• Journal of The Korean Society of Grassland and Forage Science
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• v.32 no.3
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• pp.301-308
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• 2012

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid and accurate method of evaluating some chemical compositions in forages. This study was carried out to explore the accuracy of near infrared spectroscopy (NIRS) for the prediction of chemical parameters of Italian ryegrass silages. A population of 267 Italian ryegrass silages representing a wide range in chemical parameters and fermentative characteristics was used in this investigation. Samples of silage were scanned at 2 nm intervals over the wavelength range 680~2,500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected on the basis of the highest coefficients of determination in cross validation ($R^2$) and the lowest standard error of cross validation (SECV). The results of this study showed that NIRS predicted the chemical parameters with very high degree of accuracy. The $R^2$ and SECV were 0.98 (SECV 1.27%) for moisture, 0.88 (SECV 1.26%) for ADF, 0.84 (SECV 2.0%), 0.93 (SECV 0.96%) for CP and 0.78 (SECV 0.56), 0.81 (SECV 0.31%), 0.88 (SECV 1.26%) and 0.82 (SECV 4.46) for pH, lactic acid, TDN and RFV on a dry matter (%), respectively. Results of this experiment showed the possibility of NIRS method to predict the chemical composition and fermentation quality of Italian ryegrass silages as routine analysis method in feeding value evaluation and for farmer advice.

• Journal of Gastric Cancer
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• v.8 no.4
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• pp.189-197
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• 2008

Purpose: Peritoneal lavage cytology is regarded as a useful diagnostic test for detecting intraperitoneal micrometastsis. However, there are currently no reports about cytological examination with $ThinPrep^{(R)}$ (CY), a newly introduced fluid-based diagnostic system, in patients with advanced gastric cancer (AGC). This study was performed to analyze the clinical significance of intraoperative peritoneal lavage for CY in AGC patients. Materials and Methods: 424 AGC patients were suspected to have serosal exposure macroscopically during surgery and they underwent intraoperative peritoneal lavage for CY between 2001 and 2006 at Korea Cancer Center Hospital. The clinical data, pathological data and CY results were collected and analyzed retrospectively. Results: The percentage of cytology positive results was 31.1%, and this was well correlated with the T-stage, N-stage and P-stage. The 3-year survival rates of CY0 and CY1 were 68.1% and 25.9%, respectively. According to the P-stage and CY, the 3-year survival rates were 71.1% in P0CY0, 38.9% in P0CY1, 38.5% in P1/2/3CY0 and 11.0% in P1/2/3CY1. Interestingly, both the P0CY1 and P1/2/3CY0 survival curves were similar figures, but they were significantly different from those of the other groups. Multivariate analysis indicated that CY was an independent, strong prognostic factor for survival, as well as sex, the T-stage, N-stage, P-stage, other metastasis and the serum CEA. CY1 was revealed as a risk factor for peritoneal recurrence in the curative resection group. Conclusion: The results certify indirectly that cytological examination using $ThinPrep^{(R)}$ is a very reliable diagnostic method for detecting intraperitoneal micrometastasis from the fact that it is not only a strong prognostic factor, but it is also a risk factor for peritoneal recurrence in AGC patients. Therefore intraoperative peritoneal lavage should be included in the routine intraoperative staging workup for AGC, and its result will provide a good target for the treatment of peritoneal micrometastasis.

• Radiation Oncology Journal
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• v.22 no.4
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• pp.254-264
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• 2004

Purpose: This study was carried out to confirm clinical values and limitations of postoperative radiotherapy for hypopharyngeal carcinoma, to evaluate various prognostic factors which may affect to the treatment results and to use these results as fundamental data for making a new treatment strategy. Methods and Materials:. A retrospective analysis was peformed on 64 previously untreated patients with squamous cell carcinoma of the hypopharynx, seen between 1988 and 1999 at Pusan National University Hospital. Most of patients were treated by laryngopharyngectomy and neck dissection followed by conventional fractionated postoperative radiotherapy on surgical bed and cervical nodal areas. Results: The five-year overall survival rate and cause-specific survival rate were 42.2 percent and 51.6 percent, respectively. Univariate analysis of various clinical and pathologic factors confirmed the overall stage, TN-stage, secondary primary cancers, surgical positive margin, nodal extracapsular extension, total radiation doses as significant prognostic factors of hypopharyngeal carcinomas. But in multivariate analysis, TN-stage, surgical positive margin and extracapsular extesion were only statistically significant. Conclusion: In resectable cases of hypopharyngeal carcinoma, combined surgery and postoperative radio-therapy obtained good treatement results, even though sacrificing the function of larynx and pharynx. But in advanced and unresectable cases, with respect to survivals and qualify of life issues, we were able to confirm some limitations of combined therapy. So we recommend that comparative studies of recent various chemo-radiotherapy methods and advanced radiotherapy techniques with these data should be needed.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.1
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• pp.50-57
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• 2016

This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation ($R^2{_{cv}}$) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, $R^2{_{cv}}$, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy ($R^2{_{cv}}$ 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.

• Journal of Hospice and Palliative Care
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• v.17 no.1
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• pp.27-33
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• 2014

Purpose: Although vitamin D deficiency is more commonly found in cancer patient than in non-cancer patients, there have been little data regarding the prevalence of vitamin D deficiency in cancer patients at the very end of life. We examined vitamin D deficiency in terminally ill cancer patients and related factors. Methods: This study was based on a retrospective chart review of 133 patients in a hospice ward. We collected data regarding age, sex, serum 25-hydroxyvitamin D level, cancer type, physical performance, current medications and various laboratory findings. We investigated factors related to serum vitamin D levels after multivariate adjustment for potential confounders. Serum 25-hydroxyvitamin D<20 ng/mL was considered deficient and <10 ng/mL severely deficient. Results: Ninety-five percent of the patients were serum vitamin D deficient. Severe vitamin D deficiency was more common in male patients, non-lung cancer patients, $H_2$ blocker users and non-anticonvulsant users. Elevated levels of serum alanine aminotransferase (ALT) were also associated with low serum vitamin D levels. Multiple regression analysis showed that severe vitamin D deficiency was associated with male gender (aOR 3.82, 95% CI: 1.50~9.72, P=0.005), $H_2$ blocker users (aOR 3.94, 95% CI: 1.61~9.65, P=0.003) and elevated serum ALT levels (aOR 4.52, 95% CI: 1.35~15.19, P=0.015). Conclusion: Vitamin D deficiency was highly prevalent among terminally ill cancer patients. Severe vitamin D deficiency was more common in male patients, $H_2$ blocker users, and patients with elevated ALT levels.

• Journal of Nutrition and Health
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• v.52 no.2
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• pp.227-241
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• 2019

Purpose: This study examined the relationship between caffeine intake and metabolic syndrome in Korean adults using the 2013 ~ 2016 Korea National Health and Nutrition Examination Survey data (KNHANES). Methods: The caffeine database (DB) developed by Food and Drug Safety Assessment Agency in 2014 was used to estimate the caffeine consumption. The food and beverage consumption of the 24 hr recall data of 2013 ~ 2016 KNHANES were matched to items in the caffeine DB and the daily caffeine intakes of the individuals were calculated. The sample was limited to non-pregnant healthy adults aged 19 years and older, who were not taking any medication for disease treatment. Results: The average daily caffeine intake was 41.97 mg, and the daily intake of caffeine of 97% of the participants was from coffee, teas, soft drinks, and other beverages. Multivariate analysis showed that the caffeine intake did not affect metabolic syndrome, hypertension, low HDL-cholesterol, and abdominal obesity. Diabetes and hypertriglyceridemia, however, were 0.76 (95% CI: 0.63 ~ 0.93), and 0.87 (95% CI: 0.77 ~ 0.98) in third quintile (Q3), and 0.66 (95% CI: 0.53 ~ 0.82) and 0.83 (95% CI: 0.73 ~ 0.94) in fourth quintile (Q4) compared to Q1, respectively. Therefore, caffeine intake of 3.66 ~ 45.81 mg per day is related to a lower risk of diabetes and hypertriglyceridemia. Conclusion: The study showed that adequate caffeine intake (approximately 45 mg) was associated with a lower prevalence of diabetes and hypertriglyceridemia. Therefore, it can be used as a guideline for the adequate level of caffeine intake for maintaining health.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.392-402
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• 2019

The purpose of this study is to determine the factors that predict happiness among aged males and females who live alone, and we focused on their satisfaction with their socio-physical environment, their social network, regular participation in social activities, their subjective health status and if they suffer from depression. A total of 2,76 people were the subjects of this study, their average age was 65 years old, they lived alone and all of them were selected from the '2017 Community Health Survey' data. The data was analyzed utilizing the Chi-square test, the Mann-Whitney test and multivariate logistic regression analysis. The subjects were 605 males (21.86%) and 2,163 females (78.14%). For the result of this study, the significant predictive factors of happiness for aged males living alone were monthly income (OR=2.363, 95% CI=1.473-3.791), basic livelihood rights (OR=1.903, 95% CI=1.144-3.167), trusting their neighbors (OR=2.018, 95% CI=1.263-3.225), religious activities (OR=2.098, 95% CI=1.314-3.349), subjective health (OR=2.753, 95% CI=1.217-6.228), and depression (OR=0.852, 95% CI=0.803-0.905). The significant predictive factors of happiness for aged females living alone were income (OR=2.407 95% CI=1.362-4.253), basic livelihood rights (OR=1.350, 95% CI=1.019-1.788), contact with friends (OR=1.879, 95% CI=1.323-2.669), religious activities (OR=1.372, 95% CI=1.124-1.676), recreation/leisure activities (OR=1.608, 95% CI=1.161-2.228), subjective health (OR=5.327, 95% CI=1.347-21.070), and depression (OR=0.864, 95% CI=0.840-0.890). In conclusion, programs to enhance happiness should be developed with considering the characteristics affecting the happiness of aged Korean males and females who live alone.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.2
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• pp.114-120
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• 2019

This study was carried out to explore the accuracy of near infrared spectroscopy(NIRS) for the prediction of moisture content and chemical parameters on winter annual forage crops. A population of 2454 winter annual forages representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation($R^2$) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS calibration model to predict the moisture contents and chemical parameters had very high degree of accuracy except for barely. The $R^2$ and SECV for integrated winter annual forages calibration were 0.99(SECV 1.59%) for moisture, 0.89(SECV 1.15%) for acid detergent fiber, 0.86(SECV 1.43%) for neutral detergent fiber, 0.93(SECV 0.61%) for crude protein, 0.90(SECV 0.45%) for crude ash, and 0.82(SECV 3.76%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of winter annual forage for routine analysis method to evaluate the feed value.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.885-894
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• 2006

The purpose of this study is focused on the development of the effective classification technique using ultra multiband of hyperspectral image. This study suggests the classification technique using canonical correlation analysis, one of multivariate statistical analysis in hyperspectral image classification. High accuracy of classification result is expected for this classification technique as the number of bands increase. This technique is compared with Maximum Likelihood Classification(MLC). The hyperspectral image is the EO1-hyperion image acquired on September 2, 2001, and the number of bands for the experiment were chosen at 30, considering the band scope except the thermal band of Landsat TM. We chose the comparing base map as Ground Truth Data. We evaluate the accuracy by comparing this base map with the classification result image and performing overlay analysis visually. The result showed us that in MLC's case, it can't classify except water, and in case of water, it only classifies big lakes. But Canonical Correlation Classification (CCC) classifies the golf lawn exactly, and it classifies the highway line in the urban area well. In case of water, the ponds that are in golf ground area, the ponds in university, and pools are also classified well. As a result, although the training areas are selected without any trial and error, it was possible to get the exact classification result. Also, the ability to distinguish golf lawn from other vegetations in classification classes, and the ability to classify water was better than MLC technique. Conclusively, this CCC technique for hyperspectral image will be very useful for estimating harvest and detecting surface water. In advance, it will do an important role in the construction of GIS database using the spectral high resolution image, hyperspectral data.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.