Error bounds for low-rank approximations of the first exponential integral kernel

A hierarchical matrix is an efficient data-sparse representation of a matrix, especially useful for large dimensional problems. It consists of low-rank subblocks leading to low memory requirements as well as inexpensive computational costs. In this work, we discuss the use of the hierarchical matrix technique in the numerical solution of a large scale eigenvalue problem arising from a finite rank discretization of an integral operator. The operator is of convolution type, it is defined through the first exponential-integral function and, hence, it is weakly singular. We develop analytical expressions for the approximate degenerate kernels and deduce error upper bounds for these approximations. Some computational results illustrating the efficiency and robustness of the approach are presented.

GUI Inspection from Source Code Analysis

Graphical user interfaces (GUIs) are critical components of todays software. Given their increased relevance, correctness and usability of GUIs are becoming essential. This paper describes the latest results in the development of our tool to reverse engineer the GUI layer of interactive computing systems. We use static analysis techniques to generate models of the user interface behaviour from source code. Models help in graphical user interface inspection by allowing designers to concentrate on its more important aspects. One particularly type of model that the tool is able to generate is state machines. The paper shows how graph theory can be useful when applied to these models. A number of metrics and algorithms are used in the analysis of aspects of the user interface's quality. The ultimate goal of the tool is to enable analysis of interactive system through GUIs source code inspection.

Profiling consumer behaviour in cross-border tourism destinations

Tourism is a phenomenon that moves millions of people around the world, taking as a major driver of the global economy. Such relevance is reflected in the proliferation of studies in the overall area known as tourism, under various perspectives and backgrounds. In the light of such multitude of insights our study aims at gaining a deeper understanding of customer profiling and behavior in cross-border tourism destinations. Previous studies conducted in such contexts suggest that cross-border regions (CBRs) are an attractive and desirable idea, yet requiring further theoretical and empirical research. The new configuration of many CBRs calls for a debate on issues concerning its development, raising up important dimensions, such as, organization and planning of common tourism destinations. There is still a gap in the understanding of destination management in CBRs and the customer profile and motivations. Overall this research aims at attaining a deeper understanding of the profile and behavior of consumers in tourism settings, addressing the predisposition for the destination. The study addresses the following research question: “What factors influence customer behavior and attitudes in a CBRs tourism destination?” To address our question we will take an interdisciplinary perspective bringing together inputs from marketing, tourism and local economics. When addressing consumer behavior in tourism previous studies considered the following constructs: involvement, place attachment, satisfaction and destination loyalty. In order to establish the causal relationships in our theoretical model, we intend to develop a predominant quantitative design, yet we plan to conduct exploratory interviews. In the analysis and discussion of results, we intend to use Structural Equation Modeling. It will further allow understanding how the constructs in the research model relate to each other in the specified context. Results are also expected to have managerial implications. Consequently our results may assist decision makers in developing their local policies.