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16th International Conference on Advanced Technologies, Systems and Services in Telecommunications, TELSIKS 2023

作者： Delmonte, Nicolo Silvestri, Lorenzo Masoumabad, Mehdi Alipour Perregrini, Luca Bozzi, Maurizio University of Pavia Department of Electrical Computer and Biomedical Engineering Pavia27100 Italy

ISBN: (纸本)9798350347029

This paper presents an overview of the recent advances we made in the field of microwave sensors. Sensors for different physical quantities are presented, ranging from structures for the retrieval of the electric and magnetic characteristics of materials, to devices for the determination of position and angular rotation. These sensors are based on various fabrication technologies, including planar structures, additive manufacturing, and hybrid solutions, which take advantage of the best features of different technologies. © 2023 IEEE.

关键词： 3D printing

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A ShuffleNet Architecture-Based Multi-Layer Feature Scaling and Fusion Approach for Underwater Net Cage Damage Detection in Aquaculture

A ShuffleNet Architecture-Based Multi-Layer Feature Scaling ...

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2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Huang, Xiang-Rui Chen, Yi-Cheng Chen, Liang-Bi Hu, Wu-Chih National Penghu University of Science and Technology Master Program in Electrical Engineering and Computer Science Department of Electrical Engineering Penghu Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

ISBN: (纸本)9798331530839

In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consuming and complex. To overcome this problem, this paper proposes a computer vision solution for identifying damage in underwater net cages to address the inefficiencies and challenges of traditional manual inspections. The proposed scheme utilizes a high-performance multi-branch computational architecture designed based on ShuffleNet architecture to detect net cage damage more efficiently. Experimental results demonstrate that this work performs well on the ImageNet ILSVRC-2010 dataset and achieves an accuracy of 88.54% in underwater net damage detection. © 2024 IEEE.

关键词： Aquaculture

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Granger Causality Pattern Learning Equipped with Noise Invalidation Soft Thresholding 31

Granger Causality Pattern Learning Equipped with Noise Inval...

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31st European Signal Processing Conference, EUSIPCO 2023

作者： Bayati, Khashayar Umapathy, Karthikeyan Beheshti, Soosan Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto Canada

ISBN: (纸本)9789464593600

This paper concentrates on pattern learning of Granger causality. In this context, the entities of the Granger causality matrix estimation derived from the state-space model indicate directional dependencies of the observations. Existing methods propose different forms of thresholding to eliminate insignificant entities from this matrix. These approaches do not exploit the difference in statistical characteristics of insignificant entities compared to the Granger causality itself. In this work, Noise Invalidation Soft Thresholding is chosen as the thresholding method to discard null relations in the Granger causality matrix pattern learning. Unlike existing approaches, the proposed method benefits from the statistical properties of insignificant entities. The simulation results demonstrate the advantages and superiority of the proposed method in the sense of accuracy and robustness for both randomly generated datasets with causal footprints as well as simulated electroencephalogram datasets. © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Statistical tests

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Design of a Compact 2-by-2 Horn Slot Antenna Array Fed by Printed Ridge Gap Waveguide

Design of a Compact 2-by-2 Horn Slot Antenna Array Fed by Pr...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Taraji, Mahboubeh Antoniades, Marco A. Toronto Metropolitan University Department of Electrical Computer and Biomedical Engineering TorontoON Canada

ISBN: (纸本)9781665442282

This paper presents a 2-by-2 horn slot antenna array at X-band. Metamaterial concepts are applied to the antenna design using printed ridge gap waveguide (PRGW) technology as a magnetic ground for the antenna array, which is excited by a 1-to-4 power divider. Each of the array power-divider branches excites a slot, while maintaining the impedance bandwidth of the original unloaded power divider. Directive horn antennas are used to control sidelobe levels and increase the gain. Simulation results demonstrate an impedance bandwidth of 23% and a gain of 12.7 dBi at 10 GHz, which is a significant improvement compared to an impedance bandwidth of less than 14% and a gain of 9.7 dBi for the antenna array without the horns. © 2023 IEEE.

关键词： Antenna arrays

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A soft,high-density neuroelectronic array

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npj Flexible Electronics 2023年第1期7卷 131-138页

作者： Kyung Jin Seo Mackenna Hill Jaehyeon Ryu Chia-Han Chiang Iakov Rachinskiy Yi Qiang Dongyeol Jang Michael Trumpis Charles Wang Jonathan Viventi Hui Fang Thayer School of Engineering Dartmouth CollegeHanoverNH 03755USA Department of Biomedical Engineering Duke UniversityDurhamNC 27708USA Department of Electrical and Computer Engineering Northeastern UniversityBostonMA 02115USA

Techniques to study brain activities have evolved dramatically,yet tremendous challenges remain in acquiring high-throughput electrophysiological recordings minimally ***,we develop an integrated neuroelectronic array that is filamentary,highdensity and ***,with a design of single-transistor multiplexing and current sensing,the total 256 neuroelectrodes achieve only a 2.3×0.3mm^(2)area,unprecedentedly on a flexible substrate.A single-transistor multiplexing acquisition circuit further reduces noise from the electrodes,decreases the footprint of each pixel,and potentially increases the device’s *** filamentary neuroelectronic array also integrates with a rollable contact pad design,allowing the device to be injected through a syringe,enabling potential minimally invasive array *** acute auditory experiments in rats validate the ability of the array to record neural signals with high tone decoding ***,these results establish soft,high-density neuroelectronic arrays as promising devices for neuroscience research and clinical applications.

关键词： electronic high Together

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A 3.97 μW 11.2b 500 kS/s Hybrid SAR ADC via Time-Mode Signal Processing 66

A 3.97 μW 11.2b 500 kS/s Hybrid SAR ADC via Time-Mode Signa...

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2023 IEEE 66th International Midwest Symposium on Circuits and Systems, MWSCAS 2023

作者： Perczak, Ian Yuan, Fei Toronto Metropolitan University Department of Electrical Computer and Biomedical Engineering TorontoON Canada

ISBN: (纸本)9798350302103

This paper presents a 12b hybrid ADC consisting of a 8b successive approximation register (SAR) analog-to-digital converter (ADC) with top-plate sampling, a variable-slope voltage-to-time converter with built-in absolute-value function, and a 3-stage cyclic gated Vernier TDC. The proposed ADC features the ability to accommodate a large input without sacrificing linearity, low power consumption, and technology compatibility. A number of techniques are proposed to improve performance and power efficiency of the ADC. These techniques include a sub-threshold delay-locked loop with pulsed control signals for clock generation, clock kickback reduction to minimize kickback and mismatch induced sensitivity loss of the comparator of the SAR ADC, a gated cyclic Vernier TDC to minimize the resolution loss caused by the improper injection of time inputs and a virtually unlimited dynamic range, a self-resetting arbiter with zero metastability window to improve the resolution of Vernier TDC, and a significantly simplified synchronous SAR for a better power/area efficiency. The ADC is designed in a TSMC 130 nm 1.2 V CMOS technology with a reduced supply voltage of 0.8 V and analyzed using Spectre with BSIM3.3 device models. Simulation results show that at 500 kS/s, the ADC offers a SNDR of 69.04 dB and ENOB of 11.17 while consuming 3.70 μW, yielding a Walden FOM of 3.21 fJ/conv. © 2023 IEEE.

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A Multi-Scale Control Framework for Electric and Automated Buses in Intercity Lines 63

A Multi-Scale Control Framework for Electric and Automated B...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Graffione, S. Bracco, S. Pasquale, C. Sacone, S. Siri, S. Ferrara, A. University of Genova Department of Informatics Bioengineering Robotics and Systems Engineering Italy University of Genova Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture Italy University of Pavia Department of Electrical Computer and Biomedical Engineering Italy

ISBN: (纸本)9798350316339

This paper proposes a multi-scale control scheme aimed at controlling speed, dwell time, and charging time of electric and automated buses performing the transport service on lines where there are no reserved lanes. The proposed control scheme has two layers characterized by different control objectives, level of detail and time scales. The high-level controller periodically solves a multi-objective optimal control problem formalized to ensure an adequate transport service, while the low-level controller, being based on a more accurate description of the bus dynamics and energy consumption, seeks to follow the high-level control actions while taking into account the effective traffic conditions encountered on the line and the effective dynamic behaviour of the bus. The paper concludes with the application to a case study in order to demonstrate the effectiveness of the proposed control scheme. © 2024 IEEE.

关键词： Bus transportation

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Decentralized Federated Deep Learning Image Recognition Models 4

Decentralized Federated Deep Learning Image Recognition Mode...

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4th International Conference on Artificial Intelligence, Robotics and Control, AIRC 2023

作者： Kugan, Sharun Islam, Md Quyyum Ul Kashef, Rasha Toronto Metropolitan University Department of Electrical Computer Biomedical Engineering Toronto Canada

ISBN: (纸本)9798350348248

In the era of IoT, numerous frameworks and cutting-edge models have been introduced to enhance user experience and privacy and reduce the risk of data breaches. Over time, IoT device usage has grown tremendously, and a flood of data has been sent to servers for processing. Federated learning has been deployed for efficient decentralization while preserving privacy. Federated learning has been applied in various IoT-related applications such as image classification, object segmentation, object detection, and sensor analytics. Existing centralized image recognition models fall short of providing accurate image classification with acceptable processing time for real-time deployment while preserving privacy. In this paper, we designed two decentralized deep learning models using federated learning, the CNN-TFF and the VGG16-TFF. With around 250 training iterations, we achieved a high accuracy rate of up to 90% with a decrease in the loss value for the CIFAR-100 dataset using the VGG16-TFF model while maintaining data privacy using federated learning. © 2023 IEEE.

关键词： Image classification

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Compton Camera for 3D SPECT Imaging 15

Compton Camera for 3D SPECT Imaging

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15th SPIE Conference on Developments in X-Ray Tomography

作者： Liang, Yuxuan Li, Mengzhou Han, Shuo Yu, Hengyong Wang, Ge Department of Biomedical Engineering Rensselaer Polytechnic Institute 12180 United States Department of Electrical and Computer Engineering University of Massachusetts Lowell01854 United States

ISBN: (纸本)9781510679641

Single photon emission computed tomography (SPECT) is commonly used with radioiodine scintigraphy to evaluate patients with multiple diseases such as thyroid cancer. The clinical gamma camera for SPECT contains a mechanical collimator that greatly compromises dose efficiency and limits diagnostic performance. The Compton camera is emerging as a promising alternative for mapping the distribution of radio-pharmaceuticals in the thyroid, since the Compton camera does not require mechanical collimation and in principle does not reject gamma ray photons. In this study, a high-efficiency tomographic imaging system is designed with a Compton camera for thyroid cancer imaging. A Timepix3-based Compton camera is selected for collecting gamma photons emitted from an I-131 phantom, and the backprojection filtration algorithm is applied for image reconstruction. The results demonstrate the feasibility of the Compton camera for high efficiency SPECT imaging and also the limitations that need further efforts to address. © 2024 SPIE.

关键词： Single photon emission computed tomography

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Feedforward Regulation of Interneuronal Communication 63

Feedforward Regulation of Interneuronal Communication

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Gambrell, Oliver Vahdat, Zahra Singh, Abhyudai University of Delaware Department of Electrical and Computer Engineering NewarkDE19716 United States University of Delaware Biomedical Engineering Mathematical Sciences Center for Bioinformatics and Computational Biology Department of Electrical and Computer Engineering NewarkDE19716 United States

ISBN: (纸本)9798350316339

We formulate a mechanistic model capturing the dynamics of neurotransmitter release in a chemical synapse. The proposed modeling framework captures key aspects such as the random arrival of action potentials (AP) in the presynaptic (input) neuron, probabilistic docking and release of neurotransmitter-filled vesicles, and clearance of the released neurotransmitter from the synaptic cleft. Analysis of the model results in analytical expressions for the statistical moments of docked vesicle count and the number of neurotransmitters in the cleft as a function of model parameters, and the frequency of presynaptic APs. We next consider a postsynaptic (output) neuron that fires an AP based on integrating upstream neurotransmitter activity. Our results show the existence of an optimal presynaptic AP frequency that maximizes the probability of a postsynaptic AP firing. We extend these results to consider feedforward regulation where in addition to a direct excitatory synapse, the input neuron also impacts the output indirectly via an inhibitory interneuron, and identify parameter regimes where the feedforward neuronal networks result in band-pass filtering, i.e., the output neuron frequency is maximized at intermediate input neuron frequencies. © 2024 IEEE.

关键词： Feedforward neural networks

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