experimental allergic encephalomyelitis (eae), a demyelinating disease induced in the animals parallels multiple sclerosis in human in several aspects, provides a useful model to investigate multiple sclerosis. in this study, we have therefore used this model to study functions of nerve growth factor (ngf) in eae. ngf with considerable effects on neuron survival, proliferation and differentiati...

The problem of imputing missing observations under the linear regression model is considered. It is assumed that observations are missing at random and all the observations on the auxiliary or independent variables are available. Estimates of the regression parameters based on singly and multiply imputed values are given. Jackknife as well as bootstrap estimates of the variance of the singly im...

Hidden Markov models (HMMs) are stochastic models capable of statistical learning and classification. They have been applied in speech recognition and handwriting recognition because of their great adaptability and versatility in handling sequential signals. On the other hand, as these models have a complex structure, and also because the involved data sets usually contain uncertainty, it is di...

It is a dif£cult task to hand-code optimal condition-action rules for software agents. A solution to this is reinforcement learning. In reinforcement learning, agents acquire the condition-action rules by learning from their experiences. However, acquisition of complicated rules might take a great amount of learning time and learning might not converge. To solve these drawbacks, an approach cal...

Model based diagnosis finds a growing range of practical applications, and significant performance-wise improvements have been achieved in recent years. Some of these improvements result from formulating the problem with maximum satisfiability (MaxSAT). Whereas recent work focuses on analyzing failing observations separately, it is also the case that in practical settings there may exist many f...

Peot, M.A. and R.D, Shachter, Fusion and propagation with multiple observations in belief networks (Research Note), Artificial Intelligence 48 (1991) 299-318. The Polytree Algorithm of Kim and Pearl [16, 19] is a fundamental method for evidential reasoning in belief networks. Not only does it provide exact solutions to singly connected networks using efficient, local computations, but variation...

This paper addresses the problem of detecting suspicious behavior from a collection of individuals events, where no single event is enough to decide whether his/her behavior is suspicious, but the combination of multiple events enables reasoning. We establish a Bayesian framework for evaluating multiple events and show that the current approaches lack modeling behavior history included in the e...

Multiple sclerosis is a disease with complex immune system interactions that are being painstakingly elucidated by various means of experimentation. Great effort is being put forth to discover disease processes that may be affected by immunomodulatory therapies. Difficulties of experimentation and the ability to compare separate experiments in the same context notwithstanding, results from vari...

Abstract: This paper proposes a set of observers for attitude estimation based on multiple general time-varying reference vectors, in inertial coordinates, and corresponding vectors, in body-fixed coordinates, in addition to angular velocity readings. The observer error dynamics are globally exponentially stable (GES) and problems such as singularities, unwinding phenomena, or topological limit...