524 resultados para Hierarchical Linear Modelling


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In this paper, we present the outcomes of a project on the exploration of the use of Field Programmable Gate Arrays(FPGAs) as co-processors for scientific computation. We designed a custom circuit for the pipelined solving of multiple tri-diagonal linear systems. The design is well suited for applications that require many independent tri diagonal system solves, such as finite difference methods for solving PDEs or applications utilising cubic spline interpolation. The selected solver algorithm was the Tri Diagonal Matrix Algorithm (TDMA or Thomas Algorithm). Our solver supports user specified precision thought the use of a custom floating point VHDL library supporting addition, subtraction, multiplication and division. The variable precision TDMA solver was tested for correctness in simulation mode. The TDMA pipeline was tested successfully in hardware using a simplified solver model. The details of implementation, the limitations, and future work are also discussed.

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Background Quality of work life (QWL) has been found to influence the commitment of health professionals including nurses. However, reliable information on the QWL and turnover intention of primary health care (PHC) nurses is limited. The aim of this study was to examine the relationship between QWL and turnover intention of PHC nurses in Saudi Arabia. Methods A cross-sectional survey was used in this study. Data were collected using Brooks’ survey of Quality of Nursing Work life (QNWL), the Anticipated Turnover Scale and demographic data questions. A total of 508 PHC nurses in the Jazan region, Saudi Arabia completed the questionnaire (RR = 87%). Descriptive statistics, t-test, ANOVA, General Linear Model (GLM) univariate analysis, standard multiple regression (SMR), and hierarchical multiple regression (HMR) were applied for analysis using SPSS v17 for Windows. Results Findings suggested that the respondents were dissatisfied with their work life, with almost 40% indicating a turnover intention from their current PHC centres. Turnover intention was significantly related to QWL. Using SMR, 26% of the variance in turnover intention was explained by the QWL, p < 0.001, with R² = .263. Further analysis using HMR found that the total variance explained by the model as a whole (demographics and QWL) was 32.1%, p < 0.001. QWL explained an additional 19% of the variance in turnover intention, after controlling for demographic variables. Conclusions Creating and maintaining a healthy work life for PHC nurses is very important to improve their work satisfaction, reduce turnover, enhance productivity and improve nursing care outcomes.

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The selection of appropriate analogue materials is a central consideration in the design of realistic physical models. We investigate the rheology of highly-filled silicone polymers in order to find materials with a power-law strain-rate softening rheology suitable for modelling rock deformation by dislocation creep and report the rheological properties of the materials as functions of the filler content. The mixtures exhibit strain-rate softening behaviour but with increasing amounts of filler become strain-dependent. For the strain-independent viscous materials, flow laws are presented while for strain-dependent materials the relative importance of strain and strain rate softening/hardening is reported. If the stress or strain rate is above a threshold value some highly-filled silicone polymers may be considered linear visco-elastic (strain independent) and power-law strain-rate softening. The power-law exponent can be raised from 1 to ~3 by using mixtures of high-viscosity silicone and plasticine. However, the need for high shear strain rates to obtain the power-law rheology imposes some restrictions on the usage of such materials for geodynamic modelling. Two simple shear experiments are presented that use Newtonian and power-law strain-rate softening materials. The results demonstrate how materials with power-law rheology result in better strain localization in analogue experiments.

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longitudinal study of data modelling across grades 1-3. The activity engaged children in designing, implementing, and analysing a survey about their new playground. Data modelling involves investigations of meaningful phenomena, deciding what is worthy of attention (identifying complex attributes), and then progressing to organising, structuring, visualising, and representing data. The core components of data modelling addressed here are children’s structuring and representing of data, with a focus on their display of metarepresentational competence (diSessa, 2004). Such competence includes students’ abilities to invent or design a variety of new representations, explain their creations, understand the role they play, and critique and compare the adequacy of representations. Reported here are the ways in which the children structured and represented their data, the metarepresentational competence displayed, and links between their metarepresentational competence and conceptual competence.

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In this paper, we present the outcomes of a project on the exploration of the use of Field Programmable Gate Arrays (FPGAs) as co-processors for scientific computation. We designed a custom circuit for the pipelined solving of multiple tri-diagonal linear systems. The design is well suited for applications that require many independent tri-diagonal system solves, such as finite difference methods for solving PDEs or applications utilising cubic spline interpolation. The selected solver algorithm was the Tri-Diagonal Matrix Algorithm (TDMA or Thomas Algorithm). Our solver supports user specified precision thought the use of a custom floating point VHDL library supporting addition, subtraction, multiplication and division. The variable precision TDMA solver was tested for correctness in simulation mode. The TDMA pipeline was tested successfully in hardware using a simplified solver model. The details of implementation, the limitations, and future work are also discussed.

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Currently, 1.3 billion tonnes of food is lost annually due to lack of proper processing and preservation method. Drying is one of the easiest and oldest methods of food processing which can contribute to reduce that huge losses, combat hunger and promote food security. Drying increase shelf life, reduce weight and volume of food thus minimize packing, storage, and transportation cost and enable storage of food under ambient environment. However, drying is a complex process which involves combination of heat and mass transfer and physical property change and shrinkage of the food material. Modelling of this process is essential to optimize the drying kinetics and improve energy efficiency of the process. Since material properties varies with moisture content, the models should not consider constant materials properties, constant diffusion .The objective of this paper is to develop a multiphysics based mathematical model to simulate coupled heat and mass transfer during convective drying of fruit considering variable material properties. This model can be used predict the temperature and moisture distribution inside the food during drying. Effect of different drying air temperature and drying air velocity on drying kinetics has been demonstrated. The governing equations of heat and mass transfer were solved with Comsol Multiphysics 4.3.

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This paper is concerned with recent advances in the development of near wall-normal-free Reynolds-stress models, whose single point closure formulation, based on the inhomogeneity direction concept, is completely independent of the distance from the wall, and of the normal to the wall direction. In the present approach the direction of the inhomogeneity unit vector is decoupled from the coefficient functions of the inhomogeneous terms. A study of the relative influence of the particular closures used for the rapid redistribution terms and for the turbulent diffusion is undertaken, through comparison with measurements, and with a baseline Reynolds-stress model (RSM) using geometric wall normals. It is shown that wall-normal-free rsms can be reformulated as a projection on a tensorial basis that includes the inhomogeneity direction unit vector, suggesting that the theory of the redistribution tensor closure should be revised by taking into account inhomogeneity effects in the tensorial integrity basis used for its representation.

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Building Information Modelling (BIM) appears to be the next evolutionary link in project delivery within the AEC (Architecture, Engineering and Construction) Industry. There have been several surveys of implementation at the local level but to date little is known of the international context. This paper is a preliminary report of a large scale electronic survey of the implementation of BIM and the impact on AEC project delivery and project stakeholders in Australia and internationally. National and regional patterns of BIM usage will be identified. These patterns will include disciplinary users, project lifecycle stages, technology integration–including software compatibility—and organisational issues such as human resources and interoperability. Also considered is the current status of the inclusion of BIM within tertiary level curricula and potential for the creation of a new discipline.

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The Clarence-Moreton Basin (CMB) covers approximately 26000 km2 and is the only sub-basin of the Great Artesian Basin (GAB) in which there is flow to both the south-west and the east, although flow to the south-west is predominant. In many parts of the basin, including catchments of the Bremer, Logan and upper Condamine Rivers in southeast Queensland, the Walloon Coal Measures are under exploration for Coal Seam Gas (CSG). In order to assess spatial variations in groundwater flow and hydrochemistry at a basin-wide scale, a 3D hydrogeological model of the Queensland section of the CMB has been developed using GoCAD modelling software. Prior to any large-scale CSG extraction, it is essential to understand the existing hydrochemical character of the different aquifers and to establish any potential linkage. To effectively use the large amount of water chemistry data existing for assessment of hydrochemical evolution within the different lithostratigraphic units, multivariate statistical techniques were employed.

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Linear adaptive channel equalization using the least mean square (LMS) algorithm and the recursive least-squares(RLS) algorithm for an innovative multi-user (MU) MIMOOFDM wireless broadband communications system is proposed. The proposed equalization method adaptively compensates the channel impairments caused by frequency selectivity in the propagation environment. Simulations for the proposed adaptive equalizer are conducted using a training sequence method to determine optimal performance through a comparative analysis. Results show an improvement of 0.15 in BER (at a SNR of 16 dB) when using Adaptive Equalization and RLS algorithm compared to the case in which no equalization is employed. In general, adaptive equalization using LMS and RLS algorithms showed to be significantly beneficial for MU-MIMO-OFDM systems.

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Asset management (AM) processes play an important role in assisting enterprises to manage their assets more efficiently. To visualise and improve AM processes, the processes need to be modelled using certain process modelling methodologies. Understanding the requirements for AM process modelling is essential for selecting or developing effective AM process modelling methodologies. However, little research has been done on analysing the requirements. This paper attempts to fill this gap by investigating the features of AM processes. It is concluded that AM process modelling requires intuitive representation of its processes, ‘fast’ implementation of the process modelling, effective evaluation of the processes and sound system integration.

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Significant wheel-rail dynamic forces occur because of imperfections in the wheels and/or rail. One of the key responses to the transmission of these forces down through the track is impact force on the sleepers. Dynamic analysis of nonlinear systems is very complicated and does not lend itself easily to a classical solution of multiple equations. Trying to deduce the behaviour of track components from experimental data is very difficult because such data is hard to obtain and applies to only the particular conditions of the track being tested. The finite element method can be the best solution to this dilemma. This paper describes a finite element model using the software package ANSYS for various sized flat defects in the tread of a wheel rolling at a typical speed on heavy haul track. The paper explores the dynamic response of a prestressed concrete sleeper to these defects.

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Capacity probability models of generating units are commonly used in many power system reliability studies, at hierarchical level one (HLI). Analytical modelling of a generating system with many units or generating units with many derated states in a system, can result in an extensive number of states in the capacity model. Limitations on available memory and computational time of present computer facilities can pose difficulties for assessment of such systems in many studies. A cluster procedure using the nearest centroid sorting method was used for IEEE-RTS load model. The application proved to be very effective in producing a highly similar model with substantially fewer states. This paper presents an extended application of the clustering method to include capacity probability representation. A series of sensitivity studies are illustrated using IEEE-RTS generating system and load models. The loss of load and energy expectations (LOLE, LOEE), are used as indicators to evaluate the application