863 resultados para Representation Construction Approach


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Purpose The purpose of this paper is to examine equal employment policies in Australia’s male-dominated construction industry and categorise the types of activities undertaken against an equal employment typology to identify links to outcomes for women in the form of increased participation and management. Design/methodology/approach To explore the issue of low representation of women in construction through the content analysis of 83 construction organisations’ equal employment opportunity (EEO) reports. Findings This industry is not engaging with equal employment issues and the numbers of women working in the industry and/or management are based on individual decision rather than an institutional commitment to equality in diversity. Research limitations/implications Australian legislation mandates organisational reporting of relevant data and offers public access to this information offering a unique data set. Practical implications An ageing population means that the predominately older male workforce is leaving construction in greater numbers with fewer potential replacements making new labour markets a vital consideration. Social implications Legislation and organisational policies designed to promote EEO for women have existed in numerous countries for decades. One objective of this legislation was to reduce male domination in senior positions and industries/occupations where women were under-represented. Despite this, few women are employed in construction in operational or management roles worldwide. Originality/value This study offers a comprehensive analysis of a male-dominated industry in one jurisdiction rather than a few selected cases and uses a broader rigorous typology for analysis that acknowledges both equal and different treatment options.

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Process view technology is catching more attentions in modern business process management, as it enables the customisation of business process representation. This capability helps improve the privacy protection, authority control, flexible display, etc., in business process modelling. One of approaches to generate process views is to allow users to construct an aggregate on their underlying processes. However, most aggregation approaches stick to a strong assumption that business processes are always well-structured, which is over strict to BPMN. Aiming to build process views for non-well-structured BPMN processes, this paper investigates the characteristics of BPMN structures, tasks, events, gateways, etc., and proposes a formal process view aggregation approach to facilitate BPMN process view creation. A set of consistency rules and construction rules are defined to regulate the aggregation and guarantee the order preservation, structural and behaviour correctness and a novel aggregation technique, called EP-Fragment, is developed to tackle non-well-structured BPMN processes.

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Major infrastructure and construction (MIC) projects are those with significant traffic or environmental impact, of strategic and regional significance and high sensitivity. The decision making process of schemes of this type is becoming ever more complicated, especially with the increasing number of stakeholders involved and their growing tendency to defend their own varied interests. Failing to address and meet the concerns and expectations of stakeholders may result in project failures. To avoid this necessitates a systematic participatory approach to facilitate decision-making. Though numerous decision models have been established in previous studies (e.g. ELECTRE methods, the analytic hierarchy process and analytic network process) their applicability in the decision process during stakeholder participation in contemporary MIC projects is still uncertain. To resolve this, the decision rule approach is employed for modeling multi-stakeholder multi-objective project decisions. Through this, the result is obtained naturally according to the “rules” accepted by any stakeholder involved. In this sense, consensus is more likely to be achieved since the process is more convincing and the result is easier to be accepted by all concerned. Appropriate “rules”, comprehensive enough to address multiple objectives while straightforward enough to be understood by multiple stakeholders, are set for resolving conflict and facilitating consensus during the project decision process. The West Kowloon Cultural District (WKCD) project is used as a demonstration case and a focus group meeting is conducted in order to confirm the validity of the model established. The results indicate that the model is objective, reliable and practical enough to cope with real world problems. Finally, a suggested future research agenda is provided.

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The delivery of products and services for construction-based businesses is increasingly becoming knowledge-driven and information-intensive. The proliferation of building information modelling (BIM) has increased business opportunities as well as introduced new challenges for the architectural, engineering and construction and facilities management (AEC/FM) industry. As such, the effective use, sharing and exchange of building life cycle information and knowledge management in building design, construction, maintenance and operation assumes a position of paramount importance. This paper identifies a subset of construction management (CM) relevant knowledge for different design conditions of building components through a critical, comprehensive review of synthesized literature and other information gathering and knowledge acquisition techniques. It then explores how such domain knowledge can be formalized as ontologies and, subsequently, a query vocabulary in order to equip BIM users with the capacity to query digital models of a building for the retrieval of useful and relevant domain-specific information. The formalized construction knowledge is validated through interviews with domain experts in relation to four case study projects. Additionally, retrospective analyses of several design conditions are used to demonstrate the soundness (realism), completeness, and appeal of the knowledge base and query-based reasoning approach in relation to the state-of-the-art tools, Solibri Model Checker and Navisworks. The knowledge engineering process and the methods applied in this research for information representation and retrieval could provide useful mechanisms to leverage BIM in support of a number of knowledge intensive CM/FM tasks and functions.

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A novel synthetic approach towards the recently reported anti-tumor and anti-tuberculor natural product ottelione A from the readily available Diels-Alder adduct of cyclopentadiene and p-benzoquinone is delineated. Our short strategy, besides being enantio-, regio- and stereoselective, charts an eventful course and is inherently well-suited for adaptation towards diverse synthetic analogues of this biologically potent natural product.

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Many knowledge based systems (KBS) transform a situation information into an appropriate decision using an in built knowledge base. As the knowledge in real world situation is often uncertain, the degree of truth of a proposition provides a measure of uncertainty in the underlying knowledge. This uncertainty can be evaluated by collecting `evidence' about the truth or falsehood of the proposition from multiple sources. In this paper we propose a simple framework for representing uncertainty in using the notion of an evidence space.

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Analytical solution is presented to convert a given driving-point impedance function (in s-domain) into a physically realisable ladder network with inductive coupling between any two sections and losses considered. The number of sections in the ladder network can vary, but its topology is assumed fixed. A study of the coefficients of the numerator and denominator polynomials of the driving-point impedance function of the ladder network, for increasing number of sections, led to the identification of certain coefficients, which exhibit very special properties. Generalised expressions for these specific coefficients have also been derived. Exploiting their properties, it is demonstrated that the synthesis method essentially turns out to be an exercise of solving a set of linear, simultaneous, algebraic equations, whose solution directly yields the ladder network elements. The proposed solution is novel, simple and guarantees a unique network. Presently, the formulation can synthesise a unique ladder network up to six sections.

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In a study directed toward the bioactive natural product garsubellin A, an expedient route to the bicyclo 3.3.1]nonan-9-one bearing tricyclic core, with a bridgehead anchored tetrahydrofuran ring, is delineated. The approach emanating from commercially available dimedone involved a DIBAL-H mediated retro aldol/re-aldol cyclization cascade and a PCC mediated oxidative cyclization as the key steps. (C) 2013 Elsevier Ltd. All rights reserved.

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Real-time object tracking is a critical task in many computer vision applications. Achieving rapid and robust tracking while handling changes in object pose and size, varying illumination and partial occlusion, is a challenging task given the limited amount of computational resources. In this paper we propose a real-time object tracker in l(1) framework addressing these issues. In the proposed approach, dictionaries containing templates of overlapping object fragments are created. The candidate fragments are sparsely represented in the dictionary fragment space by solving the l(1) regularized least squares problem. The non zero coefficients indicate the relative motion between the target and candidate fragments along with a fidelity measure. The final object motion is obtained by fusing the reliable motion information. The dictionary is updated based on the object likelihood map. The proposed tracking algorithm is tested on various challenging videos and found to outperform earlier approach.

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Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of 2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.

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Visual tracking is an important task in various computer vision applications including visual surveillance, human computer interaction, event detection, video indexing and retrieval. Recent state of the art sparse representation (SR) based trackers show better robustness than many of the other existing trackers. One of the issues with these SR trackers is low execution speed. The particle filter framework is one of the major aspects responsible for slow execution, and is common to most of the existing SR trackers. In this paper,(1) we propose a robust interest point based tracker in l(1) minimization framework that runs at real-time with performance comparable to the state of the art trackers. In the proposed tracker, the target dictionary is obtained from the patches around target interest points. Next, the interest points from the candidate window of the current frame are obtained. The correspondence between target and candidate points is obtained via solving the proposed l(1) minimization problem. In order to prune the noisy matches, a robust matching criterion is proposed, where only the reliable candidate points that mutually match with target and candidate dictionary elements are considered for tracking. The object is localized by measuring the displacement of these interest points. The reliable candidate patches are used for updating the target dictionary. The performance and accuracy of the proposed tracker is benchmarked with several complex video sequences. The tracker is found to be considerably fast as compared to the reported state of the art trackers. The proposed tracker is further evaluated for various local patch sizes, number of interest points and regularization parameters. The performance of the tracker for various challenges including illumination change, occlusion, and background clutter has been quantified with a benchmark dataset containing 50 videos. (C) 2014 Elsevier B.V. All rights reserved.

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Human detection is a complex problem owing to the variable pose that they can adopt. Here, we address this problem in sparse representation framework with an overcomplete scale-embedded dictionary. Histogram of oriented gradient features extracted from the candidate image patches are sparsely represented by the dictionary that contain positive bases along with negative and trivial bases. The object is detected based on the proposed likelihood measure obtained from the distribution of these sparse coefficients. The likelihood is obtained as the ratio of contribution of positive bases to negative and trivial bases. The positive bases of the dictionary represent the object (human) at various scales. This enables us to detect the object at any scale in one shot and avoids multiple scanning at different scales. This significantly reduces the computational complexity of detection task. In addition to human detection, it also finds the scale at which the human is detected due to the scale-embedded structure of the dictionary.

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This document lists the undesirable effects of water hyacinth (Eichhornia crassipes) on fisheries in Lake Kainji (Nigeria) and the integrated Water Hyacinth Control Programme in its ongoing fisheries management and development activities on the lake. Special regard is given to the design, construction and installation of a water hyacinth barrier across the River Niger. (PDF contains 44 pages)