• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.264-270
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• 2012

e-Training focusing on the experience and practice accelerates actual-active learning and enforces the learning effects against the existing theory based education. The most typical hans-on training system is augmented reality. Especially, in the training field installed augmented reality system, the automobile maintenance trainee experiences effective training with the immediate information, which is indicating the location of parts and the procedure of repairing. The tracking is the core technology of the augmented reality system. The performance of augmented reality system depends on the tracking technology. Therefore, this paper suggests the tracking technology which is proper to the e-Training augmented reality service technology for the car mechanics.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.2
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• pp.71-80
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• 2002

According to the rapid growth of high speed and precise industry, the application of synchronous motor has been increased. In the application fields, these fast dynamic response is of prime importance. In particular, since the PMLSM(Permanent Magnet Linear Synchronous Motor) has characteristics of high speed, high thrust, it has been used in high-performance servo drive. From these reasons, it is recently used for high precise position control, and machine tool. In this paper, a study of the sliding mode with VSS (Variable Structure System) design for a PMLSM is presented. For fast and precise motion control of PMLSM, the compensation of disturbance and parameter variation is necessary. Hence we eliminate the reaching phase use of VSS that is changed to switching function and vector control using the state observer. And we proposed to sliding mode control algorithm so that realize fast response without overshoot, disturbance and parameter variation.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.118-121
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• 2014

Image interpolation is a method of determining the value of new pixel coordinate in the process of image scaling. Recently, image contents are likely to be a large-capacity, interpolation algorithm is required to generate fast enhanced result image. In this paper, fast multiple mixed image interpolation for image resolution enhancement is proposed. The proposed method estimates expected 12 shortfalls from four sub-images of a input image, and generates the result image that is interpolated in the combination of the expected shortfalls with the input image. The experimental results demonstrate that PSNR increases maximum value of 1.9dB, SSIM increases maximum value of 0.052, and the subjective quality is superior to any other compared methods. Moreover, it is known by algorithm running time comparison that the proposed method has been at least three times faster than the compared conventional methods. The proposed method can be useful for application on image resolution enhancement.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.2
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• pp.123-146
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• 2005

This study aims to find consistent strategies for feature selection and feature weighting methods, which can improve the effectiveness and efficiency of kNN text classifier. Feature selection criteria and feature weighting methods are as important factor as classification algorithms to achieve good performance of text categorization systems. Most of the former studies chose conflicting strategies for feature selection criteria and weighting methods. In this study, the performance of several feature selection criteria are measured considering the storage space for inverted index records and the classification time. The classification experiments in this study are conducted to examine the performance of IDF as feature selection criteria and the performance of conventional feature selection criteria, e.g. mutual information, as feature weighting methods. The results of these experiments suggest that using those measures which prefer low-frequency features as feature selection criterion and also as feature weighting method. we can increase the classification speed up to three or five times without loosing classification accuracy.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.99-104
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• 2009

We propose a waveform inversion method for SH-wave data obtained in a shallow seismic refraction survey, to determine a 2D inhomogeneous S-wave profile of shallow soils. In this method, a 2.5D equation is used to simulate SH-wave propagation in 2D media. The equation is solved with the staggered grid finite-difference approximation to the 4th-order in space and 2nd-order in time, to compute a synthetic wave. The misfit, defined using differences between calculated and observed waveforms, is minimised with a hybrid heuristic search method. We parameterise a 2D subsurface structural model with blocks with different depth boundaries, and S-wave velocities in each block. Numerical experiments were conducted using synthetic SH-wave data with white noise for a model having a blind layer and irregular interfaces. We could reconstruct a structure including a blind layer with reasonable computation time from surface seismic refraction data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.866-869
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• 2015

With the advance in semiconductor technology, the number of elements that can be integrated in system-on-chip(SoC) increases exponentially, and thus voltage scaling is indispensable to enhance energy efficiency. Near-threshold voltage computing(NTC) improves the energy efficiency by an order of degree, hence it is able to overcome the limitation of conventional super-threshold voltage computing(STC). Although NTC-based low performance manycore system can be used to maximize energy efficiency, it demands more number of cores to sustain the performance, which results in considerable increase of area. In this paper, we analyze NTC manycore architecture considering the trade-offs between performance, power, and area. Therefore, we propose an algorithmic methodology that can optimize power consumption and area while satisfying the required performance by determining the constrained number of cores and size of caches and clusters in NTC environment. Experimental results show that proposed NTC architecture can reduce power consumption by approximately 16.5 % while maintaining the performance of STC core under area constraint.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.1-8
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• 2004

According to the development of the Internet and the pervasion of Data Base, it is not easy to search for necessary information from the huge amounts of data. In order to do efficient analysis of a large amounts of data, this paper proposes a method for pattern classification based on the effective strategy for dimension reduction for narrowing down the whole data to what users wants to search for. To analyze data effectively, Radial Basis Function Networks based on VC-dimension of Support Vector Machine, a model of statistical teaming, is proposed in this paper. The model of Radial Basis Function Networks currently used performed the preprocessing of Perceptron model whereas the model proposed in this paper, performing independent analysis on VD-dimension, classifies each datum putting precise labels on it. The comparison and estimation of various models by using Machine Learning Data shows that the model proposed in this paper proves to be more efficient than various sorts of algorithm previously used.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.115-125
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• 2011

Manufacturing companies usually manage the process to achieve high quality using various types of control chart in statistical process control. When an assignable cause occurs in a process, the data in the control chart changes with different patterns by the specific causes. It is important in process control to classify the CCP (Control Chart Pattern) recognition for fast decision making. In former research, gathered data from process used to apply as raw data, leads to degrade the performance of recognizer and to decrease the learning speed. Therefore, feature based recognizer, employing feature extraction method, has been studied to enhance the classification accuracy and to reduce the dimension of data. We propose the method to extract features that take the distances between CCP data and reference vector generated from BDK (Bi-Directional Kohonen Network). We utilize those features as the input vectors in ANN (Artificial Neural Network) and compare with raw data applied ANN to evaluate the performance.

• KSBB Journal
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• v.15 no.1
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• pp.14-21
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• 2000

In this study, algae cultivation using the photobioreactor has been applied to remove the nitrogen and phosphorus compounds in the wastewater of the livestock industry. The optimal ratio of nitrate and ortho-phosphate concentration was found for the enhancement of removal efficiency. To achieve the high density culture of algae, the photobioreactor consisted of optical fibers wes developed to get the sufficient light intensity. The light could be illuminated uniformly from light source to the entire reactor by the optical fibers. The structured kinetic model was proposed to describe the growth rate, consumption rate of nitrates and ortho-phosphates in algae culture. The self-organizing fuzzy logic controller incorporated with genetic algorithm was constructed to control the semi-continuous wastewater treatment system. The proposed fuzzy logic controller was applied to maintain the nitrated concentration at the given set-point with the control of wastewater feeding rate. The experimental results showed that the self-organizing fuzzy logic controller could keep the nitrate concentration and enhance algae growth.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.71-78
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• 2010

The road safety depend on many road factors like vertical alignment, horizontal alignment and road cross section angle. These data are hardly to get with drawings, and the real data are differ from drawings because of road pavement overlay, etc. To get these data, so many time and cost are needed, moreover it is dangerous work in heavy traffic road. In this study we obtained the road safety data with RoSSAV(Road Safety Survey & Analysis Vehicle) of Korea Institute of Construction Technology in accordance with traffic flow, and make analysis of road safety with the vertical alignment, horizontal alignment and road cross section angle data. We derived the safety improvement method in Young-dong accident prone spot and described detail method in this paper.