• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.459-466
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• 2018

Risk of radiation worker and radiation workplace are being mainly assessed by exposure dose. But, the radiation used in radiation workplace and the work environment are different. Because the nondestructive work environment varies depending on the work subject, the existence and nonexistence of shielding board, and so on. So, we need to consider the various factors in effective radiation protection aspect. We conducted a survey of radiation workers with over two years' experience in NDT workplace and heared the thoughts of experts. As a result, radiation source, exposure dose, current status of workplace management, workers with personel dosimetry problem and status of periodic regulatory inspection were chosen as main factors of radiation risk index model. Also, we primarily set weighting factors in order of importance based on questionnaires. Finally, we determined weighting factor for details of main factors through the professional advice. Therefore, we will be able to develop the radiation risk index model for assessing the risk of nondestructive test workplace based on main factors that are selected through this study.

• Journal of the Korean Society of Radiology
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• v.11 no.7
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• pp.555-564
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• 2017

The current radiation risk assessment for occupational exposure is based on the measured exposure dose and health checkups of workers. This people-centered risk assessment may occur errors because absence of using personal dosimeter or unrelated health symptoms of individuals lead to difficulties in obtaining accurate data from workers. In addition, although the established legal upper dose limit was used as a reference for the assessment, it does not imply that this limit is the optimal dose of radiation workers should get; ALARA principle should always be appreciated. Therefore, a new risk assessment model that can take account of all the important factors and implement optimization of radiation protection is required at the national level. In this paper, based on the KOSHA Risk Assessment, we studied on the workplace-centered risk assessment model for radiation field rather than the people-centered. The result of the study derived a right model for radiation field through the analysis of the risk assessment methods in various fields and also found data acquisition methods and procedures for applying to the model. Multidimensional model centering on the workplace will enables more accurate radiation risk assessment by using a risk index and radar plot, and consequently contribute to the efficient worker management, preemptive worker protection and implementation of optimization of radiation protection.

• Earthquakes and Structures
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• v.18 no.1
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• pp.73-82
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• 2020

With the coal mining depth increasing, both stress and gas pressure rapidly enhance, causing coal and gas outburst risk to become more complex and severe. The conventional method for prediction of coal and gas outburst adopts one prediction index and corresponding critical value to forecast and cannot reflect all the factors impacting coal and gas outburst, thus it is characteristic of false and missing forecasts and poor accuracy. For the reason, based on analyses of both the prediction indicators and the factors impacting coal and gas outburst at the test site, this work carefully selected 6 prediction indicators such as the index of gas desorption from drill cuttings Δh₂, the amount of drill cuttings S, gas content W, the gas initial diffusion velocity index ΔP, the intensity of electromagnetic radiation E and its number of pulse N, constructed the Bayes discriminant analysis (BDA) index system, studied the BDA-based multi-index comprehensive model for forecast of coal and gas outburst risk, and used the established discriminant model to conduct coal and gas outburst prediction. Results showed that the BDA - based multi-index comprehensive model for prediction of coal and gas outburst has an 100% of prediction accuracy, without wrong and omitted predictions, can also accurately forecast the outburst risk even for the low indicators outburst. The prediction method set up by this study has a broad application prospect in the prediction of coal and gas outburst risk.

• Journal of Preventive Medicine and Public Health
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• v.45 no.1
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• pp.14-20
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• 2012

Objectives: The aim of this study was to evaluate and quantify the risk of both individual and combined health behaviors on premature mortality in middle aged men in Korea. Methods: In total, 14 533 male subjects 40 to 59 years of age were recruited. At enrollment, subjects completed a baseline questionnaire, which included information about socio-demographic factors, past medical history, and life style. During the follow-up period from 1993 to 2008, we identified 990 all-cause premature deaths using national death certificates. A Cox proportional hazard regression model was used to estimate the hazard ratio (HR) of each health risk behavior, which included smoking, drinking, physical inactivity, and lack of sleep hours. Using the Cox model, each health behavior was assigned a risk score proportional to its regression coefficient value. Health risk scores were calculated for each patient and the HR of all-cause premature mortality was calculated according to risk score. Results: Current smoking and drinking, high body mass index, less sleep hours, and less education were significantly associated with all-cause premature mortality, while regular exercise was associated with a reduced risk. When combined by health risk score, there was a strong trend for increased mortality risk with increased score (p-trend < 0.01). When compared with the 1-9 score group, HRs of the 10-19 and 20-28 score groups were 2.58 (95% confidence intervals [CIs], 2.19 to 3.03) and 7.09 (95% CIs, 5.21 to 9.66), respectively. Conclusions: Modifiable risk factors, such as smoking, drinking, and regular exercise, have considerable impact on premature mortality and should be assessed in combination.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.21-29
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• 2024

Reducing the radiation dose during CT scanning can lower the risk of radiation exposure, but not only does the image resolution significantly deteriorate, but the effectiveness of diagnosis is reduced due to the generation of noise. Therefore, noise removal from CT images is a very important and essential processing process in the image restoration. Until now, there are limitations in removing only the noise by separating the noise and the original signal in the image area. In this paper, we aim to effectively remove noise from CT images using the wavelet transform-based GAN model, that is, the WT-GAN model in the frequency domain. The GAN model used here generates images with noise removed through a U-Net structured generator and a PatchGAN structured discriminator. To evaluate the performance of the WT-GAN model proposed in this paper, experiments were conducted on CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. As a result of the performance experiment, the WT-GAN model is better than the traditional filter, that is, the BM3D filter, as well as the existing deep learning models, such as DnCNN, CDAE model, and U-Net GAN model, in qualitative and quantitative measures, that is, PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) showed excellent results.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.1
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• pp.49-60
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• 2004

Northern Gyeonggi Province(NGP), consisting of 3 counties, is the northernmost region in South Korea adjacent to the de-militarized zone with North Korea. To supplement insufficient spatial coverage of official climate data and climate atlases based on those data, high-resolution digital climate models(DCM) were prepared to support weather- related activities of residents in NGP Monthly climate data from 51 synoptic stations across both North and South Korea were collected for 1981-2000. A digital elevation model(DEM) for this region with 30m cell spacing was used with the climate data for spatially interpolating daily maximum and minimum temperatures, solar irradiance, and precipitation based on relevant topoclimatological models. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Daily solar irradiances over sloping surfaces were estimated from nearby synoptic station data weighted by potential relative radiation, which is the hourly sum of relative solar intensity. Precipitation was assumed to increase with the difference between virtual terrain elevation and the DEM multiplied by an observed rate. Validations were carried out by installing an observation network specifically for making comparisons with the spatially estimated temperature pattern. Freezing risk in January was estimated for major fruit tree species based on the DCMs under the recurrence intervals of 10, 30, and 100 years, respectively. Frost risks at bud-burst and blossom of tree flowers were also estimated for the same resolution as the DCMs.

• Atmosphere
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• v.28 no.4
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• pp.457-467
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• 2018

This study investigated the variability of spring (March-May) forest fire risk in Korea for the period 1991~2017 and analyzed its relationship with large-scale climate factors. The Forest Weather Index (FWI) representing the meteorological risk for forest fire occurrences calculated based on observational data and its relationship with large-scale climate factors were analyzed. We performed the empirical orthogonal function (EOF) analysis on the spring FWI. The leading EOF mode of FWI accounting for about 70% of total variability was found to be highly correlated with total number of forest fire occurrences in Korea. The high FWI, forest fire occurrence risk, in Korea, is associated with warmer atmosphere temperature in midwest Eurasia-China-Korea peninsula, cyclonic circulation anomaly in northeastern China-Korea peninsula-northwest pacific, westerly wind anomaly in central China-Korea peninsula, and low humidity in Korea. These are further related with warmer sea surface temperature and enhanced outgoing longwave radiation over Western Pacific, which represents a typical condition for a La $Ni\tilde{n}a$ episode. This suggests that large-scale climate factors over East Asia and ENSO could have a significant influence on the occurrence of spring forest fires in Korea.

• Clinical Endoscopy
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• v.57 no.1
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• pp.112-121
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• 2024

Background/Aims: Since the usefulness of neoadjuvant chemo(radiation) therapy (NAT) for pancreatic cancer has been demonstrated, recurrent biliary obstruction (RBO) in patients with pancreatic cancer with a fully covered self-expandable metal stent (FCSEMS) during NAT is expected to increase. This study investigated the impact of sarcopenia on RBO in this setting. Methods: Patients were divided into normal and low skeletal muscle index (SMI) groups and retrospectively analyzed. Patient characteristics, overall survival, time to RBO (TRBO), stent-related adverse events, and postoperative complications were compared between the two groups. A Cox proportional hazard model was used to identify the risk factors for short TRBO. Results: A few significant differences were observed in patient characteristics, overall survival, stent-related adverse events, and postoperative complications between 38 patients in the normal SMI group and 17 in the low SMI group. The median TRBO was not reached in the normal SMI group and was 112 days in the low SMI group (p=0.004). In multivariate analysis, low SMI was the only risk factor for short TRBO, with a hazard ratio of 5.707 (95% confidence interval, 1.148-28.381; p=0.033). Conclusions: Sarcopenia was identified as an independent risk factor for RBO in patients with pancreatic cancer with FCSEMS during NAT.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6523-6528
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• 2013

Background: Cigarette smoking is the largest single recognized cause of human cancers. In Western countries, many epidemiologists have reported risk factors for kidney cancer including smoking. However, little is known about the Japanese population. Materials and Methods: We evaluated the association of smoking with the risk of kidney cancer death in the Japan Collaborative Cohort (JACC) Study. Participants included 46,395 males and 64,190 females. The Cox proportional hazards model was used to determine age-and-sex adjusted relative risks. Results: A total of 62 males and 26 females died from kidney cancer during the follow-up of 707,136 and 1,025,703 person-years, respectively. Heavy smokers (Brinkman index >1200), fondness of fatty foods, hypertension, diabetes mellitus (DM), and obesity were suggested to increase the risk of renal cell carcinoma while walking was suggested to decrease the risk. Even after controlling for age, sex, alcohol drinking and DM, heavy smoking significantly increased the risk. Conclusions: The present study suggests that six factors including smoking may increase and/or reduce the risk of kidney cancer in the Japanese population. Because of the small number of outcomes, however, we did not evaluate these factors after adjusting for all possible confounding factors. Further studies may be needed to confirm the findings in this study.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.10-18
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• 2017

Korean Red Pine (Pinus densiflora) has been protected and used as the most ecologically and socio-culturally important tree species in Korea. However, as dieback of Korean red pines has occurred in the protected area of the forest genetic resources. The aims of this study is to identify causes for dieback of pine tree by investigating topographical characteristics of pine tree dieback and its correlation to meteorological factors. We extracted the dead trees from the time series aerial images and analyzed geomorphological characteristics of dead tree concentration area. As a result, 1,956 dead pine trees were extracted in the study region of 2,600 ha. Dieback of pine trees was found mostly in the areas with high altitude, high solar radiation, low topographic wetness index, south and south-west slopes, ridgelines, and high wind exposure compared to other living pine forest area. These areas are classified as high temperature and high drought stress regions due to micro-climatic characteristics affected by topographic factors. As high temperature and drought stress are generally increasing with climate change, we can evaluated that a risk of pine tree dieback is also increasing. Based on these geomorphological characteristics, we developed a pine tree dieback risk map using Maximum Entropy Model (MaxEnt), and it can be useful for establishing Korean red pine protection and management strategies.