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arXiv 2022年

作者： Hayajneh, Abdullah Shaqfeh, Mohammad Serpedin, Erchin Stotland, Mitchell A. Electrical and Computer Engineering Department Texas A&M University College StationTX United States Electrical and Computer Engineering Program Texas A&M University Doha Qatar Division of Plastic Craniofacial and Hand Surgery Sidra Medicine Weill Cornell Medical College Doha Qatar

This paper presents a novel machine learning framework to consistently detect, localize and rate congenital cleft lip anomalies in human faces. The goal is to provide a universal, objective measure of facial differences and reconstructive surgical outcomes that matches human judgments. The proposed method employs the StyleGAN2 generative adversarial network with model adaptation to produce normalized transformations of cleft-affected faces in order to allow for subsequent measurement of deformity using a pixel-wise subtraction approach (as illustrated in Figure 1). The complete pipeline of the proposed framework consists of the following steps: image preprocessing, face normalization, color transformation, morphological erosion, heat-map generation and abnormality scoring. Heatmaps that finely discern anatomic anomalies are proposed by exploiting the features of the considered framework. The proposed framework is validated through computer simulations and surveys containing human ratings. The anomaly scores yielded by the proposed computer model correlate closely with the human ratings of facial differences, leading to 0.942 Pearson’s r score. © 2022, CC BY-NC-SA.

关键词： Generative adversarial networks

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Recent Advancements in Nanophotonics for Optofluidics

arXiv

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arXiv 2024年

作者： Yang, Sen Hong, Chuchuan Zhu, Guodong Anyika, Theodore Hong, Ikjun Ndukaife, Justus C. Institute of Physics Chinese Academy of Sciences Beijing National Laboratory for Condensed Matter Physics Beijing100190 China Department of Chemistry Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States Department of Mechanical Engineering Vanderbilt University NashvilleTN37235 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37240 United States

Optofluidics is dedicated to achieving integrated control of particle and fluid motion, particularly on the micrometer scale, by utilizing light to direct fluid flow and particle motion. The field has seen significant growth recently, driven by the concerted efforts of researchers across various scientific disciplines, notably for its successful applications in biomedical science. In this review, we explore a range of optofluidic architectures developed over the past decade, with a primary focus on mechanisms for precise control of micro and nanoscale biological objects and their applications in sensing. Regarding nanoparticle manipulation, we delve into mechanisms based on optical nanotweezers using nanolocalized light fields and light-based hybrid effects with dramatically improved performance and capabilities. In the context of sensing, we emphasize those works that used optofluidics to aggregate molecules or particles to promote sensing and detection. Additionally, we highlight emerging research directions, encompassing both fundamental principles and practical applications in the field. Copyright © 2024, The Authors. All rights reserved.

关键词： Flow of fluids

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Field-controlled dynamics of skyrmions and monopoles

arXiv

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arXiv 2023年

作者： Tai, Jung-Shen B. Hess, Andrew J. Wu, Jin-Sheng Smalyukh, Ivan I. Department of Physics Chemical Physics Program University of Colorado BoulderCO80309 United States Department of Electrical Computer and Energy Engineering Materials Science and Engineering Program Soft Materials Research Center University of Colorado BoulderCO80309 United States Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado BoulderCO80309 United States

Magnetic monopoles, despite their ongoing experimental search as elementary particles, have inspired the discovery of analogous excitations in condensed matter systems. In chiral condensed matter systems, emergent monopoles are responsible for the onset of transitions between topologically distinct states and phases, like in the case of transitions from helical and conical phase to A-phase comprising periodic arrays of skyrmions. By combining numerical modeling and optical characterizations, we describe how different geometrical configurations of skyrmions terminating at monopoles can be realized in liquid crystals and liquid crystal ferromagnets. We demonstrate how such complex structures can be effectively manipulated by external magnetic and electric fields. Furthermore, we discuss how our findings may hint at similar dynamics in other physical systems, and their potential applications. © 2023, CC BY.

关键词： Liquid crystals

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Gallium Oxide as Photonic Integrated Platforms in the UV–Visible Spectra

Gallium Oxide as Photonic Integrated Platforms in the UV–Vi...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Jingan Zhou Xuan Zhao Rui Xu Xiang Zhang Kai Fu Tao Li Mingfei Xu Shisong Luo Ziyi He Jacob T. Robinson Hanyu Zhu Pulickel M. Ajayan Xiaodong Zhang Yuji Zhao Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA Department of Materials Science and NanoEngineering Rice University Houston TX USA School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona USA Nanofabrication Facility Suzhou Institute of Nano-Tech and Nano-Bionics Chinese Academy of Sciences Suzhou China

We report the Ga 2 O 3 as photonic integrated platforms and its nonlinear optical effects in the UV–visible spectra. A low propagation loss of 3.7 dB/cm and second-order susceptibility of χ (2) =4.89×10 -3 pm... 详细信息

ISBN: (纸本)9781957171258

关键词： Material properties Nonlinear effects Nonlinear susceptibility Optical components Thin films Visible light communications

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Design and Implementation of Smart Street Lighting System Employing Esp-Mesh Network

SSRN

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SSRN 2023年

作者： Fuada, Syifaul Duttagupta, Subhasri Adiono, Trio Siregar, Lindawani Program Studi Sistem Telekomunikasi Universitas Pendidikan Indonesia West Java Province Bandung Indonesia Department of Computer Science and Engineering Amrita Viswa Vidyapeetham Keralam Amritapuri-Campus 690525 India Electrical Engineering Department School of Electrical Engineering and Informatics Institut Teknologi Bandung West Java Province Bandung Indonesia Teaching Factory of Manufacturing Electronics Politeknik Negeri Batam Kepulauan Riau Province Batam Indonesia

Street lighting is a public facility that gives highway users’ convenience during their nighttime trips, making it essential to be controlled and monitored using IoT technology. This study aimed to develop a smart lighting system connected through a Mesh network. The system monitors the street light and automatically controls it using the ESP8266 module, a microcontroller with Wi-Fi built-in. The options in selecting the lamp type include Halogen, Fluorescent, LED, or Incandescent. In general, LED is used because it has an advantage in energy-saving over other lamp types. Moreover, the system is equipped with automatic light intensity control through a dimming technique by Pulse Width Modulation (PWM), while BH1750 is used as a light sensor. Furthermore, it monitors the environmental temperature and humidity using DHT22. The communication between the lighting module is based on ESP-Mesh because each node is connected and forwarding data to the destination and the coverage area. ESP-Mesh allows the wireless network to have a scalable architecture in a broader area. It has features to self-organize and self-configure, implying the network could be built and maintained autonomously. Additionally, the system has a web server service with access to control each node and find out the mesh routing table. The results showed that each node could be configured as a mesh network using ESP8266, which sends dimming commands and reads the sensors. The dimming and intensity control was tested using real public street light called NL200D LED module and an off-the-self dimming control driver module, N-Channel MOSFET FQP30N06L. Furthermore, a Mesh connection was tested using five super bright 3mm LEDs representing real street light due to the limitation of the LED module in the laboratory. The street light has three control modes, including on/off-based, intensity control-based or dimming control manually through the website, and intensity control-based automatically using the two se

关键词： Mesh generation

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Vacuum Ultraviolet Light-Generating Metalens

Vacuum Ultraviolet Light-Generating Metalens

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2022 Conference on Lasers and Electro-Optics Pacific Rim, CLEO-PR 2022

作者： Tseng, Ming Lun Semmlinger, Michael Zhang, Ming Arndt, Catherine Huang, Tzu-Ting Yang, Jian Kuo, Hsin Yu Su, Vin-Cent Chen, Mu Ku Chu, Cheng Hung Cerjan, Benjamin Tsai, Din Ping Nordlander, Peter Halas, Naomi J. Institute of Electronics National Yang Ming Chiao Tung University Hsinchu300 Taiwan Research Center for Applied Sciences Academia Sinica Taipei115 Taiwan Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Laboratory for Nanophotonics Rice University HoustonTX77005 United States Applied Physics Graduate Program Rice University HoustonTX77005 United States Department of Physics and Astronomy Rice University HoustonTX77005 United States Department of Physics National Taiwan University Taipei10617 Taiwan Department of Electrical Engineering National United University Miaoli36003 Taiwan Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong Department of Chemistry Rice University HoustonTX77005 United States

Vacuum ultraviolet (VUV) light is of great importance to many applications such as photochemistry and nanolithography. In this talk, a nonlinear metalens composed of ZnO nanoantennas for VUV generation and focusing wi...

ISBN: (纸本)9798350350012

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Sodium-ion battery cycle life prediction using machine learning

Sodium-ion battery cycle life prediction using machine learn...

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International Conference on Green Energy, Computing and Intelligent Technology 2024 (GEn-CITy 2024)

作者： Linfeng Liu Filbert H. Juwono W. K. Wong Erick Purwanto Tingyan Jin Yuyang Zhen Sustainable Energy Technology Program Xi'an Jiaotong-Liverpool University Suzhou People's Republic of China Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Suzhou People's Republic of China Department of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Department of Computing Xi'an Jiaotong-Liverpool University Suzhou People's Republic of China School of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing People's Republic of China School of Instrument Science and Technology Beijing University of Technology Beijing People's Republic of China

ISBN: (数字)9781837242863

In this study, we explore the classification and prediction capabilities of three models—Genetic programming (GP), Logistic Regression (LR), and the Kolmogorov-Arnold Network (KAN)—on the task of sodium-ion battery life prediction. By leveraging a dataset composed of multiple battery characteristics, we aim to determine the remaining power of sodium-ion batteries using these machine learning models. The KAN model, being a novel approach, demonstrates superior performance across various metrics, including accuracy, precision, recall, and F1 score, when compared to the other two models. This highlights the potential of KAN as a robust model for complex classification tasks in the field of battery life prediction.

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Reducing Effective System Dimensionality with Long-Range Collective Dipole-Dipole Interactions

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Physical Review Letters 2024年第17期132卷 173803-173803页

作者： Ashwin K. Boddeti Yi Wang Xitlali G. Juarez Alexandra Boltasseva Teri W. Odom Vladimir Shalaev Hadiseh Alaeian Zubin Jacob Elmore Family School of Electrical and Computer Engineering Purdue University West Lafayette Indiana 47907 USA Birck Nanotechnology Center Purdue University West Lafayette Indiana 47907 USA Graduate Program in Applied Physics Northwestern University Evanston Illinois 60208 USA Department of Materials Science and Engineering Northwestern University Evanston Illinois 60208 USA Department of Chemistry Northwestern University Evanston Illinois 60208 USA School of Physics and Astronomy Purdue University West Lafayette Indiana 47907 USA

Dimensionality plays a crucial role in long-range dipole-dipole interactions (DDIs). We demonstrate that a resonant nanophotonic structure modifies the apparent dimensionality in an interacting ensemble of emitters, as revealed by population decay dynamics. Our measurements on a dense ensemble of interacting quantum emitters in a resonant nanophotonic structure with long-range DDIs reveal an effective dimensionality reduction to d¯=2.20(12), despite the emitters being distributed in 3D. This contrasts with the homogeneous environment, where the apparent dimension is d¯=3.00. Our work presents a promising avenue to manipulate dimensionality in an ensemble of interacting emitters.

关键词： Light-matter interaction Long-range interactions Metamaterials Optics & lasers Photonics Plasmonics Quantum optics

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Vacuum Ultraviolet Light-Generating Metalens

Vacuum Ultraviolet Light-Generating Metalens

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2022 International Conference on Optics-Photonics Design and Fabrication, ODF 2022

关键词： Nanoclay

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Hierarchical B-Frame Video Coding Using Two-Layer CANF Without Motion Coding

Hierarchical B-Frame Video Coding Using Two-Layer CANF Witho...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： David Alexandre Hsueh-Ming Hang Wen-Hsiao Peng Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

Typical video compression systems consist of two main modules: motion coding and residual coding. This general architecture is adopted by classical coding schemes (such as international standards H.265 and H.266) and deep learning-based coding schemes. We propose a novel B-frame coding architecture based on two-layer Conditional Augmented Normalization Flows (CANF). It has the striking feature of not transmitting any motion information. Our proposed idea of video compression without motion coding offers a new direction for learned video coding. Our base layer is a low-resolution image compressor that replaces the full-resolution motion compressor. The low-resolution coded image is merged with the warped high-resolution images to generate a high-quality image as a conditioning signal for the enhancement-layer image coding in full resolution. One advantage of this architecture is significantly reduced computational complexity due to eliminating the motion information compressor. In addition, we adopt a skip-mode coding technique to reduce the transmitted latent samples. The rate-distortion performance of our scheme is slightly lower than that of the state-of-the-art learned B-frame coding scheme, B-CANF, but outperforms other learned B-frame coding schemes. However, compared to B-CANF, our scheme saves 45% of multiply-accumulate operations (MACs) for encoding and 27% of MACs for decoding. The code is available at https://***.

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