Simulated Annealing and Threshold Accepting are two stochastic search algorithms that have been successfully used on a variety of complex and difficult problem sets. Due to their stochastic nature they are not guaranteed to produce the same result for each run. This means that these techniques actually produce a distribution...
Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
The introduction of an Magnetohydrodynamic (MHD) generator in coal or natural gas energy plants could significantly increase the efficiency by converting kinetic and thermal energy of the combustion exhaust to electrical energy by the generation of a Faraday and Hall current. The traditional MHD system was transformed into a simplified...
The calculation of interplanetary trajectories is a numeric problem which requires a high degree
of precision for the results to be accurate. A computer program was written for this project which
uses leapfrog integration combined with Newton’s method of iterative root finding to find ideal
interplanetary trajectories. Reasonable initial conditions...
We investigate the optimal harvesting strategies for McKendrick type population models. Models of this type endow the population with a continuous age structure. They consist of a partial differential equation with a boundary condition which involves an integral of the solution. We study two problems, the first concerns the yield...
This paper proposes a technique, called Smell-driven performance tuning (SDPT), which semi-automatically assists end-user programmers with fixing performance problems in visual dataflow programming languages. A within-subjects laboratory experiment showed SDPT increased end-user programmers’ success rate and decreased the time they required. Another study, based on using SDPT to analyze a...
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compiler’s optimization options and
potentially reducing readability.
Too Many
Variables
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Describing functions have traditionally been used to obtain the
solutions of systems of ordinary differential equations. In this
work the describing function concept has been extended to include
nonlinear, distributed parameter partial differential equations. A
three-stage solution algorithm is presented which can be applied to
any nonlinear partial differential equation....
The Elliptic Curve Digital Signature Algorithm (ECDSA) is the elliptic curve analog of the Digital Signature Algorithm (DSA) and a federal government approved digital signature method. In this thesis work, software optimization techniques were applied to speed up the ECDSA for a particular NTST curve over GF(p). The Montgomery multiplication...
Many important application problems in engineering can be formalized as nonlinear
optimization tasks. However, numerical methods for solving such problems
are brittle and do not scale well. For example, these methods depend critically
on choosing a good starting point from which to perform the optimization search.
In high-dimensional spaces, numerical...
The Elliptic Curve Digital Signature Algorithm (ECDSA) is one of the most popular algorithms to digitally sign streams or blocks of data. In this thesis we concentrate on porting and optimizing the ECDSA on the ARM7 processor for a particular NIST curve over GF(2[superscript m]). The selected curve is a...