Controlled nanochannel lattice formation utilizing prepatterned substrates

Solid substrates can be endued with self-organized regular stripe patterns of nanoscopic lengthscale by Langmuir-Blodgett transfer of organic monolayers. Here we consider the effect of periodically prepatterned substrates on this process of pattern formation. It leads to a time periodic forcing of the oscillatory behavior at the meniscus. Utilizing higher order synchronization with this forcing, complex periodic patterns of predefined wavelength can be created. The dependence of the synchronization on the amplitude and the wavelength of the wetting contrast is investigated in one and two spatial dimensions and the resulting patterns are discussed. Furthermore, the effect of prepatterned substrates on the pattern selection process is investigated

Individual Human Behavior Identification Using an Inverse Reinforcement Learning Method

Shared control techniques have a great potential to create synergies in human-machine interaction for efficient and safe applications. However, an optimal interaction requires the machine to consider the individual behavior of the human partner. A widespread approach for modeling human behavior is given by optimal control theory, where the movement trajectories of a human arise from an optimized cost function. The aim of the identification is thus to determine parameters of a cost function which explains observed human motion. The central thesis of this paper is that individual cost function parameters which describe specific behavior can be determined by means of Inverse Reinforcement Learning. We show the applicability of the approach with a tracking control task example. The experiment consists in following a reference trajectory by means of a steering wheel. The study confirms that optimal control is suitable for modeling individual human behavior and demonstrates the suitability of Inverse Reinforcement Learning in order to determine the cost function parameters which explain measured data

Dynamics of a thin liquid film with surface rigidity and spontaneous curvature

The effect of rigid surfaces on the dynamics of thin liquid films which are amenable to the lubrication approximation is considered. It is shown that the Helfrich energy of the layer gives rise to additional terms in the time-evolution equations of the liquid film. The dynamics is found to depend on the absolute value of the spontaneous curvature, irrespective of its sign. Due to the additional terms, a novel finite wavelength instability of flat rigid interfaces can be observed. Furthermore, the dependence of the shape of a droplet on the bending rigidity as well as on the spontaneous curvature is discussed.Comment: 4 pages, 5 figure

Non-Uniform Distributions in Quantitative Information-Flow

Quantitative information-flow analysis (QIF) determines the amount of information that a program leaks about its secret inputs. For this, QIF requires an assumption about the distribution of the se-cret inputs. Existing techniques either consider the worst-case over a (sub-)set of all input distributions and thereby over-approximate the amount of leaked information; or they are tailored to reason-ing about uniformly distributed inputs and are hence not directly applicable to non-uniform use-cases; or they deal with explicitly represented distributions, for which suitable abstraction techniques are only now emerging. In this paper we propose a novel approach for a precise QIF with respect to non-uniform input distributions: We present a reduction technique that transforms the problem of QIF w.r.t. non-uniform distributions into the problem of QIF for the uniform case. This reduction enables us to directly apply ex-isting techniques for uniform QIF to the non-uniform case. We furthermore show that quantitative information flow is robust with respect to variations of the input distribution. This result allows us to perform QIF based on approximate input distributions, which can significantly simplify the analysis. Finally, we perform a case study where we illustrate our techniques by using them to analyze an integrity check on non-uniformly distributed PINs, as they are used for banking

Model-Based Control of a Large-Scale Ball-on-Plate System With Experimental Validation

A ball-on-plate system is a widespread education oriented laboratory experiment for automation in mechatronics. The setup combines elements of mechanical, electrical and control engineering and is an adequate setup for learning the combination of theory and practice. This paper presents an example of a workshop result on automatic control in mechatronics. The aim of the workshop is to develop and compare model-based approaches for ball position control in a given large-scale ball-on-plate system. The result includes the derivation of a non-linear state space model of the system. The equations are linearized in the center of the horizontal plate as an operating point in order to apply cascade control, linear-quadratic optimal control and PI optimal state feedback control. The algorithms are implemented on a microcontroller and tested in the experimental setup. The results show a successful control development which achieves the control goal with good performance in terms of command response