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Large display interaction via multiple acceleration curves on a touchpadEsakia, 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
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Increasing Selection Accuracy and Speed through Progressive RefinementBacim de Araujo e Silva, Felipe 21 July 2015 (has links)
Although many selection techniques have been proposed and developed over the years, selection by pointing is perhaps the most popular approach for selection. In 3D interfaces, the laser-pointer metaphor is commonly used, since users only have to point to their target from a distance. However, the task of selecting objects that have a small visible area or that are in highly cluttered environments is hard when using pointing techniques. With both indirect and direct pointing techniques in 3D interfaces, smaller targets require higher levels of pointing precision from the user. In addition, issues such as target occlusion as well as hand and tracker jitter negatively affect user performance. Therefore, requiring the user to perform selection in a single precise step may result in users spending more time to select targets so that they can be more accurate (effect known as the speed-accuracy trade-off).
We describe an approach to address this issue, called Progressive Refinement. Instead of performing a single precise selection, users gradually reduce the set of selectable objects to reduce the required precision of the task. This approach, however, has an inherent trade-off when compared to immediate selection techniques. Progressive refinement requires a gradual process of selection, often using multiple steps, although each step can be fast, accurate, and nearly effortless. Immediate techniques, on the other hand, involve a single-step selection that requires effort and may be slower and more error-prone. Therefore, the goal of this work was to explore this trade-off. The research includes the design and evaluation of progressive refinement techniques for 3D interfaces, using both pointing- and gesture-based interfaces for single-object selection and volume selection.
Our technique designs and other existing selection techniques that can be classified as progressive refinement were used to create a design space. We designed eight progressive refinement techniques and compared them to the most commonly used techniques (for a baseline comparison) and to other state-of-the-art selection techniques in a total of four empirical studies. Based on the results of the studies, we developed a set of design guidelines that will help other researchers design and use progressive refinement techniques. / Ph. D.
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Multi-Model Semantic Interaction for Scalable Text AnalyticsBradel, Lauren C. 28 May 2015 (has links)
Learning from text data often involves a loop of tasks that iterate between foraging for information and synthesizing it in incremental hypotheses. Past research has shown the advantages of using spatial workspaces as a means for synthesizing information through externalizing hypotheses and creating spatial schemas. However, spatializing the entirety of datasets becomes prohibitive as the number of documents available to the analysts grows, particularly when only a small subset are relevant to the tasks at hand. To address this issue, we developed the multi-model semantic interaction (MSI) technique, which leverages user interactions to aid in the display layout (as was seen in previous semantic interaction work), forage for new, relevant documents as implied by the interactions, and then place them in context of the user's existing spatial layout. This results in the ability for the user to conduct both implicit queries and traditional explicit searches. A comparative user study of StarSPIRE discovered that while adding implicit querying did not impact the quality of the foraging, it enabled users to 1) synthesize more information than users with only explicit querying, 2) externalize more hypotheses, 3) complete more synthesis-related semantic interactions. Also, 18% of relevant documents were found by implicitly generated queries when given the option. StarSPIRE has also been integrated with web-based search engines, allowing users to work across vastly different levels of data scale to complete exploratory data analysis tasks (e.g. literature review, investigative journalism).
The core contribution of this work is multi-model semantic interaction (MSI) for usable big data analytics. This work has expanded the understanding of how user interactions can be interpreted and mapped to underlying models to steer multiple algorithms simultaneously and at varying levels of data scale. This is represented in an extendable multi-model semantic interaction pipeline. The lessons learned from this dissertation work can be applied to other visual analytics systems, promoting direct manipulation of the data in context of the visualization rather than tweaking algorithmic parameters and creating usable and intuitive interfaces for big data analytics. / Ph. D.
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Technology for fast-tracking high-risk head and neck cancer referrals: Co-designing with patientsOdo, Chinasa, Albutt, A., Hardman, J., Patterson, J., McVey, Lynn, Rousseau, N., Paleri, V., Randell, Rebecca 23 September 2024 (has links)
Yes / Background: Head and Neck Cancer (HNC) is the eighth most prevalent global cancer. Timely recognition of
symptoms is crucial for reducing mortality rates. The EVolution of a patiEnt-REported symptom-based risk
stratification sySTem to redesign the suspected Head and Neck cancer referral pathway (EVEREST-HN) study
aims to develop and evaluate a risk stratification tool using patient reported symptoms, which will be populated
remotely in the community before the patient is seen by the clinician to hasten HNC diagnosis. EVEREST-HN will
design a patient SYmptom iNput Clinical (SYNC) system to gather patient symptom data and calculate a risk
score to aid clinicians in identifying high-risk cases. This identification potentially allows for high-risk patients to
be seen sooner, thereby improving patient outcomes.
Methods: Three workshop sessions were conducted involving a total of 17 unique participants, with several
contributing to multiple sessions: nine in the co-design session, six in the validation session, and nine in the
evaluation session. The co-design session employed online collaboration with patients’ representatives. Thematic
analysis was used to identify requirements and concerns informing the development of a low-fidelity prototype.
The validation session assessed whether the prototype aligned with patient expectations. In the evaluation
session, participants interacted with an online prototype and provided further feedback.
Results: During the co-design workshop, participants emphasized the need for a concise and clear SYNC system
questionnaire for reporting suspected HNC symptoms. Concerns were raised about questionnaire length, language
clarity, and the inclusion of probing questions. Participants suggested concise questions using lay language,
incorporating visual aids for topics like alcohol and tobacco use, and making the sexual activity question
optional. Recommendations included diverse language options, hard copies for non-English speakers, and phone
call options for those uncomfortable with screen-based technology. The validation workshop confirmed that the
prototype reflected participants’ ideas. Feedback highlighted the need for call-back features to help those not
confident with technology and the need to present symptom questions first before social background questions.
Feedback from the evaluation demonstrated a commitment to efficiency, and continuous improvement.
Conclusion: This study aims to develop the SYNC system to enhance efficiency of suspected HNC referrals. The
workshops highlighted the importance of end-user inclusiveness in the system development life cycle, with
collaboration with stakeholders and repeated feedback, providing crucial insights for ensuring the SYNC system
effectively addresses the needs and concerns of patients in the context of HNC diagnosis. / This study is funded by the NIHR Programme Grants for Applied Research (NIHR202862).
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A user satisfaction study of the NHS Online Prescription Prepayment CertificateIrani, Zahir, Weerakkody, Vishanth J.P., Molnar, A., Lee, Habin, Hindi, N., Osman, I. 06 December 2014 (has links)
No / This research seeks to measure citizen satisfaction with the electronic Prescription Prepayment Certificate (PPC) offered by National Health Service (NHS) in the United Kingdom (UK). The paper reports on the findings of a survey of over 500 users of the NHS PPC service. Satisfaction is measured using the four dimensions from the COBRA framework (Osman et al. (2011) [1]) which comprise the cost, opportunity, benefits and risk assessment constructs. This is the first study to measure citizen satisfaction with the electronic PPC in the UK across these constructs. The results show that most citizens using the PPC electronic service are satisfied with this service and that the service meets their essential needs. The paper also presents the results of qualitative feedback obtained from the participants that can be used to determine the areas that need further improvement in the current electronic PPC service and potential influence on user satisfaction.
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Validity of interpretation: a user validity perspective beyond the test scoreMacIver, R., Anderson, Neil, Costa, Ana-Cristina, Evers, A. 2014 April 1923 (has links)
Yes / This paper introduces the concept of user validity and provides a new perspective on the validity of interpretations from tests. Test interpretation is based on outputs such as test scores, profiles, reports, spread-sheets of multiple candidates’ scores, etc. The user validity perspective focuses on the interpretations a test user makes given the purpose of the test and the information provided in the test output. This innovative perspective focuses on how user validity can be extended to content, criterion and to some extent construct-related validity. It provides a basis for researching the validity of interpretations and an improved understanding of the appropriateness of different approaches to score interpretation, as well as how to design test outputs and assessments which are pragmatic and optimal.
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Usability Engineering Applied to an Electromagnetic Modeling ToolFortson, Samuel King 19 July 2012 (has links)
There are very few software packages for model-building and visualization in electromagnetic geophysics, particularly when compared to other geophysical disciplines, such as seismology. The purpose of this thesis is to design, develop, and test a geophysical model-building interface that allows users to parameterize the 2D magnetotellurics problem. Through the evaluation of this interface, feedback was collected from a usability specialist and a group of geophysics graduate students to study the steps users take to work through the 2D forward-modeling problem, and to analyze usability errors encountered while working with the interface to gain a better understanding of how to build a more effective interface. Similar work has been conducted on interface design in other fields, such as medicine and consumer websites.
Usability Engineering is the application of a systematic set of methods to the design and development of software with the goal of making the software more learnable, easy to use, and accessible. Two different Usability Engineering techniques — Heuristic Evaluation and Thinking Aloud Protocol — were involved in the evaluation of the interface designed in this study (FEM2DGUI). Heuristic Evaluation is a usability inspection method that employs a usability specialist to detect errors based on a known set of guidelines and personal experience. Thinking Aloud Protocol is a usability evaluation method where potential end-users are observed as they verbalize their every step as they work through specific scenarios with an interface. These Usability Engineering methods were combined in a effort to understand how the first prototype of FEM2DGUI could be refined to make it more usable and to understand how end-users work through the forward-modeling problem.
The Usability Engineering methods employed in this project uncovered multiple usability errors that were corrected through a refinement of the interface. Discovery of these errors helped with refining the system to become more robust and usable, which is believed to aid users in more efficient model-building. Because geophysical model-building is inherently a difficult task, it is possible that other model-building graphical user interfaces could benefit from the application of Usability Engineering methods, such as those presented in this research.â / Master of Science
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Incorporating User Opinion into a New Wine Tourism Map for Southwest VirginiaPritchard, Katherine 31 January 2009 (has links)
Thematic tourist maps provide users with a tangible geographic route to their travel destinations and also may contain a wide variety of additional information to enhance traveler experiences. Unlike other types of maps that focus on accurate topographic representation of an area or on depiction of spatial data, tourist maps should be specifically constructed to appeal directly to the end-user. Toward that end, this research developed and implemented a model to incorporate user opinion on content, levels of detail, and labeling conventions during the process of designing and creating a wine tourism map for southwest Virginia. Over 700 (total) wine tourists completed brief questionnaires during five distinct phases of data collection and map modeling. At each point, we incorporated user input into map design for the preceding phase, and a final assessment surveyed tourist attitude of the finished product. Interestingly, surveys indicated a propensity for users to highly rank the idea of more and more detailed content data, as well as high levels of spatial detail, but when presented with the corresponding maps, they tended to favor a cleaner more simplified display. This finding underscores our conclusion that while user input is critical for developing successful tourist maps, cartographic training and skill is still required to achieve a quality product. Overall, the final map incorporating user input received overwhelmingly positive user reviews when compared to existing regional maps indicating that our iterative method of seeking user input at various stages of map development was successful, and facilitated creation of an improved product. / Master of Science
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Next-generation user authentication schemes for IoT applicationsGupta, Sandeep 27 October 2020 (has links)
The unprecedented rise of IoT has revolutionized every business vertical enthralling people to embrace IoT applications in their day-to-day lives to accrue multifaceted benefits. It is absolutely fair to say that a day without connected IoT systems, such as smart devices, smart enterprises, smart homes or offices, etc., would hamper our conveniences, drastically. Many IoT applications for these connected systems are safety-critical, and any unauthorized access could have severe consequences to their consumers and society.
In the overall IoT security spectrum, human-to-machine authentication for IoT applications is a critical and foremost challenge owing to highly prescriptive characteristics of conventional user authentication schemes, i.e., knowledge-based or token-based authentication schemes, currently used in them. Furthermore, studies have reported numerous users’ concerns, from both the security and usability perspectives, that users are facing in using available authentication schemes for IoT applications. Therefore, an impetus is required to upgrade user authentication schemes for new IoT age applications to address any unforeseen incidents or unintended consequences.
This dissertation aims at designing next-generation user authentication schemes for IoT applications to secure connected systems, namely, smart devices, smart enterprises, smart homes, or offices. To accomplish my research objectives, I perform a thorough study of ways and types of user authentication mechanisms emphasizing their security and usability ramifications. Subsequently, based on the substantive findings of my studies, I design, prototype, and validate our proposed user authentication schemes. I exploit both physiological and behavioral biometrics to design novel schemes that provide implicit (frictionless), continuous (active) or risk-based (non-static) authentication for multi-user scenarios. Afterward, I present a comparative analysis of the proposed schemes in terms of accuracy against the available state-of-the-art user authentication solutions. Also, I conduct SUS surveys to evaluate the usability of
user authentication schemes.
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Revitalizing eXeneHoag, Matthew January 1900 (has links)
Master of Science / Department of Computing and Information Sciences / Alley Stoughton / This thesis covers the process leading up to the release of eXene 2.0, a User Interface Management System (UIMS) toolkit. Since its inception, eXene has provided a unique way to create meaningful graphical user interfaces (GUIs) for Standard ML applications. Additionally, it has gone through several quality revisions which have both enhanced the toolkit and corrected many deficiencies that were present. Even with these improvements, however, the full potential of eXene has become increasingly difficult for developers to utilize. That is, in spite of the natural innovation that eXene brings to GUI construction, its current lack of extensibility, usability, and functionality has caused Standard ML developers to choose simpler, more familiar UIMS toolkits, despite their limitations, for the creation of their applications. In light of this fact, eXene needs an internal and cosmetic overhaul to extend its usage and appeal. First, to improve its extensibility, formerly weakened by organic growth, eXene requires some restructuring of its architecture. Second, to improve its overall usability, previously stifled by sparse documentation, eXene requires the implementation of an interactive electronic document for its API. Finally, to improve its functionality, several new multi-purpose widgets need to be introduced. It is the author's hypothesis that the revised structure, improved documentation, and additional multi-purpose widgets detailed in this thesis sufficiently elevate eXene's extensibility, usability, and functionality such that eXene can be considered a fully featured UIMS toolkit. With these changes and the release of eXene 2.0, eXene is more likely to be adopted as the primary UIMS toolkit for Standard ML developers.
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