924 resultados para GIS, Android, Mobile, User Experience, Java, offline, EBWorld


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This paper reports on a collaborative project between staff and students in the Department of Typography & Graphic Communication at the University of Reading The Partnerships in Learning and Teaching (PLanT) project here described is a direct response to student needs for better online support materials. Methodologically, the project embeds user-centred design principles within an iterative process of design development and participant research. This process has underpinned the development of a prototype for an online interface called Typo-Resource. The resulting initial prototype addresses the usability and user experience dimensions of an online learning resource, moving beyond providing tutor-identified sets of resources to a multifaceted, collaborative, and visual platform for peer learning.

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The chapter describes development of care bundle documentation, through an iterative, user-centred design process, to support the recognition and treatment of acute kidney injury (AKI). The chapter details stages of user and stakeholder consultation, employed to develop a design response that was sensitive to user experience and need, culminating in simulation testing of a near final prototype. The development of supplementary awareness-raising materials, relating to the main care bundle tool is also discussed. This information design response to a complex clinical decision-making process is contrasted to other approaches to promoting AKI care. The need for different but related approaches to the working tool itself and the tool’s communication are discussed. More general recommendations are made for the development of communication tools to support complex clinical processes.

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We introduce a flexible technique for interactive exploration of vector field data through classification derived from user-specified feature templates. Our method is founded on the observation that, while similar features within the vector field may be spatially disparate, they share similar neighborhood characteristics. Users generate feature-based visualizations by interactively highlighting well-accepted and domain specific representative feature points. Feature exploration begins with the computation of attributes that describe the neighborhood of each sample within the input vector field. Compilation of these attributes forms a representation of the vector field samples in the attribute space. We project the attribute points onto the canonical 2D plane to enable interactive exploration of the vector field using a painting interface. The projection encodes the similarities between vector field points within the distances computed between their associated attribute points. The proposed method is performed at interactive rates for enhanced user experience and is completely flexible as showcased by the simultaneous identification of diverse feature types.

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Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using Robust Extended Kalman Filter as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model. Through simulation, we show the accuracy and simplicity in implementation of our prediction algorithm.

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Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using robust extended Kalman filter (REKF) as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model and more effective in comparison with the standard Kalman filter.

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The vision of next generation networks (4G & beyond) is to make possible seamless mobility across heterogeneous networks and to support real-time multimedia services. This would require intra/inter-domain handovers and service reconfiguration procedures to be completed with minimum latency. Mobility Prediction has been identified as a key abettor to this goal. The increasing ease of coupling between the mobile user and the network requires that a mobility prediction scheme that is to be deployed in next generation networks be capable of high levels of prediction accuracy despite randomness in user movement. In this work we have presented a survey on mobility prediction schemes that have been proposed for wireless networks. The results of our simulation study focused on the robustness of different schemes to randomness in user movement are also presented.

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In wireless mobile computing, location management is introduced whenever users move from one place to another. In order to track a mobile user, the system must store information about their current location and report new locations to a home base station. Numerous techniques have been proposed to optimally manage the location of mobile hosts in mobile networks. This paper attempts to present a more structured and comprehensive analysis of the current location management techniques architectures and their technology enablers. We discuss some of the principal issues involved in location management and present a taxonomy and survey of location management strategies that have been proposed in the literature over the years for mobile computing systems.

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This paper reports on the design and testing of a model, which evaluates the relationship components of a Web-based EServices Acceptance Model (E-SAM). The paper proposes that user experience, user motivation, perceived usefulness, perceived ease of use that may determine user acceptance of web-based eServices. The model is tested in a university environment where students and staff use services that have moved from an old paper-based to Web-based eService system. The results of data analysis highlight that user experience is strongly related to perceived ease of use; and perceived usefulness to user motivation in user acceptance of Web-based eServices. The strength of these relationships and the lack of strong relationships between other components suggest that the model's application to eServices is able to highlight the complexity of the eService process and the need for researchers to seek additional components in studying technology acceptance on the World Wide Web.

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This research explored the potential for expansion of the current function, and usage of Interactive Television. The interviews and group discussions assisted in the determination of the theoretical framework for "Interactive Digital Vision", including its inspiration from current technologies to provide an engaging, enriching and intertaining user experience.

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This study found that user experience and perceived ease of use are the most important factors in considering the user acceptance of e-Services and that there is no significant relationship between user acceptance and continued use of e-Services. The Electronic Services Acceptance Model (E-SAM) explains user adoption of e-Services.

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In the current era increased attention and interest of utilizing advanced computer technologies for training and education at all managerial levels and functional areas is apparent. One of such technologies, virtual environment (VE), is perceived to be effective in enhancing human abilities to learn abstract concept and complex procedural tasks. Despite its adaptation for training and fast-paced technological advancements, ways in which to evaluate efficacy of such technology are unclear. We have approached this problem by developed a new evaluation method focus on cognitive, affective and skillbased learning dimensions, based on traditional usability evaluation methods but tailored to specifically suit for the quantification of 3D VE system. We first describe the construct of the new method and then report a study utilizing the method in the context of quantifying a VE efficacy in an object assembly task. At last, we discuss the implications of such a method.

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Feature aggregation is a critical technique in content-based image retrieval systems that employ multiple visual features to characterize image content. One problem in feature aggregation is that image similarity in different feature spaces can not be directly comparable with each other. To address this problem, a new feature aggregation approach, series feature aggregation (SFA), is proposed in this paper. In contrast to merging incomparable feature distances in different feature spaces to get aggregated image similarity in the conventional feature aggregation approach, the series feature aggregation directly deal with images in each feature space to avoid comparing different feature distances. SFA is effectively filtering out irrelevant images using individual features in each stage and the remaining images are images that collectively described by all features. Experiments, conducted with IAPR TC-12 benchmark image collection (ImageCLEF2006) that contains over 20,000 photographic images and defined queries, have shown that SFA can outperform the parallel feature aggregation and linear distance combination schemes. Furthermore, SFA is able to retrieve more relevant images in top ranked outputs that brings better user experience in finding more relevant images quickly.

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My research proposes novel methods to reduce the cardinality of a priori data used in recognition based augmented reality, whilst retaining distinctive and persistent features in the sets. This research will help reduce latency and increase accuracy in recognition based pose estimation systems, thus improving the user experience for augmented reality applications.

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The Taylor Family Digital Library is the central library opened in 2011 at the University of Calgary dedicated to supporting digital scholarship, creativity, analysis and a supportive learning environment for students. The new building is a technologically advanced converged cultural institution, with mandates to continually evolve in order to meet the needs of students and researchers. The infrastructure to support these mandates required research, collaboration and intense planning, resulting in new construction and technology standards for library renovation and construction projects. This pragmatic article is written for those who will follow in similar footsteps; it provides a roadmap for those embarking on the construction of a new technologically advanced library building.