Estimating equations for parameters in stochastic growth models from tag-recapture data

James (1991, Biometrics 47, 1519-1530) constructed unbiased estimating functions for estimating the two parameters in the von Bertalanffy growth curve from tag-recapture data. This paper provides unbiased estimating functions for a class of growth models that incorporate stochastic components and explanatory variables. a simulation study using seasonal growth models indicates that the proposed method works well while the least-squares methods that are commonly used in the literature may produce substantially biased estimates. The proposed model and method are also applied to real data from tagged rack lobsters to assess the possible seasonal effect on growth.

Effect of individual variability on estimation of population parameters from length-frequency data

We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock when there is individual variability in the von Bertalanffy growth parameter L-infinity and investigate the possible bias in the estimates when the individual variability is ignored. Three methods are examined: (i) the regression method based on the Beverton and Holt's (1956, Rapp. P.V. Reun. Cons. Int. Explor. Mer, 140: 67-83) equation; (ii) the moment method of Powell (1979, Rapp. PV. Reun. Int. Explor. Mer, 175: 167-169); and (iii) a generalization of Powell's method that estimates the individual variability to be incorporated into the estimation. It is found that the biases in the estimates from the existing methods are, in general, substantial, even when individual variability in growth is small and recruitment is uniform, and the generalized method performs better in terms of bias but is subject to a larger variation. There is a need to develop robust and flexible methods to deal with individual variability in the analysis of length-frequency data.

An improved Fabens method for estimation of growth parameters in the vonBertalanffy model with individual asymptotes

In the analysis of tagging data, it has been found that the least-squares method, based on the increment function known as the Fabens method, produces biased estimates because individual variability in growth is not allowed for. This paper modifies the Fabens method to account for individual variability in the length asymptote. Significance tests using t-statistics or log-likelihood ratio statistics may be applied to show the level of individual variability. Simulation results indicate that the modified method reduces the biases in the estimates to negligible proportions. Tagging data from tiger prawns (Penaeus esculentus and Penaeus semisulcatus) and rock lobster (Panulirus ornatus) are analysed as an illustration.

Product-library-derived specification parameters in building information models augmentation

This paper conceptualizes a framework for bridging the BIM (building information modelling)-specifications divide through augmenting objects within BIM with specification parameters derived from a product library. We demonstrate how model information, enriched with data at various LODs (levels of development), can evolve simultaneously with design and construction using different representation of a window object embedded in a wall as lifecycle phase exemplars at different levels of granularity. The conceptual standpoint is informed by the need for exploring a methodological approach which extends beyond current limitations of current modelling platforms in enhancing the information content of BIM models. Therefore, this work demonstrates that BIM objects can be augmented with construction specification parameters leveraging product libraries.

Estimation of cosmological parameters using adaptive importance sampling

We present a Bayesian sampling algorithm called adaptive importance sampling or population Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the potential to considerably reduce the wall-clock time required for sampling, along with providing other benefits. To assess the performance of the approach for cosmological problems, we use simulated and actual data consisting of CMB anisotropies, supernovae of type Ia, and weak cosmological lensing, and provide a comparison of results to those obtained using state-of-the-art Markov chain Monte Carlo (MCMC). For both types of data sets, we find comparable parameter estimates for PMC and MCMC, with the advantage of a significantly lower wall-clock time for PMC. In the case of WMAP5 data, for example, the wall-clock time scale reduces from days for MCMC to hours using PMC on a cluster of processors. Other benefits of the PMC approach, along with potential difficulties in using the approach, are analyzed and discussed.

Dynamics of nitrate-nitrogen removal in experimental stormwater biofilters under intermittent wetting and drying

High concentrations of nitrate-nitrogen degrade the quality of aquatic environments. The primary mechanism by which nitrate-nitrogen is removed (denitrification) requires anoxic conditions and electron donors. While removal of total and ammonium-nitrogen is often high in stormwater biofilters, poor removal or even the release of nitrate-nitrogen in the outflow has often been observed. Five Perspex biofilter columns (94 mm internal diameter) were fabricated with a filter layer that contained 8% organic material. Columns were operated at 875  mm/h 875  mm/h and fed with simulated stormwater with different antecedent dry days (ADDs) and concentrations of nitrate-nitrogen. Samples were collected from the outflow at different time intervals between 2 and 150 min and were tested for nitrate-nitrogen. The removal of nitrate-nitrogen varied during an event from a high removal percentage (60–90%) in the initial outflow that gradually decreased in the first 30 min and settled at 0–15% removal thereafter. This remained consistent during all simulated events independent of the number of ADDs or inflow concentrations. ADDs and previous event feed concentrations affected the outflow nitrate-nitrogen concentration in the first 30 min of the current event. Therefore, from this study it is concluded that denitrification within stormwater biofilters occurs mainly during drying periods rather than wetting periods.

Analytical modelling of integrated solar drying system

The drying of fruit and vegetables is a subject of great importance. Dried fruit and vegetables have gained commercial importance, and their growth on a commercial scale has become an important sector of the agricultural industry. However, food drying is one of the most energy intensive processes of the major industrial process and accounts for up to 15 % of all industrial energy usage. Due to increasingly high electricity prices and environmental concern, a dryer using traditional energy sources is not a feasible option anymore. Therefore, an alternative/renewable energy source is needed. In this regard, an integrated solar drying system that includes highly efficient double-pass counter flow v-groove solar collector, conical-shaped rock-bed thermal storage, auxiliary heater, the centrifugal fan and the drying chamber has been designed and constructed. Mathematical model for all the individual components as well as an integrated model combining all components of the drying system has been developed. Mathematical equations were solved using MATLAB program. This paper presents the analytical model and key finding of the simulation.

Multiphase porous media model for Intermittent Microwave Convective Drying (IMCD) of food

Intermittent microwave convective (IMCD) drying is an advanced drying technology that improves both energy efficiency and food quality during the drying of food materials. Despite numerous experimental studies available for IMCD, there is no complete multiphase porous media model available to describe the process. A multiphase porous media model considering liquid water, gases and the solid matrix inside the food during drying can provide in depth understanding of IMCD. In this article, firstly a multiphase porous media model was developed for IMCD. Then the model is validated against experimental data by comparing moisture content and temperature distributions after each heating and tempering periods. The profile of vapour pressures and evaporation during IMCD are presented and discussed. The relative contribution of water and vapour fluxes due to gas pressure and diffusion demonstrated that the fluxes due are relatively higher in IMCD compared to convection drying and this makes the IMCD faster.