241 resultados para 2447: modelling and forecasting


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Digital human modelling (DHM) has today matured from research into industrial application. In the automotive domain, DHM has become a commonly used tool in virtual prototyping and human-centred product design. While this generation of DHM supports the ergonomic evaluation of new vehicle design during early design stages of the product, by modelling anthropometry, posture, motion or predicting discomfort, the future of DHM will be dominated by CAE methods, realistic 3D design, and musculoskeletal and soft tissue modelling down to the micro-scale of molecular activity within single muscle fibres. As a driving force for DHM development, the automotive industry has traditionally used human models in the manufacturing sector (production ergonomics, e.g. assembly) and the engineering sector (product ergonomics, e.g. safety, packaging). In product ergonomics applications, DHM share many common characteristics, creating a unique subset of DHM. These models are optimised for a seated posture, interface to a vehicle seat through standardised methods and provide linkages to vehicle controls. As a tool, they need to interface with other analytic instruments and integrate into complex CAD/CAE environments. Important aspects of current DHM research are functional analysis, model integration and task simulation. Digital (virtual, analytic) prototypes or digital mock-ups (DMU) provide expanded support for testing and verification and consider task-dependent performance and motion. Beyond rigid body mechanics, soft tissue modelling is evolving to become standard in future DHM. When addressing advanced issues beyond the physical domain, for example anthropometry and biomechanics, modelling of human behaviours and skills is also integrated into DHM. Latest developments include a more comprehensive approach through implementing perceptual, cognitive and performance models, representing human behaviour on a non-physiologic level. Through integration of algorithms from the artificial intelligence domain, a vision of the virtual human is emerging.

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The automotive industry has been the focus of digital human modeling (DHM) research and application for many years. In the highly competitive marketplace for personal transportation, the desire to improve the customer’s experience has driven extensive research in both the physical and cognitive interaction between the vehicle and its occupants. Human models provide vehicle designers with tools to view and analyze product interactions before the first prototypes are built, potentially improving the design while reducing cost and development time. The focus of DHM research and applications began with prediction and representation of static postures for purposes of driver workstation layout, including assessments of seat adjustment ranges and exterior vision. Now DHMs are used for seat design and assessment of driver reach and ingress/egress. DHMs and related simulation tools are expanding into the cognitive domain, with computational models of perception and motion, and into the dynamic domain with models of physical responses to ride and vibration. Moreover, DHMs are now widely used to analyze the ergonomics of vehicle assembly tasks. In this case, the analysis aims to determine whether workers can be expected to complete the tasks safely and with good quality. This preface provides a review of the literature to provide context for the nine new papers presented in this special issue.

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This paper employs a VAR-GARCH model to investigate the return links and volatility transmission between the S&P 500 and commodity price indices for energy, food, gold and beverages over the turbulent period from 2000 to 2011. Understanding the price behavior of commodity prices and the volatility transmission mechanism between these markets and the stock exchanges are crucial for each participant, including governments, traders, portfolio managers, consumers, and producers. For return and volatility spillover, the results show significant transmission among the S&P 500 and commodity markets. The past shocks and volatility of the S&P 500 strongly influenced the oil and gold markets. This study finds that the highest conditional correlations are between the S&P 500 and gold index and the S&P 500 and WTI index. We also analyze the optimal weights and hedge ratios for commodities/S&P 500 portfolio holdings using the estimates for each index. Overall, our findings illustrate several important implications for portfolio hedgers for making optimal portfolio allocations, engaging in risk management and forecasting future volatility in equity and commodity markets. © 2013 Elsevier B.V.

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Purpose Food refusal is part of normal toddler development due to an innate ability to self-regulate energy intake and the onset of neophobia. For parents, this ‘fussy’ stage causes great concern, prompting use of coercive feeding practices which ignore a child’s own hunger and satiety cues, promoting overeating and overweight. This analysis defines characteristics of the ‘good eater’ using latent variable structural equation modelling and the relationship with maternal perception of her child as a fussy eater. Methods Mothers in the control group of the NOURISH and South Australian Infants Dietary Intake studies (n=332) completed a self-administered questionnaire - when child was age 12-16 months - describing refusal of familiar and unfamiliar foods and maternal perception as fussy/not fussy. Weight-for-age z-score (WAZ) was derived from weight measured by study staff. Questionnaire items and WAZ were combined in AMOS to represent the latent variable the ‘good eater’. Results/findings Mean age(sd) of children was 13.8(1.3) months, mean WAZ(sd), .58(.86) and 49% were male. The ‘good eater’ was represented by higher WAZ, a child that hardly ever refuses food, hardly ever refuses familiar food, and willing to eat unfamiliar foods (x2/df=2.80, GFI=.98, RMSEA=.07(.03-.12), CFI=.96). The ‘good eater’ was inversely associated with maternal perception of her child as a fussy eater (β=-.64, p<.05). Conclusions Toddlers displaying characteristics of a ‘good eater’ are not perceived as fussy, but these characteristics, especially higher WAZ, may be undesirable in the context of obesity prevention. Clinicians can promote food refusal as normal and even desirable in healthy young children.

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Ensuring adequate water supply to urban areas is a challenging task due to factors such as rapid urban growth, increasing water demand and climate change. In developing a sustainable water supply system, it is important to identify the dominant water demand factors for any given water supply scheme. This paper applies principal components analysis to identify the factors that dominate residential water demand using the Blue Mountains Water Supply System in Australia as a case study. The results show that the influence of community intervention factors (e.g. use of water efficient appliances and rainwater tanks) on water demand are among the most significant. The result also confirmed that the community intervention programmes and water pricing policy together can play a noticeable role in reducing the overall water demand. On the other hand, the influence of rainfall on water demand is found to be very limited, while temperature shows some degree of correlation with water demand. The results of this study would help water authorities to plan for effective water demand management strategies and to develop a water demand forecasting model with appropriate climatic factors to achieve sustainable water resources management. The methodology developed in this paper can be adapted to other water supply systems to identify the influential factors in water demand modelling and to devise an effective demand management strategy.

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Bomb attacks carried out by terrorists, targeting high occupancy buildings, have become increasingly common in recent times. Large numbers of casualties and property damage result from overpressure of the blast followed by failing of structural elements. Understanding the blast response of multi-storey buildings and evaluating their remaining life have therefore become important. Response and damage analysis of single structural components, such as columns or slabs, to explosive loads have been examined in the literature, but the studies on blast response and damage analysis of structural frames in multi-storey buildings is limited and this is necessary for assessing the vulnerability of them. This paper investigates the blast response and damage evaluation of reinforced concrete (RC) frames, designed for normal gravity loads, in order to evaluate their remaining life. Numerical modelling and analysis were carried out using the explicit finite element software, LS DYNA. The modelling and analysis takes into consideration reinforcement details together and material performance under higher strain rates. Damage indices for columns are calculated based on their residual and original capacities. Numerical results generated in the can be used to identify relationships between the blast load parameters and the column damage. Damage index curve will provide a simple means for assessing the damage to a typical multi-storey building RC frame under an external bomb circumstance.

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Purpose Waiting for service by customers is an important problem for many financial service marketers. Two new approaches are proposed. First, customer evaluation of the service is increased with an ambient scent. Second a cognitive variable is identified which different iates customers by the way they value time so that they can be segmented. Methodology Pretests included focus groups which highlighted financial services and a pilot test were foll owed by a main sample of 607 subjects. Structural equation modelling and multivariate analysis of covariance were used for analysis. Findings A cognitive variable, the need for time management can be used, together with demographic and customer net worth data, to segment a customer base. Two environmental interventions, music and scent, can increase customer satisfaction among customers kept waiting in a line. Research implications Two original approaches to a rapidly growing service marketing problem are identified. Practical implications Service contact points can reduce incidence of "queue rage" and enhance customer satisfaction by either or both of two simple modifications to the service environment or a preventive strategy of offering targeted customers an alternative. Originality A new method of segmentation and a new environmental intervention are proposed .

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For certain continuum problems, it is desirable and beneficial to combine two different methods together in order to exploit their advantages while evading their disadvantages. In this paper, a bridging transition algorithm is developed for the combination of the meshfree method (MM) with the finite element method (FEM). In this coupled method, the meshfree method is used in the sub-domain where the MM is required to obtain high accuracy, and the finite element method is employed in other sub-domains where FEM is required to improve the computational efficiency. The MM domain and the FEM domain are connected by a transition (bridging) region. A modified variational formulation and the Lagrange multiplier method are used to ensure the compatibility of displacements and their gradients. To improve the computational efficiency and reduce the meshing cost in the transition region, regularly distributed transition particles, which are independent of either the meshfree nodes or the FE nodes, can be inserted into the transition region. The newly developed coupled method is applied to the stress analysis of 2D solids and structures in order to investigate its’ performance and study parameters. Numerical results show that the present coupled method is convergent, accurate and stable. The coupled method has a promising potential for practical applications, because it can take advantages of both the meshfree method and FEM when overcome their shortcomings.

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Vendors provide reference process models as consolidated, off-the-shelf solutions to capture best practices in a given industry domain. Customers can then adapt these models to suit their specific requirements. Traditional process flexibility approaches facilitate this operation, but do not fully address it as they do not sufficiently take controlled change guided by vendors' reference models into account. This tension between the customer's freedom of adapting reference models, and the ability to incorporate with relatively low effort vendor-initiated reference model changes, thus needs to be carefully balanced. This paper introduces process extensibility as a new paradigm for customizing reference processes and managing their evolution over time. Process extensibility mandates a clear recognition of the different responsibilities and interests of reference model vendors and consumers, and is concerned with keeping the effort of customer-side reference model adaptations low while allowing sufficient room for model change.

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Orthopaedics and Trauma Queensland is an internationally recognised research group that is developing into an international leader in research and education. It provides a stimulus for research, education and clinical application within the international orthopaedic and trauma communities. Orthopaedics and Trauma Queensland develops and promotes the innovative use of engineering and technology, in collaboration with surgeons, to provide new techniques, materials, procedures and medical devices. Its integration with clinical practice and strong links with hospitals ensure that the research will be translated into practical outcomes for patients. The group undertakes clinical practice in orthopaedics and trauma and applies core engineering, modelling and clinical skills to challenges in medicine. The research is built on a strong foundation of knowledge in biomedical engineering and incorporates expertise in cell biology, mathematical modelling, human anatomy and physiology and clinical medicine in orthopaedics and trauma. New knowledge is being developed and applied to the full range of orthopaedic diseases and injuries, such as knee and hip replacements, fractures and spinal deformities.

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A study has been conducted to investigate current practices on decision-making under risk and uncertainty for infrastructure project investments. It was found that many European countries such as the UK, France, Germany including Australia use scenarios for the investigation of the effects of risk and uncertainty of project investments. Different alternative scenarios are mostly considered during the engineering economic cost-benefit analysis stage. For instance, the World Bank requires an analysis of risks in all project appraisals. Risk in economic evaluation needs to be addressed by calculating sensitivity of the rate of return for a number of events. Risks and uncertainties of project developments arise from various sources of errors including data, model and forecasting errors. It was found that the most influential factors affecting risk and uncertainty resulted from forecasting errors. Data errors and model errors have trivial effects. It was argued by many analysts that scenarios do not forecast what will happen but scenarios indicate only what can happen from given alternatives. It was suggested that the probability distributions of end-products of the project appraisal, such as cost-benefit ratios that take forecasting errors into account, are feasible decision tools for economic evaluation. Political, social, environmental as well as economic and other related risk issues have been addressed and included in decision-making frameworks, such as in a multi-criteria decisionmaking framework. But no suggestion has been made on how to incorporate risk into the investment decision-making process.