994 resultados para Building extraction
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The overarching research work is based on two approaches: - Conceptual Analysis, Extraction and Linking - Experimentation with Product Libraries - Conceptual Analysis, Extraction and Linking: This aspect of the research has been achieved through the development of a conceptual framework for facilitating the understanding of the constituting components of BIM, Specifications and Cost Planning under investigation. The framework builds on theories spanning the constituent research themes and was used as a basis for justifying the elected approaches adopted throughout the research work. By means of tags and codes, a system for classifying building specification information has been developed as a differentiator between the chosen research approach and existing classification strategies in industry. Furthermore, syntactic links between extracted classes of specification information and cost planning have been established and will be adopted as a basis for authenticating the impact of specification information within BIM models. - Experimentation with Product Libraries Following the extraction and classification of BIM, Specifications and Cost Planning information, early experimentation on linking specifications to BIM models by means of a raas-based product library have been successful. A comparative analysis between a range of existing product libraries has also been realised. The outcomes have been amply documented in papers, all of which have received positive reviews. Ongoing experiments and analysis with the product library involve integrating the cost planning component for authenticating the completeness, relevance and impact of embedded specification within BIM models.
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This digital poster (which was on display at "The Cube", Queensland University of Technology) demonstrates how specification parameters can be extracted from a product library repository for use in augmenting the information contents of the objects in a local BIM tool (Revit in this instance).
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Building information models have created a paradigm shift in how buildings are built and managed by providing a dynamic repository for building data that is useful in many new operational scenarios. This change has also created an opportunity to use building information models as an integral part of security operations and especially as a tool to facilitate fine-grained access control to building spaces in smart buildings and critical infrastructure environments. In this paper, we identify the requirements for a security policy model for such an access control system and discuss why the existing policy models are not suitable for this application. We propose a new policy language extension to XACML, with BIM specific data types and functions based on the IFC specification, which we call BIM-XACML.
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Building information models are increasingly being utilised for facility management of large facilities such as critical infrastructures. In such environments, it is valuable to utilise the vast amount of data contained within the building information models to improve access control administration. The use of building information models in access control scenarios can provide 3D visualisation of buildings as well as many other advantages such as automation of essential tasks including path finding, consistency detection, and accessibility verification. However, there is no mathematical model for building information models that can be used to describe and compute these functions. In this paper, we show how graph theory can be utilised as a representation language of building information models and the proposed security related functions. This graph-theoretic representation allows for mathematically representing building information models and performing computations using these functions.
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Aim: To examine evidence-based strategies that motivate appropriate action and increase informed decision-making during the response and recovery phases of disasters.
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Reflection can form the basis for powerful dialogue between the arts and literacy as we seek interpretive and expressive fluency across modes. Through deep, cumulative reflection we make aspects of our world and experiences more perceivable, and open them up for artistic expression and aesthetic inquiry. Such reflections are also the catalysts for self-awareness and identity building. Theories of reflexivity offer a useful lens with which to understand our relationship with the world and the people, texts and things within it. The reflexive process can prompt us to challenge our understandings and change our representations of self and others through text. This paper offers a discussion of reflexivity and the ways in which it can be expressed and performed in discursive and non-discursive ways to develop literacies through and in the arts.
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The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of 10^5, 10^2 and 10^0 sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of 10^-2, 10^-1 and 10^0 Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.
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Text is the main method of communicating information in the digital age. Messages, blogs, news articles, reviews, and opinionated information abounds on the Internet. People commonly purchase products online and post their opinions about purchased items. This feedback is displayed publicly to assist others with their purchasing decisions, creating the need for a mechanism with which to extract and summarize useful information for enhancing the decision-making process. Our contribution is to improve the accuracy of extraction by combining different techniques from three major areas, named Data Mining, Natural Language Processing techniques and Ontologies. The proposed framework sequentially mines product’s aspects and users’ opinions, groups representative aspects by similarity, and generates an output summary. This paper focuses on the task of extracting product aspects and users’ opinions by extracting all possible aspects and opinions from reviews using natural language, ontology, and frequent “tag” sets. The proposed framework, when compared with an existing baseline model, yielded promising results.
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AN ENGINEERING Workshop was held from 21 to 24 November 2006 in Veracruz, Mexico. Forty delegates from 12 countries attended the workshop on theory and practice of milling and diffusion extraction. This report provides a general overview of activities undertaken during that workshop which consisted of five technical sessions over two days with presentations and discussions plus two days of field and factory visits. Topics covered during the technical sessions included: power transmissions, cane preparation, diffusers, mills, and a comparison of milling and diffusion.
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BACKGROUND: The use of salivary diagnostics is increasing because of its noninvasiveness, ease of sampling, and the relatively low risk of contracting infectious organisms. Saliva has been used as a biological fluid to identify and validate RNA targets in head and neck cancer patients. The goal of this study was to develop a robust, easy, and cost-effective method for isolating high yields of total RNA from saliva for downstream expression studies. METHODS: Oral whole saliva (200 mu L) was collected from healthy controls (n = 6) and from patients with head and neck cancer (n = 8). The method developed in-house used QIAzol lysis reagent (Qiagen) to extract RNA from saliva (both cell-free supernatants and cell pellets), followed by isopropyl alcohol precipitation, cDNA synthesis, and real-time PCR analyses for the genes encoding beta-actin ("housekeeping" gene) and histatin (a salivary gland-specific gene). RESULTS: The in-house QIAzol lysis reagent produced a high yield of total RNA (0.89 -7.1 mu g) from saliva (cell-free saliva and cell pellet) after DNase treatment. The ratio of the absorbance measured at 260 nm to that at 280 nm ranged from 1.6 to 1.9. The commercial kit produced a 10-fold lower RNA yield. Using our method with the QIAzol lysis reagent, we were also able to isolate RNA from archived saliva samples that had been stored without RNase inhibitors at -80 degrees C for >2 years. CONCLUSIONS: Our in-house QIAzol method is robust, is simple, provides RNA at high yields, and can be implemented to allow saliva transcriptomic studies to be translated into a clinical setting.
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This article outlines the knowledge and skills students develop when they engage in digital media production and analysis in school settings. The metaphor of ‘digital building blocks’ is used to describe the material practices, conceptual understandings and production of knowledge that lead to the development of digital media literacy. The article argues that the two established approaches to media literacy education, critical reading and media production, do not adequately explain how students develop media knowledge. It suggests there has been too little focus on material practices and how these relate to the development of conceptual understanding in media learning. The article explores empirical evidence from a four-year investigation in a primary school in Queensland, Australia using actor–network theory to explore ‘moments of translation’ as students deploy technologies and concepts to materially participate in digital culture. A generative model of media learning is presented with four categories of building blocks that isolate the specific skills and knowledge that can be taught and learnt to promote participation in digital media contexts: digital materials, conceptual understandings, media production and media analysis. The final section of the article makes initial comments on how the model might become the basis for curriculum development in schools and argues that further empirical research needs to occur to confirm the model’s utility.