Cloud identification using genetic algorithms and massively parallel computation

As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user's manual was written and distributed nationwide to scientists whose work might benefit from its availability. Several papers, including two journal articles, were produced

Low cost network camera sensors for traffic monitoring

Report on a study investigating the ways new video and wireless technology can be implemented into Texas Department of Transportation video monitoring systems to increase efficiency and reduce costs

Cloud Identification Using Genetic Algorithms and Massively Parallel Computation

As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMs) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here ..

A WAVELET-BASED NOISE-AWARE METHOD FOR FUSING NOISY IMAGERY

ABSTRACT Fusion of images in the presence of noise is a challenging problem. Conventional fusion methods focus on aggregating prominent image features, which usually result in noise enhancement. To address this problem, we developed a waveletbased, noise-aware fusion method that distinguishes signal and noise coefficients on-the-fly and fuses them with weighted averaging and majority voting respectively. Our method retains coefficients that reconstruct salient features, whereas noise components are discarded. The performance is evaluated in terms of noise removal and feature retention. The comparisons with five state-of-the-art fusion methods and a combination with denoising method demonstrated that our method significantly outperformed the existing techniques with noisy inputs

On the Number of Expressions Modulo Commutativity over a Finite Semi-group

A problem, ffl n , that is closely related to Catalan numbers, b n , is formulated, analysed, and solved. The result shows that ffl n is exponential, which poses a challenge for finding a polynomial time algorithm if a search space is ffl n . Conversely, it inspires attempts to prove that such search problems are NP -complete. This work has immediate applications to the join optimization problem in database systems. Catalan numbers [7] b n = 1 n+1 i 2n n j can be interpreted as, given a finite semi-group (G; fi) with jGj = n, the number of expressions over (G; fi) which are equivalent under associativity to a specific expression e of length n. Catalan numbers have applications in such diverse areas as determining the number of ways that parentheses may be configured in matrix-chain multiplication [1], determining the number of ways that a n-polygon can be triangularized [4], and determining the number of full binary trees [2]. Given the Catalan number b n , it is easy to see t..

Supporting Array Types in Monoid Comprehensions

A widely known problem of commercial database systems is their lack of support for "scientific" applications. This is in part derived from their inability to deal with some data types such as arrays. It is the purpose of this research to make possible the full manipulation of array types using the query language for an OODB. The proposal is to use the Monoid Comprehension Calculus (MCC) [11], properly augmented, to support array types. The approach is to define arrays as functions instead of specifying them directly as monoids. This overcomes significant disadvantages of previously reported approaches. We present some examples of queries involving intensive manipulation of arrays in the context of image processing. 1 Introduction Object oriented database technology has reduced the impedance between programming languages and databases. In large part, this is due to the introduction of collections, some of which are recognizable abstract data types frequently employed in scientific pro..