In this paper I argue that both parametric variation and the alleged differences between languages in terms of their internal complexity straightforwardly follow from the Strongest Minimalist Thesis that takes the Faculty of Language (FL) to be an optimal solution to conditions that neighboring mental modules impose on it. In this paper I argue that hard conditions like legibility at the linguistic interfaces invoke simplicity metrices that, given that they stem from different mental modules, are not harmonious. I argue that widely attested expression strategies, such as agreement or movement, are a direct result of conflicting simplicity metrices, and that UG, perceived as a toolbox that shapes natural language, can be taken to consist of a limited number of markings strategies, all resulting from conflicting simplicity metrices. As such, the contents of UG follow from simplicity requirements, and therefore no longer necessitate linguistic principles, valued or unvalued, to be innately present. Finally, I show that the SMT does not require that languages themselves have to be optimal in connecting sound to meaning.

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The main idea of our work is the calibration parameters for the Heston stochastic volatility model. We make this procedure by using the OMXS30 index from the NASDAQ OMX Nordic Exchange Market. We separate our data into the stable period and high-volatility period on this Nordic Market. Deviation detection problem are solved using the Bayesian analysis of change-points. We estimate parameters of the Heston model for each of periods and make some conclusions.

In present day, digital signal processing (DSP) is a popular technology and widely used in many fields. There have increasing number of applications that need high resolution converters. Therefore, analog-to-digital converters play a major role in DSP, and a well-performed ADC will enhance the performance of a certain system. Different types of ADCs are available for various functions. Delta-sigma  converters are famous for high resolution. Dynamic parameters can be used to judge the performance of an ADC, this paper will focus on the critical parameters of spectrum analysis, which contains Signal-to-Noise-and-Distortion Ratio (SINAD), Effective Number of Bits (ENOB) and Spurious-free Dynamic Range (SFDR). The theory and test method of these critical parameters are proposed in this paper using the Evaluation Module and Matlab. The results we acquired from the Evaluation Module are SINAD=86.15dB, SFDR=109.2dB, ENOB=14.177bits; and the results we calculated from MATLAB are: SINAD=86.14dB, SFDR=108.8dB, ENOB=14bits.

A framework for assessing the key statistical parameters of complex flows in choosing appropriate turbulence prediction methods on a quantitative basis is developed. These parameters characterise flow/modelling matching conditions quantified in this work. Matching conditions are important in classifying complex turbulent flows in order to frame best practice for model predictions to inform computational aerodynamics design optimisation in the context of virtual test beds. In the incompressible low Reynolds number shear flows considered here, the boundaries of the 'conforming domain' within which turbulence models are valid need to be defined, based on basic mechanisms of turbulence, and the statistical parameters. This has led to a new guideline ‘localness map’ for standard model applications. Since the choice of turbulence model depends on the complexity of the flows considered, it is useful if systematic sets of the parameters indicate the type of flow. They are that of residence time, the degree of spatial non-locality, the straining, and the non-Gaussianity, each of which is appropriately normalised. It can be demonstrated that the quantified map, in particular that of localness for the shear flows, provides a firm foundation for evaluating a wider range of Underlying Flow Regimes, including locating the Underlying Flow Regimes on the generalised localness modeling map as a framework for best practice guidelines. This work produces 7 sets of quantitative localness-structural parameters, which are used as baseline sets for grouping the Underlying Flow Regimes, and hence it opens the possibility of having complete modelling maps for Application Challenges to assess the need for zonal modelling.

In a nuclear reactor, delayed neutrons play a critical role in sustaining a controllable chain reaction. Delayed neutron’s relative yields and decay constants are very important for modeling reactivity control and have been studied for decades. Researchers have tried different experimental and numerical methods to assess these delayed neutron parameters. The reported parameter values vary widely, much more than the small statistical errors reported with these parameters. Interestingly, the reported parameters fit their individual measurement data well in spite of these differences. This dissertation focuses on evaluation of the errors and methods of delayed neutron relative yields and decay constants for thermal fission of U-235. Various numerical methods used to extract the delayed neutron parameter from the measured data, including Matrix Inverse, Levenberg-Marquardt, and Quasi-Newton methods, were studied extensively using simulated delayed neutron data. This simulated data was Poisson distributed around Keepin’s theoretical data. The extraction methods produced totally different results for the same data set, and some of the above numerical methods could not even find solutions for some data sets. Further investigation found that ill-conditioned matrices in the objective function were the reason for the inconsistent results. To find a reasonable solution with small variation, a regularization parameter was introduced using a numerical method called Ridge Regression. The results from the Ridge Regression method, in terms of goodness of fit to the data, were good and often better than the other methods. Due to the introduction of a regularization number in the algorithm, the fitted result contains a small additional bias, but this method can guarantee convergence no matter how large the coefficient matrix condition number. Both saturation and pulse modes were simulated to focus on different groups. Some of the factors that affect the solution stability were investigated including initial count rate, sample flight time, initial guess values. Finally, because comparing reported delayed neutron parameters among different experiments is useless to determine if their data actually differs, methods are proposed that can be used to compare the delayed neutron data sets.

In recent years, the application of resampling methods to dependent data, such as time series or spatial data, has been a growing field in the study of statistics. In this dissertation, we discuss two such applications. In spatial statistics, the reliability of Kriging prediction methods relies on the observations coming from an underlying Gaussian process. When the observed data set is not from a multivariate Gaussian distribution, but rather is a transformation of Gaussian data, Kriging methods can produce biased predictions. Bootstrap resampling methods present a potential bias correction. We propose a parametric bootstrap methodology for the calculation of either a multiplicative or additive bias correction factor when dealing with Trans-Gaussian data. Furthermore, we investigate the asymptotic properties of the new bootstrap based predictors. Finally, we present the results for both simulated and real world data. In time series analysis, the estimation of covariance parameters is often of utmost importance. Furthermore, the understanding of the distributional behavior of parameter estimates, particularly the variance, is useful but often difficult. Block bootstrap methods have been particularly useful in such analyses. We introduce a new procedure for the estimation of covariance parameters for replicated time series data.

The micro PEMFCs were designed and fabricated in-house through a deep UV lithography technique and the SU-8 photoresist was used as microstructure material for fuel cell flow-field plates. The effect of different operating parameters on micro PEMFCs performances and electrochemical impedances was experimentally investigated for three different flow-field configurations (interdigitated, mesh, and serpentine). Experiments with different cell operating temperatures, different backpressures on the H2 flow channels as well as various combinations of these parameters have been conducted for three different flow geometries. Results are presented in the form of the polarization VI curves, PI curves and impedance spectroscopy under different operating conditions. The possible transport mechanisms associated with the parametric effects were discussed. With PI and VI curve were found that, among the three flow patterns considered, significant improvements can be reached with a specified flow geometry. With impedance spectroscopy was found that, the effect of the parameters on high frequency straight line, medium frequency, and low frequency arc. The influence in terms of impedance on dynamic response of the present H2/air micro fuel cell under different operating conditions and flow geometry can be quantitatively measured.

Sound propagation can be greatly affected by seabed, especially in shallow water, therefore by understanding the geoacoustic parameters of sea bottom can help to improve the performance of sonar systems. In this study, ship noise collected by the vertical line array (VLA) in South China Sea experiment of the Asian Seas International Acoustics Experiment (ASIAEX SCS) in 2001 was used as a sound source to invert the geoacoustic parameters. The nearest horizontal distance between VLA and the passing ship was estimated by beamforming the receiving sounds on the array, and this distance was used in the sound propagation modal. In the modal, two layers structure were assumed for the bottom, so the sound speed (C1) and density (£l1) of sediment layer, sound speed (C2 ) and density (£l2) of subbottom layer, and total absorption coefficient (£\) need to be inverted. Matched field processing is used to solve this inverse problem, and computing the minimum cost function between the measured and modeled sound field, the best matched bottom parameters are C1¡×1600 m/s¡BC2¡×1650 m/s¡B£l1=1.6 g/cm3¡B£l2=2.1 g/cm3¡B£\=0.6 dB/£f. These results were compared with chirp sonar survey in this area, and the agreement is satisfactory.

Wellbore stability problems make up huge over-costs worldwide. Since in recent years declining resource volumes and favorable oil prices are encouraging operators to drill deeper, more complex well trajectories drilling for hydrocarbons have turn into a much more challenging task. Furthermore, the complexity and variations of those wells have added the weight to planning and problem anticipation at both drilling and production stages. The thesis will describe the geomechanical wellbore stability analysis of Sayindere, Karabogaz and Karababa formations drilled in X field, Adiyaman. The analysis assumes validity of linear elastic theory for porous media and requires drilling reports, well logs, laboratory tests and core analysis. It was observed that with the assessment of geomechanical wellbore stability analysis mud weight window, which includes minimum mud weight and maximum mud weight can be determined for the studied formations.