Testing of delay defects is necessary in deep submicron (DSM) technologies. High coverage delay tests produced by automatic test pattern generation (ATPG) can be applied during wafer and package tests, but are difficult to apply during the board test, due to limited chip access. Delay testing at the board level is increasingly important to diagnose failures caused by supply noise or temperature in the board environment. An alternative to ATPG is the built-in self test (BIST). In combination with the insertion of test points, BIST is able to achieve high coverage of stuck-at and transition faults. The quality of BIST patterns on small delay defects is an open question. In this work we analyze the application of BIST to small delay defects using resistive short and open models in order to estimate the coverage and correlate the coverage to traditional delay fault models.

Bus Signal Priority (BSP), which has been deployed in many cities around the world, is a traffic signal enhancement strategy that facilitates efficient movement of buses through signalized intersections. Most BSP systems do not work well in transit networks with nearside bus stop because of the uncertainty in dwell time. Unfortunately, most bus stops on arterial roadways are of this type in the U.S. This dissertation showed that dwell time at nearside bus stops could be modeled using weighted least squares regression. More importantly, the prediction intervals associated with the estimate dwell time were calculated. These prediction intervals were subsequently used in the improved BSP algorithm that attempted to reduce the negative effects of nearside bus stops on BSP operations. The improved BSP algorithm was tested on urban arterial section of Bellaire Boulevard in Houston, Texas. VISSIM, a micro simulation model was used to evaluate the performance of the BSP operations. Prior to evaluating the algorithm, the parameters of the micro simulation model were calibrated using an automated Genetic Algorithm based methodology in order to make the model accurately represent the traffic conditions observed in the field. It was shown that the improved BSP algorithm significantly improved the bus operations in terms of bus delay. In addition, it was found that the delay to other vehicles on the network was not statistically different from other BSP algorithms currently being deployed. It is hypothesized that the new approach would be particularly useful in North America where there are many transit systems that utilize nearside bus stops in their networks.

Nowadays, the administration environment is changing rapidly. Since International Institute for Management Development¡]IMD¡^selects ¡§government efficiency¡¨ and ¡§business efficiency¡¨ as the major factors and criteria to compute the rankings of world competitiveness in the World Competitiveness Yearbook. Both governments and enterprises force to innovate and need to strengthen organizational performance to promote work efficiency, and to improve the strategic management system. This research applies the organizational performance theme in public institutions as well as in the operations of private enterprises by using the Balanced Scorecard¡¦s concept for measuring the scale operational activities of organization. To verify the performance of organization management, the questionnaire picks ¡§Likert Scale¡¨ criteria, and adopts the fuzzy membership function transformation to obtain measuring results. The purposes of this research are: 1) to design a performance measure scale with content validity based on Balanced Scorecord; 2) to compare weighted and fuzzy algorithm; 3) to to verify the worth of fuzzy algorithm. The results of this research are: 1) fuzzy algorithm is better than weighted algorithm in validity; 2) the Balance Scorecard helps organizational performance; 3) customer perspective is the first priority of performance measures in the Balanced Scorecard.

Let X be a compact Hausdorff topological space. The Banach space C(X) consists of all continuous complex value functions with the supnorm. An operator P on C(X) is called a generalized bicircular projection if P + £f(I − P) is an isometry for all |£f| = 1, £f in C and P2 = P. In this thesis, we study some projections which are the averages of two composition operators or two weighted composition operators on C(X). If a projection is the average of the identity and a composition operator, it is a generalized bicircular projection. And give an example of a projection which is the average of the identity and a weighted composition operator, but not a generalized bicircular projection. We also discuss some projections which are the average of two bounded linear operators on a Banach space. And the main result is that, let T1 and T2 are two bounded linear operators on a Banach space, and Q = T1+T2 2 . If T1 ¡CT2 = T2 ¡CT1 and T2 1 = T2 2 = Id then Q is a tripotent, i.e. Q3 = Q.

We build a two-pass Mandarin Automatic Speech Recognition (ASR) decoder on mobile device (PDA). The first-pass recognizing base syllable is implemented by discrete Hidden Markov Model (HMM) with time-synchronous, tree-lexicon Viterbi search. The second-pass dealing with language model, pronunciation lexicon and N-best syllable hypotheses from first-pass is implemented by Weighted Finite State Transducer (WFST). The best word sequence is obtained by shortest path algorithms over the composition result. This system limits the application in travel domain and it decouples the application of acoustic model and the application of language model into independent recognition passes. We report the real-time recognition performance performed on ASUS P565 with a 800MHz processor, 128MB RAM running Microsoft Window Mobile 6 operating system. The 26-hour TCC-300 speech data is used to train 151 acoustic model. The 3-minute speech data recorded by reading the travel-domain transcriptions is used as the testing set for evaluating the performances (syllable, character accuracies) and real-time factors on PC and on PDA. The trained bi-gram model with 3500-word from BTEC corpus is used in second-pass. In the first-pass, the best syllable accuracy is 38.8% given 30-best syllable hypotheses using continuous HMM and 26-dimension feature. Under the above syllable hypotheses and acoustic model, we obtain 27.6% character accuracy on PC after the second-pass.

When scientists collect data to be analyzed, regardless of what quantities are being measured, there are inevitably errors in the measurements. In cases where two independent variables are measured with errors, many existing techniques can produce an estimated least-squares linear fit to the data, taking into consideration the size of the errors in both variables. Yet some experiments yield data that do not only contain errors in both variables, but also a non-zero covariance between the errors. In such situations, the experiment results in measurements with error ellipses with tilts specified by the covariance terms. Following an approach suggested by Dr. Edward Robinson, Professor of Astronomy at the University of Texas at Austin, this report describes a methodology that finds the estimates of linear regression parameters, as well as an estimated covariance matrix, for a dataset with tilted error ellipses. Contained in an appendix is the R code for a program that produces these estimates according to the methodology. This report describes the results of the program run on a dataset of measurements of the surface brightness and Sérsic index of galaxies in the Virgo cluster. / text

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In the past ten years, there have been 194 hurricane-damaged platforms in the Gulf of Mexico (GOM), each with many wells that have not been permanently abandonment. This could lead to disastrous environmental consequence. The wells where their platforms were destroyed by hurricanes cannot be abandoned by conventional methods. Our research showed that barite-weighted epoxy material could be potentially used for well abandonment for those wells in GOM. Shear bond strength tests showed that between two candidates epoxy systems - the bisphenol A system and the bisphenol F system, the latter was less sensitive to barite weighting material. The shear bond strength of besphenol A system was deteriorated as barite increased, while bisphenol F system showed slightly increasing trend when barite was added. The minimum bond strength given by bisphenol A system appears around 68 wt% of barite, which is around 1290 psi. The maximum value of 2200 psi comes at 0 wt% of barite. And the bisphenol F system can stand a minimum of 1010 psi bond strength at 0 wt% of barite, and a maximum of 1160 psi of bond strength with 70 wt% of barite. Moreover, mixing with seawater did influence the shear bond strength between epoxy system and low-carbon steel. The influence that seawater has on the F system is less than that of the A system. The time that the epoxy system needs to fully develop the bond is far longer than curing time determined in our parallel research. Bond strength is lower in both seawater environment and at high temperature.

We introduce methods for dealing with linear programming (LP) problems with uncertain data, using the notion of weighted analytic centers. Our methods are based on high interaction with the decision maker (DM) and try to find solutions which satisfy most of his/her important criteria/goals. Starting with the drawbacks of different methods for dealing with uncertainty in LP, we explain how our methods improve most of them. We prove that, besides many practical advantages, our approach is theoretically as strong as robust optimization. Interactive cutting-plane algorithms are developed for concave and quasi-concave utility functions. We present some probabilistic bounds for feasibility and evaluate our approach by means of computational experiments.