30 resultados para Kannan Mappings

em Queensland University of Technology - ePrints Archive


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We consider the problem of choosing, sequentially, a map which assigns elements of a set A to a few elements of a set B. On each round, the algorithm suffers some cost associated with the chosen assignment, and the goal is to minimize the cumulative loss of these choices relative to the best map on the entire sequence. Even though the offline problem of finding the best map is provably hard, we show that there is an equivalent online approximation algorithm, Randomized Map Prediction (RMP), that is efficient and performs nearly as well. While drawing upon results from the "Online Prediction with Expert Advice" setting, we show how RMP can be utilized as an online approach to several standard batch problems. We apply RMP to online clustering as well as online feature selection and, surprisingly, RMP often outperforms the standard batch algorithms on these problems.

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This paper describes the use of property graphs for mapping data between AEC software tools, which are not linked by common data formats and/or other interoperability measures. The intention of introducing this in practice, education and research is to facilitate the use of diverse, non-integrated design and analysis applications by a variety of users who need to create customised digital workflows, including those who are not expert programmers. Data model types are examined by way of supporting the choice of directed, attributed, multi-relational graphs for such data transformation tasks. A brief exemplar design scenario is also presented to illustrate the concepts and methods proposed, and conclusions are drawn regarding the feasibility of this approach and directions for further research.

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During the early design stages of construction projects, accurate and timely cost feedback is critical to design decision making. This is particularly challenging for cost estimators, as they must quickly and accurately estimate the cost of the building when the design is still incomplete and evolving. State-of-the-art software tools typically use a rule-based approach to generate detailed quantities from the design details present in a building model and relate them to the cost items in a cost estimating database. In this paper, we propose a generic approach for creating and maintaining a cost estimate using flexible mappings between a building model and a cost estimate. The approach uses queries on the building design that are used to populate views, and each view is then associated with one or more cost items. The benefit of this approach is that the flexibility of modern query languages allows the estimator to encode a broad variety of relationships between the design and estimate. It also avoids the use of a common standard to which both designers and estimators must conform, allowing the estimator added flexibility and functionality to their work.

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Managed execution frameworks, such as the.NET Common Language Runtime or the Java Virtual Machine, provide a rich environment for the creation of application programs. These execution environments are ideally suited for languages that depend on type-safety and the declarative control of feature access. Furthermore, such frameworks typically provide a rich collection of library primitives specialized for almost every domain of application programming. Thus, when a new language is implemented on one of these frameworks it becomes necessary to provide some kind of mapping from the new language to the libraries of the framework. The design of such mappings is challenging since the type-system of the new language may not span the domain exposed in the library application programming interfaces (APIs). The nature of these design considerations was clarified in the implementation of the Gardens Point Component Pascal (gpcp) compiler. In this paper we describe the issues, and the solutions that we settled on in this case. The problems that were solved have a wider applicability than just our example, since they arise whenever any similar language is hosted in such an environment.

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The Silk Road Project was a practice-based research project investigating the potential of motion capture technology to inform perceptions of embodiment in dance performance. The project created a multi-disciplinary collaborative performance event using dance performance and real-time motion capture at Deakin University’s Deakin Motion Lab. Several new technological advances in producing real-time motion capture performance were produced, along with a performance event that examined the aesthetic interplay between a dancer’s movement and the precise mappings of its trajectories created by motion capture and real-time motion graphic visualisations.

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In this paper we investigate the heuristic construction of bijective s-boxes that satisfy a wide range of cryptographic criteria including algebraic complexity, high nonlinearity, low autocorrelation and have none of the known weaknesses including linear structures, fixed points or linear redundancy. We demonstrate that the power mappings can be evolved (by iterated mutation operators alone) to generate bijective s-boxes with the best known tradeoffs among the considered criteria. The s-boxes found are suitable for use directly in modern encryption algorithms.

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Autonomous development of sensorimotor coordination enables a robot to adapt and change its action choices to interact with the world throughout its lifetime. The Experience Network is a structure that rapidly learns coordination between visual and haptic inputs and motor action. This paper presents methods which handle the high dimensionality of the network state-space which occurs due to the simultaneous detection of multiple sensory features. The methods provide no significant increase in the complexity of the underlying representations and also allow emergent, task-specific, semantic information to inform action selection. Experimental results show rapid learning in a real robot, beginning with no sensorimotor mappings, to a mobile robot capable of wall avoidance and target acquisition.

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Search log data is multi dimensional data consisting of number of searches of multiple users with many searched parameters. This data can be used to identify a user’s interest in an item or object being searched. Identifying highest interests of a Web user from his search log data is a complex process. Based on a user’s previous searches, most recommendation methods employ two-dimensional models to find relevant items. Such items are then recommended to a user. Two-dimensional data models, when used to mine knowledge from such multi dimensional data may not be able to give good mappings of user and his searches. The major problem with such models is that they are unable to find the latent relationships that exist between different searched dimensions. In this research work, we utilize tensors to model the various searches made by a user. Such high dimensional data model is then used to extract the relationship between various dimensions, and find the prominent searched components. To achieve this, we have used popular tensor decomposition methods like PARAFAC, Tucker and HOSVD. All experiments and evaluation is done on real datasets, which clearly show the effectiveness of tensor models in finding prominent searched components in comparison to other widely used two-dimensional data models. Such top rated searched components are then given as recommendation to users.

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Dr Ian Weir's practice is driven by a passion for the Fitzgerald Bioregion, a remote, bushfire-prone landscape on the south coats of Western Australia which is renowned internationally for its biodiversity. It is here that Dr Weir collaborates with individuals and organisations from the fields of ecology, botany, bushfire science, land surveying, landscape architecture and art practice, all of whom seek to expand understandings of this remarkable landscape. This diverse practice formation is constructed to address a significant problem beyond the scope of conventional modes of architectural practice: the reconciliation of biodiversity and bushfire with human habitation, through a multimodal approach using art practice cartography and architectural intervention. The chapter articulates Dr Weir's practice through a formation diagram and depicts key works of landscape representaion taken from "Enacted Cartography" and "Lightsite", two of Dr Weir's key research themes.

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Research background: Communicating the diverse nature of multimodal practice is inherently difficult for the design-led research academic. Websites are an effective means of displaying images and text, but for the user/viewer the act of viewing is often random and disorienting, due to the non-linear means of accessing the information. This characteristic of websites limits the medium’s efficacy in regard to presenting an overarching philosophical standpoint or theme - the key driver behind most academic research. Research Contribution: This website: http://www.ianweirarchitect.com, presents a means of reconciling this problem by presenting a deceptively simple graphic and temporal layout, which limits the opportunity for the user/viewer to become disoriented and miss the key themes and issues that binds, the otherwise divergent, research material together. Research significance: http://www.ianweirarchitect.com, is a creative work that supplements Dr Ian Weir’s exhibition “Enacted Cartography” held in August 2012 in Brisbane and in August/September 2012 in Venice, Italy for the 13th International Architecture Exhibition (Venice Architecture Biennale). Dr Weir was selected by the Australian Institute of Architects to represent innovation in architectural practice for the Institute’s Formations: New Practices in Australian Architecture, exhibition and catalogue (of the same name) held in the Australian Pavilion, The Giardini, Venice. This website is creative output that compliments Dr Weir’s other multimodal outputs including photographic artworks, cartographic maps and architectural designs.

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RESEARCH BACKGROUND Enacted Cartography documents 10 years of creative research practice by Ian Weir Research Architect and was developed as standalone exhibition to support Dr Weir’s selection by the Australian Institute of Architects to represent innovative architectural practice via the Institute’s review entitled Formations: New Practices in Australian Architecture – which took the form of an exhibition and book presented in Venice, Italy for 13th International Architecture Exhibition (Venice Architecture Biennale). All works exhibited in Enacted Cartography are original works by Dr Weir and are generated either from or for the remote biodiverse landscapes of the Fitzgerald Bioregion on the south coast of Western Australia. RESEARCH CONTRIBUTION As a creative work in its own right, the Enacted Cartography exhibition makes the following contributions to knowledge: 1. Expands understandings of architectural practice by presenting a geographically-specific but multimodal form of architectural practice - wherein practitioners cross over discipline boundaries into art practice, landscape representation, website design, undergraduate university teaching and community advocacy. 2. Contributes to understandings of how such a diverse multimodal form of practice might be represented through both digital media and traditional print media in an exhibition format. 3. Expands understandings of how architectural practitioners might work within a particular place to develop a geographically-specific sense of identity, a ‘landscape of resistance’. RESEARCH SIGNIFICANCE Enacted Cartography was presented to an international audience during the 13th International Architecture Exhibition (Venice Architecture Biennale). The significance of Dr Weir’s research is evidence by his selected by the Australian Institute of Architects to represent innovation in architectural practice for the Biennale. Enacted Cartography addresses problems of national and international importance including: 1. The sustainable development of biodiverse remote landscapes; 2. The reconciliation of bushfire safety and biodiversity conservation; 3. The necessity for rethinking of architectural design methodologies to meet the complexity of landscape management and design; 4. It challenges orthodox forms of landscape representation (aerial photography, for example) which are demonstrably inadequate registrations of biophysical and cultural landscapes.

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Educators are faced with many challenging questions in designing an effective curriculum. What prerequisite knowledge do students have before commencing a new subject? At what level of mastery? What is the spread of capabilities between bare-passing students vs. the top performing group? How does the intended learning specification compare to student performance at the end of a subject? In this paper we present a conceptual model that helps in answering some of these questions. It has the following main capabilities: capturing the learning specification in terms of syllabus topics and outcomes; capturing mastery levels to model progression; capturing the minimal vs. aspirational learning design; capturing confidence and reliability metrics for each of these mappings; and finally, comparing and reflecting on the learning specification against actual student performance. We present a web-based implementation of the model, and validate it by mapping the final exams from four programming subjects against the ACM/IEEE CS2013 topics and outcomes, using Bloom's Taxonomy as the mastery scale. We then import the itemised exam grades from 632 students across the four subjects and compare the demonstrated student performance against the expected learning for each of these. Key contributions of this work are the validated conceptual model for capturing and comparing expected learning vs. demonstrated performance, and a web-based implementation of this model, which is made freely available online as a community resource.

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It is a big challenge to find useful associations in databases for user specific needs. The essential issue is how to provide efficient methods for describing meaningful associations and pruning false discoveries or meaningless ones. One major obstacle is the overwhelmingly large volume of discovered patterns. This paper discusses an alternative approach called multi-tier granule mining to improve frequent association mining. Rather than using patterns, it uses granules to represent knowledge implicitly contained in databases. It also uses multi-tier structures and association mappings to represent association rules in terms of granules. Consequently, association rules can be quickly accessed and meaningless association rules can be justified according to the association mappings. Moreover, the proposed structure is also an precise compression of patterns which can restore the original supports. The experimental results shows that the proposed approach is promising.

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This paper presents a new framework for distributed intrusion detection based on taint marking. Our system tracks information flows between applications of multiple hosts gathered in groups (i.e., sets of hosts sharing the same distributed information flow policy) by attaching taint labels to system objects such as files, sockets, Inter Process Communication (IPC) abstractions, and memory mappings. Labels are carried over the network by tainting network packets. A distributed information flow policy is defined for each group at the host level by labeling information and defining how users and applications can legally access, alter or transfer information towards other trusted or untrusted hosts. As opposed to existing approaches, where information is most often represented by two security levels (low/high, public/private, etc.), our model identifies each piece of information within a distributed system, and defines their legal interaction in a fine-grained manner. Hosts store and exchange security labels in a peer to peer fashion, and there is no central monitor. Our IDS is implemented in the Linux kernel as a Linux Security Module (LSM) and runs standard software on commodity hardware with no required modification. The only trusted code is our modified operating system kernel. We finally present a scenario of intrusion in a web service running on multiple hosts, and show how our distributed IDS is able to report security violations at each host level.

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Robust descriptor matching across varying lighting conditions is important for vision-based robotics. We present a novel strategy for quantifying the lighting variance of descriptors. The strategy works by utilising recovered low dimensional mappings from Isomap and our measure of the lighting variance of each of these mappings. The resultant metric allows different descriptors to be compared given a dataset and a set of keypoints. We demonstrate that the SIFT descriptor typically has lower lighting variance than other descriptors, although the result depends on semantic class and lighting conditions.