In this paper, face authentication using images taken in visible and near-infrared spectra (NIR) is studied. Visible images are in RGB colour space and near-infrared images are in gray levels colour space. First, the performance of system in each of the primary colour spaces of visible and near-infrared spectrum is evaluated that the verification process is based on the Normalised Correlation measure within the LDA feature space. In order to utilize the information of colour images, the scores associated to an adaptively selected subset of the colour based classifiers are then fused in the decision level. The selection process is based on a sequential search technique called the"plus L and take away R" algorithm. The sum rule and svm rule is used for fusing the related scores. Our extensive experimental studies using the HFB face database demonstrate that using the proposed method, the performance of the system considerably improves as compared to the individual Visible-based or NIR-based face verification systems.

With the advent of microarray technology it has been possible to measure thousands of expression values of genes in a single experiment. Analysis of large scale geonomics data, notably gene expression, has initially focused on clustering methods. Recently, biclustering techniques were proposed for revealing submatrices showing unique patterns. Biclustering or simultaneous clustering of both genes and conditions is challenging particularly for the analysis of high-dimensional gene expression data in information retrieval, knowledge discovery, and data mining. In biclustering of microarray data, several objectives have to be optimized simultaneously and often these objectives are in conflict with each other. A multi objective model is very suitable for solving this problem. Our method proposes a algorithm which is based on multi objective Simulated Annealing for discovering biclusters in gene expression data. Experimental result in bench mark data base present a significant improvement in overlap among biclusters and coverage of elements in gene expression and quality of biclusters.

Reproductive development and then timing of seed dispersal in many weeds is positively correlated with intensity/availability of environmental resources. In this study, we investigated the effects of nitrogen availability and the type of the crop on timing of weed seed dispersal. Two agricultural weeds; wild barley (Hordeum spontaneum Koch.) and wild mustard (Brassica kaber (DC.)) were grown in wheat and oilseed rape crops under a range of nitrogen levels. H. spontaneum seeds that developed under no or low nitrogen levels (0 and 60 kg ha -1 ) reached their final maturation stage sooner than those that developed under high nitrogen levels (120 and 240 kg ha -1 ), resulting in an earlier seed dispersal (109 and 76 degree-days where grown in wheat and oilseed rape cropping systems, correspondingly). In all nitrogen levels, H. spontaneum seeds developed in wheat crop reached their maturation stage sooner, and were then dispersed sooner than those developed in oilseed rape cropping system. The results of this study could help growers to make the best decision on weed management through management of seed dispersal. High nitrogen application, for example, with an early harvest may mean that a significant proportion of seeds are taken up to the combine harvester traveling long distances as grain impurity. In contrast, low nitrogen application with a late harvest may result in the majority of seeds falling to the ground and increasing subsequent crop interference. Therefore, an infested crop should be harvested as early as possible to reduce the quantity of weed seeds entering the seed bank.