• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.1
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• pp.27-40
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• 2014

The functions of urban open space, which embraces community revitalization, are diverse. It is the means of public healthcare, learning centers for children, hub of arts and cultural programs, as well as promoter of urban tourism. However, in-depth discourse and research on the topic of urban open spaces has been limited so far. Hence, this study aims to investigate the motivations and satisfaction of visitation based on four representative waterfront open space in Seoul; Cheongyecheon Waterfront, Seoul Forest Park, Seonyudo Park and Banpo Hangang Park. The methods of study are literature review, observation investigation, and questionnaire survey. The findings are analyzed through the Exploratory Factor Analysis, Reliability Analysis, ANOVA Analysis and Regression Analysis by SPSS 18.0. The results of the study are as follows. First, urban waterfront open spaces in Seoul has 5 factors of visitor motivation; community amenity, nature access, cultural and educational assets, aesthetic enjoyment, and lastly means of escape. Second, factors of recognizing urban waterfront open spaces as community amenity and nature access indicate meaningful differences in visitor's perception by spatial characteristics. Third, distances between the destination and the visitor's residence influence significantly their perceived motivation. Close-range visitors perceived nature access as a principal factor, whilst medium to long-range visitors perceived visitation for aesthetic purposes more importantly. Lastly, the will to escape was shown as the influential factor in visitor satisfaction. Visiting open spaces for the enjoyment of nature and aesthetic purposes were factors that also closely relate to visitor satisfaction. In addition, it was found that there are different visitor motivations that influence visitor satisfaction in accordance with the spatial characteristics of each open space. In summary, it can be said that urban waterfront open space is a hybrid space connected to various types of urban contents beyond daily experiences. It was found that several visitor motivations including community development, design aesthetics, education and culture, entertainment, enjoyment of natural landscape, and relaxation, affect the overall satisfaction of the visiting experience. It is anticipated that the results of the study will be used by the local government in setting up strategies for the creation and management of successful urban waterfront open space, and for those involved in planning and design act as a starting point for spatial programming and amenities arrangement in accordance to the city's tourism and urban marketing approach.

• Neonatal Medicine
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• v.18 no.1
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• pp.49-58
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• 2011

Purpose: The purpose of this study was to evaluate the relationship between cord blood adiponectin and insulin-like growth factor (IGF)-I and their effect on fetal growth and insulin resistance in mothers with gestational diabetes mellitus (GDM). Methods: Cord blood adiponectin and IGF-I were compared between mothers with GDM (GDM group, N=53) and controls (non-GDM group, N=101). Neonates were classified into three groups of small for gestational age (SGA, N=26), appropriate for gestational age (AGA, N=97), and large for gestational age (LGA, N=31) by birth weight. The association between cord adiponectin and IGF-I levels was evaluated in relation to maternal and neonatal clinical data. Results: Cord adiponectin was lower in the GDM group than in the non-GDM group (P<0.001). There was no significant difference in cord adiponectin among the SGA, AGA, and LGA groups in the GDM group (P=0.228). The cord adiponectin of AGA in the GDM group was significantly lower than that in the non-GDM group (P<0.001). The most powerful predictor affecting cord adiponectin was the result of maternal 75 g oral glucose tolerance test. The cord IGF-I values between the GDM group and the non-GDM group were not different (P=0.834). Neonates with the heavier birth weight had the higher cord IGF-I levels. The most powerful predictor affecting cord IGF-I was birth weight and the next was maternal parity. Conclusion: Both cord blood adiponectin and IGF-I were associated with fetal growth, but IGF-I was a more general and direct factor affecting fetal body size, and adiponectin seemed to have more association with insulin sensitivity than growth.

• Journal of agricultural medicine and community health
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• v.30 no.1
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• pp.89-100
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• 2005

Objectives: This study was to find the effected factors on customer satisfaction for medical service and the willingness to revisit among hospital users Methods: The data was collected by a questionnaire survey from February 1 to April 30, 2004, and 600 samples have been analysed among users of university hospital, private hospital and public hospital in a local city. Results and Conclusions: The satisfaction total score to use hospital was 113.54 points(out of 175 point), these scores were constituted 39.10 points(out of 55 point) on satisfaction score for kindness of hospital employee, 36.28 points(out of 60 point) for equipment utilization and service formality, 18.59 points(out of 30 point) for environmental status and 19.57 points(out of 30 points) for reliability in medical examination and treatment service. The factors effected on satisfaction total score to use hospital were type of visiting hospital, age of customer, convenience to visit the hospital, experience of using other hospitals(R2=0.171). The effected factors of willingness to revisit scores were such as satisfaction score in medical examination and treatment service, satisfaction score of kindness hospital employee, experience of health examination and age of customer($R^2=0.370$). In conclusion, to raise the response's willingness to revisit. This must be reinforced by employee's kindness education and medical service quality.

• Korean Journal of Psychosomatic Medicine
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• v.19 no.2
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• pp.83-91
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• 2011

Objectives: Posttraumatic stress disorder(PTSD) has devastating effects on multiple aspects of the quality of life(QoL). Therefore, the purpose of this study is to compare the QoL between PTSD group and non-PTSD group, and identify the variables affecting the QoL of the Vietnam War veterans. Methods: We recruited 39 veterans with PTSD and 43 veterans without PTSD, all of whom had deployed to the Vietnam War. We used the Korean version of Mini International Neuropsychiatric Interview-Plus, the Korean version of Clinician-Administered PTSD Scale, Combat Exposure Scale and the Korean version of World Health Organization Quality of Life Assessment Instrument abbreviated version. We used independent samples t-test to identify the differences between PTSD and non-PTSD group in each domains of the quality of life. We also used stepwise multiple linear regression analysis to figure out the variables affecting the QoL of the Vietnam War veterans. Results: In the PTSD group, all domains of the QoL and the QoL total score(p<0.01) were significantly lower than those in the non-PTSD group. In the Vietnam War veterans, PTSD, major depressive disorder and education levels were the variables affecting the QoL. Among these, PTSD uniquely explained the QoL of the overall and general health(${\beta}$=-1.411, $R^2$=0.180), the physical health domain(${\beta}$=-2.806, $R^2$=0.089) and the total score (${\beta}$=-11.479, $R^2$=0.104). Conclusions: These results suggest that among the Vietnam War veterans, the QoL of the PTSD group is significantly lower than that of the non-PTSD group. Among the combat exposed veterans, PTSD may be one of the main reasons that affect the multiple domains of the QoL.

• Economic and Environmental Geology
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• v.48 no.4
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• pp.337-349
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• 2015

This study has focused on investigation of correlation for As and heavy metals in paddy soil and rice crops sampled in the vicinity of the abandoned Munmyung Au-Ag mine. Soil samples extracted by various methods including aqua regia, 1 M $MgCl_2$, 0.01 M $CaCl_2$ and 0.05 M EDTA were analyzed for As and heavy metals (Cd, Cu, Pb and Zn). Rice grain samples grown on the soils were also analyzed for the same elements to evaluate the relationships between soils and rice crops. According to soil extraction methods, As and heavy metal contents in the soils were decreased in the order of aqua regia > 0.01 M $CaCl_2$ > 1 M $MgCl_2$ > 0.05 M EDTA. In addition to correlation analysis, statistically significant correlation with the four extraction methods (p<0.01) were found in the soil and rice samples. As calculation of biological accumulation coefficients (BACs) of the rice crops for As and heavy metals, the BACs for Cd, Zn and Cu were relatively higher than those for As and Pb. This study also carried out a stepwise multiple linear regression analysis to identify the dominant factors influencing metal extraction rates of the paddy soils. Furthermore, daily intakes of As and heavy metals from regularly consumed the rice grain (287 g/day) grown on the contaminated soils by the mining activities were estimated, and found that Cd and As intakes from the rice reached up to 73.7% and 51.8% for maximum allowance levels of trace elements suggested by WHO, respectively. Therefore, long-term consumption of the rice poses potential health problems to residents around the mine, although no adverse health effects have yet been observed.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.451-463
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• 2018

The empirical/statistical models to estimate the ground Particulate Matter ($PM_{2.5}$) concentration from Geostationary Ocean Color Imager (GOCI) Aerosol Optical Depth (AOD) product were developed and analyzed for the period of 2015 in Seoul, South Korea. In the model construction of AOD-$PM_{2.5}$, two vertical correction methods using the planetary boundary layer height and the vertical ratio of aerosol, and humidity correction method using the hygroscopic growth factor were applied to respective models. The vertical correction for AOD and humidity correction for $PM_{2.5}$ concentration played an important role in improving accuracy of overall estimation. The multiple linear regression (MLR) models with additional meteorological factors (wind speed, visibility, and air temperature) affecting AOD and $PM_{2.5}$ relationships were constructed for the whole year and each season. As a result, determination coefficients of MLR models were significantly increased, compared to those of empirical models. In this study, we analyzed the seasonal, monthly and diurnal characteristics of AOD-$PM_{2.5}$model. when the MLR model is seasonally constructed, underestimation tendency in high $PM_{2.5}$ cases for the whole year were improved. The monthly and diurnal patterns of observed $PM_{2.5}$ and estimated $PM_{2.5}$ were similar. The results of this study, which estimates surface $PM_{2.5}$ concentration using geostationary satellite AOD, are expected to be applicable to the future GK-2A and GK-2B.

• Sleep Medicine and Psychophysiology
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• v.21 no.1
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• pp.5-13
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• 2014

Objectives: Depression, sleep complaints and cognitive impairments are commonly observed in the elderly. Elderly subjects with depressive symptoms have been found to show both poor cognitive performances and sleep disturbances. However, the relationship between sleep complaints and cognitive dysfunction in elderly depression is not clear. The aim of this study is to identify the association between sleep disturbances and cognitive decline in late-life depression. Methods: A total of 282 elderly people who underwent nocturnal polysomnography in a sleep laboratory were enrolled in the study. The Korean version of the Neuropsychological Assessment Battery developed by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD-K) was applied to evaluate cognitive function. Depressive symptoms were assessed with the geriatric depression scale (GDS) and subjective sleep quality was measured using the Pittsburg sleep quality index (PSQI). Results: The control group ($GDS{\leq}9$) when compared with mild ($10{\leq}GDS{\leq}16$) and severe ($17{\leq}GDS$) depression groups, had significantly different scores in the Trail making test part B (TMT-B), Benton visual retention test part A (BVRT-A), and Stroop color and word test (SCWT)(all tests p<0.05). The PSQI score, REM sleep duration, apnea-hypopnea index and oxygen desaturation index were significantly different across the three groups (all indices, p<0.05). A stepwise multiple regression model showed that educational level, age and GDS score were predictive for both TMT-B time (adjusted $R^2$=35.6%, p<0.001) and BVRT-A score (adjusted $R^2$=28.3%, p<0.001). SCWT score was predicted by educational level, age, apnea-hypopnea index (AHI) and GDS score (adjusted $R^2$=20.6%, p<0.001). Poor sleep quality and sleep structure alterations observed in depression did not have any significant effects on cognitive deterioration. Conclusion: Older adults with depressive symptoms showed mild sleep alterations and poor cognitive performances. However, we found no association between sleep disturbances (except sleep apnea) and cognitive difficulties in elderly subjects with depressive symptoms. It is possible that the impact of sleep disruptions on cognitive abilities was hindered by the confounding effect of age, education and depressive symptoms.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.17-26
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• 2012

Purpose: This study mainly focuses on the patients treated with chemically stable radiopharmaceutical product $^{99m}Tc$-HMPAO (d,l-hexamethylpropylene amine oxime) which yielded reduced image quality due to a decreased brain extraction rate. $^{99m}Tc$-HMPAO will be examined further to determine whether this product may be accounted as a factor for this cause. Material and Methods: From January 2010 until December 2010, out of 272 patients who were all subjected to $^{99m}Tc$-HMPAO brain blood flow SPECT scans resulting from Cerebral Infarction; 23 patients(ages $55.3{\pm}9$, 21 males, 3 females) with decreased tissue extraction rate were examined in detail. The radiopharmaceutical product $^{99m}Tc$-HMPAO was used on patients with normal brain tissue exchange rate as well as those with reduced rate in order to prove its' chemical stability. The patients' age, sex, blood pressure, existence of diabetes, drug use, current health status, known side effects from CT/MRI, examination of the patients' past SPECT before/after images were accounted to determine the factors and correlations affecting the rate of blood tissue extractions. Result: After multiple linear regression analysis, there were no unusual correlations between the 6 factors excluding sex, and before/after examination images. Male subjects showed reduced brain tissue extraction rate than the females ($p$ > 0.05) 91.3% male, 8.7% female. Wilcoxon Matched-Pairs Signed-Ranks Test was used on the before/after images which yielded a value of 0.06, which did not indicate a significant amount of difference on the 2 tests ($p$ > 0.05). As a result, the before/after images indicated similar brain tissue extraction rates, and there were variations depending on the individual patient. Conclusion: The effects of the chemically stable radiopharmaceutical product $^{99m}Tc$-HMPAO depended on the patient's personal characteristics and status, therefore was considered to be a factor in reducing brain tissue extraction rate. The related articles of $^{99m}Tc$-HMPAO cerebral blood flow SPECT speculates a cerebrovascular disease and factors resulting from portal veins, and it was not possible to pin point the exact cause of decreasing brain tissue extraction rate. However, the $^{99m}Tc$-HMPAO cerebral blood flow SPECT scan proved to be extremely useful in tracking and inspecting brain diseases, as well as offering accurate results from patients suffering from reduced brain tissue extraction rates.