The EcoRII homodimer engages two of its recognition sequences (5'-CCWGG) simultaneously and is therefore a type IIE restriction endonuclease. To identify the amino acids of EcoRII that interact specifically with the recognition sequence, we photocross-linked EcoRII with oligonucleotide substrates that contained only one recognition sequence for EcoRII. In this recognition sequence, we substitut...

PURPOSE Letter sequence recognition accuracy has been postulated to be limited primarily by low-level visual factors. The influence of high level factors such as visual memory (load and decay) has been largely overlooked. This study provides insight into the role of these factors by investigating the interaction between letter sequence recognition accuracy, letter string length and report condi...

Owing to the linguistic richness of Arabic language, which contains more than 6000 roots, building a reliable language model for speech recognition systems faces many challenges. This paper introduces free automatic system Modern Standard based on an end-to-end-based Deep Speech architecture developed by Mozilla. The proposed uses character-level sequence-to-sequence map character alignment pro...

We present a face recognition method using image sequence. As input we utilize plural face images rather than a `single-shot', so that the input re ects variation of facial expression and face direction. For the identi cation of the face, we essentially form a subspace with the image sequence and apply the Mutual Subspace Method in which the similarity is de ned by the angle between the subspac...

This paper proposed an algorithm for 3D hands tracking on the learned hierarchical latent variable space, which employs a Hierarchical Gaussian Process Latent Variable Model(HGPLVM) to learn the hierarchical latent space of hands motion and the nonlinear mapping from the hierarchical latent space to the pose space simultaneously. Nonlinear mappings from the hierarchical latent space to the spac...

Gene recognition is one of the most important problems in computational molecular biology. Previous attempts to solve this problem were based on statistics, and applications of combinatorial methods for gene recognition were almost unexplored. Recent advances in large-scale cDNA sequencing open a way toward a new approach to gene recognition that uses previously sequenced genes as a clue for re...

This paper proposes a probabilistic sequence kernel based on the universal background model, which is widely used in speaker recognition. The Gaussian components are used to construct the speaker reference space, and the utterances with different length are mapped into the fixed size vectors after normalization with correlation matrix. Finally the linear support vector machine is used for speak...

A biologically inspired neuronal network that stores and recognizes temporal sequences of symbols is described. Each symbol is represented by excitatory input to distinct groups of neurons (symbol pools). Unambiguous storage of multiple sequences with common subsequences is ensured by partitioning each symbol pool into subpools that respond only when the current symbol has been preceded by a pa...

In the last years, the information stored in biological data-sets grew up exponentially, and new methods and tools have been proposed to interpret and retrieve useful information from such data. Most biological data-sets contain biological sequences (e.g., DNA and protein sequences). Thus, it is much significant to have techniques available capable of mining patterns from such sequences to disc...

Digitization can provide a means of preserving the content of the materials by creating an accessible facsimile of the object in order to put less strain on already fragile originals such as out of print books. The document analysis community formed to address this by digitizing the content thus, making it easily shareable over Internet, making it searchable and, enabling language translation o...