A high-order symplectic FDTD (SFDTD) framework for solving the time-dependent Schrödinger equation is established. The third-order symplectic integrators and fourth-order collocated differences are employed in th...
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Geographic objects with descriptive text are gaining in prevalence in many web services such as Google *** keyword query which combines both the location information and textual description stands out in recent *** wo...
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Geographic objects with descriptive text are gaining in prevalence in many web services such as Google *** keyword query which combines both the location information and textual description stands out in recent *** works mainly focus on finding top-k Nearest Neighbours where each node has to match the whole querying keywords.A collective query has been proposed to retrieve a group of objects nearest to the query object such that the group's keywords cover query's keywords and has the shortest inner-object *** the previous method does not consider the density of data objects in the spatial *** practice,a group of dense data objects around a query point will be more interesting than those sparse data *** distance of data objects of a group cannot reflect the density of the *** overcome this shortage,we proposed an approximate algorithm to process the collective spatial keyword query based on density and inner *** empirical study shows that our algorithm can effectively retrieve the data objects in dense areas.
Compressed Sensing (CS), a popular technique which seeks to capture a discrete signal with a small number of linear measurements, could be used to compress a signal during the process of sampling. As an iterative gree...
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Compressed Sensing (CS), a popular technique which seeks to capture a discrete signal with a small number of linear measurements, could be used to compress a signal during the process of sampling. As an iterative greedy reconstruction algorithm for practical CS, sparsity adaptive matching pursuit (SAMP) takes advantage of the capability of signal reconstruction without prior information of the sparsity in the process of resuming the original high-dimension-data from low-dimension measurement. This paper presents a backward and adaptive matching pursuit reconstruction algorithm with fixed step sizes to avoid the overestimation phenomena of SAMP by using a standard regularized approach. Firstly, a fixed and biggish step size is set to make sure the size of support set of the signal to be reconstructed increasing stably. The energy difference between adjacent reconstructed signals is then taken as the halting condition of iteration. A standard regularized approach is employed to post-dispose the final iteration results, which backward eliminates superfluous atoms to acquire exact reconstruction. Experimental results show that such an improvement of SAMP is feasible in technology and effective in acquiring quick and exact reconstruction with sufficient measurement.
The conventional 'OR' fusion rule is frequently applied in two pre-determined limits energy detection networks but its overall performance of the false alarm and miss detection probability is generally. The ne...
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In this paper, an efficient two-stage segmentation framework was proposed to address the plant leaf image with overlapping phenomenon, which is built based on the leaf approximate symmetry and level set evolution theo...
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There are a number of leaf recognition methods, but most of them are based on Euclidean space. In this paper, we will introduce a new description of feature for the leaf image recognition, which represents the leaf co...
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The quotient space theory based on fuzzy tolerance relation is put forward to solve the problem of clustering in this paper. The similarity matrix does not always satisfy ultrametric inequality, theoretically and prac...
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This paper proposes a method which is not for summarization but for extracting multiple facets from a text according to the keyword sets representing readers’ interests,so that readers can obtain the interested facet...
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This paper proposes a method which is not for summarization but for extracting multiple facets from a text according to the keyword sets representing readers’ interests,so that readers can obtain the interested facets and carry out faceted navigation on text.A facet is a meaningful combination of the subsets of the *** text process technologies are mostly based on text features such as word frequency,sentence location,syntax analysis and discourse *** approaches neglect the cognition process of human *** proposed method considers human reading *** show that the facet extraction is effective and robust.
PLSA(Probabilistic Latent Semantic Analysis) is a popular topic modeling technique for exploring document collections. Due to the increasing prevalence of large datasets, there is a need to improve the scalability of ...
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Block transform coding using discrete cosine transform is the most popular approach for image compression. However, many annoying blocking artifacts are generated due to coarse quantization on transform coefficients i...
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