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Three-Dimensional Refractive Index Estimation Based on Non-interferometric Optical Diffraction Tomography with Angular and Axial Illumination Scanning

Three-Dimensional Refractive Index Estimation Based on Non-i...

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Digital Holography and Three-Dimensional Imaging, DH 2024

作者： Bazow, Brad Raub, Christopher B. Nehmetallah, George Departments of Electrical Engineering and Computer Science The Catholic University of America 620 Michigan Avenue N.E. WashingtonDC20064 United States The Johns Hopkins University Applied Physics Laboratory 11100 Johns Hopkins Road LaurelMD20723 United States Departments of Biomedical Engineering The Catholic University of America 620 Michigan Avenue N.E. WashingtonDC20064 United States

We present computational inverse scattering to achieve three-dimensional refractive index reconstructions of biological specimens with sub-micron resolution in an optical diffraction tomography system with angular and...

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Estimating uncertainty intervals from collaborating networks

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Journal of Machine Learning Research 2021年第1期22卷 1-47页

作者： Zhou, Tianhui Li, Yitong Wu, Yuan Carlson, David Department of Biostatistics and Bioinformatics Duke University DurhamNC27705 United States Department of Electrical and Computer Engineering Duke University DurhamNC27705 United States Departments of Civil and Environmental Engineering Biostatistics and Bioinformatics Electrical and Computer Engineering Computer Science Duke University DurhamNC27705 United States

Effective decision making requires understanding the uncertainty inherent in a prediction. In regression, this uncertainty can be estimated by a variety of methods;however, many of these methods are laborious to tune, generate overconfident uncertainty intervals, or lack sharpness (give imprecise intervals). We address these challenges by proposing a novel method to capture predictive distributions in regression by defining two neural networks with two distinct loss functions. Specifically, one network approximates the cumulative distribution function, and the second network approximates its inverse. We refer to this method as Collaborating Networks (CN). Theoretical analysis demonstrates that a fixed point of the optimization is at the idealized solution, and that the method is asymptotically consistent to the ground truth distribution. Empirically, learning is straightforward and robust. We benchmark CN against several common approaches on two synthetic and six real-world datasets, including forecasting A1c values in diabetic patients from electronic health records, where uncertainty is critical. In the synthetic data, the proposed approach essentially matches ground truth. In the real-world datasets, CN improves results on many performance metrics, including log-likelihood estimates, mean absolute errors, coverage estimates, and prediction interval widths. ©2021 Tianhui Zhou and Yitong Li and Yuan Wu and David Carlson.

关键词： Decision making

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Optically-generated focused ultrasound for noninvasive brain stimulation with ultrahigh precision

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Light(science & Applications) 2022年第11期11卷 2817-2831页

作者： Yueming Li Ying Jiang Lu Lan Xiaowei Ge Ran Cheng Yuewei Zhan Guo Chen Linli Shi Runyu Wang Nan Zheng Chen Yang Ji-Xin Cheng Department of Mechanical Engineering Boston UniversityBostonMA 02215USA Graduate Program for Neuroscience Boston UniversityBostonMA 02215USA Department of Electrical and Computer Engineering Boston UniversityBostonMA 02215USA Department of Chemistry Boston UniversitBostonMA 02215USA Department of Biomedical Engineering Boston UniversityBostonMA 02215USA Division of Materials Science and Engineering Boston UniversityBostonMA 02215USA Department of Biological Engineering Massachusetts Institute of TechnologyCambridgeMA 02142USA

High precision neuromodulation is a powerful tool to decipher neurocircuits and treat neurological *** non-invasive neuromodulation methods offer limited precision at the milimeter ***,we report opticallygenerated focused ultrasound(OFUS)for non-invasive brain stimulation with ultrahigh *** is generated by a soft optoacoustic pad(SOAP)fabricated through embedding candle soot nanoparticles in a curved polydimethylsiloxane *** generates a transcranial ultrasound focus at 15 MHz with an ultrahigh lateral resolution of 83μm,which is two orders of magnitude smaller than that of conventional transcranial-focused ultrasound(tFUS).Here,we show effective OFUS neurostimulation in vitro with a single ultrasound *** demonstrate submillimeter transcranial stimulation of the mouse motor cortex in *** acoustic energy of 0.6 mJ/cm?,four orders of magnitude less than that of tFUS,is suffcient for successful OFUS *** offers new capabilities for neuroscience studies and disease treatments by delivering a focus with ultrahigh precision noninvasively.

关键词： SOAP stimulation precision

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Why do microwaves heat oil faster than water?

Why do microwaves heat oil faster than water?

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2023 American Society of Agricultural and biological Engineers Annual International Meeting, ASABE 2023

作者： Zhou, Xu Zhang, Shuang Takhar, Pawan Pedrow, Patrick Sablani, Shyam Tang, Juming Department of Biological Systems Engineering Washington State University PullmanWA99164 United States Department of Food Science and Human Nutrition University of Illinois Urbana-ChampaignIL61801 United States School of Electrical Engineering and Computer Science Washington State University PullmanWA99164 United States

ISBN: (纸本)9781713885887

It is generally believed that oil does not absorb microwave energy due to the small dielectric loss factor (only 1/100 that of water). Here, we compared the heating rates of four cooking oils versus water in a microwave oven under the same experimental conditions. Contrary to general belief, we found that oils heated 1.4 ~ 2.0 times faster than water in microwaves. We developed a theoretical explanation to show that a 10-fold stronger electric field was created in oil compared to water, resulting in approximately equal amounts of microwave power being absorbed by oil and water. After microwave energy had been absorbed, oil heated faster due to a smaller specific heat value (1/2 that of water). This study creates opportunities for electrifying industrial heating of oils and oil-rich biomass with microwaves, which would move the processes toward carbon-neutral operations. © 2023 ASABE Annual International Meeting. All Rights Reserved.

关键词： Microwave heating

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Estimation of Solar Cell Circuit Model Parameters Using an Algorithm Based on Artificial Intelligence

Estimation of Solar Cell Circuit Model Parameters Using an A...

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Iranian Conference on Renewable Energy and Distributed Generation (ICREDG)

作者： Aydin Samani Masume Khodsuz Departments of Electrical Engineering Islamic Azad University Science and Research Branch Tehran Iran Faculty of Electrical and Computer Engineering University of Science and Technology of Mazandaran Behshahr Iran

In this article, it is intended to estimate the parameters of the equivalent circuit of the two-diode model of the PV system by using the method based on artificial intelligence. Based on this, at first, using the particle swarm algorithm as a suitable method, 7 parameters of the two-diode model were optimized. In order to check the performance of the particle swarm method, different strategies were considered for it, including PSO algorithm with random inertia coefficient, time-varying inertia coefficient, time-varying learning coefficients, contraction coefficient and average. Next, the Archimedes optimization method as a new algorithm in this field was proposed and investigated, and the parameters of the two-diode model were optimized based on it. In order to check the accuracy of the proposed methods, the results obtained from the optimization of the parameters of the two-diode PV system model were compared with some optimization methods.

关键词： Photovoltaic cells Optimization methods Estimation Mean square error methods Distributed power generation Integrated circuit modeling Particle swarm optimization

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UAV Swarms for Joint Data Ferrying and Dynamic Cell Coverage via Optimal Transport Descent and Quadratic Assignment

arXiv

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arXiv 2023年

作者： Cui, Kai Baumgärtner, Lars Yilmaz, Burak Li, Mengguang Fabian, Christian Becker, Benjamin Xiang, Lin Bauer, Maximilian Koeppl, Heinz The Departments of Electrical Engineering and Information Technology Computer Science and Mechanical Engineering Technische Universität Darmstadt Darmstadt64287 Germany

Both data ferrying with disruption-tolerant networking (DTN) and mobile cellular base stations constitute important techniques for UAV-aided communication in situations of crises where standard communication infrastructure is unavailable. For optimal use of a limited number of UAVs, we propose providing both DTN and a cellular base station on each UAV. Here, DTN is used for large amounts of low-priority data, while capacity-constrained cell coverage remains reserved for emergency calls or command and control. We optimize cell coverage via a novel optimal transport-based formulation using alternating minimization, while for data ferrying we periodically deliver data between dynamic clusters by solving quadratic assignment problems. In our evaluation, we consider different scenarios with varying mobility models and a wide range of flight patterns. Overall, we tractably achieve optimal cell coverage under quality-of-service costs with DTN-based data ferrying, enabling large-scale deployment of UAV swarms for crisis communication. Copyright © 2023, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent

arXiv

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arXiv 2025年

作者： Fang, Cheng Dixit, Rishabh Bajwa, Waheed U. Gürbüzbalaban, Mert Department of Electrical and Computer Engineering Rutgers University New BrunswickNJ United States Department of Mathematics University of California San DiegoCA United States Departments of Electrical and Computer Engineering and Statistics Rutgers University New BrunswickNJ United States Departments of Electrical and Computer Engineering Management Science and Information Systems and Statistics Rutgers University New BrunswickNJ United States

Empirical risk minimization (ERM) is a cornerstone of modern machine learning (ML), supported by advances in optimization theory that ensure efficient solutions with provable algorithmic convergence rates, which measure the speed at which optimization algorithms approach a solution, and statistical learning rates, which characterize how well the solution generalizes to unseen data. Privacy, memory, computational, and communications constraints increasingly necessitate data collection, processing, and storage across network-connected devices. In many applications, these networks operate in decentralized settings where a central server cannot be assumed, requiring decentralized ML algorithms that are both efficient and resilient. Decentralized learning, however, faces significant challenges, including an increased attack surface for adversarial interference during decentralized learning processes. This paper focuses on the man-in-the-middle (MITM) attack, wherein adversaries exploit communication vulnerabilities between devices to inject malicious updates during training, potentially causing models to deviate significantly from their intended ERM solutions. To address this challenge, we propose RESIST (Resilient dEcentralized learning using conSensus gradIent deScenT), an optimization algorithm designed to be robust against adversarially compromised communication links, where transmitted information may be arbitrarily altered before being received. Unlike existing adversarially robust decentralized learning methods, which often (i) guarantee convergence only to a neighborhood of the solution, (ii) lack guarantees of linear convergence for strongly convex problems, or (iii) fail to ensure statistical consistency as sample sizes grow, RESIST overcomes all three limitations. It achieves algorithmic and statistical convergence for strongly convex, Polyak–Lojasiewicz, and nonconvex ERM problems by employing a multistep consensus gradient descent framework and robust statis

关键词： Adversarial machine learning

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Differing vibrational properties of halide and chalcogenide perovskite semiconductors and impact on optoelectronic performance

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Physical Review Materials 2024年第8期8卷 085402页

作者： Kevin Ye Matan Menahem Tommaso Salzillo Florian Knoop Boyang Zhao Shanyuan Niu Olle Hellman Jayakanth Ravichandran R. Jaramillo Omer Yaffe Department of Materials Science and Engineering Department of Chemical and Biological Physics Department of Industrial Chemistry “Toso Montanari” Department of Physics Chemistry and Biology (IFM) Mork Family Department of Chemical Engineering and Materials Science Department of Molecular Chemistry and Material Science Ming Hsieh Department of Electrical and Computer Engineering Core Center of Excellence in NanoImaging (CNI)

We report a comparative study of temperature-dependent photoluminescence and structural dynamics of two perovskite semiconductors, the chalcogenide BaZrS3 and the halide CsPbBr3. These materials have similar crystal structures and direct band gaps, but we find that they have quite distinct optoelectronic and vibrational properties. Both materials exhibit thermally activated nonradiative recombination, but the nonradiative recombination rate in BaZrS3 is four orders of magnitude faster than in CsPbBr3, for the crystals studied here. Raman spectroscopy reveals that the effects of phonon anharmonicity are far more pronounced in CsPbBr3 than in BaZrS3. Further, although both materials feature a large dielectric response due to low-energy polar optical phonons, the phonons in CsPbBr3 are substantially lower in energy than in BaZrS3. Our results suggest that electron-phonon coupling in BaZrS3 is more effective at nonradiative recombination than in CsPbBr3 and that BaZrS3 may also have a substantially higher concentration of nonradiative recombination centers than CsPbBr3. The low defect concentration in CsPbBr3 may be related to the ease of lattice reconfiguration, typified by anharmonic bonding. It remains to be seen to what extent these differences are inherent to the chalcogenide and halide perovskites and to what extent they can be affected by materials processing.

关键词： Electron-phonon coupling Lattice dynamics Photoemission Solar cells Photovoltaic absorbers Photoluminescence Raman spectroscopy

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Lightsolver challenges a leading deep learning solver for Max-2-SAT problems

arXiv

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arXiv 2023年

作者： Wirzberger, Hod Kalinski, Assaf Meirzada, Idan Primack, Harel Romano, Yaniv Tradonsky, Chene Shlomi, Ruti Ben LightSolver LTD. Tel Aviv Israel Departments of Electrical and Computer Engineering and Computer Science Technion IIT Israel

Maximum 2-satisfiability (MAX-2-SAT) is a type of combinatorial decision problem that is known to be NP-hard. In this paper, we compare LightSolver’s quantum-inspired algorithm to a leading deep-learning solver for the MAX-2-SAT problem. Experiments on benchmark data sets show that LightSolver achieves significantly smaller time-to-optimal-solution compared to a state-of-the-art deep-learning algorithm, where the gain in performance tends to increase with the problem size. © 2023, CC BY.

关键词： Learning algorithms

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Error budget of a parametric resonance entangling gate with a tunable coupler

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Physical Review Applied 2024年第1期22卷 014059-014059页

作者： Eyob A. Sete Vinay Tripathi Joseph A. Valery Daniel Lidar Josh Y. Mutus 775 Heinz Avenue Berkeley California 94710 USA Department of Physics & Astronomy and Center for Quantum Information Science & Technology Departments of Electrical & Computer Engineering Chemistry Physics & Astronomy and Center for Quantum Information Science & Technology

We analyze the experimental error budget of parametric resonance gates in a tunable coupler architecture. We identify and characterize various sources of errors, including incoherent, leakage, amplitude, and phase errors. By varying the two-qubit gate time, we explore the dynamics of these errors and their impact on the gate fidelity. To accurately capture the impact of incoherent errors on gate fidelity, we measure the coherence times of qubits under gate operating conditions. Our findings reveal that the incoherent errors, mainly arising from qubit relaxation and dephasing due to white noise, limit the fidelity of the two-qubit gates. Moreover, we demonstrate that leakage to noncomputational states is the second largest contributor to the two-qubit gates infidelity, as characterized using leakage-randomized benchmarking. The error budgeting methodology we develop here can be effectively applied to other types of gate implementations.

关键词： Quantum computation Quantum control Quantum engineering

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