Abstract
The UML is recognized to be the dominant diagrammatic modeling language in the software industry. However, it's support for building interactive systems is still acknowledged to be insufficient. There is a common misconception that the same models developed to support the design of the application internals are also adequate to support interaction design, leveraging the usability aspects of the applications. In this paper we identify and discuss the major problems using the UML to document, specify and design interactive systems. Here we propose a UML profile for interactive systems development that leverages oil human-computer interaction domain knowledge under the common notation and semantics of the UML. Our proposal integrates with existing object-oriented software engineering best practice, fostering co-evolutionary development of interactive systems and enabling artifact change between software engineering and human-computer interaction.

Abstract
Wisdom is a new software engineering method addressing the specific needs of small reams that develop and maintain interactive systems. Because Wisdom defines a process, notation, and project philosophy, it can smoothly be applied in small companies leveraging on their communication, speed, and flexibility.

Abstract
We propose a data mining model that captures the user navigation behaviour patterns. The user navigation sessions are modelled as a hypertext probabilistic grammar whose higher probability strings correspond to the user's preferred trails. An algorithm to efficiently mine such trails is given. We make use of the N gram model which assumes that the last N pages browsed affect the probability of the next page to be visited. The model is based on the theory of probabilistic grammars providing it with a sound theoretical foundation for future enhancements. Moreover, we propose the use of entropy as an estimator of the grammar's statistical properties. Extensive experiments were conducted and the results show that the algorithm runs in linear time, the grammar's entropy is a good estimator of the number of mined trails and the real data rules confirm the effectiveness of the model. © Springer-Verlag Berlin Heidelberg 2000.

Abstract

Abstract

Abstract
The nesting problem consists of defining the cutting plan of a piece of raw material in smaller irregular shapes, and has applications in the apparel and footwear industries. Due to its NP-hard nature, the optimal solution can only be guaranteed by exhaustively trying all possible solutions and choosing the best one. Because this is impractical in real-life industrial problems, automatic approaches are based on optimization meta-heuristics that search for sub-optimal but good enough solutions. These optimization techniques rely on the construction and evaluation of several solutions, thus requiring heavy geometric manipulation of the irregular polygons that constitute the problem data. Efficient processing of this geometric information is thus necessary to make effective fully automatic approaches to nesting problems in industrial environments. This paper describes Fafner, an FPGA-based custom computing machine that is used to accelerate the geometric operations, that are in the core of heuristic solutions to the nesting problem. The system is used as an auxiliary processor attached to a low cost personal computer, and combines a custom programmable processor with an array of custom circuits for the processing of irregular polygons.