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Anomaly Detection and Imaging with X-Rays (ADIX) VIII 2023

作者： Ruiz, Sarah D. Hurlock, Ava X. Yang, Shu Martinez, Mauricio Thamvichai, Ratchaneekorn Greenberg, Joel A. Ashok, Amit Gehm, Michael E. Duke University Dept. of Electrical and Computer Engineering DurhamNC United States Duke University Medical Physics Program DurhamNC United States University of Arizona TusconAZ United States

ISBN: (纸本)9781510661769

Simulation is a valuable tool for designing and evaluating the performance of x-ray imaging systems. In previous work,1, 2 a hybrid computed tomography(CT) and x-ray diffraction(XRD) imaging system was developed for improved identification of threat objects in checked baggage. Through large-scale simulations of this hybrid CT+XRD system, we can investigate the impact of various parameters on system performance. These parameters include multi-energy acquisitions, varying energy resolution, and additional system views. We will report on our findings and evaluate the system performance resulting from these variations of the simulated system as well as discuss how these findings may influence future system design. © 2023 SPIE.

关键词： computerized tomography

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Design and Optimization of the Porous Metamaterial EM Absorbers in X-band

Design and Optimization of the Porous Metamaterial EM Absorb...

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2023 IEEE Symposium on Electromagnetic Compatibility and Signal/Power Integrity, EMC+SIPI 2023

作者： Anurakparadorn, Kanat Taub, Alan Michielssen, Eric University of Michigan Macromolecular Science and Engineering Program Department of Material Science and Engineering Ann ArborMI United States University of Michigan Department of Mechanical Engineering Ann ArborMI United States University of Michigan Department of Electrical Engineering and Computer Science Ann ArborMI United States

ISBN: (纸本)9798350309768

A strategy that combines experiment and simulation to design and optimize electromagnetic (EM) metamaterial absorbers containing a periodic porous structure is described. The approach provides the ability to produce absorbers that meet multiple user-specified objectives. Using the measured intrinsic properties of the baseline materials as an input to EM-field based computational modelling and optimization, absorption by the studied metamaterials measured by their reflection loss (RL) increases significantly. The resulting metamaterials have the potential for lower cost and lighter weight while providing greater protection than traditional metal gaskets and foams. © 2023 IEEE.

关键词： Metamaterials

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Auxiliary Classifier based Residual RNN for Image Captioning 30

Auxiliary Classifier based Residual RNN for Image Captioning

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30th European Signal Processing Conference, EUSIPCO 2022

作者： Çayli, Özkan Kiliç, Volkan Onan, Aytug Wang, Wenwu Electrical and Electronics Engineering Graduate Program Izmir Katip Çelebi University Turkey Department of Computer Engineering Izmir Katip Çelebi University Turkey University of Surrey United Kingdom

ISBN: (纸本)9789082797091

Image captioning aims to generate a description of visual contents with natural language automatically. This is useful in several potential applications, such as image understanding and virtual assistants. With recent advances in deep neural networks, natural and semantic text generation has been improved in image captioning. However, maintaining the gradient flow between neurons in consecutive layers becomes challenging as the network gets deeper. In this paper, we propose to integrate an auxiliary classifier in the residual recurrent neural network, which enables the gradient flow to reach the bottom layers for enhanced caption generation. Experiments on the MSCOCO and VizWiz datasets demonstrate the advantage of our proposed approach over the state-of-the-art approaches in several performance metrics. © 2022 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Recurrent neural networks

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Dynamics of self-hybridized exciton–polaritons in 2D halide perovskites

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Light(Science & Applications) 2024年第1期13卷 13-22页

作者： Surendra B.Anantharaman Jason Lynch Christopher E.Stevens Christopher Munley Chentao Li Jin Hou Hao Zhang Andrew Torma Thomas Darlington Francis Coen Kevin Li Arka Majumdar PJames Schuck Aditya Mohite Hayk Harutyunyan Joshua R.Hendrickson Deep Jariwala Department of Electrical and Systems Engineering University of PennsylvaniaPhiladelphiaPA19104USA KBR Inc. BeavercreekOH45431USA Air Force Research Laboratory Sensors DirectorateWright-Patterson Air Force BaseOH45433USA Department of Physics University of WashingtonSeattleWA98195USA Department of Physics Emory UniversityAtlantaGA30322USA Department of Chemical and Biomolecular Engineering Rice UniversityHoustonTX77005USA Department of Materials Science and Nanoengineering Rice UniversityHoustonTX77005USA Applied Physics Program Smalley‐Curl InstituteRice UniversityHoustonTX77005USA Department of Mechanical Engineering Columbia UniversityNew YorkNY10027USA Department of Electrical and Computer Engineering University of WashingtonSeattleWA98195USA

Excitons,bound electron–hole pairs,in two-dimensional hybrid organic inorganic perovskites(2D HOIPs)are capable of forming hybrid light-matter states known as exciton-polaritons(E–Ps)when the excitonic medium is confined in an optical *** the case of 2D HOIPs,they can self-hybridize into E–Ps at specific thicknesses of the HOIP crystals that form a resonant optical cavity with the ***,the fundamental properties of these self-hybridized E–Ps in 2D HOIPs,including their role in ultrafast energy and/or charge transfer at interfaces,remain ***,we demonstrate that>0.5µm thick 2D HOIP crystals on Au substrates are capable of supporting multiple-orders of self-hybridized E–P *** E–Ps have high Q factors(>100)and modulate the optical dispersion for the crystal to enhance sub-gap absorption and *** varying excitation energy and ultrafast measurements,we also confirm energy transfer from higher energy E–Ps to lower energy E–***,we also demonstrate that E–Ps are capable of charge transport and transfer at *** findings provide new insights into charge and energy transfer in E–Ps opening new opportunities towards their manipulation for polaritonic devices.

关键词： charge polar excitation

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ReMP: Reusable Motion Prior for Multi-domain 3D Human Pose Estimation and Motion Inbetweening

ReMP: Reusable Motion Prior for Multi-domain 3D Human Pose E...

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IEEE Workshop on Applications of computer Vision (WACV)

作者： Hojun Jang Young Min Kim Dept. of Electrical and Computer Engineering Seoul National University Interdisciplinary Program in Artificial Intelligence and INMC Seoul National University

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

We present Reusable Motion prior (ReMP), an effective motion prior that can accurately track the temporal evolution of motion in various downstream tasks. Inspired by the success of foundation models, we argue that a robust spatio-temporal motion prior can encapsulate underlying 3D dynamics applicable to various sensor modalities. We learn the rich motion prior from a sequence of complete parametric models of posed human body shape. Our prior can easily estimate poses in missing frames or noisy measurements despite significant occlusion by employing a temporal attention mechanism. More interestingly, our prior can guide the system with incomplete and challenging input measurements to quickly extract critical information to estimate the sequence of poses, significantly improving the training efficiency for mesh sequence recovery. ReMP consistently outperforms the baseline method on diverse and practical 3D motion data, including depth point clouds, LiDAR scans, and IMU sensor data. Project page is available in https://***/ReMP.

关键词： Training Point cloud compression Three-dimensional displays Accuracy Tracking Shape Pose estimation Noise Parametric statistics Noise measurement

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Analysis of Selective Emitter Formation Technology of n-TOPCon Solar Cell

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Transactions of the Korean Institute of electrical Engineers 2022年第1期71卷 114-120页

作者： Jeong, Sungjin Cha, Yewon Kim, Sungheon Kim, Hongrae Park, Somin Kim, Taeyong Park, Jinjoo Ju, Minkyu Yi, Junsin Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Korea Republic of Dept. of Energy Convergence Engineering Division of Energy & Optical Technology Convergence Cheongju University Korea Republic of College of Information and Communication Engineering Sungkyunkwan University Korea Republic of

The main efficiency limiting factors for homogeneous emitter solar cells are resistance loss through metal contact on the front side and recombination loss at the surface. Herein, a selective emitter technology is introduced to solve the above problem, and it is currently commercialized in the mainstream p-PERC (Passivated Emitter Rear Contact) solar cell. The selective emitter boosts efficiency by 0.3-0.4% when compared to a homogeneous emitter, and when applied to the n-TOPCon (Tunnel Oxide Passivated Contact) solar cell, high efficiency of 26% or higher may be predicted. The most widely utilized selective emitter technologies are laser and etch-back. The One-Step Technology, which is suited to the n-TOPCon solar cell process, a laser is suitable for mass manufacturing with high yield. Because selective emitters increase electrical characteristics, which impact cell efficiency, it is required to study and create a technology that is optimal for the n-TOPCon manufacturing process. © 2022 Korean Institute of electrical Engineers. All rights reserved.

关键词： Efficiency

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A Performance Study of Selected Machine Learning Techniques for Predicting Heart Diseases 2nd

A Performance Study of Selected Machine Learning Techniques ...

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2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Olorunfemi, Blessing Oluwatobi Ogunde, Adewale Opeoluwa Adeniyi, Abidemi Emmanuel Awotunde, Joseph Bamidele Imoize, Agbotiname Lucky Li, Chun-Ta Faculty of Natural Sciences Department of Computer Science Redeemer’s University Osun Nigeria Department of Computer Science Bowen University Iwo Nigeria Faculty of Information and Communication Sciences Department of Computer Science University of Ilorin Ilorin240003 Nigeria Faculty of Engineering Department of Electrical and Electronics Engineering University of Lagos Lagos Akoka100213 Nigeria Bachelor’s Program of Artificial Intelligence and Information Security Fu Jen Catholic University New Taipei City24206 Taiwan

ISBN: (纸本)9789819777853

Heart Disease remains a leading cause of mortality worldwide. It alarmingly rises at a quick rate, making early heart disease prediction crucial for effective prevention and timely intervention. Heart disease diagnosis is a difficult process that requires technical skills and accuracy to complete. With improvements in technology, computing has lent its voice to simplify the diagnosis of various health problems. Machine learning uses past or existing history to predict future results. Various machine learning techniques have been developed over the years and used in predicting heart diseases with various levels of performance. Identifying the best-suited machine learning technique to use for prediction purposes can be a challenging task. This research work analyses the performance of seven (7) machine learning techniques, comprising AdaBoost Algorithm, KNN, Logistic Regression, Naïve Bayes Classifier, Random Forest, SVM, and XGBoost. The heart disease dataset was downloaded from the UCI repository and analysed using Python programming language in the Jupyter Notebook environment. A comparative analysis of the seven (7) techniques was performed based on Accuracy, Precision, and Recall. From the results obtained, KNN, Random Forest, and XGBoost showed superior performance over the others with an accuracy of 100%, AdaBoost Algorithm followed with an accuracy of 92.2%, SVM followed with an accuracy of 91.71%, Naïve Bayes Classifier followed with an accuracy of 88.29% while Logistic Regression has the least accuracy of 86.34%. KNN, RF, and XGBoost outperformed AdaBoost, SVN, and LR. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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An Improved I-V model for Resistive Random Access Memory

An Improved I-V model for Resistive Random Access Memory

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2022 IEEE International Conference on electrical, computer, and Energy Technologies, ICECET 2022

作者： Chung, Harry Shin, Hyungsoon Sun, Wookyung Park, Jisun Graduate Program in Smart Factory Ewha Womans University Dept. of Electronic and Electrical Engineering Seoul Korea Republic of Seoul National University Department of Electrical and Computer Engineering Seoul Korea Republic of Graduate Program in Smart Factory Ewha Womans University Seoul Korea Republic of

ISBN: (数字)9781665470872

ISBN: (纸本)9781665470872

In this paper, we performed a simulation for a physical resistive random-access device (RRAM) to propose an improved model representing its electrical characteristics. Voltage ThrEshold Adaptive Memristor (VTEAM) model that operates based on the voltage threshold of the device adapted for the RRAM simulation. We applied some physical features to the model to adjust the internal state variable to improve the simulation results. The internal state variable used in the model was designed after the physical feature such as the distance between the end of the filament and the electrode of the device. Therefore, applying some of these physical conditions affects the simulation results. Simulation results with the newly applied model showed optimized I-V characteristics that resemble the physical device's behavior more than the existing model. © 2022 IEEE.

关键词： Memristors

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IoT-based tire pressure monitoring system for air and temperature pressure using MPX5500D and LM35 sensor 8

IoT-based tire pressure monitoring system for air and temper...

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8th IEEE International Conference on Computing, engineering and Design, ICCED 2022

作者： Pangestu, Agung Sodikin, Iing Yusro, Muhammad Sapundani, Rum Al Hakim, Rosyid Ridlo Wilyanti, Sinka Jakarta Global University Faculty of Engineering and Computer Science Electrical Engineering Department Depok Indonesia State University of Jakarta Faculty of Engineering Department of Electronic Engineering Jakarta Indonesia University of Muhammadiyah Purwokerto Electromedical Engineering Technology Faculty of Health Science Purwokerto Indonesia Jakarta Global University Graduate Program in Electrical Engineering Faculty of Engineering and Computer Science Depok Indonesia

ISBN: (纸本)9781665453899

Research has been carried out to monitor vehicle tires before they are used and can reduce damage, including overcoming vehicle fuel waste because air pressure is continuously monitored. This research aims to utilize the MPX5500DP sensor as an air pressure device, the LM35 sensor as a temperature reader, and a buzzer based on IoT to build a tire pressure monitoring system (TPMS). The MPX5500DP and LM35 sensor inputs to the Arduino Uno microcontroller are distributed by the NodeMCU, fitted with a Wi-Fi module. The Blynk application sends and displays the data on a smartphone using the IoT-based. Based on this research, data on the percentage of errors in monitoring air pressure and tire temperature on vehicles were obtained by comparing the data to the pressure gauge and thermometer: 1-the results of the average reading of the sensor error value. MPX5500DP air pressure against pressure gauge is 5.3%. 2-the average reading of the LM35 sensor error value on the temperature thermometer is 6.8%. With this research, the air pressure and temperature in the tires can be monitored in real-Time via a smartphone using the IoT-based. © 2022 IEEE.

关键词： Thermometers

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Information Rates Over DMCs with Many Independent Views

Information Rates Over DMCs with Many Independent Views

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IEEE International Symposium on Information Theory

作者： V. Arvind Rameshwar Nir Weinberger IUDX Program Unit Indian Institute of Science Bengaluru India Department of Electrical and Computer Engineering Technion Haifa Israel

ISBN: (数字)9798350382846

ISBN: (纸本)9798350382853

In this paper, we investigate the fundamental limits of reliable communication over a discrete memoryless channel (DMC) when there are a large number of noisy views of a transmitted symbol, i.e., when several copies of a single symbol are sent independently through the DMC. We argue that the channel capacity and dispersion of such a multi-view DMC converge exponentially quickly in the number of views to to the entropy and varentropy of the input distribution, respectively, and identify the exact rate of convergence. This rate equals the smallest Chernoff information between two conditional distributions of the output given unequal inputs. Our results hence help us characterize the largest finite-blocklength rates achievable for any fixed error probability. We also present a new channel model that we call the Poisson approximation channel-of possible independent interest-whose capacity closely approximates the capacity of the multi-view binary symmetric channel (BSC).

关键词： Monte Carlo methods Error probability Symbols Entropy Memoryless systems Reliability Noise measurement

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