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IEEE Middle East and North Africa Communications Conference (MENACOMM)

作者： Brandon Camacho Muhammad Sana Ullah Electrical and Computer Engineering Department Florida Polytechnic University Lakeland USA

ISBN: (数字)9798331519957

ISBN: (纸本)9798331519964

This paper reviews different feature extraction and analysis methods for FECG signals. The FECG signals are very critical in monitoring the health of the fetuses; hence, most of the time, they are masked by maternal ECG and noise and introducing significant challenges during the analysis of the same signal. In this paper, several feature-extraction techniques are reviewed and compared. Techniques included, but were not limited to, time-domain, frequency-domain, and time-frequency domain methods such as PCA and ICA. We also review some newer approaches for machine learning, including deep learning methods that could be applied further to enhance the performance of signal separation and classification performance. Then, each method is tested on synthetic and realworld datasets, emphasizing computational efficiency and clinical applicability. By elaborating on the strengths and weaknesses of each approach, this paper summarize the results that give insight into optimum strategies to improve FECG signal processing for better diagnosis regarding fetal health.

关键词： Time-frequency analysis Technological innovation Source separation Reviews Noise Feature extraction Computational efficiency Time-domain analysis Monitoring Principal component analysis

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End-to-end Nanophotonic Inverse Design for Computational Imaging

End-to-end Nanophotonic Inverse Design for Computational Ima...

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2023 International Applied Computational Electromagnetics Society Symposium, ACES-Monterey 2023

作者： Lin, Zin Virginia Polytechnic Institute and State University Electrical Engineering Arlington Research Cente Bradley Department of Electrical and Computer Engineering 900 N Glebe Road ArlingtonVA22203 United States

We introduce end-to-end inverse design in which a nanophotonics frontend is optimized in conjunction with a computational-imaging backend to minimize reconstruction errors. We present several nanophotonics designs for... 详细信息

ISBN: (纸本)9781733509633

关键词： Nanophotonics

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Joint Trajectory Optimization for Redundant Manipulators with Constant Path Speed

Joint Trajectory Optimization for Redundant Manipulators wit...

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American Control Conference (ACC)

作者： Jonathan Fried Santiago Paternain Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

In this work, we present an approach to minimizing the time necessary for the end-effector of a redundant robot manipulator to traverse a given trajectory by optimizing the trajectory of its joints, under a number of restrictions. Each joint has limits in the ranges of position, velocity and acceleration, the latter making jerks in joint space undesirable. Furthermore, for the applications involved, the end-effector must traverse the path with high accuracy and at constant path velocity, i.e. the tip of the manipulator must cover equal distances in equal amounts of time. The proposed approach takes this nonlinear optimization problem that has two variables (path speed and joint trajectory) and solves it in two steps - First, we solve an inner subproblem that considers a fixed joint trajectory and maximizes path speed, for which we obtain a closed form solution that considers all joint velocity and acceleration restrictions. Moreover, we establish that the value of the inner subproblem is convex. Then, we solve an outer subproblem that takes a subgradient of the inner subproblem's value to update the trajectory with a Primal-Dual optimization method that considers all path accuracy and joint position restrictions. We show the efficacy of our proposed approach with simulations.

关键词： Accuracy Closed-form solutions Tracking Optimization methods Spraying End effectors Trajectory

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SINCHDrone Technology Demonstration UAV Hybrid Incorporating Power Regeneration Technologies & Weight Minimization

SINCHDrone Technology Demonstration UAV Hybrid Incorporating...

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2023 IEEE Conference on Technologies for Sustainability, SusTech 2023

作者： Kudebeh, Kyrie Baez, Jeff Austin, Liam Yu, Zhen Lo, Alton Dobbs, Steven K. Rico, Joseph California State Polytechnic University Pomona Electrical and Computer Engineering Department PomonaCA United States California State Polytechnic University Pomona Aerospace Engineering Department PomonaCA United States California State Polytechnic University Pomona Mechanical Engineering Department PomonaCA United States

ISBN: (纸本)9798350345483

In this paper, an in-flight power regeneration and structural battery integration approach were employed to increase the endurance, range, and therefore mission capability of a VTOL (Vertical Takeoff and Landing) fixed-wing UAV (Unmanned Aerial Vehicle) by a multidisciplinary student team in California State polytechnic University, Pomona. The average flight time for a UAV drone has a maximum flight time of 30 minutes, limiting the number of applications that can be used. Although military drones have flight time measured in hours, their cost, size, and complexity eliminate them from commercial use even after they may be retired from military use. Project BANSHEE's overarching goal is to increase the range and endurance of a UAV in a compact and economical manner. This is to be achieved by the integration of power generation and storage equipment into the load-bearing structure of the airframe. Doing so will decrease the parasitic weight from external components and extend the battery life of the craft, allowing for longer flight time. Modifications to currently available drones such as the Storm4 are being made in order to perform autonomous flight plans and in the future: return to home base when battery is low, exchange depleted battery with new one while maintaining power through induction charging. © 2023 IEEE.

关键词： Drones

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Random Policy Enables In-Context Reinforcement Learning within Trust Horizons

arXiv

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arXiv 2024年

作者： Chen, Weiqin Paternain, Santiago Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute

Pretrained foundation models (FMs) have exhibited extraordinary in-context learning performance, allowing zero-shot (or few-shot) generalization to new environments/tasks not encountered during the pretraining. In the case of reinforcement learning (RL), in-context RL (ICRL) emerges when pretraining FMs on decision-making problems in an autoregressive-supervised manner. Nevertheless, the current state-of-the-art ICRL algorithms, such as Algorithm Distillation, Decision Pretrained Transformer and Decision Importance Transformer, impose stringent requirements on the pretraining dataset concerning the behavior (source) policies, context information, and action labels, etc. Notably, these algorithms either demand optimal policies or require varying degrees of well-trained behavior policies for all pretraining environments. This significantly hinders the application of ICRL to real-world scenarios, where acquiring optimal or well-trained policies for a substantial volume of real-world training environments can be prohibitively expensive or even intractable. To overcome this challenge, we introduce a novel approach, termed State-Action Distillation (SAD), that allows to generate an effective pretraining dataset guided solely by random policies. In particular, SAD selects query states and corresponding action labels by distilling the outstanding state-action pairs from the entire state and action spaces by using random policies within a trust horizon, and then inherits the classical autoregressive-supervised mechanism during the pretraining. To the best of our knowledge, this is the first work that enables effective ICRL under (e.g., uniform) random policies and random contexts. We also establish the quantitative analysis of the trustworthiness as well as the performance guarantees of our SAD approach. Moreover, our empirical results across multiple popular ICRL benchmark environments demonstrate that, on average, SAD outperforms the best baseline by 236.3% in the offline

关键词： Reinforcement learning

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Design of a Low-Cost Vector Based Muometric Navigation System

Design of a Low-Cost Vector Based Muometric Navigation Syste...

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IEEE Southeastcon

作者： Maxx A. Lowy Muhammad Sana Ullah Department of Electrical and Computer Engineering Florida Polytechnic University Lakeland USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

This paper presents a low-cost vector based Muometric navigation system for precision location finding applications where GPS does not work. The proposed system obtains the amplitude information from a SiPM photodetector pulse using low-cost techniques. The system then obtains the location of the device using the data from a reference detector.

关键词： Scintillators Voltage measurement Mesons Navigation Microcontrollers Detectors Vectors Transistors Photonics Global Positioning System

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Strategic multi-task coordination over regular networks of robots with limited computation and communication capabilities 57

Strategic multi-task coordination over regular networks of r...

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57th Annual Conference on Information Sciences and Systems, CISS 2023

作者： Wei, Yi Vasconcelos, Marcos M. Virginia Polytechnic Institute State University Commonwealth Cyber Initiative The Bradley Department of Electrical and Computer Engineering ArlingtonVA22203 United States FAMU-FSU College of Engineering Florida State University Department of Electrical and Computer Engineering TallahasseeFL32306 United States

ISBN: (纸本)9781665451819

Coordination is a desirable feature in multiagent systems, allowing the execution of tasks that would be impossible by individual agents. We study coordination by a team of strategic agents choosing to undertake one of the multiple tasks. We adopt a stochastic framework where the agents decide between two distinct tasks whose difficulty is randomly distributed and partially observed. We show that a Nash equilibrium with a simple and intuitive linear structure exists for diffuse prior distributions on the task difficulties. Additionally, we show that the best response of any agent to an affine strategy profile can be nonlinear when the prior distribution is not diffuse. Finally, we state an algorithm that allows us to efficiently compute a data-driven Nash equilibrium within the class of affine policies. © 2023 IEEE.

关键词： Multi agent systems

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DC Terminal Impedance Modeling and Stability Analysis for VSG-Controlled Grid-Connected Inverter

DC Terminal Impedance Modeling and Stability Analysis for VS...

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2024 IEEE International Conference on DC Technologies and Systems, DCTS 2024

作者： Su, Xinyang Wang, Minghao Xue, Ying Chen, Junyu Shi, Wenzhuo Xu, Zhao The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Hong Kong The University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering China South China University of Technology School of Electric Power Engineering Guangzhou China

ISBN: (纸本)9798350379464

As a kind of grid-forming control method that can effectively provide virtual inertia for the power grid, the virtual synchronous generator (VSG) control has received increasing attention in recent years. However, the VSG control will extract energy from the DC side during a grid frequency drop, which brings a burden on the stability of the DC side of a VSG. To address this problem, this paper establishes a fully analytical small-signal model of the VSG DC terminal impedance, incorporating both the inertia mechanism and the DC side dynamics. The accuracy of the model is validated through comparison with the sweep frequency results of the simulation. Finally, the Nyquist criterion is employed to analyze the DC stability of the VSG, and the simulation results match well with the theoretical predictions. © 2024 IEEE.

关键词： Synchronous generators

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XMeta-OS: A Conceptual Framework for Unified Resource Management in Distributed Edge-Cloud Environments 3rd

XMeta-OS: A Conceptual Framework for Unified Resource Manag...

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3rd International Conference on Advances in Computing Research, ACR 2025

作者： Zacharioudakis, Eleftherios Kakoulli, Elena Evripidou, Salomi Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Pafos Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9783031876462

This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is possible. This approach offer a new GPU abstraction layer and dynamic edge-cloud allocation model that offer enhanced flexibility and resource utilization over existing systems like Kubernetes and OpenStack. By using likely sensitive data, the model applied cloud-pushed deployment model. XMeta-OS manages computer resources in real-time. Therefore, fulfilling high performance various needs. It allocates CPU and GPU in real-time to workloads requiring massive parallel processing, such as machine learning, scientific simulations, real-time data analytics, and transportation tasks. Fabrication in the laboratory of an edge-cloud environment can help to assess the scalability, fault tolerance and efficiency of the system. It showcases the overall architectural design of XMeta-OS. Changes to the kernel and security solutions for safe and effective distribution are suggested. This article presents the design of the XMeta-OS. The future of XMeta-OS entails usage and testing with which we see latency, energy, computation and other such measurements in labs. XMeta-OS is a solution to cost performance, emerging application, large-scale edge-cloud deployments, and distributed GPU-enabled infrastructures. Meta-Operating System in Edge-Cloud Continuum for dynamic resource management of GPU. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cluster computing

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Stepless Frequency Regulation for Load-Independent Wireless Power Transfer with Time-Division Switched Capacitors 49

Stepless Frequency Regulation for Load-Independent Wireless ...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Wang, Hui Chau, K.T. Liu, Wei Tang, Yao Jiang, Chaoqiang Goetz, Stefan M. Duke University Department of Electrical and Computer Engineering Durham United States The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Hong Kong The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Hong Kong City University of Hong Kong Department of Electrical Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350331820

This paper proposes and implements a stepless frequency regulation method for wireless power transfer (WPT) with a simple LC compensation network to provide load-independent transmitter current. It should be mentioned that the capacitor in LC compensation network is controlled by a switch. Different from previous switched capacitor compensation networks, which can only select a limited number of resonant frequency points, this model can choose the resonant frequency arbitrarily in a wide frequency range. In theory, the frequency range can be controlled from a few kilohertz to hundreds of kilohertz. The key is controlling the turn-on time of the switch and adjusting the activation time length of the controlled capacitor in every WPT cycle. Therefore, the proposed system is very suitable for multi-frequency WPT, as the system can work at full resonance with practically arbitrary frequency. A Simulink simulation serves for verification, and the results prove the system can change the resonant frequency from 100 kHz to 300 kHz continuously while keeping the transmitter current load-independent. © 2023 IEEE.

关键词： Natural frequencies

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