Informatics Publishing Limited

S. Venkateswaran ¹, M. Vijay Prabhu ¹, M. Mohammed Rafi ¹, K. L. K. Vallel ¹

Affiliations
1 Hydrogeological Lab, Department of Geology, Periyar University, Salem-636 011, T.N., IN

Abstract

The suitability of groundwater for irrigation uses was assessed in Cumbum valley covering a total area of about 1485.62 km². The study area is located in Uttamapalyam taluk and a small part of Periyakulam Taluk of Madurai district, Tamil Nadu. Fifty five groundwater samples were collected from open wells in the various locations in the study area. The samples were analyzed for major cations and anions and other parameters viz., EC, Kelley's ratio, SAR values, Mg-hazards, HCO₃ and RSC have been worked out to know the suitability of the groundwater for irrigational purpose. Piper trilinear diagram interpretations were made to know the chemical type of the groundwaters. It reveals that the subsurface water is alkaline earth (Ca+Mg) then alkalies (Na+K) type. The groundwater samples fall under class-I of Doneen's classification and use in good to permissible zone according to Wilcox classification. According to the SAR values plotted in the USSL Staff diagram, most of the groundwater samples belong to C₃-S₁ (41.82%) class indicating that the groundwater could be used for all types of crops on soils of medium to high permeability.

Keywords

Groundwater Quality, Cumbum Valley, Irrigation, Doneen’s Diagram, Wilcox Diagram, U.S. Salinity Laboratory, Diagram.

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K. Venkata Lakshmi ¹, S. Venkateswaran ¹

Affiliations
1 Department of Computer Science Engineering, Arasu Engineering College, Kumbakonam, IN

Abstract

Systems operating in a distributed environment need to maintain high standards regarding availability and performance. A decretive concern in distributed computing systems is to efficiently schedule the tasks among all processors so that the overall processing time of the submitted tasks is at a minimum. The increasing need for intelligent visual surveillance in commercial, law enforcement and military applications makes automated visual surveillance systems one of the main current application domains in computer vision. Parallel Hadoop implementation is better suited for large data sizes than for when a computationally intensive application is required. In this paper, we propose a probabilistic approach for face recognition suitable for a multi-camera video surveillance network using Hadoop platform. This proposed design of a hybrid intelligent surveillance system which the face detection and tracking is required for Video Surveillance to capture people. The surveillance deals with the extraction of face datasets from a video and processing of images using a Hadoop image processing interface and craniofacial identification based facial feature extraction.

Keywords

Image Processing, MapReduce, Hadoop, Distributed File System, CCTV, HDFS.

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