A physical mechanism for North Atlantic SST influence on the Indian summer monsoon

A link between the Atlantic Multidecadal Oscillation (AMO) and multidecadal variability of the Indian summer monsoon rainfall is unraveled and a long sought physical mechanism linking Atlantic climate and monsoon has been identified. The AMO produces persistent weakening (strengthening) of the meridional gradient of tropospheric temperature (TT) by setting up negative (positive) TT anomaly over Eurasia during northern late summer/autumn resulting in early (late) withdrawal of the south west monsoon and persistent decrease (increase) of seasonal monsoon rainfall. On inter-annual time scales, strong North Atlantic Oscillation (NAO) or North Annular mode (NAM) influences the monsoon by producing similar TT anomaly over Eurasia. The AMO achieves the interdecadal modulation of the monsoon by modulating the frequency of occurrence of strong NAO/NAM events. This mechanism also provides a basis for explaining the observed teleconnection between North Atlantic temperature and the Asian monsoon in paleoclimatic proxies. Citation: Goswami, B. N., M. S. Madhusoodanan, C. P. Neema, and D. Sengupta (2006), A physical mechanism for North Atlantic SST influence on the Indian summer monsoon

Context aware M-commerce services: C-IOB model approach

Context-aware computing is useful in providing individualized services focusing mainly on acquiring surrounding context of user. By comparison, only very little research has been completed in integrating context from different environments, despite of its usefulness in diverse applications such as healthcare, M-commerce and tourist guide applications. In particular, one of the most important criteria in providing personalized service in a highly dynamic environment and constantly changing user environment, is to develop a context model which aggregates context from different domains to infer context of an entity at the more abstract level. Hence, the purpose of this paper is to propose a context model based on cognitive aspects to relate contextual information that better captures the observation of certain worlds of interest for a more sophisticated context-aware service. We developed a C-IOB (Context-Information, Observation, Belief) conceptual model to analyze the context data from physical, system, application, and social domains to infer context at the more abstract level. The beliefs developed about an entity (person, place, things) are primitive in most theories of decision making so that applications can use these beliefs in addition to history of transaction for providing intelligent service. We enhance our proposed context model by further classifying context information into three categories: a well-defined, a qualitative and credible context information to make the system more realistic towards real world implementation. The proposed model is deployed to assist a M-commerce application. The simulation results show that the service selection and service delivery of the system are high compared to traditional system.

A context aware collaborative service provisioning system for mobile-commerce

In the process of service provisioning, providing required service to the user without user intervention, with reduction of the cognitive over loading is a real challenge. In this paper we propose a user centred context aware collaborative service provisioning system, which make use of context along with collaboration to provide the required service to the user dynamically. The system uses a novel approach of query expansion along with interactive and rating matrix based collaboration. Performance of the system is evaluated in Mobile-Commerce environment. The results show that the system is time efficient and perform with better precision and recall in comparison with context aware system.