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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

The design of public housing : Architects' intentions and users' reactions

Darke, J. January 1982 (has links)
No description available.
2

Image enhancement for improving visibility and feature recognition

Zubair, Juwairia 10 October 2008 (has links)
Researchers analyze images in areas such as geology, bat cardiovascular systems and art studies to verify their observations. Some images are hard to study as their details are not vivid; hence there is a need to enhance these images to facilitate their study while preserving their contents. This study is aimed at assisting the researchers in the Cardiovascular Systems Dynamic Laboratory at Texas A&M University by evaluating the importance of Image Enhancement (IE) for improving visibility of features. For this study the images were collected and manipulated using various IE techniques and were shown to the novice researchers who were asked to perform three different tasks. These tasks were representative of the research work conducted in the lab. The techniques that were selected aimed at reducing the problems that are usually associated with data obtained from microscopic feeds. A customized application was developed to expedite and automate the study. The results indicated that the researchers did not immmensely benefit from the improved visualization for easy tasks. However, their performance improved for tasks that required more practice and skill. Our approach contributes towards designing an effective training program for novice researchers in the lab. Moreover, it is promising for similar research in different fields of study.
3

Privacy and Security Attitudes, Beliefs and Behaviours: Informing Future Tool Design

Weber, Janna-Lynn 24 August 2010 (has links)
Usable privacy and security has become a significant area of interest for many people in both industry and academia. A better understanding of the knowledge and motivation is an important factor in the design of privacy and security tools. However, users of these tools are a heterogeneous group, and many past studies of user characteristics in the security and privacy domain have looked only at a small subset of factors to define differences between groups of users. The goal of this research is to critically look at the difference between people, their opinions and habits when it comes to issues of privacy and security. To address this goal, 32 in-depth qualitative interviews were conducted and analyzed to look at the heterogenous nature of this community. The participant’s attitudes and actions around the dimensions of knowledge about tools and of motivation for self-protection were used to cluster participants. The traits of these participant clusters are used to create a set of privacy and security personas, or prototypical privacy and security tool users. These personas are a tool for incorporating a broader understanding of the diversity of users into the design of privacy and security tools.
4

FlexView: An Evaluation of Depth Navigation on Deformable Mobile Devices

Burstyn, JESSE 10 September 2012 (has links)
Mobile devices are frequently used to view rich content while on the go. However, they have a tradeoff between increased screen size and portability; mobile devices, by definition, are constrained to a fraction of a desktop computer’s display area. This constraint means a user has to frequently navigate to content that lies outside the display. We present FlexView, a prototype system and set of interaction techniques, which allows users to navigate through depth-arranged large information spaces using display curvature as an additional input channel. FlexView augments the planar (X-Y) navigation currently performed by touch input with two forms of bend input to navigate through depth (Z). With leafing, the user holds one side of display and bends the opposite side. Squeezing involves gripping the display in one hand and applying pressure on both sides to create concave or convex curvatures, and supports concurrent interaction with touch input. We performed two evaluations to investigate the performance of FlexView’s interaction techniques. In Experiment 1, we measured the efficiency of participants when searching through pages of a document, and compared touch input to squeezing and leafing used in isolation. Experiment 2 introduced X-Y navigation in a pan-and-zoom pointing task where multi-touch pinch gestures were compared against squeezing and leafing for zoom operations. Panning, across all conditions, was performed with touch input using the index finger. Our experiments demonstrated that touch and bend interactions are comparable for navigation through depth-arranged content, and squeezing to zoom recorded the fastest times in the pan-and-zoom pointing task. Overall, FlexView allows users to easily browse depth-arranged information spaces without sacrificing traditional touch interactions. / Thesis (Master, Computing) -- Queen's University, 2012-09-10 13:28:18.984
5

Privacy and Security Attitudes, Beliefs and Behaviours: Informing Future Tool Design

Weber, Janna-Lynn 24 August 2010 (has links)
Usable privacy and security has become a significant area of interest for many people in both industry and academia. A better understanding of the knowledge and motivation is an important factor in the design of privacy and security tools. However, users of these tools are a heterogeneous group, and many past studies of user characteristics in the security and privacy domain have looked only at a small subset of factors to define differences between groups of users. The goal of this research is to critically look at the difference between people, their opinions and habits when it comes to issues of privacy and security. To address this goal, 32 in-depth qualitative interviews were conducted and analyzed to look at the heterogenous nature of this community. The participant’s attitudes and actions around the dimensions of knowledge about tools and of motivation for self-protection were used to cluster participants. The traits of these participant clusters are used to create a set of privacy and security personas, or prototypical privacy and security tool users. These personas are a tool for incorporating a broader understanding of the diversity of users into the design of privacy and security tools.
6

Personal Email Spam Filtering with Minimal User Interaction

Mojdeh, Mona January 2012 (has links)
This thesis investigates ways to reduce or eliminate the necessity of user input to learning-based personal email spam filters. Personal spam filters have been shown in previous studies to yield superior effectiveness, at the cost of requiring extensive user training which may be burdensome or impossible. This work describes new approaches to solve the problem of building a personal spam filter that requires minimal user feedback. An initial study investigates how well a personal filter can learn from different sources of data, as opposed to user’s messages. Our initial studies show that inter-user training yields substantially inferior results to intra-user training using the best known methods. Moreover, contrary to previous literature, it is found that transfer learning degrades the performance of spam filters when the source of training and test sets belong to two different users or different times. We also adapt and modify a graph-based semi-supervising learning algorithm to build a filter that can classify an entire inbox trained on twenty or fewer user judgments. Our experiments show that this approach compares well with previous techniques when trained on as few as two training examples. We also present the toolkit we developed to perform privacy-preserving user studies on spam filters. This toolkit allows researchers to evaluate any spam filter that conforms to a standard interface defined by TREC, on real users’ email boxes. Researchers have access only to the TREC-style result file, and not to any content of a user’s email stream. To eliminate the necessity of feedback from the user, we build a personal autonomous filter that learns exclusively on the result of a global spam filter. Our laboratory experiments show that learning filters with no user input can substantially improve the results of open-source and industry-leading commercial filters that employ no user-specific training. We use our toolkit to validate the performance of the autonomous filter in a user study.
7

Personal Email Spam Filtering with Minimal User Interaction

Mojdeh, Mona January 2012 (has links)
This thesis investigates ways to reduce or eliminate the necessity of user input to learning-based personal email spam filters. Personal spam filters have been shown in previous studies to yield superior effectiveness, at the cost of requiring extensive user training which may be burdensome or impossible. This work describes new approaches to solve the problem of building a personal spam filter that requires minimal user feedback. An initial study investigates how well a personal filter can learn from different sources of data, as opposed to user’s messages. Our initial studies show that inter-user training yields substantially inferior results to intra-user training using the best known methods. Moreover, contrary to previous literature, it is found that transfer learning degrades the performance of spam filters when the source of training and test sets belong to two different users or different times. We also adapt and modify a graph-based semi-supervising learning algorithm to build a filter that can classify an entire inbox trained on twenty or fewer user judgments. Our experiments show that this approach compares well with previous techniques when trained on as few as two training examples. We also present the toolkit we developed to perform privacy-preserving user studies on spam filters. This toolkit allows researchers to evaluate any spam filter that conforms to a standard interface defined by TREC, on real users’ email boxes. Researchers have access only to the TREC-style result file, and not to any content of a user’s email stream. To eliminate the necessity of feedback from the user, we build a personal autonomous filter that learns exclusively on the result of a global spam filter. Our laboratory experiments show that learning filters with no user input can substantially improve the results of open-source and industry-leading commercial filters that employ no user-specific training. We use our toolkit to validate the performance of the autonomous filter in a user study.
8

Large display interaction via multiple acceleration curves on a touchpad

Esakia, Andrey 23 January 2014 (has links)
Large, high resolution displays combine high pixel density with ample physical dimensions. Combination of these two factors creates a multi-scale workspace where object targeting requires both high speed and high accuracy for nearby and far apart targeting. Modern operating systems support dynamic control-display gain adjustment (i.e. cursor acceleration) that helps to maintain both speed and accuracy. However, very large high resolution displays require broad range of control-display gain ratios. Current interaction techniques attempt to solve the problem by utilizing multiple modes of interaction, where different modes provide different levels of pointer precision. We are investigating the question of the value of allowing users to dynamically choose granularity levels for continuous pointing within single mode of interaction via multiple acceleration curves. Our solution offers different cursor acceleration curves depending on the targeting conditions, thus broadening the range of control-display ratios. Our approach utilizes a consumer multitouch touchpad that allows fast and accurate detection of multiple fingers. A user can choose three different acceleration curves based on how many fingers are used for cursor positioning. Our goal is to investigate the effects of such multi-scale interaction and to compare it against standard single curve interaction. / Master of Science
9

Clustered Layout Word Cloud for User Generated Online Reviews

Wang, Ji 20 November 2012 (has links)
User generated reviews, like those found on Yelp and Amazon, have become important reference material in casual decision making, like dining, shopping and entertainment. However, very large amounts of reviews make the review reading process time consuming. A text visualization can speed up the review reading process. In this thesis, we present the clustered layout word cloud -- a text visualization that quickens decision making based on user generated reviews. We used a natural language processing approach, called grammatical dependency parsing, to analyze user generated review content and create a semantic graph. A force-directed graph layout was applied to the graph to create the clustered layout word cloud. We conducted a two-task user study to compare the clustered layout word cloud to two alternative review reading techniques: random layout word cloud and normal block-text reviews. The results showed that the clustered layout word cloud offers faster task completion time and better user satisfaction than the other two alternative review reading techniques. [Permission email from J. Huang removed at his request. GMc March 11, 2014] / Master of Science
10

Using Describers to simplify ScriptEase

Desai, Neesha Unknown Date
No description available.

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