953 resultados para computer user
Resumo:
Young males are over-represented in road crashes. Part of the problem is their proneness to boredom, a hardwired personality factor that can lead to risky driving. This paper presents a theoretical understanding of boredom in the driving context and demonstrates convincing arguments to investigate the role of boredom further. Specifically, this paper calls for the design of innovative technologies and applications that make safe driving more pleasurable and stimulating for young males, e.g., by applying gamification techniques. We propose two design concepts through the following questions: A. Can the simulation of risky driving reduce actual risky driving? B. Can the replacement of risky driving stimuli with alternative stimuli reduce risky driving? We argue that considering these questions in the future design of automotive user-interfaces and personal ubiquitous computing devices could effectively reduce risky driving behaviours among young males.
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In today’s world of information-driven society, many studies are exploring usefulness and ease of use of the technology. The research into personalizing next-generation user interface is also ever increasing. A better understanding of factors that influence users’ perception of web search engine performance would contribute in achieving this. This study measures and examines how users’ perceived level of prior knowledge and experience influence their perceived level of satisfaction of using the web search engines, and how their perceived level of satisfaction affects their perceived intention to reuse the system. 50 participants from an Australian university participated in the current study, where they performed three search tasks and completed survey questionnaires. A research model was constructed to test the proposed hypotheses. Correlation and regression analyses results indicated a significant correlation between (1) users’ prior level of experience and their perceived level of satisfaction in using the web search engines, and (2) their perceived level of satisfaction in using the systems and their perceived intention to reuse the systems. A theoretical model is proposed to illustrate the causal relationships. The implications and limitations of the study are also discussed.
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Maintenance decisions for large-scale asset systems are often beyond an asset manager's capacity to handle. The presence of a number of possibly conflicting decision criteria, the large number of possible maintenance policies, and the reality of budget constraints often produce complex problems, where the underlying trade-offs are not apparent to the asset manager. This paper presents the decision support tool "JOB" (Justification and Optimisation of Budgets), which has been designed to help asset managers of large systems assess, select, interpret and optimise the effects of their maintenance policies in the presence of limited budgets. This decision support capability is realized through an efficient, scalable backtracking- based algorithm for the optimisation of maintenance policies, while enabling the user to view a number of solutions near this optimum and explore tradeoffs with other decision criteria. To assist the asset manager in selecting between various policies, JOB also provides the capability of Multiple Criteria Decision Making. In this paper, the JOB tool is presented and its applicability for the maintenance of a complex power plant system.
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Secure protocols for password-based user authentication are well-studied in the cryptographic literature but have failed to see wide-spread adoption on the Internet; most proposals to date require extensive modifications to the Transport Layer Security (TLS) protocol, making deployment challenging. Recently, a few modular designs have been proposed in which a cryptographically secure password-based mutual authentication protocol is run inside a confidential (but not necessarily authenticated) channel such as TLS; the password protocol is bound to the established channel to prevent active attacks. Such protocols are useful in practice for a variety of reasons: security no longer relies on users' ability to validate server certificates and can potentially be implemented with no modifications to the secure channel protocol library. We provide a systematic study of such authentication protocols. Building on recent advances in modelling TLS, we give a formal definition of the intended security goal, which we call password-authenticated and confidential channel establishment (PACCE). We show generically that combining a secure channel protocol, such as TLS, with a password authentication protocol, where the two protocols are bound together using either the transcript of the secure channel's handshake or the server's certificate, results in a secure PACCE protocol. Our prototype based on TLS is available as a cross-platform client-side Firefox browser extension and a server-side web application which can easily be installed on deployed web browsers and servers.
Resumo:
Collisions between different types of road users at intersections form a substantial component of the road toll. This paper presents an analysis of driver, cyclist, motorcyclist and pedestrian behaviour at intersections that involved the application of an integrated suite of ergonomics methods, the Event Analysis of Systemic Teamwork (EAST) framework, to on-road study data. EAST was used to analyse behaviour at three intersections using data derived from an on-road study of driver, cyclist, motorcyclist and pedestrian behaviour. The analysis shows the differences in behaviour and cognition across the different road user groups and pinpoints instances where this may be creating conflicts between different road users. The role of intersection design in creating these differences in behaviour and resulting conflicts is discussed. It is concluded that currently intersections are not designed in a way that supports behaviour across the four forms of road user studied. Interventions designed to improve intersection safety are discussed.
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Reputation systems are employed to provide users with advice on the quality of items on the Web, based on the aggregated value of user-based ratings. Recommender systems are used online to suggest items to users according to the users, expressed preferences. Yet, recommender systems will endorse an item regardless of its reputation value. In this paper, we report the incorporation of reputation models into recommender systems to enhance the accuracy of recommendations. The proposed method separates the implementation of recommender and reputation systems for generality. Our experiment showed that the proposed method could enhance the accuracy of existing recommender systems.
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University orientation is a key event for new students that aids in the transition from a school to a university environment. A smartphone orientation application was built to aid students attending the event. Achievements were added to the application in an attempt to engage students further with the orientation activities and application. An exploratory field study was undertaken to evaluate the effect of the achievement system on participants attending orientation. Forty-six new students were recruited to test the orientation application. Twenty-six participants used a gamified version of the orientation application and twenty participants used a non-gamified version. While the gamification was generally well received, no impact on user experience was evident. Some effect on engagement with orientation activities was shown. Participants who used the gamified system reported the game elements as fun, but some negative issues arose, such as cheating.
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Domestic food wastage is a growing problem for the environment and food security. Some causes of domestic food wastes are attributed to a consumer’s behaviours during food purchasing, storage and consumption, such as: excessive food purchases and stockpiling in storage. Recent efforts in human-computer interaction research have examined ways of influencing consumer behaviour. The outcomes have led to a number of interventions that assist users with performing everyday tasks. The Internet Fridge is an example of such an intervention. However, new pioneering technologies frequently confront barriers that restrict their future impact in the market place, which has prompted investigations into the effectiveness of behaviour changing interventions used to encourage more sustainable practices. In this paper, we investigate and compare the effectiveness of two interventions that encourage behaviour change: FridgeCam and the Colour Code Project. We use FridgeCam to examine how improving a consumer’s food supply knowledge can reduce food stockpiling. We use the Colour Code Project to examine how improving consumer awareness of food location can encourage consumption of forgotten foods. We explore opportunities to integrate these interventions into commercially available technologies, such as the Internet Fridge, to: (i) increase the technology’s benefit and value to users, and (ii) promote reduced domestic food wastage. We conclude that interventions improving consumer food supply and location knowledge can promote behaviours that reduce domestic food waste over a longer term. The implications of this research present new opportunities for existing and future technologies to play a key role in reducing domestic food waste.
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In this paper we describe CubIT, a multi-user presentation and collaboration system installed at the Queensland University of Technology’s (QUT) Cube facility. The ‘Cube’ is an interactive visualisation facility made up of five very large-scale interactive multi-panel wall displays, each consisting of up to twelve 55-inch multi-touch screens (48 screens in total) and massive projected display screens situated above the display panels. The paper outlines the unique design challenges, features, implementation and evaluation of CubIT. The system was built to make the Cube facility accessible to QUT’s academic and student population. CubIT enables users to easily upload and share their own media content, and allows multiple users to simultaneously interact with the Cube’s wall displays. The features of CubIT were implemented via three user interfaces, a multi-touch interface working on the wall displays, a mobile phone and tablet application and a web-based content management system. Each of these interfaces plays a different role and offers different interaction mechanisms. Together they support a wide range of collaborative features including multi-user shared workspaces, drag and drop upload and sharing between users, session management and dynamic state control between different parts of the system. The results of our evaluation study showed that CubIT was successfully used for a variety of tasks, and highlighted challenges with regards to user expectations regarding functionality as well as issues arising from public use.
Resumo:
As a Lecturer of Animation History and 3D Computer Animator, I received a copy of Moving Innovation: A History of Computer Animation by Tom Sito with an element of anticipation in the hope that this text would clarify the complex evolution of Computer Graphics (CG). Tom Sito did not disappoint, as this text weaves together the multiple development streams and convergent technologies and techniques throughout history that would ultimately result in modern CG. Universities now have students who have never known a world without computer animation and many students are younger than the first 3D CG animated feature film, Toy Story (1996); this text is ideal for teaching computer animation history and, as I would argue, it also provides a model for engaging young students in the study of animation history in general. This is because Sito places the development of computer animation within the context of its pre-digital ancestry and throughout the text he continues to link the discussion to the broader history of animation, its pioneers, technologies and techniques...
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Process modelling is an integral part of any process industry. Several sugar factory models have been developed over the years to simulate the unit operations. An enhanced and comprehensive milling process simulation model has been developed to analyse the performance of the milling train and to assess the impact of changes and advanced control options for improved operational efficiency. The developed model is incorporated in a proprietary software package ‘SysCAD’. As an example, the milling process model has been used to predict a significant loss of extraction by returning the cush from the juice screen before #3 mill instead of before #2 mill as is more commonly done. Further work is being undertaken to more accurately model extraction processes in a milling train, to examine extraction issues dynamically and to integrate the model into a whole factory model.
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In a tag-based recommender system, the multi-dimensional <user, item, tag> correlation should be modeled effectively for finding quality recommendations. Recently, few researchers have used tensor models in recommendation to represent and analyze latent relationships inherent in multi-dimensions data. A common approach is to build the tensor model, decompose it and, then, directly use the reconstructed tensor to generate the recommendation based on the maximum values of tensor elements. In order to improve the accuracy and scalability, we propose an implementation of the -mode block-striped (matrix) product for scalable tensor reconstruction and probabilistically ranking the candidate items generated from the reconstructed tensor. With testing on real-world datasets, we demonstrate that the proposed method outperforms the benchmarking methods in terms of recommendation accuracy and scalability.
A tag-based personalized item recommendation system using tensor modeling and topic model approaches
Resumo:
This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment <user, item, tag>, should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.
Resumo:
The Urban Informatics Research Lab brings together a group of people who focus their research on interdisciplinary topics at the intersection of social, spatial, and technical research domains—that is, people, place, and technology. Those topics are spread across the breadth of urban life—its contemporary issues and its needs, as well as the design opportunities that we have as individuals, groups, communities, and as a whole society. The lab’s current research areas include urban planning and design, civic innovation, mobility and transportation, education and connected learning, environmental sustainability, and food and urban agriculture. The common denominator of the lab’s approach is user-centered design research directed toward understanding, conceptualizing, developing, and evaluating sociotechnical practices as well as the opportunities afforded by innovative digital technology in urban environments.