Following the pioneering work of Allenby and Ginter (1995) and Lenk et al.(1994); we propose in Section 2 a mixed effect model allowing for fixed and random effects as possible statistical solution to the problems mentioned above. Parameter estimation using a new, efficient variant of a Markov Chain Monte Carlo method will be discussed in Section 3 together with problems of model comparison techniques in the context of random effect models. Section 4 presents an application of the former to a brand-price trade-off study from the Austrian mineral water market. (author's abstract) / Series: Forschungsberichte / Institut für Statistik

To compute the expectation of a function with respect to a multivariate distribution naive Monte Carlo is often not feasible. In such cases importance sampling leads to better estimates than the rejection method. A new importance sampling distribution, the product of one-dimensional table mountain distributions with exponential tails, turns out to be flexible and useful for Bayesian integration problems. To obtain a heavy-tailed importance sampling distribution a new radius transform for the above distribution is suggested. Together with a linear transform the new importance sampling distributions lead to simple and fast integration algorithms with reliable error bounds. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

Okun's Law postulates an inverse relationship between movements of the unemployment rate and the real gross domestic product (GDP). Empirical estimates for US data indicate that a two to three percent GDP growth rate above the natural or average GDP growth rate causes unemployment to decrease by one percentage point and vice versa. In this investigation we check whether this postulated relationship exhibits structural breaks by means of Markov-Chain Monte Carlo methods. We estimate a regression model, where the parameters are allowed to switch between different states and the switching process is Markov. As a by-product we derive an estimate of the current state within the periods considered. Using quarterly Austrian data on unemployment and real GDP from 1977 to 1995 we infer only one state, i.e. there are no structural breaks. The estimated parameters demand for an excess GDP growth rate of 4.16% to decrease unemployment by one percentage point. Since only one state is inferred, we conclude that the Austrian economy exhibits a stable relationship between unemployment and GDP growth. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

In magnetic resonance imaging (MRI), sampling methods that lead to incomplete data coverage of k-space are used to accelerate imaging and reduce overall scan time. Non-Cartesian sampling trajectories such as radial, spiral, and random trajectories are employed to facilitate advanced imaging techniques, such as compressed sensing, or to provide more efficient coverage of k-space for a shorter scan period. When k-space is undersampled or unevenly sampled, traditional methods of transforming Fourier data to obtain the desired image, such as the FFT, may no longer be applicable. The Fourier reconstruction of optical interferometer data (FROID) algorithm is a novel reconstruction method developed by A. R. Hajian that has been successful in the field of optical interferometry in reconstructing images from sparsely and unevenly sampled data. It is applicable to cases where the collected data is a Fourier representation of the desired image or spectrum. The framework presented allows for a priori information, such as the positions of the sampled points, to be incorporated into the reconstruction of images. Initially, FROID assumes a guess of the real-valued spectrum or image in the form of an interpolated function and calculates the corresponding integral Fourier transform. Amplitudes are then sampled in the Fourier space at locations corresponding to the acquired measurements to form a model dataset. The guess spectrum or image is then adjusted such that the model dataset in the Fourier space is least squares fitted to measured values. In this thesis, FROID has been adapted and implemented for use in MRI where k-space is the Fourier transform of the desired image. By forming a continuous mapping of the image and modelling data in the Fourier space, a comparison and optimization with respect to data acquired in k-space that is either undersampled or irregularly sampled can be performed as long as the sampling positions are known. To apply FROID to the reconstruction of magnetic resonance images, an appropriate objective function that expresses the desired least squares fit criteria was defined and the model for interpolating Fourier data was extended to include complex values of an image. When an image with two Gaussian functions was tested, FROID was able to reconstruct images from data randomly sampled in k-space and was not restricted to data sampled evenly on a Cartesian grid. An MR image of a bone with complex values was also reconstructed using FROID and the magnitude image was compared to that reconstructed by the FFT. It was found that FROID outperformed the FFT in certain cases even when data were rectilinearly sampled.

For ultra-wideband (UWB) communications, acquisition is challenging. The reason is from the ultra short pulse shape and ultra dense multipath interference. Ultra short pulse indicates the acquisition region is very narrow. Sampling is another challenge for UWB design due to the need for ultra high speed analog-to digital converter.<p>A sub-optimum and under-sampling scheme using pilot codes as transmitted reference is proposed here for acquisition. The sampling rate for the receiver is at the symbol rate. A new architecture, the reference aided matched filter is studied in this project. The reference aided matched filter method avoids using complex rake receiver to estimate channel parameters and high sampling rate for interpolation. A limited number of matched filters are used as a filter bank to search for the strongest path. Timing offset for acquisition is then estimated and passed to an advanced verification algorithm. For optimum performance of acquisition, the adaptive post detection integration is proposed to solve the problem from dense inter-symbol interference during the acquisition. A low-complex early-late gate tracking loop is one element of the adaptive post detection integration. This tracking scheme assists in improving acquisition accuracy. The proposed scheme is evaluated using Matlab Simulink simulations in term of mean acquisition time, system performance and false alarm. Simulation results show proposed algorithm is very effective in ultra dense multipath channels. This research proves reference aided acquisition with tracking loop is promising in UWB application.

At the end of 2005, the State Council of China passed ”The Decision on adjusting the Individual Account of Basic Pension System”, which adjusted the individual account in the 1997 basic pension system. In this essay, we will analyze the adjustment above, and use Life Annuity Actuarial Theory to establish the basic pension substitution rate model. Monte Carlo simulation is also used to prove the rationality of the model. Some suggestions are put forward associated with the substitution rate according to the current policy.

<p>Ssu72 is a protein phosphatase that selectively targets phosphorylated serine residues at the 5th position (pS5) in the heptad repeats of the C-terminal domain (CTD) of RNA polymerase II, in order to regulate the CTD-mediated coupling between eukaryotic transcription and co-transcriptional events. The biological importance of Ssu72 is underscored by (1) the requirement of its activity for viability in yeast, and (2) the numerous phenotypes - affecting all three stages of the transcription cycle - that result from its mutation in yeast. Despite limited homology to the low molecular weight (LMW) subclass of protein tyrosine phosphatases (PTPs), several lines of evidence suggest that Ssu72 represents the founding member of a new class of enzymes, including its unique substrate specificity and an in vivo connection with the activity of proline isomerase Ess1.</p><p>The main focus of this thesis has been to structurally and kinetically characterize Ssu72, in order to define its relation to known enzyme families, to provide biochemical explanations for extant in vivo observations, and to allow future structure-guided investigations of its role in coordinating transcription with co-transcriptional events. To this end, we solved the structure of Ssu72 in complex with its pS5 CTD substrate, revealing an enzyme fold with unique structural features and a surprising substrate conformation with the pS5-P6 motif of the CTD adopting the cis configuration. Together with kinetic assays, the structure provides a new interpretation of the role of proline isomers in regulating the CTD phosphorylation state, with broad implications for CTD biology.</p><p>The second goal of this thesis has been to develop new methods for NMR studies of large proteins, which present unique challenges to conventional methods, including fast signal decay and severe signal degeneracy. The first of these new methods, the `just-in-time' HN(CA)CO, improves the sensitivity of a common backbone assignment experiment. The next two methods, the 4-D diagonal-suppressed TROSY-NOESY-TROSY and the 4-D time-shared NOESY, were designed for use with sparse sampling techniques that allow the acquisition of high-resolution, high-dimensionality datasets. These efforts culminate with global fold calculations for large proteins, including the 23 kDa Ssu72, with accurate and unambiguous automated assignment of NOE crosspeaks. We expect that the methods presented here will be particularly useful as the NMR community continues to push toward higher molecular weight targets.</p> / Dissertation

The research is divided into two main parts: the sensing part and the gas delivery part. The reliable chemical information from the chemical sensor requires that the sensitive layer of the sensor exhibits long-term stability. To improve the stability of the sensing layer, camphorsulfonic acid was added to the formic acid. The introduction of photo-irradiation at 254 nm as an additional treatment to the sensing layer was proved to be effective. For gas selectivity of PANI matrix, metal or metal oxide clusters have been incorporated into the matrix. The composite materials of PANI with silver, copper, iron, nickel, palladium and mercury were also prepared and exposed to different gases. The second part of the thesis discusses the gas delivery system to the sensors using the synthetic jet technology. The sniffing functionality was demonstrated using the designed jet cell for operation in the open system. The gas sniffing experiments showed that in the presence of the jet, the response time of the sensor is faster by about two orders of magnitude (20 compared to 1800 seconds). The jet sampling system was applied to continuous monitoring of ammonia gas filter performance using the chemFET array. The jet system collected the gas before and after filtering, and the difference between the two responses was compared to observe the break-through of the filter. It was concluded that the gas sensing system integrated with the gas sampling functionality can be applied to monitor a gas filter performance. The cell was designed so that the impinging jet covers the sensing active area of the array of eight chemFETs. The two-dimensional distribution of the ammonia gas concentrations showed that the jet covers the active sensing area in an effective way so that the sampling volume for sensing is significantly reduced compared with the conventional gas flow cell system. Based on these initial studies shown in this thesis, the proposed gas sniffing system was shown to be effective in realizing fast detections of gases for critical applications of a gas sensor system.

Nowadays SoC involves both software and hardware designs, performance bottleneck may occur either in software/hardware or even both. But present performance monitoring tools usually evaluates one of software/hardware performance, which is not quite enough for nowadays SoC designs. Furthermore, due to increasing complexity of user requirements, embedded OS, such as Linux is introduced to manage the limited hardware resources for complicated applications. However, it also makes performance monitoring harder since the memory addressing space is divided into user space and kernel space with different capability to access system resources, which makes user space application impossible to retrieve system performance information without kernel or hardware supports. In this thesis, we propose a performance monitoring tool suite which is capable of analyzing the performance of user pace application, kernel space device driver and AMBA AHB bus for SoC running under Linux. We develop Performance Monitoring Tool Suite (PMTS) which includes: Program Monitor (PM) to monitor the execution time of software; Bus Utilization Monitor (BUM), Bus Contention Monitor (BCM) and Bus Global Monitor (BGM) to monitor the bus utilization, contentions¡Ketc. PMTS can help user to find out the performance bottleneck of both software and hardware more easily. We have applied PMTS to FPGA develop board and find out the hardware/software performance bottlenecks of the designs. From the experimental results we can know that adding PMTS won¡¦t impact the critical path of SoC.

This thesis performs a quantitative study, derived from the Neyman-Pearson framework, on the robustness of the matched filter detector corrupted by zero mean, independent and identically distributed white Gaussian noise. The variance of the noise is assumed to be imperfectly known, but some knowledge about a nominal value is presumed. We utilized slope as a unit to quantify the robustness for different signal strengths, nominals, and sample sizes. Following to this, a weighting method is applied to the slope range of interest, the so called tolerable range, as to analyze the likelihood of these extreme slopes to occur. A ratio of the first and last quarter section of the tolerable range have been taken in order to obtain the likelihood ratio for the low slopes to occur. We finalized our analysis by developing a method that quantifies confidence as a measure of robustness. Both weighted and non-weighted procedures were applied over the tolerable range, where the weighted procedure puts greater emphasis on values near the nominal. The quantitative analysis results show the detector to be non-robust and deliver poor performance for low signal-to-noise ratios. For moderate signal strengths, the detector performs rather well if the nominal and sample size are chosen wisely. The detector has great performance and robustness for high signal-to-noise ratios. This even remains true when only a few samples are taken or when the practitioner is uncertain about the nominal chosen.