• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.2
• /
• pp.691-694
• /
• 2014

Background: Tumor length in patients with esophageal cancer (EC) has recently received great attention. However, its prognostic role for EC is controversial. The purpose of our study was to characterize the prognostic value of tumor length in EC patients and offer the optimum cut-off point of tumor length by reliable statistical methods. Materials and Methods: A retrospective analysis was conducted on 71 consecutive patients with EC who underwent surgery. ROC curve analysis was used to determine the optimal cut-off point for tumor length, measured with a handheld ruler after formalin fixation. Correlations between tumor length and other factors were surveyed, and overall survival (OS) rates were compared between the two groups. Potential prognostic factors were evaluated by univariate Kaplan-Meier survival analysis. A P value less than 0.05 was considered significant. Results: There were a total of 71 patients, with a male/female divide of 43/28 and a median age of 59. Characteristics were as follows: squamous/adenocarcinoma, 65/6; median tumor length, 4 (0.9-10); cut-off point for tumor length, 4cm. Univariate analysis prognostic factors were tumor length and modality of therapy. One, three and five year OS rates were 84, 43 and 43% for tumors with ${\leq}4cm$ length, whereas the rates were 75, 9 and 0% for tumors >4 cm. There was a significant association between tumor length and age, sex, weight loss, tumor site, histology, T and N scores, differentiation, stage, modality of therapy and longitudinal margin involvement. Conclusions: Future studies for modification of the EC staging system might consider tumor length too as it is an important prognostic factor. Further assessment with larger prospective datasets and practical methods (such as endoscopy) is needed to establish an optimal cut-off point for tumor length.

• The Journal of Industrial Distribution & Business
• /
• v.8 no.4
• /
• pp.47-52
• /
• 2017

Purpose - This current study will investigate the average financial ratio of top and failed five-star hotels in the Jeju area. A total of 14 financial ratio variables are utilized. This study aims to; first, assess financial ratio of the first-class hotels in Jeju to establishing variables, second, develop distress prediction model for the first-class hotels in Jeju district by using logit analysis and third, evaluate distress prediction capacity for the first-class hotels in Jeju district by using logit analysis. Research design, data, and methodology - The sample was collected from year 2015 and 14 financial ratios of 12 first-class hotels in Jeju district. The results from the samples were analyzed by t-test, and the independent variables were chosen. This was an empirical study where the distress prediction model was evaluated by logit analysis. This current research has focused on critically analyzing and differentiating between the top and failed hotels in the Jeju area by utilizing the 14 financial ratio variables. Results - The verification result of the accuracy estimated by logit analysis has shown to indicate that the distress prediction model's distress prediction capacity was 83.3%. In order to extract the factors that differentiated the top hotels in the Jeju area from the failed hotels among the 14 chosen, the analysis of t-black was utilized by independent variables. Logit analysis was also used in this study. As a result, it was observed that 5 variables were statistically significant and are included in the logit analysis for discernment of top and failed hotels in the Jeju area. Conclusions - The distress prediction press' prediction capability was compared in this research analysis. The distress prediction press prediction capability was shown to range from 75-85% by logit analysis from a previous study. In this current research, the study's prediction capacity was shown to be 83.33%. It was considered a high number and was found to belong to the range of the previous study's prediction capacity range. From a practical perspective, the capacity of the assessment of the distress prediction model in the top and failed hotels in the Jeju area was considered to be a prominent factor in applications of future hotel appraisal.

• The Journal of the Korea Contents Association
• /
• v.16 no.1
• /
• pp.676-687
• /
• 2016

The purpose of this study was to examine the relation of motor function, depression, and fear of falling, and to identify factors influencing fear of falling in patients with Parkinson's disease in the community. The participants were 180 patients with Parkinson's disease who were selected by convenience sampling. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation coefficient and multiple linear regression. There was a significant difference in fear of falling according to gender, occupation, walking assistance device, number of falls, Parkinson's disease stage, duration of illness, antihypertensive drug, motor function, and depression. Fear of falling showed significant positive correlations with motor function, and depression. Depression, number of falls, Parkinson's disease stage, gender, antihypertensive drug, and motor function were significant predictors influencing fear of falling in patients with Parkinson's disease, and these variables accounted for 36.0% of the variance. Depression of the influencing factors was the strongest factor. The results of this study suggest that a variety of intervention strategies for preventing or mitigating depression with systematic nursing assessment of the influencing factors on fear of falling are needed to prevent fear of falling in patients with Parkinson's disease.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.10
• /
• pp.461-470
• /
• 2020

This study analyzed the determinants of land compensation costs using the CALS (Continuous Acquisition & Life-Cycle Support) system to generate data for the construction (planning, design, building, management) process. For analysis, variables used in the related research on land costs were used, which included eight variables (Land Area, Individual Public Land Price, Appraisal & Assessment, Land Category, Use District 1, Terrain Elevation, Terrain Shape, and Road). Also, the variables were analyzed using the machine learning-based Xgboost algorithm. Individual Public Land Price was identified as the most important variable in determining land cost. We used a linear multiple regression analysis to verify the determinants of land compensation. For this verification, the dependent variable included was the Individual Public Land Price, and the independent variables were the numeric variable (Land Area) and factor variables (Land Category, Use District 1, Terrain Elevation, Terrain Shape, Road). This study found that the significant variables were Land Category, Use District 1, and Road.

• Asian-Australasian Journal of Animal Sciences
• /
• v.29 no.12
• /
• pp.1805-1811
• /
• 2016

The goal of this study was to estimate the emissions of greenhouse gases (GHG), namely methane ($CH_4$), nitrous oxide ($N_2O$), and carbon dioxide ($CO_2$) from poultry and pig production in South Korea over the last 10 years (2005 through 2014). The calculations of GHG emissions were based on Intergovernmental Panel on Climate Change (IPCC) guidelines. Over the study period, the $CH_4$ emission from manure management decreased in layer chickens, nursery to finishing pigs and gestating to lactating sows, but there was a gradual increase in $CH_4$ emission from broiler chickens and male breeding pigs. Both sows and nursery to finishing pigs were associated with greater emissions from enteric fermentation than the boars, especially in 2009. Layer chickens produced lower direct and indirect $N_2O$ emissions from 2009 to 2014, whereas the average direct and indirect $N_2O$ emissions from manure management for broiler chickens were 12.48 and $4.93Gg\;CO_2-eq/yr$, respectively. Annual direct and indirect $N_2O$ emissions for broiler chickens tended to decrease in 2014. Average $CO_2$ emission from direct on-farm energy uses for broiler and layer chickens were 46.62 and $136.56Gg\;CO_2-eq/yr$, respectively. For pig sectors, the $N_2O$ emission from direct and indirect sources gradually increased, but they decreased for breeding pigs. Carbon dioxide emission from direct on-farm energy uses reached a maximum of $53.93Gg\;CO_2-eq/yr$ in 2009, but this total gradually declined in 2010 and 2011. For boars, the greatest $CO_2$ emission occurred in 2012 and was $9.44Gg\;CO_2-eq/yr$. Indirect $N_2O$ emission was the largest component of GHG emissions in broilers. In layer chickens, the largest contributing factor to GHG emissions was $CO_2$ from direct on-farm energy uses. For pig production, the largest component of GHG emissions was $CH_4$ from manure management, followed by $CO_2$ emission from direct on-farm energy use and $CH_4$ enteric fermentation emission, which accounted for 8.47, 2.85, and $2.82Gg-CO_2/yr$, respectively. The greatest GHG emission intensity occurred in female breeding sows relative to boars. Overall, it is an important issue for the poultry and pig industry of South Korea to reduce GHG emissions with the effective approaches for the sustainability of agricultural practices.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
• /
• v.43 no.4
• /
• pp.229-238
• /
• 2017

Objectives: The primary purpose of this study was to investigate the factors related with additional administration of sedative agent during intravenous conscious sedation (IVS) using midazolam (MDZ). The secondary purpose was to analyze the factors affecting patient satisfaction. Materials and Methods: Clinical data for 124 patients who had undergone surgical extraction of mandibular third molar under IVS using MDZ were retrospectively investigated in this case-control study. The initial dose of MDZ was determined by body mass index (BMI) and weight. In the case of insufficient sedation at the beginning of surgery, additional doses were injected. During surgery, peripheral oxygen saturation, bispectral index score (BIS), heart rate, and blood pressure were monitored and recorded. The predictor variables were sex, age, BMI, sleeping time ratio, dental anxiety, Pederson scale, and initial dose of MDZ. The outcome variables were additional administration of MDZ, observer's assessment of alertness/sedation, intraoperative amnesia, and patient satisfaction. Descriptive statistics were computed, and the P-value was set at 0.05. Results: Most patients had an adequate level of sedation with only the initial dose of MDZ and were satisfied with the treatment under sedation; however, 19 patients needed additional administration, and 13 patients were unsatisfied. In multivariable logistic analysis, lower age (odds ratio [OR], 0.825; P=0.005) and higher dental anxiety (OR, 5.744; P=0.003) were related to additional administration; lower intraoperative amnesia (OR, 0.228; P=0.002) and higher BIS right before MDZ administration (OR, 1.379; P=0.029) had relevance to patient dissatisfaction. Conclusion: The preoperative consideration of age and dental anxiety is necessary for appropriate dose determination of MDZ in the minor oral surgery under IVS. The amnesia about the procedure affects patient satisfaction positively.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.40 no.4
• /
• pp.201-212
• /
• 2016

A Wind resource assessment and optimal micrositing of wind turbines were implemented for the development of an onshore wind farm of 30 MW capacity on Gadeok Island in Busan, Republic of Korea. The wind data measured by the automatic weather system (AWS) that was installed and operated in the candidate area were used, and a reliability investigation was conducted through a data quality check. The AWS data were measured for one year, and were corrected for the long term of 30 years by using the modern era retrospective analysis for research and application (MERRA) reanalysis data and a measure- correlate-predict (MCP) technique; the corrected data were used for the optimal micrositing of the wind turbines. The micrositing of the 3 MW wind turbines was conducted under 25 conditions, then the best-optimized layout was analyzed with a various wake model. When the optimization was complete, the estimated park efficiency and capacity factor were from 97.6 to 98.7 and from 37.9 to 38.3, respectively. Furthermore, the annual energy production (AEP), including wake losses, was estimated to be from 99,598.4 MWh to 100,732.9 MWh, and the area was confirmed as a highly economical location for development of a wind farm.

• Journal of Wetlands Research
• /
• v.13 no.1
• /
• pp.105-116
• /
• 2011

Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, the exact relationship and the spatial variability analysis of hydrometeorological elements and characteristic factors is critical elements to reduce the uncertainty in rainfall -runoff model. In this study, radar rainfall grid resolution and grid resolution depending on the topographic factor in rainfall - runoff models were how to respond. In this study, semi-distribution of rainfall-runoff model using the model ModClark of Inje, Gangwon Naerin watershed was used as Gwangdeok RADAR data. The completed ModClark model was calibrated for use DEM of cell size of 30m, 150m, 250m, 350m was chosen for the application, and runoff simulated by the RADAR rainfall data of 500m, 1km, 2km, 5km, 10km from 14 to 17 on July, 2006. According to the resolution of each grid, in order to compare simulation results, the runoff hydrograph has been made and the runoff has also been simulated. As a result, it was highly runoff simulation if the cell size is DEM 30m~150m, RADAR rainfall 500m~2km for peak flow and runoff volume. In the statistical analysis results, if every DEM cell size are 500m and if RADAR rainfall cell size is 30m, relevance of model was higher. Result of sensitivity assessment, high index DEM give effect to result of distributed model. Recently, rainfall -runoff analysis is used lumped model to distributed model. So, this study is expected to make use of the efficiently decision criteria for configurated models.

• Journal of the Korea Institute of Building Construction
• /
• v.20 no.2
• /
• pp.137-145
• /
• 2020

The recent bridge construction projects demand thorough and systematic safety and risk management, due to the increase of risk factors following the introduction of new and complex construction methods and technologies. Among many types of damages that can occur in bridge construction projects, the damages to third parties who are not directly related to the existing property of the contractor construction project can also bring about critical loss in the project in order to compensate the damages. Therefore, risks that could be caused by the loss occurred to indemnify the third party damages should be clearly analyzed, although there are not subsequent amount of studies focusing on the issue. Based on the past record of insurance payment from domestic insurance companies for bridge construction projects, this study aimed to analyze the risk factors of bridge construction for loss caused to compensate the third-party damages happened in actual bridge construction projects and to develop a quantified and numerical predictive loss model. In order to develop the model, the loss ratio was selected as the dependent variable; and among many analyzed independent variables, the superstructure, foundation, flood, and ranking of contractors were the four significant risk factor variables that affect the loss ratio. The results produced can be used as an essential guidance for balanced risk assessment, supplementing the existing analysis on material losses in bridge construction projects by taking into account the third-party damage and losses.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.12
• /
• pp.44-52
• /
• 2019

Industrial accidents differ considerably according to the industry and the scale of these industries. These industrial disasters have been analyzed in various ways. Therefore, a technique was developed to evaluate the disaster level among companies using the ANP method and the data derived from the disaster statistics over the past five years(2013~2017), as well as the safety information characteristics through questionnaires. The objective of the study was to determine the disaster level and safety level of a company. In this paper, six factors that are considered important for assessing the disaster level of the enterprise among the disaster statistics were selected. These factors included the industry type and size, age of employee, duration of treatment, duration of employment, and typical occurrence. Most companies use the accident rate for their disaster level to compare only with other companies. In this study, the weighting factors of the company were derived taking the characteristics of each company into consideration. Therefore, the disaster level of each company can be evaluated using the disaster statistics from each company and the derived weighting factors.