothelial carcinoma. Although the majority of renal tumors are malignant, up to 20% are benign, most commonly renal cyst and angiomyolipomas. Ultrasound is the most accessible imaging tool in medical practice, but it highly depends on operator skill, which may lead to high false-negative rate in diagnosis. The purpose of this study was to develop a predictive model for the automated classification of renal tumors on ultrasound images using deep neural network. A total of 880 kidney ultrasound images were used for training and testing. Transfer learning was used to the ten Convolution neural network models. The kidney ultrasound images were classified as benign or malignant tumors. The classification performance of the model was evaluated by sensitivity and specificity. The research results show that VGG18 yielded the best performance, with a sensitivity of 79%, and a specificity of 86%. © 2024 IEEE.

关键词： Ultrasonic imaging

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The Effect of Vehicles Speed on the Performance of VANET Protocol 1

The Effect of Vehicles Speed on the Performance of VANET Pro...

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1st International Conference on Advanced engineering and Technologies, ICONNIC 2023

作者： Qasim, Osama A. Mahdi, Dania Mohammed Noori, Mohammed S. Ali, Rabei Raad Sari, Christy Atika Rachmawanto, Eko Hari Northern Technical University Department of Computer Engineering Technology Mosul Iraq Uniersiti Tenaga Nasional Department of Electrical and Electronics Engineering Selangor Malaysia University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia

ISBN: (纸本)9798350306484

At present, ad hoc networks are getting a lot of attention, because they have many features that differ from the rest of the networks and because they are technically advanced. In routing protocols, the Vehicular Ad-hoc network (VANET) differ in performance because each protocol has different variables, such as variable density, speed, and traffic scenarios. In this work, we proposed topology-based routing namely Ad hoc On Demand Distance Vector (AODV) protocol. The AODV protocol has been simulated in case of the movement of vehicles at a fixed velocity at 60km/h, and in case of randomly changing the vehicle's locations in the network. There are three parameters used to investigate the performance of the proposed AODV protocol which are packet delivery ratio, and overheads. The Simulation results show a significant decrease from 0.55 to 0.82 in the packet delivery ratio. On the other hand, the performance of the AODV protocol demonstrates effective communication for the VANETs. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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Time-Gated Circuit for SPAD-based OWC

Time-Gated Circuit for SPAD-based OWC

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2022 IEEE Photonics Conference, IPC 2022

作者： Liu, Junzhi Jiang, Wei Deen, M. Jamal McMaster University Department of Electrical and Computer Engineering HamiltonON Canada McMaster University School of Biomedical Engineering HamiltonON Canada

A Time-gated (TG) circuit is designed to generate a TG signal applied in SPAD-based optical wireless communication (OWC) system. The simulation results demonstrate that the signal can be used to eliminate inter-symbol... 详细信息

ISBN: (数字)9781665434874

ISBN: (纸本)9781665434874

关键词： Bit error rate

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High Speed Miniaturized Multiphoton Microscopy with Elliptical Beam Excitation

High Speed Miniaturized Multiphoton Microscopy with Elliptic...

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Optics and the Brain, BRAIN 2023 - Part of Optica Biophotonics Congress: Optics in the Life Sciences 2023

作者： Mattison, Ben Liu, Shing-Jiuan Tian, Feng Yang, Weijian Department of Biomedical Engineering University of California Davis DavisCA95616 United States Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Biomedical Engineering Graduate Group University of California Davis DavisCA95616 United States

We demonstrate elliptical beam shaping in a miniaturized two-photon microscope enabling cellular resolution fluorescence imaging at over three times faster frame rate than point scanning over a 400 µm diameter FO... 详细信息

ISBN: (纸本)9781957171210

关键词： Beam shaping CMOS cameras Cylindrical lenses Hollow core fibers Laser scanning Multiphoton microscopy

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A Realistic Surgical Simulator for Non-Rigid and Contact-Rich Manipulation in Surgeries with the da Vinci Research Kit

A Realistic Surgical Simulator for Non-Rigid and Contact-Ric...

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International Conference on Ubiquitous Robots (UR)

作者： Yafei Ou Sadra Zargarzadeh Paniz Sedighi Mahdi Tavakoli Department of Electrical and Computer Engineering University of Alberta Edmonton Alberta Canada Department of Electrical and Computer Engineering and the Department of Biomedical Engineering University of Alberta Edmonton Alberta Canada

ISBN: (数字)9798350361070

ISBN: (纸本)9798350361087

Realistic real-time surgical simulators play an increasingly important role in surgical robotics research, such as surgical robot learning and automation, and surgical skills assessment. Although there are a number of existing surgical simulators for research, they generally lack the ability to simulate the diverse types of objects and contact-rich manipulation tasks typically present in surgeries, such as tissue cutting and blood suction. In this work, we introduce CRESSim, a realistic surgical simulator based on PhysX 5 for the da Vinci Research Kit (dVRK) that enables simulating various contact-rich surgical tasks involving different surgical instruments, soft tissue, and body fluids. The real-world dVRK console and the master tool manipulator (MTM) robots are incorporated into the system to allow for teleoperation through virtual reality (VR). To showcase the advantages and potentials of the simulator, we present three examples of surgical tasks, including tissue grasping and deformation, blood suction, and tissue cutting. These tasks are performed using the simulated surgical instruments, including the large needle driver, suction irrigator, and curved scissor, through VR-based teleoperation.

关键词： Medical robotics Fluids Deformation Instruments Surgery Grasping Virtual reality

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Continuously Tunable Inductorless Phase Shifter Unit Cell Based on NRI-TL Metamaterial

Continuously Tunable Inductorless Phase Shifter Unit Cell Ba...

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16th German Microwave Conference, GeMiC 2025

作者： Lavric, Andrej Batagelj, Bostjan Antoniades, Marco A. University of Ljubljana Faculty of Electrical Engineering Slovenia Toronto Metropolitan University Department of Electrical Computer & Biomedical Engineering Canada

ISBN: (纸本)9783982039749

关键词： Metamaterials

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Development of an Adaptive Artifact Subspace Reconstruction Based on Hebbian/Anti-Hebbian Learning Networks for Enhancing BCI Performance

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IEEE Transactions on Neural Networks and Learning Systems 2024年第1期35卷 348-361页

作者： Tsai, Bo-Yu Diddi, Sandeep Vara Sankar Ko, Li-Wei Wang, Shuu-Jiun Chang, Chi-Yuan Jung, Tzyy-Ping Institute of Biomedical Engineering and the Brain Research Center National Yang Ming Chiao Tung University Hsinchu300 Taiwan Hsinchu300 Taiwan College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu300 Taiwan Institute of Electrical and Control Engineering Institute of Biomedical Engineering Brain Research Center College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Department of Electronics and Electrical Engineering Hsinchu300 Taiwan Kaohsiung Medical University Department of Biomedical Science and Environment Biology Drug Development and Value Creation Research Center Kaohsiung807 Taiwan Taipei Veterans General Hospital Taipei11217 Taiwan National Yang Ming Chiao Tung University Brain Research Center School of Medicine Taipei112 Taiwan University of California San Diego Swartz Center for Computational Neuroscience San DiegoCA92093 United States

Brain-computer interface (BCI) actively translates the brain signals into executable actions by establishing direct communication between the human brain and external devices. Recording brain activity through electroencephalography (EEG) is generally contaminated with both physiological and nonphysiological artifacts, which significantly hinders the BCI performance. Artifact subspace reconstruction (ASR) is a well-known statistical technique that automatically removes artifact components by determining the rejection threshold based on the initial reference EEG segment in multichannel EEG recordings. In real-world applications, the fixed threshold may limit the efficacy of the artifact correction, especially when the quality of the reference data is poor. This study proposes an adaptive online ASR technique by integrating the Hebbian/anti-Hebbian neural networks into the ASR algorithm, namely, principle subspace projection ASR (PSP-ASR) and principal subspace whitening ASR (PSW-ASR) that segmentwise self-organize the artifact subspace by updating the synaptic weights according to the Hebbian and anti-Hebbian learning rules. The effectiveness of the proposed algorithm is compared to the conventional ASR approaches on benchmark EEG dataset and three BCI frameworks, including steady-state visual evoked potential (SSVEP), rapid serial visual presentation (RSVP), and motor imagery (MI) by evaluating the root-mean-square error (RMSE), the signal-to-noise ratio (SNR), the Pearson correlation, and classification accuracy. The results demonstrated that the PSW-ASR algorithm effectively removed the EEG artifacts and retained the activity-specific brain signals compared to the PSP-ASR, standard ASR (Init-ASR), and moving-window ASR (MW-ASR) methods, thereby enhancing the SSVEP, RSVP, and MI BCI performances. Finally, our empirical results from the PSW-ASR algorithm suggested the choice of an aggressive cutoff range of c =1-10 for activity-specific BCI applications and a moderat

关键词： Electroencephalography

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Imaging the ex-vivo human cochlea using 1.3- μ m and 1.7- μ m optical coherence tomography

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Journal of biomedical Optics 2025年第4期30卷 046007页

作者： Tang, Jack C. Pan, Dorothy W. Oghalai, John S. Applegate, Brian E. University of Southern California Caruso Department of Otolaryngology-Head and Neck Surgery Los AngelesCA United States University of Southern California Alfred Mann Department of Biomedical Engineering Los AngelesCA United States University of Southern California Ming Hsieh Department of Electrical and Computer Engineering Los AngelesCA United States

Significance: There is no clinical imaging method to visualize the soft tissues of the human cochlea, which are crucial for sound transduction and are damaged in sensorineural hearing loss. Although optical coherence tomography (OCT) has been effective in small animal models, we show for the first time that it can image through the full thickness of the ex-vivo human otic capsule and resolve cochlear microstructures despite increased scattering. Aim: We aim to investigate whether OCT could image the cochlea through the otic capsule. We compared 1.7 and 1.3 μm OCT to test if the reduced scattering at 1.7 μm provided any appreciable advantage for imaging the cochleae. Approach: OCT interferometers were built for both 1.3 and 1.7 μm wavelengths, using identical sample and reference arm optics in both systems. Imaging was performed on two fixed human temporal bones with intact cochleae. The interferometers were designed to allow seamless switching between 1.3 and 1.7 μm OCT without disrupting the temporal bone during imaging. Results: We took volumetric OCT images at the base, apex, and hook regions of fixed ex-vivo human cochleae and compared the images taken at 1.3 μm with those taken at 1.7 μm. At both wavelengths, we could see through the otic capsule and identify cochlear structures. In some cases, 1.7 μm OCT resulted in clearer images of the lateral wall, interior scala, and fine cochlear structures due to reduced multiple scattering at depth compared with 1.3 μm. Conclusions: We conclude that both 1.7 μm and 1.3 μm OCT can image through the human otic capsule, offering the potential for direct measurement of cochlear vibrometry or blood flow in living humans. Using 1.7 μm light, we observed reduced multiple scattering in the otic capsule, leading to enhanced contrast of cochlear structures compared with 1.3 μm. However, these improvements were marginal and came with trade-offs. © 2025 SPIE. All rights reserved.

关键词： Multiple scattering

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