Design and Validation of an Attention Model of Web Page Users

In this paper, we propose a model to predict the locations of the most attended pictorial information on a web page and the attention sequence of the information. We propose to divide the content of a web page into conceptually coherent units or objects, based on a survey of more than 100 web pages. The proposed model takes into account three characteristics of an image object: chromatic contrast, size, and position and computes a numerical value, the attention factor. We can predict from the attention factor values the image objects most likely to draw attention and the sequence in which attention will be drawn. We have carried out empirical studies to both develop and determine the efficacy of the proposed model. The study results revealed a prediction accuracy of about 80% for a set of artificially designed web pages and about 60% for a set of real web pages sampled from the Internet. The performance was found to be better (in terms of prediction accuracy) than the visual saliency model, a popular model to predict human attention on an image

Optimization Approaches to Adaptive Menus

Graphical menus perform as vital components and offer essential controls in today’s graphical interface. However, few studies have been conducted to modelling the performance of a menu. Furthermore, menu optimization methods previously proposed have been largely concentrating on reshaping layout of the whole menu system. In order to model menu performance, this thesis extends the Search-Decision-Pointing model by introducing two additional factors, i.e. the cost function and semantic function. The cost function is a penalty function which decreases the user expertise regarding a menu layout according to the degree of modification done to the menu. The semantic function is a reward function which encourages items with strong relations be positioned close to each other. Centered on this menu performance model, several optimization methods have been implemented. Each method focuses on improving menu performance by applying distinctive strategies, such as increasing item size or reducing item pointing distance. Three test cases have been exercised to evaluate the optimization methods in a simulated software which displays graphical user interfaces and emulates the menu utilization of real users. The results of test cases reveal that the menu performance has been successfully improved in all test cases by the fundamental heuristic search algorithm. Moreover, other optimization methods have been able to further increase menu performance ranging from 3% to 8% depending on test cases. In addition, it is identified that increasing the size of an item offers surprisingly little benefit. Conversely, reducing item pointing distance has greatly improved menu performance. Moreover, positioning items by their semantic relations may also enhance group saliency. On the other hand, optimization methods may not always succeed in providing usable menus due to design constraints. Hence, menu performance optimization shall be carefully exercised by considering the entire graphical user interface

An Empirical Methodology for Engineering Human Systems Integration

The systems engineering technical processes are not sufficiently supported by methods and tools that quantitatively integrate human considerations into early system design. Because of this, engineers must often rely on qualitative judgments or delay critical decisions until late in the system lifecycle. Studies reveal that this is likely to result in cost, schedule, and performance consequences. This dissertation presents a methodology to improve the application of systems engineering technical processes for design. This methodology is mathematically rigorous, is grounded in relevant theory, and applies extant human subjects data to critical systems development challenges. The methodology is expressed in four methods that support early systems engineering activities: a requirements elicitation method, a function allocation method, an input device design method, and a display layout design method. These form a coherent approach to early system development. Each method is separately discussed and demonstrated using a prototypical system development program. In total, this original and significant work has a broad range of systems engineer applicability to improve the engineering of human systems integration

Learning object metadata surrogates in search result interfaces: user evaluation, design and content

The purpose of this research was to evaluate user interaction with learning object metadata surrogates both in terms of content and presentation. The main objectives of this study were: (1) to review the literature on learning object metadata and user-centred evaluation of metadata surrogates in the context of cognitive information retrieval (including user-centred relevance and usability research); (2) to develop a framework for the evaluation of user interaction with learning object metadata surrogates in search result interfaces; (3) to investigate the usability of metadata surrogates in search result interfaces of learning object repositories (LORs) in terms of various presentation aspects (such as amount of information, structure and highlighting of query terms) as a means for facilitating the user relevance judgment process; (4) to investigate in-depth the type of content that should be included in learning object metadata surrogates in order to facilitate the process of relevance judgment; (5) to provide a set of recommendations—guidelines for the design of learning object metadata surrogates in search result interfaces both in terms of content and presentation. [Continues.

Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field