Sang-Woon Kim

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Various Prototype Reduction Schemes (PRS) have been reported in the literature. Based on their operating characteristics, these schemes fall into two fairly distinct categories — those which are of a creative sort, and those which are essentially selective. The norms for evaluating these methods are typically, the reduction rate and the classification(More)
BACKGROUND The CLASSIC trial was done to compare adjuvant capecitabine plus oxaliplatin versus observation after D2 gastrectomy for patients with stage II or III gastric cancer. The planned interim analysis of CLASSIC (median follow-up 34 months) showed that adjuvant capecitabine plus oxaliplatin significantly improved disease-free survival, the primary(More)
Various prototype reduction schemes have been reported in the literature. Foremost among these are the PNN, the VQ, and the SVM methods. In this paper, we shall show that these schemes can be enhanced by the introduction of a post-processing phase that is related, but not identical to, the LVQ3 process. Although the post-processing with LVQ3 has been(More)
This paper gives an overview on an intelligent avatar communication system using Korean, Chinese and Japanese sign-languages to overcome the linguistic barrier between different languages. First of all, to achieve real-time communication, an intelligent communication method based on a client-server architecture and a sign-language translation method are(More)
Most of the prototype reduction schemes (PRS), which have been reported in the literature, process the data in its entirety to yield a subset of prototypes that are useful in nearest-neighbor-like classification. Foremost among these are the prototypes for nearest neighbor classifiers, the vector quantization technique, and the support vector machines.(More)
This paper presents a novel approach to unit testing that lets users of deployed software assist in performing mutation testing of the software. Our technique, MUGAMMA, provisions a software system so that when it executes in the field, it will determine whether users’ executions would have killed mutants (without actually executing the mutants), and if so,(More)
Fisher’s Linear Discriminant Analysis (LDA) is a traditional dimensionality reduction method that has been proven to be successful for decades. To enhance the LDA’s power for high-dimensional pattern classification, such as face recognition, numerous LDA-extension approaches have been proposed in the literature. This paper proposes a new method that(More)
This paper reports the first known solution to the stochastic point location (SPL) problem when the environment is nonstationary. The SPL problem involves a general learning problem in which the learning mechanism (which could be a robot, a learning automaton, or, in general, an algorithm) attempts to learn a "parameter," for example, lambda*, within a(More)
In kernel-based nonlinear subspace (KNS) methods, the subspace dimensions have a strong influence on the performance of the subspace classifier. In order to get a high classification accuracy, a large dimension is generally required. However, if the chosen subspace dimension is too large, it leads to a low performance due to the overlapping of the resultant(More)
The subspace method of pattern recognition is a classification technique in which pattern classes are specified in terms of linear subspaces spanned by their respective class-based basis vectors. To overcome the limitations of the linear methods, Kernel based Nonlinear Subspace (KNS) methods have been recently proposed in the literature. In KNS, the kernel(More)