• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

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

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

• Journal of Navigation and Port Research
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• v.31 no.3 s.119
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• pp.235-245
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• 2007

Stiffened steel plates are basic structural members on the deck and bottom structure in ship, offshore. It has a number of one sided stiffeners in either one or both directions, the latter structure was called grillage structure. At the ship structural desgn stage, one of the major consideration is evaluation for ultimate strength of the hull girder. In general, it is accepted that hull girder strength can be represented by the local strength of the longitudinal stiffened panel. In case of considering hogging condition in a stormy sea, stiffened panel was acting on the bottom structure under axial compressive load induced hull girder bending moment, also simultaneously arising local bending moment induced lateral pressure load. In this paper, results of the structural analysis have been compared with another detailed FEA program and prediction from design guideline and a series analysis was conducted consideration of changing parameters for instance, analysis range, cross-section of stiffener, web height and amplitude of lateral pressure load subjected to combined load (axial compression and lateral pressure load). It has been found that finite element modeling is capable of predicting the behaviour and ultimate load capacity of a simply supported stiffened plate subjected to combined load of axial compression and lateral pressure load It is expected that these results will be used to examine the effect of interaction between lateral pressure and axial loads for the ultimate load-carrying capacity based on the Ultimate Limit State design guideline.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.3
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• pp.360-369
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• 2012

Parent material, climate, topography, biological factors, and time are considered five soil forming factors. This study was conducted to elucidate the effects of several environment factors on soil distribution using quantitative analysis method, called soil series estimation algorithm in the soils of Jeju Island. We selected environment factors including mean temperature, annual precipitation, surface geology, altitude, slope, aspect, altitude difference within 1 $km^2$ area, topographic wetness index, distance from the shore, distance from the mountain peak, and landuse for a quantitative analysis. We analyzed the ranges of environment factors for each soil series and calculated probabilities of possible-soil series for certain locations using estimation algorithm. The algorithm can predicted exact soil series on the soil map with correctness of 33% on $1^{st}$ ranking, 62% within $2^{nd}$ ranking, 74% within $5^{th}$ ranking after estimating using randomly extracted environment factors. In predicted soil map, soil sequences of Entisols-Alfisols-Andisols on northern area and Alfisols-Ultisols-Andisols on western area can be suggested along increasing altitude. More modeling studies will be needed for the genesis process of soils in Jeju Island.

• Computers and Concrete
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• v.11 no.2
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• pp.123-148
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• 2013

The nonlinear finite element method with eight noded isoparametric quadrilateral element for concrete and two noded element for reinforcement is used for the prediction of the behavior of reinforcement concrete structures. The disturbed state concept (DSC) including the hierarchical single surface (HISS) plasticity model with associated flow rule with modifications is used to characterize the constitutive behavior of concrete both in compression and in tension which is named DSC/HISS-CT. The HISS model is applied to shows the plastic behavior of concrete, and DSC for microcracking, fracture and softening simulations of concrete. It should be noted that the DSC expresses the behavior of a material element as a mixture of two interacting components and can include both softening and stiffening, while the classical damage approach assumes that cracks (damage) induced in a material treated acts as a void, with no strength. The DSC/HISS-CT is a unified model with different mechanism, which expresses the observed behavior in terms of interacting behavior of components; thus the mechanism in the DSC is much different than that of the damage model, which is based on physical cracks which has no strength and interaction with the undamaged part. This is the first time the DSC/HISS-CT model, with the capacity to account for both compression and tension yields, is applied for concrete materials. The DSC model allows also for the characterization of non-associative behavior through the use of disturbance. Elastic perfectly plastic behavior is assumed for modeling of steel reinforcement. The DSC model is validated at two levels: (1) specimen and (2) practical boundary value problem. For the specimen level, the predictions are obtained by the integration of the incremental constitutive relations. The FE procedure with DSC/HISS-CT model is used to obtain predictions for practical boundary value problems. Based on the comparisons between DSC/HISS-CT predictions, test data and ANSYS software predictions, it is found that the model provides highly satisfactory predictions. The model allows computation of microcracking during deformation leading to the fracture and failure; in the model, the critical disturbance, Dc, identifies fracture and failure.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.94-106
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• 2018

The epidemiological model is useful for creating simulation and associated preventive measures for disease spread, and provides a detailed understanding of the spread of disease space through contact with individuals. In this study, propose an agent-based spatial model(ABM) integrated with spatial big data to simulate the spread of MERS-CoV infections in real time as a result of the interaction between individuals in space. The model described direct contact between individuals and hospitals, taking into account three factors : population, time, and space. The dynamic relationship of the population was based on the MERS-CoV case in Seoul Metropolitan Government in 2015. The model was used to predict the occurrence of MERS, compare the actual spread of MERS with the results of this model by time series, and verify the validity of the model by applying various scenarios. Testing various preventive measures using the measures proposed to select a quarantine strategy in the event of MERS-CoV outbreaks is expected to play an important role in controlling the spread of MERS-CoV.

• The Journal of Fisheries Business Administration
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• v.51 no.2
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• pp.51-69
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• 2020

The purpose of this study is to construct an outlook model that is consistent with the "Fisheries Outlook" monthly published by the Fisheries Outlook Center of the Korea Maritime Institute(KMI). In particular, it was designed as a partial equilibrium model limited to abalone items, but a model was constructed with a dynamic ecological equation model(DEEM) system taking into account biological breeding and shipping time. The results of this study are significant in that they can be used as basic data for model development of various items in the future. In this study, due to the limitation of monthly data, the market equilibrium price was calculated by using the recursive model construction method to be calculated directly as an inverse demand. A model was built in the form of a structural equation model that can explain economic causality rather than a conventional time series analysis model. The research results and implications are as follows. As a result of the estimation of the amount of young seashells planting, it was estimated that the coefficient of the amount of young seashells planting from the previous year was estimated to be 0.82 so that there was no significant difference in the amount of young seashells planting this year and last year. It is also meant to be nurtured for a long time after aquaculture license and limited aquaculture area(edge style) and implantation. The economic factor, the coefficient of price from last year was estimated at 0.47. In the case of breeding quantity, it was estimated that the longer the breeding period, the larger the coefficient of breeding quantity in the previous period. It was analyzed that the impact of shipments on the breeding volume increased. In the case of shipments, the coefficient of production price was estimated unelastically. As the period of rearing increased, the estimation coefficient decreased. Such result indicates that the expected price, which is an economic factor variable and that had less influence on the intention to shipments. In addition, the elasticity of the breeding quantity was estimated more unelastically as the breeding period increased. This is also correlated with the relative coefficient size of the expected price. The abalone supply and demand forecast model developed in this study is significant in that it reduces the prediction error than the existing model using the ecological equation modeling system and the economic causal model. However, there are limitations in establishing a system of simultaneous equations that can be linked to production and consumption between industries and items. This is left as a future research project.

• Journal of Korea Water Resources Association
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• v.50 no.5
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• pp.303-313
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• 2017

In environmental impact assessments for large urban development projects, the Korean government requires analysis of stormwater runoff before, during and after the projects. Though hydrological models are widely used to analyze and prepare for surface runoff during storm events, accuracy of the predicted results have been in question due to limited amount of field data for model calibrations. Intensive field measurements have been made for storm events between July 2015 and July 2016 at a sub-basin of the Gwanpyung-cheon, Daejeon, Republic of Korea using an automatic monitoring system and also additional manual measurements. Continuous precipitation and surface runoff data used for utilization of SWMM model to predict surface runoff during storm events with improved accuracy. The optimal values for Manning's roughness coefficient and values for depression storage were estimated for pervious and impervious surfaces using three representative infiltration methods; the Curve Number Methods, the Horton's Method and the Green-Ampt Methods. The results of the research is expected to be used more efficiently for urban development projects in Korea.

• KSBB Journal
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• v.11 no.2
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• pp.151-158
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• 1996

For the effective ethanol fermentation, the high concentration of sugar as the substrate of microbial fermentation is required. The most important reason in the inefficient hydrolysis; the easy deactivation of enzyme by temperature or shear stress and the severe inhibition effects of its products. In our work, we comprehended the kinetic characteristics of cellulose and ${\beta}$-glucosidase in the progress of hydrolysis, and observed the potential inhibitory effects of the hydrolyzed products and the deactivation of enzymes. We also tried to present the kinetic model of enzymatic hydrolysis of cellulose, which is applicable to process at the high concentration of sugar. Cellulase and ,${\beta}$-glucosidase exhibit diverse kinetic behaviors. At a level of only 5g/$\ell$ of glucose, the ${\beta}$-glucosidase activity was reduced by more than 70%. This result means that ${\beta}$-glucosldase was the most severely inhibited by glucose. Also at l0g/$\ell$ of cellobiose, the cellulose lost approximately 70% of its activity. ${\beta}$-glucosldase was more sensitive to deactivation than cellulose by about 1.6 times. The comprehensive kinetic model in the range of confidence was obtained and the agreement between the model prediction and the experimental data was reasonably good, testifying to the validity of the model equations used and the associated parameters.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.6
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• pp.405-412
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• 2014

A number of algal bloom models (red-tide models) have been developed and applied to simulate the redtide growth and decline patterns as the interest on the phytoplankton blooms has been continuously increased. The quantitative error analysis of the model is of great importance because the accurate prediction of the red-tide occurrence and transport pattern can be used to setup the effective mitigations and counter-measures on the coastal ecosystem, aquaculture and fisheries damages. The word "red-tide model" is widely used without any clear definitions and references. It makes the comparative evaluation of the ecological models difficult and confusable. It is highly required to do the performance test of the red-tide models based on the suitable classification and appropriate error analysis because model structures are different even though the same/similar words (e.g., red-tide, algal bloom, phytoplankton growth, ecological or ecosystem models) are used. Thus, the references on the model classification are suggested and the advantage and disadvantage of the models are also suggested. The processes and methods on the performance test (quantitative error analysis) are recommend to the practical use of the red-tide model in the coastal seas. It is suggested in each stage of the modeling procedures, such as verification, calibration, validation, and application steps. These suggested references and methods can be attributed to the effective/efficient marine policy decision and the coastal ecosystem management plan setup considering the red-tide and/or ecological models uncertainty.