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Abstract in UndeterminedWe develop a discretization and computational procedures for approximation of the action of Fourier integral operators the canonical relations of which are graphs. Such operators appear, for instance, in the formulation of imaging and inverse scattering of seismic reflection data. Our discretization and algorithms are based on a multiscale low-rank expansion of the action o

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In synthetic aperture radar one wishes to reconstruct the reflectivity function of a region on the ground from a set of radar measurements taken at several angles. The ground reflectivity is found by interpolating measured samples, which typically lie on a polar grid in frequency space, to an equally spaced rectangular grid in frequency space, then computing an inverse Fourier transform. The class

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We present a non-incremental approach to structure from motion. Our solution is based on robustly computing global rotations from relative geometries and feeding these into the known-rotation framework to create an initial solution for bundle adjustment. To increase robustness we present a new method for constructing reliable point tracks from pairwise matches. We show that our method can be seen

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In this paper, we study the time-of-arrival (TOA) based self-calibration problem of dual-microphone array for known and unknown rack distance, and also for different combinations of dimension for the affine spaces spanned by the receivers and by the senders. Particularly, we analyze the minimum cases and present minimum solvers for the case of microphones and speakers in 3-D/3-D, in 2-D/3-D, and i

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A procedure for acceleration feedback control of the delayed nonlinear teleoperation system is proposed. The acceleration feedback is applied to the master controller, while in the slave side the position error plus nonlinear damping controller is used to guarantee the input-to-state stability (ISS) of the controlled system. The Lyapunov-Krasovskii methodology is applied to analyse the ISS of the

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The roof dual bound for quadratic unconstrained binary optimization is the basis for several methods for efficiently computing the solution to many hard combinatorial problems. It works by constructing the tightest possible lower-bounding submodular function, and instead of minimizing the original objective function, the relaxation is minimized. However, for higher-order problems the technique has

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Short-term very intensive storms in the years 1980-2007 from rain gauges in Malmo have been analysed to find intensities of long return periods and to investigate trends. Observations from different stations have been pooled into series to which probability functions have been adjusted. Quality control of short-term precipitation records is emphasized. In order to investigate whether high rain int

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Many problems in computer vision can be turned into a large-scale boolean optimization problem, which is in general NP-hard. In this paper, we further develop one of the most successful approaches, namely roof duality, for approximately solving such problems for higher-order models. Two new methods that can be applied independently or in combination are investigated. The first one is based on cons

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Abstract in UndeterminedIn this paper theoretical results regarding a generalized minimum rank matrix approximation problem in the spectral norm are presented. An alternative solution expression for the generalized matrix approximation problem is obtained. This alternative expression provides a simple characterization of the achievableminimum rank, which is shown to be the same as the optimal obje

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A distributed model predictive control (DMPC) approach based on distributed optimization is applied to the power reference tracking problem of a hydro power valley (HPV) system. The applied optimization algorithm is based on accelerated gradient methods and achieves a convergence rate of O(1/k^2), where k is the iteration number. Major challenges in the control of the HPV include a nonlinear and l

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Immunohistochemical (IHC) staining for the identification of nodal occult metastases (OM), not detected by routine histological examination, has been proposed for improved staging, prognostication and decision of adjuvant treatment in surgically treated primary lung cancer. In a prospective study, we analysed 178 cases of primary lung cancer stage I-III (N0-N1) for OM by immunostaining lymph node

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Power system voltage security assessment is generally applied by considering the power system loadability surface. For a large power system, the loadability surface is a complicated hyper-surface in parameter space, and local approximations are a necessity for any analysis. Unfortunately, inequality constraints due to for example generator overexitation limiters, and higher codimension bifurcation

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Lately, much work in the area of voltage stability assessment has been focused on finding post-contingency corrective controls. In this article a contribution to this area will be presented where we search for maximal loadability while considering post-contingency corrective controls. This objective is different from the usual approach to the problem, where the aim is to include the post-contingen

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We present exploratory data analysis methods to assess inversion estimates using examples based on l(2)- and l(1)-regularization. These methods can be used to reveal the presence of systematic errors such as bias and discretization effects, or to validate assumptions made on the statistical model used in the analysis. The methods include bounds on the performance of randomized estimators of a larg

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We consider the least-squares (L2) minimization problems in multiple view geometry for triangulation, homography, camera resectioning and structure-and-motion with known rotatation, or known plane. Although optimal algorithms have been given for these problems under an Linfinity cost function, finding optimal least-squares solutions to these problems is difficult, since the cost functions are not

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We construct a variational formulation for the problem of interpolating seismic data in the case of missing traces. We assume that we have derivative information available at the traces. The variational problem is essentially the minimization of the integral over the smallest eigenvalue of the structure tensor associated with the interpolated data. This has the physical meaning of penalizing the l

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A one-year study was performed at the Vavihill background station in southern Sweden to estimate the anthropogenic contribution to the carbonaceous aerosol. Weekly samples of the particulate matter PM10 were collected on quartz filters, and the amounts of organic carbon, elemental carbon, radiocarbon (C-14) and levoglucosan were measured. This approach enabled source apportionment of the total car

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Resource allocation in clouds is mostly done assuming hard requirements, applications either receive the requested resources or fail. Given the dynamic nature of workloads, guaranteeing on-demand allocations requires large spare capacity. Hence, one cannot have a system that is both reliable and efficient. To solve this issue, we introduce Service Level (SL) awareness in clouds, assuming applicati

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Industrial robots are traditionally programmed using only the internal joint position sensors, in a sense leaving the robot blind and numb. Using external sensors, such as cameras and force sensors, allows the robot to detect the existence and position of objects in an unstructured environment, and to handle contact situations not possible using only position control. This thesis presents work on