A5048317896- Meteorological Phenomena and Simulations
- Interconnection Networks and Systems
- Climate variability and models
- Advanced Graph Theory Research
- Parallel Computing and Optimization Techniques
- Algorithms and Data Compression
- graph theory and CDMA systems
- Complexity and Algorithms in Graphs
- Machine Learning and Algorithms
- Matrix Theory and Algorithms
- Game Theory and Applications
- Optimization and Search Problems
- Reservoir Engineering and Simulation Methods
- VLSI and FPGA Design Techniques
- Nonlinear Dynamics and Pattern Formation
- Statistical and numerical algorithms
- Quantum chaos and dynamical systems
- Oceanographic and Atmospheric Processes
- DNA and Biological Computing
- Atmospheric and Environmental Gas Dynamics
- Stochastic processes and financial applications
- Chaos control and synchronization
- Tropical and Extratropical Cyclones Research
- Geophysics and Gravity Measurements
- semigroups and automata theory
University of Oklahoma
2012-2024
Indian Institute of Technology Bombay
2022
Desert Research Institute
2018-2021
NOAA National Severe Storms Laboratory
1993-2021
Cooperative Institute for Mesoscale Meteorological Studies
2018
Lynn University
2016
College Track
2000
Eastern Kentucky University
1995
Yale University
1977-1978
Indian Institute of Technology Madras
1976-1977
Abstract This paper introduces a new class of interconnection scheme based on the Cayley graph alternating group. It is shown that this graphs are edge symmetric and 2‐transitive. We then describe an algorithm for (a) packet routing shortest path analysis, (b) finding Hamiltonian cycle, (c) ranking unranking along chosen (d) unit expansion dilation three embedding two‐dimensional grids, (e) variety cycles, (f) broadcasting messages. The concludes with short analysis contention resulting from...
The use of the star graph as a viable interconnection scheme for parallel computers has been examined by number authors in recent times. An attractive feature this class graphs is that it sublogarithmic diameter and great deal symmetry akin to binary hypercube. In paper we describe new algorithms embedding (a) Hamiltonian cycle (b) set all even cycles (c) variety two- multi-dimensional grids graph. addition, also derive an algorithm ranking unranking problem with respect cycle.
The use of star graphs as a viable interconnection scheme for parallel computers has been examined by number authors. An attractive feature this class is that it sublogarithmic diameter and great deal symmetry akin to the binary hypercube. authors describe new algorithms embedding Hamiltonian cycle, set all even cycles variety two multi-dimensional grids in graph. They derive an algorithm ranking unranking problem with respect cycle.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML"...
The ensemble Kalman filter (EnKF) has been used in weather forecasting to assimilate observations into models. In this study, we examine how effectively forecasts of a forest carbon cycle can be improved by assimilating with the EnKF. We EnKF terrestrial ecosystem (TECO) model eight data sets collected at Duke Forest between 1996 and 2004 (foliage biomass, fine root woody litterfall, microbial floor carbon, soil respiration). then trained forecast changes pools from 2012. Our daily analysis...
This paper extends recent results [Lakshmivarahan and Narendra, Math. Oper. Res., 6 (1981), pp. 379–386] in two-person zero-sum sequential games which the players use learning algorithms to update their strategies. It is assumed that neither player knows (i) set of strategies available other or (ii) mixed strategy used by its pure realization at any stage. The outcome game depends on chance played sequentially. distribution random as a function pair chosen also, unknown them. shown if...
Meteorological models are used to predict the weather, study atmospheric processes, and provide input decision makers on consequences of increased greenhouse gas emissions Earth's climate. Predictions future states accomplished as an initial value or marching problem, where state is specified variables advanced in time using numerical techniques. The challenge data assimilation meteorology estimate, based a set limited observations varying types, complete three-dimensional at given for...
Objective: Since computer-aided diagnosis (CAD) schemes of medical images usually computes large number image features, which creates a challenge how to identify small and optimal feature vector build robust machine learning models, the objective this study is investigate feasibility applying random projection algorithm (RPA) an from initially CAD-generated pool improve performance model. Methods: We assemble retrospective dataset involving 1,487 cases mammograms in 644 have confirmed...
Preface. Chapter 1: Sets, Fields, and Events. 1.1 Set Definitions. 1.2 Operations. 1.3 Algebras, 2: Probability Space Axioms. 2.1 Space. 2.2 Conditional Probability. 2.3 Independence. 2.4 Total Bayes' Theorem. 3: Basic Combinatorics. 3.1 Counting Principles. 3.2 Permutations. 3.3 Combinations. 4: Discrete Distributions. 4.1 Bernoulli Trials. 4.2 Binomial Distribution. 4.3 Multinomial 4.4 Geometric 4.5 Negative 4.6 Hypergeometric 4.7 Poisson 4.8 Logarithmic 4.9 Summary of 5: Random Variables....
The NOAA NWS announced at the annual meeting of American Meteorological Society in February 2003 its intent to create an Internet-based pseudo-operational system for delivering Weather Surveillance Radar-1988 Doppler (WSR-88D) Level II data. In April 2004, deployed Next-Generation Radar (NEXRAD) level central collection functionality and set up a framework distributing these action was direct result successful joint government, university, private sector development test effort called...
Short-range ensemble forecasts from the Storm and Mesoscale Ensemble Experiment (SAMEX) are examined to explore importance of model diversity in short-range forecasting systems. Two basic techniques multivariate data analysis used: cluster principal component analysis. This 25-member is constructed 36-h four different numerical weather prediction models, including Eta Model, Regional Spectral Model (RSM), Advanced Prediction System (ARPS), Pennsylvania State University–National Center for...
An automated procedure for classifying rainfall systems (meso-α scale and larger) was developed using an operational analysis of hourly precipitation estimates from radar rain gauge data. The development process followed two main phases: a training phase testing phase. First, 48 hand-selected cases were used to create dataset, which set attributes related morphological aspects extracted. A hierarchy classes systems, in the are separated into general convective (heavy rain) nonconvective...
This paper investigates conditions under which two learning algorithms playing a zero-sum sequential stochastic game would arrive at optimal pure strategies. Neither player has knowledge of either the pay-off matrix or choice strategies available to other and both players update their own every stage entirely on basis random outcome that stage. The proposed are shown converge when they exist with probabilities as close 1 desired.
Machine learning (ML) algorithms, such as principal component analysis, independent self-organizing maps, and artificial neural networks, have been used by geoscientists to not only accelerate the interpretation of their data, but also provide a more quantitative estimate likelihood that any voxel belongs given facies. Identifying best combination attributes needed perform either supervised or unsupervised ML tasks continues be most-asked question interpreters. In past decades, stepwise...
The least squares fit of observations with known error covariance to a strong‐constraint dynamical model has been developed through use the time evolution sensitivity functions—the derivatives output respect elements control (initial conditions, boundary and physical/empirical parameters). Model is assumed stem from incorrect specification elements. optimal corrections are found solution an inverse problem. Duality between this method standard 4D‐Var assimilation using adjoint equations...