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Includes bibliographical references (leaves 193-[201]).
GDA is a software belonging to the Gabriel package and is devoted to data analysis. Year after year some new features have been introduced and the latest introductions are more dedicated to food. GDA is built around modules and we describe here the most widely used in food chemistry. GDA can be obtained free of charge.
The Marine Environmental Ordinance (SFS 2010:1341) is part of a strategy to bring about ecosystem-based management and sustainable use of the marine environment in accordance with the EU’s the Marine Strategy Framework Directive (MSFD, 2008/56/EC). The ordinance is intended to maintain or achieve good environmental status in the marine environment. Under the Marine Environmental Ordinance, the Swedish Agency for Marine and Water Management (SwAM) must ensure that an initial assessment is carried out on the marine environment in the Swedish waters of the two regions, the North Sea and the Baltic Sea (Articles 13–16). The initial assessment, which is to be completed by 15 July 2012 and reported to the European Commission not later than 15 October of the same year, is to provide a basis for the establishment of good environmental status, ...
Many challenges in software quality can be tackled with dynamic analysis. However, these techniques are often limited in their efficiency or scalability as they are often applied uniformly to an entire program. In this thesis, we show that dynamic program analysis can be made significantly more efficient and scalable by first performing a static data flow analysis so that the dynamic analysis can be selectively applied only to important parts of the program. We apply this general principle to the design and implementation of two different systems, one for runtime security policy enforcement and the other for software test input generation. For runtime security policy enforcement, we enforce user-defined policies using a dynamic data flow analysis that is more general and flexible than previous systems. Our system uses the user-define...
We consider pseudodifferential operators on functions on $\R^{n+1}$ which commute with the Euler operator, and can thus be restricted to spaces of functions homogeneous of some given degree. Their symbols can be regarded as functions on a reduced phase space, isomorphic to the homogeneous space $G_n/H_n=SL(n+1,\R)/GL(n,\R)$, and the resulting calculus is a pseudodifferential analysis of operators acting on spaces of appropriate sections of line bundles over the projective space $P_n(\R)$ : these spaces are the representation spaces of the maximal degenerate series $(\pi_{i\lambda,\epsilon})$ of $G_n$ . This new approach to the quantization of $G_n/H_n$, already considered by other authors, has several advantages: as an example, it makes it possible to give a very explicit version of the continuous part from the decomposition of $L^2(...
Analysis I covers fundamentals of mathematical analysis: convergence of sequences and series, continuity, differentiability, Riemann integral, sequences and series of functions, uniformity, and interchange of limit operations.
Analysis I (18.100) in its various versions covers fundamentals of mathematical analysis: continuity, differentiability, some form of the Riemann integral, sequences and series of numbers and functions, uniform convergence with applications to interchange of limit operations, some point-set topology, including some work in Euclidean n-space. MIT students may choose to take one of three versions of 18.100: Option A (18.100A) chooses less abstract definitions and proofs, and gives applications where possible. Option B (18.100B) is more demanding and for students with more mathematical maturity; it places more emphasis from the beginning on point-set topology and n-space, whereas Option A is concerned primarily with analysis on the real line, saving for the last weeks work in 2-space (the plane) and its point-set topology. Option C (18.10...
Continues 18.100, in the direction of manifolds and global analysis. Differentiable maps, inverse and implicit function theorems, n-dimensional Riemann integral, change of variables in multiple integrals, manifolds, differential forms, n-dimensional version of Stokes' theorem. 18.901 helpful but not required.
Within this thesis, we focus on the relation between independent component analysis (ICA) and slow feature analysis (SFA). To allow a comparison between both methods we introduce CuBICA2, an ICA algorithm based on second-order statistics only, i.e.\ cross-correlations. In contrast to algorithms based on higher-order statistics not only instantaneous cross-correlations but also time-delayed cross correlations are considered for minimization. CuBICA2 requires signal components with auto-correlation like in SFA, and has the ability to separate source signal components that have a Gaussian distribution. Furthermore, we derive an alternative formulation of the SFA objective function and compare it with that of CuBICA2. In the case of a linear mixture the two methods are equivalent if a single time delay is taken i...
This course is meant as a first introduction to rigorous mathematics; understanding and writing of proofs will be emphasized. We will cover basic notions in real analysis: point-set topology, metric spaces, sequences and series, continuity, differentiability, and integration.
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