• Journal of the Korean Society of Radiology
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• v.11 no.6
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• pp.443-451
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• 2017

The purpose of this study was to comparison of measure signal to noise ratio (SNR) according to change of kernel size from region of interest (ROI) of heart shadow in chest image. We examined images of chest image of 100 patients in a University-affiliated hospital, Seoul, Korea. Chest images of each patient were calculated by using ImageJ. We have analysis socio-demographical variables, SNR according to images, 95% confidence according to SNR of difference in a mean of SNR. Differences of SNR among change of equalization were tested by SPSS Statistics21 ANOVA test for there was statistical significance 95%(p<0.05). In SNR results, with the quality of distributions in the order of kernel size 9*9 image, kernel size 7*7 image and original chest image, kernel size 3*3 image (p<0.001). In conclusion, this study would be that quantitative evaluation of heart shadow on chest image can be used as an adjunct to the kernel size chest image.

• Korean Journal of Optics and Photonics
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• v.15 no.4
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• pp.385-390
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• 2004

In this paper, we designed a 4-bit optical true time-delay(TTD) for phased array antennas(PAAs), which is composed of a wavelength-fixed optical source, 2 ${\times}$ 2 optical MEMS switches, and fiber-optic delay lines. A 4-bit TTD with a unit time delay difference of 6 ps for 10-GHz PAAs has been implemented. Measurement results on time delay show an error of -0.4 ps at maximum, corresponding to a radiation angle error of less than 1.63$^{\circ}$. Thus, the TTD implemented in this research performs in excellent agreement with theory. Each TTD line, composed of MEMS switches and fiber-optic delay lines, connected to the corresponding antenna element has insertion loss in between 1.36 ㏈ and 2.40 ㏈ depending upon the setup of the switches. On the other hand, the insertion loss difference between TTD lines was 0.32 ㏈ at maximum for a fixed radiation angle. The TTD structure proposed in this paper might be more reliable and economical than those previously proposed using tunable wavelength sources if proper power equalization either with gain control of RF amplifiers or variable attenuators is achieved.

• Korean Journal of Oriental Medicine
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• v.13 no.3
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• pp.119-124
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• 2007

Introduction: In Oriental medicine, the status of tongue is the important indicator to diagnose one's health, because it represents physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive, so tongue diagnosis is most widely used in Oriental medicine. By the way, since tongue diagnosis is affected by examination circumstances a lot, its performance depends on a light source, degrees of an angle, a medical doctor's condition etc. Therefore, it is not easy to make an objective and standardized tongue diagnosis. In order to solve this problem, in this study, we tried to design a discriminant function for thick and thin coating with color vectors of preprocessed image. Method: 52 subjects, who were diagnosed as white-coated tongue, were involved. Among them, 45 subjects diagnosed as thin coating and 7 subjects diagnosed as thick coating by oriental medical doctors, and then their tongue images were obtained from a digital tongue diagnosis system. Using those acquired tongue images, we implemented two steps: Preprocessing and image analyzing. The preprocessing part of this method includes histogram equalization and histogram stretching at each color component, especially, intensity and saturation. It makes the difference between tongue substance and tongue coating was more visible, so that we can separate tongue coating easily. Next part, we analyzed the characteristic of color values and found the threshold to divide tongue area into coating area. Then, from tongue coating image, it is possible to extract the variables that were important to classify thick and thin coating. Result : By statistical analysis, two significant vectors, associated with G, were found, which were able to describe the difference between thick and thin coating very well. Using these two variables, we designed the discriminant function for coating classification and examined its performance. As a result, the overall accuracy of thick and thin coating classification was 92.3%. Discussion : From the result, we can expect that the discriminant function is applicable to other coatings in a similar way. Also, it can be used to make an objective and standardized diagnosis.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.3
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• pp.139-146
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• 2018

Underwater acoustic communication can be applied to various area such as scientific, commercial and military survey using Autonomous Underwater Vehicles and Unmanned Underwater Vehicles. Underwater communication is studying very actively by advanced country like United States. But differ from wireless communication in the air, underwater acoustic communication has some difficult problems, ISI(Inter Symbol Interference) due to multipath and limit of transmission bandwidth due to slow propagation of sound wave. In this paper, SC-FDE and OFDM transmission system for the cancellation of ISI in conjunction with underwater acoustic channel modeling are applied to the underwater simulation of communication. The performance of these methods in the simulation guide to possibility of adopting in underwater acoustic communication algorithm. For this purpose, we compare SER performance of SC-FDE with that of OFDM for modelled underwater channel. Underwater channel is generated by Bellhop model. Simulation results show above 5dB SNR gain at 10-3 SER. And it demonstrate SC-FDE is efficient method for underwater acoustic communication.

• Journal of Science Education
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• v.32 no.1
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• pp.61-72
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• 2008

The purpose of the study is to research students' proficiency with systems-thinking approach concerning water cycles and to acquire data on Earth System-related concepts based on students' feedback. To achieve the purpose of the study, I chose 4 mid-level high school juniors living in Pohang, where the high school equalization policy has not been implemented, and the students answered a questionnaire about water cycles. Then, based on the results, I created a causal map and evaluated it using systems-thinking analysis. The results of the study are as follows: First of all, among the answers of the subjects, there were 21 concepts related to the conception of the earth system : 14 of the conceptions were linked scientifically, and 7 of the conceptions were not linked scientifically. Secondly, results of the causal map of what the subjects described showed that only two students'(A and C) feedback loops were completed, and that student C's feedback loop included unscientific reasoning. In conclusion, this study indicated that the students failed to understand the water cycle with the systems-thinking approach, or alternatively they applied low-level systems-thinking approach and had a lower understanding of it.

• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.49-56
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• 2018

Euclidean distance (ED) between error distribution and Dirac delta function has been used as an efficient performance criterion in impulsive noise environmentsdue to the outlier-cutting effect of Gaussian kernel for error signal. The gradient of ED for its minimization has two components; $A_k$ for kernel function of error pairs and the other $B_k$ for kernel function of errors. In this paper, it is analyzed that the first component is to govern gathering close together error samples, and the other one $B_k$ is to conduct error-sample concentration on zero. Based upon this analysis, it is proposed to normalize $A_k$ and $B_k$ with power of inputs which are modified by kernelled error pairs or errors for the purpose of reinforcing their roles of narrowing error-gap and drawing error samples to zero. Through comparison of fluctuation of steady state MSE and value of minimum MSE in the results of simulation of multipath equalization under impulsive noise, their roles and efficiency of the proposed normalization method are verified.

• Clean Technology
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• v.10 no.2
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• pp.101-109
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• 2004

PSA and VSA processes have been used broadly to produce oxygen from ambient air in midium- or small-sized plants. PSA and VSA processes are the separation methods which use difference of amount adsorbed as pressure is changed periodically, but they have the differences in pressurization and regeneration. In this study, the performance of 6-step PSA process was compared with that of 5-step VSA process with respect to purity and recovery. In addition, the effects of each step (pressurization step, adsorption step, and pressure equalization step) on purity and recovery were investigated. As a result, the VSA process using zeolite 10X showed better performance than the zeolite 5A PSA and zeolite 13X VSA process in comparison with purity, recovery and productivity. And it was enough to apply the vacuum pressure of 200 torr for the VSA, which produced over 90% oxygen with 70% recovery.

• Clean Technology
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• v.17 no.4
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• pp.389-394
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• 2011

A compact adsorption-based process for removal of carbon dioxide and nitrogen from natural gas has been discussed. Among the adsorption-based processes, especially, the pressure swing adsorption (PSA) process has been a suitable unit operation for the purification and separation of gas because of low operation energy and cost. A step cycle is made up of pressurization, feed, equalization, blowdown and rinse. In this work, the PSA process is composed of zeolite 13X and carbon molecular sieve (CMS) for removal of carbon dioxide and nitrogen from mixed gas containing $CH_4/CO_2/N_2$ (75:21:4 vol%). A CMS selectively removes carbon dioxide and a zeolite 13X separates nitrogen from methane. CMS is investigated experimentally due to the high throughput of the faster diffusing component ($CO_2$). The gas composition of top, bottom and feed tank was measured with the gas chromatography (GC) using TCD detector, helium as carrier gas and packed column for analysis of methane, carbon dioxide, and nitrogen.

• Journal of the Korea Organic Resources Recycling Association
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• v.22 no.3
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• pp.41-52
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• 2014

In this study, to estimate the biodegradability of sewage discharged intermittently, field scale sampling and analysis was conducted and the results were obtained as follows. According to results of the biodegradability of sewage discharged intermittently, average concentration of TCODcr is 325.5mg/L and ratio of TCOD fraction resulted 100%. Also, average concentration of SCODcr resulted 135.9mg/L and ratio of TCOD fraction resulted 41.8%. Average concentration of Ss showed 74.1mg/L and ratio of TCOD fraction resulted 22.8%. Average concentration of $S_I$ was analyzed to be 61.8mg/L and ratio of TCOD fraction was calculated to 19.0%. Xs which is particulate matter was analyzed to show 27.8mg/L and ratio of TCOD fraction also showed 8.5%. Average concentration of $X_H$ is 103.4mg/L and ratio of TCOD fraction resulted 31.8%. Inert particulate matter showed that average concentration of $X_I$ is 58.5mg/L and ratio of TCOD fraction resulted 18.0%. Accordingly, dissolved biodegradable organic matter showed the ratio of 41.8%, and readily biodegradable matter among this showed 22.8%. Thus intermittent inflow is expected to have less effect with regards equalization by organic loading rate of influent.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.1-6
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• 2014

In this study, we propose optimized RBFNNs based on night vision face recognition simulator with the aid of $(2D)^2$ PCA algorithm. It is difficult to obtain the night image for performing face recognition due to low brightness in case of image acquired through CCD camera at night. For this reason, a night vision camera is used to get images at night. Ada-Boost algorithm is also used for the detection of face images on both face and non-face image area. And the minimization of distortion phenomenon of the images is carried out by using the histogram equalization. These high-dimensional images are reduced to low-dimensional images by using $(2D)^2$ PCA algorithm. Face recognition is performed through polynomial-based RBFNNs classifier, and the essential design parameters of the classifiers are optimized by means of Differential Evolution(DE). The performance evaluation of the optimized RBFNNs based on $(2D)^2$ PCA is carried out with the aid of night vision face recognition system and IC&CI Lab data.