Gene Ontology (GO) is an important bioinformatics scheme to unify the representation of gene and gene product attributes across all species. Measuring similarity or distance between GO terms is a key step for determining hidden relationship between genes. The notion of similarity between GO terms is a usual step in knowledge discovery related tasks. In literature various similarity measures between GO terms have been proposed. We have introduced a novel similarity measure scheme to improve three conventional similarity measures to reduce their limitations. The salient feature of the proposed GO Semantic Similarity (gSemSim) measure is its ability to show more realistic similarity between concepts in perspective of domain knowledge. A comparative result with other technique has also been presented that showing an improved contextual meaning of the proposed semantic similarity. This study is expected to assist the community of bio informaticians in the selection of better similarity measure required for correct annotations of genes in gene ontology.

IMS (IP Multimedia Subsystem) is designed to provide multiple-services and can be accessed from any access network. With the advent of new multimedia services; user requirement also changed and required delay tolerant services from the service providers. The new multimedia services demands the restrictions on network parameters and this can be achieved by analyzing the traffic flow from the core as well as access network capabilities. As access and core IMS network are independent of each other and does not exchange user SLA with each other. In this paper we proposed framework based on Session border controller (SBC) that proactively monitored the traffic statistics as well as interact with access network operator for getting user's SLA and reserve resources accordingly. We are also proposing alterations in SIP invite and re-invite message to incorporate requested information. These alterations will be useful in ensuring availability of user's handset capabilities to IMS core network.

In semantic computing, Match is an operator that takes as an input two graph-like structures; it can be database schemas or XML schemas and generates a mapping between the corresponding nodes of the two graphs. In semantic schema matching, we attempt to explore the mappings between the two schemas; based on their semantics by employing any semantic similarity measure. In this study, we have defined taxonomy of all possible semantic similarity measures; moreover we also proposed an approach that exploits semantic relations stored in the DBpedia dataset while utilizing a hybrid ranking system to dig out the similarity between nodes of the two graphs.