Annual Report 1999 / Department for Computer Science

Selbstdarstellung des Instituts für Informatik der BTU Cottbus und Berichte der Lehrstühle für das Jahr 1999.Presentation of the Department for Computer Science of the BTU Cottbus and reports of the chairs at the department for the year 1999

Training of PDCA cycle using a catapult in a virtual learning environment

The sustainable teaching of quality methods in the sense of Lean Management and Six Sigma through assistance systems, such as virtual reality goggles, represents a new and growing aspect of continuing education programs. The development and usage of virtual learning environments offers the chance to deepen the theoretical prior knowledge through interactive learning possibilities. In this way, existing learning concepts are supplemented with virtual teaching content. Complex or difficult to present learning settings can be mapped virtually without high material consumption or costs. This paper presents the state of the art with respect to teaching quality methods with VR. An integrationin the created Assisted Reality Implementation Model is made. Subsequently, the requirements for a virtual learning environment based on a real business game are determined. The approach and implementation are explained using the example of the PDCA quality method. First results of the exploration tests from the questionnaires are presented. Based on this, improvements are derived and the next steps are defined

Cardinality estimation in ETL processes

The cardinality estimation in ETL processes is particularly difficult. Aside from the well-known SQL operators, which are also used in ETL processes, there are a variety of operators without exact counterparts in the relational world. In addition to those, we find operators that support very specific data integration aspects. For such operators, there are no well-examined statistic approaches for cardinality estimations. Therefore, we propose a black-box approach and estimate the cardinality using a set of statistic models for each operator. We discuss different model granularities and develop an adaptive cardinality estimation framework for ETL processes. We map the abstract model operators to specific statistic learning approaches (regression, decision trees, support vector machines, etc.) and evaluate our cardinality estimations in an extensive experimental study

Exploiting Queuing Networks to Model and Assess the Performance of Self-Adaptive Software Systems: A Survey

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