for potential extension agents before they are going to work at farmers ’ fields and a number of in-service training for field extension agents. However, most of training was crop production oriented and training in extension education has been scarce. Much of the training emphasized on new technical knowledge

and associated learning algorithm for the RVM, and give some illustrative examples of its application along with some comparative benchmarks. We offer some explanation for the exceptional degree of sparsity obtained, and discuss and demonstrate some of the advantageous features, and potential extensions

This paper considers a firm that must issue common stock to raise cash to undertake a valuable investment opportunity. Management is assumed to know more about the firm’s value than potential investors. Investors interpret the firm’s actions rationally. An. equilibrium mode1 of the issue

LT-Codes are a new class of codes introduced in [1] for the purpose of scalable and fault-tolerant distribution of data over computer networks. In this paper we introduce Raptor Codes, an extension of LT-Codes with linear time encoding and decoding. We will exhibit a class of universal Raptor codes

Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. Problems associated with initialization and poor convergence to boundary concavities, however, have limited their utility. This paper presents a new

propose a method to approach this problem by trying to estimate a function f which is positive on S and negative on the complement. The functional form of f is given by a kernel expansion in terms of a potentially small subset of the training data; it is regularized by controlling the length

-mologous residues in a target database sequence. We can always write an ad hoc program for any given problem, but the same potentially frustrating issues will always recur. One issue is that we often want to incorporate multiple heterogenous sources of information. A genefinder, for in-stance, ought to combine

The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a “true” two-dimensional transform that can capture the intrinsic geometrical structure

to be a positive function of the proportion of potentially informed traders in the population, the probability that such a trader is in fact informed (i.e., the probability that a private information signal has in fact been observed), and the preci-sion of the private information. The close dependence

We provide an overview of the extensive recent results on the Shannon capacity of single-user and multiuser multiple-input multiple-output (MIMO) channels. Although enormous capacity gains have been predicted for such channels, these predictions are based on somewhat unrealistic assumptions about