We consider Markov basis arising from fractional factorial designs with threelevel factors. Once we have a Markov basis, p values for various conditional tests are estimated by the Markov chain Monte Carlo procedure. For designed experiments with a single count observation for each run, we formulate a generalized linear model and consider a sample space with the same sufficient statistics to th...

This paper compares several optimization algorithms that can be used to generate exact D-optimal designs (i.e., designs for a specified number of runs) for any polynomial model. The merits and limitations of each algorithm are demonstrated on several low-order polynomial models, with numerical results verified against analytical results. The efficiencies – with respect to estimating model param...

We consider Markov basis arising from fractional factorial designs with threelevel factors. Once we have a Markov basis, p values for various conditional tests are estimated by the Markov chain Monte Carlo procedure. For designed experiments with a single count observation for each run, we formulate a generalized linear model and consider a sample space with the same sufficient statistics to th...

Building thermal simulation based parametric methods are computationally intensive for optimizing the building design. This work uses experimental design techniques, i.e. fractional factorial design and response surface methodology, for sensitivity analysis and surrogate modeling respectively. These techniques find the solution in a reasonable time. Their application for building design optimiz...

In recent years, biodiesel, a substitute for fossil fuels, has led to the excessive production of crude glycerol. The resulting crude glycerol can possess a high concentration of salts and an alkaline pH. Moreover, current crude glycerol purification methods are expensive, rendering this former commodity a waste product. However, Halanaerobium hydrogeniformans, a haloalkaliphilic bacterium, pos...