Multi-physics and Multi-scale Electromagnetic Modeling and High Performance Algorithms

2019 ◽  
Author(s):  
Yu Mao Wu ◽  
Ya-Qiu Jin
Keyword(s):  
High Performance ◽  
Electromagnetic Modeling ◽  
Multi Scale

scholarly journals A Fast and Lightweight Method with Feature Fusion and Multi-Context for Face Detection

2018 ◽  
Vol 10 (8) ◽  
pp. 80
Author(s):  
Lei Zhang ◽  
Xiaoli Zhi
Keyword(s):  
Face Detection ◽  
Graphics Processing Units ◽  
High Performance ◽  
Feature Fusion ◽  
Local Context ◽  
Data Set ◽  
Global Context ◽  
Detection Algorithms ◽  
Multi Scale ◽  
Benchmark Datasets

Convolutional neural networks (CNN for short) have made great progress in face detection. They mostly take computation intensive networks as the backbone in order to obtain high precision, and they cannot get a good detection speed without the support of high-performance GPUs (Graphics Processing Units). This limits CNN-based face detection algorithms in real applications, especially in some speed dependent ones. To alleviate this problem, we propose a lightweight face detector in this paper, which takes a fast residual network as backbone. Our method can run fast even on cheap and ordinary GPUs. To guarantee its detection precision, multi-scale features and multi-context are fully exploited in efficient ways. Specifically, feature fusion is used to obtain semantic strongly multi-scale features firstly. Then multi-context including both local and global context is added to these multi-scale features without extra computational burden. The local context is added through a depthwise separable convolution based approach, and the global context by a simple global average pooling way. Experimental results show that our method can run at about 110 fps on VGA (Video Graphics Array)-resolution images, while still maintaining competitive precision on WIDER FACE and FDDB (Face Detection Data Set and Benchmark) datasets as compared with its state-of-the-art counterparts.

Advanced three-dimensional electromagnetic modeling using a nested integral equation approach

2021 ◽  
Author(s):  
Chaojian Chen ◽  
Mikhail Kruglyakov ◽  
Alexey Kuvshinov
Keyword(s):  
Integral Equation ◽  
Three Dimensional ◽  
Region Of Interest ◽  
Electromagnetic Modeling ◽  
Multi Scale ◽  
Scale Modeling ◽  
Uniform Grids ◽  
The Matrix ◽  
Integral Equation Approach ◽  
Matrix Vector

Summary Most of the existing three-dimensional (3-D) electromagnetic (EM) modeling solvers based on the integral equation (IE) method exploit fast Fourier transform (FFT) to accelerate the matrix-vector multiplications. This in turn requires a laterally-uniform discretization of the modeling domain. However, there is often a need for multi-scale modeling and inversion, for instance, to properly account for the effects of non-uniform distant structures, and at the same time, to accurately model the effects from local anomalies. In such scenarios, the usage of laterally-uniform grids leads to excessive computational loads, both in terms of memory and time. To alleviate this problem, we developed an efficient 3-D EM modeling tool based on a multi-nested IE approach. Within this approach, the IE modeling is first performed at a large domain and on a (laterally-uniform) coarse grid, and then the results are refined in the region of interest by performing modeling at a smaller domain and on a (laterally-uniform) denser grid. At the latter stage, the modeling results obtained at the previous stage are exploited. The lateral uniformity of the grids at each stage allows us to keep using the FFT for the matrix-vector multiplications. An important novelty of the paper is a development of a “rim domain” concept which further improves the performance of the multi-nested IE approach. We verify the developed tool on both idealized and realistic 3-D conductivity models, and demonstrate its efficiency and accuracy.

Applying multi-scale silica-like three-dimensional networks in PEO matrix via in-situ crosslinking for high-performance solid composite electrolyte

2021 ◽  
Author(s):  
Jiawei Wu ◽  
Jing Chen ◽  
Xiaodong Wang ◽  
An'an Zhou ◽  
Zhenglong Yang
Keyword(s):  
Solid State ◽  
High Performance ◽  
Low Cost ◽  
Three Dimensional ◽  
Electrochemical Stability ◽  
Composite Electrolyte ◽  
Solid State Electrolyte ◽  
Multi Scale ◽  
In Situ Crosslinking

For the higher safety and energy density, solid-state electrolyte with better mechanical strength, thermal and electrochemical stability is a perfect choice. To improve the performance of PEO, usage of low-cost...

THE ADVANTAGE OFTHEWAVELET TRANSFORM IN PROCESSING OF SPEECH SIGNALS

2021 ◽  
Vol 4 (3) ◽  
pp. 37-41
Author(s):  
Sayora Ibragimova ◽  
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Speech Processing ◽  
High Performance ◽  
Speech Sound ◽  
Digital Signal ◽  
Speech Signals ◽  
Multi Scale ◽  
Processing Of Speech Signals

This work deals with basic theory of wavelet transform and multi-scale analysis of speech signals, briefly reviewed the main differences between wavelet transform and Fourier transform in the analysis of speech signals. The possibilities to use the method of wavelet analysis to speech recognition systems and its main advantages. In most existing systems of recognition and analysis of speech sound considered as a stream of vectors whose elements are some frequency response. Therefore, the speech processing in real time using sequential algorithms requires computing resources with high performance. Examples of how this method can be used when processing speech signals and build standards for systems of recognition.Key words: digital signal processing, Fourier transform, wavelet analysis, speech signal, wavelet transform

Facile preparation of multi-scale nanoarchitectures on cotton fabric with low surface energy for high performance self-cleaning

2020 ◽  
Vol 111 (11) ◽  
pp. 1603-1613
Author(s):  
Shengnan Tian ◽  
Jian Zhao ◽  
Jiahuan He ◽  
Haiting Shi ◽  
Bingqi Jin ◽  
...  
Keyword(s):  
Surface Energy ◽  
Cotton Fabric ◽  
High Performance ◽  
Multi Scale ◽  
Low Surface Energy ◽  
Facile Preparation ◽  
Self Cleaning

Effect of Graphene Oxide on Interfacial Interactions and Fracture Toughness of Basalt Fiber-Reinforced Epoxy Composites

2020 ◽  
Vol 20 (11) ◽  
pp. 6760-6767
Author(s):  
Seong Hwang Kim ◽  
Soo-Jin Park
Keyword(s):  
Mechanical Properties ◽  
Fracture Toughness ◽  
Graphene Oxide ◽  
High Performance ◽  
Basalt Fiber ◽  
Superior Performance ◽  
Microstructured Fibers ◽  
Multi Scale ◽  
Fundamental Understanding ◽  
Interlaminar Shear

Multiscale hierarchy is a promising chemical approach that provides superior performance in syner-gistically integrated microstructured fibers and nanostructured materials in composite applications. The main purpose of this work was to introduce graphene oxide (GO) between an epoxy matrix and basalt fibers to improve mechanical properties by enhancing interfacial adhesion. The composites were reinforced with various concentrations of GO. For all of the fabricated composites, the optimum GO content was found to be 0.5 wt%, which improved the interlaminar shear strength and fracture toughness by 66.2% and 86.1%, respectively, compared with those of neat composites. We observed a direct linear relationship between fracture toughness and certain surface free energy. In addition, the fracture toughness mechanisms were illustrated using a crack theory based on morphology analyses of fracture surfaces. Such an effort could accelerate the conversion of multi-scale composites into high-performance materials and provide rational guidance and fundamental understanding toward realizing the theoretical limits of mechanical properties.

Multi-scale integrated modelling for high performance flexible materials

2012 ◽  
Vol 65 ◽  
pp. 276-286 ◽  
Author(s):  
H. Lin ◽  
R. Ramgulam ◽  
H. Arshad ◽  
M.J. Clifford ◽  
P. Potluri ◽  
...  
Keyword(s):  
High Performance ◽  
Integrated Modelling ◽  
Multi Scale ◽  
Flexible Materials
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