Clemens Beckstein

A neural network approach for the optimisation of watershed management

Abstract Managing a catchment for drinking water supply with a high proportion of agricultural land use is a difficult task if one has to maintain a reasonable balance between water quality demand and consequent restrictions for the farming industry. In this paper, we present a neural net-based method for finding good approximations to solutions of this problem. This method is capable of ‘inverting’ a hydrological model to identify land use scenarios that match best the leaching criteria defined for establishing a certain water quality level in the stream. The method not only allows simulation land use scenarios like hydrologic models do, but can search systematically for land use scenarios that fulfill specified criteria without worrying about the complexity of combinatorial optimisation.

A Meta Level Architecture For Workflow Management

Frameworks are class hierarchies plus models of interactions which can be turned into complete applications through various kinds of specialization. Design patterns often guide the construction and documentation of frameworks. The run-time architecture of a framework is characterized by an inversion of control: event handler objects of the application are invoked via the frameworks reactive dispatching mechanism. This paper reports the development process of a software architecture that has been designed for accomplishing the transfer of operation specifications among interoperable information systems within a larger project, such that · the communication framework does not need to know the structure and different types of operation specifications to be transferred and · the individual information systems do not need to know the communication platform (in our case CORBA). Some design patterns guided the construction of the resulting object-oriented framework to achieve a flexible software architecture. The emphasis of this paper is on the discussion of the development process by which the communication framework has been designed.

A multi-layer-perceptron neural network hardware based on 3D massively parallel optoelectronic circuits

A digital neural network architecture is presented which is based on three-dimensional massively parallel optoelectronic circuits. A suitable optical interconnect system and the structure of the required electronic circuits is specified. For this system general formulas for the performance of such a neural network architecture are determined. A parameter study using current technological limitations and timing values from electronic implementation is carried out. Based on this analysis if is shown that this novel type of neuroarchitecture that is using 3D massively parallel optoelectronic circuits shows performance rates of up to one magnitude higher than systems using digital neurochips based on fully electronic implementation.

Structure, function, and behaviour of computational models in systems biology

BackgroundSystems Biology develops computational models in order to understand biological phenomena. The increasing number and complexity of such “bio-models” necessitate computer support for the overall modelling task. Computer-aided modelling has to be based on a formal semantic description of bio-models. But, even if computational bio-models themselves are represented precisely in terms of mathematical expressions their full meaning is not yet formally specified and only described in natural language.ResultsWe present a conceptual framework – the meaning facets – which can be used to rigorously specify the semantics of bio-models. A bio-model has a dual interpretation: On the one hand it is a mathematical expression which can be used in computational simulations (intrinsic meaning). On the other hand the model is related to the biological reality (extrinsic meaning). We show that in both cases this interpretation should be performed from three perspectives: the meaning of the model’s components (structure), the meaning of the model’s intended use (function), and the meaning of the model’s dynamics (behaviour). In order to demonstrate the strengths of the meaning facets framework we apply it to two semantically related models of the cell cycle. Thereby, we make use of existing approaches for computer representation of bio-models as much as possible and sketch the missing pieces.ConclusionsThe meaning facets framework provides a systematic in-depth approach to the semantics of bio-models. It can serve two important purposes: First, it specifies and structures the information which biologists have to take into account if they build, use and exchange models. Secondly, because it can be formalised, the framework is a solid foundation for any sort of computer support in bio-modelling. The proposed conceptual framework establishes a new methodology for modelling in Systems Biology and constitutes a basis for computer-aided collaborative research.

Controlling fast spring-legged locomotion with artificial neural networks

Abstract Controlling the model of an one-legged robot is investigated. The model consists merely of a mass less spring attached to a point mass. The motion of this system is characterised by repeated changes between ground contact and flight phases. It can be kept in motion by active control only. Robots that are suited for fast legged locomotion require different hardware layouts and control approaches in contrast to slow moving ones. The spring mass system is a simple model that describes this principle movement of a spring-legged robot. Multi-Layer-Perceptrons (MLPs), Radial Basis Functions (RBFs) and Self-Organising Motoric Maps (SOMMs) were used to implement neurocontrollers for such a movement system. They all prove to be suitable for control of the movement. This is also shown by an experiment where the environment of the spring-mass system is changed from even to uneven ground. The neurocontroller is performing well with this additional complexity without being trained for it.

A structuralistic approach to ontologies

It is still an open question how the relation between ontologies and their domains can be fixed. We try to give an account of semantic and pragmatic aspects of formal knowledge by describing ontologies in terms of a particular school in philosophy of science, namely structuralism. We reconstruct ontologies as empirical theories and interpret expressions of an ontology language by semantic structures of a theory. It turns out that there are relevant aspects of theories which cannot as yet be taken into consideration in knowledge representation. We thus provide the basis for extending the concept of ontology to a theory of the use of a language in a community.

Standard cell-based implementation of a digital optoelectronic neural-network hardware

A standard cell-based implementation of a digital optoelectronic neural-network architecture is presented. The overall structure of the multilayer perceptron network that was used, the optoelectronic interconnection system between the layers, and all components required in each layer are defined. The design process from VHDL-based modeling from synthesis and partly automatic placing and routing to the final editing of one layer of the circuit of the multilayer perceptrons are described. A suitable approach for the standard cell-based design of optoelectronic systems is presented, and shortcomings of the design tool that was used are pointed out. The layout for the microelectronic circuit of one layer in a multilayer perceptron neural network with a performance potential 1 magnitude higher than neural networks that are purely electronic based has been successfully designed.

Algorithmic Debugging and Hypothetical Reasoning

This paper presents a generalization of Shapiro style algorithmic debugging for generalized Horn clause intuitionistic logic. This logic offers hypothetical reasoning and negation is defined not by failure but by inconsistency. We extend Shapiros notion of intended interpretation, symptoms and errors and give formal results paralleling those known for definite clauses. We also show how a corresponding diagnosis module for RISC- a logic programming system for generalized Horn clause intuitionistic logic-can be defined by meta interpretation. In contrast to Shapiros PROLOG modules ours work independently of the specific computation rule that in RISC may be specified by the user.

SOGOS - A Distributed Meta Level Architecture for the Self-Organizing Grid of Services

Handling highly dynamic scenarios as they arise in emergency situations requires lots of semantic information about the situation and an extremely flexible, selforganizing IT infrastructure that provides services that can be used to manage the situation. We show that a distributed meta level architecture is particularly suited for the implementation of such a self-organizing grid of services. This architecture (SOGOS) distinguishes between an object level and a meta level. The middleware processes of the grid are running on the object level. The meta level defines an explicitly and declaratively represented dynamic meta model that provides the semantics for the object level processes. Additionally, this level runs processes that plan, supervise and control mobile agents on the object level. The levels are linked together by reflection processes that ensure that relevant changes on the object level are reflected in the meta model and vice versa. The corresponding reflection principles provide the basis for the implementation of the selforganizing mechanisms that govern the overall system.

Semantic services for information and management support in mass casualty incident scenarios

Operation managers in mass casualty incidents (MCI) are easily overwhelmed by the highly dynamic scenario. Today, they are often supported by paper-based checklists that help ensure that nothing important gets overlooked. In this paper, we present our approach to dramatically increase the support offered by such checklists: We suggest to replace them by IT-based intelligent checklists that will not only display information the manager should collect and tasks he might perform, but directly support semi-automatic information gathering, propagation and task-execution.