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We consider flow-inducing networks, a class of models that are well-suited to describe important biochemical systems, including the MAPK pathway and the interactions at the trans-Golgi network. A flow-inducing network is given by the interconnection of subsystems (modules), each associated with a stochastic state matrix whose entries depend on the state variables of other modules. This results in
In modern day industry, robots are indispensable for achieving high production rates and competitiveness. In small and medium scale enterprises, where the production may shift rapidly, it is vital to be able to reprogram robots quickly. Kinesthetic teaching, also known as lead-through programming (LTP), provides a fast approach for teaching a trajectory. In this approach, a trajectory is demonstra
We present a data-driven interpolation method, based on extended structure tensors. The method uses directional information, extracted from the crossline derivative of the pressure field, to interpolate both pressure field and its normal (depth) derivative. Here we focus on the interpolation of the normal derivative.
We present a data-driven method, based on extended structure tensors, that interpolates multicomponent, marine seismic data. The method is designed to interpolate pressure measurements and their normal derivatives using directional information from the crossline derivative of the pressure field.
In this paper we propose an autotuning method that combines a setup for decentralized relay autotuning of two-input two-output systems with an identification method that uses short experiments to estimate up to second-ordertime-delayed systems. A small modification of the experiment gives better low-frequency excitation and improved models. The method is successfully demonstrated in simulations an
Marine seismic data are distorted by ghosts as waves propagating upwards reflect downwards from the sea surface. Ghosts appear both on the source-side as well as on the receiver-side. However, whereas the receiver-side ghost problem has been studied in detail and many different solutions have been proposed and implemented commercially, the source-side ghost problem has remained largely "unsolved"
In wavefield signal apparition, acquisition with periodic variations in source activation parameters shifts all or part of a signal cone out to, e.g., the Nyquist wavenumber, enabling perfect separation of simultaneous-source (sim-source) data below a certain temporal frequency. Cyclic convolution in the spatial frequency domain is used to generalise the signal apparition concept to the case of ap
Despite of having no explicit shape model, multi-atlas approaches to image segmentation have proved to be a top-performer for several diverse datasets and imaging modalities. In this paper, we show how one can directly incorporate shape regularization into the multi-atlas framework. Unlike traditional methods, our proposed approach does not rely on label fusion on the voxel level. Instead, each re
We consider the potential for positioning with a system where antenna arrays are deployed as a large intelligent surface (LIS). We derive Fisher-informations and Cram\'{e}r-Rao lower bounds (CRLB) in closed-form for terminals along the central perpendicular line (CPL) of the LIS for all three Cartesian dimensions. For terminals at positions other than the CPL, closed-form expressions for the Fishe
The relay autotuner for PID control is based on the simple idea of investigating process dynamics by the oscillation obtained when the PID controller is replaced by a relay unction. In this paper an asymmetric relay function is used, which provides an equation for the static gain of the process. A method to find the normalized time delay is proposed and the benefits of this is discussed. Ways to f
Modern software applications are subject to uncertain operating conditions, such as dynamics in the availability of services and variations of system goals. Consequently, runtime changes cannot be ignored, but often cannot be predicted at design time. Control theory has been identified as a principled way of addressing runtime changes and it has been applied successfully to modify the structure an
In this paper, a compact pattern reconfigurable dual-antenna array is designed at 2.65 GHz for MIMO terminal applications, such as laptops. Each antenna is composed of two layers, i.e., the monopole layer and the PIFA layer. By switching the PIN diodes on each layer, its radiation patterns can be varied between conical and boresight patterns. Two such identical antennas are placed side by side on
A measurement of the ZZ production cross section in the ℓ−ℓ+ℓ′ −ℓ′ + and ℓ−ℓ+νν¯ channels (ℓ = e, μ) in proton-proton collisions at s=8TeV at the Large Hadron Collider at CERN, using data corresponding to an integrated luminosity of 20.3 fb−1 collected by the ATLAS experiment in 2012 is presented. The fiducial cross sections for ZZ → ℓ−ℓ+ℓ′ −ℓ′ + and ZZ→ ℓ−ℓ+νν¯ are measured in selected phase-spac
Particle methods such as the particle filter and particle smoothers have proven very useful for solving challenging nonlinear estimation problems in a wide variety of fields during the last decade. However, there are still very few existing tools available to support and assist researchers and engineers in applying the vast number of methods in this field to their own problems. This paper identifi
During the last few years most work done on the task of image segmentation has been focused on deep learning and Convolutional Neural Networks (CNNs) in particular. CNNs are powerful for modeling complex connections between input and output data but lack the ability to directly model dependent output structures, for instance, enforcing properties such as smoothness and coherence. This drawback mot
A fully automatic system for abdominal organ segmentation is presented. As a first step, an organ localization is obtained via a robust and efficient feature registration method where the center of the organ is estimated together with a region of interest surrounding the center. Then, a convolutional neural network performing voxelwise classification is applied. The convolutional neural network co
In conventional seismic surveys, there is a waiting time between sequentially fired shots. This time is determined such that the deepest reflection of interest is recorded before the following source is fired. In a survey with simultaneous or blended sources, the waiting time between the firing of shots is not dependent on the deepest reflection of interest, it is usually much shorter and/or can h
An algorithm for high-performance path tracking for robot manipulators in the presence of model uncertainties and actuator constraints is presented. The path to be tracked is assumed given, and the nominal trajectories are computed using, for example, well-known algorithms for time-optimal path tracking. For online path tracking, the nominal, feedforward trajectories are combined with feedback in
Operating systems code is often developed according to principles like simplicity, low overhead, and low memory footprint. Schedulers are no exceptions. A scheduler is usually developed with flexibility in mind, and this restricts the ability to provide real-time guarantees. Moreover, even when schedulers can provide real-time guarantees, it is unlikely that these guarantees are properly quantifie
