Manfred Grauer

Approximating a finite element model by neural network prediction for facility optimization in groundwater engineering

A common technique for modeling complex systems in many computational engineering domains is the finite element method. Analyzing these systems using the finite element method involves the application of time consuming methods of numerical simulation. Optimizing these systems often implies many hundreds of these analyses leading to an excessive computational load and therefore an impractical runtime of the optimization process. In this paper, an approach is presented to utilize predictions computed by a neural network to approximate the results of a simulation system based on the finite element method, yielding a precision of the approximation of at least 99%. This approximation is integrated into an optimization strategy. The prediction-based optimization approach is demonstrated by solving a facility optimization problem in groundwater engineering. The results demonstrate that the computation time can be reduced by at least 60%.

Stock Market Prediction with Multiple Regression, Fuzzy Type-2 Clustering and Neural Networks

Abstract Stock market forecasting research offers many challenges and opportunities, with the forecasting of individual stocks or indexes focusing on forecasting either the level (value) of future market prices, or the direction of market price movement. A three-stage stock market prediction system is introduced in this article. In the first phase, Multiple Regression Analysis is applied to define the economic and financial variables which have a strong relationship with the output. In the second phase, Differential Evolution-based type-2 Fuzzy Clustering is implemented to create a prediction model. For the third phase, a Fuzzy type-2 Neural Network is used to perform the reasoning for future stock price prediction. The results of the network simulation show that the suggested model outperforms traditional models for forecasting stock market prices.

A scalable service-oriented architecture for multimedia analysis, synthesis and consumption

Although Service-Oriented Architectures (SOAs) were not designed for multimedia processing, they speed up the development of distributed multimedia applications by allowing the composition or reconfiguration of existing services. For example, the Business Process Execution Language for Web Services (BPEL) is a powerful tool to orchestrate, model and execute workflows. However, due to its process-oriented approach, it is not directly applicable to data-intensive applications, such as those from the multimedia domain. In this paper, a comprehensive service-oriented infrastructure for multimedia applications is presented that (a) overcomes some drawbacks of BPEL for data-intensive applications and (b) provides tools that further ease the development and use of web services for a broad scope of multimedia applications covering video content analysis, audio analysis and synthesis and multimedia consumption. The proposed service-oriented infrastructure can be easily integrated into existing business processes by using BPEL. A dynamic allocation of cloud computing resources ensures the scalability of a multimedia application. To allow efficient and flexible data transfers in BPEL workflows, an implementation of the Flexible SOAP with Attachments (Flex-SwA) architecture is used that allows data transmission in conjunction with SOAP messages. The protocol requirements of services in the case of real-time, streaming or file transfer can be described by a communication policy. Three use cases of multimedia applications are evaluated.

VRML history: storing and browsing temporal 3D-worlds

Spatio-temporal data are presented and explored by VR-based visualization systems which offer 3D-navigation and time-navigation for better immersion and analysis. If the visualization results are disseminated on the WWW, they are mostly transformed into videos or, recently, into animated VRML-files which neither support 3D-navigation nor time navigation nor a time-referenced data representation. In this paper, the script language VRML History is proposed which supports the description of spatio-temporal worlds on the internet by conceptually extending VRML with a new time dimension. This is realized by a set of new nodes representing temporal geometries and time references, and a set of Java-classes extending standard VRML-browsers to perform time navigation. CR

Towards an IT-Framework for Digital Enterprise Integration

Globalization has resulted in a dynamic environment which is a combination of uncertainties and unpredictable behaviour of customers, enterprise partners and market conditions. As a consequence, manufacturing enterprises tend to improve the monitoring and control of enterprise value creation processes to achieve flexibility and adaptability. Enterprise integration (EI) can be seen as a prerequisite for realizing a multi-loop control system within and across different enterprise levels. Various standards are available for EI but these standards do not mention how to realize them in terms of technology. Therefore, an IT-framework for digital EI based on different standards and technologies is proposed. This IT-framework describes integration of manufacturing level and enterprise control level, graphical user interface for visualization and control, and process control using workflow management system and rule-based system. Finally, a case study is presented showing the application of the IT-framework for different types of manufacturing.

Parallel Nonlinear Optimization on a Multiprocessor System with Distributed Memory

This paper deals with the solution of practical nonlinear optimization problems which arise especially in the fields of engineering design and production planning. In their mathematical description these problems frequently consist of highly nonlinear objective functions and constraints whose evaluation may lead to time-consuming simulation runs. In these cases assumptions about unimodality, convexity, and smoothness of well-known solution methods in nonlinear optimization are mostly invalid. An intuitive approach to overcoming these problems would be to apply a simultaneous combination of different optimization algorithms. In this situation the basis for a more reliable and even faster solution is the controlled information exchange on the continuing solution progress between the participating and parallel running methods. This idea has been implemented on a multiprocessor system with distributed memory for the solution of nonlinear optimization problems. Based on previous experiences with different algorithms, a coarse-grained parallelization approach under asynchronous control has been developed.

OpTiX-II: A software environment for the parallel solution of nonlinear optimization problems

The intention of the paper is to give an introduction to the OpTiX-II Software Environment, which supports the parallel and distributed solution of mathematical nonlinear programming problems. First, a brief summary of nonsequential solution concepts for nonlinear optimization on multiprocessor systems will be given. The focus of attention will be put on coarse-grained parallelization and its implementation on multi-computer clusters. The conceptual design objectives for the OpTiX-II Software Environment will be presented as well as the implementation on a workstation cluster, a transputer system and a multiprocessor workstation (shared memory). The OpTiX-II system supports the steps from the formulation of nonlinear optimization problems to their solution on networks of (parallel) computers. In order to demonstrate the use of OpTiX-II, the solution of a nonlinear optimization problem from the field of structural design is discussed and some numerical test results are supplied.

An event driven software framework for enabling enterprise integration and control of enterprise processes

In recent years to sustain competitive advantages, manufacturing enterprises strive for improvements in their monitoring and control of enterprise processes. Hence in the current contribution, an event driven software framework for enabling enterprise integration (EI) and enhancing control of enterprise processes is presented. The proposed framework is composed of four main components: First, a data collection engine is used for physical resource integration. Second, data aggregation engine integrates data from different enterprise levels, thus enabling EI. Third, control of enterprise processes is performed using a complex event processing engine. Finally, real-time resource and control data, and historical data can be visualized through process visualization clients. The framework has been validated in an industrial scenario.

Efficient data transmission in service workflows for distributed video content analysis

Workflows of web services orchestrated by the Business Process Execution Language (BPEL) have been successfully used in many business applications. Although these technologies were not originally designed for multimedia processing, they offer advantages to speed up the development of distributed multimedia analysis applications by allowing the composition or reconfiguration of existing services. However, in the case of service-oriented distributed video content analysis, a huge amount of binary data has to be transferred between different services. As a consequence, service orchestration based on BPEL leads to a performance bottleneck due to indirect message and data transport: the workflow engine receives results (which are potentially very large) from finished services and passes them to a subsequent service. In this paper, we present two novel approaches based on our previously developed Flex-SwA framework to model the binary data transmission between services in BPEL workflows. The proposed approaches circumvent the performance bottleneck at the orchestrating engine and provide efficient possibilities to transfer large data amounts as well as large data units. The first approach models the data flow in BPEL; the services exchange data directly. The second approach models the data flow outside of the BPEL engine and shifts it completely to the Flex-SwA framework. Experimental results for a video analysis workflow demonstrate the advantages of the proposed approaches.

Digital Tools in Media Studies: Analysis and Research. An Overview

Within the research project “Methods and Tools for Computer-Assisted Media Analysis” funded by Deutsche Forschungsgemeinschaft, we have developed the software toolkit Videana to relieve media scholars from the time-consuming task of annotating videos and films manually. In this paper, we present the automatic analysis tools and the graphical user interface (GUI) of Videana. The following automatic video content analysis approaches are part of Videana: shot boundary detection, camera motion estimation, detection and recognition of superimposed text, detection and recognition of faces in a video, and audio segmentation. The GUI of Videana allows the user to subsequently correct erroneous detection results and to insert user-defined comments or keywords at the shot level. Furthermore, several research applications of Videana are discussed. Finally, experimental results are presented for the content analysis approaches and compared to the quality of human annotations.