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In Army Services, there are a number of valuable decisions that have to be taken for mission accomplishment. These decisions are very important and the choice of a weapon may be able to alter the outcome of a battle decisively. Among several such decisions one is to decide which weapons to deploy/assign over a given terrain. Recommender systems are intelligent applications to assist users in a decision-making process where they want to choose one item amongst a potentially overwhelming set of alternative products or services. This paper proposes the design of recommender system that automates the process of finding the appropriate type of weapon(s) that can be deployed over a terrain having certain characteristics. The user agent seeks recommendations, which are in the form of intuitionistic fuzzy set (IFS), from trustworthy peers and produces aggregated order of recommendations taking degree of trust on recommenders into consideration. Trust on recommender is also updated based on importance of recommendation given to the user. A prototype of the trust-based recommender system for modern tactical combat system has been designed and developed through which the user can get the recommendation to use a specific kind of weapon or a set of weapons that would be best-suited in a given type of terrain.

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The feasibility of using a multi-MeV He(+)-ion beam to convert the outer portion of a crystal fiber into cladding is demonstrated. When applied to a-axis LiNbO(3) fiber, the resulting structure has been found to show good waveguiding characteristics.

No abstract