Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains viii, 58 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 55-58).

This paper analyzes a proposed release controlmethodology, WIPLOAD Control (WIPLCtrl), using a transfer line case modeled by Markov process modeling methodology. The performance of WIPLCtrl is compared with that of CONWIP under 13 system configurations in terms of throughput, average inventory level, as well as average cycle time. As a supplement to the analytical model, a simulation model of the transfer line is used to observe the performance of the release control methodologies on the standard deviation of cycle time. From the analysis, we identify the system configurations in which the advantages of WIPLCtrl could be observed. / Singapore-MIT Alliance (SMA)

by J. Keilson, M. Zachmann. / Bibliography: p. 28. / "August 1981." / U.S.A.F. OSR Grant Number AFOSR-79-0043 U. S. Air Force Geophysics Laboratory Grant Number F19628-80-C-0003 National Science Foundation Grant Number NSF/ECS 79-19880

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1977. / Also available via the Internet.

This thesis focuses on the search for neutrinos from the solar hep reaction using the combined three phases of the Sudbury Neutrino Observatory (SNO) data. The data were taken over the years 19992006, totalling 1,083 days of live neutrino time. The previous published SNO hep neutrino search was completed in 2001 and only included the first phase of data taking. That hep search used an event counting approach in one energy bin with no energy spectral information included. This thesis will use a spectral analysis approach. The hep neutrino search will be a Bayesian analysis using Markov Chain Monte Carlo (MCMC), and a Metropolis-Hastings algorithm to sample the likelihood space. The method allows us to determine the best fit values for the parameters. This signal extraction will measure the 8B flux, the atmospheric neutrino background rate in the SNO detector, and the hep flux. This thesis describes the tests used to verify the MCMC algorithm and signal extraction. It defines the systematic uncertainties and how they were accounted for in the fit. It also shows the correlations between all of the parameters and the effect of each systematic uncertainty on the result. The three phase hep signal extraction was completed using only 1/3 of the full data set. With these lowered statistics, this analysis was able to place an upper limit on the hep flux of 4.2 10^4 cm2 s1 with a 90% confidence limit. It was able to measure a hep flux of (2.40(+1.19)(-1.60))10^4 cm2 s1. These numbers can be compared with the previous SNO upper limit of 2.310^4 cm2 s1 with a 90% confidence limit, and the standard solar model prediction of (7.970 1.236) 10^3 cm2 s1.

Two brain segmentation approaches based on Hidden Markov Models are proposed. The first approach aims to segment normal brain 3D multi-channel MR images into three tissues WM, GM, and CSF. Linear Discriminant Analysis, LDA, is applied to separate voxels belonging to different tissues as well as to reduce their features vector size. The second approach aims to detect MS lesions in Brain 3D multi-channel MR images and to label WM, GM, and CSF tissues. Preprocessing is applied in both approaches to reduce the noise level and to address sudden intensity and global intensity correction. The proposed techniques are tested using 3D images from Montereal BrainWeb data set. In the first approach, the results were numerically assessed and compared to results reported using techniques based on single channel data and applied to the same data sets. The results obtained using the multi channel HMM-based algorithm were better than the results reported for single channel data in terms of an objective measure of overlap, Dice coefficient, compared to other methods. In the second approach, the segmentation accuracy is measured using Dice coefficient and total lesions load percentage

Thesis (M. Phil.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

In this thesis, a two-word, three-word and four-word Mandarin phrases speech recognition system is studied and implemented. This system utilizes hidden Markov model, lexicon search strategy and tone recognition to select the initial phrase candidates and make the final decision. Experimental results indicate that using about one third of the total phrase population, 80%, 92% and 97% correct rates can be achieved for the 70,000 two-word, 24,000 three-word and 22,000 four-word phrases recognition problems respectively. Any spoken phrase can be found within 1 second, using a PC with Intel Celeron 2.4 GHz CPU and Red Hat Linux 9.0 operating system.

In this thesis, hidden Markov model, maximum likelihood ratio and lexicon search strategy are used to establish a Chinese resume inputting system. The resume contains five items: name introduction, gender, birth date, birth place and education. This system is developed using a PC with an Intel Pentium 1.6 GHz CPU and Red Hat Linux 9.0 operating system. For the speaker-dependent case, a resume can be completed within 45 seconds on the average.

The objective of this thesis is to design and implement a speech recognition system for one hundred thousand Chinese names. Mel frequency cepstrum coefficient, hidden Markov model and lexicon search strategy are utilized to choose the name candidates. Furthermore, a mandarin intonation technique is also incorporated into this system to increase the final speech recognition accuracy. The experimental results indicate that for the speaker dependent case, an 85% correct rate can be achieved by use of the proposed intonation classification scheme and the balanced monosyllable training database. The above correct rate has an increase of 8% over the previous method without using these two techniques. Under Redhat Linux 9.0 environment, a mandarin name can be recognized within 2 seconds by the use of a computer with Intel Celeron 2.4 GHz CPU.