863 resultados para Representation Construction Approach


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Purpose – Construction sector competitiveness has been a subject of interest for many years. Research too often focuses on the means of overcoming the “barriers to change” as if such barriers were static entities. There has been little attempt to understand the dynamic inter-relationship between the differing factors which impinge upon construction sector competitiveness. The purpose of this paper is to outline the benefits of taking a systems approach to construction competitiveness research. Design/methodology/approach – The system dynamics (SD) modelling methodology is described. This can provide practitioners with “microworlds” within which they can explore the dynamic effects of different policy decisions. The data underpinning the use of SD was provided by interviews and case study research which allowed an understanding of the context within which practitioners operate. Findings – The over-riding conclusion is that the SD methodology has been shown to be capable of providing a means to assess the forces which shape the sustained competitiveness of construction firms. As such, it takes the assessment of strategic policy analysis in the construction sector onto a higher plane. The need to collect data and make retrospective assessments of competitiveness and strategic performance at the statistical level is not now the only modus operandi available. Originality/value – The paper describes a novel research methodology which points towards an alternative research agenda for construction competitiveness research.

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We develop a particle swarm optimisation (PSO) aided orthogonal forward regression (OFR) approach for constructing radial basis function (RBF) classifiers with tunable nodes. At each stage of the OFR construction process, the centre vector and diagonal covariance matrix of one RBF node is determined efficiently by minimising the leave-one-out (LOO) misclassification rate (MR) using a PSO algorithm. Compared with the state-of-the-art regularisation assisted orthogonal least square algorithm based on the LOO MR for selecting fixednode RBF classifiers, the proposed PSO aided OFR algorithm for constructing tunable-node RBF classifiers offers significant advantages in terms of better generalisation performance and smaller model size as well as imposes lower computational complexity in classifier construction process. Moreover, the proposed algorithm does not have any hyperparameter that requires costly tuning based on cross validation.

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Background The information processing capacity of the human mind is limited, as is evidenced by the attentional blink (AB) - a deficit in identifying the second of two temporally-close targets (T1 and T2) embedded in a rapid stream of distracters. Theories of the AB generally agree that it results from competition between stimuli for conscious representation. However, they disagree in the specific mechanisms, in particular about how attentional processing of T1 determines the AB to T2. Methodology/Principal Findings The present study used the high spatial resolution of functional magnetic resonance imaging (fMRI) to examine the neural mechanisms underlying the AB. Our research approach was to design T1 and T2 stimuli that activate distinguishable brain areas involved in visual categorization and representation. ROI and functional connectivity analyses were then used to examine how attentional processing of T1, as indexed by activity in the T1 representation area, affected T2 processing. Our main finding was that attentional processing of T1 at the level of the visual cortex predicted T2 detection rates Those individuals who activated the T1 encoding area more strongly in blink versus no-blink trials generally detected T2 on a lower percentage of trials. The coupling of activity between T1 and T2 representation areas did not vary as a function of conscious T2 perception. Conclusions/Significance These data are consistent with the notion that the AB is related to attentional demands of T1 for selection, and indicate that these demands are reflected at the level of visual cortex. They also highlight the importance of individual differences in attentional settings in explaining AB task performance.

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There is under-representation of senior female managers within small construction firms in the United Kingdom. The position is denying the sector a valuable pool of labour to address acute knowledge and skill shortages. Grounded theory on the career progression of senior female managers in these firms is developed from biographical interviews. First, a turning point model which distinguishes the interplay between human agency and work/home structure is given. Second, four career development phases are identified. The career journeys are characterized by ad hoc decisions and opportunities which were not influenced by external policies aimed at improving the representation of women in construction. Third, the 'hidden', but potentially significant, contribution of women-owned small construction firms is noted. The key challenge for policy and practice is to balance these external approaches with recognition of the 'inside out' reality of the 'lived experiences' of female managers. To progress this agenda there is a need for: appropriate longitudinal statistical data to quantify the scale of senior female managers and owners of small construction firms over time; and, social construction and gendered organizational analysis research to develop a general discourse on gender difference with these firms.

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Major construction clients are increasingly looking to procure built facilities on the basis of added value, rather than capital cost. Recent advances in the procurement of construction projects have emphasised a whole-life value approach to meeting the client’s objectives, with strategies put in place to encourage long-term commitment and through-life service provision. Construction firms are therefore increasingly required to take on responsibility for the operation and maintenance of the construction project on the client’s behalf - with the emphasis on value and service. This inevitably throws up a host of challenges, not the least of which is the need for construction firms to manage and accommodate the new emphasis on service. Indeed, these ‘service-led’ projects represent a new realm of construction projects where the rationale for the project is driven by client’s objectives with some aspect of service provision. This vision of downstream service delivery increases the number of stakeholders, adds to project complexity and challenges deeply-ingrained working practices. Ultimately it presents a major challenge for the construction sector. This paper sets out to unravel some of the many implications that this change brings with it. It draws upon ongoing research investigating how construction firms can adapt to a more service-orientated built environment and add value in project-based environments. The conclusions lay bare the challenges that firms face when trying to compete on the basis of added-value and service delivery. In particular, how it affects deeply-ingrained working practices and established relationships in the sector.

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In financial decision-making processes, the adopted weights of the objective functions have significant impacts on the final decision outcome. However, conventional rating and weighting methods exhibit difficulty in deriving appropriate weights for complex decision-making problems with imprecise information. Entropy is a quantitative measure of uncertainty and has been useful in exploring weights of attributes in decision making. A fuzzy and entropy-based mathematical approach is employed to solve the weighting problem of the objective functions in an overall cash-flow model. The multiproject being undertaken by a medium-size construction firm in Hong Kong was used as a real case study to demonstrate the application of entropy. Its application in multiproject cash flow situations is demonstrated. The results indicate that the overall before-tax profit was HK$ 0.11 millions lower after the introduction of appropriate weights. In addition, the best time to invest in new projects arising from positive cash flow was identified to be two working months earlier than the nonweight system.

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A very efficient learning algorithm for model subset selection is introduced based on a new composite cost function that simultaneously optimizes the model approximation ability and model robustness and adequacy. The derived model parameters are estimated via forward orthogonal least squares, but the model subset selection cost function includes a D-optimality design criterion that maximizes the determinant of the design matrix of the subset to ensure the model robustness, adequacy, and parsimony of the final model. The proposed approach is based on the forward orthogonal least square (OLS) algorithm, such that new D-optimality-based cost function is constructed based on the orthogonalization process to gain computational advantages and hence to maintain the inherent advantage of computational efficiency associated with the conventional forward OLS approach. Illustrative examples are included to demonstrate the effectiveness of the new approach.

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A connection between a fuzzy neural network model with the mixture of experts network (MEN) modelling approach is established. Based on this linkage, two new neuro-fuzzy MEN construction algorithms are proposed to overcome the curse of dimensionality that is inherent in the majority of associative memory networks and/or other rule based systems. The first construction algorithm employs a function selection manager module in an MEN system. The second construction algorithm is based on a new parallel learning algorithm in which each model rule is trained independently, for which the parameter convergence property of the new learning method is established. As with the first approach, an expert selection criterion is utilised in this algorithm. These two construction methods are equivalent in their effectiveness in overcoming the curse of dimensionality by reducing the dimensionality of the regression vector, but the latter has the additional computational advantage of parallel processing. The proposed algorithms are analysed for effectiveness followed by numerical examples to illustrate their efficacy for some difficult data based modelling problems.

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A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.

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Neurofuzzy modelling systems combine fuzzy logic with quantitative artificial neural networks via a concept of fuzzification by using a fuzzy membership function usually based on B-splines and algebraic operators for inference, etc. The paper introduces a neurofuzzy model construction algorithm using Bezier-Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as the non-negativity of the basis functions, and unity of support but with the additional advantages of structural parsimony and Delaunay input space partitioning, avoiding the inherent computational problems of lattice networks. This new modelling network is based on the idea that an input vector can be mapped into barycentric co-ordinates with respect to a set of predetermined knots as vertices of a polygon (a set of tiled Delaunay triangles) over the input space. The network is expressed as the Bezier-Bernstein polynomial function of barycentric co-ordinates of the input vector. An inverse de Casteljau procedure using backpropagation is developed to obtain the input vector's barycentric co-ordinates that form the basis functions. Extension of the Bezier-Bernstein neurofuzzy algorithm to n-dimensional inputs is discussed followed by numerical examples to demonstrate the effectiveness of this new data based modelling approach.

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The paper provides details of the size and scope of construction research carried out in a number of architecture, civil engineering and building related departments in British universities. After considering the level of funding, the type of research projects undertaken and the resulting outputs, especially how these benefit industry, the paper focuses on the careers of academics and researchers and the way in which research is organized at university, departmental and team levels. Finally, the paper suggests that whilst the construction research community in universities has many strengths, there is a danger that in responding to recent opportunities it may overreach itself. The end result may be disappointing for all parties involved. Some of the factors which would contribute to an effective approach to the development of links between universities and industry are discussed.

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Lean construction is considered from a human resource management (HRM) perspective. It is contended that the UK construction sector is characterised by an institutionalised regressive approach to HRM. In the face of rapidly declining recruitment rates for built environment courses, the dominant HRM philosophy of utilitarian instrumentalism does little to attract the intelligent and creative young people that the industry so badly needs. Given this broader context, there is a danger that an uncritical acceptance of lean construction will exacerbate the industry's reputation for unrewarding jobs. Construction academics have strangely ignored the extensive literature that equates lean production to a HRM regime of control, exploitation and surveillance. The emphasis of lean thinking on eliminating waste and improving efficiency makes it easy to absorb into the best practice agenda because it conforms to the existing dominant way of thinking. 'Best practice' is seemingly judged by the extent to which it serves the interests of the industry's technocratic elite. Hence it acts as a conservative force in favour of maintaining the status quo. In this respect, lean construction is the latest manifestation of a long established trend. In common with countless other improvement initiatives, the rhetoric is heavy in the machine metaphor whilst exhorting others to be more efficient. If current trends in lean construction are extrapolated into the future the ultimate destination may be uncomfortably close to Aldous Huxley's apocalyptic vision of a Brave New World. In the face of these trends, the lean construction research community pleads neutrality whilst confining its attention to the rational high ground. The future of lean construction is not yet predetermined. Many choices remain to be made. The challenge for the research community is to improve practice whilst avoiding the dehumanising tendencies of high utilitarianism.

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The stereoselective construction of complex molecules with multiple stereogenicity in a single step represents an extremely useful, but challenging approach to complexity in chemical synthesis. The development of organocatalytic cascade processes has proven useful in these studies, but reports where four or more stereocentres are created in a single step from just two achiral reagents are rare. Herein we report the development of a novel asymmetric domino Michael-Michael reaction between nitrohex-4-enoates and nitro-olefins to generate cyclohexanes of high complexity, including one with a quaternary centre, and one with five contiguous stereocentres. This methodology provides access to a range of useful nitrocyclohexane derivatives, including a novel class of a-lycorane-like structures.

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In the early 2000s the threat of Highly Pathogenic Avian Influenza captured the attention of the world's media. While China is often considered the epicentre of the panzootic, few studies have explored coverage of this variant of avian flu in China. To address this issue, the authors examined the portrayal of Highly Pathogenic Avian Influenza across four Chinese newspapers at the local and national level. A textual analysis was performed on 160 articles across an eight-year period from 2001–2008. The study approach drew from Critical Discourse Analysis and Social Representation Theory. The headline analysis showed the extent that risk of the disease was subverted by the depiction of a strong and efficient ‘China’ that was a global leader in the fight against the disease. Ideological referents were called upon to stress teamwork in confronting the crisis. The diachronic analysis illustrated how the relationship between commercial interests, science and public health risks played out within the Chinese media.

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Hospitals represent complex and difficult contexts for AEC (architecture, engineering and construction) professionals to engage with due to their functional complexity and diversity of stakeholder interests (i.e. patient, visitor, medical specialist). Hospital designers need to take note of changing NHS policy contexts (e.g. the possible empowerment of general practitioners to shape services), technological advances in medical equipment design and the potential health needs of future generations. It is imperative for hospital designers and architects to align their processes and methodologies (e.g. briefing and requirements capture) to the needs and desires of their clients so that a medical facility design is produced which is truly aligned to the requirements of the hospital stakeholders. Semiotics, the “study” or “discipline” of signs aims to investigate the nature of signs (their inception, representation and meaning), whilst semiotics-rooted theories are concerned with investigating how meaning and understanding is mobilized between persons and between organisations. This paper details a semiotics-rooted research approach for investigating the interactions between hospital designers and stakeholders on a forthcoming NHS hospital project in the UK. A semiotics grounded study will potentially provide a deeper understanding of how meaning and understanding is established between hospital project stakeholders and construction professionals.