This study was conducted to determine the effects of horticultural therapy (HT) program using hydroponics on work adjustment skills of students with mental retardation. Based on the critical role transitional model and special education curriculum for agriculture, especially hydroponics, HT program (total 22 sessions) using hydroponics procedure for Lettuce (Lactuca sativa L. 'Asia Heuk Romaine') was developed. Fourteen (10 males, 4 females) graded $1^{st}$ to $2^{nd}$ with intellectual disabilities were recruited from a special education class in a high school located in Inchon, Korea and then a special farm for hydroponics in Inchon, Korea was offered for the HT program. The students with intellectual disabilities participated in the HT program for 4-month (from September to December of 2011, twice a week, approximately 60 minutes per session). Before and after the HT program, the McCarron assessment neuromuscular development, emotional behavioral checklist, interpersonal negotiation strategies, and KEPAD picture vocational interest test were performed by the teachers and horticultural therapists. As the results, the students significantly improved motor performance (p = 0.002), emotional behavioral strategies (p = 0.00), and interpersonal negotiation strategies (p = 0.05). However, no significant difference between before and after the HT program for vocational interest was observed. In conclusion, the HT program using hydroponics, consists of simple and easy tasks so that it would be applicable for the students with intellectual disabilities positively affected to work adjustment skills by improving the motor performance, emotional behavioral strategies, and interpersonal negotiation strategies. Additionally, HT programs using hydroponics with various kinds of vegetables are required to develop and to apply in practical settings for improving work adjustment skills.
Journal of the Korean Institute of Landscape Architecture
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v.38
no.4
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pp.25-34
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2010
This study was conducted to develop evaluation indicators to improve athletic performance and operational management of golf courses and the results of the research are as follows. Through theoretical research and a preliminary professional survey, 15 on-going evaluations of golf course composition and operational management and 55 sub-evaluation indices were rejected while 10 on-going evaluations and 52 sub-evaluation indicators were reconfigured as final for environmental-friendliness, level of member services, level of human service of game personnel, difficulties of course, management level of the course, fairness of operational management, accessibility and location characteristic, traditions and ambiance of the golf club, quality of course, and course layout. When analyzing the important decision factors in golf course user preference evaluation indicators, the following contributed in the order of higher to lower contributions: the management level of the course, excellence of the course, level of human services for personnel, course layout and environmental-friendliness. When identifying the path coefficient of golf course evaluation indicators, the curvature of a hole and the length of the course had a causal effect on the 'course layout' section. Tournament facilities and various shot values had a causal relationship with 'excellence of the course', in the order of higher to lower, and convenience of waiting and fair allocation of reservations for 'fairness of operational management'. The history of the golf course and its environmental characteristics, history and culture of the region have relatively higher causal effects on 'traditions of the golf club' and geographical conditions on 'accessibility and location characteristics', pesticide and fertilizer usage and water pollution on 'environmental-friendliness', and member benefit and kindness of employees on 'level of member services'. The kindness and expertise of the game personnel had a relatively higher causal effect on the 'level of human services of game personnel', the location of tenning area, and location of OB and hazards on 'difficulties of course', and rough conditions and obstacles management on 'management level of the course'. There is a need to complete a systematic evaluation index system for golf course user preferences through future studies for a more detailed assessment, as well as a process to verify these evaluation indicators by application to domestic and international golf courses.
Kim, Young-Soon;Lee, Chang-Geol;Lee, Kyoung-Ok;Kim, Ok-Kyum;Kim, In-Hye;Kim, Mi-Jeong;Hwang, Ae-Ran;Lee, Won-Hee
Journal of Hospice and Palliative Care
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v.7
no.2
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pp.200-213
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2004
Purpose: The purpose of this study was to create an electronic nursing record form to build a hospice nursing process database to be used in the u-hospital EMR system. Specific aims of the study were: 1. To generate a complete, accurate, and simple electronic nursing record form. 2. To verify its appropriateness following documentation with the standardized hospice protocol. 3. To verify its validity and finalize the hospice nursing process database through discussion among hospice professionals. Methods: Nursing records from three independent hospice organizations were collected and analyzed by five expert hospice nurses with more than 10 years of experience, and a nursing record database was developed. This database was applied to 81 hospice patients at three hospice organizations to verify its completeness. Results: 1. An electronic nursing record form with completeness, accuracy, and simplicity was developed. 2. The completeness of the standardized home hospice service protocol was 95.86 percent. 3. The hospice nursing process database contains 18 items on health problems, 79 items on related causes and major symptoms, and 229 items on nursing interventions. Conclusion: The new nursing record form and database will reduce documentation time and articulate and streamline the working process among team members. They can also improve the quality of hospice services, and ultimately enable us to estimate hospice service costs.
Looking into the top-five innovative sectors in Korea's manufacturing and service industries, this study empirically analyzes the effect of innovation performance on R&D investment, which is one of the most important strategic decisions for corporate management. In the midst of an uncertain business environment, R&D investment has been regarded as the most important strategic decision making in corporate management related to innovation. Corporate management, however, tend to be reluctant to make sufficient R&D investment due to the risk of an investment failure. Therefore, having R&D investment by offsetting this risk has been deemed as a key task for corporate management. However, prior studies have failed to identify which factors affect companies' strategic decision making on R&D investment. This study is to remedy this weakness of prior study. Relying on path dependency theory at organization-level and dominant logic at individual-level, this study empirically examines the multiple regression model, which sees entrepreneurial orientation as a positive mediator between innovation performance and R&D investment. The results found in the analysis of 242 local companies in the manufacturing and service sectors represent that innovation performance has a direct and positive effect on R&D investment, while it indirectly affects R&D investment through the mediating roles of entrepreneurial orientation. They also revealed that innovation performance had a meaningful impact on entrepreneurial orientation, which is an inclination to seek innovation, led to R&D investment. The founding of this study imply that innovation performance in the past affects innovation strategies in the future, and such a relationship could be strengthened by entrepreneurial orientation as the dominant logic of corporate management.
Park, Ji Hye;Yun, Jisoo;Heo, Jeong;Hwang, Tae Ho;Kwon, Sang Mo
Journal of Life Science
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v.26
no.7
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pp.835-846
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2016
Chemo-resistance is the biggest issue of effective cancer therapy. ABCG2 is highly correlated with multi-drug resistance, and represent a typical phenotype of multiple cancer stem-like cells. Accumulating evidence recently reported that oncolytic viruses represent a new strategy for multiple aggressive cancers and drug resistant cancers including cancer stem cell-like cells and ABCG2 expressing cells. In this study, we generated an evolutionally engineered vaccinia virus, SLJ-496, for drug-resistant cancer therapy. We first showed that SLJ-496 treatment enhanced tumor affinity using cytopathic effect assay, plaque assay, as well as cell viability assay. Next, we clearly demonstrated that in vitro SLJ-496 treatment represents significant cytotoxic effect in multiple cancers including colorectal cancer cells (HT-29, HCT-116, HCT-8), gastric cancer cells (AGS, NCI-N87, MKN-28), Hepatocellular carcinoma cells (SNU-449, SNU-423, SNU-475, HepG2), as well as mesothelioma cell (NCI-H226, NCI-H28, MSTO-221h). Highly ABCG2 expressing HT-29 cells represent cancer stem like phenotype including stem cell marker expression, and self-renewal bioactivities. Interestingly, we demonstrated that in vitro treatment of SLJ-496 showed significant cytotoxicity effect, as well as viral replication capacity in ABCG2 overexpressing cell. In addition, we also demonstrated the cytotoxic effect of SLJ-496 in Adriamycin-resistant cell lines, SNU-620 and ADR-300. Taken together, these findings provide us a pivotal clue that cancer therapy using SLJ-496 vaccinia virus might be new therapeutic strategy to overcome ABCG2 expressing cancer stem-like cell and multiple chemo-resistance cancer cells.
Purpose: Vitamin D has been known to play an important role in the central nervous system and brain functions in the human body, and cumulative evidence has shown that vitamin D deficiency might be linked with various mental health conditions. Epidemiologic studies have shown that vitamin D deficiency may be associated with higher risk of depression in the US and European populations. However, limited information is available regarding the association between vitamin D status and depression in the Korean population. The objective of this study was to examine the associations between vitamin D levels and prevalence of depression. Methods: We conducted a cross-sectional analysis using nationally representative data from the 2008-2010 Korean National Health and Nutrition Examination Survey from which serum 25-hydroxyvitamin D concentrations were available. A total of 18,735 adults who had available demographic, dietary, and lifestyle information were included in our analysis. We defined "depression" with a diagnosis by a physician. "Depressed condition" was defined as having feelings of sadness or depression without diagnosis by a physician. Results: The prevalence of depression was 1.63% and 5.43% in Korean men and women, respectively; 12.5% of men and 26.1% of women were defined as the group having depressed conditions. In multivariate logistic regression models, no significant associations were observed between vitamin D status and prevalence of depression or depressed conditions in Korean men and women. Conclusion: We found no association between vitamin D insufficiency and depression/depressed conditions in Korean adults. Future large prospective studies and randomized controlled trials are needed to confirm this relationship.
Korean Journal of Agricultural and Forest Meteorology
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v.24
no.1
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pp.13-34
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2022
Soil moisture data have been collected at 11 agrometeorological stations operated by The Korea Meteorological Administration (KMA). This study aimed to verify the accuracy of soil moisture data of KMA and develop a correction formula to be applied to improve their quality. The soil of the observation field was sampled to analyze its physical properties that affect soil water content. Soil texture was classified to be sandy loam and loamy sand at most sites. The bulk density of the soil samples was about 1.5 g/cm3 on average. The content of silt and clay was also closely related to bulk density and water holding capacity. The EnviroSCAN model, which was used as a reference sensor, was calibrated using the self-manufactured "reference soil moisture observation system". Comparison between the calibrated reference sensor and the field sensor of KMA was conducted at least three times at each of the 11 sites. Overall, the trend of fluctuations over time in the measured values of the two sensors appeared similar. Still, there were sites where the latter had relatively lower soil moisture values than the former. A linear correction formula was derived for each site and depth using the range and average of the observed data for the given period. This correction formula resulted in an improvement in agreement between sensor values at the Suwon site. In addition, the detailed approach was developed to estimate the correction value for the period in which a correction formula was not calculated. In summary, the correction of soil moisture data at a regular time interval, e.g., twice a year, would be recommended for all observation sites to improve the quality of soil moisture observation data.
In this study, the sensitivity of the mid-infrared radiance to atmospheric and surface factors was analyzed using the radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN6)'s simulation data. The possibility of retrieving the land surface temperature (LST) using only the mid-infrared bands at night was evaluated. Based on the sensitivity results, the LST retrieval algorithm that reflects various factors for night was developed, and the level of the LST retrieval algorithm was evaluated using reference LST and observed LST. Sensitivity experiments were conducted on the atmospheric profiles, carbon dioxide, ozone, diurnal variation of LST, land surface emissivity (LSE), and satellite viewing zenith angle (VZA), which mainly affect satellite remote sensing. To evaluate the possibility of using split-window method, the mid-infrared wavelength was divided into two bands based on the transmissivity. Regardless of the band, the top of atmosphere (TOA) temperature is most affected by atmospheric profile, and is affected in order of LSE, diurnal variation of LST, and satellite VZA. In all experiments, band 1, which corresponds to the atmospheric window, has lower sensitivity, whereas band 2, which includes ozone and water vapor absorption, has higher sensitivity. The evaluation results for the LST retrieval algorithm using prescribed LST showed that the correlation coefficient (CC), the bias and the root mean squared error (RMSE) is 0.999, 0.023K and 0.437K, respectively. Also, the validation with 26 in-situ observation data in 2021 showed that the CC, bias and RMSE is 0.993, 1.875K and 2.079K, respectively. The results of this study suggest that the LST can be retrieved using different characteristics of the two bands of mid-infrared to the atmospheric and surface conditions at night. Therefore, it is necessary to retrieve the LST using satellite data equipped with sensors in the mid-infrared bands.
In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.
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.
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