Traffic control and vehicle owner identification has become major problem in every country. Sometimes it becomes difficult to identify vehicle owner who violates traffic rules and drives too fast. Therefore, it is not possible to catch and punish those kinds of people because the traffic personal might not be able to retrieve vehicle number from the moving vehicle because of the speed of the vehicle. Therefore, there is a need to develop Automatic Number Plate Recognition (ANPR) system as a one of the solutions to this problem. There are numerous ANPR systems available today. These systems are based on different methodologies but still it is really challenging task as some of the factors like high speed of vehicle, non-uniform vehicle number plate, language of vehicle number and different lighting conditions can affect a lot in the overall recognition rate. Most of the systems work under these limitations. In this paper, different approaches of ANPR are discussed by considering image size, success rate and processing time as parameters. Towards the end of this paper, an extension to ANPR is suggested.

Spatially distributed air temperature data are required for climatological, hydrological and environmental studies. However, high spatial distribution patterns of air temperature are not available from meteorological stations due to its sparse network. The objective of this study was to estimate high spatial resolution minimum air temperature (T min) and maximum air temperature (T max) over the Indo-Gangetic Plain using Moderate Resolution Imaging Spectroradiometer (MODIS) data and India Meteorological Department (IMD) ground station data. T min was estimated by establishing an empirical relationship between IMD T min and night-time MODIS Land Surface Temperature (T s). While, T max was estimated using the Temperature-Vegetation Index (TVX) approach. The TVX approach is based on the linear relationship between T s and Normalized Difference Vegetation Index (NDVI) data where T max is estimated by extrapolating the NDVI-T s regression line to maximum value of NDVI max for effective full vegetation cover. The present study also proposed a methodology to estimate NDVI max using IMD measured T max for the Indo-Gangetic Plain. Comparison of MODIS estimated T min with IMD measured T min showed mean absolute error (MAE) of 1.73 • C and a root mean square error (RMSE) of 2.2 • C. Analysis in the study for T max estimation showed that calibrated NDVI max performed well, with the MAE of 1.79 • C and RMSE of 2.16 • C.

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Previously undescribed POU genes were detected in several invertebrate phyla using redundant primers in a polymerase chain reaction (PCR) that targeted highly conserved sequences encoding known POU-domains. A class IV gene and a gene tentatively assigned to class VI were identified in sea anemones (Condylactis), two distinct class III genes were identified in snails (Biomphalaria), and a single class IV gene was identified in earthworms (Lumbricus). The identification of POU genes in cnidarians, mollusks, and annelids completes a survey of the major metozoan phyla. As POU genes exist in all of these organisms, they appear to be a fundamental characteristic of the metazoan lineage, and may have played a major role in the diversification of these organisms.