957 resultados para Local binary pattern
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This thesis targets on a challenging issue that is to enhance users' experience over massive and overloaded web information. The novel pattern-based topic model proposed in this thesis can generate high-quality multi-topic user interest models technically by incorporating statistical topic modelling and pattern mining. We have successfully applied the pattern-based topic model to both fields of information filtering and information retrieval. The success of the proposed model in finding the most relevant information to users mainly comes from its precisely semantic representations to represent documents and also accurate classification of the topics at both document level and collection level.
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Cold-formed steel members have been widely used in residential and commercial buildings as primary load bearing structural elements. They are often made of thin steel sheets and hence they are more susceptible to local buckling. The buckling behaviour of cold-formed steel compression members under fire conditions is not fully investigated yet and hence there is a lack of knowledge on the fire performance of cold-formed steel compression members. Current cold-formed steel design standards do not provide adequate design guidelines for the fire design of cold-formed steel compression members. Therefore a research project based on extensive experimental and numerical studies was undertaken to investigate the local buckling behaviour of light gauge cold-formed steel compression members under simulated fire conditions. First a series of 91 local buckling tests was conducted at ambient and uniform elevated temperatures up to 700oC on cold-formed lipped and unlipped channels. Suitable finite element models were then developed to simulate the behaviour of tested columns and were validated using test results. All the ultimate load capacity results for local buckling were compared with the predictions from the available design rules based on AS/NZS 4600, BS 5950 Part 5, Eurocode 3 Parts 1.2 and 1.3 and the direct strength method (DSM), based on which suitable recommendations have been made for the fire design of cold-formed steel compression members subject to local buckling at uniform elevated temperatures.
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In this paper, we propose a highly reliable fault diagnosis scheme for incipient low-speed rolling element bearing failures. The scheme consists of fault feature calculation, discriminative fault feature analysis, and fault classification. The proposed approach first computes wavelet-based fault features, including the respective relative wavelet packet node energy and entropy, by applying a wavelet packet transform to an incoming acoustic emission signal. The most discriminative fault features are then filtered from the originally produced feature vector by using discriminative fault feature analysis based on a binary bat algorithm (BBA). Finally, the proposed approach employs one-against-all multiclass support vector machines to identify multiple low-speed rolling element bearing defects. This study compares the proposed BBA-based dimensionality reduction scheme with four other dimensionality reduction methodologies in terms of classification performance. Experimental results show that the proposed methodology is superior to other dimensionality reduction approaches, yielding an average classification accuracy of 94.9%, 95.8%, and 98.4% under bearing rotational speeds at 20 revolutions-per-minute (RPM), 80 RPM, and 140 RPM, respectively.
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This paper presents a combined experimental and numerical study on the behaviour of both circular and square concrete-filled steel tube (CFT) stub columns under local compression. Twelve circular and eight square CFT stub columns were tested to study their bearing capacity and the key influential parameters. A 3D finite element model was established for simulation and parametric study to investigate the structural behaviour of the stub columns. The numerical results agreed well with the experimental results. In addition, analytical formulas were proposed to calculate the load bearing capacity of CFT stub columns under local compression.
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Due to the numerous possibilities of voicing concerns and the flood of data we are exposed to, local issues are sometimes at risk of being overlooked. This study explores Local Commons, a design intervention in public space that combines situated digital and tangible media in order to engage communities in contributing and debating different perspectives on a given local issue. The intervention invited the community to submit images of their perspectives on the issue, which were displayed on a public screen. Via tangible buttons in front of the screen, community members then agree or disagree on the displayed perspectives, creating a space for deliberation. In a user study, we were specifically interested in testing three aspects of our intervention, which are discussed in this paper: The difference that situatedness, visual content, and tangible interaction can make to urban community engagement.
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This paper discusses three different ways of applying the single-objective binary genetic algorithm into designing the wind farm. The introduction of different applications is through altering the binary encoding methods in GA codes. The first encoding method is the traditional one with fixed wind turbine positions. The second involves varying the initial positions from results of the first method, and it is achieved by using binary digits to represent the coordination of wind turbine on X or Y axis. The third is the mixing of the first encoding method with another one, which is by adding four more binary digits to represent one of the unavailable plots. The goal of this paper is to demonstrate how the single-objective binary algorithm can be applied and how the wind turbines are distributed under various conditions with best fitness. The main emphasis of discussion is focused on the scenario of wind direction varying from 0° to 45°. Results show that choosing the appropriate position of wind turbines is more significant than choosing the wind turbine numbers, considering that the former has a bigger influence on the whole farm fitness than the latter. And the farm has best performance of fitness values, farm efficiency, and total power with the direction between 20°to 30°.
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A critical review and discussion of research studies of the impacts of market-based reforms on Chinese education, with a specific emphasis on local uptakes and effects of policy.
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The thesis offers the foundation of a design pattern language for urban gardening, as well as a prototype mobile storytelling platform through which urban gardeners can share gardening experiences. This study examined three urban agriculture communities – a city farm, a permaculture movement, and residential gardeners – in order to better understand some of the challenges in their food growing practices. The city is increasingly being rediscovered by gardeners, food activists, and local governments as an under-utilised opportunity space for land cultivation and local food production, and the findings of this research were analysed with a view to consider interactive technology and design interventions in response.
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Partial evaluation of infrastructure investments have resulted in expensive mistakes, unsatisfactory outcomes and increased uncertainties for too many stakeholders, communities and economies in both developing and developed nations. "Complex Stakeholder Perception Mapping" (CSPM), is a novel approach that can address existing limitations by inclusively framing, capturing and mapping the spectrum of insights and perceptions using extended Geographic Information Systems. Maps generated in CSPM offer presentations of flexibly combined, complex perceptions of stakeholders on multiple aspects of development. CSPM extends the applications of GIS software in non-spatial mapping and of Multi-Criteria Analysis with a multidimensional evaluation platform and augments decision science capabilities in addressing complexities. Application of CSPM can improve local and regional economic gains from infrastructure projects and aid any multi-objective and multi-stakeholder decision situations.
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Particle swarm optimization (PSO), a new population based algorithm, has recently been used on multi-robot systems. Although this algorithm is applied to solve many optimization problems as well as multi-robot systems, it has some drawbacks when it is applied on multi-robot search systems to find a target in a search space containing big static obstacles. One of these defects is premature convergence. This means that one of the properties of basic PSO is that when particles are spread in a search space, as time increases they tend to converge in a small area. This shortcoming is also evident on a multi-robot search system, particularly when there are big static obstacles in the search space that prevent the robots from finding the target easily; therefore, as time increases, based on this property they converge to a small area that may not contain the target and become entrapped in that area.Another shortcoming is that basic PSO cannot guarantee the global convergence of the algorithm. In other words, initially particles explore different areas, but in some cases they are not good at exploiting promising areas, which will increase the search time.This study proposes a method based on the particle swarm optimization (PSO) technique on a multi-robot system to find a target in a search space containing big static obstacles. This method is not only able to overcome the premature convergence problem but also establishes an efficient balance between exploration and exploitation and guarantees global convergence, reducing the search time by combining with a local search method, such as A-star.To validate the effectiveness and usefulness of algorithms,a simulation environment has been developed for conducting simulation-based experiments in different scenarios and for reporting experimental results. These experimental results have demonstrated that the proposed method is able to overcome the premature convergence problem and guarantee global convergence.
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Purpose The aim of this paper is to empirically explore antecedents of local food purchase intention in two food producing countries with different cultural backgrounds. Design/methodology/approach An online survey was employed to collect data from consumers located in Chile (n=283) and Australia (n=300). A proposed model is tested with structural equation modelling (SEM). Findings Attitude towards consuming local food is a strong and direct driver of intentions to purchase local food in both countries. Attitude toward supporting local agri-businesses and consumer ethnocentrism are found to positively impact attitude towards consuming local food in both countries. Attitude towards local agri-businesses also has a direct effect on intentions to purchase local food in Australia, but not in Chile. Interestingly, subjective norms are not found to affect intentions to consume local food in either country. Research limitations/implications The paper examines factors affecting the attitude toward and behavioural intention regarding local food consumption and develops an extended model of local food consumption. An outcome of this new model is the inclusion of personal variables, which influence local food purchasing behaviour. Practical implications Producers and retailers need to develop campaigns explaining how consuming local food supports local businesses and farmers, which will reinforce personal values associated with local consumption. Originality/value This is the first study to demonstrate that positive attitudes toward local foods are important drivers of local food purchase behaviour, independent of the cultural characteristics or level of economic development within a country.
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We detected and mapped a dynamically spreading wave of gray matter loss in the brains of patients with Alzheimer's disease (AD). The loss pattern was visualized in four dimensions as it spread over time from temporal and limbic cortices into frontal and occipital brain regions, sparing sensorimotor cortices. The shifting deficits were asymmetric (left hemisphere > right hemisphere) and correlated with progressively declining cognitive status (p < 0.0006). Novel brain mapping methods allowed us to visualize dynamic patterns of atrophy in 52 high-resolution magnetic resonance image scans of 12 patients with AD (age 68.4 ± 1.9 years) and 14 elderly matched controls (age 71.4 ± 0.9 years) scanned longitudinally (two scans; interscan interval 2.1 ± 0.4 years). A cortical pattern matching technique encoded changes in brain shape and tissue distribution across subjects and time. Cortical atrophy occurred in a well defined sequence as the disease progressed, mirroring the sequence of neurofibrillary tangle accumulation observed in cross sections at autopsy. Advancing deficits were visualized as dynamic maps that change over time. Frontal regions, spared early in the disease, showed pervasive deficits later (< 15% loss). The maps distinguished different phases of AD and differentiated AD from normal aging. Local gray matter loss rates (5.3 ± 2.3% per year in AD v 0.9 ± 0.9% per year in controls) were faster in the left hemisphere (p < 0.029) than the right. Transient barriers to disease progression appeared at limbic/frontal boundaries. This degenerative sequence, observed in vivo as it developed, provides the first quantitative, dynamic visualization of cortical atrophic rates in normal elderly populations and in those with dementia.
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This article contributes to the theorization of the role of informal regulation (undertaken by leading firms) in the ongoing organization of global production networks. It does so through a qualitative case study of BHP Billiton's Ravensthorpe Nickel Operation (RNO) in the rural Shire of Ravensthorpe in Western Australia. This less tangible, and to date under-researched, dimension of global production networks is foregrounded through a focus on the corporate social responsibility strategy implemented by RNO in the service of achieving and/or demonstrating a broader ‘social licence to operate’. This ‘licence’ functions – beyond the corporation – as a legitimated and legitimating multi-scalar mechanism through which to gain and maintain access to mineral resources and thus to establish viable and ongoing global production networks. Further, this informal regulation is shown to shape social relations and qualities of place conducive to competitive global mineral extraction and to facilitate the positioning of local communities and places in mineral global production networks.
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Since 2008, Australian schoolchildren in Years 3, 5, 7 and 9 have sat a series of tests each May designed to assess their attainment of basic skills in literacy and numeracy. These tests are known as the National Assessment Program – Literacy and Numeracy (NAPLAN). In 2010, individual school NAPLAN data were first published on the MySchool website which enables comparisons to be made between individual schools and statistically like schools across Australia. NAPLAN represents the increased centrality of the federal government in education, particularly in regards to education policy. One effect of this has been a recast emphasis of education as an economic, rather than democratic, good. As Reid (2009) suggests, this recasting of education within national productivity agendas mobilises commonsense discourses of accountability and transparency. These are common articles of faith for many involved in education administration and bureaucracy; more and better data, and holding people to account for that data, must improve education...
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Humans dominate many important Earth system processes including the nitrogen (N) cycle. Atmospheric N deposition affects fundamental processes such as carbon cycling, climate regulation, and biodiversity, and could result in changes to fundamental Earth system processes such as primary production. Both modelling and experimentation have suggested a role for anthropogenically altered N deposition in increasing productivity, nevertheless, current understanding of the relative strength of N deposition with respect to other controls on production such as edaphic conditions and climate is limited. Here we use an international multiscale data set to show that atmospheric N deposition is positively correlated to aboveground net primary production (ANPP) observed at the 1-m2 level across a wide range of herbaceous ecosystems. N deposition was a better predictor than climatic drivers and local soil conditions, explaining 16% of observed variation in ANPP globally with an increase of 1 kg N·ha-1·yr-1 increasing ANPP by 3%. Soil pH explained 8% of observed variation in ANPP while climatic drivers showed no significant relationship. Our results illustrate that the incorporation of global N deposition patterns in Earth system models are likely to substantially improve estimates of primary production in herbaceous systems. In herbaceous systems across the world, humans appear to be partially driving local ANPP through impacts on the N cycle.