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7th International Conference on computer Vision and Image Processing, CVIP 2022

作者： Dell’Acqua, Fabio Marzi, David Department of Electrical Computer Biomedical Engineering University of Pavia Pavia Italy

ISBN: (纸本)9783031314063

Whereas a vast literature exists reporting on mapping of rice paddy fields in Asia based on spaceborne data, especially from radar sen¬sors, comparatively little has been done so far on the European context, where production is much smaller in absolute terms. From a scientific standpoint, it would be interesting to characterize rice paddy fields in terms of typical annual trend of radar response in a context where seasons follow different patterns with respect to the Asian one. In this manuscript we report a case study on a designated set of rice paddy fields in north-ern Italy, where the largest fraction of European rice paddy fields are located. Building on previous work, more in-depth analysis of the time trends of radar response is carried out, and some preliminary conclusions on features usable in mapping are presented. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Mapping

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Deep Semantic Segmentation of Echocardiographic Images using Vision Transformers

Deep Semantic Segmentation of Echocardiographic Images using...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Bosco, Edoardo Casula, Filippo Cotogni, Marco Cusano, Claudio Matrone, Giulia University of Pavia Department of Electrical Computer and Biomedical Engineering Pavia Italy

ISBN: (纸本)9798350346459

Deep learning (DL) methods have revolutionized image segmentation by providing tools to automatically identify structures within images, with high levels of accuracy. In particular, Convolutional Neural Networks (CNN), such as the U-Net and its variants, have achieved remarkable results in many segmentation tasks. Only recently, Vision Transformer (ViT)-based models have emerged and in some cases demonstrated to outperform CNNs in semantic segmentation tasks. However, transformers typically require larger amounts of data for training as compared to CNNs. This can result in a significant drawback given the time-consuming nature of collecting and annotating data, especially in a clinical setting. In particular, only a few studies involved the application of ViT networks for ultrasound image *** this study, we propose one of the earliest applications of ViT-based architectures for segmenting the left heart chambers in 2D echocardiographic images. Indeed, the identification of cardiac structures, like e.g. heart chambers, can be used to derive relevant quantitative parameters, such as atrial and ventricular volumes, the ejection fraction, *** trained and tested several ViT models using the publicly available CAMUS dataset, composed by cardiac image sequences from 500 patients, with the corresponding mask labels of the left ventricle and left atrium. ViT networks performances were then compared to an implementation of the U-Net. We demonstrate how, on this type of data, recent ViT variants can reach and even outperform CNNs, despite the limited data availability. © 2023 IEEE.

关键词： Echocardiography

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Using a 3D-Printed Waveguide Filter with Ridge Resonators as a Dielectric Permittivity Sensor

Using a 3D-Printed Waveguide Filter with Ridge Resonators as...

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2023 IEEE/MTT-S International Microwave Symposium, IMS 2023

作者： Romano, Francesco Delmonte, Nicolo Perregrini, Luca Bozzi, Maurizio University of Pavia Computer and Biomedical Engineering Department of Electrical Pavia Italy

ISBN: (纸本)9798350347647

This paper presents the use of a waveguide filter with ridge resonators that exhibits transmission zeros to implement a dielectric permittivity sensor. Thanks to its geometry, the electric field is intense under the ridge resonators, where the dielectric slab to be characterized is located. The operation principle is based on the evaluation of the frequency shift of transmission zeros, and exhibits high sensitivity and tolerance to vertical positioning errors. The designed sensor operates around the frequency of 10 GHz. The manufacturing process is based on the 3D printing with plastic material and the subsequent metallization. A set of commercial dielectric laminates have been adopted to validate the performance of the sensor. © 2023 IEEE.

关键词： 3D printing

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EventLFM:event camera integrated Fourier light field microscopy for ultrafast 3D imaging

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Light(Science & Applications) 2024年第7期13卷 1401-1415页

作者： Ruipeng Guo Qianwan Yang Andrew S.Chang Guorong Hu Joseph Greene Christopher V.Gabel Sixian You Lei Tian Department of Electrical and Computer Engineering Boston UniversityBostonMA 02215USA Department of Physiology and Biophysics Boston UniversityBostonMA 02215USA. Neurophotonics Center Boston UniversityBostonMA 02215USA. Research Laboratory of Electronics(RLE)in the Department of Electrical Science and Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA. Department of Biomedical Engineering Boston UniversityBostonMA 02215USA

Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological *** scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product(SBP).Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems,thus restricting data throughput to maintain high SBP at limited frame *** address this,we introduce EventLFM,a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy(LFM),a state-of-theart single-shot 3D wide-field imaging *** event camera operates on a novel asynchronous readout architecture,thereby bypassing the frame rate limitations inherent to conventional CMOS *** further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by *** results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame ***,we highlight EventLFM’s capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving *** believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.

关键词： field linking overcome

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Spectral Learning of Shared Dynamics Between Generalized-Linear Processes 38

Spectral Learning of Shared Dynamics Between Generalized-Lin...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Oganesian, Lucine L. Sani, Omid G. Shanechi, Maryam M. Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA United States Ming Hsieh Department of Electrical and Computer Engineering Thomas Lord Department of Computer Science Alfred E. Mann Department of Biomedical Engineering Neuroscience Graduate Program University of Southern California Los AngelesCA United States

Generalized-linear dynamical models (GLDMs) remain a widely-used framework within neuroscience for modeling time-series data, such as neural spiking activity or categorical decision outcomes. Whereas the standard usage of GLDMs is to model a single data source, certain applications require jointly modeling two generalized-linear time-series sources while also dissociating their shared and private dynamics. Most existing GLDM variants and their associated learning algorithms do not support this capability. Here we address this challenge by developing a multi-step analytical subspace identification algorithm for learning a GLDM that explicitly models shared vs. private dynamics within two generalized-linear time-series. In simulations, we demonstrate our algorithm's ability to dissociate and model the dynamics within two time-series sources while being agnostic to their respective observation distributions. In neural data, we consider two specific applications of our algorithm for modeling discrete population spiking activity with respect to a secondary time-series. In both synthetic and real data, GLDMs learned with our algorithm more accurately decoded one time-series from the other using lower-dimensional latent states, as compared to models identified using existing GLDM learning algorithms. © 2024 Neural information processing systems foundation. All rights reserved.

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Factors Affecting the Performance of FastICA Algorithm for Decomposition of High-Density Surface Electromyogram 9th

Factors Affecting the Performance of FastICA Algorithm for D...

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9th Latin American Congress on biomedical engineering, CLAIB 2022 and 28th Brazilian Congress on biomedical engineering, CBEB 2022

作者： Castilhos, Mateus Augusto Schneider Elias, Leonardo Abdala Department of Electronics and Biomedical Engineering School of Electrical and Computer Engineering University of Campinas SP Campinas Brazil Neural Engineering Research Laboratory Center for Biomedical Engineering University of Campinas SP Campinas Brazil

ISBN: (纸本)9783031494031

The motor unit (MU) physiology and the neural control of human movement can be studied via surface electromyogram (sEMG) decomposition techniques, which estimate the discharge times of MUs during a given contraction. The recent decomposition methods are based on the blind source separation (BSS) methods, and some approaches such as independent component analysis (ICA) can be applied to solve the problem. This study aims to investigate the influence of several parameters of the fast independent component analysis (FastICA) algorithm in the decomposition process of high-density sEMG. The extension factor, the number of iterations, and the method of initialization of the separation vector were explored for three evaluation metrics, namely, the execution time of decomposition, the absolute number of unique decomposed MUs, and the ratio of the number of unique MUs to the total number of extracted MUs. The number of iterations increased the execution time of decomposition and the absolute number of unique decomposed MUs. Besides, the method of initialization of the separation vector had little influence on the execution time of decomposition, an optimal value can be achieved for the absolute number of unique decomposed MUs. Moreover, the repeated convergence of the FastICA algorithm to the same source was mainly affected by the number of iterations. The study has reinforced the importance of evaluating the parameter combinations to achieve a better FastICA decomposition performance based on the chosen evaluation metric. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Blind source separation

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Controlling Biomolecular Timekeeping via Regulated Gene Product Degradation 63

Controlling Biomolecular Timekeeping via Regulated Gene Prod...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Rezaee, Sayeh Nieto, Cesar Singh, Abhyudai University of Delaware Department of Electrical and Computer Engineering NewarkDE United States University of Delaware Biomedical Engineering Mathematical Sciences Center of Bioinformatic and Computational Biology Department of Electrical and Computer Engineering NewarkDE United States

ISBN: (纸本)9798350316339

Numerous biological timing mechanisms are associated with the duration required for key regulatory molecules to reach critical threshold levels. Recent studies have mainly explored how random fluctuations affect the timing of events as molecules accumulate to reach a high threshold. This study examines the complementary scenario: decrease in protein levels until they reach a low critical threshold. We aim to study the timing precision resulting from different degradation pathways and their inherent stochastic nature, especially under low-copy number conditions. More specifically, we explore how integer-valued protein molecular counts decrease stochastically following Michaelis-Menten kinetics. This approach encompasses both zero-order (where the net degradation rate is independent of protein levels) and first-order (where the rate is proportional to protein levels) decay processes. Our results show that, while zero-order decay can be sluggish in terms of mean timing, it provides the highest precision in timing with the lowest noise in threshold-crossing time. Conversely, upon considering randomness in the initial protein levels, first-order decay demonstrates better precision compared to zero-order. Interestingly, in the presence of multiple noise sources, timing stochasticity can be minimized when Michaelis-Menten decay kinetics operate under sub-saturation conditions. This characterization of timing driven by decreasing copy numbers has implications for improving the precision of biological clocks and understanding the timing of cell-cycle events. © 2024 IEEE.

关键词： Stochastic systems

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Weak and Extremely Low Frequency Magnetic Fields Alter the Growth Rates of HT-1080 Fibrosarcoma

Weak and Extremely Low Frequency Magnetic Fields Alter the G...

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2025 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2025

作者： Dang, Nhat Keller, Jason Bajtos, Marek Gurhan, Hakki Barnes, Frank Department of Electrical Computer and Energy Engineering College of Engineering and Applied Science University of Colorado Boulder BoulderCO United States Department of Electromagnetics and Biomedical Engineering Faculty of Electrical Engineering and Information Technology University of Zilina Zilina Slovakia

ISBN: (纸本)9781946815200

This study presents experimental results showing that weak, extremely low frequency electromagnetic (EM) fields influence the growth rates of HT-1080 fibrosarcoma cells in vitro and offers a theoretical explanation for these effects. The results demonstrate that weak magnetic fields both increase and decrease the growth rates of fibrosarcoma cells by altering the mitochondrial superoxide (O2-) and calcium ions (Ca2+) concentrations in living cells. Over a 4-day exposure period, fibrosarcoma growth rates were modulated in the presence of low-level alternating current (AC) magnetic fields at a 10 μT amplitude at 13.5 Hz to 30 Hz frequency, superimposed on a 45 μT static background field. Effects due to changes in amplitude from 10 to 30 μT at selected frequencies are also investigated with the same superimposed static field. © 2025 USNC-URSI.

关键词： Electromagnetic field effects

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PWM-Based Hardware Authentication for Smart Inverters: Detecting Counterfeit Inverter through Transient Response Analysis

PWM-Based Hardware Authentication for Smart Inverters: Detec...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Hingu, Chanakya Fu, Xingang Mishan, Ramkrishna Kim, Taesic University of Nevada Reno Department of Electrical and Biomedical Engineering Reno United States University of Missouri-Columbia Department of Electrical Engineering and Computer Science Columbia United States

ISBN: (纸本)9798350376067

Amidst the growing complexity of inverter-based power systems, the security of smart inverters is becoming increasingly critical, particularly for protecting power electronics components from counterfeit threats. Typical methods of PCB hardware authentication utilize a signal injection to the PCB through a hardware interface such as JTAG, which might be impractical in smart inverters. This paper presents a cost-effective hardware authentication method using Pulse Width Modulation (PWM) and transient response to detect counterfeit solar inverters. By conducting a detailed analysis and comparing the transient responses from both inverters, this work reveals significant differences that can serve as analog signatures for authentication. The effectiveness of this validation method is demonstrated through an extensive statistical analysis, providing a solid basis for implementing this strategy as a safeguard against counterfeit penetration in power systems. Additionally, this method shows a potential tool for industry practitioners and researchers to verify, detect, and distinguish between counterfeit and genuine printed circuit boards, enhancing the security posture of power systems infrastructure. © 2024 IEEE.

关键词： Transient analysis

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RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

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2024 Prognostics and System Health Management Conference, PHM 2024

作者： Cai, Congrui Lu, Zhonghai School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Embedded Systems Master Program Sweden School of Electrical Engineering and Computer Science Department of Electrical Engineering KTH Royal Institute of Technology Sweden

ISBN: (纸本)9798350360585

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms. © 2024 IEEE.

关键词： Long short-term memory

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