Abstract. Freshwater management is challenging, and advance warning that poor water quality was likely, a season ahead, could allow for preventative measures to be put in place. To this end, we developed Bayesian network (BN) seasonal lake prediction. BNs have become popular recent years, but the vast majority are discrete. Here, Gaussian (GBN), simple class of continuous BN. The aim forecast, ...

This paper introduces a new probabilistic graphical model called gated Bayesian network (GBN). This model evolved from the need to represent processes that include several distinct phases. In essence, a GBN is a model that combines several Bayesian networks (BNs) in such a manner that they may be active or inactive during queries to the model. We use objects called gates to combine BNs, and to ...

Measurement of words semantic relatedness plays an important role in a wide range of natural language processing and information retrieval applications, such as full-text search, summarization, classification and clustering. In this paper, we propose an easy to implement and low-cost method for estimating words semantic relatedness. The proposed method is based on the utilization of words tempo...

Human cytomegalovirus (HCMV) strains can be classified into four glycoprotein B (gB) genotypes, and there has been evidence of differences in viral virulence. In this study, intragenic variability of HCMV gB strains was analyzed. The gB gene was amplified by nested polymerase chain reaction using samples from immunosuppressed patients. The genotype of fragments corresponding to the cleavage sit...

A multistage network is a Generalized Butterry Network (GBN) if there are 2 n end-to-end paths, (P 0 ; P 1 ; ; P n?1), that cover all the vertices and are vertex disjoint and for any two consecutive stages k and k + 1 there is an integer`s.t. the k-th vertex of P i is adjacent to the (k + 1)-th vertex of P j ii the binary presentations of i and j diier at most at thè-th bit. The GBN family cont...

In non-stationary channels, error rates vary considerably. The paper compares Yao’s Adaptive Go-backN (GBN) Automatic-Repeat-Request (ARQ) scheme with Adaptive go-back-N with sliding window mechanism which both estimate the channel state in a simple manner, and adaptively switch their operation mode. The throughput of these schemes is compared in conditions of Additive White Gauss Noise (AWGN) ...

Learning the structure of a graphical model from data is a common task in a wide range of practical applications. In this paper we focus on Gaussian Bayesian networks (GBN), that is, on continuous data and directed graphs. We propose to work in an equivalence class search space that, combined with regularization techniques to guide the search of the structure, allows to learn a sparse network c...