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Measuring 3D Chemistry at 1 nm Resolution with Fused Multi-Modal Electron Tomography

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 1394-1395页

作者： Schwartz, Jonathan Di, Zichao Wendy Jiang, Yi Cho, Min Gee Qian, Yiwen Gu, Junsi Rozeveld, Steve Ercius, Peter Fessler, Jeffrey A. Xu, Ting Scott, Mary Hovden, Robert Department of Materials Science and Engineering University of Michigan Ann Arbor MI United States Mathematics and Computer Science Division Argonne National Laboratory Lemont IL United States Advanced Photon Source Argonne National Laboratory Lemont IL United States Department of Materials Science and Engineering University of California at Berkeley Berkeley CA United States National Center for Electron Microscopy Lawrence Berkeley National Laboratory Berkeley CA United States Dow Chemical Co. Midland MI United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI United States Materials Science Division Lawrence Berkeley National Laboratory Berkeley CA United States Applied Physics Program University of Michigan Ann Arbor MI United States

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Improved Metaheuristics with Machine Learning Enabled Medical Decision Support System

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computers, materials & Continua 2022年第11期73卷 2423-2439页

作者： Sara A.Althubiti JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Romany F.Mansour Fayadh Alenezi Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Research Center-CIENS Escuela Naval de Suboficiales A.R.C.“Barranquilla”BarranquillaColombia Electronics and Telecommunications Engineering Program Universidad Autónoma del CaribeBarranquilla080001Colombia Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080001Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080001Colombia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga 72511Egypt Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia

Smart healthcare has become a hot research topic due to the contemporary developments of Internet of Things(IoT),sensor technologies,cloud computing,and ***,the latest advances of Artificial Intelligence(AI)tools find helpful for decision-making in innovative healthcare to diagnose several *** Cancer(OC)is a kind of cancer that affects women’s ovaries,and it is tedious to identify OC at the primary stages with a high mortality *** OC data produced by the Internet of Medical Things(IoMT)devices can be utilized to differentiate *** this aspect,this paper introduces a new quantum black widow optimization with a machine learningenabled decision support system(QBWO-MLDSS)for smart *** primary intention of the QBWO-MLDSS technique is to detect and categorize the OC rapidly and ***,the QBWO-MLDSS model involves a Z-score normalization approach to pre-process the *** addition,the QBWO-MLDSS technique derives a QBWO algorithm as a feature selection to derive optimum feature ***,symbiotic organisms search(SOS)with extreme learning machine(ELM)model is applied as a classifier for the detection and classification of ELM model,thereby improving the overall classification *** design of QBWO and SOS for OC detection and classification in the smart healthcare environment shows the study’s *** experimental result analysis of the QBWO-MLDSS model is conducted using a benchmark dataset,and the comparative results reported the enhanced outcomes of the QBWO-MLDSS model over the recent approaches.

关键词： Ovarian cancer decision support system smart healthcare IoMT deep learning feature selection

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Micro-Mechanical Investigation of Process-Induced Fiber Waviness in Thermoplastic Composites 38

Micro-Mechanical Investigation of Process-Induced Fiber Wavi...

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38th Technical Conference of the American Society for Composites, ASC 2023

作者： Chen, Branndon R. Parambil, Nithin K. Deitzel, Joseph M. Gillespie, John W. Center for Composite Materials University of Delaware NewarkDE19716 United States Department of Materials Science and Engineering University of Delaware NewarkDE19716 United States Department of Mechanical Engineering University of Delaware NewarkDE19716 United States Department of Civil and Environmental Engineering University of Delaware NewarkDE19716 United States Department of Computer and Electrical Engineering University of Delaware NewarkDE19716 United States

ISBN: (纸本)9781605956916

Thermoplastic carbon fiber reinforced polymer (CFRPs) composite materials are attractive for their higher throughput, chemical resistance, and higher toughness compared to their thermoset counterparts. One challenge of processing these materials is controlling the process induced wrinkle/waviness formation arising from the high temperature change from process to room temperature. The process induced waviness is a significant microstructural defect that negatively affects the static and fatigue properties of the CFRP. This study offers a micromechanical approach to isolate, visualize, and monitor the development of fiber waviness as a function of process temperature, temperature dependent viscosity, and polymer crystallization. The approach utilizes a single AS4 carbon fibers (7 µm nominal diameter) in a thin film. Three different matrix polymers are studied: amorphous polyetherimide (PEI) and semicrystalline low-melt poly-aryl-ether-ketone (LM-PAEK) and polypropylene (PP). A key observation is that fiber waviness initiates during cooling from the melt processing temperature (where all polymers are amorphous) and ceases at a temperature associated with a critical viscosity level (40,000 P) for all three matrix resins (PEI, PP, LM-PAEK) having very different ranges of temperature dependent viscosity. The magnitude of the fiber waviness was measured in a hot-stage microscope by observing fiber waviness upon cooling the micro-composites from various starting temperatures. In the case of LM-PAEK and PP, the critical viscosity (40,000 P) occurs during the onset of crystallization (cooling rate dependent). The amplitude of the fiber waviness does not increase further due to crystallization shrinkage. Amorphous PEI polymer at the recommended process temperature of 335 °C exhibits a viscosity approximately equal to the critical value of 40,000 P and the fiber remains straight through the entire cooling process to room temperature confirming the important role of viscosity on

关键词： Polypropylenes

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Selective Area Growth of Ga-and N-Polar InGaN/GaN Nanowires - A Comparative Study

Selective Area Growth of Ga-and N-Polar InGaN/GaN Nanowires ...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Arnob Ghosh Kamruzzaman Khan Shrivatch Sankar Elaheh Ahmadi Shamsul Arafin Department of Electrical and Computer Engineering The Ohio State University Columbus OH USA Department of Materials Science and Engineering University of Michigan Ann Arbor MI USA

InGaN quantum disks in GaN nanowires are grown on both Ga-and N-polar GaN templates. Comparative analysis indicates superior geometric control in N-polar GaN with higher vertical, reduced lateral growth rates, flat to... 详细信息

ISBN: (纸本)9798350369311

关键词： Lasers and electrooptics Nanowires Electro-optical waveguides

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Wide field-of-view metalens: a tutorial

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Advanced Photonics 2023年第3期5卷 1-21页

作者： Fan Yang Mikhail YShalaginov Hung-I Lin Sensong An Anu Agarwal Hualiang Zhang Clara Rivero-Baleine Tian Gu Juejun Hu Massachusetts Institute of Technology Department of Materials Science and EngineeringCambridgeMassachusettsUnited States University of Massachusetts Lowell Department of Electrical and Computer EngineeringLowellMassachusettsUnited States Lockheed Martin Corporation OrlandoFloridaUnited States Massachusetts Institute of Technology Materials Research LaboratoryCambridgeMassachusettsUnited States

Wide field-of-view(FOV)optics are essential components in many optical systems,with applications spanning imaging,display,sensing,and beam *** refractive wide FOV optics often involve multiple stacked lenses,resulting in large size and weight as well as high *** lenses or metalenses promise a viable solution to realizing wide FOV optics without complex lens *** review the various architectures of wide FOV metalenses,elucidate their fundamental operating principles and design trade-offs,and quantitatively evaluate and contrast their imaging *** applications enabled by wide FOV metasurface optics are also discussed.

关键词： metasurface lens imaging field of view aberration

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Estimation of Energy and Time Usage in 3D Printing With Multimodal Neural Network 4

Estimation of Energy and Time Usage in 3D Printing With Mult...

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4th International Conference on Frontiers Technology of Information and computer, ICFTIC 2022

作者： Cheng, Qisen Zhang, Chang Shen, Xiang University of Michigan Department of Electrical Engineering and Computer Science Ann Arbor United States University of Minnesota Department of Chemical Engineering and Materials Science Minneapolis United States Georgia Washington University Department of Statistics WashingtonDC United States

ISBN: (纸本)9798350321951

Estimation of resources (i.e. energy and time) consumed in the 3D printing process provides critical information for resource-efficient planning, designing and manufacturing. The existing approaches predict the resource usage by either making calculations based on numerical control (NC) codes or generating estimations by processing digital 3D models. On one hand, the former approach usually requires laborious experiments to calibrate the resources consumption of different printing actions by running human selected NC codes segments. On the other hand, the later approach is often less accurate due to the lack of printing process information (i.e. trajectory, velocity, temperature, etc.) varying significantly over different machines. In this paper, we present a deep learning-based approach that addresses those issues. Our model 1) directly learns from the NC code files accumulated in 3D printing, without human intervention, and 2) leverages the information from both 3D models and NC codes to yield improved estimations. Our approach achieves mathbf{R}^{mathbf{2}} > mathbf{0}.mathbf{93} on real-world 3D printing datasets. © 2022 IEEE.

关键词： 3D printing

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Effect of Parasitic Leakage Currents Associated with the Regrown Aperture of AlGaN/GaN Current Aperture Vertical Electron Transistors (CAVETs)

Effect of Parasitic Leakage Currents Associated with the Reg...

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IEEE Electron Devices Technology and Manufacturing Conference (EDTM)

作者： Sara Pouladi Jae Hyun Ryou Department of Mechanical Engineering Texas Center for Superconductivity at UH Advanced Manufacturing Institute University of Houston USA Department of Electrical and Computer Engineering Materials Science and Engineering Program University of Houston USA

We present a numerical simulation on the effect of leakage paths in the regrown GaN layer in the aperture and above the current blocking layer (CBL) of current aperture vertical electron transistor (CAVET) devices. Here, a 2D TCAD modeling is employed to simulate a CAVET device structure considering two main origins of parasitic leakage current from CBL/regrown-GaN interface and gate/regrown-GaN bulk and their degree of detrimental effect on the characteristics of AlGaN/GaN CAVETs.

关键词： Performance evaluation Apertures Logic gates Numerical simulation Wide band gap semiconductors Numerical models Leakage currents

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An Optimal Framework for SDN Based on Deep Neural Network

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computers, materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

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Development of Support Vector Machine Method to Forecast Dengue-Endemic Areas

Development of Support Vector Machine Method to Forecast Den...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Meileni, Hetty Ermatita Abdiansah Husni, Nyayu Latifah Desmawati Doctoral Program in Engineering Science Palembang30139 Indonesia Universitas Sriwijaya Faculty of Computer Science Palembang30139 Indonesia Palembang30139 Indonesia Politeknik Negeri Sriwijaya Palembang Department of Electrical Engineering Palembang30139 Indonesia Universitas Pembangunan Nasional Veteran Jakarta Faculty of Health Science Jakarta12450 Indonesia

ISBN: (纸本)9798350307306

The cases of dengue hemorrhagic fever (DHF) in Indonesia have increased significantly since 2020. Data shown by the Central Statistics Agency, for example, in South Sumatra Province, there were 6,348 cases of DHF during that period. To suppress the case number of DHF, forecasting areas that are susceptible to this disease is urgently needed. This research aims to develop a machine learning method Support Vector Machine (SVM). The data used include area data, population density data, weather data, and dengue fever case data. The development of the SVM model is carried out using a machine learning method that combines regional data, population density data, weather data, and dengue case data. In the end, using the SVM method can be used to forecast dengue-endemic areas, so that the government and society can take further action to reduce the negative impact of DHF. © 2023 IEEE.

关键词： Forecasting

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Maximizing the Thermal Performance of Microheaters for Non-Volatile Phase Change Photonics: A Comparative Study of Pulse Width Parameter Effects 23

Maximizing the Thermal Performance of Microheaters for Non-V...

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23rd IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems, ITherm 2024

作者： F., Vasquez-Aza H., Sun C., Lian Y.-S., Huang S.A., Vitale I., Takeuchi J., Hu N., Youngblood C.A.R., Ocampo G., Pavlidis University of Connecticut School of Mechanical Aerospace and Manufacturing Engineering StorrsCT06269 United States University of Maryland Department of Materials Science and Engineering College ParkMD20742 United States University of Maryland Institute for Research in Electronics and Applied Physics College ParkMD20742 United States Mit Lincoln Laboratory Advanced Materials and Microsystems Group LexingtonMA02139 United States University of Maryland Quantum Materials Center Department of Physics College ParkMD20742 United States Massachusetts Institute of Technology Department of Materials & Science Engineering CambridgeMA02139 United States The University of Pittsburgh Electrical & Computer Engineering Department PittsburghPA15213 United States

ISBN: (数字)9798350364330

ISBN: (纸本)9798350364330

Guiding, manipulating, and detecting light is integral to modern photonic systems that can be designed for displays, memory, data transfer, and sensors. The prospect of realizing programmable yet zero-static power photonics has recently gained attention thanks to the rise of optical phase change materials (PCMs). PCMs have a unique set of properties that make them desirable for this task: nonvolatile retention and reversible switching between their amorphous and crystalline states, which, in addition, display distinct optical and electronic properties. Nonvolatile photonic devices have primarily relied on either electrical or optical switching of PCMs. electrical switching offers effortless CMOS integration;however, it is predominantly limited to binary output. In contrast, optical switching enables accurate multilevel control but is limited in scalability. This paper studies an alternative electro-thermal approach to nonvolatile photonics by controlling the PCM phase via doped silicon microheaters. The results highlight the significance of precise spatial and temporal temperature control to ensure optimal modulation of the PCM. Specifically, this paper investigates the impact of the electric pulse width (0.2 μs to 10 μs) on the maximum temperature for two different microheater designs. High resolution (≈410 nm) transient thermoreflectance imaging (TTI) is used to measure and analyze the surface temperature distribution across each microheater under pulsed biasing. To assess the impact of varying pulse widths, this study systematically examines their effects on maximum temperature, response time, and maximum power. Shorter pulse widths ( 1 μs) provide greater thermal stability but exhibit reduced maximum temperatures due to limited current levels. The experimental results demonstrate a nonlinear relationship between the peak temperature and the power supplied at sub-steady state thermalization time scales. For the specific microheater geometry, the optimal pulse wid

关键词： Photonic integration technology

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