A method of sensor location selection is introduced for distributed parameter systems. In this method, the sensitivities of spatial outputs to model parameters are computed by a model and transformed via continuous wavelet transforms into the time-scale domain to characterize the shape attributes of output sensitivities and accentuate their differences. Regions are then sought in the time-scale plane wherein the wavelet coefficient of an output-sensitivity surpasses all the others’ as indication of the output sensitivity’s uniqueness. This method yields a comprehensive account of identifiability each output provides for the model parameters as the basis of output selection. This output selection strategy is evaluated for a numerical case of pollutant dispersion by advection and discussion in a two-dimensional area.

Today increasing amounts of data are available for analysis purposes and often times for resource allocation. One method for analysis is linear regression which utilizes the least squares estimation technique to estimate a model's parameters. This research investigated, from a user's perspective, the ability of linear regression to estimate the parameters' confidence intervals at the usual 95% level for medium sized data sets. A controlled environment using simulation with known data characteristics (clean data, bias and or multicollinearity present) was used to show underlying problems exist with confidence intervals not including the true parameter (even though the variable was selected). The Elder/Pregibon rule was used for variable selection. A comparison of the bootstrap Percentile and BCa confidence interval was made as well as an investigation of adjustments to the usual 95% confidence intervals based on the Bonferroni and Scheffe multiple comparison principles. The results show that linear regression has problems in capturing the true parameters in the confidence intervals for the sample sizes considered, the bootstrap intervals perform no better than linear regression, and the Scheffe method is too wide for any application considered. The Bonferroni adjustment is recommended for larger sample sizes and when the t-value for a selected variable is about 3.35 or higher. For smaller sample sizes all methods show problems with type II errors resulting from confidence intervals being too wide.

Cardiolex Medical AB är ett medicintekniskt företag som säljer ett komplett EKG-hanterings system med tillhörande vakuumsystem. Produkten EC View med lagring i EC Store är idag de produkter som Cardiolex säljer till sina kunder för att kunna lagra och hantera EKG-undersökningar på sjukhus och vårdcentraler. Cardiolex önskade utöka EC View med fler sökfunktioner för användning i forskningssyfte. Parametermaterial har länge funnits, men hanteringen har varit manuell, vilket varit tidsineffektivt. Intresset av att kunna sortera ut specifika EKG-undersökningar efter enskilda mätvärden är stort och därmed är en utökad sökfunktion viktig att ha med i ny mjukvara. För att få en djupare inblick i vilka av de vanligaste mätvärdena är, studerades artiklar för att kunna fastställa att den sökfunktion som implementerades var ett användbart tillägg i befintlig produkt. Det mätvärde som ansågs mest attraktivt att skapa en sökfunktion för var ST-amplituden. Funktionen som plockar ut detta värde ur ett lagrat EKG är skapad i Visual Studio, med programspråket T-SQL, där funktionen anropas i en SQL-vy som sammanställer all information för användaren. Fördelen med att använda sig av en SQL-vy presentation är också att information kan sammanställas undertiden en sökning genomförs. / Cardiolex Medical AB has an ambition that ECG should be easy to use, they sell ECG systems compatible with all types of electrodes and has special knowledge in ECG modulation. Today Cardiolex has three products to manage ECG examinations and patient information with EC view and EC Store. Their ECG system is operating with EC Sense and together with EC View and EC Store, Cardiolex offer a complete solution available to use with many softwares and systems at the market. With EC Store, examinations can be saved and found in the database and EC View is a client for reviewing and making medical assessments. Moreover, Cardiolex has a vision to offer a wider functionality for researchers, who research in ECG. Therefore, an extended search tool was important for future functionality in the products. To get a better insight in which of the ECG measurements was of interest to implement in a search function, a literature study of today’s recherche is summarised in this project. The ST-value was considered one of the most common parameters, therefore this parameter was decided to be implemented in the search function. The function which return a ST-amplitude value stored in the examination, was created in Visual Studios, with the language SQL. The data from the function became represented of a SQL-view which can sort data during a searching process in the database.

In this work we develop and analyze algorithms motivated by the parameter estimation problem corresponding to a multilayer aquifer/interbed groundwater flow model. The parameter estimation problem is formulated as an optimization problem, then addressed with algorithms based on adjoint equations, quasi-Newton schemes, and multilevel optimization. In addition to the parameter estimation problem, we consider properties of the parameter to solution map. This includes invertibility (known as identifiability) and differentiability properties of the map. For differentiability, we expand existing results on Fréchet sensitivity analysis to convection diffusion equations and groundwater flow equations. This is achieved by proving that the Fréchet  derivative of the solution operator is Hilbert-Schmidt, under smoothness assumptions for the parameter space. In addition, we approximate this operator by time dependent matrices, where their singular values and singular vectors converge to their infinite dimension peers. This decomposition proves to be very useful as it provides vital information as to which perturbations in the distributed parameters lead to the most significant changes in the solutions, as well as applications to uncertainty quantification. Numerical results complement our theoretical findings. / Ph. D.

Optimization is omnipresent in our world. Its numerous applications spread from industrial cases, such as logistics, construction management or production planning; to the private sphere, filled with problems of selecting daycare or vacation planning. In this thesis, we concentrate on expensive black-box optimization (EBBO) problems, a subset of optimization problems (OPs), which are characterized by an expensive cost of evaluating an objective function. Such OPs are reoccurring in various domains, being known as: hyperpameter optimization in machine learning, performance configuration optimization or parameter tuning in search-based software engineering, simulation optimization in operations research, meta-optimization or parameter tuning in the optimization domain itself. High diversity of domains introduces a plethora of solving approaches, which adhere to a similar structure and workflow, but differ in details. The software frameworks stemming from different areas possess only partially intersecting manageability points, i.e., lack manageability. In this thesis, we argue that the lack of manageability in EBBO is a major problem, which leads to underachieving optimization quality. The goal of this thesis is to study the role of manageability in EBBO and to investigate whether improving the manageability of EBBO frameworks increases optimization quality. To reach this goal, we appeal to software product line engineering (SPLE), a methodology for developing highly-manageable software systems. Based on the foundations of SPLE, we introduce a novel framework for EBBO called BRISE. It offers: 1) a loosely-coupled software architecture, separating concerns of the experiment designer and the developer of EBBO strategies; 2) a full coverage of all EBBO problem types; and 3) a context-aware variability model, which captures the experiment-designer-defined OP with the content model; and manageability points including their variants and constraints with the cardinality-based feature model. High manageability of the introduced BRISE framework enables us: 1) to extend the framework with novel efficient strategies, such as adaptive repetition management; and 2) to introduce novel EBBO mechanisms, such as multi-objective compositional surrogate modeling, dynamic sampling and hierarchical surrogate modeling. The evaluation of the novel approaches with a set of case studies, including: the WFG benchmark for multi-objective optimization, combined selection and parameter control of meta-heuristics, and energy optimization; demonstrated their superiority over the state-of-the-art competitors. Thus, it supports the research hypothesis of this thesis: Improving manageability of an EBBO framework enables to increase optimization quality.

Master of Science / Department of Statistics / James Neill / In financial mathematics, asset prices for European options are often modeled according to the Black-Scholes-Merton (BSM) model, a stochastic differential equation (SDE) depending on unknown parameters. A derivation of the solution to this SDE is reviewed, resulting in a stochastic process called geometric Brownian motion (GBM) which depends on two unknown real parameters referred to as the drift and volatility. For additional insight, the BSM equation is expressed as a heat equation, which is a partial differential equation (PDE) with well-known properties. For American options, it is established that asset value can be characterized as the solution to an obstacle problem, which is an example of a free boundary PDE problem. One approach for estimating the parameters in the GBM solution to the BSM model can be based on the method of maximum likelihood. This approach is discussed and applied to a dataset involving the weekly closing prices for the Dow Jones Industrial Average between January 2012 and December 2012.

Wafer handling robotics are critical in semiconductor manufacturing to enable tight control of temperature, humidity, and particle contamination during processing. Closed-loop dynamic modeling during the robot design process ensures designs meet throughput and stability specifications prior to prototype hardware purchase. Dynamic models are also used in model-based control to improve performance. This thesis describes the generation and mathematical verification of a dynamic model for a three degrees-of-freedom wafer handling mechanism with one linear and two rotary axes. The dynamic plant model is integrated with motion and motor controller models, and the closed-loop performance is compared with experimental data. Models with rigid and flexible connections are compared, and the flexible connection models are shown to overall agree better with a measured step response. The simulation time increase from the addition of flexible connections can be minimized by modeling only the component stiffnesses that impact the closed-loop mechanism response. A method for selecting which elements to include based on controller bandwidth is presented and shown to significantly improve simulation times with minimal impact on model predictive performance.

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / The number of aircraft parameters used in flight-testing has constantly increased over the years and there is no sign that situation will change in the near future. On the contrary, in modern, software-driven, digital avionic systems, all sorts of parameters circulate through digital buses and can be transferred to on-board data acquisition systems more easily than those converted from traditional analog transducers, facilitating the request for more and more parameters to be acquired, processed, visualized, stored and retrieved at any given time. The constant unbalance between what parameter quantity engineers believe to be “sufficient” for developing and troubleshooting systems in a new aircraft, which tends to grow with aircraft complexity, and the associated cost of instrumenting a test prototype accordingly, which tends to grow beyond budget limits, pushes for new creative ways of handling both tendencies without compromising the ease of performing an engineering analysis directly from flight test data. This paper presents an alternative for handling large collections of flight test parameters through a relational approach, particularly in two important scenarios: the very basic creation and administration of the traditional “Flight Test Parameter List” and the transmission of selected data over a telemetry link for visualization in a Ground Station.

Mobile wireless positioning has recently received great attention. For mobile wireless communication networks, an inherently suitable approach is to obtain the parameters that are used for positioning estimates from the radio signal measurements between a mobile device and one or more xed base stations. However, obtaining accurate estimates of these location-dependent channel parameters is a challenging task. The focus of this thesis is on the estimation of these channel parameters for mobile wireless positioning applications. In particular, we investigate novel estimators that jointly estimate more than one type of channel parameters. We rst perform a comprehensive critical review on the most recent and popular joint channel parameter estimation techniques. Secondly, we improve a state-of-the-art technique, namely the Space Alternating Generalised Expectation maximisation (SAGE) algorithm by employing adaptive interference cancellation to improve the estimation accuracy of weaker paths. Thirdly, a novel intelligent channel parameter estimation technique using Evolution Strategy (ES) is proposed to overcome the drawbacks of the existing iterative maximum likelihood methods. Furthermore, given that in reality it is di cult to obtain the number of multipath in advance, we propose a two tier Hierarchically Organised ES to jointly estimate the number of multipath as well as the channel parameters. Finally, we extend the proposed ES method to further estimate the Doppler shift in mobile environments. Our proposed intelligent joint channel estimation techniques are shown to exhibit excellent performance even with low Signal to Noise Ratio (SNR) channel conditions as well as robust against uncertainties in initialisations.

International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / This paper takes one through the processes followed by a designer when responding to a specification for an earth terminal. The orbital parameters of Low-Earth Orbiting and Medium-Earth Orbiting (LEO and MEO) satellites that affect autotracking and pointing of an antenna are presented. The do’s and don’ts of specifying (or over specifying) the antenna feed and pedestal size are discussed. The axis velocity and acceleration rates required of a Y over X and El over AZ type pedestal are developed as a function of satellite altitude, radio frequency of operation, and ground antenna terminal diameter. Decision criteria are presented leading to requiring a tilt mechanism or a third axis to cover direct and near overhead passes using an El over Az pedestal. Finally, the expressions transforming Y over X configuration position angles to azimuth and elevation axis position angles are presented.