998 resultados para contracting functions


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Optimal design for generalized linear models has primarily focused on univariate data. Often experiments are performed that have multiple dependent responses described by regression type models, and it is of interest and of value to design the experiment for all these responses. This requires a multivariate distribution underlying a pre-chosen model for the data. Here, we consider the design of experiments for bivariate binary data which are dependent. We explore Copula functions which provide a rich and flexible class of structures to derive joint distributions for bivariate binary data. We present methods for deriving optimal experimental designs for dependent bivariate binary data using Copulas, and demonstrate that, by including the dependence between responses in the design process, more efficient parameter estimates are obtained than by the usual practice of simply designing for a single variable only. Further, we investigate the robustness of designs with respect to initial parameter estimates and Copula function, and also show the performance of compound criteria within this bivariate binary setting.

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The Australian construction industry is characterized as being a competitive and risky business environment due to lack of cooperation, insufficient trust, ineffective communication and adversarial relationships which are likely lead to poor project performance. Relational contracting (RC) is advocated by literature as an innovative approach to improve the procurement process in the construction industry. Various studies have collectively added to the current knowledge of known RC norms, but there seem to be little effort on investigating the determinants of RC and its efficacy on project outcomes. In such circumstances, there is a lack of evidence and explanation on the manner on how these issues lead to different performance. Simultaneously, the New Engineering Contract (NEC) that embraced the concept of RC is seen as a modern way of contracting and also considered as one of the best approaches to the perennial problem of improving adversarial relationships within the industry. The reality of practice of RC in Australia is investigated through the lens of the NEC. A synthesis of literature views on the concept, processes and tools of RC is first conducted to develop the framework of RC.

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Multivariate volatility forecasts are an important input in many financial applications, in particular portfolio optimisation problems. Given the number of models available and the range of loss functions to discriminate between them, it is obvious that selecting the optimal forecasting model is challenging. The aim of this thesis is to thoroughly investigate how effective many commonly used statistical (MSE and QLIKE) and economic (portfolio variance and portfolio utility) loss functions are at discriminating between competing multivariate volatility forecasts. An analytical investigation of the loss functions is performed to determine whether they identify the correct forecast as the best forecast. This is followed by an extensive simulation study examines the ability of the loss functions to consistently rank forecasts, and their statistical power within tests of predictive ability. For the tests of predictive ability, the model confidence set (MCS) approach of Hansen, Lunde and Nason (2003, 2011) is employed. As well, an empirical study investigates whether simulation findings hold in a realistic setting. In light of these earlier studies, a major empirical study seeks to identify the set of superior multivariate volatility forecasting models from 43 models that use either daily squared returns or realised volatility to generate forecasts. This study also assesses how the choice of volatility proxy affects the ability of the statistical loss functions to discriminate between forecasts. Analysis of the loss functions shows that QLIKE, MSE and portfolio variance can discriminate between multivariate volatility forecasts, while portfolio utility cannot. An examination of the effective loss functions shows that they all can identify the correct forecast at a point in time, however, their ability to discriminate between competing forecasts does vary. That is, QLIKE is identified as the most effective loss function, followed by portfolio variance which is then followed by MSE. The major empirical analysis reports that the optimal set of multivariate volatility forecasting models includes forecasts generated from daily squared returns and realised volatility. Furthermore, it finds that the volatility proxy affects the statistical loss functions’ ability to discriminate between forecasts in tests of predictive ability. These findings deepen our understanding of how to choose between competing multivariate volatility forecasts.

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In response to the need to leverage private finance and the lack of competition in some parts of the Australian public sector major infrastructure market, especially in very large economic infrastructure procured using Pubic Private Partnerships, the Australian Federal government has demonstrated its desire to attract new sources of in-bound foreign direct investment (FDI) into the Australian construction market. This paper aims to report on progress towards an investigation into the determinants of multinational contractors’ willingness to bid for Australian public sector major infrastructure projects and which is designed to give an improved understanding of matters surrounding FDI into the Australian construction sector. This research deploys Dunning’s eclectic theory for the first time in terms of in-bound FDI by multinational contractors and as head contractors bidding for Australian major infrastructure public sector projects. Elsewhere, the authors have developed Dunning’s principal hypothesis associated with his eclectic framework in order to suit the context of this research and to address a weakness arising in Dunning’s principal hypothesis that is based on a nominal approach to the factors in the eclectic framework and which fail to speak to the relative explanatory power of these factors. In this paper, an approach to reviewing and analysing secondary data, as part of the first stage investigation in this research, is developed and some illustrations given, vis-à-vis the selected sector (roads, bridges and tunnels) in Australia (as the host location) and using one of the selected home countries (Spain). In conclusion, some tentative thoughts are offered in anticipation of the completion of the first stage investigation - in terms of the extent to which this first stage based on secondary data only might suggest the relative importance of the factors in the eclectic framework. It is noted that more robust conclusions are expected following the future planned stages of the research and these stages including primary data are briefly outlined. Finally, and beyond theoretical contributions expected from the overall approach taken to developing and testing Dunning’s framework, other expected contributions concerning research method and practical implications are mentioned.

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In this study we set out to dissociate the developmental time course of automatic symbolic number processing and cognitive control functions in grade 1-3 British primary school children. Event-related potential (ERP) and behavioral data were collected in a physical size discrimination numerical Stroop task. Task-irrelevant numerical information was processed automatically already in grade 1. Weakening interference and strengthening facilitation indicated the parallel development of general cognitive control and automatic number processing. Relationships among ERP and behavioral effects suggest that control functions play a larger role in younger children and that automaticity of number processing increases from grade 1 to 3.

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In response to the need to leverage private finance and the lack of competition in some parts of the Australian public sector infrastructure market, especially in the very large economic infrastructure sector procured using Pubic Private Partnerships, the Australian Federal government has demonstrated its desire to attract new sources of in-bound foreign direct investment (FDI). This paper aims to report on progress towards an investigation into the determinants of multinational contractors’ willingness to bid for Australian public sector major infrastructure projects. This research deploys Dunning’s eclectic theory for the first time in terms of in-bound FDI by multinational contractors into Australia. Elsewhere, the authors have developed Dunning’s principal hypothesis to suit the context of this research and to address a weakness arising in this hypothesis that is based on a nominal approach to the factors in Dunning's eclectic framework and which fails to speak to the relative explanatory power of these factors. In this paper, a first stage test of the authors' development of Dunning's hypothesis is presented by way of an initial review of secondary data vis-à-vis the selected sector (roads and bridges) in Australia (as the host location) and with respect to four selected home countries (China; Japan; Spain; and US). In doing so, the next stage in the research method concerning sampling and case studies is also further developed and described in this paper. In conclusion, the extent to which the initial review of secondary data suggests the relative importance of the factors in the eclectic framework is considered. It is noted that more robust conclusions are expected following the future planned stages of the research including primary data from the case studies and a global survey of the world’s largest contractors and which is briefly previewed. Finally, and beyond theoretical contributions expected from the overall approach taken to developing and testing Dunning’s framework, other expected contributions concerning research method and practical implications are mentioned.

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This paper illustrates the damage identification and condition assessment of a three story bookshelf structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). A major obstacle of using measured frequency response function data is a large size input variables to ANNs. This problem is overcome by applying a data reduction technique called principal component analysis (PCA). In the proposed procedure, ANNs with their powerful pattern recognition and classification ability were used to extract damage information such as damage locations and severities from measured FRFs. Therefore, simple neural network models are developed, trained by Back Propagation (BP), to associate the FRFs with the damage or undamaged locations and severity of the damage of the structure. Finally, the effectiveness of the proposed method is illustrated and validated by using the real data provided by the Los Alamos National Laboratory, USA. The illustrated results show that the PCA based artificial Neural Network method is suitable and effective for damage identification and condition assessment of building structures. In addition, it is clearly demonstrated that the accuracy of proposed damage detection method can also be improved by increasing number of baseline datasets and number of principal components of the baseline dataset.

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Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

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Radial Hele-Shaw flows are treated analytically using conformal mapping techniques. The geometry of interest has a doubly-connected annular region of viscous fluid surrounding an inviscid bubble that is either expanding or contracting due to a pressure difference caused by injection or suction of the inviscid fluid. The zero-surface-tension problem is ill-posed for both bubble expansion and contraction, as both scenarios involve viscous fluid displacing inviscid fluid. Exact solutions are derived by tracking the location of singularities and critical points in the analytic continuation of the mapping function. We show that by treating the critical points, it is easy to observe finite-time blow-up, and the evolution equations may be written in exact form using complex residues. We present solutions that start with cusps on one interface and end with cusps on the other, as well as solutions that have the bubble contracting to a point. For the latter solutions, the bubble approaches an ellipse in shape at extinction.

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In response to the need to leverage private finance and the lack of competition in some parts of the Australian public sector infrastructure market, the Australian Federal government has demonstrated its desire to attract new sources of in-bound foreign direct investment (FDI) by multinational contractors. This study aims to update progress towards an investigation into the determinants of multinational contractors’ willingness to bid for Australian public sector major road and bridges. This research deploys Dunning’s eclectic theory for the first time in terms of in-bound FDI by multinational contractors into Australia. Elsewhere, the authors have developed Dunning’s principal hypothesis to suit the context of this research and to address a weakness arising in this hypothesis that is based on a nominal (yes or no) approach to the ownership, location and internalisation factors in Dunning's eclectic framework and which fails to speak to the relative explanatory power of these factors. The authors have completed a first stage test of this development of Dunning's hypothesis based on publically available secondary data, in which it was concluded tentatively that the location factor appears to have the greatest explanatory power. This paper aims to present, for the first time, a further and novel development of the operation of Dunning's eclectic paradigm within the context of multinational contracting, as well as a preview of the design and planned analysis of the next empirical stage in this research concerning case studies. Finally, and beyond the theoretical contributions expected, other expected contributions are mentioned concerning research method and practical implications.

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A community nurse is required to have excellent interpersonal, teaching, collaborative and clinical skills in order to develop effective individualised client care contracts. Using a descriptive qualitative design data was collected from two focus groups of fourteen community nurses to explore the issues surrounding negotiating and contracting client care contracts from the perspective of community nurses. Thematic analysis revealed three themes: ‘assessment of needs’, ‘education towards enablement’, and ‘negotiation’. ‘Assessment of needs’ identified that community nurses assess both the client’s requirements for health care as well as the ability of the nurse to provide that care. ‘Education towards enablement’ described that education of the client is a common strategy used by community nurses to establish realistic goals of health care as part of developing an ongoing care plan. The final theme, ‘negotiation’, involved an informed agreement between the client and the community nurse which forms the origin of the care contract that will direct the partnership between the client and the nurse. Of importance for community nurses is that development of successful person-centred care contracts requires skillful negotiation of care that strikes the balance between the needs of the client and the ability of the nurse to meet those needs.

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The research described in this paper forms part of an in-depth investigation of safety culture in one of Australia’s largest construction companies. The research builds on a previous qualitative study with organisational safety leaders and further investigates how safety culture is perceived and experienced by organisational members, as well as how this relates to their safety behaviour and related outcomes at work. Participants were 2273 employees of the case study organisation, with 689 from the Construction function and 1584 from the Resources function. The results of several analyses revealed some interesting organisational variance on key measures. Specifically, the Construction function scored significantly higher on all key measures: safety climate, safety motivation, safety compliance, and safety participation. The results are discussed in terms of relevance in an applied research context.

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In 1980 Alltop produced a family of cubic phase sequences that nearly meet the Welch bound for maximum non-peak correlation magnitude. This family of sequences were shown by Wooters and Fields to be useful for quantum state tomography. Alltop’s construction used a function that is not planar, but whose difference function is planar. In this paper we show that Alltop type functions cannot exist in fields of characteristic 3 and that for a known class of planar functions, x^3 is the only Alltop type function.