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Most of the existing IDS use all the features in network packet to evaluate and look for known intrusion patterns. This data contains irrelevant and redundant features. Unfortunately, the drawback to this approach is a lengthy detection process. In real-time environment this may degrade the performance of an IDS. Thus, feature selection is required to(More)
3D object reconstruction is frequent used in various fields such as product design, engineering, medical and artistic applications. Numerous reconstruction techniques and software were introduced and developed. However, the purpose of this paper is to fully integrate an adaptive artificial neural network (ANN) based method in reconstructing and representing(More)
Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method developed in 1995 by Eberhart and Kennedy based on the social behaviors of birds flocking or fish schooling. A number of basic variations have been developed due to improve speed of convergence and quality of solution found by the PSO. On the other(More)
Writer Identification (WI) is one of the areas in pattern recognition that have created a center of attention for many researchers to work in. Recently, its main focus is in forensics and biometric application, e.g. writing style can be used as biometric features for authenticating individuality uniqueness. Existing works in WI concentrate on feature(More)
Three Term Backpropagation(BP) Network as proposed by Zweiri in 2003 has outperformed standard Two Term Backpropagation. However, further studies on Three Term Backpropagation in 2007 indicated that this network only surpassed standard BP for small scale datasets but not for medium and large scale datasets. It has also been observed that by using Mean(More)
Abstract— In Complex Event Processing (CEP), we dealwith how to search through a sequence of incoming eventsto find a specified and desired pattern. CEP has a broaduse in today enterprise. It can act on sent and/or receivedevents. The result can generate other events that can beused in different layers of an enterprise system. Growingnumber of areas(More)
The author's unique characteristic is determined by the variation of generated features from feature extraction process. Different sets of features produced are based on different feature extraction methods (local or global). Thus, the process has led to the production of high dimensional datasets that contributing to many irrelevant or redundant features.(More)
This paper compares performance of several classifiers provided in WEKA such as Bayes, decision tree and classification rules in classifying student's learning style. The student's preferences and behavior while using e-learning system have been observed and analyzed and twenty attributes have been selected to map into Felder Silverman learning style model.(More)