• Asian Pacific Journal of Cancer Prevention
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• v.15 no.17
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• pp.7371-7375
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• 2014

Background: Concurrent chemo-radiotherapy is the recommended standard treatment modality for patients with locally advanced lung cancer. The purpose of three-dimensional conformal radiotherapy (3DCRT) is to minimize normal tissue damage while a high dose can be delivered to the tumor. The most common dose limiting side effect of thoracic RT is radiation pneumonia (RP). In this study we evaluated the relationship between dose-volume histogram parameters and radiation pneumonitis. This study targeted prediction of the possible development of RP and evaluation of the relationship between dose-volume histogram (DVH) parameters and RP in patients undergoing 3DCRT. Materials and Methods: DVHs of 41 lung cancer patients treated with 3DCRT were evaluated with respect to the development of grade ${\geq}2$ RP by excluding gross tumor volume (GTV) and planned target volume (PTV) from total (TL) and ipsilateral (IPSI) lung volume. Results: Were admitted statistically significant for p<0.05. Conclusions: The cut-off values for V5, V13, V20, V30, V45 and the mean dose of TL-GTV; and V13, V20,V30 and the mean dose of TL-PTV were statistically significant for the development of Grade ${\geq}2$ RP. No statistically significant results related to the development of Grade ${\geq}2$ RP were observed for the ipsilateral lung and the evaluation of PTV volume. A controlled and careful evaluation of the dose-volume histograms is important to assess Grade ${\geq}2$ RP development of the lung cancer patients treated with concurrent chemo-radiotherapy. In the light of the obtained data it can be said that RP development may be avoided by the proper analysis of the dose volume histograms and the application of optimal treatment plans.

• Food Science and Biotechnology
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• v.18 no.1
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• pp.162-166
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• 2009

This study evaluated glucose effect on Listeria monocytogenes survival under gamma irradiation and NaCl stress. L. monocytogenes in phosphate buffered saline (PBS) plus glucose (0-4%) was treated with gamma irradiation (0-0.5 kGy), and the samples were then exposed to NaCl (0-9%) in tryptic soy agar plus 0.6% yeast extract. $D_{10}$ and $t_{3D}$ values were determined, and a model for prediction of $D_{10}$ values was developed. Cell counts of L. monocytogenes reduced as irradiation dose increased, and L. monocytogenes in PBS (no glucose) was more sensitive to irradiation and NaCl compared to those in PBS (2 or 4% glucose). $D_{10}$ values were 0.07-0.1, 0.12-0.16, and 0.13-0.15 kGy for 0, 2, and 4% glucose, respectively. The $t_{3D}$ values were 0.22-0.3 (0% glucose), 0.35-0.48 (2% glucose), and 0.40-0.44 (4% glucose). A model performance was acceptable. These results indicate that glucose in foods would increase the resistance of L. monocytogenes to gamma irradiation and NaCl stress.

• Atmosphere
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• v.32 no.4
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• pp.277-295
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• 2022

The global weather prediction model, Korean Integrated Model (KIM), has been in operation since April 2020 by the Korea Meteorological Administration. This study assessed the performance of heat waves (HWs) in Korea in 2020. Case experiments during 2018-2020 were conducted to support the reliability of assessment, and the factors which affect predictability of the HWs were analyzed. Simulated expansion and retreat of the Tibetan High and North Pacific High during the 2020 HW had a good agreement with the analysis. However, the model showed significant cold biases in the maximum surface temperature. It was found that the temperature bias was highly related to underestimation of downward shortwave radiation at surface, which was linked to cloudiness. KIM tended to overestimate nighttime clouds that delayed the dissipation of cloud in the morning, which affected the shortage of downward solar radiation. The vertical profiles of temperature and moisture showed that cold bias and trapped moisture in the lower atmosphere produce favorable conditions for cloud formation over the Yellow Sea, which affected overestimation of cloud in downwind land. Sensitivity test was performed to reduce model bias, which was done by modulating moisture mixing parameter in the boundary layer scheme. Results indicated that the daytime temperature errors were reduced by increase in surface solar irradiance with enhanced cloud dissipation. This study suggested that not only the synoptic features but also the accuracy of low-level temperature and moisture condition played an important role in predicting the maximum temperature during the HWs in medium-range forecasts.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.503-509
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• 2020

This study aims to develop a patient-specific radiation exposure dose prediction model based on anthropometric data that can be easily measurable during CT examination, and to be used as basic data for DRL setting and radiation dose management system in the future. In addition, among the machine learning algorithms, the most suitable model for predicting exposure doses is presented. The data used in this study were chest CT scan data, and a data set was constructed based on the data including the patient's anthropometric data. In the pre-processing and sample selection of the data, out of the total number of samples of 250 samples, only chest CT scans were performed without using a contrast agent, and 110 samples including height and weight variables were extracted. Of the 110 samples extracted, 66% was used as a training set, and the remaining 44% were used as a test set for verification. The exposure dose was predicted through random forest, linear regression analysis, and SVM algorithm using Orange version 3.26.0, an open software as a machine learning algorithm. Results Algorithm model prediction accuracy was R^2 0.840 for random forest, R^2 0.969 for linear regression analysis, and R^2 0.189 for SVM. As a result of verifying the prediction rate of the algorithm model, the random forest is the highest with R^2 0.986 of the random forest, R^2 0.973 of the linear regression analysis, and R^2 of 0.204 of the SVM, indicating that the model has the best predictive power.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.3
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• pp.175-184
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• 2004

Ground-borne noise and vibration generated by underground transit system has been recognized as an important environmental problem. This study reviews several of the procedures that have been used to predict ground-borne vibration. The vibration responses are measured at three sites that have different soil qualities. The measured vibration levels are compared with the predicted results by previously used vibration level prediction models. There are some drawbacks to apply these prediction models to selected sites because most of the existing prediction models are primarily based on empirical data and all of them lack of analytical models for the mechanism of ground-borne vibration generation. radiation, and propagation. In this study a numerical method, which is based on explicit differential method, is used to compensate for the shortcomings of existing prediction models. Although numerically computed results are not quantitatively in good agreement with the measured results, the trends are comparable in the sense that vibration level does not decrease monotonically with distance. Also, the site with the deepest tunnel gives the highest vibration level.

• Proceedings of the KSRS Conference
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• v.1
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• pp.301-304
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• 2006

For the purpose of investigating the contributions of various gases to climate change, the thermal radiation associated with greenhouse gases are extracted from AIRS (Atmospheric Infrared Sounder) infrared radiances over the tropical pacific region. AIRS instrument which was launched on the EOS-Aqua satellite in May 2002 covers the spectral range from 650 cm-1 to 2700 cm-1 with a spectral resolution of between 0.4 cm-1 and 1 cm-1. In order to extract the thermal radiation absorbed by individual gases, the interfering background radiances at the top of the atmosphere are simulated using the radiative transfer code MODTRAN (MODerate spectral resolution atmospheric TRANsmittance). The simulations incorporated the temperature and water vapor profiles taken from NCEP (National Centers for Environmental Prediction) reanalyses. The differences between the simulated background radiance and AIRS-measured radiance result in the absorption of upward longwave radiation by atmospheric gases (i.e. greenhouse effect). The extracted absorption bands of individual gases will allow us to quantify the radiative forcing of individual greenhouse gases and thus those data will be useful for climate change studies and for the validation of radiative transfer codes used in general circulation models.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.4
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• pp.533-542
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• 2000

Analytical experiments to determine the line-of-sight temperature distribution is conducted by using spectral radiation intensities. For this study, fourteen narrow bands of $25cm^{-1}$ interval in $CO_2\;4.3{\mu}m$ band ($2,050cm^{-1}$ to $2375cm^{-1}$) are selected. The applied system is a one-dimensional gas slab filled with 100% $CO_2$ gas at 1 atm. Two types of temperature profile are tested; parabolic and boundary layer types. Three kinds of radiation calculation are used in the iteration procedure for the temperature inversion; LBL(Line by Line), SNB(Statistical Narrow Band) and WNB(WSGGM. based Narrow Band) models. The LBL solution shows perfect agreement while some error of temperature prediction is caused by radiation modeling error when using SNB and WNB models. The inversion result shows that the WNB model may be used more accurately in spectral remote sensing techniques than the traditional SNB model.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.3
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• pp.584-590
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• 1994

A theoretical model has been developed to analyze the jet-edge interaction and the sound radiation. The edge responding to the sinuous impinging jet is regarded as an array of dipoles and their strength is determined by the boundary condition on the edge surface. The surface pressure distribution and the edgeforce are estimated using these dipoles. Then the pressure amplitude and directivity of the sound field is obtained by summing the radiating sounds from the dipole sources. It is found that the effective source is located a little distance downstream from the edge tip. And the directivity of the sound radiation is cardioid pattern near the edge but dipole pattern far from the edge. The theoretical model is confirmed by comparing the theoretical prediction of the edgeforce and sound pressure level with available experimental data.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.354-356
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• 2011

Renewable energy resources such as wind, wave, solar, micro hydro, tidal and biomass etc. are becoming importance stage by stage because of considering effect of the environment. Solar energy is one of the most successful sources of renewable energy for the production of electrical energy following solar energy. And, the solar/photovoltaic cell generators depend on the solar radiation, which is a random variable so this poses difficulty in the system scheduling and energy dispatching, as the schedule of the photovoltaic cell generators availability is not known in advance. This paper proposes to use the two-layered artificial neural networks for predicting the actual solar radiation from the previous values of the same variable.

• Journal of Ocean Engineering and Technology
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• v.15 no.4
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• pp.53-59
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• 2001

The Primary Production of phytoplanktons produces organic matter in high concentration in eutrophicated Hakata Bay, Japan, even during the winter season in spite of low water temperature. Phytoplanktons are considered to have any biological capabilities to keep activities of photosynthesis under the unfavorable conditions, and this affects water quality of the bay. In this study, seasonal variations in primary production efficiency were predicted by using a simple box-type ecosystem model, which introduced the concept of efficiency for absorption of solar radiation energy in relation to growth of phytoplanktons under the low solar radiation intensity. According to the simulation result of primary production, it was organic pollution comes from dissolved organic carbon (DOC) throughout the year, DOC of which is originated from the primary production of phytoplanktons on biological response of the seasonal variation of ambient conditions.