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In this paper, we study the probability of using heart sound as a biometric for human authentication. The most significant contribution of using heart sound as a biometric is that it cannot be easily replicated as compared to other conventional biometrics. The proposed Heart Sound Authentication System (HSAS) consists of five main phases, namely, Heart Sound Capturing, Pre-processing, Feature Extraction,...
Recently, more and more research is devoted for ontology in the semantic web domain. Firstly, a method for choosing the set of candidate similar concepts is presented based on ontology graphical structural features and data mining. Secondly, a calculation method of conceptual similarity is proposed based on the characteristics of the concept ontology and information content. Finally, the optimized...
Differential Evolution (DE) is generally considered as a reliable, accurate and robust optimization technique. However, the algorithm suffers from slow convergence rate and takes large computational time for optimizing the computationally expensive objective functions. Therefore, an attempt to speed up DE is considered necessary. This research introduces a modified differential evolution, called Ant...
In the present study a Modified Differential Evolution (MDE) algorithm is proposed. This algorithm is different in three ways from basic DE. For initialization it utilizes opposition-based learning while in basic DE uniform random numbers serve this task. Secondly, in basic DE mutant individual is random while in MDE it is tournament best and finally MDE utilizes only one set of population as against...
To achieve high accuracy while lowering false alarm rates are major challenges in designing an intrusion detection system. In addressing this issue, this paper proposes an ensemble of one-class classifiers where each uses different learning paradigms. The techniques deployed in this ensemble model are; linear genetic programming (LGP), adaptive neural fuzzy inference system (ANFIS) and random forest...
Our previous research illustrated the design of fuzzy logic based online risk assessment for Distributed Intrusion Prediction and Prevention Systems (DIPPS) [3]. Based on the DIPPS sensors, instead of merely preventing the attackers or blocking traffic, we propose a fuzzy logic based online risk assessment scheme. This paper propose a Hierarchical Neuro-Fuzzy online Risk Assessment (HiNFRA) model...
This article presents the application of meta-learning evolutionary artificial neural network (MLEANN) for a pharmaceutical research problem. Designing drugs is a current problem in the pharmaceutical research domain. By designing a drug we mean to choose some variables of drug formulation (inputs), for obtaining optimal characteristics of drug (outputs). To solve such a problem we propose an evolutionary...
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