• Journal of the Korea Society of Computer and Information
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• v.17 no.3
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• pp.67-76
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• 2012

Traffic classification plays an important role in traffic management. To traditional methods, P2P and encryption traffic may become a problem. Support Vector Machine (SVM) is a useful classification tool which is able to overcome the traditional bottleneck. The main disadvantage of SVM algorithms is that it's time-consuming to train large data set because of the quadratic programming (QP) problem. However, the useful support vectors are only a small part of the whole data. If we can discard the useless vectors before training, we are able to save time and keep accuracy. In this article, we discussed the feasibility to remove the useless vectors through a sequential method to accelerate training speed when dealing with large scale data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.311-318
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• 2014

As modern computer graphics technology has been developed, it is hard to discriminate computer graphics from photographic images with the naked eye. Advances in graphics technology has brought a lot of convenience to human, it has side effects such as image forgery, malicious edit and fraudulent means. In order to cope with such problems, studies of various algorithms using a feature that represents a characteristic of an image has been processed. In this paper, we verify directly the existing algorithm, and provide new features based a noise that represents the characteristics of the computer graphics well. And this paper introduces the method of using SVM(Support Vector Machine) with features proposed in previous research to improve the discrimination accuracy.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.47-54
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• 2023

Infants utilize crying as a non-verbal means of communication [1]. However, deciphering infant cries presents challenges. Extensive research has been conducted to interpret infant cry audios [2,3]. This paper proposes the classification of infant cries using 3D feature vectors augmented with various audio data techniques. A total of 5 classes (belly pain, burping, discomfort, hungry, tired) are employed in the study dataset. The data is augmented using 5 techniques (Pitch, Tempo, Shift, Mixup-noise, CutMix). Tempo, Shift, and CutMix augmentation techniques demonstrated improved performance. Ultimately, applying effective data augmentation techniques simultaneously resulted in a 17.75% performance enhancement compared to models using single feature vectors and original data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.9-15
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• 2017

In this study we performed the experiment to detect the ERP using SVM with wavelet features. The EEG signal that is generated visual stimulated ERP database in SCCN applied for the experiment. The feature vectors for experiment are categorized frequency and continuous wavelet- based vectors. In experimental results, the detection rate of SVM with wavelet feature vectors improved above 10% comparing with frequency- based feature vector. Based on the experimental results we analyzed the relation between the activity degree of the ERP and the band split characteristics of the ERP by wavelet transform.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.183-190
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• 2016

This study proposed a more stable robust recognition algorithm which detects faces reliably even in cases where there are changes in lighting and angle of view, as well it satisfies efficiency in calculation and detection performance. The algorithm proposed detects the face area alone after normalization through pre-processing and obtains a feature vector using (PCA). Also, by applying the feature vector obtained for SVM, face areas can be tested. After the testing, using the feature vector is final face recognition performed. The algorithm proposed in this study could increase the stability and accuracy of recognition rates and as a large amount of calculation was not necessary due to the use of two dimensions, real-time recognition was possible.

• Proceedings of the KIPE Conference
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• 2011.11a
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• pp.71-72
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• 2011

This paper presents a novel and direct dead time compensation method of the 3 phase inverter using space vector pulse width modulation(SVPWM) topology. In the turn on time calculation of the effective voltage, the dead time effect is directly compensated according to the current direction of the midium voltage reference. Since the turn on time of the effective voltage vector is affected by the dead time, the loss time is compensated to turn on time of the effective voltage vector. And the dead time is added to the calculated voltage vector switching times according to the current direction. For the more effective compensation, the direction of the midium phase current is considered by the practical direction and voltage drops in the power devices. The proposed method can compensate the dead time which is considered feedback error or direction of middle phase current without coordinate transform in added controller. The proposed dead time compensation scheme is verified by the computer simulation and experiments of 3 phase R L load.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.603-605
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• 1996

The SLIM used in the conveyance system has been generally developed the controller based on the slip frequency control and the VVVF method to obtain the quick response for the position control signal. This paper deals with the trust control of the SLIM by vector control with Bang-Bang condition. Also, the control system is composed of the PI controller for soft start of the SLIM and the q-axis current controller for correction in phase with Space Vector for reducing the harmonic pulsation in low speed. The processing for vector control and robust dynamic breaking control is carried out by MC80196KC micro processor and IGBT module. The proposed scheme is verified through the computer simulation and experiments for the 10KW SLIM.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1664-1670
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• 1991

For kinematically redundant manipulators, conventional dynamic control methods of local torque optimization showed the instability which resulted in physically unachievable torque requirements. In order to guarantee stability of the null space vector method which resolves redundancy at the acceleration level, Maciejewski[1] analyzed the kinetic behavior of homogeneous solution component and proposed the condition to identify regions of stability and instability for this method. 'In this paper, a modified null space vector method is first presented based on the Maciejewski's condition which is a function of a manipulator's configuration. Secondly, a new control method which is based on the concept of aspects is proposed. It was shown by computer simulations that the modified null space vector method and the proposed method have a common property that a preferred aspect is preserved during the execution of a task. It was also illustrated that both methods demonstrate a drastic reduction of torque loadings at the joints in the tracking motion of a long trajectory when compared with the null space vector method, and thus guarantee the stability of joint torque.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.51-56
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• 2005

There are many sources of systematic variations in cDNA microarray experiments which affect the measured gene expression levels like differences in labeling efficiency between the two fluorescent dyes. Print-tip lowess normalization is used in situations where dye biases can depend on spot overall intensity and/or spatial location within the array. However, print-tip lowess normalization performs poorly in situation where error variability for each gene is heterogeneous over intensity ranges. We proposed the new print-tip normalization methods based on support vector machine regression(SVMR) and support vector machine quantile regression(SVMQR). SVMQR was derived by employing the basic principle of support vector machine (SVM) for the estimation of the linear and nonlinear quantile regressions. We applied our proposed methods to previous cDNA micro array data of apolipoprotein-AI-knockout (apoAI-KO) mice, diet-induced obese mice, and genistein-fed obese mice. From our statistical analysis, we found that the proposed methods perform better than the existing print-tip lowess normalization method.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3986-3994
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• 2000

A multiple vector reductive processing occurs during the vector inner product operation ([C] = [A] $\bigodot$,$\square$ [B]) and proceeds at the hardware dyadic pipeline unit. Every scalar result has to be generated with the component merging delay time in the multiple vector reduction($\bigodot$). In this paper we propose a new design method by which the component merging time could be eliminated from the multiple reduction and the scalar results from the reduction($\bigodot$) could be generated nearly in the almost same condensed time as the input components are fel>ded in the dyadic pipeline unitlo) or the output components are drained out of the dyadic pipeline unit($\square$), so called a dedicated chained pipeline unit for only a inner product operation.