988 resultados para Cloud Workshop


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As technology continues to become more accessible, miniaturised and diffused into the environment, the potential of wearable technology to impact our lives in significant ways becomes increasingly viable. Wearables afford unique interaction, communication and functional capabilities between users, their environment as well as access to information and digital data. Wearables also demand an inter-disciplinary approach and, depending on the purpose, can be fashioned to transcend cultural, national and spatial boundaries. This paper presents the Cloud Workshop project based on the theme of ‘Wearables and Wellbeing; Enriching connections between citizens in the Asia-Pacific region’, initiated through a cooperative partnership between Queensland University of Technology (QUT), Hong Kong Baptist University (HKBU) and Griffith University (GU). The project was unique due to its inter-disciplinary, inter-cultural and inter-national scope that occurred simultaneously between Australia and Hong Kong.

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The ways in which technology mediates daily activities is shifting rapidly. Global trends point toward the uptake of ambient and interactive media to create radical new ways of working, interacting and socialising. Tech giants such as Google and Apple are banking on the success of this emerging market by investing in new future focused consumer products such as Google Glass and the Apple Watch. The potential implications of ubiquitous technological interactions via tangible and ambient media have never been more real or more accessible.

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This paper details a workshop aimed at exploring opportunities for experience design through wearable art and design concepts. Specifically it explores the structure of the workshop with respect to facilitating learning through technology in the development of experiential wearable art and design. A case study titled Cloud Workshop: Wearables and Wellbeing; Enriching connections between citizens in the Asia-Pacific region was initiated through a cooperative partnership between Hong Kong Baptist University (HKBU), Queensland University of Technology (QUT) and Griffith University (GU). Digital technologies facilitated collaboration through an inter-disciplinary, inter-national and inter- cultural approach (Facer & Sandford, 2010) between Australia and Hong Kong. Students cooperated throughout a two-week period to develop innovative wearable concepts blending art, design and technology. An unpacking of the approach, pedagogical underpinning and final outcomes revealed distinct educational benefits as well as certain learning and technological challenges of the program. Qualitative feedback uncovered additional successes with respect to student engagement and enthusiasm, while uncovering shortcomings in the delivery and management of information and difficulties with cultural interactions. Potential future versions of the program aim to take advantage of the positives and overcome the limitations of the current pedagogical approach. It is hoped the case study will become a catalyst for future workshops that blur the boundaries of art, design and technology to uncover further benefits and potentials for new outcomes in experience design.

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A patient-centric DRM approach is proposed for protecting privacy of health records stored in a cloud storage based on the patient's preferences and without the need to trust the service provider. Contrary to the current server-side access control solutions, this approach protects the privacy of records from the service provider, and also controls the usage of data after it is released to an authorized user.

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For the past few years, research works on the topic of secure outsourcing of cryptographic computations has drawn significant attention from academics in security and cryptology disciplines as well as information security practitioners. One main reason for this interest is their application for resource constrained devices such as RFID tags. While there has been significant progress in this domain since Hohenberger and Lysyanskaya have provided formal security notions for secure computation delegation, there are some interesting challenges that need to be solved that can be useful towards a wider deployment of cryptographic protocols that enable secure outsourcing of cryptographic computations. This position paper brings out these challenging problems with RFID technology as the use case together with our ideas, where applicable, that can provide a direction towards solving the problems.

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Automating the model generation process of infrastructure can substantially reduce the modeling time and cost. This paper presents a method to generate a sparse point cloud of an infrastructure scene using a single video camera under practical constraints. It is the first step towards establishing an automatic framework for object-oriented as-built modeling. Motion blur and key frame selection criteria are considered. Structure from motion and bundle adjustment are explored. The method is demonstrated in a case study where the scene of a reinforced concrete bridge is videotaped, reconstructed, and metrically validated. The result indicates the applicability, efficiency, and accuracy of the proposed method.

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Most of the manual labor needed to create the geometric building information model (BIM) of an existing facility is spent converting raw point cloud data (PCD) to a BIM description. Automating this process would drastically reduce the modeling cost. Surface extraction from PCD is a fundamental step in this process. Compact modeling of redundant points in PCD as a set of planes leads to smaller file size and fast interactive visualization on cheap hardware. Traditional approaches for smooth surface reconstruction do not explicitly model the sparse scene structure or significantly exploit the redundancy. This paper proposes a method based on sparsity-inducing optimization to address the planar surface extraction problem. Through sparse optimization, points in PCD are segmented according to their embedded linear subspaces. Within each segmented part, plane models can be estimated. Experimental results on a typical noisy PCD demonstrate the effectiveness of the algorithm.