• Journal of Radiation Protection and Research
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• v.47 no.3
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• pp.158-166
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• 2022

Background: The effects of radiation on the health of radiation workers who are constantly susceptible to occupational exposure must be assessed based on an accurate and reliable reconstruction of organ-absorbed doses that can be calculated using personal dosimeter readings measured as H_p(10) and dose conversion coefficients. However, the data used in the dose reconstruction contain significant biases arising from the lack of reality and could result in an inaccurate measure of organ-absorbed doses. Therefore, this study quantified the biases involved in organ dose reconstruction and calculated the bias-corrected H_p(10)-to-organ-absorbed dose coefficients for the use in epidemiological studies of Korean radiation workers. Materials and Methods: Two major biases were considered: (a) the bias in H_p(10) arising from the difference between the dosimeter calibration geometry and the actual exposure geometry, and (b) the bias in air kerma-to-H_p(10) conversion coefficients resulting from geometric differences between the human body and slab phantom. The biases were quantified by implementing personal dosimeters on the slab and human phantoms coupled with a Monte Carlo method and considered to calculate the bias-corrected H_p(10)-to-organ-absorbed dose conversion coefficients. Results and Discussion: The bias in H_p(10) was significant for large incident angles and low energies (e.g., 0.32 for right lateral at 218 keV), whereas the bias in dose coefficients was significant for the posteroanterior (PA) geometry only (e.g., 0.79 at 218 keV). The bias-corrected H_p(10)-to-organ-absorbed dose conversion coefficients derived in this study were up to 3.09- fold greater than those from the International Commission on Radiological Protection publications without considering the biases. Conclusion: The obtained results will aid future studies in assessing the health effects of occupational exposure of Korean radiation workers. The bias-corrected dose coefficients of this study can be used to calculate organ doses for Korean radiation workers based on personal dose records.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3243-3257
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• 2021

Deep neural networks provide excellent performance in pattern recognition, audio classification, and image recognition. It is important that they accurately recognize input data, particularly when they are used in autonomous vehicles or for medical services. In this study, we propose a data correction method for increasing the accuracy of an unknown classifier by modifying the input data without changing the classifier. This method modifies the input data slightly so that the unknown classifier will correctly recognize the input data. It is an ensemble method that has the characteristic of transferability to an unknown classifier by generating corrected data that are correctly recognized by several classifiers that are known in advance. We tested our method using MNIST and CIFAR-10 as experimental data. The experimental results exhibit that the accuracy of the unknown classifier is a 100% correct recognition rate owing to the data correction generated by the proposed method, which minimizes data distortion to maintain the data's recognizability by humans.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.221-224
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• 2005

Hyperspectral image data have great potential to depict more detailed information on biophysical characteristics of surface materials, which are not usually available with multispectral data. This study aims to test the potential of hyperspectral data for classifying five soil classes defined by the vector product interim terrain data (VITD). In this study, we try to classify surface materials of bare soil over the study area in Korea using both hyperspectral and multispectral image data. Training and test samples for classification are selected with using VITD vector map. The spectral angle mapper (SAM) method is applied to the EO-I Hyperion data and Landsat ETM+ data, that has been radiometrically corrected and geo-rectified. Higher classification accuracy is obtained with the hyperspectral data for classifying five soil classes of gravel, evaporites, inorganic silt and sand.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.21-26
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• 2016

Purpose Because of many advantages, PET-CT Scanners generally use CT Data for attenuation correction. By using CT based attenuation correction, we can get anatomical information, reduce scan time and make more accurate correction of attenuation. However in case metal artifact occurred during CT scan, CT-based attenuation correction can induce artifacts and quantitative errors that can affect the PET images. Therefore this study infers true SUV of metal artifact region from attenuation corrected image count -to- non attenuation corrected image count ratio. Materials and Methods Micro phantom inserted $^{18}F-FDG$ 4mCi was used for phantom test and Biograph mCT S(40) is used for medical test equipment. We generated metal artifact in micro phantom by using metal. Then we acquired both metal artifact region of correction factor and non metal artifact region of correction factor by using attenuation correction image count -to- non attenuation correction image count ratio. In case of clinical image, we reconstructed both attenuation corrected images and non attenuation corrected images of 10 normal patient($66{\pm}15age$) who examined PET-CT scan in SNUH. After that, we standardize several organs of correction factor by using attenuation corrected image count -to- non attenuation corrected count ratio. Then we figured out metal artifact region of correction factor by using metal artifact region of attenuation corrected image count -to- non attenuation corrected count ratio And we compared standard organs correction factor with metal artifact region correction factor. Results according to phantom test results, metal artifact induce overestimation of correction factor so metal artifact region of correction factors are 12% bigger than the non metal artifact region of correction factors. in case of clinical test, correction factor of organs with high CT number(>1000) is $8{\pm}0.5%$, correction factor of organs with CT number similar to soft tissue is $6{\pm}2%$ and correction factor of organs with low CT number(-100>) is $3{\pm}1%$. Also metal artifact correction factors are 20% bigger than soft tissue correction factors which didn't happened metal artifact. Conclusion metal artifact lead to overestimation of attenuation coefficient. because of that, SUV of metal artifact region is overestimated. Thus for more accurate quantitative evaluation, using attenuation correction image count -to-non attenuation correction image count ratio is one of the methods to reduce metal artifact affect.

• Journal of Digital Convergence
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• v.16 no.5
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• pp.399-406
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• 2018

Much research has been done using the KDDCup99 data set to study intrusion detection using artificial intelligence. Previous studies have shown that the performance of the SMO (SVM) algorithm is superior. However, intrusion detection studies of new intrusion types not used in training are insufficient. In this paper, a model was created using the instances of weka's SMO and KDDCup99 training data set, kddcup.data.gz. We tested existing instances(292,300) of the corrected.gz file and new intrusions(18,729). In general, intrusion labels not used in training are not tested, so new intrusion labels were changed to normal. Of the 18,729 new intrusions, 1,827 were classified as intrusions. 1,827 instances classified as new intrusions are buffer_overflow. Three, neptune. 392, portsweep. 164, ipsweep. 9, back. 511, imap. 1, satan. Dogs, 645, nmap. 102.

• Wind and Structures
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• v.26 no.3
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• pp.129-146
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• 2018

Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of daily maximum wind speed and annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modeling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.

• Journal of Korean society of Dental Hygiene
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• v.19 no.5
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• pp.731-742
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• 2019

Objectives: To analyze the association between sleep duration and the number of remaining teeth in people aged 65 years or older in order to provide basic data for improving sleep quality and developing oral health programs for teeth maintenance. Methods: The raw data for the analysis were obtained from the sixth Korean National Health and Nutrition Examination Survey (KNHANES) dataset, conducted between 2013 and 2015. The 4,340 subjects included in the study underwent oral examinations and then proceeded to answer related questions. The collected data were analyzed using SPSS (ver 23.0) program via composite samples, with the calculations for mean, standard deviation, chi-square test, and logistic return analysis being performed. Results: An analysis of the effect of sleep duration on the number of remaining teeth among people aged >65 years old showed that if the confounding variables were not corrected for, the risk of having less than 9 hours of sleep was 1.40 times higher (95% CI: 1.06-1.86). However, this was not statistically significant in models that corrected for gender, age, and other confounding variables (p>0.05). Conclusions: The association between sleep duration among the elderly with their number of remaining teeth was confirmed. Therefore, measures to improve sleep quality and oral care practices to maintain the remaining teeth in people over 65 years old should be developed.

• Journal of Power System Engineering
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• v.13 no.2
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• pp.63-70
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• 2009

This paper discusses the influence on long-tenn predictions of the ship response in ocean by using the Global Wave Statistics data, GWS, and wave information from the remote sensing satellites. GWS's standard scatter diagrams of significant wave height and zero-crossing wave period are suggested to be corrected to a round number of 0.01/1000 fitted with a statistical analytic model of the conditional lognormal distribution for zero-crossing wave period. The GEOSAT satellite data are utilized which presented by I. R. Young and G. J. Holland (1996, named as GEOSAT data). At first, qualities of this data are investigated, and statistical characteristic trends are studied by means of applying known probability distribution functions. The wave height data of GEOSAT are compared to the data observed onboard merchant ships, the data observed by measure instrument installed on the ocean-going container ship and so on. To execute a long-tenn prediction of ship response, joint probability functions between wave height and wave period are introduced, therefore long-term statistical predictions are executed by using the functions.

• Journal of Veterinary Clinics
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• v.10 no.1
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• pp.65-94
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• 1993

This study examined metabolic profiles of 1349 Holstein cows from 91 commercial herds. Thirteen parameters which are consisted of twelve blood components and body condition score were examined and their mean values. standard deviations and standard limits, which are 80% confidential limits, in each lactational stage were reported. The variations of each parameter affected by season, individual milk yield, adjusted corrected milk yield of herd. and lactation number were also reported. A model of metabolic profile test applicable to this country where the average number of cows in a herd is small as to be fifteen is designed. Metabolic profiles as reflected in each parameter were discussed in relation to adequacy of dietary intake for production, milk production, reproductive performance, and diseases, and the possible measure to improve productivity of dairy cows were proposed. Much of the variation in parameters was due to differences between herds, and less to differences between seasons, differences between individual milk yield, and differences between lactational stages. As the average herd size in this country is small, it is believed that all the cows in a herd must be sampled, and the individual result of each parameter was compared with the standard limit for each lactational stage, and the percentage of cows which are outside the standard limits in a herd was calculated to use as a criteria for evaluation of the herd. Data outside the 99% confidential limits were to be deleted at first, but when the trends of the data outside the 99% confidential limits are same as the trends of the data within 99% confidential limits, the deleted data must be reviewed again, otherwise some important informations would be missed. The mean concentration of blood urea nitrogen in this study was much higher than that was reported in England, U.S.A. and Japan, and it was similar to the upper limits reported in England, U.S.A. and Japan. So it was thought that the concentration of blood urea nitrogen is improper as a criteria for protein intake. The increase of serum total protein cocentration beyond standard limits was due to increase of serum globulin concentration in most of the cows. The correlation coefficient between serum and protein and serum globulin concentration was 0.83. Serum globulin concentration was negatively related to adjusted corrected milk of herd. Serum albumin, calcium and magnessium concentrations were negatively related to adjusted corrected milk of herd, which indicate that high-producing individual or high-producing herd have not taken sufficient protein/amino acids, calcium and magnessium. Packed cell volume was negatively related to adjusted corrected milk of the herd, and the trend was same In each lactational stage. The correlation coefficient between serum and packed cell volume was 0.16 and the correlation was very weak. Blood glucose concentration was lowest in early lactational stage, which indicates negative energy balance in early lactational stage. Blood glucose concentration was negatively related to adjusted corrected milk of herd from peak to late lactational stage, which indicates negative energy balance during the period in high-producing individuals or high-producing herds. Correlation coefficient between serum aspartate aminotransferase activity and serum ${\gamma}$-glutamyltransferase activity was 0.41, and this indicates that serum ${\gamma}$-glutamyltransferase should be included as a parameter of metabolic profile test to evaluate liver function. Body condition score of dairy cows in this country was lower than that of Japan in every lactational stages, and the magnitude of increase in body condition score during middle and late lactational stages was small. Metabolic profile can not be evaluated with solely nutritional intake. When an individual or large percentage of cows in a herd have adnormal values In parameters of metabolic profile test, veterinary clinician and nutritionist should cooperate so as to diagnose diseases and to calculate the e of no운ents simultaneously.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.61-71
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• 2015

Quantitative variability of AMSR2 (Advanced Microwave Scanning Radiometer 2) soil moisture data shows that the remotely sensed soil moisture is underestimated during Spring and Winter seasons and is overestimated during Summer and Fall seasons. Therefore the bias correction of the remotely sensed data is essential for the purpose of water resource management. To enhance their applicability, the bias of AMSR2 soil moisture data was corrected using ground observation data at Cheorwon Chuncheon, Suwon, Cheongju, Jeonju, and Jinju sites. Test statistics demonstrated that the correlation coefficient R is improved from 0.107~0.328 to 0.286~0.559 and RMSE is improved from 9.46~14.36 % to 5.38~9.62 %. Bias correction using ground network data improved the applicability of remotely sensed soil moisture data.