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Understanding wide field-of-view flat lenses:an analytical solution[Invited]

Chinese Optics Letters 2023年第2期21卷 111-118页

作者：杨帆安森松 Mikhail Y.Shalaginov 张华亮胡崛隽古田 Department of Materials Science&Engineering Massachusetts Institute of TechnologyCambridgeMassachusetts 02139USA Department of Electrical&Computer Engineering University of Massachusetts LowellLowellMassachusetts 01854USA Materials Research Laboratory Massachusetts Institute of TechnologyCambridgeMassachusetts 02139USA

Wide field-of-view(FOV)optics are widely used in various imaging,display,and sensing *** wide FOV optics rely on complicated lens assembly comprising multiple elements to suppress coma and other Seidel *** emergence of flat optics exemplified by metasurfaces and diffractive optical elements(DOEs)offers a promising route to expand the FOV without escalating complexity of optical *** date,design of large FOV flat lenses has been relying upon iterative numerical ***,we derive,for the first time,to the best of our knowledge,an analytical solution to enable computationally efficient design of flat lenses with an ultra-wide FOV approaching 180°.This analytical theory further provides critical insights into working principles and otherwise non-intuitive design trade-offs of wide FOV optics.

关键词： metasurface metalens field-of-view

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Sailing Through Point Clouds: Safe Navigation Using Point Cloud Based Control Barrier Functions

arXiv

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arXiv 2024年

作者： Dai, Bolun Khorrambakht, Rooholla Krishnamurthy, Prashanth Khorrami, Farshad Control/Robotics Research Laboratory Electrical & Computer Engineering Department Tandon School of Engineering New York University BrooklynNY11201 United States

The capability to navigate safely in an unstructured environment is crucial when deploying robotic systems in real-world scenarios. Recently, control barrier function (CBF) based approaches have been highly effective in synthesizing safety-critical controllers. In this work, we propose a novel CBF-based local planner comprised of two components: Vessel and Mariner. The Vessel is a novel scaling factor based CBF formulation that synthesizes CBFs using only point cloud data. The Mariner is a CBF-based preview control framework that is used to mitigate getting stuck in spurious equilibria during navigation. To demonstrate the efficacy of our proposed approach, we first compare the proposed point cloud based CBF formulation with other point cloud based CBF formulations. Then, we demonstrate the performance of our proposed approach and its integration with global planners using experimental studies on the Unitree B1 and Unitree Go2 quadruped robots in various environments. © 2024, CC BY.

关键词： Robot programming

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Computing on Surface: A Multi-Task Multi-Access Offloading Scheme in Maritime Edge Networks

Computing on Surface: A Multi-Task Multi-Access Offloading S...

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2024 International Conference on Cloud and Network Computing, ICCNC 2024

作者： Dai, Minghui Dou, Chenglong Wu, Yuan Qian, Liping Lin, Bin Su, Zhou Shen, Xuemin Sherman University of Macau State Key Laboratory of Internet of Things for Smart City China Zhuhai UM Science and Technology Research Institute Zhuhai China Zhejiang University of Technology College of Information Engineering Hangzhou China Dalian Maritime University Department of Communication Engineering Dalian China Xi'An Jiaotong University School of Cyber Science and Engineering Xi'an China University of Waterloo Department of Electrical and Computer Engineering Waterloo Canada

ISBN: (纸本)9798350367805

The recent development of unmanned aerial vehicles (UAVs) technology has been envisioned as a promising paradigm to cater for the growing maritime activities. However, the increasing growth of marine services poses challenges for processing maritime data. In this paper, we propose a surface computing paradigm in maritime networks, in which multi-Task sensed by UAVs can be offloaded to multiple beacon stations. Multiple UAVs can process their workloads locally or offload to surface computing. Taking the system welfare and energy consumption into consideration, we present an optimization problem to determine the selection of beacon stations and the offloading decision, with the objective of maximizing the system welfare. We propose a hybrid auction and convex optimization approach to address the formulated problem. Finally, simulation results demonstrate the effectiveness of our proposed algorithms compared to several baselines. © 2024 IEEE.

关键词： Convex optimization

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Impact of Zoning Definition on electrical Heating Systems Flexibility Potential in Residential Buildings: A Quebec Case Study 5th

Impact of Zoning Definition on Electrical Heating Systems Fl...

引用

5th International Conference on Building Energy and Environment, COBEE 2022

作者： Hosseini, Sayed Saeed Vallianos, Charalampos Agbossou, Kodjo Athienitis, Andreas Delcroix, Benoit Henao, Nilson Rao, Jiwu Kelouwani, Sousso Department of Electrical and Computer Engineering Smart Energy Research and Innovation Laboratory Hydrogen Research Institute University of Quebec at Trois-Rivieres Trois-RivieresQC Canada Centre for Zero Energy Building Studies Department of Building Civil and Environmental Engineering Concordia University MontrealQC Canada Laboratoire des Technologies de l’Énergie Hydro-Quebec Research Institute ShawiniganQC Canada Department of Mechanical Engineering Smart Energy Research and Innovation Laboratory Hydrogen Research Institute University of Quebec at Trois-Rivieres Trois-RivieresQC Canada

ISBN: (纸本)9789811998218

This paper examines the impact of building zoning on demand flexibility potentials. The building thermal dynamic response is modeled by using the state-space representation method. The comfort preference of the occupants is defined by statistical analysis of set-point temperature patterns. The created models are used to study energy flexibility through a coordinated energy management problem by means of the Stackelberg game strategy. The zoning influence on flexibility potentials is analyzed by applying this procedure to a set of houses in Quebec based on two specific scenarios accounting for single and multi-zones. The flexibility potential is evaluated by comparing overall demand peak reduction and heating consumption under each scenario signifying passive heating storage capacity of buildings. The single-zone scenario performs better at harvesting energy flexibility through reducing the peak load by 33%. The results demonstrate that the building zoning definition can lead to conditions under which the demand flexibility can change. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Buildings

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Reconfigurable Distributed FPGA Cluster Design for Deep Learning Accelerators

arXiv

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arXiv 2023年

作者： Johnson, Hans Fang, Tianyang Perez-Vicente, Alejandro Saniie, Jafar Research Laboratory Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL United States

We propose a distributed system based on low-power embedded FPGAs designed for edge computing applications focused on exploring distributing scheduling optimizations for Deep Learning (DL) workloads to obtain the best performance regarding latency and power efficiency. Our cluster was modular throughout the experiment, and we have implementations that consist of up to 12 Zynq-7020 chip-based boards as well as 5 UltraScale+ MPSoC FPGA boards connected through an ethernet switch, and the cluster will evaluate configurable Deep Learning Accelerator (DLA) Versatile Tensor Accelerator (VTA). This adaptable distributed architecture is distinguished by its capacity to evaluate and manage neural network workloads in numerous configurations which enables users to conduct multiple experiments tailored to their specific application needs. The proposed system can simultaneously execute diverse Neural Network (NN) models, arrange the computation graph in a pipeline structure, and manually allocate greater resources to the most computationally intensive layers of the NN graph. Copyright © 2023, The Authors. All rights reserved.

关键词： Field programmable gate arrays (FPGA)

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A V-Band 16% Efficiency Frequency Doubler-Based RF Beamforming Front-End Module for Vector Modulated Signal Transmission

A V-Band 16% Efficiency Frequency Doubler-Based RF Beamformi...

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European Conference on Microwave

作者： Mahitab Eladwy Ahmed Ben Ayed Ali M. Darwish Slim Boumaiza Department of Electrical and Computer Engineering University of Waterloo Canada Army Research Laboratory United States of America

This paper presents a millimeter-wave frequency multiplier (FM)-based RF beamforming front-end (FE) suitable for high-frequency vector signal transmission. The design considerations (i.e., tuning range, phase resolution, and magnitude variation) of the phase shifter are discussed in the context of FM-based FE. These considerations guided the design of the proposed FE which incorporates an 8-bit phase shifter, a driver amplifier, and a frequency doubler with their matching networks co-designed to minimize the FE area. A proof-of-concept prototype is designed using 45-nm CMOS-SOI technology. The measurements conducted at 62 GHz output frequency showed an average conversion gain (CG) of 5.7 dB, a doubler drain efficiency of 22.7%, and an FE drain efficiency of 16%. When the phase is varied to cover the full 360° in a step of 2.8° with an RMS phase error of 0.57°, the CG deviated by a maximum of ±0.35 dB. Using a low-complexity digital pre-distortion technique, the designed FE maintained an error vector magnitude of -30 dB and an average drain efficiency of 6% when used to generate a 256-QAM 200 MHz orthogonal frequency division multiplexing vector modulated signal and the phase is varied to cover the full 360°.

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Dual Inverter Parallel Consequent Pole PM-Assisted Two-Layer Sub-Harmonic Synchronous Machine

Dual Inverter Parallel Consequent Pole PM-Assisted Two-Layer...

引用

IEEE Conference on Electromagnetic Field Computation

作者： S M Sajjad Hossain Rafin Qasim Ali Osama A. Mohammed Dept. of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Florida USA Department of Electrical Engineering Sukkur IBA University Sukkur Pakistan

ISBN: (数字)9798350348958

ISBN: (纸本)9798350348965

A parallel consequent pole PM-assisted 2-layer subharmonic machine consisting of dual inverter topology is proposed here, which is designed to enhance torque generation and control compared to its predecessors. The stator of the sub-harmonic synchronous machine has two sets of 3-phase windings, and the dual inverter supplies current to them separately. Similarly, the rotor has two concentric windings, one for field excitation and the other for harmonic excitation. To validate the proposed model, an 8-pole, 48-slot, 2-inverter, 2-layer sub-harmonic machine is designed and simulated through 2-D finite element analysis. The results show a better torque and performance than the subharmonic and wound field synchronous machines.

关键词： Performance evaluation Torque Windings Stator windings Rotors Motors Harmonic analysis

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Enhancing Solar Radiation Forecasting with Hybrid Ensemble Empirical Mode Decomposition and Machine Learning Techniques

Enhancing Solar Radiation Forecasting with Hybrid Ensemble E...

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International Conference on Environment and electrical engineering (EEEIC)

作者： Ahmed. Aghmadi Osama Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami USA

The importance of short-term solar radiation forecasting for power system use and management cannot be overstated. However, Non-stationarity and unpredictability make accurate forecasting difficult. Time series approaches are suitable for forecasting stationary time series derived from a non-stationary sequence. Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) are time-domain decomposition methods used to separate the components of the original solar radiation time series that have distinct time 1 -scale characteristics. As a result, the components are forecasted using the Back Propagation Neural Network (BPNN) model, which is a simple and effective machine learning method. This paper presents a hybrid EMD/EEMD-BPNN model for predicting short-term solar irradiance. To identify unique data information at different time scales, EMD/EEMD first breaks up the solar radiation time series into several stationary or fundamental sub-series. The next step is to create BPNN models with specified parameters for each subsequence to forecast new ones. Finally, each subsequence's projected value is combined to generate the final forecast result. The accuracy of solar forecasts has greatly increased, especially when utilizing hybrid methods. Furthermore, using the proposed hybrid technique for multistep forecasting resulted in even more improvement. The basic BPNN model for 15 min time step achieves predicting with a root mean square error (RMSE) of roughly 416.04 W/m2 for 15min; however, this error decreases to 65.25 W/m2 with the EMD-Hybrid Model, and 32.86 W/m2 with the EEMD-Hybrid Model. In addition, the results of the skill score have proven clearly that EMD/EEMD-BPNN Model performs better compared to typical BPNN using several meteorological inputs

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Improving Temperature Stability of Dickson Charge Pump Rectifiers for Battery-Free Wireless Sensing Applications

Improving Temperature Stability of Dickson Charge Pump Recti...

引用

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

作者： Gu, Xiaoqiang Hemour, Simon Khazaka, Roni Wu, Ke McGill University Department of Electrical and Computer Engineering MontrealQC Canada Polytechnique Montreal Poly-GRAMES Research Center MontrealQC Canada University of Bordeaux IMS Laboratory CNRS UMR 5218 Bordeaux INP Talence France

ISBN: (纸本)9798350347647

Temperature stability is critical for microwave circuits and systems that experience significant temperature variations throughout the year in the real world. This work proposes a multi-stage Dickson charge pump (DCP) rectifier with improved temperature stability. A suitable Schottky diode, SMS7621, is identified for rectifier design with the help of theoretical analysis. The mismatch between diode junction resistance and load resistance resulting in rectification performance degradation related to temperature change is highlighted. Experimental results confirm that this proposed DCP rectifier can offer a stable dc output voltage higher than 3.2 V when the radiofrequency input is -8 dBm in a wide temperature range of -40 °C to +60 °C, which is good for energizing a commercial wireless sensor platform as shown in the experimental demonstration. © 2023 IEEE.

关键词： Energy harvesting

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Detection and Mitigation of Subtle Feature-map Attacks in Pseudo Parallel Collaborative CNN Models for Distributed Edge Intelligence

Detection and Mitigation of Subtle Feature-map Attacks in Ps...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Parth Patel Syed Rafay Hasan Mohammad Ashiqur Rahman Soamar Homsi Department of Electrical and Computer Engineering Tennessee Tech University USA Department of Computer Science Florida International University USA Information Warfare Division AirForce Research Laboratory USA

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

Although Collaborative Deep Neural Network (CDNN) promises to be an alternative mechanism to mitigate the effects of the untrusted cloud, this approach is susceptible to other kinds of adversarial attacks, which arise from one or more untrusted devices in CDNN acting maliciously. However, since each untrusted node in the CDNN contains only partial information of the complete DNN model, it is worth investigating whether the attacker can still muster a viable threat to CDNN or not. This led to the investigation of attack scenarios and their effects on convolutional neural networks (CNN) used for image classification in the CDNN environment. In this research, we are investigating the shortcomings of existing attacks on CDNN, that lead to non-subtle attack to the defender who is on look out against such attacks. Our research showed that sparse nature of feature maps (FMs) due to the ReLU function lead to many existing attacks more obvious to the attacker. Next, we investigated how one can detect the existing attacks if the defender has some previous knowledge of the complete CNN’s FMs. Our results show minimal detection overhead of about 2%, with an accuracy of 95% and F1 score of above 0.97. 1

关键词： Vehicular and wireless technologies Accuracy Frequency modulation Prevention and mitigation Image edge detection Collaboration Detectors Feature extraction Convolutional neural networks Image classification

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