The problem of identification of statistically significant patterns in a sequence of data has been applied to many domains such as intrusion detection systems, financial models, web-click records, automated monitoring systems, computational biology, cryptology, and text analysis. An observed pattern of events is deemed to be statistically significant if it is unlikely to have occurred due to ra...

This paper describes an approach to generating prosody parameters for Mandarin Chinese text-to-speech system. The Chinese fundamental frequency contour is decomposed into two parts, a global intonation contour and a syllable level tone contour. The global intonation contour is converted to pitch target labels in corpus. It is predicted by first predicting pitch target labels using statistical m...

Experiments in NSTX have now demonstrated the coupling of toroidal plasmas produced by the technique of Coaxial Helicity Injection (CHI) to inductive sustainment and ramp-up of the toroidal plasma current. In these discharges, the central Ohmic transformer was used to apply an inductive loop voltage to discharges with a toroidal current of about 100 kA created by CHI. The coupled discharges hav...

Statistical significance is used to ascertain whether the outcome of a given experiment can be ascribed to some extraneous factors or is solely due to chance. An observed pattern of events is deemed to be statistically significant if it is unlikely to have occurred due to randomness or chance alone. In the thesis, we study the problem of identifying the statistically relevant patterns in string...

Inexpensive wearable sensors are well-suited for the automatic recognition of many activities occuring in everyday life. But what about fast and involved movements such as those occuring in athletic sports? We tackle this question by studying the feasibility of using bodyworn gyroscopes and acceleration sensors to recognize Tai Chi movements. To this end, we conducted an initial experiment with...

Many complex engineering problems have multi-objectives where each objective is conflicting with others. However, a lot research Jiradej Ponsawat et al. 2 works in optimization by Competent Genetic Algorithm are focused on single objective methods. These algorithms work very well for single objective problems but stumble when trying to discover a large number of solutions naturally occurred in ...