Challenges in Survey Research

While being an important and often used research method, survey research has been less often discussed on a methodological level in empirical software engineering than other types of research. This chapter compiles a set of important and challenging issues in survey research based on experiences with several large-scale international surveys. The chapter covers theory building, sampling, invitation and follow-up, statistical as well as qualitative analysis of survey data and the usage of psychometrics in software engineering surveys.Comment: Accepted version of chapter in the upcoming book on Contemporary Empirical Methods in Software Engineering. Update includes revision of typos and additional figures. Last update includes fixing two small issues and typo

Multivariable adaptive control of nonlinear completely mixed bioreactors

It is shown how to extend adaptive linearizing control laws of single-input-single-output (SISO) stirred bioreactors to the multi-input-multi-output (MIMO) case. More precisely, the problem of controlling two reactant concentrations with two control inputs is considered and illustrated by three process examples (activated sludge process, yeast growth, and anaerobic digestion). The performance of the multivariable adaptive nonlinear controller is further illustrated by simulation in the first example.Anglai

Two-mode stochastic process control

The minimum variance control of a stochastic process, the dynamics of which is time-varying according to two distinct linear modes, is studied. An approximate solution is proposed, combining the implementation of an adaptive minimum error classifier performed by means of the window function technique and the use of the control theory of linear systems developed by Astrom.Anglai

[St1884] Sturm, R., “Bemerkungen und Zusatze zu Steiners Aufsazen uber Maxima und Minima,”

[YKII88] Yamamoto, P., Kato, K., Imai, K. and Imai, H., “Algorithms for vertical and orthogona

Estimation in random fields with scattered data

The design of linear minimum-variance unbiased estimates in 2-D random fields (RF) is a standard problem when the mean and the covariance function of the field are known. A case is investigated where the data are so scarce and so scattered in space that reliable estimates of the covariance function are impossible to obtain by classical procedures. Using the variogram of the RF rather than the covariance function, a procedure is developed for the estimation of a variogram model which leads to meaningful estimates of various functionals of the RF.Anglai

Optimal allocation of pointwise controllers in stochastic distributed systems

The problem of optimal allocation of pointwise controllers for a class of linear stochastic distributed parameter systems is considered. The optimal pointwise control is derived, via a direct approach, while minimizing a quadratic cost functional w.r.t. both control gains and controller positions using gradient techniques.Anglai