14 resultados para Classify

em Cambridge University Engineering Department Publications Database


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Optimised ultrafast laser ablation can result in almost complete ionisation of the target material and the formation of a high velocity plasma jet. Collisions with the ambient gas behind the shock front cools the material resulting in the formation of mainly spherical, single crystal nanoscale particles in the condensate. This work characterises the nanoscale structures produced by the ultrafast laser interactions in He atmospheres at STP with Ni and Al. High resolution transmission electron microscopy was employed to study the microstructure of the condensates and to classify the production of particles forms as a function of the illumination conditions.

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We present in this paper a new multivariate probabilistic approach to Acoustic Pulse Recognition (APR) for tangible interface applications. This model uses Principle Component Analysis (PCA) in a probabilistic framework to classify tapping pulses with a high degree of variability. It was found that this model, achieves a higher robustness to pulse variability than simpler template matching methods, specifically when allowed to train on data containing high variability. © 2011 IEEE.

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The amount of original imaging information produced yearly during the last decade has experienced a tremendous growth in all industries due to the technological breakthroughs in digital imaging and electronic storage capabilities. This trend is affecting the construction industry as well, where digital cameras and image databases are gradually replacing traditional photography. Owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks like monitoring an activity's progress and keeping evidence of the "as built" in case any disputes arise. So far, retrieval methodologies are done manually with the user being responsible for imaging classification according to specific rules that serve a limited number of construction management tasks. New methods that, with the guidance of the user, can automatically classify and retrieve construction site images are being developed and promise to remove the heavy burden of manually indexing images. In this paper, both the existing methods and a novel image retrieval method developed by the authors for the classification and retrieval of construction site images are described and compared. Specifically a number of examples are deployed in order to present their advantages and limitations. The results from this comparison demonstrates that the content based image retrieval method developed by the authors can reduce the overall time spent for the classification and retrieval of construction images while providing the user with the flexibility to retrieve images according different classification schemes.

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This book explores the processes for retrieval, classification, and integration of construction images in AEC/FM model based systems. The author describes a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval that have been integrated into a novel method for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks. objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.

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The Architecture, Engineering, Construction and Facilities Management (AEC/FM) industry is rapidly becoming a multidisciplinary, multinational and multi-billion dollar economy, involving large numbers of actors working concurrently at different locations and using heterogeneous software and hardware technologies. Since the beginning of the last decade, a great deal of effort has been spent within the field of construction IT in order to integrate data and information from most computer tools used to carry out engineering projects. For this purpose, a number of integration models have been developed, like web-centric systems and construction project modeling, a useful approach in representing construction projects and integrating data from various civil engineering applications. In the modern, distributed and dynamic construction environment it is important to retrieve and exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research demonstrated that a major hurdle in AEC/FM data integration in such systems is caused by its variety of data types and that a significant part of the data is stored in semi-structured or unstructured formats. Therefore, new integrative approaches are needed to handle non-structured data types like images and text files. This research is focused on the integration of construction site images. These images are a significant part of the construction documentation with thousands stored in site photographs logs of large scale projects. However, locating and identifying such data needed for the important decision making processes is a very hard and time-consuming task, while so far, there are no automated methods for associating them with other related objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.

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Digital photographs of construction site activities are gradually replacing their traditional paper based counterparts. Existing digital imaging technologies in hardware and software make it easy for site engineers to take numerous photographs of “interesting” processes and activities on a daily basis. The resulting photographic data are evidence of the “as-built” project, and can therefore be used in a number of project life cycle tasks. However, the task of retrieving the relevant photographs needed in these tasks is often burdened by the sheer volume of photographs accumulating in project databases over time and the numerous objects present in each photograph. To solve this problem, the writers have recently developed a number of complementary techniques that can automatically classify and retrieve construction site images according to a variety of criteria (materials, time, date, location, etc.). This paper presents a novel complementary technique that can automatically identify linear (i.e., beam, column) and nonlinear (i.e., wall, slab) construction objects within the image content and use that information to enhance the performance of the writers’ existing construction site image retrieval approach.

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Surfaces coated with nanoscale filaments such as silicon nanowires and carbon nanotubes are potentially compelling for high-performance battery and capacitor electrodes, photovoltaics, electrical interconnects, substrates for engineered cell growth, dry adhesives, and other smart materials. However, many of these applications require a wet environment or involve wet processing during their synthesis. The capillary forces introduced by these wet environments can lead to undesirable aggregation of nanoscale filaments, but control of capillary forces can enable manipulation of the filaments into discrete aggregates and novel hierarchical structures. Recent studies suggest that the elastocapillary self-assembly of nanofilaments can be a versatile and scalable means to build complex and robust surface architectures. To enable a wider understanding and use of elastocapillary self-assembly as a fabrication technology, we give an overview of the underlying fundamentals and classify typical implementations and surface designs for nanowires, nanotubes, and nanopillars made from a wide variety of materials. Finally, we discuss exemplary applications and future opportunities to realize new engineered surfaces by the elastocapillary self-assembly of nanofilaments. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Widespread approaches to fabricate surfaces with robust micro- and nanostructured topographies have been stimulated by opportunities to enhance interface performance by combining physical and chemical effects. In particular, arrays of asymmetric surface features, such as arrays of grooves, inclined pillars, and helical protrusions, have been shown to impart unique anisotropy in properties including wetting, adhesion, thermal and/or electrical conductivity, optical activity, and capability to direct cell growth. These properties are of wide interest for applications including energy conversion, microelectronics, chemical and biological sensing, and bioengineering. However, fabrication of asymmetric surface features often pushes the limits of traditional etching and deposition techniques, making it challenging to produce the desired surfaces in a scalable and cost-effective manner. We review and classify approaches to fabricate arrays of asymmetric 2D and 3D surface features, in polymers, metals, and ceramics. Analytical and empirical relationships among geometries, materials, and surface properties are discussed, especially in the context of the applications mentioned above. Further, opportunities for new fabrication methods that combine lithography with principles of self-assembly are identified, aiming to establish design principles for fabrication of arbitrary 3D surface textures over large areas. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Decision making in an uncertain environment poses a conflict between the opposing demands of gathering and exploiting information. In a classic illustration of this 'exploration-exploitation' dilemma, a gambler choosing between multiple slot machines balances the desire to select what seems, on the basis of accumulated experience, the richest option, against the desire to choose a less familiar option that might turn out more advantageous (and thereby provide information for improving future decisions). Far from representing idle curiosity, such exploration is often critical for organisms to discover how best to harvest resources such as food and water. In appetitive choice, substantial experimental evidence, underpinned by computational reinforcement learning (RL) theory, indicates that a dopaminergic, striatal and medial prefrontal network mediates learning to exploit. In contrast, although exploration has been well studied from both theoretical and ethological perspectives, its neural substrates are much less clear. Here we show, in a gambling task, that human subjects' choices can be characterized by a computationally well-regarded strategy for addressing the explore/exploit dilemma. Furthermore, using this characterization to classify decisions as exploratory or exploitative, we employ functional magnetic resonance imaging to show that the frontopolar cortex and intraparietal sulcus are preferentially active during exploratory decisions. In contrast, regions of striatum and ventromedial prefrontal cortex exhibit activity characteristic of an involvement in value-based exploitative decision making. The results suggest a model of action selection under uncertainty that involves switching between exploratory and exploitative behavioural modes, and provide a computationally precise characterization of the contribution of key decision-related brain systems to each of these functions.

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Historically, waste pickers around the globe have utilised urban solid waste as a principal source of livelihood. Formal waste management sectors usually perceive the informal waste collection/recycling networks as backward, unhygienic and generally incompatible with modern waste management systems. It is proposed here that through careful planning and administration, these seemingly troublesome informal networks can be integrated into formal waste management systems in developing countries, providing mutual benefits. A theoretical framework for integration based on a case study in Lahore, Pakistan, is presented. The proposed solution suggests that the municipal authority should draw up and agree on a formal work contract with the group of waste pickers already operating in the area. The proposed system is assessed using the integration radar framework to classify and analyse possible intervention points between the sectors. The integration of the informal waste workers with the formal waste management sector is not a one dimensional or single step process. An ideal solution might aim for a balanced focus on all four categories of intervention, although this may be influenced by local conditions. Not all the positive benefits will be immediately apparent, but it is expected that as the acceptance of such projects increases over time, the informal recycling economy will financially supplement the formal system in many ways.

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BACKGROUND: The utilisation of good design practices in the development of complex health services is essential to improving quality. Healthcare organisations, however, are often seriously out of step with modern design thinking and practice. As a starting point to encourage the uptake of good design practices, it is important to understand the context of their intended use. This study aims to do that by articulating current health service development practices. METHODS: Eleven service development projects carried out in a large mental health service were investigated through in-depth interviews with six operation managers. The critical decision method in conjunction with diagrammatic elicitation was used to capture descriptions of these projects. Stage-gate design models were then formed to visually articulate, classify and characterise different service development practices. RESULTS: Projects were grouped into three categories according to design process patterns: new service introduction and service integration; service improvement; service closure. Three common design stages: problem exploration, idea generation and solution evaluation - were then compared across the design process patterns. Consistent across projects were a top-down, policy-driven approach to exploration, underexploited idea generation and implementation-based evaluation. CONCLUSIONS: This study provides insight into where and how good design practices can contribute to the improvement of current service development practices. Specifically, the following suggestions for future service development practices are made: genuine user needs analysis for exploration; divergent thinking and innovative culture for idea generation; and fail-safe evaluation prior to implementation. Better training for managers through partnership working with design experts and researchers could be beneficial.

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Historically, waste pickers around the globe have utilised urban solid waste as a principal source of livelihood. Formal waste management sectors usually perceive the informal waste collection/recycling networks as backward, unhygienic and generally incompatible with modern waste management systems. It is proposed here that through careful planning and administration, these seemingly troublesome informal networks can be integrated into formal waste management systems in developing countries, providing mutual benefits. A theoretical framework for integration based on a case study in Lahore, Pakistan, is presented. The proposed solution suggests that the municipal authority should draw up and agree on a formal work contract with the group of waste pickers already operating in the area. The proposed system is assessed using the integration radar framework to classify and analyse possible intervention points between the sectors. The integration of the informal waste workers with the formal waste management sector is not a one dimensional or single step process. An ideal solution might aim for a balanced focus on all four categories of intervention, although this may be influenced by local conditions. Not all the positive benefits will be immediately apparent, but it is expected that as the acceptance of such projects increases over time, the informal recycling economy will financially supplement the formal system in many ways. © The Author(s) 2013.

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The need to create high-value products for specialist applications, and the search for efficient forming routes that obviate the need for some machining steps, is driving Interest In a novel class of forming processes aiming to create locally thickened features within sheet work- pieces. A number of novel forming processes have been proposed to meet this need, but it is as yet unclear which processes will be most effective in creating local thickening of various geometries, and many process configurations have yet to be tried. This paper aims to provide some basic principles for designing and characterising process behaviour. A simplified generic description of sheet thickening processes is provided, with two tools of variable operating on a sheet workpiece in plane strain, with different tool separations and motions parameterised. A comprehensive numerical study of the behaviour of this class of processes is conducted in Abaqus to predict the main characteristics of the material flow in each configuration. The results are used to classify the different basic behaviours that can be achieved by the sheet-bulk thickening processes and to give guidance on future process development, capability and applicability. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA. Weinheim.