911 resultados para 1145


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Security indicators in web browsers alert users to the presence of a secure connection between their computer and a web server; many studies have shown that such indicators are largely ignored by users in general. In other areas of computer security, research has shown that technical expertise can decrease user susceptibility to attacks. In this work, we examine whether computer or security expertise affects use of web browser security indicators. Our study takes place in the context of web-based single sign-on, in which a user can use credentials from a single identity provider to login to many relying websites; single sign-on is a more complex, and hence more difficult, security task for users. In our study, we used eye trackers and surveyed participants to examine the cues individuals use and those they report using, respectively. Our results show that users with security expertise are more likely to self-report looking at security indicators, and eye-tracking data shows they have longer gaze duration at security indicators than those without security expertise. However, computer expertise alone is not correlated with recorded use of security indicators. In survey questions, neither experts nor novices demonstrate a good understanding of the security consequences of web-based single sign-on.

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The act of computer programming is generally considered to be temporally removed from a computer program’s execution. In this paper we discuss the idea of programming as an activity that takes place within the temporal bounds of a real-time computational process and its interactions with the physical world. We ground these ideas within the context of livecoding – a live audiovisual performance practice. We then describe how the development of the programming environment “Impromptu” has addressed our ideas of programming with time and the notion of the programmer as an agent in a cyber-physical system.

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Deciding the appropriate population size and number of is- lands for distributed island-model genetic algorithms is often critical to the algorithm’s success. This paper outlines a method that automatically searches for good combinations of island population sizes and the number of islands. The method is based on a race between competing parameter sets, and collaborative seeding of new parameter sets. This method is applicable to any problem, and makes distributed genetic algorithms easier to use by reducing the number of user-set parameters. The experimental results show that the proposed method robustly and reliably finds population and islands settings that are comparable to those found with traditional trial-and-error approaches.

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Distributed Genetic Algorithms (DGAs) designed for the Internet have to take its high communication cost into consideration. For island model GAs, the migration topology has a major impact on DGA performance. This paper describes and evaluates an adaptive migration topology optimizer that keeps the communication load low while maintaining high solution quality. Experiments on benchmark problems show that the optimized topology outperforms static or random topologies of the same degree of connectivity. The applicability of the method on real-world problems is demonstrated on a hard optimization problem in VLSI design.

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The convergence of locative and social media with collaborative interfaces and data visualisation has expanded the potential of online information provision. Offering new ways for communities to share contextually specific information, it presents the opportunity to expand social media’s current focus on micro self-publishing with applications that support communities to actively address areas of local need. This paper details the design and development of a prototype application that illustrates this potential. Entitled PetSearch, it was designed in collaboration with the Animal Welfare League of Queensland to support communities to map and locate lost, found and injured pets, and to build community engagement in animal welfare issues. We argue that, while established approaches to social and locative media provide a useful foundation for designing applications to harness social capital, they must be re-envisaged if they are to effectively facilitate community collaboration. We conclude by arguing that the principles of user engagement and co-operation employed in this project can be extrapolated to other online approaches that aim to facilitate co-operative problem solving for social benefit.

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Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. One of the most popular web personalization systems is recommender systems. In recommender systems choosing user information that can be used to profile users is very crucial for user profiling. In Web 2.0, one facility that can help users organize Web resources of their interest is user tagging systems. Exploring user tagging behavior provides a promising way for understanding users’ information needs since tags are given directly by users. However, free and relatively uncontrolled vocabulary makes the user self-defined tags lack of standardization and semantic ambiguity. Also, the relationships among tags need to be explored since there are rich relationships among tags which could provide valuable information for us to better understand users. In this paper, we propose a novel approach for learning tag ontology based on the widely used lexical database WordNet for capturing the semantics and the structural relationships of tags. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users’ tagging behavior together. To personalize further, clustering of users is performed to generate a more accurate ontology for a particular group of users. In order to evaluate the usefulness of the tag ontology, we use the tag ontology in a pilot tag recommendation experiment for improving the recommendation performance by exploiting the semantic information in the tag ontology. The initial result shows that the personalized information has improved the accuracy of the tag recommendation.

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In this study, we explore the design and evaluation of a mobile online discussion system for motivating students to share their learning experiences. The system supports interaction with peers and academic staff anytime and anywhere using mobile devices. The application introduces a set of features that enables customisation for different purposes. This paper describes the application and explains the motivation for developing the application. We describe the methods and results of a case study that explores usage of the application among a small group of localised participants. Finally, we discuss the implications of this work and outline future areas of research and development.

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Mobile devices are becoming indispensable personal assistants in people's daily life as these devices support work, study, play and socializing activities. The multi-modal sensors and rich features of smartphones can capture abundant information about users' life experience, such as taking photos or videos on what they see and hear, and organizing their tasks and activities using calendar, to-do lists, and notes. Such vast information can become useful to help users recalling episodic memories and reminisce about meaningful experiences. In this paper, we propose to apply autobiographical memory framework to provide an effective mechanism to structure mobile life-log data. The proposed model is an attempt towards a more complete personal life-log indexing model, which will support long term capture, organization, and retrieval. To demonstrate the benefits of the proposed model, we propose some design solutions for enabling users-driven capture, annotation, and retrieval of autobiographical multimedia chronicles tools.

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Binge drinking is an important issue in Australia and worldwide. Existing studies have shown that mobile tools provide an effective method to self-monitor drink sessions, whereas social tool such as Facebook, can be used to construct social drinker identity (thus normalizing binge drinking), but if used among a peer-support that promotes the importance of responsible drinking, it potentially can be effective in moderating alcohol consumption. To combine mobile and social tool approaches, the study involves two complementary and largely qualitative studies to inform a novel design of an engaging mobile social tool for supporting responsible drinking among young women: (1) a survey of literature and mobile tools on alcohol related studies and interventions; (2) an in-depth focus group interview among young women aged 18 to 24. The results and discussions provide some valuable insights for future research and development in the field.

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The use of material artefacts within the design process is a long-standing and continuing characteristic of interaction design. Established methods, such as prototyping, which have been widely adopted by educators and practitioners, are seeing renewed research interest and being reconsidered in light of the evolving needs of the field. Alongside this, the past decade has seen the introduction and adoption of a diverse range of novel design methods into interaction design, such as cultural probes, technology probes, context mapping, and provotypes.

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In this paper we introduce the idea of "social contraptions", which are interactive physical devices employed as designerly explorations of social relations as mediated by physical space and artefacts. We present two independent but related design explorations that were situated in fine art and industrial research contexts. We argue that these contraptions open up for exploration some interaction issues related to the theme of ’Embodied Facilitation'. This is particularly in relation to awareness and coordination between interactants as mediated by the spatial and material configuration of the contraptions. These methods, as well as the insights gained from them can contribute to the development of the emerging field of embodied interaction.

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We investigated the collaboration of ten doctor-nurse pairs with a prototype digital telehealth stethoscope. Doctors could see and hear the patient but could not touch them or the stethoscope. The nurse in each pair controlled the stethoscope. For ethical reasons, an experimenter stood in for a patient. Each of the ten interactions was video recorded and analysed to understand the interaction and collaboration between the doctor and nurse. The video recordings were coded and transformed into maps of interaction that were analysed for patterns of activity. The analysis showed that as doctors and nurses became more experienced at using the telehealth stethoscope their collaboration was more effective. The main measure of effectiveness was the number of corrections in stethoscope placement required by the doctor. In early collaborations, the doctors gave many corrections. After several trials, each doctor and nurse had reduced corrections and all pairs reduced their corrections. The significance of this research is the identification of the qualities of effective collaboration in the use of the telehealth stethoscope and telehealth systems more generally.

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With increasing demands on our time, everyday behaviors such as food purchasing, preparation, and consumption have become habitual and unconscious. Indeed, modern food values are focused on conve- nience and effortlessness, overshad- owing other values such as environ- mental sustainability, health, and pleasure. The rethinking of how we approach everyday food behaviors appears to be a particularly timely concern. In this special section, we explore work carried out and dis- cussed during the recent workshop “Food for Thought: Designing for Critical Reflection on Food Practices,” at the 2012 Designing Interactive Systems Conference in Newcastle upon Tyne, U.K.

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This paper illustrates a field research performed with a team of experts involved in the evaluation of Trippple, a system aimed at supporting the different phases of a tourist trip, in order to provide feedback and insights, both on the functionalities already implemented (that at the time of evaluation were available only as early and very unstable prototypes), and on the functionalities still to be implemented. We show how the involvement of professionals helped to focus on challenging aspects, instead of less important, cosmetic, issues and resulted profitable in terms of early feedback, issues spotted, and improvements suggested

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This paper presents a graph-based method to weight medical concepts in documents for the purposes of information retrieval. Medical concepts are extracted from free-text documents using a state-of-the-art technique that maps n-grams to concepts from the SNOMED CT medical ontology. In our graph-based concept representation, concepts are vertices in a graph built from a document, edges represent associations between concepts. This representation naturally captures dependencies between concepts, an important requirement for interpreting medical text, and a feature lacking in bag-of-words representations. We apply existing graph-based term weighting methods to weight medical concepts. Using concepts rather than terms addresses vocabulary mismatch as well as encapsulates terms belonging to a single medical entity into a single concept. In addition, we further extend previous graph-based approaches by injecting domain knowledge that estimates the importance of a concept within the global medical domain. Retrieval experiments on the TREC Medical Records collection show our method outperforms both term and concept baselines. More generally, this work provides a means of integrating background knowledge contained in medical ontologies into data-driven information retrieval approaches.