• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.855-866
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• 2017

Several research cases using remote sensing methods to analyze changes of storage and dynamics of groundwater aquifer were reviewed in this paper. The status of groundwater storage, in an area with regional scale, could be qualitatively inferred from geological feature, surface water altimetry and topography, distribution of vegetation, and difference between precipitation and evapotranspiration. These qualitative indicators could be measured by geological lineament analysis, airborne magnetic survey, DEM analysis, LAI and NDVI calculation, and surface energy balance modeling. It is certain that GRACE and InSAR have received remarkable attentions as direct utilization from satellite data for quantification of groundwater storage and dynamics. GRACE, composed of twin satellites having acceleration sensors, could detect global or regional microgravity changes and transform them into mass changes of water on surface and inside of the Earth. Numerous studies in terms of groundwater storage using GRACE sensor data were performed with several merits such that (1) there is no requirement of sensor data, (2) auxiliary data for quantification of groundwater can be entirely obtained from another satellite sensors, and (3) algorithms for processing measured data have continuously progressed from designated data management center. The limitations of GRACE for groundwater storage measurement could be defined as follows: (1) In an area with small scale, mass change quantification of groundwater might be inaccurate due to detection limit of the acceleration sensor, and (2) the results would be overestimated in case of combination between sensor and field survey data. InSAR can quantify the dynamic characteristics of aquifer by measuring vertical micro displacement, using linear proportional relation between groundwater head and vertical surface movement. However, InSAR data might now constrain their application to arid or semi-arid area whose land cover appear to be simple, and are hard to apply to the area with the anticipation of loss of coherence with surface. Development of GRACE and InSAR sensor data preprocessing algorithms optimized to topography, geology, and natural conditions of Korea should be prioritized to regionally quantify the mass change and dynamics of the groundwater resources of Korea.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1037-1051
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• 2020

The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.

• Journal of Korean Society of Transportation
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• v.33 no.4
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• pp.379-392
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• 2015

Freight flow data in Korea has been collected for a variety of purposes by various organizations. However, since the representation and format of the data varies, it has not been substantially used for freight analyses and furthermore for freight policies. In order to increase the applicability of those data sets, it is required to bring them in a table and compare for finding the differences. Then, it is shown that the raw data can be aggregated by a particular criterion such as mode, origin and destination, and type commodity. This study aims to examine the freight data issue in terms of three different points of view. First, we investigated various freight volume data sets which are released by several organizations. Second, we tried to develop formulations for freight volume data. Third, we discussed how to apply the formulations to network models in which particular OR (Operations Research) techniques are used. The results emphasized that some data might be useless for modeling once they are aggregated. As a result of examining the freight volume data, this study found that 14 organizations share their data sets at various aggregation levels. This study is not an ordinary research article, which normally includes data analysis, because it seems to be impossible to conduct extensive case studies. The reason is that the data dealt in this study are diverse. Nevertheless, this study might guide the research direction in the freight transport research society in terms of data issue. Especially, it can be concluded that this study is a timely research because the governmemt has emphasized the importance of sharing data to public throughout 'government 3.0' for research purpose.

• Radiation Oncology Journal
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• v.14 no.1
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• pp.77-85
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• 1996

Purpose : Multileaf collimator(MLC) is very suitable tool for conformal radio-therapy and commissioning measurements for a multileaf collimator installed on a dual energy accelerator with 6 and 10MV photons are required, For modeling the collimator with treament planning software, detailed dosimetric characterization of the multileaf collimator including the penumbra width, leaf transmission between leaf leakage and localization of the leaf ends and sides is an essential requirement. materials and Methods : Measurement of characteristic data of the MLC with 26 pair block leaves installed on CLINAC 2100C linear accelerator was performed. Low sensitive radiographic film(X-omatV) was used for the penumbra measurement and separate experiments using radiographic film and thermoluminescent dosimeters were performed to verify the dose distribution, Measured films were analized with a photodensitometer of WP700i scanner. Results : For 6 & 10 MV x-ray energies, approximately $2.0\%$ of photons incident on the multileaf collimator were transmitted and an additional $0.5\%$ leakage occurs between the leaves. Localizing the physical end of the leaves showed less than 1mm deviation from the $50\%$ decrement line and this difference is attributed to the curved shaped end on the leaves One side of a sin히e leaf corresponded to the $50\%$ decrement line, but the opposite face was aligned with a lower value. This difference is due to the tongue and groove used to decrease between leaf leakage. Alignment of the leaves to form a straight edge resulted larger penumbra at far position from isocenter as compare with divergent alloy blocks. When the MLC edge is stepped by sloping field, the isodose lines follow the leaf pattern and Produce scalloping isodose curves in tissue. The effective penumbra by 45 degree stepped MLC is about 10mm at 10cm depth for 6MV x-ray. The difference of effective penumbra in deep tissue between MLC and divergent alloy blocks is small (5mm). Conclusion : Using the characteristic data of MLC, the MLC has the clinlical acceptability and suitability for 3-D conformal radiotherapy except small field size.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.105-130
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• 2008

Consumers of e-learning market differ from those of other markets in that they are replaced in a specific time scale. For example, e-learning contents aimed at highschool senior students cannot be consumed by a specific consumer over the designated period of time. Hence e-learning service providers need to attract new groups of students every year. Due to lack of information on products designed for continuously emerging consumers, the consumers face difficulties in making rational decisions in a short time period. Increased uncertainty of product purchase leads customers to herding behaviors to obtain information of the product from others and imitate them. Taking into consideration of these features of e-learning market, this study will focus on the online herding behavior in purchasing e-learning contents. There is no definite concept for e-learning. However, it is being discussed in a wide range of perspectives from educational engineering to management to e-business etc. Based upon the existing studies, we identify two main view-points regarding e-learning. The first defines e-learning as a concept that includes existing terminologies, such as CBT (Computer Based Training), WBT (Web Based Training), and IBT (Internet Based Training). In this view, e-learning utilizes IT in order to support professors and a part of or entire education systems. In the second perspective, e-learning is defined as the usage of Internet technology to deliver diverse intelligence and achievement enhancing solutions. In other words, only the educations that are done through the Internet and network can be classified as e-learning. We take the second definition of e-learning for our working definition. The main goal of this study is to investigate what factors affect consumer intention to purchase e-learning contents and to identify the differential impact of the factors between consumers with purchase experience and those without the experience. To accomplish the goal of this study, it focuses on herding behavior and perceived usefulness as antecedents to behavioral intention. The proposed research model in the study extends the Technology Acceptance Model by adding herding behavior and usability to take into account the unique characteristics of e-learning content market and e-learning systems use, respectively. The current study also includes consumer experience with e-learning content purchase because the previous experience is believed to affect purchasing intention when consumers buy experience goods or services. Previous studies on e-learning did not consider the characteristics of e-learning contents market and the differential impact of consumer experience on the relationship between the antecedents and behavioral intention, which is the target of this study. This study employs a survey method to empirically test the proposed research model. A survey questionnaire was developed and distributed to 629 informants. 528 responses were collected, which consist of potential customer group (n = 133) and experienced customer group (n = 395). The data were analyzed using PLS method, a structural equation modeling method. Overall, both herding behavior and perceived usefulness influence consumer intention to purchase e-learning contents. In detail, in the case of potential customer group, herding behavior has stronger effect on purchase intention than does perceived usefulness. However, in the case of shopping-experienced customer group, perceived usefulness has stronger effect than does herding behavior. In sum, the results of the analysis show that with regard to purchasing experience, perceived usefulness and herding behavior had differential effects upon the purchase of e-learning contents. As a follow-up analysis, the interaction effects of the number of purchase transaction and herding behavior/perceived usefulness on purchase intention were investigated. The results show that there are no interaction effects. This study contributes to the literature in a couple of ways. From a theoretical perspective, this study examined and showed evidence that the characteristics of e-learning market such as continuous renewal of consumers and thus high uncertainty and individual experiences are important factors to be considered when the purchase intention of e-learning content is studied. This study can be used as a basis for future studies on e-learning success. From a practical perspective, this study provides several important implications on what types of marketing strategies e-learning companies need to build. The bottom lines of these strategies include target group attraction, word-of-mouth management, enhancement of web site usability quality, etc. The limitations of this study are also discussed for future studies.

• Asia pacific journal of information systems
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• v.21 no.4
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• pp.1-25
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• 2011

Internet-based commerce has undergone an explosive growth over the past decade as consumers today find it more economical as well as more convenient to shop online. Nevertheless, the shift in the common mode of shopping from offline to online commerce has caused consumers to have worries over such issues as private information leakage, online fraud, discrepancy in product quality and grade, unsuccessful delivery, and so forth, Numerous studies have been undertaken to examine the role of perceived risk as a chief barrier to online purchases and to understand the theoretical relationships among perceived risk, trust and purchase intentions, However, most studies focus on empirically investigating the effects of trust on perceived risk, with little attention devoted to the effects of perceived risk on trust, While the influence trust has on perceived risk is worth studying, the influence in the opposite direction is equally important, enabling insights into the potential of perceived risk as a prohibitor of trust, According to Pavlou (2003), the primary source of the perceived risk is either the technological uncertainty of the Internet environment or the behavioral uncertainty of the transaction partner. Due to such types of uncertainty, an increase in the worries over the perceived risk may negatively affect trust, For example, if a consumer who sends sensitive transaction data over Internet is concerned that his or her private information may leak out because of the lack of security, trust may decrease (Olivero and Lunt, 2004), By the same token, if the consumer feels that the online merchant has the potential to profit by behaving in an opportunistic manner taking advantage of the remote, impersonal nature of online commerce, then it is unlikely that the merchant will be trusted, That is, the more the probable danger is likely to occur, the less trust and the greater need to control the transaction (Olivero and Lunt, 2004), In summary, a review of the related studies indicates that while some researchers looked at the influence of overall perceived risk on trust level, not much attention has been given to the effects of different types of perceived risk, In this context the present research aims at addressing the need to study how trust is affected by different types of perceived risk, We classified perceived risk into six different types based on the literature, and empirically analyzed the impact of each type of perceived risk upon consumer trust in an online merchant and further its impact upon purchase intentions. To meet our research objectives, we developed a conceptual model depicting the nomological structure of the relationships among our research variables, and also formulated a total of seven hypotheses. The model and hypotheses were tested using an empirical analysis based on a questionnaire survey of 206 college students. The reliability was evaluated via Cronbach's alphas, the minimum of which was found to be 0.73, and therefore the questionnaire items are all deemed reliable. In addition, the results of confirmatory factor analysis (CFA) designed to check the validity of the measurement model indicate that the convergent, discriminate, and nomological validities of the model are all acceptable. The structural equation modeling analysis to test the hypotheses yielded the following results. Of the first six hypotheses (H1-1 through H1-6) designed to examine the relationships between each risk type and trust, three hypotheses including H1-1 (performance risk ${\rightarrow}$ trust), H1-2 (psychological risk ${\rightarrow}$ trust) and H1-5 (online payment risk ${\rightarrow}$ trust) were supported with path coefficients of -0.30, -0.27 and -0.16 respectively. Finally, H2 (trust ${\rightarrow}$ purchase intentions) was supported with relatively high path coefficients of 0.73. Results of the empirical study offer the following findings and implications. First. it was found that it was performance risk, psychological risk and online payment risk that have a statistically significant influence upon consumer trust in an online merchant. It implies that a consumer may find an online merchant untrustworthy if either the product quality or the product grade does not match his or her expectations. For that reason, online merchants including digital storefronts and e-marketplaces are suggested to pursue a strategy focusing on identifying the target customers and offering products that they feel best meet performance and psychological needs of those customers. Thus, they should do their best to make it widely known that their products are of as good quality and grade as those purchased from offline department stores. In addition, it may be inferred that today's online consumers remain concerned about the security of the online commerce environment due to the repeated occurrences of hacking or private information leakage. Online merchants should take steps to remove potential vulnerabilities and provide online notices to emphasize that their website is secure. Second, consumer's overall trust was found to have a statistically significant influence on purchase intentions. This finding, which is consistent with the results of numerous prior studies, suggests that increased sales will become a reality only with enhanced consumer trust.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.2
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• pp.190-204
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• 2018

The probability of safe cropping and the major phenological stages in rice were assessed using daily mean temperature data from 1981 to 2016 at 27 sites in North Korea. The threshold temperatures for early marginal transplanting date (EMTD), marginal harvesting date (MHVD), safe marginal heading date (SMHD), and cumulative temperature-based heading date (CTHD) were set to be $14^{\circ}C$, $13^{\circ}C$, $22^{\circ}C$ for 40 days after heading, and cumulative temperature of $1200^{\circ}C$ to MHVD, respectively. The safe heading date (SHD) was assumed to be either SMHD or CTHD whichever was earlier. It was also assumed that the minimum requirement for the suitability of safe rice cropping was met when both SMHD and CTHD appeared along with the time period of 60 days or more from EMTD to SHD. It was analyzed that 17 sites (Kaesong, Haeju, Yongyon, Singye, Sariwon, Nampo, Pyongyang, Anju, Kusong, Sinuiju, Changjon, Wonsan, Hamhung, Pyonggang, Huichon, Supung, Kanggye) had 90% or higher probability, two sites (Yangdok, Sinpo) had 80-90% probability, and eight sites (Kimchaek, Chunggang, Chongjin, Sonbong, Changjin, Pungsan, Hyesan, Samjiyon) had less than 80% probability of the safe rice cropping. For each region, the representative EMTD, SHD, and MHVD were analyzed using the 80 percentile of total years tested. The ranges for EMTD, SHD, and MHVD were May 4 in Sariwon~May 24 in Sinpo, June 21 in Kanggye~August 11 in Haeju, and September 17 in Kanggye~October 16 in Haeju and Changjon, respectively. Time durations from EMTD to SHD and from SHD to MHVD were 67~97 days and 57~72 days, respectively, depending on the regions. This study would facilitate modeling efforts for rice yield simulation in future studies. Our results would also provide basic information for practical researches on the rice cropping system in North Korea.

• Journal of Preventive Medicine and Public Health
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• v.40 no.5
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• pp.363-370
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• 2007

Objectives: The principal objective of this study was to determine the relationship between maternal exposure to air pollution and low birth weight and to propose a possible environmental health surveillance system for low birth weight. Methods: We acquired air monitoring data for Seoul from the Ministry of Environment, the meteorological data from the Korean Meteorological Administration, the exposure assessments from the National Institute of Environmental Research, and the birth data from the Korean National Statistical Office between January 1, 2002 and December 31, 2003. The final birth data were limited to singletons within $37{\sim}44$ weeks of gestational age. We defined the Low Birth Weight (LBW) group as infants with birth weights of less than 2500g and calculated the annual LBW rate by district. The air monitoring data were measured for $CO,\;SO_2,\;NO_2,\;and\;PM_{10}$ concentrations at 27 monitoring stations in Seoul. We utilized two models to evaluate the effects of air pollution on low birth weight: the first was the relationship between the annual concentration of air pollution and low birth weight (LBW) by individual and district, and the second involved a GIS exposure model constructed by Arc View 3.1. Results: LBW risk (by Gu, or district) was significantly increased to $1.113(95%\;CI=1.111{\sim}1.116)\;for\;CO,\;1.004(95%\;CI=1.003{\sim}1.005)\;for\;NO_2,\;1.202(95%\;CI=1.199{\sim}1.206\;for\;SO_2,\;and\;1.077(95%\;CI=1.075{\sim}1.078)\;\;for\;PM_{10}$ with each interquartile range change. Personal LBW risk was significantly increased to $1.081(95%\;CI=1.002{\sim}1.166)\;for\;CO,\;1.145(95%\;CI=1.036{\sim}1.267)\;for\;SO_2,\;and\;1.053(95%\;CI=1.002{\sim}1.108)\;for\;PM_{10}$ with each interquartile range change. Personal LBW risk was increased to $1.003(95%\;CI=0.954{\sim}1.055)\;for\;NO_2$, but this was not statistically significant. The air pollution concentrations predicted by GIS positively correlated with the numbers of low birth weights, particularly in highly polluted regions. Conclusions: Environmental health surveillance is a systemic, ongoing collection effort including the analysis of data correlated with environmentally-associated diseases and exposures. In addition. environmental health surveillance allows for a timely dissemination of information to those who require that information in order to take effective action. GIS modeling is crucially important for this purpose, and thus we attempted to develop a GIS-based environmental surveillance system for low birth weight.

• Tunnel and Underground Space
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• v.30 no.4
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• pp.359-381
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• 2020

Within the framework of DECOVALEX-2019 Task D, full-scale engineered barriers experiment (FEBEX) at Grimsel Test Site was numerically simulated to investigate an applicability of implemented Barcelona basic model (BBM) into TOUGH2-MP/FLAC3D simulator, which was developed for the prediction of the coupled thermo-hydro-mechanical behavior of bentonite buffer. And the calculated heater power, temperature, relative humidity, total stress, saturation, water content and dry density were compared with in situ data monitored in the various sections. In general, the calculated heater power and temperature provided a fairly good agreement with experimental observations, however, the difference between power of heater #1 and that of heater #2 could not captured in the numerical analysis. It is necessary to consider lamprophyre with low thermal conductivity around heater #1 and non-simplified installation progresses of bentonite blocks in the tunnel for better modeling results. The evolutions and distributions of relative humidity were well reproduced, but hydraulic model needs to be modified because the re-saturation process was relatively fast near the heaters. In case of stress evolutions due to the thermal and hydraulic expansions, the computed stress was in good agreement with the data. But, the stress is slightly higher than the measured in situ data at the early stage of the operation, because gap between rock mass and bentonite blocks have not been considered in the numerical simulations. The calculated distribution of saturation, water content, and dry density along the radial distance showed good agreement with the observations after the first and final dismantling. The calculated dry density near the center of the FEBEX tunnel and heaters were overestimated compared with the observations. As a result, the saturation and water content were underestimated with the measurements. Therefore, numerical model of permeability is needed to modify for the production of better numerical results. It will be possible to produce the better analysis results and more realistically predict the coupled THM behavior in the bentonite blocks by performing the additional studies and modifying the numerical model based on the results of this study.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.919-932
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• 2019

Fine particulate matter (PM2.5) is not only affected by anthropogenic emissions, but also intensifies, migrates, decreases by hydrometeorological factors. Therefore, it is essential to understand relationships between the hydrometeorological factors and PM2.5 concentration. In Korea, PM2.5 concentration is measured at the ground observatories and estimated data are given to locations where observatories are not present. In this way, the data is not suitable to represent an area, hence it is impossible to know accurate concentration at such locations. In addition, it is hard to trace migration, intensification, reduction of PM2.5. In this study, we analyzed the relationships between hydrometeorological factors, acquired from Global Land Data Assimilation System (GLDAS), and PM2.5 by means of Bayesian Model Averaging (BMA). By BMA, we also selected factors that have meaningful relationship with the variation of PM2.5 concentration. 4 PM2.5 concentration models for different seasons were developed using those selected factors, with Aerosol Optical Depth (AOD) from MODerate resolution Imaging Spectroradiometer (MODIS). Finally, we mapped the result of the model, to show spatial distribution of PM2.5. The model correlated well with the observed PM2.5 concentration (R ~0.7; IOA ~0.78; RMSE ~7.66 ㎍/㎥). When the models were compared with the observed PM2.5 concentrations at different locations, the correlation coefficients differed (R: 0.32-0.82), although there were similarities in data distribution. The developed concentration map using the models showed its capability in representing temporal, spatial variation of PM2.5 concentration. The result of this study is expected to be able to facilitate researches that aim to analyze sources and movements of PM2.5, if the study area is extended to East Asia.