• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1141-1141
• /
• 2001

The aim of the study was to evaluate the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural network (ANN) on the prediction of chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with information relative to moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected with 10 different Foss NIR Systems instruments, which were either standardized or not standardized to one master instrument. The spectra were trimmed to a wavelength range between 1100 and 2498 nm. Two data sets, one standardized (IVAL) and the other not standardized (SVAL) were used as independent validation sets, but 10% of both sets were omitted and kept for later expansion of the calibration database. The remaining samples were combined into one database (n=21,696), which was split into 75% calibration (CALBASE) and 25% validation (VALBASE). The chemical components in the 3 validation data sets were predicted with each model derived from CALBASE using the calibration database before and after it was expanded with 10% of the samples from IVAL and SVAL data sets. Calibration performance was evaluated using standard error of prediction corrected for bias (SEP(C)), bias, slope and R2. None of the models appeared to be consistently better across all validation sets. VALBASE was predicted well by all models, with smaller SEP(C) and bias values than for IVAL and SVAL. This was not surprising as VALBASE was selected from the calibration database and it had a sample population similar to CALBASE, whereas IVAL and SVAL were completely independent validation sets. In most cases, Local and ANN models, but not modified PLS, showed considerable improvement in the prediction of IVAL and SVAL after the calibration database had been expanded with the 10% samples of IVAL and SVAL reserved for calibration expansion. The effects of sample processing, instrument standardization and differences in reference procedure were partially confounded in the validation sets, so it was not possible to determine which factors were most important. Further work on the development of large databases must address the problems of standardization of instruments, harmonization and standardization of laboratory procedures and even more importantly, the definition of the database population.

• Journal of the Korean earth science society
• /
• v.28 no.2
• /
• pp.214-226
• /
• 2007

Because precipitation is influenced by various atmospheric variables, it is highly nonlinear. Although precipitation predicted by a dynamic model can be corrected by using a nonlinear Artificial Neural Network, this approach has limits such as choices of the initial weight, local minima and the number of neurons, etc. In the present paper, we correct simulated precipitation by using a multiple linear regression (MLR) method, which is simple and widely used. First of all, Ensemble hindcast is conducted by the PNU/CME Coupled General Circulation Model (CGCM) (Park and Ahn, 2004) for the period from April to August in 1979-2005. MLR is applied to precipitation simulated by PNU/CME CGCM for the months of June (lead 2), July (lead 3), August (lead 4) and seasonal mean JJA (from June to August) of the Northeast Asian region including the Korean Peninsula $(110^{\circ}-145^{\circ}E,\;25-55^{\circ}N)$. We build the MLR model using a linear relationship between observed precipitation and the hindcasted results from the PNU/CME CGCM. The predictor variables selected from CGCM are precipitation, 500 hPa vertical velocity, 200 hPa divergence, surface air temperature and others. After performing a leave-oneout cross validation, the results are compared with the PNU/CME CGCM's. The results including Heidke skill scores demonstrate that the MLR corrected results have better forecasts than the direct CGCM result for rainfall.

• Journal of Korea Water Resources Association
• /
• v.43 no.11
• /
• pp.995-1009
• /
• 2010

Accelerated soil erosion due to extreme climate change, such as increased rainfall intensity, and human-induced environmental changes, is a widely recognized problem. Existing soil erosion models are generally based on the gross erosion concept to compute annual upland soil loss in tons per acre per year. However, such models are not suitable for event-based simulations of erosion and deposition in time and space. Recent advances in computer geographic information system (GIS) technologies have allowed hydrologists to develop physically based models, and the trend in erosion prediction is towards process-based models, instead of conceptually lumped models. This study aims to propose an effective and robust distributed rainfall-sediment yield-runoff model consisting of basic element modules: a rainfall-runoff module based on the kinematic wave method for subsurface and surface flow, and a runoff-sediment yield-runoff model based on the unit stream power method. The model was tested on the Cheoncheon catchment, upstream of the Yongdam dam using hydrological data for three extreme flood events due to typhoons. The model provided acceptable simulation results with respect to both discharge and sediment discharge even though the simulated sedigraphs were underestimated, compared to observations. The spatial distribution of erosion and deposition demonstrated that eroded sediment loads were deposited in the cells along the channel network, which have a short overland flow length and a gentle local slope while the erosion rate increased as rainfall became larger. Additionally, spatially heterogeneous rainfall intensity, dependant on Thiessen polygons, led to spatially-distinct erosion and deposition patterns.

• The Journal of Bigdata
• /
• v.5 no.2
• /
• pp.17-27
• /
• 2020

District heating system supplies heat from low-cost high-efficiency heat production facilities to heat demand areas through a heat pipe network. For efficient heat supply system operation, it is important to accurately predict the heat demand within the region and optimize the heat production plan accordingly. In this study, a heat demand forecasting model is proposed considering real-time calorimeter information from local heat demands. Previous models considered ambient temperature and heat demand history data to predict future heat demands. To improve forecast accuracy, the proposed heat demand forecast model added big data from real-time calorimeters installed in the heat demands within the target region. By employing calorimeter information directly in the model, it is expected that the proposed forecast model is to reflect heat use pattern of each demand. Computational experiemtns based on the actual heat demand data shows that the forecast accuracy of the proposed model improved when the calorimeter big data is reflected.

• Journal of Korea Water Resources Association
• /
• v.49 no.7
• /
• pp.589-597
• /
• 2016

In this study, we investigated the use of satellite-derived flow (SDF) signals and a data-based model for the estimation of outflow for the river reach where in situ measurements are either completely unavailable or are difficult to access for hydraulic and hydrology analysis such as the upper basin of Imjin River. It has been demonstrated by many studies that the SDF signals can be used as the river width estimates and the correlation between SDF signals and river width is related to the shape of cross sections. To extract the nonlinear relationship between SDF signals and river outflow, Artificial Neural Network (ANN) model with SDF signals as its inputs were applied for the computation of flow discharge at Imjin Bridge located in Imjin River. 15 pixels were considered to extract SDF signals and Partial Mutual Information (PMI) algorithm was applied to identify the most relevant input variables among 150 candidate SDF signals (including 0~10 day lagged observations). The estimated discharges by ANN model were compared with the measured ones at Imjin Bridge gauging station and correlation coefficients of the training and validation were 0.86 and 0.72, respectively. It was found that if the 1 day previous discharge at Imjin bridge is considered as an input variable for ANN model, the correlation coefficients were improved to 0.90 and 0.83, respectively. Based on the results in this study, SDF signals along with some local measured data can play an useful role in river flow estimation and especially in flood forecasting for data-scarce regions as it can simulate the peak discharge and peak time of flood events with satisfactory accuracy.

• Information Systems Review
• /
• v.20 no.2
• /
• pp.63-85
• /
• 2018

Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.

• Journal of Environmental Impact Assessment
• /
• v.24 no.2
• /
• pp.134-153
• /
• 2015

When making urban planning, it is important to understand climate effect caused by urban structural changes. Seoul city applies UPIS(Urban Plan Information System) which provides information on urban planning scenario. Technology for analyzing climate effect resulted from urban planning needs to developed by linking urban planning scenario provided by UPIS and climate analysis model, CAS(Climate Analysis Seoul). CAS develops for analyzing urban climate conditions to provide realistic information considering local air temperature and wind flows. Quantitative analyses conducted by CAS for the production, transportation, and stagnation of cold air, wind flow and thermal conditions by incorporating GIS analysis on land cover and elevation and meteorological analysis from MetPhoMod(Meteorology and atmospheric Photochemistry Meso-scale model). In order to reflect land cover and elevation of the latest information, CAS used to highly accurate raster data (1m) sourced from LiDAR survey and KOMPSAT-2(KOrea Multi-Purpose SATellite) satellite image(4m). For more realistic representation of land surface characteristic, DSM(Digital Surface Model) and DTM(Digital Terrain Model) data used as an input data for CFD(Computational Fluid Dynamics) model. Eight inflow directions considered to investigate the change of flow pattern, wind speed according to reconstruction and change of thermal environment by connecting green area formation. Also, MetPhoMod in CAS data used to consider realistic weather condition. The result show that wind corridors change due to reconstruction. As a whole surface temperature around target area decreases due to connecting green area formation. CFD model coupled with CAS is possible to evaluate the wind corridor and heat environment before/after reconstruction and connecting green area formation. In This study, analysis of climate impact before and after created the green area, which is part of 'Connecting green network across the north and south in Seoul' plan, one of the '2020 Seoul master plan'.

• Journal of the Korea Convergence Society
• /
• v.7 no.6
• /
• pp.259-266
• /
• 2016

The purpose of this study is to explore the feasibility of establishing the elderly protection system for the elderly in the local community, and to explore the linkage model and action strategy. In Korea, there is a need to build a comprehensive elderly care system so that elderly people can have appropriate counseling and support programs in the community, as the elderly increase their diverse needs (leisure, housing, employment). In this study, we set up a linkage model of elderly care system and suggested two ways to practice it. First, it is suggested that it is desirable to focus on the formation of the elderly protection system in the community, and divide the practice process into three stages: organization, practice, and organization. Second, it is necessary to apply the long-term care professional manpower which can play a central role such as care manager and nursing care provider in order to apply the community organizing model of the elderly protection system and stable operation of long-term care insurance for the elderly. In addition, a social welfare council and a private network should be established to form a social welfare council, the establishment of related legal provisions, and the education of care managers. Therefore, it is necessary to establish basic data through this study, to establish diverse strategies and plans for the elderly protection system, and to promote it in a phased manner.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.8 no.2
• /
• pp.159-166
• /
• 2010

The block-scale groundwater flow system at Olkiluoto site in Finland was simulated. The heterogeneous and anisotropic hydraulic conductivity field for the domain was constructed from the discrete fracture network, which considered only the fractured zones identified in the deep boreholes installed in the study site. The groundwater flow model was calibrated by adjusting the recharge rate and the transmissivities of the fractured zones to fit the calculated hydraulic heads and into- and out-flow rates in the observation intervals of the boreholes with the observed ones. In the calibrated model, the calculated flow rates at some intervals were not in accordance with the observed ones although the calculated hydraulic heads fit well with the observed ones, which revealed that the number of the conduits for groundwater flow is insufficient in the conceptual model for groundwater flow modeling. Therefore, it was recommended that the potential local conduits such as background fractures should be added to the present conceptual model.

• Informatization Policy
• /
• v.24 no.3
• /
• pp.67-90
• /
• 2017

This study is conducted to find out problems in the implementation system of regional informatization policies in Korea and solutions to enhance the effectiveness in policy execution. The study uses research methodologies such as participant observation, interview and AHP for experts and employees of public organizations for regional informatization policies. Many implications were found in the analysis, including that policy relations, structure of the policy implementation system, and environment and contents of regional informatization policiesin Korea have to be innovated and re-organized. Especially, this paper emphasizes the horizontal and cooperative relationship between the central and local governments and redesigning of the legal system on the regional informatization. This paper also shows expectations on reshaping of the regional informatization policies with the paradigm shift of the government power toward decentralization. This paper also finds diverse views on the problems and solutions for the regional informatization policy implementation system based on different characteristics and interests of policy participants. This paper finds the possibility of applying the policy network model to regional informatization policy implementation, which can be supported by Rhodes & Marsh(1992)'s theory. Therefore, this paper shows the change of regional informatization policies can be expected through application of the policy network. Although the paper draws many academic and policy implications, they are limited to the implementation system of regional informatization policies only.