• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.594-600
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• 2017

The new design methodology of prediction model and pattern classification, which is based on the dimension reduction algorithm called principal component analysis, is introduced in this paper. Principal component analysis is one of dimension reduction techniques which are used to reduce the dimension of the input space and extract some good features from the original input variables. The extracted input variables are applied to the prediction model and pattern classifier as the input variables. The introduced prediction model and pattern classifier are based on the very simple regression which is the key point of the paper. The structural simplicity of the prediction model and pattern classifier leads to reducing the over-fitting problem. In order to validate the proposed prediction model and pattern classifier, several machine learning data sets are used.

• Restorative Dentistry and Endodontics
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• v.40 no.2
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• pp.113-122
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• 2015

Objectives: The aim of this paper was evaluating the ratios of electrical impedance measurements reported in previous studies through a correlation analysis in order to explicit it as the contributing factor to the accuracy of electronic apex locator (EAL). Materials and Methods: The literature regarding electrical property measurements of EALs was screened using Medline and Embase. All data acquired were plotted to identify correlations between impedance and log-scaled frequency. The accuracy of the impedance ratio method used to detect the apical constriction (APC) in most EALs was evaluated using linear ramp function fitting. Changes of impedance ratios for various frequencies were evaluated for a variety of file positions. Results: Among the ten papers selected in the search process, the first-order equations between log-scaled frequency and impedance were in the negative direction. When the model for the ratios was assumed to be a linear ramp function, the ratio values decreased if the file went deeper and the average ratio values of the left and right horizontal zones were significantly different in 8 out of 9 studies. The APC was located within the interval of linear relation between the left and right horizontal zones of the linear ramp model. Conclusions: Using the ratio method, the APC was located within a linear interval. Therefore, using the impedance ratio between electrical impedance measurements at different frequencies was a robust method for detection of the APC.

• Nuclear Engineering and Technology
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• v.43 no.6
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• pp.567-572
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• 2011

A sensitivity analysis of the methods used to evaluate the transport properties of a CdZnTe detector was performed using two different radiations (${\alpha}$ particle and gamma-ray) emitted from an $^{241}Am$ source. The mobility-lifetime products of the electron-hole pair in a planar CZT detector ($5{\times}5{\times}2\;mm^3$) were determined by fitting the peak position as a function of biased voltage data to the Hecht equation. To verify the accuracy of these products derived from ${\alpha}$ particles and low-energy gamma-rays, an energy spectrum considering the transport property of the CZT detector was simulated through a combination of the deposited energy and the charge collection efficiency at a specific position. It was found that the shaping time of the amplifier module significantly affects the determination of the (${\mu}{\tau}$) products; the ${\alpha}$ particle method was stabilized with an increase in the shaping time and was less sensitive to this change compared to when the gamma-ray method was used. In the case of the simulated energy spectrum with transport properties evaluated by the ${\alpha}$ particle method, the peak position and tail were slightly different from the measured result, whereas the energy spectrum derived from the low-energy gamma-ray was in good agreement with the experimental results. From these results, it was confirmed that low-energy gamma-rays are more useful when seeking to obtain the transport properties of carriers than ${\alpha}$ particles because the methods that use gamma-rays are less influenced by the surface condition of the CZT detector. Furthermore, the analysis system employed in this study, which was configured by a combination of Monte Carlo simulation and the Hecht model, is expected to be highly applicable to the study of the characteristics of CZT detectors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.243-253
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• 2002

These days, the application range of digital photogrammetry is being extended actively, so the great variety of research is being progressed about improvement of measurement accuracy. This method can acquisite a high analysis accuracy and can acquisite easily image. But, So this method require a much processing time and effort by increasing a data amount, as the automation of processing must be completed for efficiency improvement of processing. In this study, the automation of image processing stage is established for multi-image aquisition and analysis about a radio telescope. Also, the precise measurement and the accuracy on object were intended to be improved. As a result of this study, the accuracy on the object which demands precise measurement was enhanced from multi image analysis, and also the assembly accuracy of the object could be checked by precise measurement and curve fitting.

• Journal of Fashion Business
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• v.9 no.6
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• pp.12-28
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• 2005

The purpose of this study is to help develop high quality brassieres with functionality and comfort, fitting adolescents' physical features during their growth period. This study conducts a comparative analysis of juvenile brassiere and adult brassiere to identify the problems of brassieres in the market. The raw data for this study was processed by SPSS 10.1. The results of this study are summarized as follows: 1. The results of this survey show that the girls' satisfaction of their breasts has correlations between breast protrusion degree and volume. The girls think that if they have protrusive breasts their breast volume is big, and their breast satisfaction level shows high. 2. The results show that the objective of brassiere wearing is to prevent breasts sag and rupture, make good breast shape, balance their entire body shape, and make beautiful outer garment line. Brassiere functions are to prevent jiggle of breasts, make a good body line, and cover the nipples. For the grader school students, they are wearing brassiere to make a good balanced body and as their breasts developed, they are wearing brassiere for beautiful body shape not just to cover up their breasts. 3. In regard to brassiere cup size recognition, as students have higher grade at school, they have better recognition abouxt their cup size. As they are better aware of their cup size, they have better satisfaction with their cup size. Therefore, choosing the right size of brassiere for their bust is very important. 4. Girl students' brassiere preference shows that 317 students (56.9%) prefer white for brassiere colors, following pink and flesh color. Their most preferred brassiere material is cotton (354 people, 63.6%) because cotton is not sensitive even for weak skin. For brassiere style, 273 students (49%) prefer round style, following spots and mold. Their most preferred brassiere style is stake. In addition, brassiere should not press their breasts because their breasts are developing during puberty period.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.133-140
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• 2016

In active sonar field, a target detection and localization based on a distributed sensor network has been much studied for the underwater surveillance of the coast. Zhou et al. proposed a target localization method utilizing the positions of target-detected sensors in distributed sensor network which consists of detection-only sensors. In contrast with a conventional method, Zhou's method dose not require to estimate the propagation model parameters of detection signal. Also it needs the lower computational complexity, and to transmit less data between network nodes. However, it has large target localization error. So it has been modified for reducing localization error by Ryu. Modified Zhou's method has better estimation performance than Zhou's method, but still relatively large estimation error. In this paper, a target localization method based on modified Zhou's method is proposed for reducing the localization error. The proposed method utilizes the geometry of the positions of target-detected sensors and a line that represents the bearing of target, a line can be found by modified Zhou's method. This paper shows that the proposed method has better target position estimation performance than Zhou's and modified Zhou's method by computer simulations.

• Journal of agriculture & life science
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• v.44 no.4
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• pp.1-7
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• 2010

Data was collected to develop equation for predicting stemp taper for Carpinus laxiflora in Jeju Experimental Forests. The Models tested for choosing the best-fit equations were Max & Burkhart's model, Kozak's model, and Lee's model. Performance of the equations in predicting stem diameter at a specific point along a stem was evaluated with fit and validation statistics and distribution of residuals on predicted values. In result, all the three models gave slightly better values of fitting statistics. In plotting residuals against predicted diameter, Max & Burkhart's model showed underestimation in predicting small diameter and Lee's Model did the same in predicting small diameter. Based on the above analysis of the three models in predicting stem taper, Kozak's model was chosen for the best-fit stem taper equations, and its parameters were given for C. laxiflora. Kozak's model was used to develop a stem volume table of outside bark for C. laxiflora.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.179-186
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• 2008

In proportion as the growth of the wireless sensor network applications, we need for more accuracy wireless channel information. In the case of indoor or outdoor wireless sensor networks, multipath propagation causes severe problems in terms of fading. Therefore, a path-loss model for multipath environment is required to optimize communication systems. This paper deals with log-normal path loss modeling of the indoor 2.4 GHz channel. We measured variation of the received signal strength between the sender and receiver of which separation was increased from 1 to 30m. The path-loss exponent and the standard deviation of wireless channel were determined by fitting of the measured data. By using the PRR(Packet Reception Rate) of this model. Wireless sensor channel is defined CR(Connect Region), DR(Disconnected Region). In order to verify the characteristics of wireless channel, we performed simulations and experiments. We demonstrated that connection ranges are 24m in indoor, and 14m in outdoor.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.869-875
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• 2021

The purpose of this study is to derive a formula for calculating the effective energy of an X-ray beam generated by a CT simulator. Under 90, 120, and 140 kVp X-ray beams, the CT number calibration insert part of the AAPM CT performance phantom was scanned 5 times with a CT simulator. The CT numbers of polyethylene, polystyrene, water, nylon, polycarbonate, and acrylic were measured for each CT slice image. The average value of CT number measured under a single tube voltage and the linear attenuation coefficients corresponding to each photon energy calculated from the data of the National Institute of Standards and Technology were linearly fitted. Among the obtained correlation coefficients, the photon energy having the maximum value was determined as the effective energy. In this way, the effective energy of the X-ray beam generated at each tube voltage was determined. By linearly fitting the determined effective energies(y) and tube voltages(x), y=0.33026x+30.80263 as an effective energy calculation formula was induced.

• Genomics & Informatics
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• v.19 no.1
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• pp.11.1-11.8
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• 2021

For the novel coronavirus disease 2019 (COVID-19), predictive modeling, in the literature, uses broadly susceptible exposed infected recoverd (SEIR)/SIR, agent-based, curve-fitting models. Governments and legislative bodies rely on insights from prediction models to suggest new policies and to assess the effectiveness of enforced policies. Therefore, access to accurate outbreak prediction models is essential to obtain insights into the likely spread and consequences of infectious diseases. The objective of this study is to predict the future COVID-19 situation of Korea. Here, we employed 5 models for this analysis; SEIR, local linear regression (LLR), negative binomial (NB) regression, segment Poisson, deep-learning based long short-term memory models (LSTM) and tree based gradient boosting machine (GBM). After prediction, model performance comparison was evelauated using relative mean squared errors (RMSE) for two sets of train (January 20, 2020-December 31, 2020 and January 20, 2020-January 31, 2021) and testing data (January 1, 2021-February 28, 2021 and February 1, 2021-February 28, 2021) . Except for segmented Poisson model, the other models predicted a decline in the daily confirmed cases in the country for the coming future. RMSE values' comparison showed that LLR, GBM, SEIR, NB, and LSTM respectively, performed well in the forecasting of the pandemic situation of the country. A good understanding of the epidemic dynamics would greatly enhance the control and prevention of COVID-19 and other infectious diseases. Therefore, with increasing daily confirmed cases since this year, these results could help in the pandemic response by informing decisions about planning, resource allocation, and decision concerning social distancing policies.