Blockchain is an emerging technology for decentralized and transactional data sharing across a large network of untrusted participants. It enables new forms of distributed software architectures, where components can find agreements on their shared states without trusting a central integration point or any particular participating components. Considering the block- chain as a software connector...

Blockchain is an emerging technology for decentralized and transactional data sharing across a large network of untrusted participants. It enables new forms of distributed software architectures, where components can find agreements on their shared states without trusting a central integration point or any particular participating components. Considering the block- chain as a software connector...

This paper proposes a method for measuring semantic similarity between words as a new tool for text analysis. The similarity is measured on a semantic network constructed systematically from a subset of the English dictionary, LDOCE (Longman Dictionary of Contemporary English). Spreading activation on the network can directly compute the similarity between any two words in the Longman De ning V...

The events which occur in an Intensive Care Unit (ICU) are many and varied. Very often, events which are important to an understanding of what has happened to the patient are not recorded in the electronic patient record. This paper describes an approach to the automatic detection of such unrecorded 'target' events which brings together signal analysis to generate temporal patterns, and tempora...

The problem of minimum cost extension of an existing communication network, over a given time period [0,T], is stated and formulated. A two phase solution method is then described, in which: a) an optimal long-range configuration is sought, assuming static routing all over the period [0,T]; b) the optimal dynamic routing problem is solved by relaxing the fixed routing assumption, and taking int...

In this study, we applied the local learning paradigm and conditional independence assumptions to control the rapid growth of the dimensionality introduced by multivariate time series. We also combined various univariate time series with different stationary assumptions in temporal models. These techniques are applied to learn simple Bayesian networks from temporal data and to predict survival ...

The measurement of semantic relatedness between two words is an important metric for many natural language processing applications. In this paper, we present a novel approach for measuring semantic relatedness that is based on a weighted semantic network. This approach explores the use of a lexicon, semantic relation types as weights, and word definitions as a basis to calculate semantic relate...

A total of 1099 data points consisting of alcohol-alcohol, alcohol-alkane, alkane-alkane, alcohol-amine and acid-acid binary solutions were collected from scientific literature to develop an appropriate artificial neural network (ANN) model. Temperature, molecular weight of the pure components, mole fraction of one component and the structural groups of the components were used as input paramet...