A cloud detection algorithm for a low power micropulse lidar is presented that attempts to identify all of the significant power returns from the vertical column above the lidar at all times, The main feature of the a...
详细信息
A cloud detection algorithm for a low power micropulse lidar is presented that attempts to identify all of the significant power returns from the vertical column above the lidar at all times, The main feature of the algorithm is construction of lidar power return profiles during periods of clear sky against which cloudy-sky power returns are compared. This algorithm supplements algorithms designed to detect cloud-base height in that the tops of optically thin clouds are identified and it provides an alternative approach to algorithms that identify significant power returns by analysis of changes in the slope of the backscattered powers with height. The cloud-base heights produced by the current algorithm during nonprecipitating periods are comparable with the results of a cloud-base height algorithm applied to the same data. Although an objective validation of algorithm performance on high, thin cirrus is lacking because of no truth data, the current algorithm produces few false positive and false negative classifications as determined through manual comparison of the original photoelectron count data to the final cloud mask image.
Background: In recent times, there has been an exponential rise in the number of protein structures in databases e. g. PDB. So, design of fast algorithms capable of querying such databases is becoming an increasingly ...
详细信息
Background: In recent times, there has been an exponential rise in the number of protein structures in databases e. g. PDB. So, design of fast algorithms capable of querying such databases is becoming an increasingly important research issue. This paper reports an algorithm, motivated from spectral graph matching techniques, for retrieving protein structures similar to a query structure from a large protein structure database. Each protein structure is specified by the 3D coordinates of residues of the protein. The algorithm is based on a novel characterization of the residues, called projections, leading to a similarity measure between the residues of the two proteins. This measure is exploited to efficiently compute the optimal equivalences. Results: Experimental results show that, the current algorithm outperforms the state of the art on benchmark datasets in terms of speed without losing accuracy. Search results on SCOP 95% nonredundant database, for fold similarity with 5 proteins from different SCOP classes show that the current method performs competitively with the standard algorithm CE. The algorithm is also capable of detecting non-topological similarities between two proteins which is not possible with most of the state of the art tools like Dali.
暂无评论