This study proposes to introduce the remote sensing and geographic information system (GIS) techniques in mapping the groundwater potential zones. Remote sensing and GIS techniques have been used to map the groundwater potential zones in Salem Chalk Hills, Tamil Nadu, India. Charnockites and fissile hornblende biotite gneiss are the major rock types in this region. Dunites and peridodites are the ultramafic rocks which cut across the foliation planes of the gneisses and are highly weathered. It comprises magnesite and chromite deposits which are excavated by five mining companies by adopting bench mining. The thickness of weathered and fracture zone varies from 2.2 to 50 m in gneissic formation and 5.8 to 55 m in charnockite. At the contacts of gneiss and charnockite, the thickness ranges from 9.0 to 90.8 m favoring good groundwater potential. The mine lease area is underlined by fractured and sheared hornblende biotite gneiss where groundwater potential is good. Water catchment tanks in this area of 5 km radius are small to moderate in size and are only seasonal. They remain dry during summer seasons. As perennial water resources are remote, the domestic and agricultural activities in this region depend mainly upon the groundwater resources. The mines are located in gently slope area, and accumulation of water is not observed except in mine pits even during the monsoon period. Therefore, it is essential to map the groundwater potential zones for proper management of the aquifer system. Satellite imageries were also used to extract lineaments, hydrogeomorphic landforms, drainage patterns, and land use, which are the major controlling factors for the occurrence of groundwater. Various thematic layers pertaining to groundwater existence such as geology, geomorphology, land use/land cover, lineament, lineament density, drainage, drainage density, slope, and soil were generated using GIS tools. By integrating all the above thematic layers based on the ranks and weightages, eventually groundwater potential zones were demarcated. The study indicates that groundwater potential is good to high in 22 villages and moderate in 13 villages. The good to high potential zone occupies an area of 128 km2 and moderate potential zone occupies an area of 77 km2. Groundwater occurrence is poor in five villages which need artificial recharge to augment groundwater.

The wide spread of the Internet increases the availability of all digital data such as image, audio and video to the publics. Digital watermarking is introduced to provide the security, data authentication and copyright to the digital data. This paper provides the basics of watermarking techniques, various applications; attacks carried in watermarking and detail study of reversible watermarking technique. One of the important techniques in watermarking is a reversible watermarking [52] technique. Reversible watermarking strengthens the ownership of the digital data and also supports to recover the original data from the watermarked digital data.

Cloud computing has seen tremendous growth in recent days. As a result of this, there has been a great increase in the growth of data centers all over the world. These data centers consume a lot of energy, resulting in high operating costs. The imbalance in load distribution among the servers in the data center results in increased energy consumption. Server consolidation can be handled by migrating all virtual machines in those underutilized servers. Migration causes performance degradation of the job, based on the migration time and number of migrations. Considering these aspects, the proposed clustering agent-based model improves energy saving by efficient allocation of the VMs to the hosting servers, which reduces the response time for initial allocation. Middle VM migration (MVM) strategy for server consolidation minimizes the number of VM migrations. Further, randomization of extra resource requirement done to cater to real-time scenarios needs more resource requirements than the initial requirement. Simulation results show that the proposed approach reduces the number of migrations and response time for user request and improves energy saving in the cloud environment.

The basic issue in the online social network is to provide the ability for the user to manage the messages post on their wall. Online social networks offer only minimal assistance to avoid unwanted content displayed in the user wall. To enhance the support, a system is designed to filter unwanted messages and allow user to have direct control on the messages posted in the wall. It is achieved using flexible rule based system that allows the user to specify filtering rule for their wall. And, Inference algorithms are used to infer new information from the filtering rules to increase the efficiency of the filtering process. Machine Learning based soft classifier is employed to facilitate the content based filtering.

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