Phosphorylation is the most abundant post-translational modification, regulating several aspects of protein and cell function. Quantitative phosphoproteomics approaches have expanded the scope of phosphorylation analysis enabling the quantification of changes in thousands of phosphorylation sites simultaneously in two or more conditions. These approaches offer a global view of the impact of cel...

In order to improve the performance of basic bacterial foraging optimization (BFO) for various global optimization problems, a superior attraction bacterial foraging optimizer (SABFO) is proposed in this paper. In SABFO, a novel movement guiding technique termed as superior attraction strategy is introduced to make use of all bacteria historical experience as potential exemplars to lead individ...

The canonical particle swarm optimization (PSO) has its own disadvantages, such as the high speed of convergence which often implies a rapid loss of diversity during the optimization process, which inevitably leads to undesirable premature convergence. In order to overcome the disadvantage of PSO, a perturbed particle swarm algorithm (pPSA) is presented based on the new particle updating strate...

[1] Estimated parameter distributions in groundwater models may contain significant uncertainties because of data insufficiency. Therefore, adaptive uncertainty reduction strategies are needed to continuously improve model accuracy by fusing new observations. In recent years, various ensemble Kalman filters have been introduced as viable tools for updating high-dimensional model parameters. How...

Distributed Lagrangian Relaxation Protocol (DisLRP) has been proposed to solve a distributed combinatorial maximization problem called the Generalized Mutual Assignment Problem (GMAP). In DisLRP, when updating Lagrange multipliers (prices) of goods, the agents basically control their step length, which determines the degree of update, by a static rule. A merit of this updating rule is that sinc...

Title of dissertation: GLOBAL OPTIMIZATION OF FINITE MIXTURE MODELS Jeffrey W. Heath Doctor of Philosophy, 2007 Dissertation directed by: Professor Michael Fu Robert H. Smith School of Business & Professor Wolfgang Jank Robert H. Smith School of Business The Expectation-Maximization (EM) algorithm is a popular and convenient tool for the estimation of Gaussian mixture models and its natural ext...

A strategy is described for using linear programming (LP) to bound the solution set of the linear interval equation system that must be solved in the context of the interval-Newton method for deterministic global optimization. An implementation of this technique is described in detail, and several important issues are considered. These include selection of the interval corner required by the LP...

Present and future concentrations of DDT in the environment are calculated with the global multimedia model CliMoChem. Monte Carlo simulations are used to assess the importance of uncertainties in substance property data, emission rates, and environmental parameters for model results. Uncertainties in the model results, expressed as 95% confidence intervals of DDT concentrations in various envi...

The prevailing nature-based solution to tackle climate change is tree planting. However, there growing evidence that it has serious contraindications in many regions. main shortcoming of global planting its awareness disparity alternative ecosystem types, mainly grasslands. Grasslands, where they constitute the natural vegetation, may support higher biodiversity and a safer, soil-locked carbon ...

Much local government has been utilizing a large-scale digital map using Geographic Information System (GIS). However, the maintenance and renewal of a map database need much labor and time. Moreover, the updating method of a map has not been established yet and there have been almost no successful examples. The purpose of the study is to establish a method of updating the large-scale map for l...