• Journal of Hospice and Palliative Care
• /
• v.11 no.4
• /
• pp.181-187
• /
• 2008

Purpose: In order to establish efficient palliative treatment plans. It is important to estimate the survival time of a terminally ill cancer patient as accurate as possible. Proper estimation of life expectancy aids not only in improving the quality of life of the patient, it also promotes productive communication between the medical staff and the patient. The aim of this study is to determine the efficacy of neutrophil-lymphocyte ratio as a predictor of survival time in terminally ill cancer patients. Methods: Between January 2004 and June 2007, 67 terminally ill cancer patients who were admitted or transferred for palliative care, were included. Patients were categorized into three groups by Neutrophil-Lymphocyte Ratio. Demographic characteristics, clinical characteristics and blood samples were analyzed. Results: In univariate analysis, survival time of the highest Neutrophil-Lymphocyte Ratio group (${\geq}12.5$) was significantly shorter than that of the others (hazard ratio (HR)=3.270, P=0.001). After adjustment for low performance status (ECOG score 4) and dyspnea, high Neutrophil-Lymphocyte Ratio (${\geq}12.5$) was significantly and independently associated with short survival time (HR=2.907, P=0.007). Neutrophil-Lymphocyte Ratio was also significantly increased before death (P=0.001). Conclusion: Neutrophil-Lymphocyte Ratio can be useful in predicting life expectancy in terminally ill cancer patients.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.20 no.3
• /
• pp.125-140
• /
• 2017

Until recently, regression based spatial interpolation methods and Kriging based spatial interpolation methods have been largely used to estimate land price or housing price, but less attention has been paid on comparing the performance of these spatial interpolation methods. In this regard, this research applied regression based spatial interpolators and Kriging based spatial interpolators for estimating the land prices in Dalseo-gu, Daegu metropolitan city and evaluated the accuracy of eight spatial interpolators. OLS, SLM, SEM, and GWR were used as regression based spatial interpolators while SK, OK, UK, and CK were employed as Kriging based spatial interpolators. The global accuracy was statistically evaluated by RMSE, adjusted RMSE, and COD. The relative accuracy was visually compared by three-dimensional residual error map and scatterplot. Results from statistical and visual analyses indicate that GWR reflecting the spatial non-stationarity was a relatively more accurate spatial predictor to estimate land prices in the study area than SAR and Kriging based spatial interpolators considering the spatial dependence. The findings from this research will contribute to the secondary research into analyzing the urban spatial structure with land prices.

• Journal of Digital Convergence
• /
• v.16 no.8
• /
• pp.169-179
• /
• 2018

Recently, web search query information has been applied in advanced predictive model research. Google dominates the global web search market in the Korean market; however, Naver possesses a dominant market share. Based on this characteristic, this study intends to compare the utility of the Korean web search query information of Google and Naver using predictive models. Therefore, this study develops three time-series predictive models to estimate the youth unemployment rate in Korea using the ARIMA model. Model 1 only used the youth unemployment rate in Korea, whereas Models 2 and 3 added the Korean web search query information of Naver and Google, respectively, to Model 1. Compared to the predictability of the models during the training period, Models 2 and 3 showed better fit compared with Model 1. Models 2 and 3 correlated different query information. During predictive periods 1 (continuous with the training period) and 2 (discontinuous with the training period), Model 3 showed the best performance. During predictive period 2, only Model 3 exhibited a significant prediction result. This comparative study contributes to a general understanding of the usefulness of Korean web query information using the Naver and Google search engines.

• Journal of Korean Academy of Nursing
• /
• v.29 no.5
• /
• pp.1087-1102
• /
• 1999

Diabetes mellitus, a universal and prevalent chronic disease, is projected to be one of the most formidable worldwide health problems in the 21st century. For those living with diabetes, there is a need for self-care skills to manage a complex medical regimen. Self-efficacy which refers to one's belief in his/her capability to monitor and perform the daily activities required to manage diabetes has be found to be related to self-care. The concept of self-efficacy comes from social cognitive theory which maintains that cognitive mechanism mediate the performance of behavior. The literature cites several research studies which show a strong relationship between self-efficacy and self-care behavior. Meta-analysis is a technique that enables systematic review and quantitative integration of the results from multiple primary studies that are relevant to a particular research question. Therefore, this study was done using meta-analysis to quantitatively integrate the results of independent research studies to obtain numerical estimates of the overall effect of a self-efficacy with diabetic patient on self-care behaviors. The research proceeded in three stages : 1) literature search and retrieval of studies in which self-efficacy was related to self-care, 2) coding, and 3) calculation of mean effect size and data analysis. Seventeen studies which met the research criteria included study population of adults with diabetes, measures of self-care and measures of self-efficacy as a predictive variable. Computation of effect size was done on DSTAT which is a statistical computer program specifically designed for meta-analysis. To determine the effect of self-efficacy on self-care practice homogeneity tests were conducted. Pooled effect size estimates, to determine the best subvariable for composite variables, metabolic control variables and component of self-efficacy and self-care, indicated that the effect of self-efficacy composite on self-care composite was moderate to large. The weighted mean effect size of self-efficacy composite and self-care composite were ＋.76 and the confidence interval was from ＋.66 to ＋.86 with the number of subjects being 1,545. The total for this meta-analysis result showed that the weighted mean effect sizes ranged from ＋.70 to ＋1.81 which indicates a large effect. But since reliabilities of the instruments in the primary studies were low or not stated, caution must be applied in unconditionally accepting the results from these effect sizes. Meta-analysis is a useful took for clarifying the status of knowledge development and guiding decision making about future research and this study confirmed that there is a relationship between self-efficacy and self-care in patients with diabetes. It, thus, provides support for nurses to promote self-efficacy in their patients. While most of the studies included in this meta-analysis used social cognitive theory as a framework for the study, some studies use Fishbein & Ajzen's attitude model as a model for active self-care. Future research is needed to more fully define the concept of self-care and to determine what it is that makes patients feel competent in their self-care activities. The results of this study showed that self-efficacy can promote self-care. Future research is needed with experimental design to determine nursing interventions that will increase self-efficacy.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.3
• /
• pp.160-174
• /
• 2008

In this paper, we propose new coding techniques for photometry data of three-dimensional(3-D) mesh models. We make a good use of geometry and connectivity information to improve coding efficiency of color, normal vector, and texture data. First of all, we determine the coding order of photometry data exploiting connectivity information. Then, we exploit the obtained geometry information of neighboring vortices through the previous process to predict the photometry data. For color coding, the predicted color of the current vertex is computed by a weighted sum of colors for adjacent vortices considering geometrical characteristics between the current vortex and the adjacent vortices at the geometry predictor. For normal vector coding, the normal vector of the current vertex is equal to one of the optimal plane produced by the optimal plane generator with distance equalizer owing to the property of an isosceles triangle. For texture coding, our proposed method removes discontinuity in the texture coordinates and reallocates texture image segments according to the coding order. Simulation results show that the proposed compression schemes provide improved performance over previous works for various 3-D mesh models.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2005.05a
• /
• pp.273-280
• /
• 2005

Robust magneto-telluric (MT) response function estimators are now in standard use in electromagnetic induction research. Properly devised and applied, these methods can reduce the influence of unusual data (outlier) in the response (electric field) variable, but often not sensitive to exceptional predictor (magnetic field) data, which are termed leverage points. A bounded influence estimator is described which simultaneously limits the influence of both outlier and leverage point, and has proven to consistently yield more reliable MT response function estimates than conventional robust approach. The bounded influence estimator combines a standard robust M-estimator with leverage weighting based on the statistics of the hat matrix diagonal, which is a standard statistical measure of unusual predictors. Further extensions to MT data analysis are proposed, including a establishment of data rejection criterion which minimize the influence of both electric and magnetic outlier in frequency domain based on statistical distribution of electromagnetic field. The rejection scheme made in this study seems to have an effective performance on eliminating extreme data, which is even not removed by BI estimator, in frequency domain. The effectiveness and advantage of these developments are illustrated using real MT data.

• Journal of muscle and joint health
• /
• v.7 no.1
• /
• pp.102-130
• /
• 2000

The aims of this study were to understand and to predict the determinant factors affecting the exercise behaviors and physical fitness by testing the Ponder's health promotion model, and to help the patients with rheumatoid arthritis and osteoarthritis perform the continuous exercise program, and to help them maximize the physical effect such as muscle strength. endurance, and fuctional status and mental effects including self efficacy and quality of life, and improve the physical and mental wellbeing, and to provide a basis for the nursing intervention strategies. We analyzed the clinical records of 208 patients with rheumatoid arthritis and degenerative arthritis who visited the outpatient clinics at H university hospital in Seoul between October 5, 1999 and October 24, 1999. Data were composed of self reported questionnaire and good of fitness score which were obtained by pedalling the ergometer of bicycle for 9 minutes. SPSS Win 8.0 and Window LISREL 8.12a were used for statistical analysis. 24 Of 54 hypothetical paths were supported in modified model, which was considered as a proper model with improved fit index. The physical fitness was directly influenced by exercise participation behavior and education level, and indirectly by physical fitness, while fatigue, physical disability, pastexercise behavior, life-style, self-efficacy, which explained 20% of physical fitness. The exercise participation were directly influenced by perceived benefits and self-efficacy, and indirectly influenced by life-style, fatigue and physical disability, and directly and indirectly by past exercise behavior, which explained 53% of exercise participation. Exercise score were directly affected by perceived health status, perceived benefits, self efficacy, and past exercise behavior, and were indirectly affected by fatigue, physical disability, and life-style, which explained 50%. Perceived health status were directly influeced by level of education, depression, sleep disorder, and physical disability, which explained 34% of perceived health status. Perceived benefit was directly influenced by fatigue, sleep disorder, physical disability, and life-style, which explained 45%. Perceived barriers was directly influenced by fatigue, sleep disorder, and lifestyle, which explained 9%. Self- efficacy was directly influenced by fatigue, physical disability, past exercise behavior, and level of education, which explained 61%. In conclusion, important variables for physical fitness were exercise participation and level of education, and variables affecting exercise participation were perceived self-efficacy, benefits, and past exercise behavior. Perceived self-efficacy of exercise was a significant predictor of exercise participation. Life-style, fatigue, and physical disability showed direct effects on perceived benefit, perceived barriers, and self-efficacy, and indirect effects on exercise behavior. Therefore, disease related factor should be minimized for physical performance and well being in nursing intervention for patients with rheumatoid arthritis, and plans to promote and continue exercise should be soaked to reduce disability. In addition, Exercise program should be planned and performed by the exact evaluation of exercise according to the ability of the patients and the contents to improve the importance of exercise and self efficacy in self control program, dedicated educational program should be involved.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.5
• /
• pp.361-366
• /
• 2017

As the recent development of computing architecture and application software technology, real world simulation, which is the ultimate destination of computer simulation, is emerging as a practical issue in several research sectors. In this paper, metal plate motion in a square shock tube for small time interval was calculated using a supercomputing-based fluid-structure-combustion multi-physics simulation tool called Illinois Rocstar, developed in a US national R amp; D program at the University of Illinois. Afterwards, the simulation results were compared with those from experiments. The coupled solvers for unsteady compressible fluid dynamics and for structural analysis were based on the finite volume structured grid system and the large deformation linear elastic model, respectively. In addition, a strong correlation between calculation and experiment was shown, probably because of the predictor-corrector time-integration scheme framework. In the future, additional validation studies and code improvements for higher accuracy will be conducted to obtain a reliable open-source software research tool.

• Journal of the Korean earth science society
• /
• v.30 no.3
• /
• pp.294-304
• /
• 2009

A statistical prediction model for the typhoon intensity and track in the Northwestern Pacific area was developed based on the artificial neural network scheme. Specifically, this model is focused on the 5-day prediction after tropical cyclone genesis, and used the CLIPPER parameters (genesis location, intensity, and date), dynamic parameters (vertical wind shear between 200 and 850hPa, upper-level divergence, and lower-level relative vorticity), and thermal parameters (upper-level equivalent potential temperature, ENSO, 200-hPa air temperature, mid-level relative humidity). Based on the characteristics of predictors, a total of seven artificial neural network models were developed. The best one was the case that combined the CLIPPER parameters and thermal parameters. This case showed higher predictability during the summer season than the winter season, and the forecast error also depended on the location: The intensity error rate increases when the genesis location moves to Southeastern area and the track error increases when it moves to Northwestern area. Comparing the predictability with the multiple linear regression model, the artificial neural network model showed better performance.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.15
• /
• pp.6449-6453
• /
• 2014

Background: Prior studies showed a relationship between serum albumin and the albumin to globulin ratio with different types of cancer. We aimed to evaluate the predictive value of the albumin-globulin ratio (AGR) for survival of patients with lung adenocarcinoma. Materials and Methods: This retrospective study included 240 lung adenocarcinoma patients. Biochemical parameters before chemotherapy were collected and survival status was obtained from the hospital registry. The AGR was calculated using the equation AGR=albumin/(total protein-albumin) and ranked from lowest to highest, the total number of patients being divided into three equal tertiles according to the AGR values. Furthermore, AGR was divided into two groups (low and high tertiles) for ROC curve analysis. Cox model analysis was used to evaluate the prognostic value of AGR and AGR tertiles. Results: The mean survival time for each tertile was: for the $1^{st}$ 9.8 months (95%CI:7.765-11.848), $2^{nd}$ 15.4 months (95%CI:12.685-18.186), and $3^{rd}$ 19.9 months (95%CI:16.495-23.455) (p<0.001). Kaplan-Meier curves showed significantly higher survival rates with the third and high tertiles of AGR in comparison with the first and low tertiles, respectively. At multivariate analysis low levels of albumin and AGR, low tertile of AGR and high performance status remained an independent predictors of mortality. Conclusions: Low AGR was a significant predictor of long-term mortality in patients with lung adenocarcinoma. Serum albumin measurement and calculation of AGR are easily accessible and cheap to use for predicting mortality in patients with lung adenocarcinoma.