This thesis is about how to represent and solve decision problems in Bayesian decision theory (e.g. Fishburn 1988). A general representation named decision networks is proposed based on influence diagrams (Howard and Matheson 1984). This new representation incorporates the idea, from Markov decision processes (e.g. Puterman 1990, Denardo 1982), that a decision may be conditionally independent o...

Identification of constituent gases in effluent plumes is performed using linear least-squares regression techniques. Airborne thermal hyperspectral imagery is used for this study. Synthetic imagery is employed as the test-case for algorithm development. Synthetic images are generated by the Digital Imaging and Remote Sensing Image Generation (DIRSIG) Model. The use of synthetic data provides a...

A graph $G$ is called irregular if the degrees of all its vertices are not same. said to be \textit{Stepwise Irregular} (SI) difference any two adjacent always 1 (one). This paper deals with \textit{2-Stepwise (2-SI) graphs in which every pair differ by 2. Here we discuss some properties 2-SI and generalize them for $k$-SI imbalance edge $k$. Besides, also compute bounds irregularity Albertson ...

Complex student models often include key parameters critical to their behavior and effectiveness. For example, one meta-cognitive model of student help-seeking in intelligent tutors includes 15 rules and 10 parameters. We explore whether or not this model can be improved both in accuracy and generalization by using a variety of techniques to select and tune parameters. We show that such techniq...

Most character motion capture data does not contain secondary motions like detailed hand motion, therefore the resultant animation looks unnatural due to the stiffness of hand motion. In this paper, we analyzed the pose space distance from the character’s motion capture data and used stepwise searching algorithm to find the key poses for hand motion synthesis. We adaptively changed the contrast...

We present and study the Contribution-Selection algorithm (CSA), a novel algorithm for feature selection. The algorithm is based on the Multiperturbation Shapley Analysis, a framework which relies on game theory to estimate usefulness. The algorithm iteratively estimates the usefulness of features and selects them accordingly, using either forward selection or backward elimination. Empirical co...

Aims: Hemospermia is an infrequently discussed urological problem. Most health care providers including general surgeons and physicians are unfamiliar with this disorder, its etiology & management. We undertook the present review to ascertain the magnitude of this problem and to device a working algorithm to help the clinician in approaching a case of hematospermia. The symptoms, differential d...

Algorithms for simultaneous shrinkage and selection in regression and classification provide attractive solutions to knotty old statistical challenges. Nevertheless, as far as we can tell, Tibshirani’s Lasso algorithm has had little impact on statistical practice. Two particular reasons for this may be the relative inefficiency of the original Lasso algorithm and the relative complexity of more...