Balado, Félix(SPIE--The International Society for Optical Engineering, 2010-01)
A number of methods have been proposed over the last decade for embedding information within deoxyribonucleic acid (DNA). Since a DNA sequence is conceptually equivalent to a unidimensional digital signal, DNA data embedding ...
We analyze the maximum number of ways in which one can intrinsically tag
a very particular kind of digital asset: a gene, which is just a DNA sequence that encodes
a protein. We consider gene tagging under the most ...
This paper firstly gives a brief overview of information embedding in deoxyribonucleic acid (DNA) sequences and its applications. DNA data embedding can be considered as a particular case of communications with or without ...
This report explores equality issues arising in the collection and publication of data in Ireland and the ways in which data may be used in equality policies and practices.
A clustering algorithm which is based on density and adaptive density-reachable is developed and presented for arbitrary data point distributions in some real world applications, especially in geophysical data interpretation. ...
DNA data embedding is a relatively recent area which aims at embedding arbitrary information in deoxyribonucleic acid (DNA) strands. One interesting application of DNA data embedding can be tracing pathways of genetic ...
A new family of mixture models for the model-based clustering of longitudinal data is introduced.
The covariance structures of eight members of this new family of models are given and the associated maximum likelihood ...
Item response modelling is a well established method for analysing ordinal response data. Ordinal data are typically collected as responses to a number
of questions or items. The observed data can be viewed as discrete ...
Ranked preference data arise when a set of judges rank, in order of their preference, a set of objects. Such data arise in preferential voting systems and market
research surveys. Covariate data associated with the judges ...
A spatial information system (SIS) is critical to the hosting, querying, and analyzing of spatial data sets. The increasing availability of three-dimensional (3D) data (e.g. from aerial and terrestrial laser scanning) and ...