• Journal of KIISE:Software and Applications
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• v.32 no.12
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• pp.1260-1270
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• 2005

Support Vector Machines (SVM) is well known for a representative learner as one of the kernel methods. SVM which is based on the statistical learning theory shows good generalization performance and has been applied to various pattern recognition problems. However, SVM is basically to deal with a two-class classification problem, so we cannot solve directly a multi-class problem with a binary SVM. One-Per-Class (OPC) and All-Pairs have been applied to solve the face recognition problem, which is one of the multi-class problems, with SVM. The two methods above are ones of the output coding methods, a general approach for solving multi-class problem with multiple binary classifiers, which decomposes a complex multi-class problem into a set of binary problems and then reconstructs the outputs of binary classifiers for each binary problem. In this paper, we introduce the output coding methods as an approach for extending binary SVM to multi-class SVM and propose new output coding schemes based on the Error-Correcting Output Codes (ECOC) which is a dominant theoretical foundation of the output coding methods. From the experiment on the face recognition, we give empirical results on the properties of output coding methods including our proposed ones.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.22-28
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• 2010

Adaboost is well known for a representative learner as one of the kernel methods. Adaboost which is based on the statistical learning theory shows good generalization performance and has been applied to various pattern recognition problems. However, Adaboost is basically to deal with a two-class classification problem, so we cannot solve directly a multi-class problem with Adaboost. One-Vs-All and Pair-Wise have been applied to solve the multi-class classification problem, which is one of the multi-class problems. The two methods above are ones of the output coding methods, a general approach for solving multi-class problem with multiple binary classifiers, which decomposes a complex multi-class problem into a set of binary problems and then reconstructs the outputs of binary classifiers for each binary problem. However, two methods cannot show good performance. In this paper, we propose the method to solve a multi-target classification problem by using radial basis function of Adaboost weak classifier.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.1-6
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• 2007

The SVDD (support vector data description) is one of the most well-known one-class support vector learning methods, in which one tries the strategy of utilizing balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. Recently, with the objective of generalizing the SVDD which treats all training data with equal importance, the so-called D-SVDD (density-induced support vector data description) was proposed incorporating the idea that the data in a higher density region are more significant than those in a lower density region. In this paper, we consider the problem of further improving the D-SVDD toward the use of a partial reference set for testing, and propose an LMI (linear matrix inequality)-based optimization approach to solve the improved version of the D-SVDD problems. Our approach utilizes a new class of density-induced distance measures based on the RSDE (reduced set density estimator) along with the LMI-based mathematical formulation in the form of the SDP (semi-definite programming) problems, which can be efficiently solved by interior point methods. The validity of the proposed approach is illustrated via numerical experiments using real data sets.

• Journal of the Korea Society of Computer and Information
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• v.23 no.2
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• pp.77-82
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• 2018

In this paper, we propose an improvement plan to increase the learning effect and satisfaction through the PBL - related video design class. PBL To prepare for the Fourth Industrial Revolution era, we must acquire diverse knowledge and skills to discover problems and solve them creatively. Therefore, various learning methods are being studied, and one of them is PBL learning. PBL is a learner-centered education that explores problems that may arise from specific topics other than existing curriculum-based education methods and finds solutions to problems. In this study, two lectures on video design related to video contents and image contents were taught in PBL class, and PBL class problem was analyzed and the improvement plan was studied.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.222-228
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• 2019

In recent years, in order to enhance the problem-solving skills required by the industrial field, universities have introduced the Problem-Based Learning(PBL) method to solve the problems caused by the lack of creativity, problem solving ability and self-directed learning. This study applied PBL class methods such as 'learning based on individual specific problems', 'self-directed learning', and 'small-group learning of small members' to practical design of fashion design. To do this, I conducted a questionnaire after conducting research based on the PBL module for one semester in a practical class of fashion design major at P University. As a result of the survey, the satisfaction and achievement of the class conducted by PBL learning method was improved than the existing teaching method. As such, if PBL class is used as a way of solving problems through close communication between professors and learners, it is expected to be established as a learner-centered education method that can improve creativity and professionalism.

• East Asian mathematical journal
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• v.35 no.1
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• pp.77-83
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• 2019

$L^1$-weight functions are investigated to give necessary conditions on the existence of nontrivial solutions for various types of scalar equations and systems of one-dimensional Minkowski-curvature problems.

• 한국데이터정보과학회:학술대회논문집
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• 2003.10a
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• pp.123-123
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• 2003

More elaborated methods allowing the usage of binary classifiers for the resolution of multi-class classification problems are briefly presented. This way of using FSVC to learn a K-class classification problem consists in choosing the maximum applied to the outputs of K FSVC solving a one-per-class decomposition of the general problem.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.123-130
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• 2009

When we apply MLPs(multilayer perceptrons) to pattern classification problems, we generally allocate one output node for each class and the index of output node denotes a class. On the contrary, in this paper, we propose to increase the number of output nodes per each class for performance improvement of MLPs. For theoretical backgrounds, we derive the misclassification probability in two class problems with additional outputs under the assumption that the two classes have equal probability and outputs are uniformly distributed in each class. Also, simulations of 50 isolated-word recognition show the effectiveness of our method.

• International Journal of Advanced Culture Technology
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• v.12 no.3
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• pp.106-113
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• 2024

This study is conducted to determine whether Chinese students currently attending Korean universities are satisfied with their university life and to identify the problems they are experiencing. A survey was conducted with the graduate students attending K University and 202 students participated in the study. According to the study, most students are very satisfied with Korean universities and would recommend them to their friends. Regardless of gender, degree program, or major, the most difficult aspect of school life is understanding and communicating in class due to language problems. Even students with high TOPIK scores experience difficulties in communication and comprehension during class. One of the most significant problems that Chinese students have is a lack of interaction with Korean students. They want to interact with Korean students through club and team activities at the university. They requested that the university provide international students with opportunities to participate in various programs, such as sports activities, to help overcome feelings of alienation and isolation. Based on the study results, suggestions to support Chinese students to adjust educational environments in Korea were presented.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.365-374
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• 2009

Under certain conditions, we use augmented Lagrangians to transform a class of generalized semi-infinite min-max problems into common semi-infinite min-max problems, with the same set of local and global solutions. We give two conditions for the transformation. One is a necessary and sufficient condition, the other is a sufficient condition which can be verified easily in practice. From the transformation, we obtain a new first-order optimality condition for this class of generalized semi-infinite min-max problems.