A great effort has been made today in the area of Artificial Intelligence for defining reliable automated planning systems that can be applied in real life applications. That leads to the need of a systematic design process, in which the initial phases are not neglected and where Knowledge and Requirement Engineering tools have a fundamental role for supporting designers. Following this principle, this paper presents the evolution of the tool itSIMPLE which implements a KE integrated environment where designers can perform knowledge acquisition, domain modeling, domain model analysis, model testing, maintenance and plan analysis processes by using different well-known languages such as UML, Petri Nets, PDDL and XML, each one of them with its best contribution. The tool supports users in an organized object-oriented domain design process with a friendly and easy-to-use interface.
Schramm, Joachim (Clausthal University of Technology) | Strickroth, Sven (Clausthal University of Technology) | Le, Nguyen-Thinh (Clausthal University of Technology) | Pinkwart, Niels (Clausthal University of Technology)
Modeling skills are essential during the process of learning programming. ITS systems for modeling are typically hard to build due to the ill-definedness of most modeling tasks. This paper presents a system that can teach UML skills to novice programmers. The system is “simple and cheap” in the sense that it only requires an expert solution against which the student solutions are compared, but still flexible enough to accommodate certain degrees of solution flexibility and variability that are characteristic of modeling tasks. An empirical evaluation via a controlled lab study showed that the system worked fine and, while not leading to significant learning gains as compared to a control condition, still revealed some promising results.
Virtual Enterprise is an important organization pattern for future enterprises, one of whose major functions is the distributed and parallel business process execution. This paper aims at the study on business process modeling in virtual enterprises. Based on the object-oriented description of business processes in virtual enterprises, we propose a UML and Petri nets integrated modeling method for business processes in virtual enterprises. The method provides an integrative framework supporting requirement description, model specification and design, model analysis and simulation, and model implementation.
Andrew Kusiak, Intelligent Systems Laboratory, Department of Industrial Engineering Nick Larson, Intelligent Systems Laboratory, Deparlment of Industrial Engineering The University of Iowa, Iowa City, Iowa 52242-1527 1. Introduction Evaluating system reliability requires modeling the interaction of resources, information, and material within the system. Such a model must consider quantitative data describing the reliability of each element of the system, as well as logical data describing the relationship between individual components. For example, a manufacturing system may assemble products X, Y, and Z, on machines M1, M2, and M3, respectively, and package the products on a fourth machine, M4. Therefore, three different relationships exist between the components of the system, one for each product. Similarly, the reliability of the system as a whole will be affected by the production levels of products X, Y, and Z. Given the example above, with only three products and four machines, it becomes apparent that determining system reliability requires a significant amount of data and a structured modeling methodology.
Genomics is becoming a data-intensive science, and an increasing number of laboratories are generating data which swampstorage in traditional paper-and-ink notebooks. Capturing the data flow requires large systems with multiple applications manipulating the same or similar data. Large systems often have conflicting requirements for data representation. Consistency across applications is a prime consideration, and appropriate data representation is an important issue in developing practical systems for molecular biologists. Graphs are a natural representation for describing genome data, while objects are good for modeling the behavior necessary, for laboratory, applications. We present a method for translating graph descriptions of genome data into objects using objects as views on graphs. Graph representations describe genome concepts while objects capture individual views for application development insuring consistency across genome applications.