In this paper, we have tried to predict earthquake events in a cluster of seismic data on pacific ring of fire, using multivariate adaptive regression splines (MARS). The model is employed as either a predictor for a sequence prediction task, or a binary classifier for a sequence recognition problem, which could alternatively help to predict an event. Here, we explain that sequence prediction/r...

Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems significantly improves the performance of these systems. There are two phases in DNN-based phoneme recognition systems including training and testing. Mos...

A three dimensional model of the basic Helix-Loop-Helix motif and its sequence specific recognition of DNA is described. The basic-helix I is modeled as a continuous ?-helix because no ?-helix breaking residue is found between the basic region and the first helix. When the basic region of the two peptide monomers are aligned in the successive major groove of the cognate DNA, the hydrophobi...

Background and Objectives: Action recognition, as the processes of labeling an unknown action of a query video, is a challenging problem, due to the event complexity, variations in imaging conditions, and intra- and inter-individual action-variability. A number of solutions proposed to solve action recognition problem. Many of these frameworks suppose that each video sequence includes only one ...

Uncovering DNA sequence variations that correlate with phenotypic changes, e.g., diseases, is the aim of sequence variation studies. Common types sequence variations are Single nucleotide polymorphism (SNP, pronounced snip).SNPs are the third-generation molecular marker. SNP represents a DNA sequence variant of a single base pair with the minor allele occurring in more than 1% of a given popula...