• Horticultural Science & Technology
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• v.31 no.5
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• pp.531-537
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• 2013

The average annual and winter ambient air temperatures in Korea have risen by 0.7 and $1.4^{\circ}C$, respectively, during the last 30 years. Radish (Raphanus sativus), one of the most important cool season crops, may well be used as a model to study the influence of climatic change on plant growth, because it is more adversely affected by elevated temperatures than warm season crops. This study examined the influence of transplanting time, nitrogen fertilizer level, and climate parameters, including air temperature and growing degree days (GDD), on the performance of a radish cultivar 'Mansahyungtong' to estimate crop growth during the spring growing season. The radish seeds were sown from April 24 to May 22, 2012, at internals of 14 days and cultivated with 3 levels of nitrogen fertilization. The data from plants sown on April 24 and May 8, 2012 were used for the prediction of plant growth as affected by planting date and nitrogen fertilization for spring production. In our study, plant fresh weight was higher when the radish seeds were sown on $24^{th}$ of April than on $8^{th}$ and $22^{nd}$ of May. The growth model was described as a logarithmic function using GDD according to the nitrogen fertilization levels: for 0.5N, root dry matter = 84.66/(1+exp (-(GDD - 790.7)/122.3)) ($r^2$ = 0.92), for 1.0N, root dry matter = 100.6/(1 + exp (-(GDD - 824.8)/112.8)) ($r^2$ = 0.92), and for 2.0N, root dry matter = 117.7/(1+exp (-(GDD - 877.7)/148.5)) ($r^2$ = 0.94). Although the model slightly tended to overestimate the dry mass per plant, the estimated and observed root dry matter and top dry matter data showed a reasonable good fit with 1.12 ($R^2$ = 0.979) and 1.05 ($R^2$ = 0.991), respectively. Results of this study suggest that the GDD values can be used as a good indicator in predicting the root growth of radish.

• Applied Chemistry for Engineering
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• v.19 no.3
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• pp.299-303
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• 2008

A thermally cross-linkable polymer, poly[(2,5-dimethoxy-1,4-phenylenevinylene)-alt-(1,4-phenylenevinylene)] (Cross-PPV), was synthesized by the Heck coupling reaction. In order for the polymer to be cross-linkable, 20 mol% excess divinylbenzene was added. The chemical structure of Cross-PPV and thermally crosslinked Cross-PPV were confirmed by FT-IR spectroscopy. From the FT-IR, UV-Vis, and PL spectral data, thermally crosslinked Cross-PPV was insoluble in common organic solvents. The HOMO and LUMO energy level of thermally cross-linked Cross-PPV were estimated -5.11 and -2.56 eV, respectively, which were determined by the cyclic voltammetry and UV-Vis spectroscopy. From the energy level data, one can easily notice that thermally crosslinked Cross-PPV can be used for hole injection layer effectively. Bilayer structured device (ITO/crosslinked Cross-PPV/PM-PPV/Al) was fabricated using poly(1,4-phenylenevinylene-(4-dicyanomethylene-4H-pyran)-2,6-vinylene-1,4-phenylenevinylene-2,5-bis(dodecyloxy)-1,4-phenylenevinylene (PM-PPV) as the emitting layer, which have HOMO and LUMO energy levels of -5.44 eV and -3.48 eV, respectively. The bilayered device had much enhanced the maximum efficiency (0.024 cd/A) and luminescence ($45cd/m^2$) than those of a single layer device (ITO/PM-PPV/Al, 0.003 cd/A, $3cd/m^2$). The enhanced performance originated from that fact that cross-linked Cross-PPV facilitatse the hole injection to the emissive layer and the injected hole and electron from ITO and Al are recombined in emitting layer (PM-PPV) effectively.

• Korean Journal of Ecology and Environment
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• v.42 no.2
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• pp.200-211
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• 2009

A mathematical modeling program called Soil and Water Assessment Tool (SWAT) developed by USDA was applied to Kyongan stream watershed. It was run under BASINS (Better Assessment Science for Integrating point and Non-point Sources) program, and the model was calibrated and validated using KTMDL monitoring data of 2004${\sim}$2008. The model efficiency of flow ranged from very good to fair in comparison between simulated and observed data and it was good in the water quality parameters like flow range. The model reliability and performance were within the expectation considering complexity of the watershed and pollutant sources. The results of pollutant loads estimation as yearly (2004${\sim}$2008), pollutant loadings from 2006 were higher than rest of year caused by high precipitation and flow. Average non-point source (NPS) pollution rates were 30.4%, 45.3%, 28.1% for SS, TN and TP respectably. The NPS pollutant loading for SS, TN and TP during the monsoon rainy season (June to September) was about 61.8${\sim}$88.7% of total NPS pollutant loading, and flow volume was also in a similar range. SS concentration depended on precipitation and pollution loading patterns, but TN and TP concentration was not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. SWAT based on BASINS was applied to the Kyongan stream watershed successfully without difficulty, and it was found that the model could be used conveniently to assess watershed characteristics and to estimate pollutant loading including point and non-point sources in watershed scale.

• 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 the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.628-634
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• 2016

Many pitchers suffer from various types of injury (distortion, sprain and so on). The rate of injury is increased if there are differences in strength between the extensor and flexor muscles when a joint movement is performed with maximum speed. However, there has been insufficient research into the injury caused by strength differences between the extensor and flexor muscles. Thus, the purpose of the study was to examine the effects of elbow ulnar collateral ligament injury on the maximal isometric strength in young baseball pitchers. The data collection was conducted for 2 weeks. The subjects (n=36) who participated in this study were placed into either the injury group (n = 18, IG) or normal group (n = 18, NG). The maximal isometric strength for the pectoralis major (PM), infraspintus (I), biceps brachii (BB), triceps brachii (TB), flexor carpi radialis (ECR) and extensor carpi radialis (FCR) muscles were determined by an isometric strength machine (K-DFX) and then the differences in strength were calculated by muscle group. All of the data were analyzed by SPSS 18.0 with the independent t-test. In the results, the maximal isometric strengths in the IG for the I (p=0.035), BB (p=0.031) and TB (p=0.041) were significantly lower than those in the NG, while that for the ECR (p=0.047) was significantly greater. In addition, the differences of the maximal isometric strength between the PM and I (p = 0.008), BB and TB (p = 0.002), and FCR and ECR (p = 0.032) in the IG were significantly greater than those in the NG. In conclusion, the differences in muscle strengths of the subjects in the IG were greater than those in the NG, which suggests that they might have a higher injury rate in the future. However, they might be able to recover from their injury and achieve better performance if the differences in strength were reduced by training.

• Anatomy & Biological Anthropology
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• v.29 no.4
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• pp.145-154
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• 2016

The purpose of this study was to provide basic biometric data on Korean adults through magnetic resonance imaging (MRI)-based measurements of the distances between the apex of sacral hiatus (SH) and the termination of dural sac (DS), and between SH and conus medullaris (CM) because they are critical to the performance of epidural neuroplasty. A total of 200 patients(88 males and 112 females) with back pain, who had no spine fracture, significant spinal deformity, and spondyloisthesis were selected for this study. The subjects were of mean age 54.3 (20~84) years and mean height 161.3 cm (135~187). T2-weighted MRI images were used for correlation analysis to evaluate the relationships between the distances, and variables such as sex and height. In all patients, the mean distance between SH and DS was $62.8{\pm}9.4mm$ and the mean distance between SH and CM was $232.2{\pm}21.8mm$. The minimum distance and the maximum distance between SH and DS were 34.8 mm and 93.9 mm respectively, and the minimum distance and the maximum distance between SH and CM were 155.0 mm and 284.0 mm respectively. In female patients, both the distances between the SH and DS, and between SH and CM were shorter when compared to those of the male patients(p<0.05). Both the distances between SH and DS and between SH and CM showed a significant correlation with height(p<0.01). The results of this study will provide a useful biometric data on the distances between SH and DS and between SH and CM in Korean in ensuring clinical safety and in the development of more effective catheterization techniques for epidural neuroplasty in Korean.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.83-98
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• 2021

Urban green space is an important component for enhancing urban ecosystem health. Thus, identifying the spatial structure of urban green space is required to manage a healthy urban ecosystem. The Ministry of Environment has provided the level 3 land cover map(the highest (1m) spatial resolution map) with a total of 41 classes since 2010. However, specific urban green information such as street trees was identified just as grassland or even not classified them as a vegetated area in the map. Therefore, this study classified detailed urban green information(i.e., tree, shrub, and grass), not included in the existing level 3 land cover map, using two types of high-resolution(<1m) remote sensing data(i.e., airborne LiDAR and RGB ortho imagery) in Suwon, South Korea. U-Net, one of image segmentation deep learning approaches, was adopted to classify detailed urban green space. A total of three classification models(i.e., LRGB10, LRGB5, and RGB5) were proposed depending on the target number of classes and the types of input data. The average overall accuracies for test sites were 83.40% (LRGB10), 89.44%(LRGB5), and 74.76%(RGB5). Among three models, LRGB5, which uses both airborne LiDAR and RGB ortho imagery with 5 target classes(i.e., tree, shrub, grass, building, and the others), resulted in the best performance. The area ratio of total urban green space(based on trees, shrub, and grass information) for the entire Suwon was 45.61%(LRGB10), 43.47%(LRGB5), and 44.22%(RGB5). All models were able to provide additional 13.40% of urban tree information on average when compared to the existing level 3 land cover map. Moreover, these urban green classification results are expected to be utilized in various urban green studies or decision making processes, as it provides detailed information on urban green space.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.337-357
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• 2021

Because the growth of paddy rice is affected by meteorological factors, the selection of appropriate meteorological variables is essential to build a rice yield prediction model. This paper examines the suitability of multiple meteorological datasets for the rice yield modeling in South Korea, 1996-2019, and a hindcast experiment for rice yield using a machine learning method by considering the nonlinear relationships between meteorological variables and the rice yield. In addition to the ASOS in-situ observations, we used CRU-JRA ver. 2.1 and ERA5 reanalysis. From the multiple meteorological datasets, we extracted the four common variables (air temperature, relative humidity, solar radiation, and precipitation) and analyzed the characteristics of each data and the associations with rice yields. CRU-JRA ver. 2.1 showed an overall agreement with the other datasets. While relative humidity had a rare relationship with rice yields, solar radiation showed a somewhat high correlation with rice yields. Using the air temperature, solar radiation, and precipitation of July, August, and September, we built a random forest model for the hindcast experiments of rice yields. The model with CRU-JRA ver. 2.1 showed the best performance with a correlation coefficient of 0.772. The solar radiation in the prediction model had the most significant importance among the variables, which is in accordance with the generic agricultural knowledge. This paper has an implication for selecting from multiple meteorological datasets for rice yield modeling.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.275-290
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• 2021

Sulfur dioxide (SO2) in the atmosphere is mainly generated from anthropogenic emission sources. It forms ultra-fine particulate matter through chemical reaction and has harmful effect on both the environment and human health. In particular, ground-level SO2 concentrations are closely related to human activities. Satellite observations such as TROPOMI (TROPOspheric Monitoring Instrument)-derived column density data can provide spatially continuous monitoring of ground-level SO2 concentrations. This study aims to propose a 2-step residual corrected model to estimate ground-level SO2 concentrations through the synergistic use of satellite data and numerical model output. Random forest machine learning was adopted in the 2-step residual corrected model. The proposed model was evaluated through three cross-validations (i.e., random, spatial and temporal). The results showed that the model produced slopes of 1.14-1.25, R values of 0.55-0.65, and relative root-mean-square-error of 58-63%, which were improved by 10% for slopes and 3% for R and rRMSE when compared to the model without residual correction. The model performance by country was slightly reduced in Japan, often resulting in overestimation, where the sample size was small, and the concentration level was relatively low. The spatial and temporal distributions of SO2 produced by the model agreed with those of the in-situ measurements, especially over Yangtze River Delta in China and Seoul Metropolitan Area in South Korea, which are highly dependent on the characteristics of anthropogenic emission sources. The model proposed in this study can be used for long-term monitoring of ground-level SO2 concentrations on both the spatial and temporal domains.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.