• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.433-442
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• 2018

The reservoir area is defined as the area surrounded by the planned flood level of the dam or the land under the planned flood level of the dam. In this study, supervised classification based on RF (Random Forest), which is a representative machine learning technique, was performed to detect cropland in the reservoir area. In order to classify the cropland in the reservoir area efficiently, the GLCM (Gray Level Co-occurrence Matrix), which is a representative technique to quantify texture information, NDWI (Normalized Difference Water Index) and NDVI (Normalized Difference Vegetation Index) were utilized as additional features during classification process. In particular, we analyzed the effect of texture information according to window size for generating GLCM, and suggested a methodology for detecting croplands in the reservoir area. In the experimental result, the classification result showed that cropland in the reservoir area could be detected by the multispectral, NDVI, NDWI and GLCM images of UAV, efficiently. Especially, the window size of GLCM was an important parameter to increase the classification accuracy.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.83-95
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• 2019

Recently, a variety of IoT data is collected by attaching geosensors to many vehicles that are on the road. IoT data basically has time and space information and is composed of various data such as temperature, humidity, fine dust, Co2, etc. Although a certain sensor data can be retrieved using time, latitude and longitude, which are keys to the IoT data, advanced search engines for IoT data to handle high-level user queries are still limited. There is also a problem with searching large amounts of IoT data without generating indexes, which wastes a great deal of time through sequential scans. In this paper, we propose a unified spatial index model that handles both grid and trajectory queries using a cell-based space-filling curve method. also it presents a visualization method that helps user grasp intuitively. The Trajectory query is to aggregate the traffic of the trajectory cells passed by taxi on the road searched by the user. The grid query is to find the cells on the road searched by the user and to aggregate the fine dust. Based on the generated spatial index, the user interface quickly summarizes the trajectory and grid queries for specific road and all roads, and proposes a Web-based prototype system that can be analyzed intuitively through road and heat map visualization.

• Journal of Physiology & Pathology in Korean Medicine
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• v.24 no.5
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• pp.892-897
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• 2010

Insomnia is common disease generating about 30% incidence in Korea. It describes not only a state of a lack of sleep but also a causative factor for both psychological and physical disorders. According to Oriental Medicine theory, there are many causes of insomnia, and Wibulhwa(胃不和) is one of causes. In this study, we diagnosed as Wibulhwa(胃不和) for three patients and mainly treated with Modified Yukgunja-tang. We compared with before and after Insomnia Severity Index(ISI) treatment. As a result, ISI score falled, and it showed an improvement in insomnia. So we suggest that Modified Yukgunja-tang might be usefully applied to the treatment of insomnia caused by Wibulhwa(胃不和).

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.145-147
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• 2009

This research measures EEG signals which are generating on head skin and extracts brain concentration level related with brain activity. We have developed concentration wireless transmission system by displaying this EEG signal on PDA mobile device. The front head was used for measuring EEG signal and INA128 with TL084 and analog elements was used for measuring EEG signal, amplifying and filtering the signal. Measured analog EEG signals changed into digital signals by using ADC of PIC24FJ192 with 10bit resolution and 500Ks/s sampling rate. So The changed digital signals have transmitted to the PDA by using bluetooth. LabView 8.5 was also used for FFT transformation, frequency and spectrum analysis of the transferred EEG signal. As a result, $\alpha$ wave, $\beta$ wave, $\theta$ wave and $\delta$ wave were classified. we extracted the concentration index by adapting concentration extraction algorithm. This concentration index was transferred into PDA by wireless module and displaying.

• Fashion & Textile Research Journal
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• v.24 no.4
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• pp.443-450
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• 2022

This study developed a three-dimensional helmet mold design software that can design helmets for treating the infant plagiocephaly (flat head syndrome) using three-dimensional head scan data. For this, the three-dimensional head data of sixth SizeKorea body measurement project as well as the data produced by a head modeling software were used to prepare the head shape data of plagiocephaly patients. A total of 14 landmarks and 10 dimensions of heads required for helmet mold shape design and plagiocephaly diagnosis were automatically measured using an anthropometric analysis software. Using the software developed in this study, plagiocephaly can be diagnosed not only visually by three-dimensional head data visualization but also quantitatively by calculating the medically defined indices such as cranial index, which measures the proportions of the head, and the cranial vault asymmetry index, which measures the asymmetry of the head. The basic shape of the helmet mold was automatically generated based on the head scan data. Additionally, it is possible to fine tune the shape of the mold to reflect individual characteristics by using a free form deformation technique. Finally, the designed helmet mold was converted into the data that can be printed on a three-dimensional printer for generating the actual prototype.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.151-157
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• 2019

This study is about the process capability index (PCI). In this study, we introduce several indices including the index $C_{PR}$ and present the characteristics of the $C_{PR}$ as well as its validity. The difference between the other indices and the $C_{PR}$ is the way we use to estimate the standard deviation. Calculating the index, most indices use sample standard deviation while the index $C_{PR}$ uses range R. The sample standard deviation is generally a better estimator than the range R. But in the case of the panel process, the $C_{PR}$ has more consistency than the other indices at the point of non-conforming ratio which is an important term in quality control. The reason why the $C_{PR}$ using the range has better consistency is explained by introducing the concept of 'flatness ratio'. At least one million cells are present in one panel, so we can't inspect all of them. In estimating the PCI, it is necessary to consider the inspection cost together with the consistency. Even though we want smaller sample size at the point of inspection cost, the small sample size makes the PCI unreliable. There is 'trade off' between the inspection cost and the accuracy of the PCI. Therefore, we should obtain as large a sample size as possible under the allowed inspection cost. In order for $C_{PR}$ to be used throughout the industry, it is necessary to analyze the characteristics of the $C_{PR}$. Because the $C_{PR}$ is a kind of index including subgroup concept, the analysis should be done at the point of sample size of the subgroup. We present numerical analysis results of $C_{PR}$ by the data from the random number generating method. In this study, we also show the difference between the $C_{PR}$ using the range and the $C_P$ which is a representative index using the sample standard deviation. Regression analysis was used for the numerical analysis of the sample data. In addition, residual analysis and equal variance analysis was also conducted.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.4
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• pp.518-525
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• 2016

This paper presents the characteristics of non-fundamental multi-mode combustion instability and the effects of high-harmonic components on the Rayleigh criterion. Phenomenological observations of multi-harmonic-mode dynamic pressure waves regarding the intensity of harmonic components and the source of wave distortion have been explained by introducing examples of second- and third-order harmonics at various amplitudes. The amplitude and order of the harmonic components distorted the wave shapes, including the peak and the amplitude, of the dynamic pressure and heat release, and consequently the temporal Rayleigh index and its integrals. A cause-and-effect analysis was used to identify the root causes of the phase delay and the amplification of the Rayleigh index. From this analysis, the skewness of the dynamic pressure turned out to be a major source in determining whether multi-mode instability is driving or damping, as well as in optimizing the combustor design, such as the mixing length and the combustor length, to avoid unstable regions. The results can be used to minimize errors in predicting combustion instability in cases of high multi-mode combustion instability. In the future, the amount of research and the number of applications will increase because new fuels, such as fast-burning syngases, are prone to generating multi-mode instabilities.

• The Journal of the Korea Contents Association
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• v.9 no.7
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• pp.304-314
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• 2009

A valuation of the most hotels in Korea have been decided by their asset value and influenced by real estate market. On the other hand, most hotels aim to maximize their through generating profit as other enterprise do it. Therefore a valuation of the hotel industry should be decided from calculating in their profit value. This study is tried to find out the relationships of the company value by free cash flow model between accounting index in hotel industry. The results are as follows. First, there is a 25% gap between high level and low level in hotel industry. Second, in the first rate hotels it is meaningful 99% between asset size and liability rate. Third, there is 99% meaningful relationship asset size of the first level and second level hotels and company values.

• Journal of Power System Engineering
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• v.20 no.6
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• pp.27-33
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• 2016

BLDC motors have the strong point of allowing high-efficiency operation, yet with the weak point of requiring position information for operation. Moreover, there have recently been frequent cases where the product differentiation of even a cheap BLDC motor demanded a high level of control performance similar to that of a controller using a high-precision position sensor. This paper proposes low cost position sensor that enables the acquisition of rotor position information based on index and incremental PWM, using a single position sensor instead of an expensive incremental encoder or a cheap 3 phase hall sensor. The characteristic of the proposed encoder is that index information at every $60^{\circ}$ of electrical angle is inscribed on the encoder disk, as well as a multiple number of values representing information about PWM, which is obtained by modulating information about the electrical angle of the rotor that has the resolution of $60^{\circ}$. Such a method has the characteristic of enabling the acquisition of high-precision position information based on the information about a multiple number of PWM waveforms and counter values that have all been inscribed on the encoder disk for each $60^{\circ}$ range. The feasibility of the proposed new encoder was verified by fabricating a prototype encoder generating 240 pulses, followed by confirming its performance using Micom's capture and software counter functions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2619-2643
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• 2018

In this paper, a new clustering algorithm based on the connected region generation (CRG-clustering) is proposed. It is an effective and robust approach to clustering on the basis of the connectivity of the points and their neighbors. In the new algorithm, a connected region generating (CRG) algorithm is developed to obtain the connected regions and an isolated point set. Each connected region corresponds to a homogeneous cluster and this ensures the separability of an arbitrary data set theoretically. Then, a region expansion strategy and a consensus criterion are used to deal with the points in the isolated point set. Experimental results on the synthetic datasets and the real world datasets show that the proposed algorithm has high performance and is insensitive to noise.