Introduction to Algorithms

TL;DR: A new algorithm for exploiting the nonlinear structure of hyperspectral imagery is developed and compared against the de facto standard of linear mixing, and it is demonstrated that the new manifold representation provides better separation of spectrally similar classes than one of the standard linear mixing models.

TL;DR: In this literature survey, different aspects of dynamics of two-phase flow in porous media are discussed and dynamic pore-network models are reviewed under different classifications; structure, computational algorithm, and local rules and applications.

TL;DR: A critical and systematic review of renewable energy and electricity prediction models applied as an energy planning tool and three major states-of-art forecasting classifications: machine learning algorithms; ensemble-based approaches; iii) and artificial neural networks are analyzed.

TL;DR: The detection of communities with temporal smoothness is formulated as a multiobjective problem and a method based on genetic algorithms is proposed and the main advantage of the algorithm is that it automatically provides a solution representing the best trade-off between the accuracy of the clustering obtained, and the deviation from one time step to the successive.

TL;DR: In this paper, a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments is introduced based on the theory of support vector machines (SVMs).

TL;DR: DNA microarray analysis was used to assay gene expression levels in postmortem dorsolateral prefrontal cortex of schizophrenic and control patients, and differential expression of myelination-related genes suggesting a disruption in oligodendrocyte function in schizophrenia were identified.

TL;DR: It is proved that the value of the span is always smaller (and can be much smaller) than the diameter of the smallest sphere containing the support vectors, used in previous bounds.

TL;DR: The Stuttgart Neural Net Simulator was used to train algorithms on a data set of 2,182 randomly selected siRNAs targeted to 34 mRNA species, assayed through a high-throughput fluorescent reporter gene system and BIOPREDsi was used in the design of a genome-wide siRNA collection with two potent si RNAs per gene.