Tracking control for boundary controlled parabolic PDEs with varying parameters: Combining backstepping and differential flatness

The combination of backstepping-based state-feedback control and flatness-based trajectory planning and feedforward control is considered for the design of an exponentially stabilizing tracking controller for a linear diffusion-convection-reaction system with spatially and temporally varying parameters and nonlinear boundary input. For this, in a first step the backstepping transformation is utilized to determine a state-feedback controller, which transforms the original distributed-parameter system into an appropriately chosen exponentially stable distributed-parameter target system of a significantly simpler structure. In a second step, the flatness property of the target system is exploited in order to determine the feedforward controller, which allows us to realize the tracking of suitably prescribed trajectories for the system output. This results in a systematic procedure for the design of an exponentially stabilizing tracking controller for the considered general linear diffusion-convection-reaction system with varying parameters, whose applicability and tracking performance is evaluated in simulation studies.     

Coding of watershed and river hierarchy to support GIS-based hydrological analyses at different scales

A procedure is presented to automatically assign a modified Pfafstetter code to a stream network and its associated watersheds. The first step is to build a topological network according to the object-oriented Arc Hydro framework definition in ArcGIS. These network relations are then mapped into a code that fully represents the stream hierarchy of a basin in a single attribute. Its use does not depend on ArcGIS object orientation and facilitates simple hierarchical aggregation and querying using only the attribute tables of shapefile versions of the stream network and watershed datasets. The code was implemented for the whole of Austria to support the flexible presentation and user-defined aggregation of water balance results in the digital version of the Hydrological Atlas of Austria.     

The Complexity of Hybrid Logics over Equivalence Relations

This paper examines and classifies the computational complexity of model checking and satisfiability for hybrid logics over frames with equivalence relations. The considered languages contain all possible combinations of the downarrow binder, the existential binder, the satisfaction operator, and the global modality, ranging from the minimal hybrid language to very expressive languages. For model checking, we separate polynomial-time solvable from PSPACE-complete cases, and for satisfiability, we exhibit cases complete for NP, PSpace, NExpTime, and even N2ExpTime. Our analysis includes the versions of all these languages without atomic propositions, and also complete frames.     

A new dynamic hydrogen reference electrode for applications in thin-film sensor systems

The realization and applicability of a new dynamic hydrogen reference electrode (DHRE) within an electrochemical microcell for sensor applications is reported. The electrodes are fabricated in thin-film technology and fixed within a flow-through device. An experimental setup for accurate electrochemical potential measurements is described. Smooth platinum, platinized platinum and pHEMA coated electrodes are investigated with regard to their initialization behavior, stability, reproducibility and interference with electrolytes. It is found that platinized platinum DHREs show excellent stability and reproducibility. For uncoated electrodes, the electrochemical potential is established within seconds. The potential is independent of the pH value within the range of pH 4–10. Interference with sulfate and phosphate is observed. Thus, the platinized platinum DHRE is well suited for bioanalytical sensor applications, where the pH value is buffered and the concentrations of the disturbing anions are constant or very low.     

Recording and interpretation/analysis of tilt signals with five ASKANIA borehole tiltmeters at the KTB

In June 2003, a large scale injection experiment started at the Continental Deep Drilling site (KTB) in Germany. A tiltmeter array was installed which consisted of five high resolution borehole tiltmeters of the ASKANIA type, also equipped with three dimensional seismometers. For the next 11 months, 86 000 m(3) were injected into the KTB pilot borehole 4000 m deep. The average injection rate was approximately 200 l/min. The research objective was to observe and to analyze deformation caused by the injection into the upper crust at the kilometer range. A new data acquisition system was developed by Geo-Research Center Potsdam (GFZ) to master the expected huge amount of seismic and tilt data. Furthermore, it was necessary to develop a new preprocessing software called PREANALYSE for long-period time series. This software includes different useful functions, such as step and spike correction, interpolation, filtering, and spectral analysis. This worldwide unique installation offers the excellent opportunity of the separation of signals due to injection and due to environment by correlation of the data of the five stations with the ground water table and meteorological data.     

Deformation models for image recognition

We present the application of different nonlinear image deformation models to the task of image recognition. The deformation models are especially suited for local changes as they often occur in the presence of image object variability. We show that, among the discussed models, there is one approach that combines simplicity of implementation, low-computational complexity, and highly competitive performance across various real-world image recognition tasks. We show experimentally that the model performs very well for four different handwritten digit recognition tasks and for the classification of medical images, thus showing high generalization capacity. In particular, an error rate of 0.54 percent on the MNIST benchmark is achieved, as well as the lowest reported error rate, specifically 12.6 percent, in the 2005 international ImageCLEF evaluation of medical image specifically categorization.     

The Dynamics of Syntactic Knowledge

The syntactic approach to epistemic logic avoids the logicalomniscience problem by taking knowledge as primary rather thanas defined in terms of possible worlds. In this study, we combinethe syntactic approach with modal logic, using transition systemsto model reasoning. We use two syntactic epistemic modalities:‘knowing at least’ a set of formulae and ‘knowingat most’ a set of formulae. We are particularly interestedin models restricting the set of formulae known by an agentat a point in time to be finite. The resulting systems are investigatedfrom the point of view of axiomatization and complexity. Weshow how these logics can be used to formalise non-omniscientagents who know some inference rules, and study their relationshipto other systems of syntactic epistemic logics, such as Ågotnesand Walicki (2004, Proc. 2nd EUMAS, pp. 1–10), Alechinaet al. (2004, Proc. 3rd AAMAS, pp. 601–613), Duc (1997,J. Logic Comput., 7, 633–648).     

Oscillatory networks: pattern recognition without a superposition catastrophe

Using an oscillatory network model that combines classical network models with phase dynamics, we demonstrate how the superposition catastrophe of pattern recognition may be avoided in the context of phase models. The model is designed to meet two requirements: on and off states should correspond, respectively, to high and low phase velocities, and patterns should be retrieved in coherent mode. Nonoverlapping patterns can be simultaneously active with mutually different phases. For overlapping patterns, competition can be used to reduce coherence to a subset of patterns. The model thereby solves the superposition problem.     

Distributed Symbolic Bounded Property Checking

In this paper we describe an algorithm for distributed, BDD-based bounded property checking and its implementation in the verification tool SymC. The distributed algorithm verifies larger models and returns results faster than the sequential version.The core algorithm distributes partitions of the state set to computation nodes after reaching a threshold size. The nodes proceed with image computation on the nodes asynchronously. The main scalability problem of this scheme is the overlap of state set partitions. We present static and dynamic overlap reduction techniques.