检索结果-内蒙古大学图书馆

23rd International Conference on Numerical Simulation of Optoelectronic Devices, NUSOD 2023

作者： Glennon, John Bellotti, Enrico Boston University Div. of Material Science and Engineering BostonMA02215 United States Boston University Div. of Material Science and Engineering Dep. of Electrical and Computer Engineering BostonMA02215 United States

ISBN: (纸本)9798350314298

Gaussian process regression is used to develop a model for predicting the superlattice (SL) structures grown on a 6.3 Å lattice. This model is used to search for optimized hole transport properties. Nonequilibrium Green's functions calculations are used to determine the vertical hole mobility of the structure which is compared with both the calculated and experimental results for an experimental SL grown on a GaSb substrate. Ultimately, a simple analytical model is used to approximate and compare the quantum efficiency of a photodiode containing each structure demonstrating an improvement in device performance using the optimized SL structure. © 2023 IEEE.

关键词： Gallium compounds

来源：评论

学校读者我要写书评

暂无评论

Quantum transport simulation of a mid-wave infrared Ga-based type-II superlattice for curved focal-plane arrays 13

Quantum transport simulation of a mid-wave infrared Ga-based...

引用

Infrared Sensors, Devices, and Applications XIII 2023

作者： Glennon, John Bellotti, Enrico Div. of Material Science and Engineering Boston University BostonMA02215 United States Dept. of Electrical and Computer Engineering Boston University BostonMA02215 United States

ISBN: (纸本)9781510665880

Type-II strained-layer superlattices have theoretically predicted advantages that make them an attractive material system for use in infrared technology. However, the influence of structural disorder has been demonstrated to negatively impact the performance of these materials. A recent development in infrared technology is the use of curved focal-plane arrays which promise improved uniformity of sensitivity and a reduction in the optical complexity of the device. Curving of the wafer introduces mechanical strain into the absorber layer which can also impact the vertical carrier mobility. This work reports on an analysis of the influence of external strain and disorder on the vertical hole mobility in curved focal-plane arrays utilizing a mid-wave InAs/GaSb absorber layers. A series of quantum transport calculations is performed over a range of strain configurations for two different structures: an ideal superlattice and a superlattice with graded interfaces and disorder. Finally, the impact these effects have on the quantum efficiency of a hypothetical curved-FPA is approximated, and a potential avenue for improved device design is suggested. © 2023 SPIE. All rights reserved.

关键词： Quantum efficiency

来源：评论

学校读者我要写书评

暂无评论

Manifold Compressive Sensing 2D-Direction of Arrival Using Single Pixel Programmable Array

Manifold Compressive Sensing 2D-Direction of Arrival Using S...

引用

Antennas and Propagation & USNC/URSI National Radio Science Meeting

作者： Firas Slewa Dawod Sayan Roy Electrical and Computer Engineering Div. of Energy Matter and Systems University of Missouri-Kansas City MO USA

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

This paper introduces a new approach for determining the direction of arrival (DoA) of a signal with multi-path reflections based on signal spars representation and the Compressive Sensing (CS) algorithms. Employing CS in DoA enables the use of a single-pixel reconfigurable antenna array to detect multipath signals, thus significantly reducing circuit and hardware complexity by utilizing only one common feeding port with a simple circuit interface, thereby lowering footprint and costs. Utilizing a single-pixel programmable antenna array with a mapping of active array elements through biasing diodes, a dynamic aperture with orthogonal manifold paradigms was achieved. The same map would feature various parts of the numerically constructed sensing matrix for CS-DoA. MATLAB was used to model and synthesize both the dynamic aperture measurements and sensing matrix as essential inputs for the presented CS-DoA algorithm. The results confirmed the effectiveness of this innovative algorithm under various noise levels.

关键词： Manifolds Solid modeling Three-dimensional displays Heuristic algorithms Mathematical models Stability analysis Sensors

来源：评论

学校读者我要写书评

暂无评论

Fast Dynamic Time Warping for Temperature Compensation in Guided Waves

e-Journal of Nondestructive Testing

引用

e-Journal of Nondestructive Testing 2024年第6期29卷

作者： Kumar, Narendra Gupta, Payal Carlson, Johan E. Department of Computer Science Electrical and Space Engineering Div. of Signals and Systems Luleå University of Technology Luleå Sweden

The paper discusses Structural Health Monitoring (SHM) based on ultrasonic guided waves for damage detection in structures. Guided waves allow inspection over long distances and inaccessible features, but are also sensitive to changes in environmental and operating conditions (EOC). The focus of this paper is on temperature compensation methods for guided waves. The compensation techniques include Baseline Signal Stretch (BSS), Optimal Baseline Selection (OBS), OBS+BSS, and Dynamic Time-Warping (DTW). In particular, a new, fast approximation of DTW is evaluated and compared with conventional but computationally expensive DTW. The FDTW algorithm utilizes a multilevel approach inspired by graph bisection principles to achieve precise warping path determination with linear computational complexity. The study evaluates the compensation performance of FDTW using a single baseline at a single temperature, thus addressing the complexity and inaccessibility issues of obtaining an extensive database of baseline signals in practical applications. The Open Guided Wave (OGW) dataset is employed for a fair comparison with other compensation methods. Results indicate that FDTW performs well, demonstrating comparable warping performance to DTW but with significantly reduced computational complexity. The analysis also includes comparisons with BSS, OBS+BSS, and DTW across a range of temperatures, highlighting the effectiveness of FDTW in mitigating errors introduced by larger temperature variations. © 2024 The Authors.

关键词： Structural health monitoring

来源：评论

学校读者我要写书评

暂无评论

Advanced Remaining Useful Life of Lithium-Ion Batteries Prediction with Positive and Negative Perceptron and Convolution Neural Network

Advanced Remaining Useful Life of Lithium-Ion Batteries Pred...

引用

International Conference on System Reliability and Science (ICSRS)

作者： Gwiman Bak Eunseo Lee Eunseong Lee Yonghyeon Kim Sang-Yong Rhee Youngchul Bae Dept. of Electrical and Semiconductor Engineering Chonnam National University Yeosu Korea Dept. of Computer Engineering Kyungnam University Changwon Korea Div. of Electrical and Computer Engineering Chonnam National University Yeosu Korea

ISBN: (数字)9798350354508

ISBN: (纸本)9798350354515

Lithium-ion batteries (LIBs) play a significant role in various applications such as electric vehicles, portable electronic devices, and renewable energy storage systems. Accurately predicting the remaining useful life (RUL) of LIBs is essential for enhancing the reliability and efficiency of battery management systems and establishing optimal maintenance plans. In this study, we propose the deep learning network with positive and negative perceptron and convolution neural network (DNPC) that combines the positive and negative perceptron (PNC) model and the convolution neural network (CNN) model, which have high prediction accuracy for the RUL of LIBs. Experimental results using the LIBs dataset show that the root mean square error (RMSE) and mean absolute percentage error (MAPE) for the RUL prediction using test dataset of DNPC are 98.86 [cycle] and 7.25%, respectively, which are lower compared to other deep learning networks (DNNs). Both RMSE and MAPE of the DNPC are also lower compared to other studies using the same LIBs dataset. When analyzing the combination results of the PNC model with other models, the DNN combining the PNC model with the LSTM model has higher RMSE and MAPE, whereas the DNN using the PNC model alone has lower RMSE and MAPE. This means that while the PNC model is suitable for prediction RUL of LIBs, its effectiveness may decrease when combined with recurrent neural network (RNN)-based models. Future research aims to develop a new deep learning model that can enhance synergy with the PNC model and validate their usefulness across various battery types and industrial fields.

关键词： Lithium-ion batteries Deep learning Analytical models Renewable energy sources Recurrent neural networks Convolution Predictive models Reliability engineering Safety Root mean square

来源：评论

学校读者我要写书评

暂无评论

Smart Highways Based Vehicle Speed Sensor With Piezoelectric Energy Harvesting: A Progress Report

Smart Highways Based Vehicle Speed Sensor With Piezoelectric...

引用

2023 IEEE International Conference on Industrial Technology, ICIT 2023

作者： Rall, Keven Charles Bailen, Kara Leah Bender, Elizabeth Nicole Taha, Luay Yassin Abdeltawab, Hussein M Anwar, Sohail Penn State Behrend Electrical and Computer Engineering BehrendPA United States Penn State Altoona Div. of Bus. Eng. and Inf. Sc.and Tech. AltoonaPA United States

ISBN: (纸本)9798350336504

Smart highway and smart road are terms for several different ways of technologies that are incorporated into roads, for improving the operation of connected and autonomous vehicles (CAVs), In our previous work, we completed the design and testing of the preliminary piezoelectric road energy harvester prototype. The prototype outputs electrical pulses when stressed by a vehicle. The aim of this paper is to present our progress work in designing a piezoelectric harvester and speed sensor by embedding, in the asphalt, two piezoelectric modules at a known distance. Each one generates pulses when stressed by the vehicle wheels. These pulses are sent to the Arduino microcontroller. The time delay between the pulses is then estimated using time delay estimation algorithm, then the vehicle speed is computed from the distance to time ratio. The sensing pulses are also converted to DC and used to charge the microcontroller battery. The system is tested for different vehicle speeds. Results have shown considerable accuracy in sensing the vehicle speed when varied from 10 km/h to 240 km/h, and when the input signal-to-noise ratio is varied from 10 dB to 100 dB. © 2023 IEEE.

关键词： Energy harvesting

来源：评论

学校读者我要写书评

暂无评论

Machine-Learning-Assisted Optimization of Type-II Superlattices for Enhanced Vertical Hole Mobility

Machine-Learning-Assisted Optimization of Type-II Superlatti...

引用

International Conference on Numerical Simulation of Optoelectronic Devices, (NUSOD)

作者： John Glennon Enrico Bellotti Div. of Material Science and Engineering Boston University Boston Massachusetts USA Dep. of Electrical and Computer Engineering Div. of Material Science and Engineering Boston University Boston Massachusetts USA

Gaussian process regression is used to develop a model for predicting the superlattice (SL) structures grown on a 6.3 Å lattice. This model is used to search for optimized hole transport properties. Nonequilibrium Green’s functions calculations are used to determine the vertical hole mobility of the structure which is compared with both the calculated and experimental results for an experimental SL grown on a GaSb substrate. Ultimately, a simple analytical model is used to approximate and compare the quantum efficiency of a photodiode containing each structure demonstrating an improvement in device performance using the optimized SL structure.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Application of a Smart Gate Driver to Detect Aging in SiC Power MOSFETs 35

Application of a Smart Gate Driver to Detect Aging in SiC Po...

引用

35th International Symposium on Power Semiconductor Devices and ICs, ISPSD 2023

作者： Wang, Mengqi Zhang, Jiupeng Ng, Wai Tung Nishio, Haruhiko Iwamoto, Motomitsu Sumida, Hitoshi University of Toronto The Edward S. Rogers Sr. Dept. of Electrical & Computer Engineering Toronto Canada Fuji Electric Co. Ltd. Development Div. Electronic Device Business Group Device Development Dept. Matsumoto Japan

ISBN: (纸本)9798350396829

In this paper we present an integrated smart gate driver (SGD) capable of in-operation detection of SiC power MOSFET aging. The SGD IC monitors the discrete time differentiated (DTD) gate voltage slope, Δ VGS, to identify the time to start of the Miller plateau, t1, during turn-on. Under known operating conditions, the value of t1 can be used as an aging indicator to detect changes in the Miller plateau due to threshold voltage shifts. A synthesized digital central control unit (CCU) within the SGD can adjust the gate drive profile and gate drive bus voltage (VDR) based on the aging-induced changes in t1. We demonstrate that following 200 hours of high-temperature gate bias (HTGB) at 200 °C, V DR, stress=30\ V, aging-induced gate degradation of a 1.2 kV 75A SiC MOSFET results in a decrease in drain current (ID) by 1.5%. An increase in VMP by 0.5 V can restore ID by 1.7% to pre-aged levels. This is achieved by adjusting the digital pulse width modulation (PWM) duty cycle of the on-chip DC-DC boost converter. © 2023 IEEE.

关键词： Drain current

来源：评论

学校读者我要写书评

暂无评论

Personalized Stress Detection using a Lightweight Machine Learning Framework With Convenient Wrist-Worn Sensors

Personalized Stress Detection using a Lightweight Machine Le...

引用

2024 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2024

作者： Hasan, M. Mithun, S. Mahmud, M. Baral, S. Poudel, K. Middle Tennessee State University Computational And Data Science MurfreesboroTN United States University Of Memphis Dept. Of Computer Science TN United States University Of Memphis Dept. Of Electrical And Computer Engineering TN United States Middle Tennessee State University Dept. Of Computer Science MurfreesboroTN United States Univ. Of Tennessee Health Science Center Div. Of General Internal Medicine MemphisTN United States

ISBN: (纸本)9798350388572

Over 70% Americans experience daily stress, making real-time, accurate stress detection crucial for timely intervention, and promoting physical and mental well-being. In this study, we detect stress using machine learning from publicly available wrist-worn sensor data. We examined both population and indiv.dual levels, focusing on simple, computation friendly statistical features for reduced processing to facilitate adoptions in real-life mHealth applications. Our framework demonstrates that stress detection achieves over 96% accuracy at both the population and indiv.dual levels, with the Extreme Gradient Boosting classifier achieving the highest predictive accuracy. We found significant variability between indiv.duals and achieved an average accuracy of 99.63% with area under the curve (AUC) 99.23%, F1-score 99.00%, precision, and recall 99.22%. This approach offers a promising solution for real-life stress detection due to its high accuracy and simplicity. © 2024 IEEE.

关键词： LightGBM Machine learning Personalization Stress detection Wrist-band sensors

来源：评论

学校读者我要写书评

暂无评论

Decoding Speech Categorization using Microstate Cortical EEG Signals and Machine Learning

Decoding Speech Categorization using Microstate Cortical EEG...

引用

2024 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2024

作者： Mahmud, M. Hasan, M. Yeasin, M. Bidelman, G. Univ. Of Tennessee Health Science Center Div. Of General Internal Medicine MemphisTN United States Middle Tennessee State University Computational And Data Science MurfreesboroTN United States University Of Memphis Department Of Electrical And Computer Engineering TN United States Indiana University Language And Hearing Sciences Department Of Speech BloomingtonIN United States

ISBN: (纸本)9798350388572

Categorical perception (CP) is a perceptual phenomenon that refers to the tendency of humans to group speech sounds into discrete units. In this work, we used cortical event-related potential (ERP) signals, recorded during a speech identification task, as input to a Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) and machine learning (ML) classifiers to examine how neural signatures of the brain distinguish prototypical vs. ambiguous speech token categories. Particularly, we used extreme gradient boosting (XGBoost), support vector machine, and random forest classifiers. Our analysis shows that using source reconstructed whole-brain data, the XGBoost classifier yielded the best classification accuracy of 94.12% with (area under the curve (AUC) 94.13%, Precision 94.00%, F1-score 94.00%) in the 197-258 ms time window after the stimulus onset. We also identified 15 important brain regions that distinguished vowel classes with accuracy of 90.28% (AUC 90.17%, F1-score 90.00%, Precision 90.00%), 4% less than whole-brain data. Remarkably, out of these 15 critical brain regions, nine were from the left hemisphere, consistent with the left-brain dominance for language processing. The best speech decoding was obtained from early portions of the ERP (~180-320 ms), which corroborates notions that sensory encoding is critical for successful phonetic processing. © 2024 IEEE.

关键词： Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：