646 research outputs found
On parameter identification problems for elliptic boundary value problems in divergence form, Part I: An abstract framework
No full textParameter identification problems for partial differential equations are an important subclass of inverse problems. The parameter-to-state map, which maps the parameter of interest to the respective solution of the PDE or state of the system, plays the central role in the (usually nonlinear) forward operator. Consequently, one is interested in well-definedness and further analytic properties such as continuity and differentiability of this operator w.r.t. the parameter in order to make sure that techniques from inverse problems theory may be successfully applied to solve the inverse problem. In this work, we present a general functional analytic framework suited for the study of a huge class of parameter identification problems including a variety of elliptic boundary value problems (in divergence form) with Dirichlet, Neumann, Robin or mixed boundary conditions. In particular, we show that the corresponding parameter-to-state operators fulfil, under suitable conditions, the tangential cone condition, which is often postulated for numerical solution techniques. This framework particularly covers the inverse medium problem and an inverse problem that arises in terahertz tomography
On parameter identification problems for elliptic boundary value problems in divergence form, Part I: An abstract framework
No full textParameter identification problems for partial differential equations are an important subclass of inverse problems. The parameter-to-state map, which maps the parameter of interest to the respective solution of the PDE or state of the system, plays the central role in the (usually nonlinear) forward operator. Consequently, one is interested in well-definedness and further analytic properties such as continuity and differentiability of this operator w.r.t. the parameter in order to make sure that techniques from inverse problems theory may be successfully applied to solve the inverse problem. In this work, we present a general functional analytic framework suited for the study of a huge class of parameter identification problems including a variety of elliptic boundary value problems (in divergence form) with Dirichlet, Neumann, Robin or mixed boundary conditions. In particular, we show that the corresponding parameter-to-state operators fulfil, under suitable conditions, the tangential cone condition, which is often postulated for numerical solution techniques. This framework particularly covers the inverse medium problem and an inverse problem that arises in terahertz tomography
Parameter identification for elliptic boundary value problems: an abstract framework and applications
No full textAbstractParameter identification problems for partial differential equations are an important subclass of inverse problems. The parameter-to-state map, which maps the parameter of interest to the respective solution of the PDE or state of the system, plays the central role in the (usually nonlinear) forward operator. Consequently, one is interested in well-definedness and further analytic properties such as continuity and differentiability of this operator w.r.t. the parameter in order to make sure that techniques from inverse problems theory may be successfully applied to solve the inverse problem. In this work, we present a general functional analytic framework suited for the study of a huge class of parameter identification problems including a variety of elliptic boundary value problems with Dirichlet, Neumann, Robin or mixed boundary conditions in Hilbert and Banach spaces and possibly complex-valued parameters. In particular, we show that the corresponding parameter-to-state operators fulfill, under suitable conditions, the tangential cone condition, which is often postulated for numerical solution techniques. This framework particularly covers the inverse medium problem and an inverse problem that arises in terahertz tomography
Kernel PCA for Novelty Detection
No full textHoffmann H. Kernel PCA for Novelty Detection. Pattern Recognition. 2007;40(3):863-874
Perception through visuomotor anticipation in a mobile robot
Full text linkHoffmann H. Perception through visuomotor anticipation in a mobile robot. Neural Networks. 2007;20(1):22-33
Biologically-inspired dynamical systems for movement generation: Automatic real-time goal adaptation and obstacle avoidance
No full textDynamical systems can generate movement trajectories that are robust against perturbations. This article presents an improved modification of the original dynamic movement primitive (DMP) framework by Ijspeert et al [1], [2]. The new equations can generalize movements to new targets without singularities and large accelerations. Furthermore, the new equations can represent a movement in 3D task space without depending on the choice of coordinate system (invariance under invertible affine transformations). Our modified DMP is motivated from biological data (spinal-cord stimulation in frogs) and human behavioral experiments. We further extend the formalism to obstacle avoidance by exploiting the robustness against perturbations: an additional term is added to the differential equations to make the robot steer around an obstacle. This additional term empirically describes human obstacle avoidance. We demonstrate the feasibility of our approach using the Sarcos Slave robot arm: after learning a single placing movement, the robot placed a cup between two arbitrarily given positions and avoided approaching obstacles
Movement reproduction and obstacle avoidance with dynamic movement primitives and potential fields
No full textRobots in a human environment need to be compliant. This compliance requires that a preplanned movement can be adapted to an obstacle that may be moving or appearing unexpectedly. Here, we present a general framework for movement generation and mid-flight adaptation to obstacles. For robust motion generation, Ijspeert et al developed the framework of dynamic movement primitives [1], [2], [3], [4], which represent a demonstrated movement with a set of differential equations. These equations allow adding a perturbing force without sacrificing stability of the desired movement. We extend this framework such that arbitrary movements in end-effector space can be represented - which was not possible before. Furthermore, we include obstacle avoidance by adding to the equations of motion a repellent force - a gradient of a potential field centered around the obstacle. In addition, this article compares different potential fields and shows how to avoid obstacle-link collisions within this framework. We demonstrate the abilities of our approach in simulations and with an anthropomorphic robot arm
The two putative comS homologs of the biotechnologically important Bacillus licheniformis do not contribute to competence development
No full textIn Bacillus subtilis, natural genetic competence is subject to complex genetic regulation and quorum sensing dependent. Upon extracellular accumulation of the peptide-pheromone ComX, the membrane-bound sensor histidine kinase ComP initiates diverse signaling pathways by activating-among others-DegQ and ComS. While DegQ favors the expression of extracellular enzymes rather than competence development, ComS is crucial for competence development as it prevents proteolytic degradation of ComK, the key transcriptional activator of all genes required for the uptake and integration of DNA. In Bacillus licheniformis, ComX/ComP sensed cell density negatively influences competence development, suggesting differences from the quorum-sensing-dependent control mechanism in Bacillus subtilis. Here, we show that each of six investigated strains possesses both of two different, recently identified putative comS genes. When expressed from an inducible promoter, none of the comS candidate genes displayed an impact on competence development neither in B. subtilis nor in B. licheniformis. Moreover, disruption of the genes did not reduce transformation efficiency. While the putative comS homologs do not contribute to competence development, we provide evidence that the degQ gene as for B. subtilis negatively influences genetic competency in B. licheniformis
Modelling Interregional Trade of Energy Crops in Eastern Germany
Full text linkRenewable resources gain in importance in our modern society. The line of reasoning is based on their positive effects on agriculture, the environment and the economy. To support renewable energy from biomass the EU promotes the cultivation of energy crops. A spatial equilibrium model is applied based on the concept of maximizing net welfare, to provide information whether energy crop production competes with food production for land area. The Model of Interregional Trade of Energy Crops (ITEC) refers to Eastern Germany and adjacent areas of Poland. First results show that the regions have enough feedstocks to meet the required demand for food and biofuel production. In many cases both food crops and biofuels are either traded on interregional basis or exported to "Rest of Europe" indicating that there is no competition between food and energy crops. Only green maize for biogas production strongly competes in areas where the crop is required as feed for cattle.Energy crops, spatial equilibrium analysis, interregional trade, International Relations/Trade,
In-situ study of emerging metallicity and memory effect on ion-beam bombarded strontium titanate surface:
No full textIn this work we present an investigation of the occurrence of conductivity on the surface of SrTiO3 due to argon ion bombardment. We created a model to describe this process and found that the temperature during the ion milling is a crucial factor for the conductivity. Depending on the temperatures we found surface carrier densities ranging from 1.5*10^18 to 2.6*10^20cm^-3 by just analyzing the conductivity behavior.
Clustering of vacancies goes along with temperature and affects the conductivity significantly. Furthermore we found that ion milling is a gentle way create vacancies because the clustering rate is small compared to annealing samples in high vacuum. The amount of clusters at room temperature was measured to be around 3-4 times higher than at -140C.
We found that samples with a conducting surface change their resistance over time at room temperature due to the ongoing process of oxygen vacancy clustering. This effect may be suppressed by decreasing the temperature.
The bistable switching behavior in oxygen deficient SrTiO3 is shown without any additional doping. The vacancy migration is the major mechanism behind this memory effect. Comparing this behavior with annealed samples in high vacuum shows that the therein present amount of vacancy clusters must be much larger and has a negative effect on the bistable switching behavior.M.S.Includes bibliographical references (p. 83-87)by Heiko Gros
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