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JSAP-OSA Joint Symposia, JSAP 2021

作者： Bao, J. Peraca, N. Marquez Tay, F. Kritzell, T.E. Li, X. Noe, G.T. Katayama, I. Takeda, J. Nojiri, H. Yamahara, H. Tabata, H. Baydin, A. Kono, J. Department of Physics and Astronomy Rice University HoustonTX United States Department of Electrical and Computer Engineering Rice University HoustonTX United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX United States Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama Japan Institute for Materials Research Tohoku University Sendai Japan Department of Electrical Engineering and Information Systems Graduate School of Engineering University of Tokyo Japan Smalley-Curl Institute Rice University HoustonTX United States Department of Materials Science and NanoEngineering Rice University HoustonTX United States

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Cycle Consistency-based Uncertainty Quantification of Neural Networks in Inverse Imaging Problems

arXiv

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arXiv 2023年

作者： Huang, Luzhe Li, Jianing Ding, Xiaofu Zhang, Yijie Chen, Hanlong Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los AngelesCA90095 United States University of California Los AngelesCA90095 United States Computer Science Department University of California Los AngelesCA90095 United States Department of Mathematics University of California Los AngelesCA90095 United States David Geffen School of Medicine University of California Los Angeles Los AngelesCA90095 United States

Uncertainty estimation is critical for numerous applications of deep neural networks and draws growing attention from researchers. Here, we demonstrate an uncertainty quantification approach for deep neural networks used in inverse problems based on cycle consistency. We build forward-backward cycles using the physical forward model available and a trained deep neural network solving the inverse problem at hand, and accordingly derive uncertainty estimators through regression analysis on the consistency of these forward-backward cycles. We theoretically analyze cycle consistency metrics and derive their relationship with respect to uncertainty, bias, and robustness of the neural network inference. To demonstrate the effectiveness of these cycle consistency-based uncertainty estimators, we classified corrupted and out-of-distribution input image data using some of the widely used image deblurring and super-resolution neural networks as testbeds. The blind testing of our method outperformed other models in identifying unseen input data corruption and distribution shifts. This work provides a simple-to-implement and rapid uncertainty quantification method that can be universally applied to various neural networks used for solving inverse problems. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

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Electrostatic Energy Harvesting from Human Interactions with Smart Paper Electronics*

Electrostatic Energy Harvesting from Human Interactions with...

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Alyssa Y. Zhou Michel M. Maharbiz Department of Electrical Engineering and Computer Science University of California Berkeley CA USA Department of Electrical Engineering and Computer Science and the Department of Bioengineering University of California Berkeley CA USA

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Smart devices are quickly becoming ubiquitous with the rise of portable biosensors and the internet of things. There exists particular interest in enhancing common objects to have smart capabilities and finding inexpensive solutions for diagnostic tools. One such example is transforming paper items into interactive devices and point-of-care analytic products. Due to the lightweight, flexible, and cost-efficient qualities of paper, unobtrusively powering these devices remains an outstanding problem. In this paper, we demonstrate an electrostatic human-touch powered energy harvesting system, integrated with flexible painted conductive electrodes on paper. This system harvests 8.5 nJ of energy and reaches a voltage of 1.3 V on a 10 nF energy storage capacitor. This technology not only provides a method of powering paper-based products with routine human gestures but can also detect human touch for input communication to sensors.

关键词： Electrodes Energy harvesting Capacitance Capacitors Fingers Ink Photovoltaic cells

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Structural tuning magnetism and topology in a magnetic topological insulator

arXiv

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arXiv 2023年

作者： Eckberg, Christopher Qiu, Gang Qu, Tao Kwon, Sohee Liu, Yuhang Tai, Lixuan Graf, David Chong, Su Kong Zhang, Peng Wong, Kin L. Lake, Roger K. Neupane, Mahesh R. Wang, Kang L. Fibertek Inc. HerndonVA20171 United States DEVCOM Army Research Laboratory AdelphiMD20783 United States DEVCOM Army Research Laboratory Playa Vista CA90094 United States Department of Electrical and Computer Engineering University of California Los AngelesCA90095 United States Department of Electrical and Computer Engineering University of California RiversideCA92521 United States National High Magnetic Field Laboratory Florida State University TallahasseeFL32310 United States Materials Science and Engineering Program University of California RiversideCA92521 United States

To date, the most widely-studied quantum anomalous Hall insulator (QAHI) platform is achieved by dilute doping of magnetic ions into thin films of the alloyed tetradymite topological insulator (TI) (Bi1−xSbx)2Te3 (BST) [1–4]. In these films, long-range magnetic ordering of the transition metal substituants opens an exchange gap ∆ in the topological surface states, stabilizing spin-polarized, dissipationless edge channels with a nonzero Chern number C. The long-range ordering of the spatially separated magnetic ions is itself mediated by electronic states in the host TI, leading to a sophisticated feedback between magnetic and electronic properties. Here we present a study of the electronic and magnetic response of a BST-based QAHI system to structural tuning via hydrostatic pressure. We identify a systematic closure of the topological gap under compressive strain accompanied by a simultaneous enhancement in the magnetic ordering strength. Combining these experimental results with first-principle calculations we identify structural deformation as a strong tuning parameter to traverse a rich topological phase space and modify magnetism in the magnetically doped BST system. © 2023, CC BY-NC-ND.

关键词： Topology

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StyleKQC: A Style-Variant Paraphrase Corpus for Korean Questions and Commands

arXiv

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arXiv 2021年

作者： Cho, Won Ik Moon, Sangwhan Kim, Jong In Kim, Seok Min Kim, Nam Soo Department of Electrical and Computer Engineering INMC Seoul National University Korea Republic of Department of Computer Science Tokyo Institute of Technology Japan Google LLC Interdisciplinary Program in Cognitive Science Seoul National University Korea Republic of

Paraphrasing is often performed with less concern for controlled style conversion. Especially for questions and commands, style-variant paraphrasing can be crucial in tone and manner, which also matters with industrial applications such as dialog systems. In this paper, we attack this issue with a corpus construction scheme that simultaneously considers the core content and style of directives, namely intent and formality, for the Korean language. Utilizing manually generated natural language queries on six daily topics, we expand the corpus to formal and informal sentences by human rewriting and transferring. We verify the validity and industrial applicability of our approach by checking the adequate classification and inference performance that fit with conventional fine-tuning approaches, at the same time proposing a supervised formality transfer task. © 2021, CC BY-SA.

关键词： Natural language processing systems

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Opto-thermoelectric pulling of light-absorbing particles

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Light(science & Applications) 2020年第1期9卷 1686-1696页

作者： Linhan Lin Pavana Siddhartha Kollipara Abhay Kotnala Taizhi Jiang Yaoran Liu Xiaolei Peng Brian A.Korgel Yuebing Zheng Walker Department of Mechanical Engineering The University of Texas at AustinAustinTX 78712USA Materials Science&Engineering Program and Texas Materials Institute The University of Texas at AustinAustinTX 78712USA State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua UniversityBeijing 100084People’s Republic of China McKetta Department of Chemical Engineering The University of Texas at AustinAustinTX 78712USA Department of Electrical and Computer Engineering The University of Texas at AustinAustinTX 78712USA

Optomechanics arises from the photon momentum and its exchange with low-dimensional *** is well known that optical radiation exerts pressure on objects,pushing them along the light ***,optical pulling of an object against the light path is still a counter-intuitive ***,we present a general concept of optical pulling-opto-thermoelectric pulling(OTEP)—where the optical heating of a light-absorbing particle using a simple plane wave can pull the particle itself against the light *** irradiation orientation-directed pulling force imparts self-restoring behaviour to the particles,and three-dimensional(3D)trapping of single particles is achieved at an extremely low optical intensity of 10^(−2)mWμm^(−2).Moreover,the OTEP force can overcome the short trapping range of conventional optical tweezers and optically drive the particle flow up to a macroscopic *** concept of selfinduced opto-thermomechanical coupling is paving the way towards freeform optofluidic technology and lab-on-achip devices.

关键词： absorbing light trapping

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The behavior of internet traffic for internet services during COVID-19 pandemic scenario

arXiv

引用

arXiv 2021年

作者： da Silva, Carlos Alexandre Gouvea Ferrari, Allan Christian Krainski Osinski, Cristiano Pelacini, Douglas Antonio Firmino Computer Science Department State University of Parana Midwest Unicentro Guarapuava Brazil Centro Universitário Unicuritiba Curitiba Brazil Department of Electrical Engineering Electrical Engineering Graduate Program Federal University of Paraná Curitiba Brazil

Since the end of 2019, the SARS-CoV-2 virus known as COVID-19 has spread rapidly around the world, forcing many governments to impose restrictive blocking or lockdown to combat the pandemic. With locomotion restriction of people in almost of countries of the world, workers and students needed to keep their activities at home. As a result, people's behavior, habits, and the way they started using the Internet changed significantly. Like professionals of offices, the younger played an important role in this behavior, especially in the type of resources used by them. As result, the characterization and traffic of communication networks were affected in some way. In this perspective article, we join from many available studies about the COVID-19 effect at networks and investigate the effects on the Internet traffic of using services such as video streaming, video conferencing, and gaming during 2020's months of the pandemic. © 2021, CC BY.

关键词： Diseases

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Quantum Diamond Microscope for Dynamic Imaging of Magnetic Fields

arXiv

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arXiv 2023年

作者： Tang, Jiashen Yin, Zechuan Hart, Connor A. Blanchard, John W. Oon, Jner Tzern Bhalerao, Smriti Schloss, Jennifer M. Turner, Matthew J. Walsworth, Ronald L. Department of Physics University of Maryland College ParkMD20742 United States Quantum Technology Center University of Maryland College ParkMD20742 United States Department of Electrical Engineering and Computer Science University of Maryland College ParkMD20742 United States Fischell Department of Bioengineering University of Maryland College ParkMD20742 United States Lincoln Laboratory Massachusetts Institute of Technology LexingtonMA02421 United States

Wide-field imaging of magnetic signals using ensembles of nitrogen-vacancy (NV) centers in diamond has garnered increasing interest due to its combination of micron-scale resolution, millimeter-scale field of view, and compatibility with diverse samples from across the physical and life sciences. Recently, wide-field NV magnetic imaging based on the Ramsey protocol has achieved uniform and enhanced sensitivity compared to conventional measurements. Here, we integrate the Ramsey-based protocol with spin-bath driving to extend the NV spin dephasing time and improve magnetic sensitivity. We also employ a high-speed camera to enable dynamic wide-field magnetic imaging. We benchmark the utility of this quantum diamond microscope (QDM) by imaging magnetic fields produced from a fabricated wire phantom. Over a 270 × 270 µm2 field of view, a median per-pixel magnetic sensitivity of 4.1(1) nT/√Hz is realized with a spatial resolution . 10 µm and sub-millisecond temporal resolution. Importantly, the spatial magnetic noise floor can be reduced to the picotesla scale by time-averaging and signal modulation, which enables imaging of a magnetic-field pattern with a peak-to-peak amplitude difference of about 300 pT. Finally, we discuss potential new applications of this dynamic QDM in studying biomineralization and electrically-active cells. © 2023, CC BY.

关键词： Magnetic fields

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Minimizing Number of Nodes in Decision Trees with Hypotheses

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Procedia computer science 2021年 192卷 232-240页

作者： Mohammad Azad Igor Chikalov Shahid Hussain Mikhail Moshkov Jouf University College of Computer and Information Sciences Department of Computer Science Sakaka 72441 Saudi Arabia Intel Corporation 5000 W Chandler Blvd Chandler AZ 85226 USA Habib University Dhanani School of Science and Engineering Computer Science Program Karachi 75290 Pakistan King Abdullah University of Science and Technology (KAUST) Computer Electrical and Mathematical Sciences & Engineering Division Thuwal 23955-6900 Saudi Arabia

In this paper, we consider decision trees that use both conventional queries based on one attribute each and queries based on hypotheses about values of all attributes. This approach is similar to one studied in exact learning, where membership and equivalence queries are considered. We propose dynamic programming algorithms for the minimization of the number of nodes in such decision trees and discuss results of computer experiments.

关键词： Decision tree Hypothesis Number of nodes

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Fault Diagnosis of Wind Energy Conversion Systems Using Gaussian Process Regression-based Multi-Class Random Forest

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IFAC-PapersOnLine 2022年第6期55卷 127-132页

作者： Majdi Mansouri Radhia Fezai Mohamed Trabelsi Hajji Mansour Hazem Nounou Mohamed Nounou Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Department of Mathematics and Sciences Prince Sultan University Riyadh 11586 Saudi Arabia Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir 5019 Tunisia Electronic and Communications Engineering Department Kuwait College of Science and Technology P. O. Box 27235 Kuwait Higher Institute of Applied Science and Technology of Kasserine University of Kairouan PO Box 471 1200 Kasserine Tunisia Chemical Engineering Program Texas A&M University at Qatar Doha Qatar

This work proposes a new fault diagnosis approach for a wind energy conversion (WEC) system. The proposed technique merges the benefits of feature extraction based on Gaussian Process Regression (GPR) and Multi-Class Random Forest (MCRF)-based fault classification where instances are classified into one or more classes. In the developed GPR-MCRF approach, the nonlinear statistical features including the mean vector M GPR and the variance matrix C GPR are computed using the GPR model with aim of extracting the most relevant features from the WEC system. Then, these features are introduced to the RF classifier for classification and diagnosis purposes. Therefore, the application of the GPR-MCRF technique for WEC systems aims to enhance the use of the classical raw data-based MCRF and diagnosis accuracy. Three kinds of faults (wear-out, open-circuit, and short-circuit faults) are considered in this work. Different case studies are investigated in order to illustrate the effectiveness and robustness of the developed technique compared to the state-of-the-art methods. The obtained results show that the the developed GPR-MCRF technique is an effective feature extraction and fault diagnosis technique for WEC systems.

关键词： Random Forest (RF) Multi-Class Gaussian Process Regression (GPR) Fault Diagnosis Wind Energy Conversion Systems

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