In this paper, we define the Range LCP problem as follows. Preprocess a string S, of length n, to enable efficient solutions of the following query: Given [i, j], 0 < i ≤ j ≤ n, compute max`,k∈{i,...,j} LCP (S`, Sk), where LCP (S`, Sk) is the length of the longest common prefix of the suffixes of S starting at locations ` and k. This is a natural generalization of the classical LCP problem. Sur...

We investigate models of the mitogenactivated protein kinases (MAPK) network, with the aim of determining where in parameter space there exist multiple positive steady states. We build on recent progress which combines various symbolic computation methods for mixed systems of equalities and inequalities. We demonstrate that those techniques benefit tremendously from a newly implemented graph th...

functional magnetic resonance imaging (fmri) has become the most popular method for imaging of brain functions. currently, there is a large variety of software packages for the analysis of fmri data, each providing many features for users. since there is no single package that can provide all the necessary analyses for the fmri data, it is helpful to know the features of each software package. ...

This paper studies the power of non-restricted preprocessing on a communication graph G, in a synchronous, reliable system. In our scenario, arbitrary preprocessing can be performed on G, after which a sequence of labeling problems have to be solved on diierent subgraphs of G. We suggest a preprocessing that produces an orientation of G. The goal is to exploit this preprocessing for minimizing ...

We present an interactive web tool for preprocessing microarray gene expression data. It analyses the data, suggests the most appropriate transformations and proceeds with them after user agreement. The normal preprocessing steps include scale transformations, management of missing values, replicate handling, flat pattern filtering and pattern standardization and they are required before perfor...

This paper presents a data mining application in metabolomics. It aims at building an enhanced machine learning classifier that can be used for diagnosing cachexia syndrome and identifying its involved biomarkers. To achieve this goal, a data-driven analysis is carried out using a public dataset consisting of 1H-NMR metabolite profile. This dataset suffers from the problem of imbalanced classes...

various destructive and non-destructive methods are used to measure the maturity and internal quality parameters of fruits. destructive methods often consume time and are costly. in this study, the ability of near infrared spectroscopy for prediction of the quality properties such as soluble solids content, titratable acid, ph, total phenol and extract anthocyanin of &apos;bidaneh ghermez&apos;...