Normal 0 false false false ...

Employing a machine learning approach we predict, up to 24 hours prior, a diagnosis of severe sepsis. Strongly predictive models are possible that use only text reports from the Electronic Health Record (EHR), and omit structured numerical data. Unstructured text alone gives slightly better performance than structured data alone, and the combination further improves performance. We also discuss...

The so-called Frobenius number in the famous linear Diophantine problem of is largest integer such that equation [Formula: see text] ([Formula: are given positive integers with text]) does not have a non-negative solution text]. generalized (called text]-Frobenius number) this has at most solutions. That is, when text], original number. In paper, we introduce and discuss text]-numerical semigro...

In this paper, a second-order nonlinear singular boundary value problem is presented, which is equivalent to the well-known Falkner-Skan equation. And the one-dimensional third-order boundary value problem on interval [Formula: see text] is equivalently transformed into a second-order boundary value problem on finite interval [Formula: see text]. The finite difference method is utilized to solv...

Modern epidemiology integrates knowledge from heterogeneous collections of data consisting of numerical, descriptive and imaging. Largescale epidemiological studies use sophisticated statistical analysis, mathematical models using differential equations and versatile analytic tools that handle numerical data. In contrast, knowledge extraction from images and descriptive information in the form ...

This paper proposes a symbolic pattern retrieval method using emotional feature vectors. Queries and symbolic patterns are represented by emotional vectors composed of eight numerical parameters. Since the proposed method uses numerical vectors close to raw data instead of recognized text, the information loss by data conversion is small. This point is advantageous compared with conventional te...

Clustering is an unsupervised learning method that determines partitions and (possibly) prototypes from pattern sets. Sets of numerical patterns can be clustered by alternating optimization (AO) of clustering objective functions or by alternating cluster estimation (ACE). Sets of non–numerical patterns can often be represented numerically by (pairwise) relations. These relational data sets can ...

Sarcasm occurring due to the presence of numerical portions in text has been quoted as an error made by automatic sarcasm detection approaches in the past. We present a first study in detecting sarcasm in numbers, as in the case of the sentence ‘Love waking up at 4 am’. We analyze the challenges of the problem, and present Rulebased, Machine Learning and Deep Learning approaches to detect sarca...

A vast number of mathematical models in various areas of science and engineering involve differential equations. This chapter provides a starting point for a journey into the branch of scientific computing that is concerned with the simulation of differential problems. We shall concentrate mostly on developing methods and concepts for solving initial value problems for ordinary differential equ...