Fault detection and isolation in nonlinear systems

This paper deals with fault detection and identification in dynamic systems when the system dynamics can be modeled by smooth nonlinear differential equations including affine, bilinear or linear parameter varying (LPV) systems. Two basic approaches will be considered, these apply differential algebraic and differential geometric tools.In the differential algebraic approach the state elimination methods will be used to derive nonlinear parity relations. In the specific case when a reconstruction of the fault signal is needed the dynamic inversion based approach will be investigated. This approach will also be studied from geometric point of view. The geometric approach, as proposed by Isidori and De Persis, is suitable to extend the detection filter and unknown input observer design approaches (well elaborated for LTI systems) to affine nonlinear systems.Beyond the development of the theory of fault detection and identification it is equally important to offer computable methods and to analyze the robustness properties against uncertainties. Both the observer based and the inversion based approaches will be elaborated for LPV systems that may offer computational tools inherited from linear systems and also allow to design for robustness utilizing results from robust filtering and disturbance attenuation.     

Interactive survival analysis with the OCDM system: From development to application

Medical data mining is currently actively pursued in computer science and statistical research but not in medical practice. The reasons therefore lie in the difficulties of handling and statistically analyzing medical data. We have developed a system that allows practitioners in the field to interactively analyze their data without assistance of statisticians or data mining experts. In the course of this paper we will introduce data mining of medical data and show how this can be achieved for survival data. We will demonstrate how to solve common problems of interactive survival analysis by presenting the Online Clinical Data Mining (OCDM) system. Thereby the main focus is on similarity based queries, a new method to select similar cases based on their covariables and the influence of these on their survival.     

Finite-source M/M/S retrial queue with search for balking and impatient customers from the orbit

The present paper deals with a generalization of the homogeneous multi-server finite-source retrial queue with search for customers in the orbit. The novelty of the investigation is the introduction of balking and impatience for requests who arrive at the service facility with a limited capacity and FIFO queue. Arriving customers may balk, i.e., they either join the queue or go to the orbit. Moreover, the requests are impatient and abandon the buffer after a random time and enter the orbit, too. In case of an empty buffer, each server searches for a customer in the orbit after finishing service. All random variables involved in the model construction are supposed to be exponentially distributed and independent of each other. The primary aim of this analysis is to show the effect of balking, impatience, and buffer size on the steady-state performance measures. Concentrating on the mean response time, several numerical examples are investigated by the help of the MOSEL-2 tool used for creating the model and calculating the stationary characteristics.     

Detail-preserving fluid control

We propose a new fluid control technique that uses scale-dependent force control to preserve small-scale fluid detail. Control particles define local force fields and can be generated automatically from either a physical simulation or a sequence of target shapes. We use a multi-scale decomposition of the velocity field and apply control forces only to the coarse-scale components of the flow. Small-scale detail is thus preserved in a natural way avoiding the artificial viscosity often introduced by force-based control methods. We demonstrate the effectiveness of our method for both Lagrangian and Eulerian fluid simulation environments.     

Multicriteria decisions on interdependent infrastructure transportation projects using an evolutionary-based framework

When evaluating transportation infrastructure projects and determining which of them will be carried out from a set of projects and given a budget constraint, several criteria need to be considered in the decision. Standard evaluation practices imply the aggregation of impacts into one utility function which is later optimized. Nevertheless these techniques used for translation of different measuring units into monetary terms are highly controversial. Multicriteria techniques can explicitly deal with different measuring units, however, they are not suitable to model interdependence relationships of projects that share a common characteristic (same route, location or target population, for instance). In this research we model this transportation planning problem, the multi-objective transportation infrastructure project selection problem (MTIPSP), as a constrained multi-objective optimization problem with quadratic objective functions, using a variation of the multi-objective 0–1 knapsack problem plus some additional constraints. Given the combinatorial nature of the problem, an evolutionary-based framework is used for the identification of Pareto solutions, and later, those with non-attractive properties are filtered using a Knee Identification Procedure. The final selection of the projects portfolio is made using a well known multicriteria decision aid method and including the decision makers’ preferences based on the existing context.     

An Interoperable Grid Information System for Integrated Resource Monitoring Based on Virtual Organizations

In many Grid infrastructures different kinds of information services are in use, which utilize different incompatible data structures and interfaces to encode and provide their data. Homogeneous monitoring of these infrastructures with the monitoring data being accessible everywhere independently of the middleware which provided it, is the basis for a consistent status reporting on the Grids’ resources and services. Thus, interoperability or interoperation between the different information services in a heterogeneous Grid infrastructure is required. Monitoring data must contain the identity of the affected Virtual Organization (VO) so that it can be related to the resources and services the VO has allocated to enable VO-specific information provision. This paper describes a distributed architecture for an interoperable information service, which combines data unification and categorization with policies for VO membership, VO resource management and data transformations. This service builds the basis for an integrated and interoperating monitoring of Grids, which provide their data to more than one VO and utilize heterogeneous information services.     

Acclimatization model of an aerobic bioreactor for the treatment of toxic wastewater

This work proposes a mathematical model for the acclimatization process of a bioreactor treating toxic wastewater. Experimental data was used to identify the changing kinetic parameters of the model as acclimatization progresses. It was found that only one key parameter, the specific biomass growth rate function, changed during the acclimatization process. Therefore, an acclimatization model was proposed to explain the changes of this parameter.     

Das datenschutzrechtliche Vollzugsdefizit im Bereich der Telemedien — ein Schreckensbericht

Zusammenfassung  Die Autoren untersuchen das datenschutzrechtliche Vollzugsdefizit im Anwendungsbereich des Telemediengesetzes. Ihr Ergebnis ist, dass das Ausma? des datenschutzrechtlichen Vollzugsdefizits der von au?en zu überprüfenden datenschutzrechtlichen Pflichten der Anbieter „erschreckend“ ist. Nur einem ganz geringen Teil der Anbieter gelingt es, sich rechtskonform zu verhalten. Prof. Dr. Jürgen Kühling Inhaber eines Lehrstuhls für ?ffentliches Recht an der Universit?t Regensburg. Anastasios Sivridis wissenschaftlicher Mitarbeiter und Doktorand am Lehrstuhl Prof. Kühling. Mathis Schwuchow studentische Hilfskraft am Lehrstuhl Prof. Kühling. Thorben Burghardt wissenschaftlicher Mitarbeiter und Doktorand am Lehrstuhl für Systeme der Informationsverwaltung (TH Karlsruhe).     

Metamodeling live sequence charts for code generation

This article presents a metamodeling study for Live Sequence Charts (LSCs) and Message Sequence Charts (MSCs) with an emphasis on code generation. The article discusses specifically the following points: the approach to building a metamodel for MSCs and LSCs, a metamodel extension from MSC to LSC, support for model-based code generation, and finally action model and domain-specific data model integration. The metamodel is formulated in metaGME, the metamodel language for the Generic Modeling Environment.