321 research outputs found
Experimental study and numerical simulation of hydration and microstructure development of ternary cement-based materials
Os dados foram recolhidos e registados pelo técnico da ESACB João Nunes sob a supervisão da Prof.ª Maria do Carmo Horta Monteiro.Dados climáticos relativos ao ano de 1993, recolhidos e registados no Posto Meteorológico da Escola Superior Agrária do Instituto Politécnico de Castelo Branco
Experimental study and numerical simulation of hydration and microstructure development of ternary cement-based materials
Industrial structure and employment growth in the 1990s in Appalachian counties
Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2005.Includes bibliographical references (leaves 88-90).Employment growth in the 1990s and its relationship with the initial industrial structure in 1990 are examined in the case of Appalachian counties, after controlling for labor-market conditions and other factors, such as labor mobility, natural amenities, and market size. Spatial exploratory data analysis of the competitive employment growth (CEG) in Appalachian region shows that strong spillover effect of CEG exists among 410 counties. Counties with higher employment growth rates are concentrated in the north side of Atlanta Metropolitan area around Interstate highway 1-75. Counties with lower growth rates concentrated in Central Appalachia, along the convergent border of three states, Kentucky, Virginia, and West Virginia. Another low growth rate concentration is in Northeast Pennsylvania. The existence of spatial autocorrelation affects my empirical model's explanatory power, the significance levels, and the values of coefficients of independent variables. There is no specific theoretical base for the county-interacting mechanism of this empirical model, whereas, the magnitude of each independent variable's impact on employment growth depends on the spatial-weight matrixes. To find a better match, I compare the parameters of the model by using two different weight matrixes, i.e., weights based on physical neighbor interaction and weights based on commuting ties.(cont.) Based on the result of statistical comparison, the commuting tie is more likely the way by which counties interact with each other than physical proximity in the Appalachian Region. My empirical model is not able to explain completely the employment growth for all the counties in Appalachian Region, even after being adjusted for the spatial spillover effects, but it does provide some insight about what factors might matter for many places for their competitive employment growth from 1990 to 2000. Also, by analyzing the residuals of this model, analysts will be able to find some good candidates for case studies to understand what other determinants of economic growth might be.by Zhijun (Jeanne) Tan.M.C.P
Uniformly asymptotic stability of almost periodic solutions for a competitive system with impulsive perturbations
Improvement of k-means Clustering Algorithm for Analyzing the Morphology of Ice Ridge Sails
An improved k-means clustering algorithm is proposed after analyzing the disadvantages of the traditional k-means algorithm. The cluster centers are initialized by combining the sample mean and standard deviation, the optimal cluster centers are searched by the hybridizing particle swarm optimization and traditional k-means algorithm, and the criterion function is improved during the iteration process to search the optimal number of clusters. The theory analysis and experimental results show that the improved algorithm not only avoids the local optima, also has greater searching capability than the traditional algorithm. This improved algorithm is used to analyze the morphology of the ridge sail (the upper surface of ice ridges). The comparison with the measured data shows that the influences of the geographical locations and the growing environments on the formation of ice ridges can be perfectly reflected by the clustered results
一种基于模糊成像机理的QR码图像快速盲复原方法.
A fast blind restoration method of QR code images was proposed based on a blurred imaging mechanism. On the basis of the research on the centroid invariance of the blurred imaging diffuse light spots, the circular finder pattern is designed. When the image is blurred, the centroid of the pattern and the position of the QR code symbol can be quickly detected by methods such as connected components. Moreover, combined with step edge characteristics, gradient and intensity characteristics, edge detection technology, and optical imaging mechanism, the defocus radius of the blurred QR code image can be quickly and accurately estimated. Furthermore, the Wiener filter is applied to restore the QR code image quickly and effectively. Compared with the other algorithms, the proposed method has improved deblurring results in both structural similarity and peak signal-to-noise ratio, especially in the recovery speed. The average recovery time is 0.329 2 s. Experimental results show that this method can estimate the defocus radius with high accuracy and can quickly realize the blind restoration of QR code images. It has the advantages of rapidity and robustness, which are convenient for embedded hardware implementation and suitable for barcode identification-related industrial Internet of Things application scenarios
Classifier-head Informed Feature Masking and Prototype-based Logit Smoothing for Out-of-Distribution Detection
Out-of-distribution (OOD) detection is essential when deploying neural
networks in the real world. One main challenge is that neural networks often
make overconfident predictions on OOD data. In this study, we propose an
effective post-hoc OOD detection method based on a new feature masking strategy
and a novel logit smoothing strategy. Feature masking determines the important
features at the penultimate layer for each in-distribution (ID) class based on
the weights of the ID class in the classifier head and masks the rest features.
Logit smoothing computes the cosine similarity between the feature vector of
the test sample and the prototype of the predicted ID class at the penultimate
layer and uses the similarity as an adaptive temperature factor on the logit to
alleviate the network's overconfidence prediction for OOD data. With these
strategies, we can reduce feature activation of OOD data and enlarge the gap in
OOD score between ID and OOD data. Extensive experiments on multiple standard
OOD detection benchmarks demonstrate the effectiveness of our method and its
compatibility with existing methods, with new state-of-the-art performance
achieved from our method. The source code will be released publicly.Comment: 10 pages, 7 figure
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