• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.7-14
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• 2011

Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rate per fault (hazard function). This infinite non-homogeneous Poisson process is model which reflects the possibility of introducing new faults when correcting or modifying the software. In this paper, polynomial hazard function have been proposed, which can efficiency application for software reliability. Algorithm for estimating the parameters used to maximum likelihood estimator and bisection method. Model selection based on mean square error and the coefficient of determination for the sake of efficient model were employed. In numerical example, log power time model of the existing model in this area and the polynomial hazard function model were compared using failure interval time. Because polynomial hazard function model is more efficient in terms of reliability, polynomial hazard function model as an alternative to the existing model also were able to confirm that can use in this area.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.3
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• pp.220-229
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• 2003

An experimental study on the air-side pressure drop and heat transfer coefficient of slit fin-tube heat exchanger has been carried out. The data reduction methodology for air-side heat transfer coefficients in the literature is not based on a consistent approach. This paper focuses on new method of data reduction to obtain the air-side performance of fin-tube heat exchanger using R22 and recommends standard procedures for dry surface heat transfer estimation in fin-tube heat exchanger having refrigerant on the tube-side. Results are presented as plots of friction f-factor and Colburn j -factor against Reynolds number based on the fin collar outside diameter and compared with previous studies. The data covers a range of refrigerant mass fluxes of 150~250 kg/$m^2$s with air flows at velocity ranges from 0.6 m/s to 1.6 m/s.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.50-52
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• 2004

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and the floor decreases suddenly, the robot has slip state. First of all, this paper models adhesion characteristics and slip in wheeled robot. Secondly, the paper proposes estimation method of adhesion force coefficient according to slip velocity. In oder to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. The paper proposes an anti-slip control system based on an ordinary disturbance observer, that is, the anti-slip control is achieved by reducing the driving torque enough to give maximum adhesion force coefficient. These procedure is implemented using a Pioneer 2-DXE parameter.

• Journal of the Optical Society of Korea
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• v.9 no.3
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• pp.107-110
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• 2005

An optical method of measuring hematocrit noninvasively is presented. An LED Light with multiple wavelengths was irradiated on fingernail and transmitted light from the finger was measured to predict hematocrit. A finger probe contained an LED array and detector. Our previous experience showed that prediction accuracy was sensitive to reliability of the finger probe hardware and we optimized the finger probe parameters such as the internal color, detector area and the emission area of a light source based on Design of Experiment. Using the optimized finger probe, we developed a hematocrit monitoring system and tested with 549 persons. For the calibration model with 368 persons, a regression coefficient of 0.74 and a standard deviation of 3.67 and the mean percent error of $8\%$ were obtained. Hematocrits for 181 persons were predicted. We achieved a mean percent error of $8.2\%$ where the regression coefficient was 0.68 and the standard deviation was 3.69.

• Annual Conference of KIPS
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• 2010.04a
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• pp.405-408
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• 2010

This paper presents a new feature extraction technique, correlation coefficient and Manhattan distance (MD) based method for recognition of rotated object in an image. This paper also represented a new concept of intensity invariant. We extracted global features of an image and converts a large size image into a one-dimensional vector called circular feature vector's (CFVs). An especial advantage of the proposed technique is that the extracted features are same even if original image is rotated with rotation angles 1 to 360 or rotated. The proposed technique is based on fuzzy sets and finally we have recognized the object by using histogram matching, correlation coefficient and manhattan distance of the objects. The proposed approach is very easy in implementation and it has implemented in Matlab7 on Windows XP. The experimental results have demonstrated that the proposed approach performs successfully on a variety of small as well as large scale rotated images.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.481-494
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• 2008

In this paper we propose Fourier magnitudes based privacy preserving clustering on time-series data. The previous privacy-preserving method, called DFT coefficient method, has a critical problem in privacy-preservation itself since the original time-series data may be reconstructed from privacy-preserved data. In contrast, the proposed DFT magnitude method has an excellent characteristic that reconstructing the original data is almost impossible since it uses only DFT magnitudes except DFT phases. In this paper, we first explain why the reconstruction is easy in the DFT coefficient method, and why it is difficult in the DFT magnitude method. We then propose a notion of distance-order preservation which can be used both in estimating clustering accuracy and in selecting DFT magnitudes. Degree of distance-order preservation means how many time-series preserve their relative distance orders before and after privacy-preserving. Using this degree of distance-order preservation we present greedy strategies for selecting magnitudes in the DFT magnitude method. That is, those greedy strategies select DFT magnitudes to maximize the degree of distance-order preservation, and eventually we can achieve the relatively high clustering accuracy in the DFT magnitude method. Finally, we empirically show that the degree of distance-order preservation is an excellent measure that well reflects the clustering accuracy. In addition, experimental results show that our greedy strategies of the DFT magnitude method are comparable with the DFT coefficient method in the clustering accuracy. These results indicate that, compared with the DFT coefficient method, our DFT magnitude method provides the excellent degree of privacy-preservation as well as the comparable clustering accuracy.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.883-893
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• 2019

In this study, crop coefficients were calculated in two different methods and the results were evaluated. In the first method, appropriateness of GLDAS-based evapotranspiration was evaluated by comparing it with observed data of Cheongmi-cheon (CMC) Flux tower. Then, crop coefficient was calculated by dividing actual evapotranspiration with potential evapotranspiration that derived from GLDAS. In the second method, crop coefficient was determined by using MLR (Multiple Linear Regression) analysis with vegetation index (NDVI, EVI, LAI and SAVI) derived from MODIS and in-situ soil moisture data observed in CMC, In comparison of two crop coefficients over the entire period, for each crop coefficient GLDAS K_c and SM&VI K_c, shows the mean value of 0.412 and 0.378, the bias of 0.031 and -0.004, the RMSE of 0.092 and 0.069, and the Index of Agree (IOA) of 0.944 and 0.958. Overall, both methods showed similar patterns with observed evapotranspiration, but the SM&VI-based method showed better results. One step further, the statistical evaluation of GLDAS K_c and SM&VI K_c in specific period was performed according to the growth phase of the crop. The result shows that GLDAS K_c was better in the early and mid-phase of the crop growth, and SM&VI K_c was better in the latter phase. This result seems to be because of reduced accuracy of MODIS sensors due to yellow dust in spring and rain clouds in summer. If the observational accuracy of the MODIS sensor is improved in subsequent study, the accuracy of the SM&VI-based method will also be improved and this method will be applicable in determining the crop coefficient of unmeasured basin or predicting the crop coefficient of a certain area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1149-1154
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• 2017

To obtain good recognition performance of speech recognition system under background noise, it is very important to select appropriate feature parameters of speech. The feature parameter used in this paper is Mel frequency cepstral coefficient (MFCC) with the human auditory characteristics applied to Wiener filter method. That is, the feature parameter proposed in this paper is a new method to extract the parameter of clean speech signal after removing background noise. The proposed method implements the speaker recognition by inputting the proposed modified MFCC feature parameter into a multi-layer perceptron network. In this experiments, the speaker independent recognition experiments were performed using the MFCC feature parameter of the 14th order. The average recognition rates of the speaker independent in the case of the noisy speech added white noise are 94.48%, which is an effective result. Comparing the proposed method with the existing methods, the performance of the proposed speaker recognition is improved by using the modified MFCC feature parameter.

• Magazine of the Korea Concrete Institute
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• v.11 no.1
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• pp.243-254
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• 1999

This paper presents a numerical study for developing the moment magnifier method that is applicable to RC flat plates subject to combined axial compressive and floor load. For the nonlinear finite element analysis, a computer program addressing material and geometric nonlinearities was developed. The flat plates to be studied are designed in accordance with the Direct Design Method in Korean Building Code for Structural Concrete. This paper proposes the buckling force and the moment magnification factor for the flat plate under the governing load condition that is the combined vertical and subsequently applied uniaxial compressive load. The buckling force is defined with two ingredients: the buckling coefficient and the effective flexural rigidity. Parametric studies are performed to investigate variations of the buckling coefficient and the effective flexural rigidity. Based on the numerical results, this paper provides the design values of the buckling coefficient and the effective flexural rigidity, and the design procedure for the moment magnifier method.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.79-84
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• 2022

This paper presents an enhancement method of document restoration capability which is robust for security, loss, and contamination, It is based on two methods, that is, encryption and DnCNN(DeNoise Convolution Neural Network). In order to implement this encryption method, a mathematical model is applied as a spatial frequency transfer function used in optics of 2D image information. Then a method is proposed with optical interference patterns as encryption using spatial frequency transfer functions and using mathematical variables of spatial frequency transfer functions as ciphers. In addition, by applying the DnCNN method which is bsed on deep learning technique, the restoration capability is enhanced by removing noise. With an experimental evaluation, with 65% information loss, by applying Pre-Training DnCNN Deep Learning, the peak signal-to-noise ratio (PSNR) shows 11% or more superior in compared to that of the spatial frequency transfer function only. In addition, it is confirmed that the characteristic of CC(Correlation Coefficient) is enhanced by 16% or more.