The causes for surface defects in the con tinuouscasting process must be understood so that surface defects can be eradicated. The defects which were considered are presented and an approach to eliminate many of the in uencing variables using statistical hypothesis testing is presented. These methods show that only the thermocouple temperature readings within the mould are necessary to accurate...

The paper studies problem of continuous time optimal portfolio selection for a diffusion model of incomplete market. It is shown that, under some mild conditions, the suboptimal strategies for investors with different performance criterions can be constructed using a limited number of fixed processes (mutual funds), for a market with a larger number of available risky stocks. In other words, a ...

1 Department of Integrative Biology, Ecology, Evolutionary Biology, and Behavior Graduate Group, Michigan State University, MI 48824 2 Center for Population Biology, Department of Evolution and Ecology, University of California, Davis, CA 95616 3 Institute of Ecology and Evolution, Departments of Mathematics and Biology, University of Oregon, Eugene, OR 97403 a [email protected]; b gmcoop@ucdavi...

UNLABELLED Evaluation of protein structure prediction methods is difficult and time-consuming. Here, we describe EVA, a web server for assessing protein structure prediction methods, in an automated, continuous and large-scale fashion. Currently, EVA evaluates the performance of a variety of prediction methods available through the internet. Every week, the sequences of the latest experimentall...

There is growing interest in artificial, intelligent agents which can operate autonomously for an extended period of time in complex environments and fulfill a variety of different tasks. Such agents will face different problems during their lifetime which may not be foreseeable at the time of their deployment. Thus, the capacity for lifelong learning of new behaviors is an essential prerequisi...

In this paper we present a probabilistic non-parametric conditional independence test of X and Y given a third variable Z in domains where X, Y , and Z are continuous. This test can be used for the induction of the structure of a graphical model (such as a Bayesian or Markov network) from experimental data. We also provide an effective method for calculating it from data. We show that our metho...

Bayesian networks in general, and continuous variable networks in particular, have become increasingly popular in recent years, largely due to advances in methods that facilitate automatic learning from data. Yet, despite these advances, the key task of learning the structure of such models remains a computationally intensive procedure, which limits most applications to parameter learning. This...

We develop a theory of the pole topology of the Laplace transform of the structure functions of continuous N component systems based on the Wiener-Hopf technique. We classify systems according to the spectrum of the NxN matrix Q(t), with elements Q(ij)(t)=delta(ij)-2pi square root [rho(i)rho(j)]integrale(-tr)q(ij)(r)dr, associated with their factor functions q(ij)(r). For the simplest nontrivia...

Development cycles are getting shorter and Continuous Integration and Delivery are being established in the automotive industry. We give an overview of the peculiarities in an automotive deployment pipeline, introduce technologies used and analyze Tesla’s deliveries as a state-of-the-art showcase.

Graphical models are widely used to reason about high-dimensional domains. Yet, learning the structure of the model from data remains a formidable challenge, particularly in complex continuous domains. We present a highly accelerated structure learning approach for continuous densities based on the recently introduced Copula Bayesian Network representation. For two common copula families, we pr...