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100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Zhang, Jingyuan Tai, Ching-Lun Sivakumar, Raghupathy Blough, Douglas M. Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA United States

ISBN: (纸本)9798331517786

A low-complexity direction of arrival (DoA) estimation approach based on transmissive intelligent surfaces (TISs) is proposed for single-target scenarios. The proposed DoA estimator is composed of one TIS with pre-designed phase shifts and two receive antennas. The signal from the target transmits through the TIS before being captured by the two antennas, and the DoA of the target is estimated solely based on the ratio of power received at the two antennas. An optimization method is proposed to design the phase shifts of the TIS and the relative positions of the two antennas with two primary objectives: (1) enhancing DoA estimation accuracy, and (2) guaranteeing an analytical expression of the estimated DoA derived from the power ratio. To be specific, the power ratio is approximated using a limited number of Fourier series coefficients, so that the optimization problem is formulated as a small set of quadratic programming problems aimed at optimizing these Fourier series coefficients. Simulation results validate the effectiveness of the proposed TIS-based DoA estimator and the optimization method. The method demonstrates comparable or even lower root mean squared error (RMSE) of DoA estimation in comparison to classic approaches. Unlike classic approaches that rely on complex-valued received signals, the proposed method offers reduced hardware complexity, relying solely on power measurements. Additionally, it involves reduced computational complexity compared to classic approaches including the multiple signal classification (MUSIC) algorithm and the discrete Fourier transform (DFT)-based DoA estimation method. © 2024 IEEE.

关键词： Mean square error

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Enhancing Vehicle Routing with Time Windows: A Machine Learning-Driven Ant Colony Optimization Approach

Enhancing Vehicle Routing with Time Windows: A Machine Learn...

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2024 International Conference on Frontiers of Information technology, FIT 2024

作者： Tariq, Khizer Safdar, Ali Awais Zaman, Mubashir Shah, Syed Usman Ali School of Electrical Engineering and Computer Science National University of Sciences & Technology Islamabad Pakistan

ISBN: (纸本)9798331510503

The Vehicle Routing Problem with Time Windows (VRPTW) is a challenging optimization problem in logistics and transportation, where the objective is to efficiently plan routes for vehicles to service a set of customers within specified time windows while minimizing costs. This paper introduces a novel approach to solving VRPTW using a Machine Learning-Driven Ant Colony Optimization (ML-ACO) algorithm, referred to as Machine Learning-Driven Ant Colony Optimization for Vehicle Routing with Time Windows (ML-ACO-VRPTW). The proposed algorithm enhances traditional ACO by integrating a machine learning model, to predict heuristic values that capture the urgency of time windows and vehicle capacity constraints. The algorithm begins with initializing pheromone levels and parameters, followed by constructing routes based on probabilistic path selection influenced by pheromone intensity and machine learning-predicted heuristic values. Key innovations include dynamic pheromone updates that adapt to the algorithm’s progress and the incorporation of penalties for time window violations and vehicle capacity exceedances. The pheromones are used to maintain a memory of the paths, and the machine learning model ensures adaptive and accurate heuristic predictions. © 2024 IEEE.

关键词： Ant colony optimization

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Investigations and Time Estimation on Federated Learning for Future Internet of Vehicles

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IEEE Internet of Things Journal 2025年第11期12卷 17387-17398页

作者： Fukumoto, Shun Li, Ruidong Zeng, Kai Nan, Haihan Su, Zhou Kanazawa University Intelligent Computation and Network Laboratory Division of Electrical Information and Communication Engineering Kanazawa920-1192 Japan Kunming University of Science and Technology Faculty of Information Engineering Automation Kunming066000 China Kanazawa University Division of Electrical Information and Communication Engineering Kanazawa920-1192 Japan George Mason University Electrical and Computer Engineering Department FairfaxVA22030 United States Xi’an Jiaotong University School of Cyber Science and Engineering Xi’an710049 China

For future Internet of Vehicles (IoV), communications and computing will converge to provide services. Federated learning (FL), as one of the typical distributed computing technologies, needs to be integrated with IoV. For such integration, FL suffers from the straggler effect that the entire learning speed is lowered down, because of the existence of the devices, such as low-powered road side units and vehicles, taking more time to complete their tasks. Although the existing mechanisms reduce straggler effects by adopting asynchronous mechanisms and clustering mechanisms, they lack the detailed analysis of the reasons and the impacts of each cause, leading to inefficiencies in the design of algorithm. Additionally, most of the existing work only considered the impact of a single factor in computation, communication, or data distribution, which lacks comprehensive on research for causes of stragglers effects. The bottleneck is that it is laborious to observe the time delay precisely with the existing high-calculating evaluations. In this article, we elaborately explore the effects of computing power, communication capability, and data distributions on the straggler effects with carefully designing and conducting the extensive experiments. After investigations, we propose a novel learning completion time estimation formula for low computing capability devices with mini-batch stochastic gradient decent (SGD). We compare our proposed estimation formula with the one based on floating operation per second (FLOPs). Through the evaluations, our formula can demonstrate the improvement up to 72.4% at docker and 32.4% at Raspberry Pi device compared to the existing work. © 2014 IEEE.

关键词： Stochastic systems

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Smart Solar Forecasting: Machine Learning Approaches for Predicting Solar Power

Smart Solar Forecasting: Machine Learning Approaches for Pre...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Kumar, Madhav Borgohain, Santanu Panda, Kaibalya Prasad Thokchom, Surmila Panda, Gayadhar National Institute of Technology Department of Electrical Engineering Meghalaya India Pandit Deendayal Energy University Department of Electrical Engineering Gujarat Gandhinagar India National Institute of Technology Department of Computer Science and Engineering Meghalaya India Nitttr Department of Electrical Engineering Kolkata India

ISBN: (纸本)9798350350821

Solar energy is one of the most popular renewable energy sources in recent years. These solar systems not only reduce the need for electricity but also greatly improve the environment. Due to our excessive dependence on fossil fuels and their limited sources and the pollution caused by them, most people are turning to solar energy to power their homes and industries. It's critical to understand the location of the solar panel and the local weather since solar power efficiency is highly dependent on environmental factors. With the inherent unpredictability of photovoltaic power output, machine learning is a useful tool for predicting how weather conditions affect solar power plants, and there are various other viable prediction methods available. This research evaluates several meteorological characteristics for PV forecasting using numerous machine learning algorithms. Using the collected historical data set, a machine learning model is created. Necessary preprocessing techniques such as univariate and bivariate analysis are used. Machine learning algorithms benefit from data visualization as it makes it easier to understand features and create a robust classification model. Accuracy-related performance metrics such as MAE, MSE, and RMSE are used to compare the methods. We evaluate and contrast the various models' performances. This evaluation approach helps to choose the algorithm that best suits the task at hand. © 2024 IEEE.

关键词： Mean square error

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Review of power electronics converters and associated components/systems at cryogenic temperatures

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International Journal of Powertrains 2022年第2-3期11卷 243-263页

作者： Ul-Hassan, Mustafeez Azadeh, Yalda Emon, Asif Imran Luo, Fang Department of Electrical and Computer Engineering Stony Brook University New York United States Department of Electrical Engineering University of Engineering and Technology Lahore Pakistan

Increasing trends towards electrified transportation and future deep space missions target extremely low environmental operating temperatures of aircraft and spacecraft. For such applications, advantages associated with low temperature operation of power electronics converters, superconducting machines, energy storage devices, and current leads can significantly help improve the efficiency and density of integrated power conversion systems. Power electronics converters, being an integral part of such a conversion system, offer reduced losses, better switching speeds, and lesser size and weight. Similarly, superconducting machines are lighter and are more efficient at such temperatures. Owing to the improved performance of cryogenic power conversion systems compared to room temperature (RT) operation, a detailed review of low operating temperature power electronics converters and their constituent components including semiconductor devices, passive components, and superconducting machines is presented in this paper. © 2022 Inderscience Enterprises Ltd.

关键词： Temperature

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Prescribed-Time Nash Equilibrium Seeking for Pursuit-Evasion Game

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1518-1520页

作者： Lei Xue Jianfeng Ye Yongbao Wu Jian Liu D.C.Wunsch Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationNanjing 210096 School of Automation Southeast UniversityNanjing 210096China Department of Electrical and Computer Engineering Missouri University of Science and TechnologyRollaMO 65409 USA IEEE

Dear Editor,This letter is concerned with prescribed-time Nash equilibrium(PTNE)seeking problem in a pursuit-evasion game(PEG)involving agents with second-order *** order to achieve the prior-given and user-defined convergence time for the PEG,a PTNE seeking algorithm has been developed to facilitate collaboration among multiple pursuers for capturing the evader without the need for any global ***,it is theoretically proved that the prescribedtime convergence of the designed algorithm for achieving Nash equilibrium of ***,the effectiveness of the PTNE method was validated by numerical simulation results.A PEG consists of two groups of agents:evaders and *** pursuers aim to capture the evaders through cooperative efforts,while the evaders strive to evade *** is a classic noncooperative *** has attracted plenty of attention due to its wide application scenarios,such as smart grids[1],formation control[2],[3],and spacecraft rendezvous[4].It is noteworthy that most previous research on seeking the Nash equilibrium of the game,where no agent has an incentive to change its actions,has focused on asymptotic and exponential convergence[5]-[7].

关键词： seeking prescribed convergence

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A FSS Inverse Design Method Based on Output Space Mapping Enhanced ECM

A FSS Inverse Design Method Based on Output Space Mapping En...

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2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Tian, Ziheng Zhang, Juntao Kuang, Yu Cheng, Qingsha S. Southern University of Science and Technology Department of Electrical and Electronic Engineering Shenzhen China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore

ISBN: (纸本)9798350355581

This paper proposes an inverse design method for frequency selective surfaces (FSS) based on an equivalent circuit model (ECM) and output space mapping (OSM) technique. The method establishes an OSM enhanced ECM model (forward model) to replace expensive electromagnetic (EM) simulations for FSS shielding effectiveness (SE) evaluation. Furthermore, an inverse model is proposed to predict FSS unit cell structure parameter values using specification-driven feature point sampling method. Experiment results demonstrate that FSS designs with shielding frequency between 2-18GHz can be efficiently predicted and verified by EM simulation. © 2024 IEEE.

关键词： Frequency selective surfaces

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Design of a High Voltage Common Mode Resilient FlexRay Receiver in 180nm/5V CMOS Process 6

Design of a High Voltage Common Mode Resilient FlexRay Recei...

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6th Iranian International Conference on Microelectronics, IICM 2024

作者： Mansoury, Hamid Sadat Saeedi, Saeed Atarodi, Mojtaba Sharif University of Technology Dept. of Electrical Engineering Tehran Iran Tarbiat Modares University Dept. of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798331511371

A FlexRay receiver that is capable of operating within [-60V, 60V] common mode range using a common mode cancellation method is presented in this paper. The receiver uses 5V MOSFET transistors and incorporates a digital block to reduce the required number of comparators to 2, potentially leading to lower power consumption and die area. Extensive simulations have been conducted to ensure the receiver's functionality within a temperature range of [-40°C, 150°C], which is particularly crucial for automotive applications. Furthermore, corner and mismatch simulations have been performed to ensure the circuit's process tolerance and suitability for mass production. Additionally, Electromagnetic Immunity simulations have been performed to ensure that the receiver, intended for automotive applications, meets the necessary standards. The layout of the receiver occupies an area of 153.6 × 128.7 μm2.. © 2024 IEEE.

关键词： CMOS integrated circuits

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An 840 V-to-120 V Radiation-Tolerant Flying Capacitor Multilevel Converter for Space Robotics

An 840 V-to-120 V Radiation-Tolerant Flying Capacitor Multil...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Krause, Elisa Coday, Samantha Horowitz, Logan Pilawa-Podgurski, Robert C.N. University of California Department of Electrical Engineering and Computer Sciences BerkeleyCA United States Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science CambridgeMA United States

ISBN: (纸本)9798350376067

High-performance, high conversion ratio power electronics are necessary to enable robotics in future space exploration. This work utilizes the flying capacitor multilevel topology to build a lightweight, efficient converter for these applications. The design is optimized to minimize the mass of the passive components, and a stacked printed circuit board layout is used to further reduce the size. Radiation-tolerant part equivalents are utilized to emulate the performance of a space-rated prototype, and GaN HEMTs are used to further improve the converter's resiliency towards radiation effects. The design approach is verified through an 840 V, 600 W, 8-level FCML hardware prototype. The design achieves a peak efficiency of 95.4% and a power density of 4.92 kW/kg. © 2024 IEEE.

关键词： Gallium nitride

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Enhancing Human-in-the-Loop Learning for Binary Sentiment Word Classification 63

Enhancing Human-in-the-Loop Learning for Binary Sentiment Wo...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Martin-Urcelay, Belen Rozell, Christopher J. Bloch, Matthieu R. Georgia Institute of Technology Department of Electrical and Computer Engineering AtlantaGA United States

ISBN: (纸本)9798350316339

While humans intuitively excel at classifying words according to their connotation, transcribing this innate skill into algorithms remains challenging. We present a human-guided methodology to learn binary word sentiment classifiers from fewer interactions with humans. We introduce a human perception model that relates the perceived sentiment of a word to the distance between the word and the unknown classifier. Our model informs the design of queries that capture more nuanced information than traditional queries solely requesting labels. Together with active learning strategies, our approach reduces human effort without sacrificing learning fidelity. We validate our method through experiments with human data, demonstrating improved accuracy in binary sentiment word classification. © 2024 IEEE.

关键词： Contrastive Learning

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