Supporting shape reinterpretation with eye tracking

It has been argued that reinterpretation is an essential process in design generation and idea exploration. However, computational design tools, such as computer-aided design systems, offer poor support for shape reinterpretation, and as such are not well suited to ideation in conceptual design. One of the key difficulties in implementing computational systems that support shape reinterpretation is the issue of interface – how can a user intuitively guide a system with respect to their interpretation of a designed shape? In this paper, a software prototype is presented that uses an eye tracking interface to support reinterpretation of shapes according to recognised subshapes. The prototype is based on eye tracking studies, and uses gaze data and user input to restructure designed shapes so that they afford manipulation according to users’ interpretations

Image mining: trends and developments

[Abstract]: Advances in image acquisition and storage technology have led to tremendous growth in very large and detailed image databases. These images, if analyzed, can reveal useful information to the human users. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. Image mining is more than just an extension of data mining to image domain. It is an interdisciplinary endeavor that draws upon expertise in computer vision, image processing, image retrieval, data mining, machine learning, database, and artificial intelligence. In this paper, we will examine the research issues in image mining, current developments in image mining, particularly, image mining frameworks, state-of-the-art techniques and systems. We will also identify some future research directions for image mining

Post-processing of association rules.

In this paper, we situate and motivate the need for a post-processing phase to the association rule mining algorithm when plugged into the knowledge discovery in databases process. Major research effort has already been devoted to optimising the initially proposed mining algorithms. When it comes to effectively extrapolating the most interesting knowledge nuggets from the standard output of these algorithms, one is faced with an extreme challenge, since it is not uncommon to be confronted with a vast amount of association rules after running the algorithms. The sheer multitude of generated rules often clouds the perception of the interpreters. Rightful assessment of the usefulness of the generated output introduces the need to effectively deal with different forms of data redundancy and data being plainly uninteresting. In order to do so, we will give a tentative overview of some of the main post-processing tasks, taking into account the efforts that have already been reported in the literature.

Business model design: an evaluation of paper-based and computer-aided canvases

In recent years, Business Model Canvas design has evolved from being a paper-based activity to one that involves the use of dedicated computer-aided business model design tools. We propose a set of guidelines to help design more coherent business models. When combined with functionalities offered by CAD tools, they show great potential to improve business model design as an ongoing activity. However, in order to create complex solutions, it is necessary to compare basic business model design tasks, using a CAD system over its paper-based counterpart. To this end, we carried out an experiment to measure user perceptions of both solutions. Performance was evaluated by applying our guidelines to both solutions and then carrying out a comparison of business model designs. Although CAD did not outperform paper-based design, the results are very encouraging for the future of computer-aided business model design

Translating Scientific Content into Accessible Formats with Visually Impaired Learners: Recommendations and a Decision Aid Based on Haptic Rules of Perception

Students with visual impairments (VI) miss out on science because of inaccessible visual graphics (such as pictures and diagrams) of the phenomena that are the focus of curricula. My project examines how efforts to translate these into non-visual representations, such as raised line graphics, tend to be less effective than expected because they are perceived using “rules” of haptic perception by VI learners but developed using “rules”' of visual perception by sighted designers. In response, I introduce my recommendations, in the form of a decision aid, informed by a series of interlinked concatenated studies consisting of user testing, workshops, and co-design sessions composed of multi-disciplinary teams that included VI educators, learners, inclusive designers, musicians, and domain experts from engineering and the cognitive neuroscience

Interactive visual exploration of association rules with rule-focusing methodology

International audienceOn account of the enormous amounts of rules that can be produced by data mining algorithms, knowledge post-processing is a difficult stage in an association rule discovery process. In order to find relevant knowledge for decision making, the user (a decision maker specialized in the data studied) needs to rummage through the rules. To assist him/her in this task, we here propose the rule-focusing methodology, an interactive methodology for the visual post-processing of association rules. It allows the user to explore large sets of rules freely by focusing his/her attention on limited subsets. This new approach relies on rule interestingness measures, on a visual representation, and on interactive navigation among the rules. We have implemented the rule-focusing methodology in a prototype system called ARVis. It exploits the user's focus to guide the generation of the rules by means of a specific constraint-based rule-mining algorithm

Applications of Virtual Reality

Information Technology is growing rapidly. With the birth of high-resolution graphics, high-speed computing and user interaction devices Virtual Reality has emerged as a major new technology in the mid 90es, last century. Virtual Reality technology is currently used in a broad range of applications. The best known are games, movies, simulations, therapy. From a manufacturing standpoint, there are some attractive applications including training, education, collaborative work and learning. This book provides an up-to-date discussion of the current research in Virtual Reality and its applications. It describes the current Virtual Reality state-of-the-art and points out many areas where there is still work to be done. We have chosen certain areas to cover in this book, which we believe will have potential significant impact on Virtual Reality and its applications. This book provides a definitive resource for wide variety of people including academicians, designers, developers, educators, engineers, practitioners, researchers, and graduate students