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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Varinya Phanichraksaphong Karuna Yampray Department of Electronic Engineering International Graduate Program of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan College of Creative Design and Entertainment Technology Dhurakij Pundit University Bangkok Thailand

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

A great number of deep learning-based models have been recently proposed for automatic piano classification. In this paper, we describe our contribution to the challenge of automatic piano classification when the performer performs at the concert or stage. Among these models in deep learning, we use init-1D-WaveNet and init-2D-MLNet for comparison the accuracy in the piano beginning level of the Christmas song (Jingle bells). Our experimental results show that the assessment using the init-2D-MLNet still achieve high accuracy of 87.5%.

关键词： Deep learning Accuracy Instruments Collaboration Consumer electronics

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Creating semi-Quanta multi-layer synthetic CNT images using CycleGAN

Creating semi-Quanta multi-layer synthetic CNT images using ...

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Applied Imagery Pattern Recognition Workshop (AIPR)

作者： Kaveh Safavigerdini Ramakrishna Surya Andrew Reinhard Zach Quinlan Filiz Bunyak Matthew R. Maschmann Kannappan Palaniappan Department of Electrical Engineering and Computer Science University of Missouri Columbia Mo USA Department of Mechanical & Aerospace Engineering University of Missouri Columbia Mo USA MU Materials Science and Engineering Institute University of Missouri Columbia Mo USA

We address the challenge of creating semi-Quanta images of vertically-oriented carbon nanotubes (CNT). Our previous method, CNTNeXt, successfully predicted the mechanical properties for semi-Scanning Electron Microscopy (SEM) images of CNT forests. However, for Quanta images, a more sophisticated approach is required. We propose a novel pipeline that modifies multi-layer synthetic (MLS) CNT images, which are synthetic representations of CNT structures, to resemble Quanta images. This is achieved using CycleGAN, a deep learning model designed for image-to-image translation tasks, which can learn mappings between two different domains without paired training data. By training the CycleGAN on both Quanta and MLS images, we are able to transfer the texture of Quanta images to the MLS images. The resulting ’semi-Quanta’ images are ready to train CNTNeXt, which effectively predicts the mechanical properties, including buckling load and stiffness of synthetic MLS images. Our method represents an advancement towards our ultimate goal of creating an automated CNT growth process, and opens up possibilities for further improvements and applications.

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Impact of oxygen-containing carbonyl and ether groups on dielectric properties of poly(oxa)norbornene cyclic olefins

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Journal of Advanced Dielectrics 2023年第4期13卷 65-68页

作者： Chao Wu Ajinkya A.Deshmukh Lihua Chen Rampi Ramprasad Gregory A.Sotzing Yang Cao Institute of Materials Science University of Connecticut StorrsCT 06269USA School of Materials Science and Engineering Georgia Institute of Technology AtlantaGA 30332USA Department of Electrical and Computer Engineering University of Connecticut StorrsCT 06269USA

Flexible dielectric polymers that can withstand high electric field and simultaneously have high dielectric constant are desired for high-density energy ***,we systematically investigated the impact of oxygen-containing ether and carbonyl groups in the backbone structure on dielectric properties of a series of cyclic *** comparison to the influence of the-CF3 pendant groups that had more impact on the dielectric constant rather than the band gap,the change of the backbone structure affected both the dielectric constant and band *** one polymer with ether and carbonyl groups in the backbone has the largest band gap and highest discharge efficiency,while it has the lowest dielectric *** polymer without any ether groups in the backbone has the smallest band gap and lowest discharge efficiency,but it has the highest dielectric *** that have no dipolar relaxation exhibit an inversely correlated dielectric constant and band *** the dipolar relaxation through rational molecular structure design can be a novel way to break through the exclusive constraint of dielectric constant and band gap for high-density energy storage.

关键词： Polymer dielectric band gap glass transition conduction energy density DFT

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Deep Style Transfer for Generation of Photo-realistic Synthetic Images of CNT Forests

Deep Style Transfer for Generation of Photo-realistic Synthe...

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Applied Imagery Pattern Recognition Workshop (AIPR)

作者： Prashanth Reddy Kotha Minasadat Attari Matthew Maschmann Filiz Bunyak Department of Electrical Engineering and Computer Science University of Missouri Columbia MO USA Department of Mechanical and Aerospace Engineering University of Missouri Columbia MO USA MU Materials Science and Engineering Institute University of Missouri Columbia MO USA

Carbon nanotubes (CNTs) are promising nano-materials with diverse applications in various fields, ranging from electronics and energy storage to biomedical applications. Characterization of CNT forest structures and prediction of material properties through image analytics are critical for new material design and discovery. Artificial intelligence and machine learning (AI/ML) driven approaches offer promising solutions towards these goals. These data-driven approaches rely on large amounts of annotated data for robust training. However, growing, imaging, and annotation of CNT forests are complex, time consuming, expensive processes limiting availability of such data. In this paper, we propose a novel neural style transfer pipeline to generate photo-realistic and structure-aware synthetic images of CNT forests by imposing scanning electron microscopy (SEM) like appearance to physics-based simulation results. The proposed pipeline relies on a novel wavelet-based style transfer network and a selective decision fusion mechanism that allows better preservation of the thin curvilinear structures of CNTs, particularly their intricate details and connectivity, without introducing unwanted artifacts. Experimental results and quantitative analysis demonstrate refined style transfer that generates photo-realistic images that can be used to train AI/ML- driven CNT forest image analysis systems.

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A Transparent Ultrasound Array for Real-Time Optical,Ultrasound,and Photoacoustic Imaging

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Biomedical engineering Frontiers 2022年第1期3卷 284-297页

作者： Haoyang Chen Sumit Agrawal Mohamed Osman Josiah Minotto Shubham Mirg Jinyun Liu Ajay Dangi Quyen Tran Thomas Jackson Sri-Rajasekhar Kothapalli Department of Biomedical Engineering The Pennsylvania State UniversityUniversity ParkPA 16802USA School of Electrical Engineering and Computer Science The Pennsylvania State UniversityUniversity ParkPA 16802USA Penn State Cancer Institute The Pennsylvania State UniversityHersheyPA 17033USA Graduate Program in Acoustics The Pennsylvania State UniversityUniversity ParkPA 16802USA

Objective and Impact *** imaging of ultrasound and optical contrasts can help map structural,functional,and molecular biomarkers inside living subjects with high spatial *** is a need to develop a platform to facilitate this multimodal imaging capability to improve diagnostic sensitivity and ***,combining ultrasound,photoacoustic,and optical imaging modalities is challenging because conventional ultrasound transducer arrays are optically *** a result,complex geometries are used to coalign both optical and ultrasound waves in the same field of *** elegant solution is to make the ultrasound transducer transparent to ***,we demonstrate a novel transparent ultrasound transducer(TUT)linear array fabricated using a transparent lithium niobate piezoelectric material for real-time multimodal *** TUT-array consists of 64 elements and centered at~6 MHz *** demonstrate a quad-mode ultrasound,Doppler ultrasound,photoacoustic,and fluorescence imaging in real-time using the TUT-array directly coupled to the tissue mimicking *** TUT-array successfully showed a multimodal imaging capability and has potential applications in diagnosing cancer,neurological,and vascular diseases,including image-guided endoscopy and wearable imaging.

关键词： Ultrasound specificity transparent

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Temperature Dependent Low-Frequency Noise Characteristics of NiOx/β-Ga2O3 p-n Heterojunction Diodes

arXiv

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arXiv 2023年

作者： Ghosh, Subhajit Mudiyanselage, Dinusha Herath Kargar, Fariborz Zhao, Yuji Fu, Houqiang Balandin, Alexander A. Department of Electrical and Computer Engineering University of California RiversideCA92521 United States School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Materials Science and Engineering University of California Los AngelesCA90095 United States

We report on the temperature dependence of the low-frequency electronic noise in NiOx/βGa2O3 p-n heterojunction diodes. The noise spectral density is of the 1/f-type near room temperature but shows signatures of Lorentzian components at elevated temperatures and at higher current levels (f is the frequency). We observed an intriguing non-monotonic dependence of the noise on temperature near T = 380 K. The Raman spectroscopy of the device structure suggests material changes, which results in reduced noise above this temperature. The normalized noise spectral density in such diodes was determined to be on the order of 10–14 cm2/Hz (f = 10 Hz) at 0.1 A/cm2 current density. In terms of the noise level, NiOx/β-Ga2O3 p-n diodes occupy an intermediate position among devices of various designs implemented with different ultra-wide-bandgap semiconductors. The obtained results are important for understanding the electronic properties of NiOx/β-Ga2O3 heterojunctions and contribute to the development of noise spectroscopy as the quality assessment tool for new electronic materials and device technologies. Copyright © 2023, The Authors. All rights reserved.

关键词： Electronic properties

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Defeating broken symmetry with doping: Symmetric resonant tunneling in noncentrosymetric heterostructures

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Physical Review B 2023年第12期107卷 125301-125301页

作者： Jimy Encomendero Vladimir Protasenko Debdeep Jena Huili Grace Xing School of Electrical and Computer Engineering Cornell University Ithaca New York 14853 USA Department of Materials Science and Engineering Cornell University Ithaca New York 14853 USA Kavli Institute at Cornell for Nanoscale Science Cornell University Ithaca New York 14853 USA

Resonant tunneling transport in polar heterostructures is intimately connected to the polarization fields emerging from the geometric Berry-phase. In these structures, quantum confinement results not only in a discrete electronic spectrum, but also in built-in polarization charges exhibiting a broken inversion symmetry along the transport direction. Thus, electrons undergo highly asymmetric quantum interference effects with respect to the direction of current flow. By employing doping to counter the broken symmetry, we deterministically control the resonant transmission through GaN/AlN resonant tunneling diodes and experimentally demonstrate the recovery of symmetric resonant tunneling injection across the noncentrosymmetric double-barrier potential.

关键词： Heterostructures III-V semiconductors Nitrides Molecular beam epitaxy Resistivity measurements Tunnel diode resonance

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electrically Tuning Quasi-Bound States in the Continuum with Hybrid Graphene-Silicon Metasurfaces

arXiv

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arXiv 2024年

作者： Cai, Ziqiang Zhang, Xianzhe Karnik, Tushar Sanjay Xu, Yihao Kim, Tae Yoon Hu, Juejun Liu, Yongmin Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Mechanical and Industrial Engineering Northeastern University BostonMA02115 United States

Metasurfaces have become one of the most prominent research topics in the field of optics owing to their unprecedented properties and novel applications on an ultrathin platform. By combining graphene with metasurfaces, electrical tunable functions can be achieved with fast tuning speed, large modulation depth and broad tuning range. However, the tuning efficiency of hybrid graphene metasurfaces within the short-wavelength infrared (SWIR) spectrum is typically low because of the small resonance wavelength shift in this wavelength range. In this work, through the integration of graphene and silicon metasurfaces that support quasi-bound states in the continuum (quasi-BIC), we experimentally demonstrate significant transmittance tuning even with less than 30 nm resonance wavelength shift thanks to the high quality-factor of quasi-BIC metasurfaces. The tunable transmittance spectrum was measured using Fourier Transform Infrared Spectroscopy (FTIR) with a modified reflective lens to improve the accuracy, and the electrical tuning was realized utilizing the "cut-and-stick" method of ion gel. At the wavelength of 3.0 µm, the measured change of transmittance ΔT = Tmax − Tmin and modulation depth ΔT/Tmax can reach 22.2% and 28.9%, respectively, under a small bias voltage ranging from -2 V to +2 V. To the best of our knowledge, this work is the first experimental demonstration of tunable graphene/quasi-BIC metasurfaces, which have potential applications in optical modulation, reconfigurable photonic devices, and optical communications. Copyright © 2024, The Authors. All rights reserved.

关键词： Graphene

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Colossal Birefringence from Periodic Structural Modulations

Colossal Birefringence from Periodic Structural Modulations

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Mei, Hongyan Ren, Guodong Zhao, Boyang Salman, Jad Jung, Gwan-Yeong Chen, Huandong Thind, Arashdeep S. Cavin, John Hachtel, Jordan A. Chi, Miaofang Niu, Shanyuan Joe, Graham Wan, Chenghao Settineri, Nick Teat, Simon J. Chakoumakos, Bryan C. Ravichandran, Jayakanth Mishra, Rohan Kats, Mikhail A. Department of Electrical and Computer Engineering University of Wisconsin-Madison MadisonWI53706 United States Institute of Materials Science and Engineering Washington University in St. Louis St. LouisMO63130 United States Mork Family Department of Chemical Engineering and Materials Science University of Southern California Los AngelesCA90089 United States Department of Mechanical Engineering and Material Science Washington University in St. Louis St. LouisMO63130 United States Department of Physics Washington University in St. Louis St. LouisMO63130 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States Department of Materials Science and Engineering University of Wisconsin-Madison MadisonWI53706 United States Advanced Light Source Lawrence BerkeleyNational Laboratory BerkeleyCA94720 United States Neutron Scattering Division Oak Ridge NationalLaboratory Oak RidgeTN37830 United States Ming Hsieh Department of Electrical Engineering University of Southern California Los AngelesCA90089 United States

We introduce structural modulation as a new mechanism for achieving colossal optical anisotropy. Modulated nonstoichiometric material Sr9/8TiS3 is shown to have an extraordinary refractive index ne = 4.5 and ordinary ... 详细信息

ISBN: (纸本)9781957171258

关键词： Refractive index

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Lightweight Pedestrian Detection through Guided Filtering and Deep Learning 10

Lightweight Pedestrian Detection through Guided Filtering an...

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10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Muchtar, Kahlil Saddami, Khairun Bintang, Akhyar Cenggoro, Tjeng Wawan Pardamean, Bens Lin, Chih-Yang Ernita, Tia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Universitas Syiah Kuala Department of Electrical And Computer Engineering Aceh Indonesia Bina Nusantara University School of Computer Science Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Bioinformatics And Data Science Research Center Computer Science Department Jakarta Indonesia Yuan-Ze University Department of Electrical And Engineering Taoyuan Taiwan

ISBN: (纸本)9781665436762

In this paper, we propose a novel approach to locate and detect moving pedestrians in a video. Our proposed method first locates the region of interest (ROI) using a background subtraction algorithm based on guided filtering. This novel background subtraction algorithm allows our method to also filter unexpected noises at the same time, which could benefit the performance of our proposed method. Subsequently, the pedestrians are detected using YOLOv3 within the provided ROI. Our experiments showed that the proposed method has a competitive performance in the CDNET2014 dataset with a fast-processing time. © 2021 IEEE.

关键词： Convolutional neural networks

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