Park, Min Ji;Shin, Hyung Jin;Park, Geun Ae;Kim, Seong Joon
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.4B
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pp.337-346
/
2010
Climate change has a huge impact on various parts of the world. This study quantified and analyzed the effects on hydrological behavior caused by climate, vegetation canopy and land use change of Soyanggang dam watershed (2,694.4 $km^2$) using the semi-distributed model SWAT (Soil Water Assessment Tool). For the 1997-2006 daily dam inflow data, the model was calibrated with the Nash-Sutcliffe model efficiencies between the range of 0.45 and 0.91. For the future climate change projection, three GCMs of MIROC3.2hires, ECHAM5-OM, and HadCM3 were used. The A2, A1B and B1 emission scenarios of IPCC (Intergovernmental Panel on Climate Change) were adopted. The data was corrected for each bias and downscaled by Change Factor (CF) method using 30 years (1977-2006, baseline period) weather data and 20C3M (20th Century Climate Coupled Model). Three periods of data; 2010-2039 (2020s), 2040-2069 (2050s), 2070-2099 (2080s) were prepared for future evaluation. The future annual temperature and precipitation were predicted to change from +2.0 to $+6.3^{\circ}C$ and from -20.4 to 32.3% respectively. Seasonal temperature change increased in all scenarios except for winter period of HadCM3. The precipitation of winter and spring increased while it decreased for summer and fall for all GCMs. Future land use and vegetation canopy condition were predicted by CA-Markov technique and MODIS LAI versus temperature regression respectively. The future hydrological evaluation showed that the annual evapotranspiration increases up to 30.1%, and the groundwater recharge and soil moisture decreases up to 55.4% and 32.4% respectively compared to 2000 condition. Dam inflow was predicted to change from -38.6 to 29.5%. For all scenarios, the fall dam inflow, soil moisture and groundwater recharge were predicted to decrease. The seasonal vapotranspiration was predicted to increase up to 64.2% for all seasons except for HadCM3 winter.
This study examined the chemical composition of lotus root and functionally evaluated a fermented lotus root drink. Electron-donating ability using DPPH along with nitrite-scavenging ability were used to compare the antioxidative activities of unfermented and fermented lotus root drinks. The electron-donating abilities of the unfermented lotus root drink (1%) and fermented lotusroot drink (1%) were 22.55% and 23.88%, respectively. At pH 6.0, the nitrite-scavenging abilities of the unfermented lotus root drink and the fermented lotus root drink (100%) were 27.64% and 40.3%, respectively, and their scavenging ability increased in a dose-dependent manner at all pH values. In order to study the anti-obesity effects of the two drinks, male Sprague-Dawley rats were divided into four groups (A: basal diet, B: high fat diet, C: high fat diet+unfermented lotus root drink, D: high fat diet+fermented lotus root drink). Net weight gains were not significantly different among the four groups. Plasma total cholesterol concentrations significantly decreased in the groups receiving the unfermented and fermented lotus root drinks. Also, plasma total lipid and triglyceride contents were lower in the groups receiving the unfermented and fermented lotus root drinks as compared to the high fat diet group; however, the differences among the three groups were not significant.
The purpose of this research is to analyze the overall problems at the moment of October 2008, and then to find the improvements of home-help services of the Long-Term Care Insurance(LTCI), which has been revealed many problems since it was released in July 2008. The research uses the literature survey which analyzes 2nd-hand materials studied by other people already, and survey research was executed from active social workers in the area of LTCI. Based on the policy analysis framework of Gilbert and Specht, all the data are analyzed in the scopes of client·benefit(service)·finance·transferring system. This research has found the problems in each scope of home-help services of the LTCI. Firstly, the client system has some problems in mismatching between registered and service clients, estimating client number, and judging service levels. Secondly, the service system reveals deficiency in professionality of social workers, service quality lowering by loose qualification criteria on workers, non-reasonable limitation of service time available, and the same fare system applied to visiting-help service in spite of different levels. Thirdly, in financing system, clients need to pay additional money to get extra services such as meal, hair cutting, bathing etc., due to government financial support stopped, some organizations have to reduce services and replace full-time workers to part-time ones, which makes the service quality worse. Lastly, in the transferring system, the management system for service quality is not well prepared. There are too much competion because of allowing too many home-help service organizations and care worker academies. The suggestions that this research has found to improve the policy are as follows. ① It is desirable to make the registered clients the service ones as many as possible in the long term perspective. ② The LTCI organization requires more workers and higher professionality. ③ Many elderly people who are not eligible now require connection system to be more served. ④ Management system and service manual for care worker are to be developed. ⑤ Laws related to the service contents and process should be modified, the proportion of client charge needs to adjust. ⑥ Home-help service organization licensed by the LTCI needs to be financially supported publicly. ⑦ Monitoring system to home-help service organization needs to be strengthened. ⑧ Evaluation tools to home-help service organization and workers is required. ⑨ Specification to open the home-help service organization needs to be more strict.
Dongwon Kwon;Wan-Gyu Sang;Sungyul Chang;Woo-jin Im;Hyeok-jin Bak;Ji-hyeon Lee;Jung-Il Cho
Korean Journal of Agricultural and Forest Meteorology
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v.25
no.4
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pp.387-397
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2023
Plant height is a growth parameter that provides visible insights into the plant's growth status and has a high correlation with yield, so it is widely used in crop breeding and cultivation research. Investigation of the growth characteristics of crops such as plant height has generally been conducted directly by humans using a ruler, but with the recent development of sensing and image analysis technology, research is being attempted to digitally convert growth measurement technology to efficiently investigate crop growth. In this study, the canopy height of rice grown at various nitrogen fertilization levels was measured using a laser scanner capable of precise measurement over a wide range, and a comparative analysis was performed with the actual plant height. As a result of comparing the point cloud data collected with a laser scanner and the actual plant height, it was confirmed that the estimated plant height measured based on the average height of the top 1% points showed the highest correlation with the actual plant height (R2 = 0.93, RMSE = 2.73). Based on this, a linear regression equation was derived and used to convert the canopy height measured with a laser scanner to the actual plant height. The rice growth curve drawn by combining the actual and estimated plant height collected by various nitrogen fertilization conditions and growth period shows that the laser scanner-based canopy height measurement technology can be effectively utilized for assessing the plant height and growth of rice. In the future, 3D images derived from laser scanners are expected to be applicable to crop biomass estimation, plant shape analysis, etc., and can be used as a technology for digital conversion of conventional crop growth assessment methods.
Mi-El Kim;Jaehoon Sim;Aein Mon;Myung-Joo Kim;Young-Seok Park;Ho-Beom Kwon;Jaeheung Park
The Journal of Korean Academy of Prosthodontics
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v.61
no.4
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pp.257-267
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2023
Purpose. The purpose of the study was to fabricate a prototype robotic simulator for dental education, to test whether it could simulate mandibular movements, and to assess the possibility of the stimulator responding to stimuli during dental practice. Materials and methods. A virtual simulator model was developed based on segmentation of the hard tissues using cone-beam computed tomography (CBCT) data. The simulator frame was 3D printed using polylactic acid (PLA) material, and dentiforms and silicone face skin were also inserted. Servo actuators were used to control the movements of the simulator, and the simulator's response to dental stimuli was created by pressure and water level sensors. A water level test was performed to determine the specific threshold of the water level sensor. The mandibular movements and mandibular range of motion of the simulator were tested through computer simulation and the actual model. Results. The prototype robotic simulator consisted of an operational unit, an upper body with an electric device, a head with a temporomandibular joint (TMJ) and dentiforms. The TMJ of the simulator was capable of driving two degrees of freedom, implementing rotational and translational movements. In the water level test, the specific threshold of the water level sensor was 10.35 ml. The mandibular range of motion of the simulator was 50 mm in both computer simulation and the actual model. Conclusion. Although further advancements are still required to improve its efficiency and stability, the upper-body prototype simulator has the potential to be useful in dental practice education.
In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.18
no.5
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pp.91-107
/
2023
Lean startup is a concept that combines the words "lean," meaning an efficient way of running a business, and "startup," meaning a new business. It is often cited as a strategy for minimizing failure in early-stage businesses, especially in software-based startups. By scrutinizing the case of a startup L, this study suggests that lean startup methodology(LSM) can be useful for hardware and manufacturing companies and identifies ways for early startups to successfully implement LSM. To this end, the study explained the core of LSM including the concepts of hypothesis-driven approach, BML feedback loop, minimum viable product(MVP), and pivot. Five criteria to evaluate the successful implementation of LSM were derived from the core concepts and applied to evaluate the case of startup L . The early startup L pivoted its main business model from defecation alert system for patients with limited mobility to one for infants or toddlers, and finally to a smart bottle for infants. In developing the former two products, analyzed from LSM's perspective, company L neither established a specific customer value proposition for its startup idea and nor verified it through MVP experiment, thus failed to create a BML feedback loop. However, through two rounds of pivots, startup L discovered new target customers and customer needs, and was able to establish a successful business model by repeatedly experimenting with MVPs with minimal effort and time. In other words, Company L's case shows that it is essential to go through the customer-market validation stage at the beginning of the business, and that it should be done through an MVP method that does not waste the startup's time and resources. It also shows that it is necessary to abandon and pivot a product or service that customers do not want, even if it is technically superior and functionally complete. Lastly, the study proves that the lean startup methodology is not limited to the software industry, but can also be applied to technology-based hardware industry. The findings of this study can be used as guidelines and methodologies for early-stage companies to minimize failures and to accelerate the process of establishing a business model, scaling up, and going global.
With the advancement of big data processing technology using cloud platforms, access, processing, and analysis of large-volume data such as satellite imagery have recently been significantly improved. In this study, the Change Detection Method, a relatively simple technique for retrieving soil moisture, was applied to the backscattering coefficient values of pre-processed Sentinel-1 synthetic aperture radar (SAR) satellite imagery product based on Google Earth Engine (GEE), one of those platforms, to estimate the surface soil moisture for six observatories within the Yongdam Dam watershed in South Korea for the period of 2015 to 2023, as well as the watershed average. Subsequently, a correlation analysis was conducted between the estimated values and actual measurements, along with an examination of the applicability of GEE. The results revealed that the surface soil moisture estimated for small areas within the soil moisture observatories of the watershed exhibited low correlations ranging from 0.1 to 0.3 for both VH and VV polarizations, likely due to the inherent measurement accuracy of the SAR satellite imagery and variations in data characteristics. However, the surface soil moisture average, which was derived by extracting the average SAR backscattering coefficient values for the entire watershed area and applying moving averages to mitigate data uncertainties and variability, exhibited significantly improved results at the level of 0.5. The results obtained from estimating soil moisture using GEE demonstrate its utility despite limitations in directly conducting desired analyses due to preprocessed SAR data. However, the efficient processing of extensive satellite imagery data allows for the estimation and evaluation of soil moisture over broad ranges, such as long-term watershed averages. This highlights the effectiveness of GEE in handling vast satellite imagery datasets to assess soil moisture. Based on this, it is anticipated that GEE can be effectively utilized to assess long-term variations of soil moisture average in major dam watersheds, in conjunction with soil moisture observation data from various locations across the country in the future.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.19
no.1
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pp.119-133
/
2024
As a result of significant investments by the government in promoting public technology commercialization and fostering a venture startup ecosystem, there have been quantitative achievements, such as the registration of over 1,600 Innopolis Start-ups since 2006, generating a total revenue of 1.1 trillion won as of 2021. However, these achievements have been overshadowed by critical qualitative challenges, including a continuous decline in average revenue per Innopolis Start-up. This led to a focus on whether managers' technological and market orientations affect business performance. This study aims to provide insights into improving the qualitative growth of Innopolis Start-ups by analyzing the effects of technological and market orientations on business performance, as well as the moderating effects of adjusting marketing and research and development (R&D) costs on this relationship. Through prior research and empirical analysis, this study derives three main findings. First, technological excellence and innovation significantly influence the business performance of Innopolis Start-ups, while technological intensity does not. Second, customer orientation and competitive orientation significantly impact business performance, whereas entry barriers as a single factor do not. Third, adjusting marketing and R&D costs, as controlled variables obtained through general situations, has no direct impact on other variables. However, it interacts with entry barriers, influencing financial business performance, with R&D costs exhibiting a negative buffering effect and marketing costs showing a positive enhancing effect. This study confirms that both technological and market orientations directly influence the business performance of Innopolis Start-ups, thus being crucial factors affecting their growth. Moreover, it establishes that investments in marketing and R&D play significant roles in alleviating initial entry barriers and enhancing financial performance. Consequently, it underscores the importance of reinforcing technological and market orientations tailored to the characteristics of Innopolis Start-ups. Additionally, it proposes five theoretical contributions: strengthening institutional support systems for technology commercialization and innovation, improving qualitative evaluation criteria during the selection process of Innopolis Start-ups, conducting comprehensive analyses of technological and market aspects during startup selection, enhancing support for marketing education and consulting for smooth market entry, and supporting expenditure strategies and milestone setting tailored to the industrial characteristics of individual Innopolis Start-ups.
SEUNG HYEON KIM;JONG-HYEOB KIM;HYEGWANG KIM;JIN WOO KU;KI YOUNG KIM;KUN-SEOP LEE
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.29
no.1
/
pp.28-41
/
2024
The carbon balance serves as a valuable indicator of a plant's physiological status under diverse environmental conditions. We investigated the photosynthetic and respiratory responses of the Asian surfgrass Phyllospadix iwatensis along the northeast coast of the Korean peninsula in response to changing water temperature (ranging from 5℃ to 30℃) to estimate the seasonal whole-plant carbon balance through a series of incubation experiments. The maximum gross photosynthetic rate (Pmax) showed a significant difference among the temperature treatments, while there was no significant difference in photosynthetic efficiency (α). The maximum gross photosynthetic rate of P. iwatensis reached its peaks at 20℃ treatment (101.65 μmol O2 g-1 DW h-1) but decreased rapidly at 30℃. The saturation irradiance (Ik), compensation irradiance (Ic), and respiration rate (R) of P. iwatensis exhibited significant differences among the temperature treatments. The saturation irradiance increased up to 20-25℃ (121.59-124.50 μmol photons m-2 s-1) and sharply decreased at 30℃. The compensation irradiance and respiration rate increased steadily with rising water temperature. The ratio of Pmax to R (Pmax:R ratio) was the highest at 5℃ but dramatically decreased at 30℃. The whole-plant carbon balance, calculated based on photosynthetic parameters, respiration rates, and biomass, exhibited distinct seasonal variation, increasing during winter and spring and decreasing during summer and fall, which is consistent with the highest in situ growth in spring and severely limited growth at the highest water temperature conditions. Phyllospadix iwatensis displayed a negative carbon balance during late summer, fall, and winter, but demonstrated a positive carbon balance during spring and early summer. Our findings suggest that the rising seawater temperatures associated with climate change may lead to significant alterations in the seagrass ecosystem functioning along the rocky shores of the Korean east coast.
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