Hermite finite elements for high accuracy electromagnetic field calculations: A case study of homogeneous and inhomogeneous waveguides

2016 ◽  
Vol 119 (14) ◽  
pp. 143106 ◽  
Author(s):  
C. R. Boucher ◽  
Zehao Li ◽  
C. I. Ahheng ◽  
J. D. Albrecht ◽  
L. R. Ram-Mohan
Keyword(s):  
Electromagnetic Field ◽  
Finite Elements ◽  
High Accuracy ◽  
Hermite Finite Elements

scholarly journals Influence of foundation settlements in load redistribution on columns in a monitoring construction - Case Study

2010 ◽  
Vol 3 (3) ◽  
pp. 346-356 ◽  
Author(s):  
G. Savaris ◽  
P. H. Hallak ◽  
P. C. A. Maia
Keyword(s):  
Numerical Analysis ◽  
Numerical Model ◽  
Finite Elements ◽  
Load Distribution ◽  
Numerical Models ◽  
Normal Load ◽  
Finite Elements Method ◽  
Load Redistribution

The objective of this article is to present the results obtained in a study on the interaction between the behavior of the structure and the foundation settlements and verify the influence of normal load distribution on the columns. In this mechanism, known as structure soil interaction (SSI), as the building is constructed, a transfer of loads occurs from the columns which tend to settle more to those that tend to settle less. The study was conducted in a building which had its settlements monitored from the beginning of construction. For this purpose, a linear tridimensional numerical model was constructed and numerical analysis was performed, using the finite elements method. In these analyses, numerical models corre- sponding to the execution of each floor were used, considering the settlements measured in each stage of the construction. The results of analy- ses showed that the effect of SSI are significant for calculating the normal efforts on the columns, particularly on those located in the first floors.

scholarly journals A design methodology for approximate multipliers in convolutional neural networks: A case of MNIST

2021 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Kenta Shirane ◽  
Takahiro Yamamoto ◽  
Hiroyuki Tomiyama
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Convolutional Neural Network ◽  
Design Methodology ◽  
Critical Path ◽  
High Accuracy ◽  
Path Delay ◽  
Trade Off ◽  
Critical Path Delay

In this paper, we present a case study on approximate multipliers for MNIST Convolutional Neural Network (CNN). We apply approximate multipliers with different bit-width to the convolution layer in MNIST CNN, evaluate the accuracy of MNIST classification, and analyze the trade-off between approximate multiplier’s area, critical path delay and the accuracy. Based on the results of the evaluation and analysis, we propose a design methodology for approximate multipliers. The approximate multipliers consist of some partial products, which are carefully selected according to the CNN input. With this methodology, we further reduce the area and the delay of the multipliers with keeping high accuracy of the MNIST classification.

scholarly journals Developing an Analytical Solution that Mimics Simulation Modeling for Construction Planning: Earthwork Case

2019 ◽  
pp. 552-562
Author(s):  
Waleed Shakeel ◽  
Ming Lu
Keyword(s):  
Analytical Solution ◽  
Dynamic System ◽  
Simulation Modeling ◽  
High Accuracy ◽  
Analytical Tool ◽  
Controlled Experiments ◽  
Cost Estimating ◽  
Construction Planning ◽  
Using Data

Deriving a reliable earthwork job cost estimate entails analysis of the interaction of numerous variables defined in a highly complex and dynamic system. Using simulation to plan earthwork haul jobs delivers high accuracy in cost estimating. However, given practical limitations of time and expertise, simulation remains prohibitively expensive and rarely applied in the construction field. The development of a pragmatic tool for field applications that would mimic simulation-derived results while consuming less time was thus warranted. In this research, a spreadsheet based analytical tool was developed using data from industry benchmark databases (such as CAT Handbook and RSMeans). Based on a case study, the proposed methodology outperformed commonly used estimating methods and compared closely to the results obtained from simulation in controlled experiments.

Prediction and Analysis of Safety Production Accident in Mining Based on the GM(1,1)

2014 ◽  
Vol 989-994 ◽  
pp. 3443-3446
Author(s):  
Chen Fang Jiang ◽  
Ke Peng Hou ◽  
Hua Fen Sun
Keyword(s):  
Production Management ◽  
Management Practices ◽  
Safety Management ◽  
High Accuracy ◽  
Mine Safety ◽  
Grey Theory ◽  
Procedure Code ◽  
Safety Production ◽  
Mine Accidents

According to the grey theory, in order to predict and prevent accident effectively, the paper built a grey model and forecast the mine accidents in china in 2013 based on the statistics of mine accidents happened in China during period from 2007 to 2012. MATLAB was used to write procedure code of GM (1, 1) and empirical verification follows. The prediction results show that if high accuracy goes with the precision of the calculable model, which could be used to provide the basis for decision making to the safety production management practices in China. This case study indicates that GM (1, 1) plays an important role in mine safety management.

scholarly journals Cognitive Deficit of Deep Learning in Numerosity

2019 ◽  
Vol 33 ◽  
pp. 1303-1310
Author(s):  
Xiaolin Wu ◽  
Xi Zhang ◽  
Xiao Shu
Keyword(s):  
Deep Learning ◽  
Cognitive Deficit ◽  
Visual Representations ◽  
High Accuracy ◽  
Black Box ◽  
Cognitive Computing ◽  
Minimum Level ◽  
Test Bed ◽  
Abstract Notion

Subitizing, or the sense of small natural numbers, is an innate cognitive function of humans and primates; it responds to visual stimuli prior to the development of any symbolic skills, language or arithmetic. Given successes of deep learning (DL) in tasks of visual intelligence and given the primitivity of number sense, a tantalizing question is whether DL can comprehend numbers and perform subitizing. But somewhat disappointingly, extensive experiments of the type of cognitive psychology demonstrate that the examples-driven black box DL cannot see through superficial variations in visual representations and distill the abstract notion of natural number, a task that children perform with high accuracy and confidence. The failure is apparently due to the learning method not the CNN computational machinery itself. A recurrent neural network capable of subitizing does exist, which we construct by encoding a mechanism of mathematical morphology into the CNN convolutional kernels. Also, we investigate, using subitizing as a test bed, the ways to aid the black box DL by cognitive priors derived from human insight. Our findings are mixed and interesting, pointing to both cognitive deficit of pure DL, and some measured successes of boosting DL by predetermined cognitive implements. This case study of DL in cognitive computing is meaningful for visual numerosity represents a minimum level of human intelligence.

scholarly journals Service Recommendation with High Accuracy and Diversity

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Shengqi Wu ◽  
Huaizhen Kou ◽  
Chao Lv ◽  
Wanli Huang ◽  
Lianyong Qi ◽  
...  
Keyword(s):  
Web Services ◽  
Web Service ◽  
Weight Vector ◽  
High Accuracy ◽  
Information Resources ◽  
Cosine Similarity ◽  
Service Recommendation ◽  
Key Factor ◽  
Novel Method

In recent years, the number of web services grows explosively. With a large amount of information resources, it is difficult for users to quickly find the services they need. Thus, the design of an effective web service recommendation method has become the key factor to satisfy the requirements of users. However, traditional recommendation methods often tend to pay more attention to the accuracy of the results but ignore the diversity, which may lead to redundancy and overfitting, thus reducing the satisfaction of users. Considering these drawbacks, a novel method called DivMTID is proposed to improve the effectiveness by achieving accurate and diversified recommendations. First, we utilize users’ historical scores of web services to explore the users’ preferences. And we use the TF-IDF algorithm to calculate the weight vector of each web service. Second, we utilize cosine similarity to calculate the similarity between candidate web services and historical web services and we also forecast the ranking scores of candidate web services. At last, a diversification method is used to generate the top- K recommended list for users. And through a case study, we show that DivMTID is an effective, accurate, and diversified web service recommendation method.

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