1,115 research outputs found
Novel interface-selected waves and their influences on wave competitions
The topic of interface effects in wave propagation has attracted great
attention due to their theoretical significance and practical importance. In
this paper we study nonlinear oscillatory systems consisting of two media
separated by an interface, and find a novel phenomenon: interface can select a
type of waves (ISWs). Under certain well defined parameter condition, these
waves propagate in two different media with same frequency and same wave
number; the interface of two media is transparent to these waves. The frequency
and wave number of these interface-selected waves (ISWs) are predicted
explicitly. Varying parameters from this parameter set, the wave numbers of two
domains become different, and the difference increases from zero continuously
as the distance between the given parameters and this parameter set increases
from zero. It is found that ISWs can play crucial roles in practical problems
of wave competitions, e.g., ISWs can suppress spirals and antispirals
Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms
Due to the unmanned aerial vehicle remote sensing images (UAVRSI) within rich texture details of ground objects and obvious phenomenon, the same objects with different spectra, it is difficult to effectively acquire the edge information using traditional edge detection operator. To solve this problem, an edge detection method of UAVRSI by combining Zernike moments with clustering algorithms is proposed in this study. To begin with, two typical clustering algorithms, namely, fuzzy c-means (FCM) and K-means algorithms, are used to cluster the original remote sensing images so as to form homogeneous regions in ground objects. Then, Zernike moments are applied to carry out edge detection on the remote sensing images clustered. Finally, visual comparison and sensitivity methods are adopted to evaluate the accuracy of the edge information detected. Afterwards, two groups of experimental data are selected to verify the proposed method. Results show that the proposed method effectively improves the accuracy of edge information extracted from remote sensing images
A Discussion on Exceptions to Export Restrictions under GATT/WTO
In recent years, the proliferation of natural resource trade has caused rising demand in supply of resource products, leading to “widespread anxiety over the security of access to natural re-source.” In context of this, export restrictions have been frequently imposed on resource products, most of which come from the developing world.
Recently, known as China − Rare Earths, a case against China’s measures related to the exportation of rare earths was brought to WTO and a panel has been established by request of Japan. It is another sign for the increasingly heated topic of export restrictions during recent decades subsequent to the high profile case China − Raw Materials.
Against this backdrop, it is thus vital for exporting countries to seek justifications provided in GATT/WTO when facing challenges to their export restrictions. This thesis aims to elaborate on the issue of applying current possible exception clauses to alleged unlawful export restrictions, in accordance with present articles under GATT 1994 and available case laws. Meanwhile, a highly relevant case China − Rare Earths would be discussed in light of this
Research Progress on Integrated Traditional Chinese and Western Medicine in the Treatment of Post-Cholecystectomy Syndrome
Laparoscopic cholecystectomy (LC) is a highly accepted treatment at this stage, with the increasing incidence of biliary tract disease and the development of endoscopic technique in recent years However, some patients after cholecystectomy still have symptoms similar to preoperative symptoms, such as abdominal pain, diarrhea, indigestion and so on. This series of syndromes has become a common clinical problem at present.This article reviews the research progress of etiology, pathogenesis, diagnosis and treatment of post-cholecystectomy syndrome by reading related literatures
Inhomogeneous graph trend filtering via a l2,0 cardinality penalty
We study estimation of piecewise smooth signals over a graph. We propose a
-norm penalized Graph Trend Filtering (GTF) model to estimate
piecewise smooth graph signals that exhibits inhomogeneous levels of smoothness
across the nodes. We prove that the proposed GTF model is simultaneously a
k-means clustering on the signal over the nodes and a minimum graph cut on the
edges of the graph, where the clustering and the cut share the same assignment
matrix. We propose two methods to solve the proposed GTF model: a spectral
decomposition method and a method based on simulated annealing. In the
experiment on synthetic and real-world datasets, we show that the proposed GTF
model has a better performances compared with existing approaches on the tasks
of denoising, support recovery and semi-supervised classification. We also show
that the proposed GTF model can be solved more efficiently than existing models
for the dataset with a large edge set.Comment: 21 pages, 3 figures, 4 table
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