• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.55-74
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• 2005

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper employs a relatively new machine learning technique, support vector machines (SVMs). to bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use grid search technique using 5-fold cross-validation to find out the optimal values of the parameters of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM. we compare its performance with multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.124-135
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• 2021

Object detection is a fundamental yet challenging task in computer vision that plays an important role in object recognition, tracking, scene analysis and understanding. This paper aims to propose a multiproperty fusion algorithm for moving object detection. First, we build a scale-invariant feature transform (SIFT) vector field and analyze vectors in the SIFT vector field to divide vectors in the SIFT vector field into different classes. Second, the distance of each class is calculated by dispersion analysis. Next, the target and contour can be extracted, and then we segment the different images, reversal process and carry on morphological processing, the moving objects can be detected. The experimental results have good stability, accuracy and efficiency.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1487-1490
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• 2003

In this paper, the application of object-oriented Data Model to develop a multibody dynamic system, called O-DYN, is introduced. Mechanical components, such as bodies, joints, forces are modeled as objects which have data and method by using object-oriented modeling methodology. O-DYN, a dynamic analysis system, based on the object-oriented modeling concept is made in C++. One example is analyzed through the O-DYN, It is expected that the analysis program or individual module constructed in this paper would be useful for mechanical engineers in predicting the dynamic responses of multibody systems and developing an analysis program

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.11
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• pp.1071-1077
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• 2010

The reduction of the vehicle interior noise has been the main interest of noise and vibration harshness(NVH) engineers. A passenger vehicle has various and complicated transmission paths of sound and vibration. In order to identify the mechanism of transfer path, estimation of excitation force and exact modeling of transfer path are required. This paper presents method for estimating the noise source contribution on the road noise of the vehicle in a multiple input system where the input sources may be coherent with each other. And vector synthesis technique is employed to identify the characteristics of road noise and its transmission to vehicle compartment through noise and vibration analysis. Vibration reduction efficiency of each transfer path is evaluated by comparing individual vector components obtained virtual simulation.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.399-407
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• 2021

Stock movement is difficult to predict because it has dynamic characteristics and is influenced by many factors. Even so, there are some approaches to predict stock price movements, namely technical analysis, fundamental analysis, and sentiment analysis. Many researches have tried to predict stock price movement by utilizing these analysis techniques. However, the results obtained are varied and inconsistent depending on the variables and object used. This is because stock price movement is influenced by a variety of factors, and it is likely that those studies did not cover all of them. One of which is that no research considers the use of fundamental analysis in terms of currency exchange rates and the use of foreign stock price index movement related to the technical analysis. This research aims to predict stock price movements in Indonesia based on sentiment analysis, technical analysis, and fundamental analysis using Support Vector Machine. The result obtained has a prediction accuracy rate of 65,33% on an average. The inclusion of currency exchange rate and foreign stock price index movement as a predictor in this research which can increase average prediction accuracy rate by 11.78% compared to the prediction without using these two variables which only results in average prediction accuracy rate of 53.55%.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.811-816
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• 2019

This paper first proposes a technique to separate clean speech signals and mixed noise signals by using an independent vector analysis algorithm of frequency band for 4 channel speech source signals with a noise. An improved output speech signal from the proposed independent vector analysis algorithm is obtained by using the cross-correlation between the signal outputs from the frequency domain delay-sum beamforming and the output signals separated from the proposed independent vector analysis algorithm. In the experiments, the proposed algorithm improves the maximum SNRs of 10.90dB and the segmental SNRs of 10.02dB compared with the frequency domain delay-sum beamforming algorithm for the input mixed noise speeches with 0dB and -5dB SNRs including white noise, respectively. Therefore, it can be seen from this experiment and consideration that the speech quality of this proposed algorithm is improved compared to the frequency domain delay-sum beamforming algorithm.

• Korean Journal Plant Pathology
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• v.11 no.1
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• pp.66-72
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• 1995

The coat protein (CP) gene of cucumber mosaic virus-As (CMV-As) strain was engineered for expression in the plant by using the cauliflower mosaic virus 35S transcript regulatory sequences. The CP gene was cloned into an Agrobacterium-derived binary vector. A chimeric gene was constructed by the cDNA of CMV-As CP and plant expression vector pBI121. The clone, pCMAS66, was first introduced into the phagemid vector pSPORT1 for situating sense orientation for translation and making restriction sites in order to re-introduce plant expression vector, pHI121. The resulting subclone pCASCP02 and plant expression vector pBI121 were treated with BamHI-SacI for excising the target gene and removing GUS gene, respectively. After Agrobacterium transformation by freeze-thaw technique, the clone, pCMASCP121-123 which contains sense orientation of the target gene, was selected and confirmed by restriction endonuclease analysis. The CMV-As CP gene was introduced into A. tumefaciens. The results on tobacco plant transformation with the vector system revealed that the system could be successfully introduced and showed high frequency of selection to putative transformations.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.5
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• pp.421-428
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• 2015

An advanced direct torque control (DTC) with pulse width modulation (PWM) method is presented in this paper. The duty ratio calculation of the selected voltage vector is based on the voltage functions of the selected voltage vector according to the sector angle. The proposed DTC uses a conventional DTC scheme with six sector divisions and switching rules. However, the winding voltages are supplied by the PWM approach. Furthermore, the duty ratio of the switching voltage vector is determined by the flux, torque error, and motor speed. The base voltage that shall determine the duty ratio can be calculated by approximate voltage functions according to the voltage angle. For the calculation of base voltages, second-order quadratic functions are used to express the output voltage of the selected voltage vector according to voltage angle. The coefficients for the second-order quadratic functions are selected by the voltage vector, which is determined by the switching rules of the DTC. In addition, the voltage functions are calculated by the coefficients and voltage angle between the voltage vector and rotor position. The switching voltages from the calculated duty ratio can supply the proper torque and flux to reduce the ripple and error. The proposed control scheme is verified through practical experimental comparisons.

• Bulletin of the Korean Space Science Society
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• 2004.04a
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• pp.66-66
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• 2004

Observability of two spacecraft system is considered with relative line-of-sight vector measurements between two spacecraft system for autonomous navigation using the linear observability analysis. First, the dynamical equations and measurement models are introduced, and the basic assumption of attitude knowledge for one of two spacecrafts is explained. Then, we introduce a pair of nominal orbits of two spacecraft system, and the observability analysis for the nominal orbits is presented with the available measurements (for the numerical observability analysis). (omitted)

• Journal of Power Electronics
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• v.17 no.4
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• pp.972-982
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• 2017

The Park's vector of stator current is a popular technique for the detection of induction motor faults. While the detection of the faulty condition using the Park's vector technique is easy, the classification of different types of faults is intricate. This problem is overcome by the Multiple Park's Vector (MPV) approach proposed in this paper. In this technique, the characteristic fault frequency component (CFFC) of stator winding faults, rotor winding faults, unbalanced voltage and bearing faults are extracted from three phase stator currents. Due to constructional asymmetry, under the healthy condition these characteristic fault frequency components are unbalanced. In order to balanced them, a correction factor is added to the characteristic fault frequency components of three phase stator currents. Therefore, the Park's vector pattern under the healthy condition is circular in shape. This pattern is considered as a reference pattern under the healthy condition. According to the fault condition, the amplitude and phase of characteristic faults frequency components changes. Thus, the pattern of the Park's vector changes. By monitoring the variation in multiple Park's vector patterns, the type of fault and its severity level is identified. In the proposed technique, the diagnosis of faults is immune to the effects of unbalanced voltage and multiple faults. This technique is verified on a 7.5 hp three phase wound rotor induction motor (WRIM). The experimental analysis is verified by simulation results.