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The analogy between immune systems and intrusion detection systems encourage the use of artificial immune systems for anomaly detection in computer networks. This paper describes a technique of applying artificial immune system along with genetic algorithm to develop an intrusion detection system. Far from developing primary immune response, as most of the(More)
The paper introduces particle swarm optimization as a viable strategy to find numerical solution of Diophantine equation, for which there exists no general method of finding solutions. The proposed methodology uses a population of integer particles. The candidate solutions in the feasible space are optimised to have better positions through particle best(More)
The paper proposes a perceptron based artificial neural network model for diagnosing learning disability using curriculum based test conducted by special educators in medical environment. The model comprises of a single input layer with eleven units which correspond to different sections of a conventional test and one output unit. The method is not only(More)
The paper introduces a connectionist network approach to find numerical solutions of Diophantine equations as an attempt to address the famous Hilbert " s tenth problem. The proposed methodology uses a three layer feed forward neural network with back propagation as sequential learning procedure to find numerical solutions of a class of Diophantine(More)
The paper proposes a novel idea of finding consensus of biological sequences using sequence evolution. It involves application of meta-heuristic optimization technique called Differential Evolution for the creation of a population of evolved sequences. This evolved population of sequences is used to find consensus using Position Frequency Matrix. DNA(More)
The paper proposes a methodology to find numerical solutions of Diophantine equations using steepest ascent version of Hill Climbing. It represents possible solutions of a Diophantine equation using tree and adopts a novel mechanism to generate successors. The proposed heuristic function makes the process of finding numerical solution a minimization(More)
The paper proposes a novel methodology for finding motifs of biological data. It uses music inspired meta-heuristic optimization technique called harmony search to find motif. The model is based on randomly generated <i>l</i>-mers as the initial harmony memory. Pitch adjustment and random selection are used to generate new <i>l</i>-mers, which are adjudged(More)
The paper proposes a novel methodology using the classification technique called Identification tree (IDT) to diagnose pulmonary tuberculosis (TB) computationally. It uses an exhaustive list of parameters by integrating the results of different medical examinations that are used conventionally. The model reduces the number of parameters required for the(More)
Search engines retrieve relevant information when users know exactly what they are looking for. The search is usually guided by relevant keywords provided by the user. But the key words provided might belong to different domains and the search may end up giving results on domains where the users are not interested on. This paper proposes a novel information(More)