Generating vegetation leaf area index Earth system data record from multiple sensors. Part 2: Implementation,analysis and validation

The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the inter-comparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.     

Prognostics of machine condition using soft computing

This paper presents a system for monitoring and prognostics of machine conditions using soft computing (SC) techniques. The machine condition is assessed through a suitable ‘monitoring index’ extracted from the vibration signals. The progression of the monitoring index is predicted using an SC technique, namely adaptive neuro-fuzzy inference system (ANFIS). Comparison with a machine learning method, namely support vector regression (SVR), is also presented. The proposed prediction procedures have been evaluated through benchmark data sets. The prognostic effectiveness of the techniques has been illustrated through previously published data on several types of faults in machines. The performance of SVR was found to be better than ANFIS for the data sets used. The results are helpful in understanding the relationship of machine conditions, the corresponding indicating features, the level of damage/degradation and their progression.     

Multilevel segmentation of Hippocampus images using global steered quantum inspired firefly algorithm

Applied Intelligence - Microscopic Image segmentation has a crucial role in detecting and diagnosing numerous critical diseases like Alzheimer’s disease, Kidney disease, Cancer, many...     

Construction of a radial basis function network using an evolutionary algorithm for grade estimation in a placer gold deposit

This paper presents a study highlighting the predictive performance of a radial basis function (RBF) network in estimating the grade of an offshore placer gold deposit. In applying the radial basis function network to grade estimation of the deposit, several pertinent issues regarding RBF model construction are addressed in this study. One of the issues is the selection of the RBF network along with its center and width parameters. Selection was done by an evolutionary algorithm that utilizes the concept of cooperative coevolutions of the RBFs and the associated network. Furthermore, the problem of data division, which arose during the creation of the training, calibration and validation of data sets for the RBF model development, was resolved with the help of an integrated approach of data segmentation and genetic algorithms (GA). A simulation study conducted showed that nearly 27% of the time, a bad data division would result if random data divisions were adopted in this study. In addition, the efficacy of the RBF network was tested against a feed-forward network and geostatistical techniques. The outcome of this comparative study indicated that the RBF model performed decisively better than the feed-forward network and the ordinary kriging (OK).     

Nano and micro structural studies of thin films of ZnO

Zinc oxide thin films grown by sol–gel and RF sputtering methods have been characterized. The characterization techniques used involve ellipsometry, optical absorption, scanning tunneling microscopy, scanning and transmission electron microscopy. The films grown by sol–gel spin method which followed zinc acetate route exhibited a smoother texture than the films, which were deposited by using zinc nitrate route. The later type of films showed a dendritic character. Nano-structured fine grains of size ranging from 20 to 60 nm were observed with zinc nitrate precursor film. Individual grains show a sharp contrast with different facets and boundaries. Crystal planes and lattice parameters calculated by electron diffraction and X-ray diffraction are quite close and in agreement with the reported values in literature. Scanning tunneling microscopy has been used for measuring the average roughness of the surface and estimating the lattice constants. The STM studies of RF sputtered films, although showing a ZnO structure, exhibited a disturbed lattice. This was presumably due to the fact that after deposition the films were not annealed. Nanographs of 2D and 3D view of atomic positions of ZnO have been presented by using scanning tunneling microscopy.     

A stabilized volume‐averaging finite element method for flow in porous media and binary alloy solidification processes

A stabilized equal‐order velocity–pressure finite element algorithm is presented for the analysis of flow in porous media and in the solidification of binary alloys. The adopted governing macroscopic conservation equations of momentum, energy and species transport are derived from their microscopic counterparts using the volume‐averaging method. The analysis is performed in a single domain with a fixed numerical grid. The fluid flow scheme developed includes SUPG (streamline‐upwind/Petrov–Galerkin), PSPG (pressure stabilizing/Petrov–Galerkin) and DSPG (Darcy stabilizing/Petrov–Galerkin) stabilization terms in a variable porosity medium. For the energy and species equations a classical SUPG‐based finite element method is employed. The developed algorithms were tested extensively with bilinear elements and were shown to perform stably and with nearly quadratic convergence in high Rayleigh number flows in varying porosity media. Examples are shown in natural and double diffusive convection in porous media and in the directional solidification of a binary‐alloy. Copyright © 2004 John Wiley & Sons, Ltd.     

Globally linearized control on diabatic continuous stirred tank reactor: a case study

This paper focuses on the promise of globally linearized control (GLC) structure in the realm of strongly nonlinear reactor system control. The proposed nonlinear control strategy is comprised of: (i) an input-output linearizing state feedback law (transformer), (ii) a state observer, and (iii) an external linear controller. The synthesis of discrete-time GLC controller for single-input single-output diabatic continuous stirred tank reactor (DCSTR) has been studied first, followed by the synthesis of feedforward/feedback controller for the same reactor having dead time in process as well as in disturbance. Subsequently, the multivariable GLC structure has been designed and then applied on multi-input multi-output DCSTR system. The simulation study shows high quality performance of the derived nonlinear controllers. The better-performed GLC in conjunction with reduced-order observer has been compared with the conventional proportional integral controller on the example reactor and superior performance has been achieved by the proposed GLC control scheme.