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A plausible representation of relational information among entities in dynamic systems such as a living cell or a social community is a stochastic network which is topologically rewiring and semantically evolving over time. While there is a rich literature on modeling static or temporally invariant networks, much less has been done toward modeling the(More)
In a dynamic social or biological environment, the interactions between the underlying actors can undergo large and systematic changes. The latent roles or membership of the actors as determined by these dynamic links will also exhibit rich temporal phenomena, assuming a distinct role at one point while leaning more towards a second role at an another(More)
Recently, more and more intelligent algorithms are applied to biomedical, which have improved the biomedical data analysis and classification greatly. In this paper, a new method of automatic identification of heart sound by using DTW (dynamic time warping) and MFCC (Mel-frequency cepstral coefficients) of heart is introduced. MFCC of heart sound are(More)
It is important to extract minutiae of a fingerprint for the implementation of an auto fingerprint identification system. In this paper, the principal graph algorithm proposed by Kegl is used to obtain principal curves, which can be served as the skeletons of a fingerprint. Based on the obtained principal curves, a minutiae extraction algorithm is proposed(More)
MOTIVATION Identifying transcription factor binding sites (TFBSs) encoding complex regulatory signals in metazoan genomes remains a challenging problem in computational genomics. Due to degeneracy of nucleotide content among binding site instances or motifs, and intricate 'grammatical organization' of motifs within cis-regulatory modules (CRMs), extant(More)
Multi-core processors with ever increasing number of cores per chip are becoming prevalent in modern parallel computing. Our goal is to make use of the multi-core as well as multi-processor architectures to speed up data mining algorithms. Specifically, we present a parallel algorithm for approximate learning of Linear Dynamical Systems (LDS), also known as(More)
In a dynamic social or biological environment, the interactions between the actors can undergo large and systematic changes. In this paper we propose a model-based approach to analyze what we will refer to as the dynamic tomography of such time-evolving networks. Our approach offers an intuitive but powerful tool to infer the semantic underpinnings of each(More)
  • Jyoti Rajharia, P. C. Gupta, +11 authors Loris Nann
  • 2012
Fingerprint recognition is one of the oldest form of biometric identification. It has been used for over a century because of their uniqueness and consistency over time. In this paper a new approach has been used in which feed forward back propagation neural network is implemented through matlab. The result obtained shows that the proposed approach somewhat(More)