Dempster-Shafer Theory (DST) of Evidence is a powerful and flexible mathematical tool for handling uncertainty, impreciseness, and incomplete information. It can be used when both epistemic and aleatory uncertainties are present in the problem under consideration. The fundamental and important object of this theory of evidence is the primitive function called basic probability assignment (bpa). In the absence of empirical data, experts in related fields provide necessary information (bpa). However how to obtain BPA is still an open issue. In this paper, we propose methods to determine BPA when only the minimum, maximum and most likely values of the parameter are known. An example is illustrated to demonstrate and check the efficiency of the proposed methods. We have also developed an extended version of uncertainty measurement in evidence theory in order to calculated total uncertainty in the body of evidence obtained by the proposed methods.

Risk assessment is a popular and important tool in decision making process. Risk assessment is generally performed using models and model is a function of some parameters which are usually affected by uncertainty. Here, we consider that model parameters are affected by epistemic uncertainty. To represent epistemic uncertainty in general triangular fuzzy number or trapezoidal fuzzy numbers are used. In this paper, we study Gaussian fuzzy number to represent epistemic type uncertainty and try to fuse with triangular fuzzy numbers and also risk assessment is carried out under fuzzy environment.

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The genetic code is the rule by which DNA stores the genetic information about formation of protein molecule. In this paper, a partial ordering is equipped on the genetic code and a lattice structure has been developed from it. The codon-anticodon interaction, hydrogen bond number and the chemical types of bases play an important role in the partial ordering. We have established some relations between the lattice structure of the genetic code and physico-chemical properties of amino acids. Taking into consideration the evolutionary importance of base positions in codons we have constructed a distance matrix for the amino acids. Further with a real life example we have demonstrated the relationship between frequently occurring mutations and codon distances.