Most existing language modeling approaches are based on the term independence hypothesis. To go beyond this assumption, two main directions were investigated. The first one considers the use of the proximity features ...
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Currently, a majority of existing algorithms for sparse optimization problems are based on regularization framework. The main goal of these algorithms is to recover a sparse solution with k non-zero components(called ...
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A kind of SND-based algorithm for self-adapting network congestion control has been presented in this paper, which is for the complicated and integrated network environment that the Internet of Things (IOT) to face in...
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Purpose. Since fractal image coding is time-consuming and is prone to causing "blocking artifact", the article aims to combine fractal image coding, wavelet transform and compressed sensing to put forward a ...
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Support Vector Machines (SVM) learning can be used to construct classification models of high accuracy. However, the performance of SVM learning should be improved. This paper proposes a bilinear grid search method to...
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Support Vector Machines (SVM) learning can be used to construct classification models of high accuracy. However, the performance of SVM learning should be improved. This paper proposes a bilinear grid search method to achieve higher computation efficiency in choosing kernel parameters (C, γ) of SVM with RBF kernel. Experiments show that the proposed method retains the advantages of a small number of training SVMs of bilinear search and the high prediction accuracy of grid search. It has been proved that bilinear grid search method (BGSM) is an effective way to train SVM with RBF kernel. With the application of BGSM, the protein secondary structure prediction can obtain a better learning accuracy compared with other related algorithms.
Summary form only given. The magnetostrictive/piezoelectric laminate composites consisting of Ni, Permendur, Metglas or Terfenol-D as magnetostrictive phase and PVDF, PZT or PMN-PT as piezoelectric phase demonstrate s...
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Summary form only given. The magnetostrictive/piezoelectric laminate composites consisting of Ni, Permendur, Metglas or Terfenol-D as magnetostrictive phase and PVDF, PZT or PMN-PT as piezoelectric phase demonstrate strong magnetoelectric effect due to the product property, which provide effective conversion between electric field energy and magnetic field energy. The superior performances make them potential applications in novel multifunctional devices, such as multiple-state storages, energy harvesting transducers, tunable microwave devices, magnetic field sensors, and transformers. Recently, it has been found that the magnetic permeability for magnetostrictive material directly affects its effective piezomagnetic coefficient and corresponding magnetoelectric effect. Combining traditional magnetostrictive/piezoelectric laminate composites and high permeability materials can significantly enhance the effective permeability, which produce the self-biased ME effect. However, in previous reports, most researchers have focused on the preparation method and testing composite structure consisting of specific high permeability materials, which is lack of comparisons and analysis for composites with different high permeability material. Actually for the practical applications of magnetoelectric composites, it is both physically interesting and technologically important to systematically investigate the ME composites with different high permeability materials. Hence in this study, by bonding three different high permeability materials FeCuNbSiB, FeSiB and CoNiFeSiB into Terfenol-D/PZT laminate, the FeCuNbSiB/Terfenol-D/PZT, FeSiB/Terfenol-D/PZT, and CoNiFeSiB/Terfenol-D/PZT laminate composites are prepared. The influences of the different high permeability materials on the ME characteristics of the composites have been investigated, as shown in Fig.1. On one hand, the experimental results demonstrate that the maximum zero-bias ME voltage coefficient for FeCuNbSiB/Terfenol-
It's well known machine learning from examples is an effective method to solve non-linear classification problem. A new dynamic method of machine learning from transition example is given in this paper. This metho...
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In embedded Internet of Things(IOT) environment, there are the troubles such as complex background, illumination changes, shadows and other factors for detecting moving object, so we put forward a new detection servic...
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In embedded Internet of Things(IOT) environment, there are the troubles such as complex background, illumination changes, shadows and other factors for detecting moving object, so we put forward a new detection service method through mixing Gaussian Mixture Model(GMM), edge detection service method and continuous frame difference method in this paper. In time domain, the new method uses GMM to model and updates the background. In spatial domain, it uses the hybrid detection service method which mixes edge detection service method, continuous frame difference method and GMM to get initial contour of moving object, and gets ultimate moving object. This method not only can well adapt to the illumination gradients and background disturbance occurred on scene, but also can well solve some problems such as inaccurate target detection, incomplete edge detection, cavitation and ghost which usually appears in traditional method. As experimental result showing, this method holds better real-time and robustness. It is not only easily implemented, but also can accurately detect moving object.
作者：
Guo, KuoLi, YifanChen, HaoShen, Hong-BinYang, YangShanghai Jiao Tong University
Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Jiao Tong University
Key Laboratory of System Control and Information Processing Ministry of Education of China Institute of Image Processing and Pattern Recognition Shanghai200240 China Carnegie Mellon University
School of Computer Science Computational Biology Department PittsburghPA15213 United States
Isoforms refer to different mRNA molecules transcribed from the same gene, which can be translated into proteins with varying structures and functions. Predicting the functions of isoforms is an essential topic in bio...
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Cryo-electron microscopy (cryo-EM) has become a mainstream technology for solving spatial structures of biomacromolecules, while the processing of cryo-EM images is a very challenging task. One of the great challenges...
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