Cognitive reliability and error analysis method (CREAM) has been developed and gradually complemented with novel quantitative techniques to enhance its inherent perspective human error probability (HEP) analysis. Whil...
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Cognitive reliability and error analysis method (CREAM) has been developed and gradually complemented with novel quantitative techniques to enhance its inherent perspective human error probability (HEP) analysis. While some probabilistic models are used to improve the accuracy of analyzing HEP, they ignore the characteristics of the easiness, visibility and integrity of the traditional deterministic method in CREAM. This paper aims to establish a novel Bayesian network model, which is capable of providing the instant and precise estimate of HEP given the updated information about a dynamic context without compromising the easiness and visibility features of the traditional method. The mathematical procedure of developing the Bayesian network is described in a 6-step methodology, including definition of primary effects of common performance conditions (CPCs), adjustment of dependency of CPCs, new grouping of CPCs, distributions of prior conditional probabilities, integration of positive and negative CPCs and estimate of HEP. Main contributions of this paper lie in its original intention of eliminating irrelevant neutral primary effects in the process of adjusting CPC dependency and separately treating the numbers of positive and negative effects of CPCs. The proposed quantitative HEP analysis methodology can be widely applied to various industries to facilitate the associated human error reduction and operational safety improvement.
This paper advocates an approach to requirements analysis drawing on social scientific research strategies (Ethnography) and model based engineering (MBE). Our work is aimed at bridging the gap between applied ethnogr...
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This paper advocates an approach to requirements analysis drawing on social scientific research strategies (Ethnography) and model based engineering (MBE). Our work is aimed at bridging the gap between applied ethnographic reports and the early stages of the software development lifecycle (SDLC). Taking a view on how we think data should be represented at the requirements level, we demonstrate an approach to modeling and documenting requirement-centric ethnographic reports based on linguistic statements and humanbehaviour. The work is particularly oriented towards documenting requirements for `data'. We make an arguement on what types of information should be included in requirements level data schemas. Our methodology looks at an established ethnographic study in order to elucidate problems that you find with standard requirements models. Our solution is to extend UML with so called Tacit Contracts that enhance requirements-level data schemas by highlighting tacit information to do with the composition and characteristics of the data being described. The tacit contract then requires system designers at latter phases of the SDLC to also take into account information expressed as tacit in the requirements models when making design decisions about the system.
humanbehaviour plays an important role in the spread of infectious diseases, and understanding the influence of behaviour on the spread of diseases can be key to improving control efforts. While behavioural responses...
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humanbehaviour plays an important role in the spread of infectious diseases, and understanding the influence of behaviour on the spread of diseases can be key to improving control efforts. While behavioural responses to the spread of a disease have often been reported anecdotally, there has been relatively little systematic investigation into how behavioural changes can affect disease dynamics. mathematical models for the spread of infectious diseases are an important tool for investigating and quantifying such effects, not least because the spread of a disease among humans is not amenable to direct experimental study. Here, we review recent efforts to incorporate humanbehaviour into disease models, and propose that such models can be broadly classified according to the type and source of information which individuals are assumed to base their behaviour on, and according to the assumed effects of such behaviour. We highlight recent advances as well as gaps in our understanding of the interplay between infectious disease dynamics and humanbehaviour, and suggest what kind of data taking efforts would be helpful in filling these gaps.
Mathematics-based computational mechanics involves idealization in going from the observed behaviour of a system into mathematical equations representing the underlying mechanics of that behaviour. Idealization may le...
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Mathematics-based computational mechanics involves idealization in going from the observed behaviour of a system into mathematical equations representing the underlying mechanics of that behaviour. Idealization may lead mathematical models that exclude certain aspects of the complex behaviour that may be significant. An alternative approach is data-centric modelling that constitutes a fundamental shift from mathematical equations to data that contain the required information about the underlying mechanics. However, purely data-centric methods often fail for infrequent events and large state changes. In this article, a new hybrid modelling framework is proposed to improve accuracy in simulation of real-world systems. In the hybrid framework, a mathematical model is complemented by information-based components. The role of informational components is to model aspects which the mathematical model leaves out. The missing aspects are extracted and identified through Autoprogressive Algorithms. The proposed hybrid modelling framework has a wide range of potential applications for natural and engineered systems. The potential of the hybrid methodology is illustrated through modelling highly pinched hysteretic behaviour of beam-to-column connections in steel frames.
Climate change is the major problem that every human being is facing over the world. The rise in fossil fuel usage increases the emission of 'greenhouse' gases, particularly carbon dioxide continuously into th...
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Climate change is the major problem that every human being is facing over the world. The rise in fossil fuel usage increases the emission of 'greenhouse' gases, particularly carbon dioxide continuously into the earth's atmosphere. This causes a rise in the amount of heat from the sun withheld in the earth's atmosphere that would normally radiated back into space. This increase in heat has led to the greenhouse effect, resulting in climate change and rise in temperature along with other climatological parameters directly affects evaporation losses. Accurate modelling and forecasting of these evaporation losses are important for preventing further effects due to climate change. Evaporation is purely non-linear and varying both spatially and temporally. This needs suitable data driven approach to model and should have the ability to take care of all these non-linear behaviour of the system. As such, though there are many empirical and analytical models suggested in the literature for the estimation of evaporation losses, such models should be used with care and caution. Further, difficulties arise in obtaining all the climatological data used in a given analytical or empirical model. Genetic programming (GP) is one such technique applied where the non-linearity exist. GP has the flexible mathematical structure which is capable of identifying the non-linear relationship between input and output data sets. Thus, it is easy to construct 'local' models for estimating evaporation losses. The performance of GP model is compared with Thornthwaite method, and results from the study indicate that the GP model performed better than the Thornthwaite method. Forecasting of meteorological parameters such as temperature, relative humidity and wind velocity has been performed using Markovian chain series analysis subsequently it is used to estimate the future evaporation losses using developed GP model. Finally the effect of possible future climate change on evaporation losses in Pil
Steam assisted gravity drainage (SAGD) is a thermal oil recovery technique which has been used mostly for Alberta's unconventional oil sands reservoirs. Roger Butler, known as the father of SAGD, was the first one...
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Steam assisted gravity drainage (SAGD) is a thermal oil recovery technique which has been used mostly for Alberta's unconventional oil sands reservoirs. Roger Butler, known as the father of SAGD, was the first one to establish a theory and an analytical model for SAGD. His model is a rigorous solution and is widely referred to as a SAGD fast flow simulator. However, geomechanics, which has been shown to be a relevant part of SAGD's physics, has not been included in the model. When rock properties are influenced by geomechanical behaviour, the Butler theory is not able to capture the complete physics of the SAGD process. In such cases, the model must adopt unrealistic or high values for rock properties. In this study, a classical theory in the field of geotechnical engineering (limit equilibrium) is employed to act as the geomechanical module for SAGD's mathematical coupled simulation. The Butler/Reis model has also been Unproved using a model of slices for flow simulation. Methodology of combining these two models in a single coupled mathematical simulator is presented in this paper. The solver is a fast and realistic proxy and can be used as a low-order tool for history matching. The results of coupled simulations show that the model is able to predict permeability and porosity of the reservoir closer to real values than uncoupled (flow only) modelling.
This paper presents mathematicalmodelling of a single-link flexible manipulator in vertical plane motion. This extends the previously developed mathematical model for motion in the horizontal plane, where the effects...
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ISBN:
(纸本)9814291269
This paper presents mathematicalmodelling of a single-link flexible manipulator in vertical plane motion. This extends the previously developed mathematical model for motion in the horizontal plane, where the effects of gravity, rotary inertia and shear deformation were ignored. The dynamic model of the system is obtained using the Lagrange equation. The finite difference method is used to transform this into a discrete formulation. The dynamic behaviour of the system in vertical motion is studied using the developed algorithm. Simulation results of the response of the manipulator are assessed in comparison to corresponding theoretical ones in the time and the frequency domains to verify the accuracy of the algorithm in characterizing the behaviour of the flexible manipulator system.
human activity recognition is an active research field in computer vision and image processing. This paper has been concentrated on the recognition between different cyclic motion activities such as running and walkin...
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Bioengineering features of native vegetation are currently being evolved to enhance soil stiffness, slope stabilisation and erosion control. The effects of tree roots on soil moisture content and ground settlement are...
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Bioengineering features of native vegetation are currently being evolved to enhance soil stiffness, slope stabilisation and erosion control. The effects of tree roots on soil moisture content and ground settlement are discussed in this paper. Matric suction induced by tree roots is a key factor, governing the properties of unsaturated soils, directly imparting stability to slopes and resistance for yielding behaviour. A mathematical model for the rate of root water uptake that considers ground conditions, type of vegetation and climatic parameters has been developed. This study highlights the inter-related parameters contributing to the development of a conceptual evapo-transpiration and root moisture uptake equilibrium model that is then incorporated in a comprehensive numerical finite element model. The developed model considers fully coupled-flow-deformation behaviour of soil. Field measurements obtained by the Authors from a site in Victoria, South of Australia, are used to validate the model. In this study, the active tree root distribution has been predicted by measuring soil organic content distribution. The predicted results show acceptable agreement with the field data in spite of the assumptions made for simplifying the effects of soil heterogeneity and anisotropy. The results prove that the proposed root water uptake model can reliably predict the region of the maximum matric suction away from the tree axis. (C) 2009 Elsevier B.V. All rights reserved.
This paper describe the development of a flexible plate structure rig for the implementation of active vibration control algorithm. The experimental rig is designed as an apparatus to create vibration along the flexib...
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