Sunil Vadera

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Since their inception, entity relationship models have played a central role in systems specification, analysis and development. They have become an important part of several development methodologies and standards such as SSADM. Obtaining entity relationship models, can however, be a lengthy and time consuming task for all but the very smallest of(More)
Recent years have seen much debate about the appropriate content of software engineering (SE) programs and how they relate to computer science (CS) programs, culminating in the distinguishing knowledge areas identified in the ACM/IEEE CS and SE curricula. Given these publications, a reasonable question to ask is: how do current SE programs differ from CS(More)
Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have(More)
This article presents a new decision tree learning algorithm called CSNL that induces <b>C</b>ost-<b>S</b>ensitive <b>N</b>on-<b>L</b>inear decision trees. The algorithm is based on the hypothesis that nonlinear decision nodes provide a better basis than axis-parallel decision nodes and utilizes discriminant analysis to construct nonlinear decision trees(More)
An important advantage of using a formal method of developing software is that one can prove that development steps are correct with respect to their specification. Conducting proofs by hand, however, can be time consuming to the extent that designers have to judge whether a proof of a particular obligation is worth conducting. Even if hand proofs are worth(More)
This paper develops a new theory and model for information and sensor validation. The model represents relationships between variables using Bayesian networks and utilizes probabilistic propagation to estimate the expected values of variables. If the estimated value of a variable differs from the actual value, an apparent fault is detected. The fault is(More)
Decision tree induction has been has been widely studied and applied. In safety applications, such as determining whether a chemical process is safe, or whether a person has a medical condition, the cost of misclassification in one of the classes is significantly higher than the other class. Several authors have tackled this problem by developing(More)