• Journal of Advanced Marine Engineering and Technology
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• v.37 no.5
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• pp.533-540
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• 2013

Prime movers in engine rooms inherently are much affected by the adjustment of their governors for the steady state and transient properties, consequently requiring that marine engineers shall be well familiar with the way to manage governor dials for normal operation. The hydro-mechanical governors basically have different control characteristics and adjustment parameters of stability from digital governors. The former include compensation mechanism using dash pot while the control algorithm of the latter is usually based on the PID action. This study is for configuring a simulation module to let trainees practice how to adjust dials for stability on hydraulic governors in the view that the practice by real governors and engines is time consuming and high cost for operation. The governor module includes the adjusting points such as speed set, speed droop, needle valve and compensation pointer with engine module of $2^{nd}$ order coupled. The results of simulation showed satisfactory responses as a training tool for the adjustment of control parameters.

• Journal of the Korean Solar Energy Society
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• v.38 no.2
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• pp.15-31
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• 2018

A program to design a small capacity wind turbine blade is proposed in this study. The program is based on a matlab GUI environment and designed to perform blade design based on the blade element momentum theory. The program is different from other simulation tools available in a point that it can analyze the side-furling power regulation mechanism and also has an algorithm to find out optimal torque schedule above the rated wind speed region. The side-furling power regulation is used for small-capacity horizontal axis wind turbines because they cannot use active pitch control due to high cost which is commonly used for large-capacity wind turbine. Also, the torque schedule above the rated wind speed region should be different from that of the large capacity wind turbines because active pitching is not used. The program developed in this study was validated with the results with FAST which is the only program that can analyze the performance of side-furled wind turbines. For the validation a commercial 10 kW wind turbine data which is available in the literature was used. From the validation, it was found that the performance prediction from the proposed simple program is close to those from FAST. It was also found that the optimal torque scheduling from the proposed program was found to increase the turbine power substantially. Further experimental validation will be performed as a future work.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.3 no.1
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• pp.43-48
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• 2017

We are confirmed to the variation of the transfer condition and the functional penetration by the permitted conversion energy on the skin. The given conversion energy is consist of the flow level of penetration control and go to the processing transfer in the skin that is to create the modeling for algorithm. The energy level of control processing was achieved effectively modeling system that was the composition of auto and local control level in the epidermis-dermis layer. Their penetration pulse control system was consisted of conversion energy with reference of fixing situation and recreation of designed apparatus for the energy control function that was converted to capacity by the size, form and combination. Also, the system was shown accurately distribution of conversion at the depth of skin correction. Therefore, conversion modeling was established effectively to separate the division parts for conversion system. We will be possible to progress the improvement effectiveness of the skin and to consist of the continuous penetration control system for functional energy on the skin.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.289-294
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• 2020

Peptic ulcer disease is a gastrointestinal disorder caused by Helicobacter pylori infection and the use of nonsteroid anti-inflammatory drugs. While many studies have been conducted to find the risk factors of peptic ulcers, there are no studies on the suggestion of peptic ulcer prediction models for Koreans. Therefore, the purpose of this study is to implement peptic ulcer prediction model using machine learning based on demographic information, obesity information, blood information, and nutritional information for middle-aged and elderly people. For model building, wrapper-based variable selection method and naive Bayes algorithm were used. The classification accuracy of the female prediction model was the area under the receiver operating characteristics curve (AUC) of 0.712, and males showed an AUC of 0.674, which is lower than that of females. These results can be used for prediction and prevention of peptic ulcers in the middle and elderly people.

• The Journal of Society for e-Business Studies
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• v.19 no.4
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• pp.45-60
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• 2014

Dentist can obtain 3D anatomical information without distortion and information loss by using dental Computed Tomography scan images on line, and also can make the preoperative plan of implant placement or orthodontics. It is essential to segment individual tooth for making an accurate diagnosis. However, it is very difficult to distinguish the difference in the brightness between the dental and adjacent area. Especially, the root of a tooth is very elusive to automatically identify in dental CT images because jawbone normally adjoins the tooth. In the paper, we propose a method of automatically tooth region segmentation, which can identify the root of a tooth clearly. This algorithm separate the tooth from dental CT scan images by using Seeded Region Growing method on dental crown and by using Level-set method on dental root respectively. By using the proposed method, the results can be acquired average 19.2% better accuracy, compared to the result of the previous methods.

• Journal of Applied Reliability
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• v.17 no.3
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• pp.213-223
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• 2017

Purpose: The purpose of this study is to arrange the life data analysis literatures based on the Bayesian method quantitatively and provide it as tables. Methods: The Bayesian method produces a more accurate estimates of other traditional methods in a small sample size, and it requires specific algorithm and prior information. Based on these three characteristics of the Bayesian method, the criteria for classifying the literature were taken into account. Results: In many studies, there are comparisons of estimation methods for the Bayesian method and maximum likelihood estimation (MLE), and sample size was greater than 10 and not more than 25. In probability distributions, a variety of distributions were found in addition to the distributions of Weibull commonly used in life data analysis, and MCMC and Lindley's Approximation were used evenly. Finally, Gamma, Uniform, Jeffrey and extension of Jeffrey distributions were evenly used as prior information. Conclusion: To verify the characteristics of the Bayesian method which are more superior to other methods in a smaller sample size, studies in less than 10 samples should be carried out. Also, comparative study is required by various distributions, thereby providing guidelines necessary.

• Journal of the Optical Society of Korea
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• v.14 no.3
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• pp.221-227
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• 2010

Aerosol size distribution provides good information for predicting weather changes and understanding cloud formation. Aerosol extinction coefficient and backscattering coefficient are measured by many scientists, but these parameters depend not only on aerosol size but on aerosol concentrations. An algorithm has been developed to measure aerosol parameters such as ${\AA}$ngstr$\ddot{o}$m exponent, color ratio, and LIDAR ratio without any assumptions by using two wavelength rotational Raman LIDAR signals. These parameters are good indicators for the aerosol size. And we can find ${\AA}$ngstr$\ddot{o}$m exponent, color ratio, and LIDAR ratio under various weather conditions. Finally, it can be seen that the ${\AA}$ngstr$\ddot{o}$m exponent has an inverse relationship to the particle size of the aerosol and the color ratio is linearly dependent on the aerosol size. An ${\AA}$ngstr$\ddot{o}$m exponent from 1.2 to 3.1, a color ratio from 0.28 to 1.04, and a LIDAR ratio 66.9 sr at 355 nm and 32.6 sr at 532 nm near the cloud were obtained.

• Journal of the Korea Computer Graphics Society
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• v.3 no.2
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• pp.27-34
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• 1997

3-D image modeling is in high demand for automated visual inspection and non-destructive testing. It also can be useful in biomedical research, medical therapy, surgery planning, and simulation of critical surgery (i.e. cranio-facial). Image processing and image analysis are used to enhance and classify medical volumetric data. Analyzing medical volumetric data is very difficult In this paper, we propose a new image modeling method based on tetrahedrization to improve the visualization of three-dimensional medical volumetric data. In this method, the trivariate piecewise linear interpolation is applied through the constructed tetrahedral domain. Also, visualization methods including iso-surface, color contouring, and slicing are discussed. This method can be useful to the correct and speedy analysis of medical volumetric data, because it doesn't have the ambiguity problem of Marching Cubes algorithm and achieves the data reduction. We expect to compensate the degradation of an accuracy by using an adaptive sub-division of tetrahedrization based on least squares fitting.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6A
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• pp.379-385
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• 2003

In this paper, we propose a time constant control method for sieving local minimum problem of the multiuser detector using Hopfield neural network for synchronous multi-rate code division multiple access(CDMA) system in selective fading environments and its performance is compared with that of the parallel interference cancellation(PIC). We also assume that short scrambling codes of 256 chip length are used an uplink, suggest a simple correlation estimation algorithm and circuit complexity reduction method by using cyclostationarity property of short scrambling code.It is verified that multiuser detector using Hopfield neural network more efficiently cancels multiple access interference(MAI) and obtain better bit error rate and near-far resistant than conventional detector.