858 resultados para hidden Markov models (HMMs)
Resumo:
Groundwater is a major resource on Bribie Island and its sustainable management is essential to maintain the natural and modified eco-systems, as well as the human population and the integrity of the island as a sand mass. An effective numerical model is essential to enable predictions, and to test various water use and rainfall/climate scenarios. Such a numerical model must, however, be based on a representative conceptual hydrogeological model to allow incorporation of realistic controls and processes. Here we discuss the various hydrogeological models and parameters, and hydrological properties of the materials forming the island. We discuss the hydrological processes and how they can be incorporated into these models, in an integrated manner. Processes include recharge, discharge to wetlands and along the coastline, abstraction, evapotranspiration and potential seawater intrusion. The types and distributions of groundwater bores and monitoring are considered, as are scenarios for groundwater supply abstraction. Different types of numerical models and their applicability are also considered
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Finite Element Modeling (FEM) has become a vital tool in the automotive design and development processes. FEM of the human body is a technique capable of estimating parameters that are difficult to measure in experimental studies with the human body segments being modeled as complex and dynamic entities. Several studies have been dedicated to attain close-to-real FEMs of the human body (Pankoke and Siefert 2007; Amann, Huschenbeth et al. 2009; ESI 2010). The aim of this paper is to identify and appraise the state of-the art models of the human body which incorporate detailed pelvis and/or lower extremity models. Six databases and search engines were used to obtain literature, and the search was limited to studies published in English since 2000. The initial search results identified 636 pelvis-related papers, 834 buttocks-related papers, 505 thigh-related papers, 927 femur-related papers, 2039 knee-related papers, 655 shank-related papers, 292 tibia-related papers, 110 fibula-related papers, 644 ankle related papers, and 5660 foot-related papers. A refined search returned 100 pelvis-related papers, 45 buttocks related papers, 65 thigh-related papers, 162 femur-related papers, 195 kneerelated papers, 37 shank-related papers, 80 tibia-related papers, 30 fibula-related papers and 102 ankle-related papers and 246 foot-related papers. The refined literature list was further restricted by appraisal against a modified LOW appraisal criteria. Studies with unclear methodologies, with a focus on populations with pathology or with sport related dynamic motion modeling were excluded. The final literature list included fifteen models and each was assessed against the percentile the model represents, the gender the model was based on, the human body segment/segments included in the model, the sample size used to develop the model, the source of geometric/anthropometric values used to develop the model, the posture the model represents and the finite element solver used for the model. The results of this literature review provide indication of bias in the available models towards 50th percentile male modeling with a notable concentration on the pelvis, femur and buttocks segments.
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Over the past decade our understanding of foot function has increased significantly[1,2]. Our understanding of foot and ankle biomechanics appears to be directly correlated to advances in models used to assess and quantify kinematic parameters in gait. These advances in models in turn lead to greater detail in the data. However, we must consider that the level of complexity is determined by the question or task being analysed. This systematic review aims to provide a critical appraisal of commonly used marker sets and foot models to assess foot and ankle kinematics in a wide variety of clinical and research purposes.
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In this work a biomechanical model is used for simulation of muscle forces necessary to maintain the posture in a car seat under different support conditions.
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In information retrieval (IR) research, more and more focus has been placed on optimizing a query language model by detecting and estimating the dependencies between the query and the observed terms occurring in the selected relevance feedback documents. In this paper, we propose a novel Aspect Language Modeling framework featuring term association acquisition, document segmentation, query decomposition, and an Aspect Model (AM) for parameter optimization. Through the proposed framework, we advance the theory and practice of applying high-order and context-sensitive term relationships to IR. We first decompose a query into subsets of query terms. Then we segment the relevance feedback documents into chunks using multiple sliding windows. Finally we discover the higher order term associations, that is, the terms in these chunks with high degree of association to the subsets of the query. In this process, we adopt an approach by combining the AM with the Association Rule (AR) mining. In our approach, the AM not only considers the subsets of a query as “hidden” states and estimates their prior distributions, but also evaluates the dependencies between the subsets of a query and the observed terms extracted from the chunks of feedback documents. The AR provides a reasonable initial estimation of the high-order term associations by discovering the associated rules from the document chunks. Experimental results on various TREC collections verify the effectiveness of our approach, which significantly outperforms a baseline language model and two state-of-the-art query language models namely the Relevance Model and the Information Flow model
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In 2002, the United Nations Office on Drugs and Crime (UNODC) issued a report entitled Results of a pilot survey of forty selected organized criminal groups in sixteen countries which established five models of organised crime. This paper reviews these and other common organised crime models and drug trafficking models, and applies them to cases of South East Asian drug trafficking in the Australian state of Queensland. The study tests the following hypotheses: (1) South-East Asian drug trafficking groups in Queensland will operate within a criminal network or core group; (2) Wholesale drug distributors in Queensland will not fit consistently under any particular UN organised crime model; and (3) Street dealers will have no organisational structure. The study concluded that drug trafficking or importation closely resembles a criminal network or core group structure. Wholesale dealers did not fit consistently into any UN organised crime model. Street dealers had no organisational structure as an organisational structure is typically found in mid- to high-level drug trafficking.
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PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models (SSM). PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries Numpy and Scipy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimised and parallelised Fortran routines. These Fortran routines heavily utilise Basic Linear Algebra (BLAS) and Linear Algebra Package (LAPACK) functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.
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Evidence exists that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication may stem from the fact that the repository describes variants of the same pro- cesses and/or because of copy/pasting activity throughout the lifetime of the repository. Previous work has put forward techniques for identifying duplicate fragments (clones) that can be refactored into shared subprocesses. However, these techniques are limited to finding exact clones. This paper analyzes the prob- lem of approximate clone detection and puts forward two techniques for detecting clusters of approximate clones. Experiments show that the proposed techniques are able to accurately retrieve clusters of approximate clones that originate from copy/pasting followed by independent modifications to the copied fragments.
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In this paper, we argue that second language (L2) reading research, which has been informed by studies involving first language (L1) alphabetic English reading, may be less relevant to L2 readers with non-alphabetic reading backgrounds, such as Chinese readers with an L1 logographic (Chinese character) learning history. We provide both neuroanatomical and behavioural evidence from Chinese language reading studies to support our claims. The paper concludes with an argument outlining the need for a universal L2 reading model which can adequately account for readers with diverse L1 orthographic language learning histories.
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Purpose – The purpose of this paper is to provide of a review of the theory and models underlying project management (PM) research degrees that encourage reflective learning. Design/methodology/approach – Review of the literature and reflection on the practice of being actively involved in conducting and supervising academic research and disseminating academic output. The paper argues the case for the potential usefulness of reflective academic research to PM practitioners. It also highlights theoretical drivers of and barriers to reflective academic research by PM practitioners. Findings – A reflective learning approach to research can drive practical results though it requires a great deal of commitment and support by both academic and industry partners. Practical implications – This paper suggests how PM practitioners can engage in academic research that has practical outcomes and how to be more effective at disseminating these research outcomes. Originality/value – Advanced academic degrees, in particular those completed by PM practitioners, can validate a valuable source of innovative ideas and approaches that should be more quickly absorbed into the PM profession’s sources of knowledge. The value of this paper is to critically review and facilitate a reduced adaptation time for implementation of useful reflective academic research to industry.
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Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.
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The Australian income tax regime is generally regarded as a mechanism by which the Federal Government raises revenue, with much of the revenue raised used to support public spending programs. A prime example of this type of spending program is health care. However, a government may also decide that the private sector should provide a greater share of the nation's health care. To achieve such a policy it can bring about change through positive regulation, or it can use the taxation regime, via tax expenditures, not to raise revenue but to steer or influence individuals in its desired direction. When used for this purpose, tax expenditures steer taxpayers towards or away from certain behaviour by either imposing costs on, or providing benefits to them. Within the context of the health sector, the Australian Federal Government deploys social steering via the tax system, with the Medicare Levy Surcharge and the 30 percent Private Health Insurance Rebate intended to steer taxpayer behaviour towards the Government’s policy goal of increasing the amount of health provision through the private sector. These steering mechanisms are complemented by the ‘Lifetime Health Cover Initiative’. This article, through the lens of behavioural economics, considers the ways in which these assorted mechanisms might have been expected to operate and whether they encourage individuals to purchase private health insurance.
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Airports represent the epitome of complex systems with multiple stakeholders, multiple jurisdictions and complex interactions between many actors. The large number of existing models that capture different aspects of the airport are a testament to this. However, these existing models do not consider in a systematic sense modelling requirements nor how stakeholders such as airport operators or airlines would make use of these models. This can detrimentally impact on the verification and validation of models and makes the development of extensible and reusable modelling tools difficult. This paper develops from the Concept of Operations (CONOPS) framework a methodology to help structure the review and development of modelling capabilities and usage scenarios. The method is applied to the review of existing airport terminal passenger models. It is found that existing models can be broadly categorised according to four usage scenarios: capacity planning, operational planning and design, security policy and planning, and airport performance review. The models, the performance metrics that they evaluate and their usage scenarios are discussed. It is found that capacity and operational planning models predominantly focus on performance metrics such as waiting time, service time and congestion whereas performance review models attempt to link those to passenger satisfaction outcomes. Security policy models on the other hand focus on probabilistic risk assessment. However, there is an emerging focus on the need to be able to capture trade-offs between multiple criteria such as security and processing time. Based on the CONOPS framework and literature findings, guidance is provided for the development of future airport terminal models.
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Exploiting wind-energy is one possible way to ex- tend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.
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Fire safety of buildings has been recognised as very important by the building industry and the community at large. Gypsum plasterboards are widely used to protect light gauge steel frame (LSF) walls all over the world. Gypsum contains free and chemically bound water in its crystal structure. Plasterboard also contains gypsum (CaSO4.2H2O) and calcium carbonate (CaCO3). The dehydration of gypsum and the decomposition of calcium carbonate absorb heat, and thus are able to protect LSF walls from fires. Kolarkar and Mahendran (2008) developed an innovative composite wall panel system, where the insulation was sandwiched between two plasterboards to improve the thermal and structural performance of LSF wall panels under fire conditions. In order to understand the performance of gypsum plasterboards and LSF wall panels under standard fire conditions, many experiments were conducted in the Fire Research Laboratory of Queensland University of Technology (Kolarkar, 2010). Fire tests were conducted on single, double and triple layers of Type X gypsum plasterboards and load bearing LSF wall panels under standard fire conditions. However, suitable numerical models have not been developed to investigate the thermal performance of LSF walls using the innovative composite panels under standard fire conditions. Continued reliance on expensive and time consuming fire tests is not acceptable. Therefore this research developed suitable numerical models to investigate the thermal performance of both plasterboard assemblies and load bearing LSF wall panels. SAFIR, a finite element program, was used to investigate the thermal performance of gypsum plasterboard assemblies and LSF wall panels under standard fire conditions. Appropriate values of important thermal properties were proposed for plasterboards and insulations based on laboratory tests, literature review and comparisons of finite element analysis results of small scale plasterboard assemblies from this research and corresponding experimental results from Kolarkar (2010). The important thermal properties (thermal conductivity, specific heat capacity and density) of gypsum plasterboard and insulation materials were proposed as functions of temperature and used in the numerical models of load bearing LSF wall panels. Using these thermal properties, the developed finite element models were able to accurately predict the time temperature profiles of plasterboard assemblies while they predicted them reasonably well for load bearing LSF wall systems despite the many complexities that are present in these LSF wall systems under fires. This thesis presents the details of the finite element models of plasterboard assemblies and load bearing LSF wall panels including those with the composite panels developed by Kolarkar and Mahendran (2008). It examines and compares the thermal performance of composite panels developed based on different insulating materials of varying densities and thicknesses based on 11 small scale tests, and makes suitable recommendations for improved fire performance of stud wall panels protected by these composite panels. It also presents the thermal performance data of LSF wall systems and demonstrates the superior performance of LSF wall systems using the composite panels. Using the developed finite element of models of LSF walls, this thesis has proposed new LSF wall systems with increased fire rating. The developed finite element models are particularly useful in comparing the thermal performance of different wall panel systems without time consuming and expensive fire tests.