• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.20
• /
• pp.8607-8612
• /
• 2014

Background: Breast cancer patients experience a variety of altered appearance - such as loss or disfigurement of breasts, discolored skin, and hair loss - which result in psychological distress that affect their quality of life. This study aims to evaluate the impact of socioeconomic status on the altered appearance distress, body image, and quality of life among Korean breast cancer patients. Materials and Methods: A cross-sectional survey was conducted at advocacy events held at 16 different hospitals in Korea. Subjects were eligible to participate if they were 18 years of age or older, had a histologically confirmed diagnosis of breast cancer, had no evidence of recurrence or metastasis, and had no psychological problems at the time of the survey. Employment status, marital status, education, and income were assessed for patient socioeconomic status. Altered appearance distress was measured using the NCI's cancer treatment side effects scale; body image and quality of life were measured by the EORTC QLC-C30 and BR23. Means and standard deviations of each outcome were compared by socioeconomic status and multivariate linear regression models for evaluating the association between socioeconomic status and altered appearance distress, body image, and quality of life. Results: A total of 126 breast cancer patients participated in the study; the mean age of participants was 47.7 (SD=8.4). Of the total, 83.2% were married, 85.6% received more than high school education, 35.2% were employed, and 41% had more than $3000 in monthly household income. About 46% had mastectomy, and over 30% were receiving either chemotherapy or radiation therapy at the time of the survey. With fully adjusted models, the employed patients had significantly higher altered appearance distress (1.80 vs 1.48; p<0.05) and poorer body image (36.63 vs 51.69; p<0.05) compared to the patients who were unemployed. Higher education (10.58, standard error (SE)=7.63) and family income (12.88, SE=5.08) was positively associated with better body image after adjusting for age, disease stage at diagnosis, current treatment status, and breast surgery type. Similarly, patients who were married and who had higher education had better quality of life were statistically significant in the multivariate models. Conclusions: Socioeconomic status is significantly associated with altered appearance distress, body image, and quality of life in Korean women with breast cancer. Patients who suffer from altered appearance distress or lower body image are much more likely to experience psychosocial, physical, and functional problems than women who do not, therefore health care providers should be aware of the changes and distresses that these breast cancer patients go through and provide specific information and psychosocial support to socioeconomically more vulnerable patients.

• Korean journal of applied entomology
• /
• v.49 no.4
• /
• pp.305-312
• /
• 2010

The developmental time of immature stages of Paromius exiguus (Distant) was investigated at nine constant temperatures (15, 17.5, 20, 22.5, 25, 27.5, 30, 32.5, $35{\pm}1^{\circ}C$), 20-30% RH, and a photoperiod of 14:10h (L:D). Eggs did not develop at $15^{\circ}C$, and their developmental time decreased with increasing temperatures. Its developmental time was longest at $17.5^{\circ}C$ (28.2 days) and shortest at $35^{\circ}C$ (5.9 days). The first nymphs failed to reach the next nymphal stage at 17.5 and $35^{\circ}C$. Nymphal developmental time decreased with increasing temperatures between $20^{\circ}C$ and $32.5^{\circ}C$, and developmental rate was decreased at temperatures above $30^{\circ}C$ in all stages except for the fourth nymphal stage. The relationship between developmental rate and temperature fit a linear model and three nonlinear models (Briere 1, Lactin 2, and Logan 6). The lower threshold temperature of egg and total nymphal stage was $l3.8^{\circ}C$ and $15.3^{\circ}C$, respectively. The thermal constant required to reach complete egg and the total nymphal stage was 109.9 and 312.5DD, respectively. The Logan-6 model was best fitted ($r^2$=0.94-0.99), among three nonlinear models. The distribution of completion of each development stage was well described by the 3-parameter Weibull function ($r^2$=0.91-0.99).

• Korean journal of applied entomology
• /
• v.50 no.4
• /
• pp.343-352
• /
• 2011

The developmental period of Laodelphax striatellus Fallen, a vector of rice stripe virus (RSV), was investigated at ten constant temperatures from 12.5 to $35{\pm}1^{\circ}C$ at 30 to 40% RH, and a photoperiod of 14:10 (L:D) h. Eggs developed successfully at each temperature tested and their developmental time decreased as temperature increased. Egg development was fasted at $35^{\circ}C$(5.8 days), and slowest at $12.5^{\circ}C$ (44.5 days). Nymphs could not develop to the adult stage at 32.5 or $35^{\circ}C$. The mean total developmental time of nymphal stages at 12.5, 15, 17.5, 20, 22.5, 25, 27.5 and $30^{\circ}C$ were 132.7, 55.9, 37.7, 26.9, 20.2, 15.8, 14.9 and 17.4 days, respectively. One linear model and four nonlinear models (Briere 1, Lactin 2, Logan 6 and Poikilotherm rate) were used to determine the response of developmental rate to temperature. The lower threshold temperatures of egg and total nymphal stage of L. striatellus were $10.2^{\circ}C$ and $10.7^{\circ}C$, respectively. The thermal constants (degree-days) for eggs and nymphs were 122.0 and 238.1DD, respectively. Among the four nonlinear models, the Poikilotherm rate model had the best fit for all developmental stages ($r^2$=0.98~0.99). The distribution of completion of each development stage was well described by the two-parameter Weibull function ($r^2$=0.84~0.94). The emergence rate of L. striatellus adults using DYMEX$^{(R)}$ was predicted under the assumption that the physiological age of over-wintered nymphs was 0.2 and that the Poikilotherm rate model was applied to describe temperature-dependent development. The result presented higher predictability than other conditions.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_1
• /
• pp.627-646
• /
• 2022

Recently, the seriousness of climate change-related problems caused by global warming is growing, and the average temperature is also rising. As a result, it is affecting the environment in which various temperature-sensitive creatures and creatures live, and changes in the ecosystem are also being detected. Seasons are one of the important factors influencing the types, distribution, and growth characteristics of creatures living in the area. Among the most popular and easily recognized plant seasonal phenomena among the indicators of the climate change impact evaluation, the blooming day of flower and the peak day of autumn leaves were modeled. The types of plants used in the modeling were forsythia and cherry trees, which can be seen as representative plants of spring, and maple and ginkgo, which can be seen as representative plants of autumn. Weather data used to perform modeling were temperature, precipitation, and solar radiation observed through the ASOS Observatory of the Korea Meteorological Administration. As satellite data, MODIS NDVI was used for modeling, and it has a correlation coefficient of about -0.2 for the flowering date and 0.3 for the autumn leaves peak date. As the model used, the model was established using multiple regression models, which are linear models, and Random Forest, which are nonlinear models. In addition, the predicted values estimated by each model were expressed as isopleth maps using spatial interpolation techniques to express the trend of plant seasonal changes from 2003 to 2020. It is believed that using NDVI with high spatio-temporal resolution in the future will increase the accuracy of plant phenology modeling.

• Korean journal of applied entomology
• /
• v.62 no.4
• /
• pp.315-323
• /
• 2023

The brassica leaf beetle, Phaedon brassicae Baly (Coleoptera: Chrysomelidae), is one of the important pests infesting cruciferous vegetables. In order to understand the biological characteristics of the insect, we investigated the effects of temperature on development of each life stage, adult longevity and fecundity of P. brassicae at four constant temperatures of 15, 20, 25 and 27.5℃ for immature life stage and five constant different temperatures of 10, 15, 20, 25 and 27.5℃ for adult stage. Eggs and larvae successfully developed next life stage at temperature tested. The development period of egg, larva, and pupa decreased as temperature increased. Lower developmental threshold (LDT) and thermal constant (K) were calculated using linear regression as 8.7℃ and 344.73DD, respectively. Lower and higher threshold temperature (TL and TH) from egg to adult emergence were estimated by Briere function as 5.3℃ and 40.4℃, respectively. Adults produced eggs at the temperature range between 10℃ and 27.5℃, and showed an estimated maximum number, ca. 627.5 eggs at 21.7℃. Adult oviposition models including aging rate, age-specific survival rate, age-specific cumulative oviposition, and temperature-dependent fecundity were constructed. Temperature-dependent development models and adult oviposition models would be useful components to understand the population dynamics of P. brassicae and to establish the strategy of integrated pest management in cruciferous crops.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.123-139
• /
• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.9 no.5 s.45
• /
• pp.41-52
• /
• 2005

Using the variable control gain scheme on the basis of fuzzy-based decision-making process, Fuzzy supervisory control (FSC) technique exhibits better control performance than linear control technique with one static control gain. This paper demonstrates the effectiveness of the FSC technique by evaluating the robust performance of the FSC technique under the presence of uncertainties in the models and the excitations. Robust performance of the FSC system is compared with that of optimally designed LQG control system for the benchmark cable-stayed bridge presented by Dyke et al. Parameter studies on the robust performance evaluation are carried out by varying the stiffness of the bridge model as well as the magnitudes of several earthquakes with different frequency contents. From the comparative study of two control systems, FSC system shows the enhanced control performance against various magnitudes of several earthquakes while maintaining lower level of power required for controlling the bridge response. Especially, FSC system clearly guarantees the improved robust performance of the control system with stable reduction effects on the seismic responses and slight increases in total power and stroke for the control system, while LQG control system exhibits poor robust performance.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.17 no.3
• /
• pp.1-9
• /
• 2013

This paper presents high-velocity impact analysis of two-way RC slabs, including steel fibers and strengthening with fiber reinforced polymer (FRP) sheets for evaluating impact resistance. The analysis uses the LS-DYNA program, which is advanced in impact analysis. The present analysis was performed similarly to the high-velocity impact tests conducted by VTT, the technical research center of Finland, to verify the analysis results. High-velocity impact loads were applied to $2100{\times}2100{\times}250$ mm size two-way RC slab specimens, using a non-deformable steel projectile of 47.5kg mass and 134.9m/s velocity. In this research, extra impact analysis of material specimens was carried out to verify the material models used to the analysis. The elastic-plastic hydrodynamic model, concrete damage model and orthotropic elastic model were used to simulate the non-linear softening behavior of steel fiber reinforced concrete (SFRC), and material properties of normal concrete and FRP sheets, respectively. It is concluded that the suggested analysis technique has good reliability, and can be effectively applied in evaluating the effectiveness of reinforcing/retrofitting materials and techniques. Also, the Steel fiber and FRP sheet strengthening systems provided outstanding performance under high-velocity impact loads.

• Environmental and Resource Economics Review
• /
• v.13 no.4
• /
• pp.593-619
• /
• 2004

This study analyzes the interfuel substitution of energy demand in Korean manufacturing sector using static and dynamic linear logit models. For the period of 1981~2002, this study uses petroleum, electricity, natural gas and coal as energy sources. According to the empirical results, firstly, the own-price elasticity of coal has been increased steadily even though its elasticity is smallest compared with those of other energy sources. On the other hand, price elasticity of natural gas is largest, but its value has been decreased after 1997. Price elasticities of petroleum and electricity are very stable over the sample period. One of the main features in trends of interfuel substitution is as follows. Substitution effect of a change in price of natural gas on both petroleum and coal has been increased especially after 1997. The implication of the empirical results is summarized as follows: First, the fact of inelastic own-price elasticity of petroleum implies that the dependency of Korean manufacturing sector on petroleum and coal will be persistent even in a sharp fluctuation of petroleum price. Second, the effects of price increase in natural gas on demand for petroleum and coal are very significant. Thus, price decline of natural gas rather than price declines of coal and petroleum could be more effective as an energy price policy for the reduction of $CO_2$ emission. The assessment on this implication will remain for future researches.

• Journal of Korea Water Resources Association
• /
• v.44 no.10
• /
• pp.819-830
• /
• 2011

The multi-slope MUSCL, proposed by T. Buffard and S. Clain, determines slopes of conserved variables at each edge of a cell in the linear reconstructions of data. In this study, the second order accurate numerical model was developed according to the multi-slope MUSCL to solve the shallow water equations on the unstructured grids. The HLLL scheme of approximate Riemann solvers was used to calculate fluxes. For the review of the applicability of the developed model, the results of the model were compared to the 'isolated building test' and the 'model city flooding experiment' conducted as part of the IMPACT (Investigation of extreMe flood Processes And unCerTainty) project in Europe. There were limitations to predict abrupt rising of water depths by the resistance of model buildings and water depths at the specific locations among the buildings. But they were identified as the same problems also revealed in results of the other models to the same experiment. On the more refined meshes to the 'model city flooding experiment' simulated results showed good agreement with measurements. It was verified that the developed model simulated well the complex phenomena such as a dam-break problem and the urban inundation by flash floods.