the problems of sequential change-point have several important applications in quality control, signal processing, and failure detection in industry and finance. we discuss a bayesian approach in the context of statistical process control: at an unknown time $tau$, the process behavior changes and the distribution of the data changes from p0 to p1. two cases are considered: (i) p0 and p1 are fu...

in this research, the decision on belief (dob) approach was employed to analyze and classify the states of uni-variate quality control systems. the concept of dob and its application in decision making problems were introduced, and then a methodology for modeling a statistical quality control problem by dob approach was discussed. for this iterative approach, the belief for a system being out-o...

We introduce a novel rule-based approach for handling regression problems. The new methodology carries elements from two frameworks: (i) it provides information about the uncertainty of parameters interest using Bayesian inference, and (ii) allows incorporation expert knowledge through systems. blending those different frameworks can be particularly beneficial various domains (e.g., engineering...

A ctin fi laments lie in a wide range of orientations in the leading edge of a migrating cell, according to images from Stefan Koestler, Victor Small (Austrian Academy of Sciences, Vienna, Austria), and colleagues. What looks like disorder might help organize both protrusion at the front and retraction behind. The work casts doubt on the textbook view of the network in the very front of a migra...

In this paper, we present a Non-Bayesian conditioning rule for belief revision. This rule is truly Non-Bayesian in the sense that it doesn’t satisfy the common adopted principle that when a prior belief is Bayesian, after conditioning by X, Bel(X|X) must be equal to one. Our new conditioning rule for belief revision is based on the proportional conflict redistribution rule of combination develo...

We present an algorithm for building rule lists that is two orders of magnitude faster than previous work. Rule list algorithms are competitors for decision tree algorithms. They are associative classifiers, in that they are built from pre-mined association rules. They have a logical structure that is a sequence of IF-THEN rules, identical to a decision list or one-sided decision tree. Instead ...