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2023 Annual Intermountain engineering, technology and Computing, IETC 2023

作者： Sweeney, Nathaniel Xu, Caroline Shaw, Joseph A. Hocking, Toby D. Whitaker, Bradley M. Montana State University Electrical and Computer Engineering Department United States University of Michigan Electrical Engineering and Computer Science Department United States Montana State University Optical Technology Center United States School of Informatics Computing and Cyber Systems Northern Arizona University United States

ISBN: (纸本)9798350335903

Noninvasive entomological insect monitoring often utilizes a variety of tools such as LiDAR to gather information without interfering with the insects in their habitat. These collection methods often result in large amounts of data that can be te-dious and lengthy to interpret and analyze. Machine learning has been previously used in the past in order to analyze Li-DAR images to detect insects, but often suffers from pitfalls such as long training times and large computational power requirements. In an attempt to offer an alternative that takes little to no training on the data and much less computational power, this paper looks at the use of changepoint detection algorithms to analyze LiDAR images containing insects. By analyzing the rows or columns of a LiDAR image, the algorithms should be able to detect abrupt changes in the image that would represent the insects. While not as accurate, the changepoint detection algorithms give comparable results to a machine learning algorithm tested on the same dataset without the need for supervised training. © 2023 IEEE.

关键词： Anomaly detection

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Effective uniaxial dielectric function tensor and optical phonons in (2¯01)-oriented β-Ga2O3 films with equally distributed sixfold-rotation domains

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Physical Review Applied 2024年第4期22卷 044003页

作者： Alyssa Mock Steffen Richter Alexis Papamichail Vallery Stanishev Misagh Ghezellou Jawad Ul-Hassan Andreas Popp Saud Bin Anooz Daniela Gogova Praneeth Ranga Sriram Krishnamoorthy Rafal Korlacki Mathias Schubert Vanya Darakchieva Department of Electrical and Computer Engineering College of Engineering Applied Science and Technology Solid State Physics and NanoLund Terahertz Materials Analysis Center (THeMAC) and Competence Center for III-Nitride Technology C3NiT - Janzén Department of Physics Chemistry and Biology (IFM) Berlin 12489 Germany Department of Electrical and Computer Engineering Materials Department

Monoclinic β-Ga2O3 films grown on c-plane sapphire have been shown to exhibit six (2¯01)-oriented domains, which are equally spaced by rotation around the surface normal and equally sized by volume that render the film optical response effectively uniaxial. We derive and discuss an optical model suitable for ellipsometry data analysis of such films. We model mid- and far-infrared ellipsometry data from undoped and electrically insulating films with an effective uniaxial dielectric tensor based on projections of all phonon modes within the rotation domains parallel and perpendicular to the sample normal, i.e., to the reciprocal lattice vector g2¯01. Two effective response functions are described by the model, and found sufficient to calculate ellipsometry data that best match measured ellipsometry data from a representative film. We propose to render either effective dielectric functions, or inverse effective dielectric functions, each separately for electric field directions parallel and perpendicular to g2¯01, by sums of Lorentz oscillators, which permit determination of either sets of transverse optical phonon-mode parameters, or sets of longitudinal optical phonon-mode parameters, respectively. Transverse optical modes common to both dielectric functions can be traced back to single-crystal modes with Bu character, while modes with Au character appear only within the dielectric function for polarization perpendicular to the sample surface. The thereby obtained parameter sets reveal all phonon modes anticipated from averaging over the sixfold-rotation domains of single crystal β-Ga2O3, but with slightly shifted transverse optical, and completely different longitudinal optical phonon modes. Structural analysis of the film revealed virtually strain-free material. We suggest small crystal grains and high density of grain boundaries as a possible origin for the observed transverse optical phonon-frequency shifts with respect to bulk material. The differences in longit

关键词： Dielectric properties Optical phonons Optoelectronics Semiconductor compounds Transparent conducting oxides Wide band gap systems Ellipsometry Infrared techniques

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Multidomain Object Detection Framework Using Feature Domain Knowledge Distillation

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IEEE Transactions on Cybernetics 2024年第8期54卷 4643-4651页

作者： Jaw, Da-Wei Huang, Shih-Chia Lu, Zhi-Hui Fung, Benjamin C. M. Kuo, Sy-Yen National Taiwan University Department of Electrical Engineering Taipei106 Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei106 Taiwan Fudan University School of Computer Science The Engineering Research Center of Cyber Security Auditing and Monitoring Ministry of Education Shanghai200433 China McGill University School of Information Studies MontrealQCH3A 1X1 Canada

Object detection techniques have been widely studied, utilized in various works, and have exhibited robust performance on images with sufficient luminance. However, these approaches typically struggle to extract valuable features from low-luminance images, which often exhibit blurriness and dim appearence, leading to detection failures. To overcome this issue, we introduce an innovative unsupervised feature domain knowledge distillation (KD) framework. The proposed framework enhances the generalization capability of neural networks across both low- and high-luminance domains without incurring additional computational costs during testing. This improvement is made possible through the integration of generative adversarial networks and our proposed unsupervised KD process. Furthermore, we introduce a region-based multiscale discriminator designed to discern feature domain discrepancies at the object level rather than from the global context. This bolsters the joint learning process of object detection and feature domain distillation tasks. Both qualitative and quantitative assessments shown that the proposed method, empowered by the region-based multiscale discriminator and the unsupervised feature domain distillation process, can effectively extract beneficial features from low-luminance images, outperforming other state-of-the-art approaches in both low- and sufficient-luminance domains. © 2013 IEEE.

关键词： Feature extraction

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Effect of helium-ion implantation on 3C-SiC nanomechanical string resonators

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Physical Review Applied 2024年第3期22卷 034036页

作者： Philipp Bredol Felix David Nagesh S. Jagtap Yannick S. Klaß Georgy V. Astakhov Artur Erbe Eva M. Weig Department of Electrical Engineering School of Computation Information and Technology Institute of Ion Beam Physics and Materials Research Faculty of Physics TU Dresden 01069 Dresden Germany Faculty of Electrical and Computer Engineering TU Dresden 01069 Dresden Germany 80799 Munich Germany TUM Center for Quantum Engineering (ZQE) 85748 Garching Germany

Hybrid quantum devices enable novel functionalities by combining the benefits of different subsystems. Particularly, point defects in nanomechanical resonators made of diamond or silicon carbide (SiC) have been proposed for precise magnetic field sensing and as versatile quantum transducers. However, the realization of a hybrid system may involve trade-offs in the performance of the constituent subsystems. In a spin-mechanical system, the mechanical properties of the resonator may suffer from the presence of engineered defects in the crystal lattice. This may severely restrict the performance of the resulting device and needs to be carefully explored. Here we focus on the impact of defects on high-Q nanomechanical string resonators made of prestressed 3C-SiC grown on Si(111). We use helium-ion implantation to create point defects and study their accumulated effect on the mechanical performance. Using Euler-Bernoulli beam theory, we present a method to determine Young’s modulus and the prestress of the strings. We find that Young’s modulus is not modified by implantation. Under implantation doses relevant for single-defect or defect-ensemble generation, both tensile stress and damping rate also remain unaltered. For a higher implantation dose, both exhibit a characteristic change.

关键词： Elastic deformation Point defects Quantum information with hybrid systems Stress Micromechanical & nanomechanical oscillators Single crystal materials Transducers Ion implantation

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Quantum Fourier Transform Using Dynamic Circuits

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Physical Review Letters 2024年第15期133卷 150602页

作者： Elisa Bäumer Vinay Tripathi Alireza Seif Daniel Lidar Derek S. Wang IBM Quantum 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

In dynamic quantum circuits, classical information from midcircuit measurements is fed forward during circuit execution. This emerging capability of quantum computers confers numerous advantages that can enable more efficient and powerful protocols by drastically reducing the resource requirements for certain core algorithmic primitives. In particular, in the case of the n-qubit quantum Fourier transform followed immediately by measurement, the scaling of resource requirements is reduced from O(n2) two-qubit gates in an all-to-all connectivity in the standard unitary formulation to O(n) midcircuit measurements in its dynamic counterpart without any connectivity constraints. Here, we demonstrate the advantage of dynamic quantum circuits for the quantum Fourier transform on IBM’s superconducting quantum hardware with certified process fidelities of >50% on up to 16 qubits and >1% on up to 37 qubits, exceeding previous reports across all quantum computing platforms. These results are enabled by our contribution of an efficient method for certifying the process fidelity, as well as of a dynamical decoupling protocol for error suppression during midcircuit measurements and feed forward within a dynamic quantum circuit that we call “feed-forward-compensated dynamical decoupling.” Our results demonstrate the advantages of leveraging dynamic circuits in optimizing the compilation of quantum algorithms.

关键词： Measurement-based quantum computing Quantum algorithms Quantum benchmarking Quantum circuits

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Real-Time Tunable Gas Sensing Platform Based on SnO_(2) Nanoparticles Activated by Blue Micro-Light-Emitting Diodes

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Nano-Micro Letters 2024年第12期16卷 103-119页

作者： Gi Baek Nam Jung-El Ryu Tae Hoon Eom Seung Ju Kim Jun Min Suh Seungmin Lee Sungkyun Choi Cheon Woo Moon Seon Ju Park Soo Min Lee Byungsoo Kim Sung Hyuk Park Jin Wook Yang Sangjin Min Sohyeon Park Sung Hwan Cho Hyuk Jin Kim Sang Eon Jun Tae Hyung Lee Yeong Jae Kim Jae Young Kim Young Joon Hong Jong-In Shim Hyung-Gi Byun Yongjo Park Inkyu Park Sang-Wan Ryu Ho Won Jang Department of Materials Science and Engineering Seoul National UniversitySeoul 08826Republic of Korea Research Laboratory of Electronics Department of Mechanical EngineeringMassachusetts Institute of TechnologyCambridgeMA 02139USA Ming Hsieh Department of Electrical and Computer Engineering University of Southern CaliforniaLos AngelesCA 90089USA Department of Display Materials Engineering Soonchunhyang UniversityAsan 31538Republic of Korea Department of Photonics and Nanoelectronics BK21 FOUR ERICA-ACE CenterHanyang University ERICAAnsan 15588Republic of Korea Department of Nanotechnology and Advanced Materials Engineering Sejong UniversitySeoul 05006Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok 25913Republic of Korea Advance Institute of Convergence Technology Seoul National UniversitySuwon 16229Republic of Korea Department of Mechanical Engineering Korea Advanced Institute of Science and TechnologyDaejeon 34141Republic of Korea Department of Physics Chonnam National UniversityGwangju 500-757Republic of Korea

Micro-light-emitting diodes(μLEDs)have gained significant interest as an activation source for gas sensors owing to their advantages,including room temperature operation and low power ***,despite these benefits,challenges still exist such as a limited range of detectable gases and slow *** this study,we present a blueμLED-integrated light-activated gas sensor array based on SnO_(2)nanoparticles(NPs)that exhibit excellent sensitivity,tunable selectivity,and rapid detection with micro-watt level power *** optimal power forμLED is observed at the highest gas response,supported by finite-difference time-domain ***,we first report the visible light-activated selective detection of reducing gases using noble metal-decorated SnO_(2)*** noble metals induce catalytic interaction with reducing gases,clearly distinguishing NH3,H2,and ***-time gas monitoring based on a fully hardwareimplemented light-activated sensing array was demonstrated,opening up new avenues for advancements in light-activated electronic nose technologies.

关键词： Micro-LED Gas sensor array Low power consumption Metal decoration Real-time detection

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Soft,full Wheatstone bridge 3D pressure sensors for cardiovascular monitoring

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npj Flexible Electronics 2024年第1期8卷 910-917页

作者： Yoonseok Park Haiwen Luan Kyeongha Kwon Ted S.Chung Seyong Oh Jae-Young Yoo Gooyoon Chung Junha Kim Suhyeon Kim Sung Soo Kwak Junhwan Choi Hoang-Phuong Phan Seonggwang Yoo Hyoyoung Jeong Jaeho Shin Sang Min Won Hong-Joon Yoon Yei Hwan Jung John A.Rogers Department of Advanced Materials Engineering for Information and Electronics Integrated Education Institute for Frontier Science&Technology(BK21 Four)Kyung Hee UniversityYongin-siGyeonggi-do 17104Republic of Korea Department of Mechanical and Aerospace Engineering University of California San DiegoLa JollaCA 92093USA School of Electrical Engineering Korea Advanced Institute of Science and TechnologyDaejeonRepublic of Korea Department of Mechanical Engineering Columbia UniversityNew YorkNYUSA Division of Electrical Engineering Hanyang University ERICAAnsan 15588Republic of Korea Department of Semiconductor Convergence Engineering Sungkyunkwan UniversitySuwonRepublic of Korea Biomedical Research Division Korea Institute of Science and TechnologySeoul 02792Republic of Korea Department of Chemical Engineering Dankook UniversityYonginGyeonggi-do 16890Republic of Korea School of Mechanical and Manufacturing Engineering Tyree Institute of Health EngineeringUniversity of New South WalesSydneyNSW 2052Australia Querrey Simpson Institute for Bioelectronics Northwestern University EvanstonEvanstonIL 60208USA Department of Electrical and Computer Engineering University of California DavisDavisCA 95616USA Department of Electrical and Computer Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon-siGyeonggi-do 16419Republic of Korea Department of Electronic Engineering Gachon UniversitySeongnamsiGyeonggi-do 13120Republic of Korea Department of Electronic Engineering Hanyang UniversitySeoulRepublic of Korea Department of Materials Science and Engineering Biomedical EngineeringNeurological SurgeryChemistryMechanical EngineeringElectrical Engineering and Computer Science Simpson Querrey Institute and Feinberg Medical SchoolCenter for Bio-Integrated ElectronicsNorthwestern University EvanstonEvanstonIL 60208USA

Variations in parameters associated with the ambient environment can introduce noise in soft,body-worn *** example,many piezoresistive pressure sensors exhibit a high degree of sensitivity to fluctuations in temperature,thereby requiring active compensation *** research presented here addresses this challenge with a multilayered 3D microsystem design that integrates four piezoresistive sensors in a full-Wheatstone bridge *** optimized layout of the sensors relative to the neutral mechanical plane leads to both an insensitivity to temperature and an increased sensitivity to pressure,relative to previously reported devices that rely on similar operating *** this 3D pressure sensor into a soft,flexible electronics platform yields a system capable of real-time,wireless measurements from the surface of the *** above the radial and carotid arteries yields high-quality waveforms associated with pulsatile blood flow,with quantitative correlations to blood *** results establish the materials and engineering aspects of a technology with broad potential in remote health monitoring.

关键词： Wheat bridge thereby

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Ferroelectric Enhancement in a TiN/Hf1-xZrxO2/W Device with Controlled Oxidation of the Bottom Electrode

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ACS Applied Electronic Materials 2024年第2期6卷 1078-1086页

作者： Chiniwar, Santosh P. Hsieh, Ya-Chen Shih, Ching-Hsiang Teng, Chih-Yu Yang, Jheng-Lin Hu, Chenming Lin, Bi-Hsuan Tang, Mau-Tsu Tseng, Yuan-Chieh Department of Material Science & Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan International College of Semiconductor Technology National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States National Synchrotron Radiation Research Center Hsinchu30076 Taiwan

Hf1-xZxO2 (HZO) is a promising ferroelectric (FE) material with CMOS compatibility, while the TiN/HZO/W metal-ferroelectric-metal structure provides balanced thermal expansion for stacking. In this study, we developed a 7 nm film of HZO with a FE polarization (2Pr) value of ∼43 μC/cm2 and cycling endurance of 108 by determining the appropriate oxidation state for a W bottom electrode deposited via atomic layer deposition with a relatively low annealing temperature of 400 °C. To visualize FE uniformity, we used X-ray absorption spectroscopy phase mapping to construct a two-dimensional map of the orthorhombic (O), tetragonal (T), and monoclinic (M) phases of the HZO film. Subsequent orientation- and chemical-state-resolved X-ray analysis revealed that the enhanced FE polarization performance can be attributed to the combined effects of interface strain and oxygen vacancies. Piezoelectric force microscopy verified the switching uniformity of the devices and revealed the electrical characteristics for use in device optimization. © 2024 The Authors. Published by American Chemical Society

关键词： X ray diffraction analysis

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Advanced BERT and CNN-Based computational Model for Phishing Detection in Enterprise Systems

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computer Modeling in engineering & Sciences 2024年第12期141卷 2165-2183页

作者： Brij B.Gupta Akshat Gaurav Varsha Arya Razaz Waheeb Attar Shavi Bansal Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Business Administration Asia UniversityTaichung413Taiwan Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon College of Business Administration Management DepartmentPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Research and Innovation Insights2TechinfoJaipur302001India Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Electronic Engineering and Computer Science Hong Kong Metropolitan University(HKMU)Hong Kong518031China

Phishing attacks present a serious threat to enterprise systems,requiring advanced detection techniques to protect sensitive *** study introduces a phishing email detection framework that combines Bidirectional Encoder Representations from Transformers(BERT)for feature extraction and CNN for classification,specifically designed for enterprise information ***’s linguistic capabilities are used to extract key features from email content,which are then processed by a convolutional neural network(CNN)model optimized for phishing *** an accuracy of 97.5%,our proposed model demonstrates strong proficiency in identifying phishing *** approach represents a significant advancement in applying deep learning to cybersecurity,setting a new benchmark for email security by effectively addressing the increasing complexity of phishing attacks.

关键词： Phishing BERT convolutional neural networks email security deep learning

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IDSDeep-CCD: intelligent decision support system based on deep learning for concrete cracks detection

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Multimedia Tools and Applications 2025年第12期84卷 10013-10026页

作者： Abualigah, Sayel M. Al-Naimi, Ahmad F. Sachdeva, Gagan AlAmri, Omran Abualigah, Laith Department of Computer Information Systems Jordan University of Science and Technology Irbid Jordan Gagan Sachdeva Dubai United Arab Emirates Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan Computer Science Department Al al-Bayt University Mafraq25113 Jordan Research Center University of Tabuk Tabuk71491 Saudi Arabia MEU Research Unit Middle East University Amman11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia Applied Science Research Center Applied Science Private University Amman11931 Jordan College of Engineering Yuan Ze University Taoyuan32003 Taiwan

In an era where Intelligent Decision Support Systems (IDSS) are integral to managing the vast data from Internet of Everything (IoE) systems, this study introduces IDSDeep-CCD, a novel IDSS approach for detecting concrete cracks, a critical issue in civil infrastructure maintenance. Traditional visual inspection methods for crack detection are time-consuming and error-prone. To address this, IDSDeep-CCD employs deep learning, utilizing an open-source dataset of concrete crack images for enhanced accuracy. The system's two-stage approach, featuring feature extraction via pre-trained models and a fully connected network for classification, significantly outperforms existing methods. Our results demonstrate a remarkable 99.9% accuracy rate in crack detection without data augmentation, marking a notable advancement in automatic detection technology. This breakthrough offers practical benefits for the industry by enabling more precise and efficient identification of concrete cracks, paving the way for timely and accurate remedial actions. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Deep neural networks

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