Tropical cyclones (TC) are among the most devastating forms of natural hazards and the east coast of India is more prone to TC landfall causing significant socio-economic impacts. The Bay of Bengal (BoB) which forms the eastern sub basin of North Indian Ocean experiences the seasonally reversing monsoon, depression and TCs. In this study TC best track dataset of NIO basin over the period 1960–2016 from the IBTrACKs archive maintained by NOAA are used. In this work Firefly optimization is coupled with FCM for TC tracks classification. The classical FCM uses random initialization of cluster centroid often gets trapped in local optimal problem. The firefly algorithm is applied on the FCM for the cluster centroid computation, in this way improving the efficiency of FCM algorithm. The obtained classes are then projected in the visualization space. Visualizations are generated using the GIS environment to gain insight into the spatial distribution of TC tracks over decades. This study aims to develop a comprehensive assessment of variability in tropical cyclones with respect to ENSO modulated events, inter decadal variability and track sinuosity. In this paper we attempt to convey the cognitive results of comparative visualizations of TC tracks over Arabian Sea and Bay of Bengal sub basin during the strong, very strong El Niño and La Niña events. Finally we use Parallel Coordinate Plot (PCP) a visualization technique to demonstrate the correlation patterns of the TC parameters.

The use of vehicles in our daily lives is growing rapidly, and as more vehicles violate traffic laws, theft of vehicles, and a high number of incidents occur, crime rates rise linearly. Vehicle License Plate Detection (VLPD) is a image processing technology for recognizing the vehicle number plate. In a typical VLPD the image of the vehicle is first detected and the vehicle license plate region is captured. Then the filtering techniques are applied to the captured license plate region. In this study bounding box technique is applied for the segmentation and character recognition. It is observed that the created framework effectively detects and recognizes the vehicle number on different test pictures.