12045621
Visualization of the Interaction of Multiple Sclerosis Lesions with Adjacent White Matter Fibers Using Streamtubes and Streamsurfaces
Multiple sclerosis (MS) is a chronic disease of the central nervous system that predominantly affects young adults during their most productive years. Pathologically, MS is characterized by the presence of areas of demyelination and T-cell predominant perivascular inflammation in the brain white matter. In order to study the effect of MS lesion on the white matter, we acquire diffusion tensor imaging (DTI) data on MS patients and employ streamtubes and streamsurfaces to visualize the DTI data. We also register structural data sets with DTI data sets and generate isosurfaces of the MS lesions and the ventricles. The simultaneous visualization of all the models has the potential to elucidate the complex relationship between the MS lesions, the white matter neural fibers and the affected gray matter regions.
11872886
Software visualization
From the Publisher: 
In the past decade, high-quality interfaces have become standard in a growing number of areas such as games and CD-ROM-based encyclopedias. Yet the overwhelming majority of programmers edit their code using a single font within a single window and view code execution via the hand insertion of print statements. Software Visualization (SV) redresses this imbalance by using typography, graphics, and animation techniques to show program code, data, and control flow. This book describes the history of SV, techniques and frameworks for its construction, its use in education and program debugging, and recent attempts to evaluate its effectiveness. In making programming a multimedia experience, SV leaves programmers and computer science researchers free to explore more interesting issues and to tackle more challenging problems.
9641916
Investigating the Relationship between Internet Privacy Concerns and Online Purchase Behavior
Many organizations now emphasize the use of technology that can help them get closer to consumers and build ongoing relationships with them. The ability to compile consumer data profiles has been made even easier with Internet technology. However, it is often assumed that consumers like to believe they can trust a company with their personal details. Lack of trust may cause consumers to have privacy concerns. Addressing such privacy concerns may therefore be crucial to creating stable and ultimately profitable customer relationships. Three specific privacy concerns that have been frequently identified as being of importance to consumers include unauthorized secondary use of data, invasion of privacy, and errors. Results of a survey study indicate that both errors and invasion of privacy have a significant inverse relationship with online purchase behavior. Unauthorized use of secondary data appears to have little impact. Managerial implications include the careful selection of communication channels for maximum impact, the maintenance of discrete “permission-based” contact with consumers, and accurate recording and handling of data.
12258232
Building IT Competence in Line Management: Investigation of a Best Practice
RESEARCH QUESTION During a prior research study, the first author interviewed the Vice President of IS for Common ]nsurance Group, one of the largest life insurance companies in Canada. She learned that the company had transferred more than forty information systems (IS) people into various management jobs throughout its insurance divisions during the twelve years from 1980 to 1992. Permission to conduct an in-depth study of this unusual IS-to-line project was granted to the researchers in 1993. Our interest in investigating this org ization was to find answers to three questions: 1. What organizational factors (e.g., structures, incentives, training) made it possible for Common Insurance Group to move IS maimgers into line positions with regularity for over a decade? 2. What individual factors affected the ease with which these IS-trained people made the transition into line positions? 3. Within Common Insurance Group, what are the results of having many business unit managers with extensive IS experience? RESEARCH DESIGN The study will investigate the research questions at two levels, organizational and individual. There are three stages in the research: 1) initial interviews with ex-IS managers, 2) a matched survey of non-IS managers, ex-IS managers and current IS managers, and 3) follow-up interviews with selected managers. Our exploratory research model suggests that Organizational Factors, Individual Factors, Job-Related Factors and Transition Factors influence the movement of an IS manager to a line management job. Further, movement of IS people into the line will have both organizational and individual results. SUMMARY Our hope is that, at the end of this research project, we will understand clearly how Common Insurance Group accomplished a very uncommon feat. The revised model will create a solid foundation for further research and the set of anec(total cases will assist other organizations in creating programs to increase IT competence in their line areas.
205912556
Visualization in Scientific Computing
Publisher Summary Computational science and engineering (CSE it enables them to analyze the data to uncover new information. Computational scientists rely upon a host of high-volume data sources in order to conduct their research. However, they are deluged by the flood of data generated. Using an exclusively numerical format, the human brain cannot interpret gigabytes of data each day, so much information now goes to waste. It is impossible for users to ever quantitatively examine more than a tiny fraction of the solution; that is, it is impossible to investigate the qualitative global nature of numeric solutions. Therefore, the ability to visualize complex computations and simulations is absolutely essential to ensure the integrity of analyses, to provoke insights, and to communicate those insights with others. The chapter focuses on visualization. It is a method of computing that gives visual form to complex data. The growing importance of CS&E, especially with supercomputer capabilities, is creating a commensurate need for more sophisticated visual representations of natural phenomena across time. This requires the development of new tool sets for image generation, visual communication, and analysis. The chapter discusses examples of scientific-visualization for facilitating CS&E research specifically in the fields of planetary sciences, molecular modeling, mathematics, and medical Imaging. The chapter also highlights the current limitations and bottlenecks in visualization technology, focusing on software limitations, data management limitation, hardware limitations, educational limitations, and communication and publication limitation.
37732410
User Identification via Keystroke Characteristics of Typed Names using Neural Networks
Abstract A method for identifying computer users by analysing keystroking patterns with neural networks and a simple geometric distance is presented. A model of each user's normal typing style was created and compared with later typing samples. Preliminary results demonstrate complete exclusion of imposters and a reasonably low false alarm rate when the sample text was limited to the user's name.
14196251
Unsupervised 3D object recognition and reconstruction in unordered datasets
This paper presents a system for fully automatic recognition and reconstruction of 3D objects in image databases. We pose the object recognition problem as one of finding consistent matches between all images, subject to the constraint that the images were taken from a perspective camera. We assume that the objects or scenes are rigid. For each image, we associate a camera matrix, which is parameterised by rotation, translation and focal length. We use invariant local features to find matches between all images, and the RANSAC algorithm to find those that are consistent with the fundamental matrix. Objects are recognised as subsets of matching images. We then solve for the structure and motion of each object, using a sparse bundle adjustment algorithm. Our results demonstrate that it is possible to recognise and reconstruct 3D objects from an unordered image database with no user input at all.