• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.119-128
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• 2014

In this paper, a fast human detection method using adaptive UV-histogram and template matching is proposed. The proposed method improves the detection rate in the scene of complex environment. The method firstly generates U-histogram to extract human candidates and adaptively generates V-histogram for each labled U-histogram, thus it could extract humans correctly, which was impossible in the previous method. The method tries to match the human candidates with the adaptively sized omega shape template to the focal length and distance in order to improve the detection accuracy. It also detects false positives by rematching the template with accumulated foreground images and hence is robust to the occlusion. Experimental results showed that the proposed method has superior performance to the Bae's method in the complex environment with about 15% improvement in precision and 80% in recall and has 20 times faster processing time than Xia's method.

• Journal of Technologic Dentistry
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• v.36 no.1
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• pp.9-15
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• 2014

Purpose: Generally dental technicians clinically decide the sintering temperature of zirconia artificial teeth to match the color of the teeth. However, the sintering temperature influence the microstructure and mechanical strength of ceramic body. In this study, to evaluate the free choice of sintering temperature which leads to color the problems in zirconia false teeth, the variation of microstructure, mechanical strength, and colortone of zirconia ceramics according to the change of sintering temperature was investigated. Methods: Bar type specimens were prepared from commercial zirconia blocks by cutting and polishing into $0.8cm(L){\times}1.0cm(W){\times}4.8cm(H)$. Specimens were fired from 1,400 to $1,700^{\circ}C$ at $50^{\circ}C$ intervals and held for 1hour at highest temperature. Apparent porosity, water absorption, firing shrinkage, bulk density, bend strength, whiteness were tested. Microstructures were observed by SEM. Results: When fired above $1450^{\circ}C$, all specimens showed 0% apparent porosity and water absorption, 20% firing shrinkage, and $6.1g/cm^3$ bulk density regardless of firing temperatures. SEM photomicrographs showed grain growth of zirconia occurred above $1,600^{\circ}C$. Whiteness was also largely changed above this temperature. Maximum bend strength of 1,05MPa was obtained at $1,550^{\circ}C$. Bend strength lowered slightly above this temperature and showed $950{\ss}\acute{A}$ at $1,700^{\circ}C$. Conclusion: In order to fit the colortone of zirconia artificial teeth, arbitrary choice of firing temperature higher than $1,500^{\circ}C$, up to $1,700^{\circ}C$ did not influence the mechanical strength.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.11
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• pp.1044-1050
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• 2013

This paper analyzes what is mitigated as spoofing attack using the U-Blox Receiver and GPS RF signal generator developed at ETRI. Generally the spoofing attack made the target receiver to be wrong navigation solution by providing false measurement of code and carrier. So we analyzed the impact of spoofing attack through the signal strength and navigation solution. In oder to test of effect of anti-spoofing signal, we consider the signal with antiphase code to spoofing signal and generated GPS normal signal and spoofing signal and anti-spoofing signal using GPS RF signal generator. This paper analyzed that the GPS receiver was responded to the spoofing attack according to code phase difference between spoofing and anti-spoofing signal. We confirmed that the spoofing signal was disappeared by anti-spoofing signal if code phase is an exact match.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.15-34
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• 2014

Overall, accuracy as a performance measure does not fully consider modular accuracy: the accuracy of classifying 1 (or true) as 1 is not same as classifying 0 (or false) as 0. A smarter classification algorithm would optimize the classification rules to match the modular accuracies' goals according to the nature of problem. Correspondingly, smarter algorithms must be both more generalized with respect to the nature of problems, and free from decretization, which may cause distortion of the real performance. Hence, in this paper, we propose a novel vertical boosting algorithm that improves modular accuracies. Rather than decretizing items, we use simple classifiers such as a regression model that accepts continuous data types. To improve the generalization, and to select a classification model that is well-suited to the nature of the problem domain, we developed a model selection algorithm with smartness. To show the soundness of the proposed method, we performed an experiment with a real-world application: predicting the intellectual properties of e-transaction technology, which had a 47,000+ record data set.

• Journal of Korean Medical Science
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• v.33 no.53
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• pp.343.1-343.8
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• 2018

Background: Linkage of public healthcare data is useful in stroke research because patients may visit different sectors of the health system before, during, and after stroke. Therefore, we aimed to establish high-quality big data on stroke in Korea by linking acute stroke registry and national health claim databases. Methods: Acute stroke patients (n = 65,311) with claim data suitable for linkage were included in the Clinical Research Center for Stroke (CRCS) registry during 2006-2014. We linked the CRCS registry with national health claim databases in the Health Insurance Review and Assessment Service (HIRA). Linkage was performed using 6 common variables: birth date, gender, provider identification, receiving year and number, and statement serial number in the benefit claim statement. For matched records, linkage accuracy was evaluated using differences between hospital visiting date in the CRCS registry and the commencement date for health insurance care in HIRA. Results: Of 65,311 CRCS cases, 64,634 were matched to HIRA cases (match rate, 99.0%). The proportion of true matches was 94.4% (n = 61,017) in the matched data. Among true matches (mean age 66.4 years; men 58.4%), the median National Institutes of Health Stroke Scale score was 3 (interquartile range 1-7). When comparing baseline characteristics between true matches and false matches, no substantial difference was observed for any variable. Conclusion: We could establish big data on stroke by linking CRCS registry and HIRA records, using claims data without personal identifiers. We plan to conduct national stroke research and improve stroke care using the linked big database.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.31-39
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• 2010

The goal of automatic velocity analysis is to extract accurate velocity from voluminous seismic data with efficiency. In this study, we developed an efficient automatic velocity analysis algorithm by using bootstrapped differential semblance (BDS) and Monte Carlo inversion. To estimate more accurate results from automatic velocity analysis, the algorithm we have developed uses BDS, which provides a higher velocity resolution than conventional semblance, as a coherency estimator. In addition, our proposed automatic velocity analysis module is performed with a conditional initial velocity determination step that leads to enhanced efficiency in running time of the module. A new optional root mean square (RMS) velocity constraint, which prevents picking false peaks, is used. The developed automatic velocity analysis module was tested on a synthetic dataset and a marine field dataset from the East Sea, Korea. The stacked sections made using velocity results from our algorithm showed coherent events and improved the quality of the normal moveout-correction result. Moreover, since our algorithm finds interval velocity ($\nu_{int}$) first with interval velocity constraints and then calculates a RMS velocity function from the interval velocity, we can estimate geologically reasonable interval velocities. Boundaries of interval velocities also match well with reflection events in the common midpoint stacked sections.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.1
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• pp.9-18
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• 2018

Recently, the use of image stitching technology has been increasing as the number of contents based on virtual reality increases. Image Stitching is a method for matching multiple images to produce a high resolution image and a wide field of view image. The image stitching is used in various fields beyond the limitation of images generated from one camera. Image Stitching detects feature points and corresponding points to match multiple images, and calculates the homography among images using the RANSAC algorithm. Generally, corresponding points are needed for calculating conversion relation. However, the corresponding points include various types of noise that can be caused by false assumptions or errors about the conversion relationship. This noise is an obstacle to accurately predict the conversion relation. Therefore, RANSAC algorithm is used to construct an accurate conversion relationship from the outliers that interfere with the prediction of the model parameters because matching methods can usually occur incorrect correspondence points. In this paper, we propose an algorithm that extracts more accurate inliers and computes accurate transformation relations by using correspondence point relation information used in RANSAC algorithm. The correspondence point relation information uses distance ratio between corresponding points used in image matching. This paper aims to reduce the processing time while maintaining the same performance as RANSAC.

• Journal of Preventive Medicine and Public Health
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• v.30 no.4 s.59
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• pp.741-751
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• 1997

Measurement of blood lead (PbB) and blood zinc protoporphyrin (ZPP) are most common biological indices to identify the individual at risk for excess or the health sequences by lead exposure. Because PbB is known most important and reliable index of lead exposure, PbB is often regarded as a gold standard to detect lead exposure. But in Korea PbB is a secondary test item of detailed health check-up with positive finding of screening test in most occasion. Our lead standard requires all lead workers to take annual heath-check twice a year for investigation of their health effect due to lead exposure. Blood ZPP is one of most important index to detect high lead absorption in lead workers as a screening test. Measurement of blood ZPP is known ,well to correlate with PbB in steady state of exposure in most lead workers and is often used as a primary screening test to detect high lead absorption of lead workers with the advantage of simplicity, easiness, portability and low cost. The current cut-off criteria of blood ZPP for further detailed health check-up is $100{\mu}g/d\ell$ which is supposed to match the level of $40{\mu}g/d\ell$ of PbB according to our standard. Authors tried to investigate the validity of current criteria of cut-off level $(100{\mu}g/d\ell)$ of blood ZPP and possible another better cut-off level of it to detect the lead workers whose PbB level over $40{\mu}g/d\ell$. The subjects in our study were 212 male workers in three small scale storage battery industries. Blood ZPP, PbB and hemoglobin (Hb) were selected as the indices of lead exposure. The results were as follows. 1. The mean of blood ZPP, PbB and Hb in lead workers were $79.5{\pm}46.7{\mu}g/d\ell,\;38.7{\pm}15.1{\mu}g/d\ell,\;and\;14.8{\pm}1.2g/d\ell$, respectively. There were significant differences in blood ZPP, PbB and Hb by industry (P<0.01). 2. The percents of lead workers whose blood ZPP were above $100{\mu}g/d\ell$ in the group of work duration below 1, 1-4, 5-9 and above 10 years were 8.6%, 17.2%, 47.6%, and 50.0%, respectively. The percents of lead workers whose PbB were above $40{\mu}g/d\ell$ in those were 31.4%, 40.4%, 71.4%, and 86.4%, respectively. 3. The percents of lead workers whose PbB were below $40{\mu}g/d\ell$, $40-59{\mu}g/d\ell$ and above $60{\mu}g/d\ell$ were 54.7%, 34.9% and 10.4%, respectively. Those of lead workers whose blood ZPP were below $100{\mu}g/d\ell$, $100-149{\mu}g/d\ell$ and above $150{\mu}g/d\ell$ were 79.2%, 13.7% and 7.1%, respectively. 4. Simple linear regression of PbB on blood ZPP was statistically significant (P<0.01) and as PbB was $40{\mu}g/d\ell$, blood ZPP was $82.1{\mu}g/d\ell$. 5. While the highest sensitivity and specificity of blood ZPP test to detect lead workers with PbB eve. $40{\mu}g/d\ell$ were observed in the cut-off level of $50{\mu}g/d\ell$ and $100{\mu}g/d\ell$ of blood ZPP, respectively, the highest validity (sensitivity+specificity) of blood ZPP to detect lead workers with PbB over $40{\mu}g/d\ell$ was observed in the cut-off level of around $70{\mu}g/d\ell$ of blood ZPP. But even with optimal cut-off level of around $70{\mu}g/d\ell$ of blood ZPP, still 25.0% of false negative and 20.7% false positive lead workers were found. As the result of this study, it was suggested that reconsideration of current blood ZPP cut-off of our lead standard from $100{\mu}g/d\ell$ to somewhat lower level such as around $70{\mu}g/d\ell$ and the inclusion of PbB measurement as a primary screening test for lead workers was highly recommended for the effective prevention of lead workers.