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Ultrasonics Symposium (LAUS), IEEE UFFC Latin America

作者： Amauri Amorin Assef Ednilson de Souza Contieri Gilson Maekawa Kanashiro Michel Andrey Freitas Kohler Joaquim Miguel Maia Eduardo Tavares Costa Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) DAELT Federal University of Technology– Paraná (UTFPR) Curitiba Brazil Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) Federal University of Technology– Paraná (UTFPR) Curitiba Brazil Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) Federal University of Technology– Paraná (UTFPR) Federal Institute of Paraná (IFPR) Paranavaí Brazil Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) DAELN Federal University of Technology–Paraná (UTFPR) Curitiba Brazil DEEB-FEEC & CEB State University of Campinas (UNICAMP) Campinas Brazil

ISBN: (数字)9798350349085

ISBN: (纸本)9798350349092

Developing novel ultrasound methods for biomedical investigations typically requires costly instruments, which are not always available in research laboratories. This paper describes the implementation of a flexible computer-controlled FPGA-based pulser/receiver (P/R) system for ultrasound research. The system's main features are limited dimensions, the capability to generate complex waveforms using the Pulse Width Modulation (PWM) technique, and direct access to raw data. The proposed system was characterized in the first evaluation by measuring the central frequency and bandwidth of the output waveforms generated using a 5 MHz transducer. A 3-cycle 5 MHz sinusoidal excitation pulse with the Hanning window and a 5 µs chirp pulse from 3 to 7 MHz with the Tukey window were applied. Next, phantom experiments were performed using a 1.6 MHz transducer to measure the resolution of 15 targets with 1 mm diameter and 10 mm apart in the axial direction using the FWHM method. The results demonstrate that the P/R system can be used for medical ultrasound research and instrumentation, including piezoelectric transducer driver, high-intensity focused ultrasound (HIFU), non-destructive testing (NDT), and pulse waveform generator.

关键词： Ultrasonic imaging Ultrasonic variables measurement Chirp Instruments Piezoelectric transducers Pulse width modulation Biomedical measurement

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A Multistep Multivariate Fuzzy-Based Time-Series Forecasting on Internet of Things Data

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IEEE Internet of Things Journal 2025年第12期12卷 21679-21690页

作者： Bitencourt, Hugo Vinicius Lucas, Patrícia de Oliveira Orang, Omid Silva, Petrônio C. L. Guimarães, Frederico Gadelha Universidade Federal de Minas Gerais Graduate Program in Electrical Engineering Belo Horizonte31270-901 Brazil Federal Institute of Northern Minas Gerais Salinas39560-000 Brazil Universidade Federal de Minas Gerais Department of Computer Science Belo Horizonte31270-901 Brazil

Multistep ahead time series forecasting is essential in Internet of Things (IoT) applications in smart cities and smart homes to make accurate future predictions and precise decision making. Thus, this study introduces a novel multiple-input single-output (MISO) forecasting method called Multistep Embedding-based fuzzy time series (MS-EFTS), designed to predict high-dimensional nonstationary time series data. As a first-order approach, it employs a direct strategy that integrates an embedding transformation with a weighted multivariate FTS (WMVFTS) model. This combination allows for effective predictions over long-term horizons within low-dimensional, learned continuous representations. The effectiveness of the proposed MS-EFTS is assessed using three high-dimensional IoT time series in this investigation. The obtained results showcase the superior performance of the proposed method compared to some deep learning forecasting methods, including LSTM, BiLSTM, TCN, and CNN-LSTM, in terms of accuracy, parsimony, and efficiency. © 2014 IEEE.

关键词： Smart homes

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Nonreciprocal coupling in space-time modulated systems at exceptional points

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Physical Review B 2022年第10期105卷 L100304-L100304页

作者： Junfei Li Yun Jing Steven A. Cummer Department of Electrical and Computer Engineering Duke University Durham North Carolina 27708 USA Graduate Program in Acoustics The Pennsylvania State University University Park Pennsylvania 16802 USA

Exceptional points (EPs) are critical points in the parameter space of non-Hermitian systems, where two or more eigenvalues and eigenvectors simultaneously coalesce. The remarkable physics and behavior of waves at these EPs have raised considerable attention. Previous research has accessed EPs in parity-time (PT) symmetric systems through spatially modulated parameters. Using acoustics, this Letter demonstrates a different family of EPs in classical wave systems that emerge from coordinated modulation of mass density and loss/gain in time. This condition can create nonreciprocal coupling between arbitrary modes at the EPs, leading to exotic behaviors such as unilateral frequency conversion and linear amplification of waves that are unattainable at conventional time-invariant systems. Moreover, these phenomena can be attained with only loss, and acoustic gain via modal energy transfer is demonstrated in a loss-only system at such EPs. Our work marries time-varying systems with EPs, which could open new avenues for wave manipulation.

关键词： Classical mechanics Continuum mechanics Dynamical systems Hamiltonian systems Traveling waves

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Overview of Versatile Video Coding (H.266/VVC) and Its Coding Performance Analysis

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IEIE Transactions on Smart Processing and Computing 2023年第2期12卷 122-154页

作者： Lee, Minhun Song, HyeonJu Park, Jeeyoon Jeon, Byeungwoo Kang, Jungwon Kim, Jae-Gon Lee, Yung-Lyul Kang, Je-Won Sim, Donggyu Department of Computer Engineering Kwangwoon University Seoul Korea Republic of Department of Computer Engineering Sejong University Seoul Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Kyunggi-do Korea Republic of Communication and Media Research Laboratory Electronics and Telecommunications Research Institute Deajeon Korea Republic of School of Electronics and Information Engineering Korea Aerospace University Kyunggi-do Korea Republic of Department of Electronic and Electrical Engineering Graduate Program in Smart Factory Ewha Womans University Seoul Korea Republic of

Versatile Video Coding (H.266/VVC) is the newest video coding standard jointly developed by the Joint Video Experts Team (JVET), which is organized by the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG). H.266/VVC provides about 40% bitrate reduction compared with High Efficiency Video Coding (H.265/HEVC) for the same visual quality. This paper introduces in detail the core structure of H.266/VVC by highlighting its features within block partitioning structure, intra/inter prediction, transform, quantization, and in-loop filtering, compared to its predecessor (H.265/HEVC). H.266/VVC yields significantly improved the coding performance, but it increased the computational complexity, particularly for the encoder side, which remains a problem to be tackled for successful commercialization in the future. This paper examined the statistical performance of H.266/VVC coding tools from the bitstreams encoded by the VVC test model (VTM12.0) encoder through rate-distortion optimization under the JVET common test conditions. In addition, the complexity and performance analyses are conducted on the block partitioning structure and group of picture structure. It is expected that an optimized H.266/VVC encoder can be designed and developed by minimizing the coding loss based on the analysis data. © 2023 Institute of Electronics and Information Engineers. All rights reserved.

关键词： Image compression

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Design and implementation of a multifunctional FPGA-based system for intravascular ultrasound imaging and therapy

Design and implementation of a multifunctional FPGA-based sy...

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IEEE International Symposium on Applications of Ferroelectrics (ISAF)

作者： Amauri A. Assef Joaquim M. Maia Paula L S. De Moura Phuong Vu Adeoye Olomodosi Stephan Strassle Rojas Brooks D. Lindsey Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) DAELT Federal University of Technology - Parana (UTFPR) Curitiba Brazil Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) DAELN Federal University of Technology - Parana (UTFPR) Curitiba Brazil Graduate School of Electrical Engineering and Applied Computer Sciences (CPGEI) Federal University of Technology - Parana (UTFPR) Curitiba Brazil Department of Biomedical Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (数字)9798350371901

ISBN: (纸本)9798350371918

Coronary artery disease is a leading cause of death, with 17.8 million deaths globally. Intravascular ultrasound (IVUS) imaging is used to characterize coronary lesions and guide intervention in the cardiac catheterization lab. Separately, catheter-directed thrombolysis provides therapeutic ultrasound in an intravascular form factor to treat clots. In this paper, we propose to develop a flexible, multifunctional, FPGA-based pulser/receiver system for combined IVUS imaging and therapy. The novel system consists of a computer with a Matlab-based graphical user interface, an FPGA board and a custom proprietary board. An example therapy excitation is shown for a 1000-cycle, 550 kHz output waveform with an amplitude of 102 Vpp. This excitation was applied to a custom 3 mm therapy transducer, resulting in hydrophone-measured peak negative acoustic pressure of 305.28 kPa, a mechanical index of 0.41, I spta.3 of 5.64 mW/cm 2 and I sppa.3 of 310.36 mW/cm 2 . For imaging, the system can produce waveforms such as a 160 Vpp 1-cycle, 16.67 MHz sinusoidal pulse with a -6 dB bandwidth of 21 MHz. Thus, the developed system can be used to drive simultaneous IVUS imaging to assess the coronary environment and provide image-guided therapy of clots or plaques.

关键词： Ultrasonic imaging Transducers Imaging Medical treatment Pulse width modulation Universal Serial Bus Acoustics MATLAB Field programmable gate arrays Graphical user interfaces

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ConvNeXt Model for Breast Cancer Image Classification 6

ConvNeXt Model for Breast Cancer Image Classification

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6th International Conference on Cybernetics and Intelligent System, ICORIS 2024

作者： Setiawan, Devin Karnyoto, Andrea Stevens Intan, Indo Pardamean, Bens Department of Electrical Engineering and Computer Science University of Kansas Lawrence United States Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Informatics Engineering Universitas Dipa Makassar Makassar Indonesia Computer Science Department BINUS Graduate Program Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798331539603

Breast cancer is an occurrence of cancer that attacks breast tissue and is the most common cancer among women worldwide, affecting one in eight women. In this modern world, breast cancer image classification simplifies the process of analyzing, providing objective and accurate results. By leveraging machine learning algorithms and computer vision techniques, we developed breast cancer detection. The dataset is histopathology dataset from BreakHis and UNHAS Hospital. We chose the ConvNeXt-Tiny model then modified the classifier head as the proposed method. Before the dataset is processed by the model, we augment the images by applying random horizontal and vertical flips, adjustments to brightness, contrast, saturation, and hue using color jitter. The augmentation process simulates real-world variance and enhances the model's ability to generalize to unseen data. Our proposed model gained better performance (accuracy, F1-Score) results compared two other techniques to VGG16 and SVM. According to our experiments, the F1-Score for the ConvNeXt-Tiny model with classifier head modification is higher at 0.9516, than the gain for VGG16 at 0.9292, and the gain for the SVM at 0.83. © 2024 IEEE.

关键词： Lung cancer

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Aerodynamic Effects Compensation on Multi-Rotor UAVs Based on a Neural Network Control Allocation Approach

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 295-312页

作者： Sarah P.Madruga Augusto H.B.M.Tavares Saulo O.D.Luiz Tiago P.do Nascimento Antonio Marcus N.Lima Graduate Program of Electrical Engineering Universidade Federal de Campina GrandeCampina Grande-PBBrazil Department of Electrical Engineering Universidade Federal de Campina GrandeCampina Grande-PBBrazil IEEE Department of Computer Systems Universidade Federal da ParaibaJoao Pessoa-PBBrazil

This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural ***,the system performance can be improved by replacing the classic allocation matrix,without using the aerodynamic inflow equations *** network training is performed offline,which requires low computational *** target system is a Parrot MAMBO drone whose flight control is composed of PD-PID controllers followed by the proposed neural network control allocation *** a quadrotor is particularly susceptible to the aerodynamics effects of interest to this work,because of its small *** compared the mechanical torques commanded by the flight controller,i.e.,the control input,to those actually generated by the actuators and established at the *** was observed that the proposed neural network was able to closely match them,while the classic allocation matrix could not achieve *** allocation error was also determined in both ***,the closed-loop performance also improved with the use of the proposed neural network control allocation,as well as the quality of the thrust and torque signals,in which we perceived a much less noisy behavior.

关键词： Aerodynamics effects control allocation minidrone multi-rotor UAV neural networks

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A Comprehensive Technique Based on Machine Learning for Device and Circuit Modeling of Gate-All-Around Nanosheet Transistors

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 181-194页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering the Institute of Biomedical Engineering the Department of Electronics and Electrical Engineering the Institute of Pioneer Semiconductor Innovation and the Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

Machine learning (ML) is poised to play an important part in advancing the predicting capability in semiconductor device compact modeling domain. One major advantage of ML-based compact modeling is its ability to capture complex relationships and patterns in large datasets. Therefore, in this paper a novel design scheme based on dynamically adaptive neural network (DANN) is proposed to develop fast and accurate compact model (CM). This framework constitutes a powerful yet computationally efficient methodology and exhibits emergent dynamic behaviors. This paper demonstrates that the compact model based on ML can be designed to replicate the performance of conventional compact model for nanodevices. For this work, gate-all-around (GAA) nanosheet (NS) device characteristics are comprehensively analyzed for process variability sources using the proposed model. The device geometry parameters such as channel length, nanosheet width and nanosheet thickness are fed as input features to the DANN model. The adaptive neural network learns dynamically by updating weights of the model in accordance with the input features and achieves accurate neural weight convergence. The proposed model predicted the electrical characteristics of NS devices with less than 1% error rate. The model is also implemented and validated for the simulations of digital circuit designs such as inverter, and logic gates. ©;2023 The Authors.

关键词： Circuit simulation

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Trajectory Learning and Demonstration of a Robot Manipulator Based-on Sensor Fusion from a Hand-held Tool

Trajectory Learning and Demonstration of a Robot Manipulator...

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2024 International Automatic Control Conference, CACS 2024

作者： Song, Kai-Tai Ou, Szu-Chen National Yang Ming Chiao Yang Ming Chiao Tung University Institute of Electrical and Control Engineering College of Electrical and Computer Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Graduate Degree Program of Robotics Hsinchu300093 Taiwan

ISBN: (纸本)9798350354904

This paper presents a programming system for a robot manipulator using a hand-held demonstration tool. In this system, a user holds the self-designed tool to demonstrate a desired motion path, and the robot arm replicates the learned trajectory. The path-demonstration tool, including optical tags (OT) and an IMU, is designed to collect trajectory data from hand motion. Sensor data fusion allows the system to track accurately the demonstrated trajectory. A calibration procedure is proposed to transform the trajectory from tool's coordinate system to robot's coordinate system. A cubic spline-based trajectory planning method is proposed to ensure smooth reproduction of the learned trajectory in both time and space. Experimental results show that the robot is able to replicate squared and curved trajectories collected from the path-demonstration tool. The average position error is within 2.435 mm in XYZ directions and the average orientation error is within 0.65 degrees. © 2024 IEEE.

关键词： Demonstrations

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AI-driven Maintenance Tool for Synchronous Power Generator Temperature Monitoring Using Fiber Bragg Gratings

AI-driven Maintenance Tool for Synchronous Power Generator T...

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SBMO/IEEE MTT-S International Conference on Microwave and Optoelectronics (IMOC)

作者： Uilian José Dreyer Erlon V. da Silva Wilian Oliveira Paulo H. R. Mazzo Kleiton de M. Sousa André Biffe Di Renzo Cicero Martelli Jean Carlos Cardozo da Silva Graduate Program in Energy Systems (PPGSE) ENGlE Brasil Energia Universidade Tecnologica Federal do Parana-UTFPR Curitiba Parana Brazil Graduate Program in Electrical and Computer Engineering (CPGEI)

The carbon brushes and slip rings of a hydrogen-erator are the main components guiding the excitation current from the bridge to the rotor windings. The brushes' temperature are crucial to infer their operational condition and, the generator status. This work presents the temperature measurement of six Fiber Bragg Gratings (FBG) sensors installed in a 370 MVA electric generator brushes. The results show the sensors' capacity to monitor the brushes' temperature in accordance with the current flowing through them. Together with the sensors, an Artificial Intelligence (AI) technique was applied to the measured temperature to detect anomalous events regarding the current supplied to the rotor windings. The optical sensors combined with the AI could detect five events of abnormal current behaviour. One is presented in detail in this paper. This sensing system can be further applied to online fault detection using the temperature measured by the FBGs as a brush condition indicator and a generator operation and maintenance tool.

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