NASTRAN migration to UNIX

COSMIC/NASTRAN, as it is supported and maintained by COSMIC, runs on four main-frame computers - CDC, VAX, IBM and UNIVAC. COSMIC/NASTRAN on other computers, such as CRAY, AMDAHL, PRIME, CONVEX, etc., is available commercially from a number of third party organizations. All these computers, with their own one-of-a-kind operating systems, make NASTRAN machine dependent. The job control language (JCL), the file management, and the program execution procedure of these computers are vastly different, although 95 percent of NASTRAN source code was written in standard ANSI FORTRAN 77. The advantage of the UNIX operating system is that it has no machine boundary. UNIX is becoming widely used in many workstations, mini's, super-PC's, and even some main-frame computers. NASTRAN for the UNIX operating system is definitely the way to go in the future, and makes NASTRAN available to a host of computers, big and small. Since 1985, many NASTRAN improvements and enhancements were made to conform to the ANSI FORTRAN 77 standards. A major UNIX migration effort was incorporated into COSMIC NASTRAN 1990 release. As a pioneer work for the UNIX environment, a version of COSMIC 89 NASTRAN was officially released in October 1989 for DEC ULTRIX VAXstation 3100 (with VMS extensions). A COSMIC 90 NASTRAN version for DEC ULTRIX DECstation 3100 (with RISC) is planned for April 1990 release. Both workstations are UNIX based computers. The COSMIC 90 NASTRAN will be made available on a TK50 tape for the DEC ULTRIX workstations. Previously in 1988, an 88 NASTRAN version was tested successfully on a SiliconGraphics workstation

Surface Impedance and Bulk Band Geometric Phases in One-Dimensional Systems

Surface impedance is an important concept in classical wave systems such as photonic crystals (PCs). For example, the condition of an interface state formation in the interfacial region of two different one-dimensional PCs is simply Z_SL +Z_SR=0, where Z_SL (Z_SR)is the surface impedance of the semi-infinite PC on the left- (right-) hand side of the interface. Here, we also show a rigorous relation between the surface impedance of a one-dimensional PC and its bulk properties through the geometrical (Zak) phases of the bulk bands, which can be used to determine the existence or non-existence of interface states at the interface of the two PCs in a particular band gap. Our results hold for any PCs with inversion symmetry, independent of the frequency of the gap and the symmetry point where the gap lies in the Brillouin Zone. Our results provide new insights on the relationship between surface scattering properties, the bulk band properties and the formation of interface states, which in turn can enable the design of systems with interface states in a rational manner

On-line Bayes adaptation of SCHMM parameters for speech recognition

On-line adaptation of semi-continuous (or tied mixture) hidden Markov model (SCHMM) is studied. A theoretical formulation of the segmental quasi-Bayes learning of the mixture coefficients in SCHMM for speech recognition is presented. The practical issues related to the use of this algorithm for on-line speaker adaptation are addressed. A pragmatic on-line adaptation approach to combine the long-term adaptation of the mixture coefficients and the short-term adaptation of the mean vectors of the Gaussian mixture components are also proposed. The viability of these techniques are confirmed in a series of comparative experiments using a 26-word English alphabet vocabulary.published_or_final_versio

Contextual modeling of hand written Chinese character for recognition. II. Discriminative training

This is an extension of a companion paper entitled 'Contextual Modeling of Hand Written Chinese Character for Recognition (I) - A Comparative Study' which is also submitted to this conference for presentation. In this investigation, contextual models are discriminatively trained using a gradient projection technique. Both open test and close test recognition rates are substantially upgraded when compared with the results of the decision directed training algorithm reported in the other paper.published_or_final_versio

On-line adaptation of the SCHMM parameters based on the segmental quasi-bayes learning for speech recognition

On-line quasi-Bayes adaptation of the mixture coefficients and mean vectors in semicontinuous hidden Markov model (SCHMM) is studied. The viability of the proposed algorithm is confirmed and the related practical issues are addressed in a specific application of on-line speaker adaptation using a 26-word English alphabet vocabulary.published_or_final_versio

A discrete contextual stochastic model for the off-line recognition of handwritten Chinese characters

We study a discrete contextual stochastic (CS) model for complex and variant patterns like handwritten Chinese characters. Three fundamental problems of using CS models for character recognition are discussed, and several practical techniques for solving these problems are investigated. A formulation for discriminative training of CS model parameters is also introduced and its practical usage investigated. To illustrate the characteristics of the various algorithms, comparative experiments are performed on a recognition task with a vocabulary consisting of 50 pairs of highly similar handwritten Chinese characters. The experimental results confirm the effectiveness of the discriminative training for improving recognition performance.published_or_final_versio