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This dissertation investigates the possibility of justifying simplicity principles in science. The labor of these projects is organized into three chapters. The first chapter introduces some of the key authors and issues in the history of simplicity in science. This chapter also gives a detailed discussion of the work of the 19th century physicists Le Verrier and Newcomb who played a crucial role in setting the stage for Einstein's theory of relativity. These examples are used to illustrate points in the following chapters. However, they play a specific role in the first chapter to show serious problems with a view defended by an important contemporary author, Richard Swinburne, that one version of the principle of parsimony contributes to the probability that scientific theories will be true. The second chapter elucidates the problems involved in specifying and measuring the simplicity of scientific hypotheses and theories. When simplicity criteria are employed in a scientific methodology, we find that simplicity judgments of one kind are always traded-off with simplicity judgments of another kind. We also find that the scientific project involves a delicate balancing of several aims. This analysis renders a valuable result: that some dogmas, in particular, the dogma that principles of parsimony are the final court of appeal in scientific theory selection must be jettisoned. I also find that it is misguided to ask the question of whether or not simplicity of some clearly specified kind is related to the truth. In point of fact, the legitimate questions about the justification of specific simplicity judgments in science are much more complex and nuanced than this. This becomes clear when it is seen exactly how different simplicity criteria are related to one another and to the various desiderata of science. The third chapter investigates which argument forms may be available to justify simplicity principles in science. In some cases it is nonsense to ask the question of how simplicity is related to the truth. However, we can investigate the forms of various arguments that may be given to justify methodological principles involving simplicity criteria. The results from the second chapter are employed in two ways. First, methodological principles stand in a tight-knit set of interrelations, so our analysis of justificatory argument forms must incorporate the complexity of these relations. Second, simplicity is extremely heterogeneous and since no conceptual reduction of all of the various simplicity criteria is possible, justificatory arguments must deal with clusters of interrelated principles. This result may have certain advantages and other disadvantages for inductive, transcendental, or inference to the best explanation approaches to the justification of simplicity. My analysis shows what will and what will not work for these possible approaches to the question of justification and shows what some of the systematic and metaphilosophical commitments would have to be were philosophers to pursue this project.

Thesis (Ph. D.)--University of Washington, 1996. / Vita. Includes bibliographical references (leaves [294]-305).

In the first chapter of this paper I focus on the general overview of Occam's Razor, and develop several interpretations and adaptations of Occam's Razor as a principle of simplicity. In the second chapter I apply these different interpretations in the Physicalism/Dualism debate, and critically assess the validity of these implementations of Occam's Razor in philosophy of mind. In the final chapter I give an overview of my discussion thus far, and make assertions about what my paper means for the usage of Occam's Razor's as a whole.

This thesis deals with usage of MVC (Model View Controller) technology in web development on ASP.NET platform from Microsoft. Mainly it deals with latest version of framework ASP.NET MVC 3. First part describes MVC architecture and the second describes usage of MVC in certain parts of web application an comparing with PHP.

Thesis (M.Sc.)--Memorial University of Newfoundland, 1999. / Restricted until November 2000. Includes bibliographical references.

Idag utförs arbete ofta på resande fot och då används smarta telefoner och surfplat- tor istället för datorer. Dessa skärmar är oftast mindre än vad en datorskärm är. Där- för efterfrågas en mer dynamisk design av webbsidor som anpassar sig till storleken på skärmen. Webbsidans statiska design var 1000 pixlar bred och innehöll många tabeller vilket skulle få plats i den dynamiska designen med en minsta bredd på 320 pixlar. En del viktig information behövde även lyftas fram och göras tydligare. Det implementerades en ny CSS-mall samt flera nya JavaScript. En del HTML justerades för att passa den nya CSS-mallen. Eftersom en del viktig information behövdes pre- senteras tydligare skapades en helt ny flik. Innehållet blev driftinformation relaterat till den inloggade kunden. Efter simuleringarna i Chrome verifierades responsivite- ten av sidorna på alla skärmstorlekar. Implementeringen av AJAX gjorde att de lång- samma sidorna svarade direkt, men förbättrade inte den totala laddtiden. För att förbättra den skulle en back-end optimering behöva utföras. Projektets webbsida fu- gerade enligt önskemål. / In today ́s society people are working more and more while travelling, which makes them use smartphones and tablets instead of laptops. These screens are usually smaller than a laptop screen. That is why a more dynamic web design has been re- quested in order to fit the screen on the device being used. The static webpage’s width was 1000 pixels and the goal was to fit all the tables and information in the respon- sive version with a width of 320 pixels. Important information also had to be moved to a different page in order to make it more visible. A new CSS-template was imple- mented and several new Java Scripts followed by finer adjustments to the HTML code. Since some information had to be more visible to the user, a new tab was cre- ated in order to fulfill this demand. The new tab contained information about “Net- work Status” only related to the signed in user. After simulating the webpage in Chrome the responsiveness of the page was confirmed on all screen sizes. Sending the webpage asynchronously made the slow pages respond instantly but the total loading time was still slow. To fix this, back-end programming would have been re- quired. The project’s webpage fulfilled all the requirements.

This thesis presents a framework for understanding first-order theories by investigating their models. A common application is to help users, who are not necessarily experts in formal methods, analyze software artifacts, such as access-control policies, system configurations, protocol specifications, and software designs. The framework suggests a strategy for exploring the space of finite models of a theory via augmentation. Also, it introduces a notion of provenance information for understanding the elements and facts in models with respect to the statements of the theory. The primary mathematical tool is an information-preserving preorder, induced by the homomorphism on models, defining paths along which models are explored. The central algorithmic ideas consists of a controlled construction of the Herbrand base of the input theory followed by utilizing SMT-solving for generating models that are minimal under the homomorphism preorder. Our framework for model-exploration is realized in Razor, a model-finding assistant that provides the user with a read-eval-print loop for investigating models.

In this dissertation, we explore and illustrate the concept of ranked sparsity, a phenomenon that often occurs naturally in the presence of derived variables. Ranked sparsity arises in modeling applications when an expected disparity exists in the quality of information between different feature sets. Its presence can cause traditional model selection methods to fail because statisticians commonly presume that each potential parameter is equally worthy of entering into the final model - we call this principle "covariate equipoise". However, this presumption does not always hold, especially in the presence of derived variables. For instance, when all possible interactions are considered as candidate predictors, the presumption of covariate equipoise will often produce misclassified and opaque models. The sheer number of additional candidate variables grossly inflates the number of false discoveries in the interactions, resulting in unnecessarily complex and difficult-to-interpret models with many (truly spurious) interactions. We suggest a modeling strategy that requires a stronger level of evidence in order to allow certain variables (e.g. interactions) to be selected in the final model. This ranked sparsity paradigm can be implemented either with a modified Bayesian information criterion (RBIC) or with the sparsity-ranked lasso (SRL). In chapter 1, we provide a philosophical motivation for ranked sparsity by describing situations where traditional model selection methods fail. Chapter 1 also presents some of the relevant literature, and motivates why ranked sparsity methods are necessary in the context of interactions. Finally, we introduce RBIC and SRL as possible recourses. In chapter 2, we explore the performance of SRL relative to competing methods for selecting polynomials and interactions in a series of simulations. We show that the SRL is a very attractive method because it is fast, accurate, and does not tend to inflate the number of Type I errors in the interactions. We illustrate its utility in an application to predict the survival of lung cancer patients using a set of gene expression measurements and clinical covariates, searching in particular for gene-environment interactions, which are very difficult to find in practice. In chapter 3, we present three extensions of the SRL in very different contexts. First, we show how the method can be used to optimize for cost and prediction accuracy simulataneously when covariates have differing collection costs. In this setting, the SRL produces what we call "minimally invasive" models, i.e. models that can easily (and cheaply) be applied to new data. Second, we investigate the use of the SRL in the context of time series regression, where we evaluate our method against several other state-of-the-art techniques in predicting the hourly number of arrivals at the Emergency Department of the University of Iowa Hospitals and Clinics. Finally, we show how the SRL can be utilized to balance model stability and model adaptivity in an application which uses a rich new source of smartphone thermometer data to predict flu incidence in real time.

Thesis (Ph.D.)--Memorial University of Newfoundland, 2000. / Includes bibliographical references.