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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Sabouni, Ehsan Sabbir Ahmad, H.M. Giammarino, Vittorio Cassandras, Christos G. Paschalidis, Ioannis Ch. Li, Wenchao Boston University Division of Systems Engineering BostonMA02215 United States Boston University Department of Electrical and Computer Engineering The Division of Systems Engineering BostonMA02215 United States Boston University Department of Electrical and Computer Engineering Division of Systems Engineering Department of Biomedical Engineering BostonMA02215 United States

ISBN: (纸本)9798350316339

Optimal control methods provide solutions to safety-critical problems but easily become intractable. Control Barrier Functions (CBFs) have emerged as a popular technique that facilitates their solution by provably guaranteeing safety, through their forward invariance property, at the expense of some performance loss. This approach involves defining a performance objective alongside CBF-based safety constraints that must always be enforced with both performance and solution feasibility significantly impacted by two key factors: (i) the selection of the cost function and associated parameters, and (ii) the calibration of parameters within the CBF-based constraints, which capture the trade-off between performance and conservativeness. To address these challenges, we propose a Reinforcement Learning (RL)-based Receding Horizon Control (RHC) approach leveraging Model Predictive Control (MPC) with CBFs (MPC-CBF). In particular, we parameterize our controller and use bilevel optimization, where RL is used to learn the optimal parameters while MPC computes the optimal control input. We validate our method by applying it to the challenging automated merging control problem for Connected and Automated Vehicles (CAVs) at conflicting roadways. Results demonstrate improved performance and a significant reduction in the number of infeasible cases compared to traditional heuristic approaches used for tuning CBF-based controllers, showcasing the effectiveness of the proposed method. In order to guarantee reproducibility, our code is provided here: ***/EhsanSabouni/CDC2024_RL_adpative_MPC_CBF/tree/main © 2024 IEEE.

关键词： Adaptive control systems

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Automatic Voice Classification of Autistic Subjects 18th

Automatic Voice Classification of Autistic Subjects

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18th EAI International Conference on Body Area Networks, BODYNETS 2024

作者： Vacca, Jessica Brondino, Natascia Dell’Acqua, Fabio Vizziello, Anna Savazzi, Pietro Department of Electrical Computer Biomedical Engineering University of Pavia Pavia Italy Department of Brain and Behavioral Sciences University of Pavia Pavia Italy Department of Electrical Computer Biomedical Engineering University of Pavia & CNIT Consorzio Nazionale Interuniversitario per le Telecomunicazioni Pavia Italy

ISBN: (纸本)9783031725234

Autism Spectrum Disorders (ASD) describe a heterogeneous set of conditions classified as neurodevelopmental disorders. Although the mechanisms underlying ASD are not yet fully understood, more recent literature focused on multiple genetics and/or environmental risk factors. Heterogeneity of symptoms, especially in milder forms of this condition, could be a challenge for the clinician. In this work, an automatic speech classification algorithm is proposed to characterize the prosodic elements that best distinguish autism, to support the traditional diagnosis. The performance of the proposed algorithm is evaluted by testing the classification algorithms on a dataset composed of recorded speeches, collected among both autustic and non autistic subjects. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Diseases

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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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Towards Secure and Resilient Synchrophasor Networks Using P4 Programmable Switches

Towards Secure and Resilient Synchrophasor Networks Using P4...

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2024 IEEE Green Technologies Conference, GreenTech 2024

作者： He, Zhiyao Qu, Yanfeng Chen, Gong Raj, Reuben Samson Lin, Hui Jin, Dong University of Arkansas Electrical Engineering and Computer Science FayettevilleAR United States Illinois Institute of Technology Computer Science ChicagoIL United States University of Rhode Island Electrical Computer and Biomedical Engineering KingstonRI United States

ISBN: (纸本)9798350308587

Phasor Measurement Units (PMUs) enable high-speed and high-precision power quality measurements, but their vulnerability to cyber-attacks poses substantial risks to the stability and reliability of power systems. This paper explores the application of programmable networks, specifically P4 switches, to enhance the cybersecurity of PMU systems. These switches can be programmed to enable the creation of custom forwarding and processing logic at the data plane level. We analyze PMU-specific attacks through attack trees, propose effective mitigation strategies using programmable switches, and present a case study demonstrating the recovery of missing synchrophasor data by implementing a matrix completion algorithm on the switch data plane. The recovery scheme is evaluated in a container-based P4 network emulator using real PMU data from a campus microgrid. For instance, in the 10% missing data scenario, the recovery scheme can achieve a mean absolute percentage error of 0.038% for voltage magnitude and a phase angle error discrepancy of around 0.08 degrees. © 2024 IEEE.

关键词： Phasor measurement units

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Unobstructive andsafe-to-wear watt-level wireless charger

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npj Flexible Electronics 2024年第1期8卷 117-131页

作者： Sangjun Kim Jonathan Wells Sarnab Bhattacharya Hamsi Nathan Jiaming He Isabella Tubilla Heeyong Huh Pooja Kakani Ali Farshkaran Praveenkum Pasupathy Jianshi Zhou Emily Porter Nathan Lazarus Nanshu Lu Department of Mechanical Engineering The University of Texas at AustinAustinTXUSA Department of Electrical and Computer Engineering The University of Texas at AustinAustinTXUSA Department of Biomedical Engineering The University of Texas at AustinAustinTXUSA Texas Materials Institute The University of Texas at AustinAustinTXUSA Department of Aerospace Engineering and Engineering Mechanics The University of Texas at AustinAustinTXUSA Department of Electrical and Computer Engineering University of DelawareNewarkDEUSA US Army Research Laboratory AdelphiMDUSA

A wearable microgrid that centralizes and distributes harvested energy across different body regions can optimize power utilization and reduce overall battery *** setup underscores the importance of developing cable-free wireless power transfer(WPT)systems for mobile and portable devices to eliminate the risks posed by wired connections,especially in dynamic and hazardous *** introduce a thin,stretchable,and safe hand band capable of watt-level wireless charging through the widely adopted Qi protocol operating at 130 *** implementation of nonadhesive fabric encapsulation serves to protect the 50-μm-thin spiral copper antenna from mechanical strain,ensuring an overall hand band stretchability of 50%.We also create a stretchable“Ferrofabric”,characterized by a magnetic permeability of 11.3 and a tensile modulus of 75.3 kPa,that provides magnetic shielding for the antenna without compromising ***“Ferrofabric”improves the coil inductance but induces core loss in AC *** fully understanding and managing loss mechanisms such as the skin effect,proximity effect,core loss,and joule heating,we achieve a wireless charging efficiency of71%andpower delivery of 3.81Win the kHz frequency *** band is unobstructive to hand motion and can charge a handheld smartphone as fast as a desktop charger or power a battery-free chest-laminated e-tattoo sensor,with well-managed thermal and electromagnetic *** a holistic electromagnetic,structural,and thermal design,our device culminates in a safe,rugged,and versatile solution for wearable WPT systems.

关键词： antenna charge wear

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Influence of parallel kinematic machine dimensional tolerances on the estimation of payload inertia

Influence of parallel kinematic machine dimensional toleranc...

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2023 International Conference on electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Farías, José Alfonso Sergenti, Carol Carnevale, Marco Giberti, Hermes Università di Pavia Dept. Electrical Computer and Biomedical Engineering Pavia Italy

ISBN: (纸本)9798350322972

Estimating the inertial parameters of a rigid body linked to the end effector of a parallel kinematic machine may be useful in many applications (e.g., set-up of control parameters, orientation estimation, inertial compensation). The quality of the estimation depends on different aspects such as the implemented method, the excitation movement trajectories and the disturbances of the input signals. The model inputs are generally the forces and torques at the interface between the end effector and the workpiece under estimation, commonly measured through a 6-axis load cell, and the related motion. However, when evaluating the imposed motion based on the motion of the actuators, rather than the most common adoption of an Inertial Measurement Unit for direct measurement, geometrical tolerances of the machine links are likely to affect the identification results, since they introduce uncertainty in the terms of the Jacobian *** paper studies the influence of the variability of the robot link lengths on the accuracy in the estimation of the inertial properties of the payload, when the end effector motion is evaluated based on the actuator motion and forward kinematics. It is found that, under a certain limit of geometrical tolerances, the error in the estimation of the center of gravity and inertia tensor can be contained to acceptable values, comparable to those achievable through direct measurement of the end effector *** a given geometrical error in the link lengths, the influence of the excitation trajectory (i.e. matrix conditioning number) on the identification error is also addressed. Finally, the analysis points out how much the accelerations used as input can differ from the real ones, which is useful information to size the sensitivity of the IMU sensor to be used when direct measurement is possible or required. © 2023 IEEE.

关键词： End effectors

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Making our Voices Heard: The Art of Machine Learning for Speech Classification

Making our Voices Heard: The Art of Machine Learning for Spe...

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2024 IEEE MIT Undergraduate Research Technology Conference, URTC 2024

作者： Wu, Janie Norceide, Flore Aoki, Emi Thompson, Charles Chandra, Kavitha University of Massachusetts Lowell Biomedical Engineering LowellMA United States University of Massachusetts Lowell Electrical and Computer Engineering LowellMA United States

ISBN: (纸本)9798331531003

Emerging voice activated technologies depend on fast and accurate classification of a coustic s ignals. R ecent advances in machine learning and application specific computational systems have enabled highly accurate classifiers when trained with a large amount of data. This research presents the performance of a convolutional neural network when trained with distinct feature sets and assesses the performance tradeoff in size and feature-selective training. The experiments are conducted using the Free Spoken Digit Dataset that includes spoken digits from six different speakers with different accents. The classification e fficiency of on e an d tw o la yer CN N's are reported using three different types of spectrograms. To encourage the participation of a student body in machine learning applications of acoustics, the essential features of the neural network are captured in digital art form to render a more accessible introduction to the topic. © 2024 IEEE.

关键词： Spectrographs

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Hybrid In-Vehicle Background Noise Reduction for Robust Speech Recognition:The Possibilities of Next Generation 5G Data Networks

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computers, Materials & Continua 2022年第6期71卷 4659-4676页

作者： Radek Martinek Jan Baros Rene Jaros Lukas Danys Jan Nedoma VSB-Technical University of Ostrava Faculty of Electrical Engineering and Computer ScienceDepartment of Cybernetics and Biomedical Engineering70800Ostrava-PorubaCzechia VSB Technical University of Ostrava Faculty of Electrical Engineering and Computer ScienceDepartment of Telecommunications70800Ostrava-PorubaCzechia

This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise *** vehicles are nowadays increasingly supporting voice commands,which are one of the pillars of autonomous and SMART *** speaker recognition for context-aware in-vehicle applications is limited to a certain extent by in-vehicle back-ground *** article presents the new concept of a hybrid system which is implemented as a virtual *** highly modular concept of the virtual car used in combination with real recordings of various driving scenarios enables effective testing of the investigated methods of in-vehicle background noise *** study also presents a unique concept of an adaptive system using intelligent clusters of distributed next generation 5G data networks,which allows the exchange of interference information and/or optimal hybrid algorithm settings between individual *** average,the unfiltered voice commands were successfully recognized in 29.34%of all scenarios,while the LMS reached up to 71.81%,and LMS-ICA hybrid improved the performance further to 73.03%.

关键词： 5G noise reduction hybrid algorithms speech recognition 5G data networks in-vehicle background noise

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Building a Brain computer Interface (BCI) Using Electroencephalogram (EEG) Signals' Classification 7

Building a Brain Computer Interface (BCI) Using Electroencep...

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7th International Conference on Advances in biomedical engineering, ICABME 2023

作者： Younis, Mohammad Nabil Sleiman, Sary Haj Khadra, Salma Zaylaa, Amira Daher, Alaa Ayache, Mohammad Beirut Arab University Biomedical Program Depatment of Electrical and Computer Engineering Debbieh Lebanon

ISBN: (纸本)9798350325850

Development of Brain computer Interface (BCI) has been rapid since the mid 1990's. There are three criteria for BCI, (i) comfortability and possession of a suitable signal acquisition device, (ii) system validation and dissemination, and (iii) reliability and potentiality. As there are no BCI possessing the optimal criteria, it was essential to consider building a new one. Thereby, the paper investigates building BCI based on the utilization of EEG signals to translate brainwave patterns into actionable commands. The primary objective is to enhance communication capabilities for individuals afflicted with neurological disorders, empowering them to command external devices and engage more effectively with their surroundings. We built our model on EEG online dataset for the purpose of feature extraction and classification. Statistical features and Discrete Wavelet Transform (DWT) have been applied for feature selection. Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) were the classifiers involved. Results showed that the proposed architecture of MLP and RBF were able to classify the EEG signals into two classes (open eye and closed eye). Results also showed that the proposed approach, which is based on the combination of statistical features and DWT for features selection using AF3 and AF4 channels by the application of MLP, has 98% succession rate. BCI system based on Arduino circuit has been built after the classification Further algorithms and system evaluation need to be considered as future work. © 2023 IEEE.

关键词： Discrete wavelet transforms

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In Search for Model-Driven eXplainable Artificial Intelligence 1

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10th IFIP International Workshop on Artificial Intelligence for Knowledge Management, AI4KMES 2023

作者： Ligęza, Antoni Sepiolo, Dominik Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Applied Computer Science AGH University of Krakow al. Mickiewicza 30 Krakow30-059 Poland

ISBN: (数字)9783031610691

ISBN: (纸本)9783031610684

This paper reports on ongoing and innovative research in the area of eXplainable Artificial Intelligence (XAI). A classical XAI task is considered as finding an explanation of the model generated via Machine Learning by identifying the most influential variables for local decision-making. Such an approach suffers from severe limitations. The proposed approach moves the explanatory process to a new, knowledge-level dimension. It is oriented towards Model Discovery, i.e. the internal structure and functions of the components. The concept of Model-Driven XAI is put forward and explained with examples. An experiment on Function Discovery via Grammatical Evolution is reported in brief. © IFIP International Federation for Information Processing 2024.

关键词： Decision making

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