Akadej Udomchaiporn

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For a large scale of software development, there is a tremendous number of software requirements documents in a collection which may be produced for different domains by different developer teams. They may be later reused to reduce cost and time for the next development. Thus, there is a need to retrieve ones that meet user's need efficiently. This paper(More)
This paper presents a procedure for the classification of specific 3-D features in Magnetic Resonance Imaging (MRI) brain scan volumes. The main contributions of the paper are: (i) a proposed Bounding Box segmentation technique to extract the 3-D features of interest from MRI volumes, (ii) an oct-tree technique to represent the extracted sub-volumes and(More)
This paper presents a procedure for the classification of 3D objects in Magnetic Resonance Imaging (MRI) brain scan volumes. More specifically the classification of the left and right ventricles of the brain according to whether they feature epilepsy or not. The main contributions of the paper are two point series representation techniques to support the(More)
This paper proposes a number of techniques for 3-D image classification according to the nature of a particular Volume of Interest (VOI) that appears across a given image set. Three VOI Based Image Classification (VOIBIC) approaches are considered: (i) Statistical metric based, (ii) Point series based and (iii) Tree based. For evaluation purpose, two 3-D(More)
A 3-D classification method is presented for Magnetic Resonance Imaging (MRI) brain scan volumes of interest. The objective of the classification is to identify volumes that feature indicators of epilepsy against volumes that do not by considering the shape and size of the lateral (left and right) ventricles of the brain. The dataset used with respect to(More)
This paper proposes a new intersection algorithm of sorted sets. The new algorithm employs a comparison- and-elimination approach to the intersection problem instead of using search algorithms as existing intersection solutions. It takes (1) O(T) times for the best case; (2) O(lambda) times for the average case, where lambda is an average size of sorted(More)
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