• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.4
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• pp.22-29
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• 2015

Quadrotor is widely used in variable application nowadays. Due to its inherent unstable characteristics, control system to augment the stability is essential for quadrotor operation. To design control system and verify its performance through simulation, accurate dynamic model is required. Quadrotor dynamic model is simply compared with conventional rotorcraft such as helicopter. However, the accurate dynamic model of quadrotor is not easy to develop because of the highly correlated aerodynamic effect of each rotor. In this paper, quadrotor dynamic model is identified from the flight data using frequency domain approach. Flight test of quadrotor is performed in closed loop configuration with stability augmentation system included. Frequency sweep input is applied in each of lateral, longitudinal, yaw and heave axis separately. The bare dynamic model is identified from the flight data of quadrotor responses and thrust measurement through Pulse Width Modulation(PWM) data. The frequency responses of identified model match well with those of flight data, and time responses of identified model for doublet input in each axis are also shown to agree with flight data.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.15 no.2
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• pp.1-8
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• 2007

In this research, algorithm and software for the medium frequency signal analysis of DGPS(Differential Global Positioning System) station were developed. Based on new MF(Medium Frequency) algorithm, the software of NDGPS(National DGPS) signal analysis was developed for coverage analysis. Predicted MF propagation data from this software was compared to the measurement data for the verification of a developed MF algorithm. GIS(Geographic Information System) techniques including digital map with elevation data were used because MF propagation is closely related to ground conductivity, mountains, building intensity.

• Journal of the Ergonomics Society of Korea
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• v.21 no.2
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• pp.1-11
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• 2002

Classification of Korean characters(alphabets) and frequency data of them are studied that is essential to information process of Korean. We defined a classification of characters using the concept of 'set of 2 parts' and 'set of 3 parts', and we researched frequencies about all combinations of continual two characters. These data would be important basic data to design input device of computer, for example.

• Fashion & Textile Research Journal
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• v.20 no.5
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• pp.533-547
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• 2018

The objective of this study is to examine the perception of golfwear and related trends based on major keywords and associated words related to golfwear utilizing big data. For this study, the data was collected from blogs, Jisikin and Tips, news articles, and web $caf{\acute{e}}$ from two of the most commonly used search engines (Naver & Daum) containing the keywords, 'Golfwear' and 'Golf clothes'. For data collection, frequency and matrix data were extracted through Textom, from January 1, 2016 to December 31, 2017. From the matrix created by Textom, Degree centrality, Closeness centrality, Betweenness centrality, and Eigenvector centrality were calculated and analyzed by utilizing Netminer 4.0. As a result of analysis, it was found that the keyword 'brand' showed the highest rank in web visibility followed by 'woman', 'size', 'man', 'fashion', 'sports', 'price', 'store', 'discount', 'equipment' in the top 10 frequency rankings. For centrality calculations, only the top 30 keywords were included because the density was extremely high due to high frequency of the co-occurring keywords. The results of centrality calculations showed that the keywords on top of the rankings were similar to the frequency of the raw data. When the frequency was adjusted by subtracting 100 and 500 words, it showed different results as the low-ranking keywords such as J. Lindberg in the frequency analysis ranked high along with changes in the rankings of all centrality calculations. Such findings of this study will provide basis for marketing strategies and ways to increase awareness and web visibility for Golfwear brands.

• Water Engineering Research
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• v.1 no.1
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• pp.49-61
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• 2000

Magnitude-frequency relationships are used in the design of dams, highway bridges, culverts, water supply systems, and flood control structures. In this paper, possible techniques for analyzing flood frequency at a site are presented. A currently used approach to flood frequency analysis is based on the concept of parametric statistical inference. In this analysis, the assumption is make that the distribution function describing flood data in known. However, such an assumption is not always justified. Even though many people have shown that the nonparametric method provides a better fit to the data than the parometric method and gives more reliable flood estimates. the noparpmetric method implies a small probability in extrapolation beyond the highest observed data in the sample. Therefore, a remedy is presented in this paper by introducing an estimator which mixes parametric and nonparametric density estimate.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.155-164
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• 2015

In this paper, we propose a new color interpolation method based on trilateral filter approach, which not only preserve the high-frequency components(image edge) while interpolating the missing raw data of color image(bayer data pattern), but also immune to the image noise components and better preserve the detail of the low-frequency components. The method is the trilateral filter approach applying a gradient to the low frequency components of the image signal in order to preserve the high-frequency components and the detail of the low-frequency components through the measure of the freedom of similarity among adjacent pixels. And also we perform Gaussian smoothing to the interpolated image data in order to robust to the noise. In this paper, we compare the conventional demosaicing algorithm and the proposed algorithm using 10 test images in terms of hue MAD, saturation MAD and CPSNR for the objective evaluation, and verify the performance of the proposed algorithm.

• Korea Journal of Hospital Management
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• v.7 no.4
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• pp.152-171
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• 2002

The research objective is segmenting outpatients for CRM(Customer Relationship Management) in medical service. Using modified RFM(Recently, Frequency, Monetary) method based on frequency and profitability in the hospital, the data were analyzed with the data mining technique. The result can be summarized as follows : The outpatients were semented into the four groups: 1) the loyal patient group, who have kept visiting until recently and give high profitability; 2) potential loyal patient group, who give lower profitability but high frequency of use, 3) potential withdrawer patient group, who have lower frequency of use but give high profitability and; 4) withdrawer patient group, who give low frequency of use and have not visited recently.

• Journal of Wetlands Research
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• v.20 no.2
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• pp.105-115
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• 2018

The frequency analysis of hydrometeorological data is one of the most important factors in response to natural disaster damage, and design standards for a disaster prevention facilities. In case of frequency analysis of hydrometeorological data, it assumes that observation data have statistical stationarity, and a parametric method considering the parameter of probability distribution is applied. For a parametric method, it is necessary to sufficiently collect reliable data; however, snowfall observations are needed to compensate for insufficient data in Korea, because of reducing the number of days for snowfall observations and mean maximum daily snowfall depth due to climate change. In this study, we conducted the frequency analysis for snowfall using the Bootstrap method and SIR algorithm which are the resampling methods that can overcome the problems of insufficient data. For the 58 meteorological stations distributed evenly in Korea, the probability of snowfall depth was estimated by non-parametric frequency analysis using the maximum daily snowfall depth data. The results of frequency based snowfall depth show that most stations representing the rate of change were found to be consistent in both parametric and non-parametric frequency analysis. According to the results, observed data and Bootstrap method showed a difference of -19.2% to 3.9%, and the Bootstrap method and SIR(Sampling Importance Resampling) algorithm showed a difference of -7.7 to 137.8%. This study shows that the resampling methods can do the frequency analysis of the snowfall depth that has insufficient observed samples, which can be applied to interpretation of other natural disasters such as summer typhoons with seasonal characteristics.

• Proceedings of the KIEE Conference
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• 2001.11a
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• pp.213-215
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• 2001

We investigated the frequency characteristics of surges induced on Lan equipments by using V-F converter. which installed on the second part of protection system. We stored and analyzed the frequency converting data with the amplitude of overvoltage. In addition. The data acquisition system was made so that we could be examine the results wave through WEB. From this results, it is found that this frequency analysis could be helped for design and protection of various undesired surges.

• Water Engineering Research
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• v.2 no.1
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• pp.1-10
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• 2001

The frequency analyses for the precipitation data in Korea were performed. We used daily maximum series, monthly maximum series, and annual series. For nonparametric frequency analyses, variable kernel estimators were used. Nonparametric methods do not require assumptions about the underlying populations from which the data are obtained. Therefore, they are better suited for multimodal distributions with the advantage of not requiring a distributional assumption. In order to compare their performance with parametric distributions, we considered several probability density functions. They are Gamma, Gumbel, Log-normal, Log-Pearson type III, Exponential, Generalized logistic, Generalized Pareto, and Wakeby distributions. The variable kernel estimates are comparable and are in the middle of the range of the parametric estimates. The variable kernel estimates show a very small probability in extrapolation beyond the largest observed data in the sample. However, the log-variable kernel estimates remedied these defects with the log-transformed data.