• Proceedings of the KOR-KST Conference
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• 1997.12a
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• pp.33-69
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• 1997

This study was conducted to develop a methodology to predict utility pole accident rates and to evaluate cost-effectiveness for safety improvement for utility pole accidents. The utility pole accident rate prediction model was based on the encroachment rate approach introduced in the Transportation Research Board Special Report 214. The utility pole accident rate on a section of highway depends on the roadside encroachment rate and the lateral extent of encroachment. The encroachment rate is influenced by the horizontal and vertical alignment of the highway as well as traffic volume and mean speed. The lateral extent of encroachment is affected by the horizontal and vertical alignment, the mean speed and the roadside slope. An analytical method to generate the probability distribution function for the lateral extent of encroachment was developed for six kinds of encroachment types by the horizontal alignment and encroachment direction. The encroachment rate was calibrated with the information on highway and roadside conditions and the utility pole accident records collected on the sections of 55mph speed limit of the State Trunk Highway 12 in Wisconsin. The encroachment rate on a tangent segment was calibrated as a function of traffic volume with the actual average utility pole accident rates by traffic volume strategies. The adjustment factors for horizontal and vertical alignment were then derived by comparing the actual average utility pole accident rates to the estimations from the model calibrated for tangent and level sections. A computerized benefit-cost analysis procedure was then developed as a means of evaluating alternative countermeasures. The program calculates the benefit-cost ratio and the percent of reduction of utility pole accidents resulting from the implementation of a safety improvement. This program can be used to develop safety improvement: alternatives for utility pole accidents when a predetermined performance level is specified.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.6 no.2
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• pp.139-149
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• 1994

In this paper, a finite element technique is applied to the prediction of the wave resonance phenomena in harbors. The mild-slope equation is used with a partial reflection boundary condition introduced to model the energy dissipating effects on the solid boundary. For an efficient modeling of the radiation condition at infinity, a new infinite element is developed. The shape function of the infinite element is derived from the asymptotic behavior of the first kind of the Hankel's function in the analytical boundary series solutions. For the computational efficiency, the system matrices of the element are constructed by performing the relevant integrations in the infinite direction analytically. Comparisons with the results from experiments and other solution methods show that the present model gives fairly good results. Numerical experiments are also carried out to determine the proper distance to the infinite elements from the mouth of the halter, which directly affect the accuracy and efficiency of the solution.

• Proceedings of the KOR-KST Conference
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• 1997.12b
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• pp.35-72
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• 1997

This study was conducted to develop a methodology to predict utility pole accident rates and to evaluate cost-effectiveness for safety improvement for utility pole accidents. The utility pole accident rate prediction model was based on the encroachment rate approach introduced in the Transportation Research Board special Report 214. The utility pole accident rate on a section of highway depends on the roadside encroachment rate and the lateral extent of encroachment. The encroachment rate is influenced by the horizontal and vertical alignment of the highway as well as traffic volume and mean speed. The lateral extent of encroachment is affected by the horizontal and vertical alignment, the mean speed and the roadside slope. An analytical method to generate the probability distribution function for the lateral extent of encroachment was developed for six kinds of encroachment types by the horizontal alignment and encroachment direction. The encroachment rate was calibrated with the information on highway and roadside conditions and the utility pole accident records collected on the sections of 55mph speed limit of the State Trunk Highway 12 in Wisconsin. The encroachment rate on tangent segment was calibrated as a function of traffic volume with the actual average utility pole accident rates by traffic volume strategies. The adjustment factors for horizontal and vertical alignment were when derived by comparing the actual average utility pole accident rates to the estimations from the model calibrated for tangent and level sections. A computerized benefit-cost analysis procedure was then developed as a means of evaluating alternative countermeasures. The program calculates the benefit-cost ratio and the percent of reduction of utility pole accidents resulting from the implementation of a safety improvement. This program can be used to develop safety improvement alternatives for utility pole accidents when a predetermined performance level is specified.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.395-406
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• 2016

Population and development are concentrated by urbanization. Consequently, the usage of underground area and the riverside area have been increased. By increasing impermeable layer, the urban basin drainage is depending on level of sewer. Flood damage is occurred by shortage of sewer capacity and poor interior drainage at river stage. Many of researches about flood stress the unavailability of connection at the river stage with the internal inundation organically. In this study, flood calculated considering rainfall and combined inland-river. Also, using urban runoff model analyze the overflow of sewer. By using results of SWMM model, using flood inundation analysis model analyzed internal drainage efficiency of drainage system. Applying SWMM model, which results to flood inundation analysis model, analyzes internal drainage efficiency of drainage system under localized heavy rain in a basin of the city. The results of SWMM model show the smoothness of internal drainage can be impossible to achieve because of the influence of the river level and sewer overflow appearing. The main manholes were selected as the manhole of a lot of overflow volume. Overflow reduction scenarios were selected for expansion of sewer conduit and instruction retention pond. Overflow volume reduces to 45% and 33~64% by retention pond instruction and sewer conduit expansion. In addition, the results of simulating of flood inundation analysis model show the flood occurrence by road runoff moving along the road slope. Flooded area reduces to 19.6%, 60.5% in sewer conduit expansion scenarios.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.262-276
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• 2018

Models to predict Leaf Wetness Duration (LWD) were evaluated using the observed meteorological and dew data at the 11 citrus orchards in Jeju, South Korea from 2016 to 2017. The sensitivity and the prediction accuracy were evaluated with four models (i.e., Number of Hours of Relative Humidity (NHRH), Classification And Regression Tree/Stepwise Linear Discriminant (CART/SLD), Penman-Monteith (PM), Deep-learning Neural Network (DNN)). The sensitivity of models was evaluated with rainfall and seasonal changes. When the data in rainy days were excluded from the whole data set, the LWD models had smaller average error (Root Mean Square Error (RMSE) about 1.5hours). The seasonal error of the DNN model had the similar magnitude (RMSE about 3 hours) among all seasons excluding winter. The other models had the greatest error in summer (RMSE about 9.6 hours) and the lowest error in winter (RMSE about 3.3 hours). These models were also evaluated by the statistical error analysis method and the regression analysis method of mean squared deviation. The DNN model had the best performance by statistical error whereas the CART/SLD model had the worst prediction accuracy. The Mean Square Deviation (MSD) is a method of analyzing the linearity of a model with three components: squared bias (SB), nonunity slope (NU), and lack of correlation (LC). Better model performance was determined by lower SB and LC and higher NU. The results of MSD analysis indicated that the DNN model would provide the best performance and followed by the PM, the NHRH and the CART/SLD in order. This result suggested that the machine learning model would be useful to improve the accuracy of agricultural information using meteorological data.

• Journal of the Korean Geographical Society
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• v.40 no.3 s.108
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• pp.296-309
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• 2005

In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.

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

• The Journal of Engineering Geology
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• v.24 no.4
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• pp.643-648
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• 2014

Understanding of fracture networks and rock mass properties during tunnel construction is extremely important for the prediction of dangers during excavation, and for deciding on appropriate excavation techniques and support. However, rapid construction process do not allow sufficient time for surveys and interpretations for spatial distributions of fractures and rock mass properties. This study introduces a new statistical approach for predicting joint distributions at foreside of current excavation face during the excavation process. The proposed methodology is based on a cumulative space diagram for joint sets. The diagram displays the cumulative spacing between adjacent joints on the vertical axis and the sequential position of each joint plotted at equally spaced intervals on the horizontal axis. According to the diagram, the degree of linearity of points representing the regularity of joint spacing; a linear trend of the points indicates that the joints are evenly spaced, with the slope of the line being directly related to the spacing. The linear points which are stepped indicates that the fracture set show clustered distribution. A clustered pattern within the linear group of points indicates a clustered joint distribution. Fractures surveyed from an excavated space can be plotted on this diagram, and the diagram can then be extended further according to the plotted diagram pattern. The extension of the diagram allows predictions about joint spacing in areas that have not yet been excavated. To test the model, we collected and analyzed data during excavation of a 10-m-long tunnel. Fractures in a 3-m zone behind the excavation face were predicted during the excavation, and the predictions were compared with observations. The methodology yielded reasonably good predictions of joint locations.

• Journal of Korea Water Resources Association
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• v.44 no.2
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• pp.157-167
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• 2011

A numerical model was developed to predict the stage-discharge curve and lateral distribution of unit discharge in open channels with nonuniform cross section or compound open-channels. The governing equation is the one-dimensional momentum equation based on assumptions of the steady and uniform flow conditions in the longitudinal direction and the uniform water surface elevation in a cross section. Vegetative drag force term was included in governing equation in order to reflect the effect of floodplain vegetation on the flow characteristics. Finite element method was applied to obtain the numerical solution of the governing equation. Stage-discharge curve and lateral distribution of unit discharge for a given water surface are calculated based on input data, such as the cross sectional geometry, Manning's roughness coefficient, vegetative information and longitudinal slope of channel bed. The developed model was verified by comparing the calculated results with the observed data and the results of Darby and Thorne's(1996) model and the nonlinear k-$\epsilon$ model. The verified model was applied to estimate the upstream boundary conditions in two-dimensional flow model. The numerical results using laterally distributed unit discharge were compared with those obtained using uniformly distributed unit discharge in two-dimensional flow model.

• Spatial Information Research
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• v.20 no.1
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• pp.9-18
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• 2012

South Korea has many landslides caused by heavy rains during summer time recently and the landslides continue to cause damages in many places. These landslides occur repeatedly each year, and the frequency of landslides is expected to increase in the coming future due to dramatic global climate change. In Korea, 81.5% of the population is living in urban areas and about 1,055 million people are living in Seoul. In 2011, the landslide that occurred in Seocho-dong killed 18 people and about 9% of Seoul's area is under the same land conditions as Seocho-dong. Even the size of landslide occurred in a city is small, but it is more likely to cause a big disaster because of a greater population density in the city. So far, the effort has been made to identify landslide vulnerability and causes, but now, the new dem and arises for the prediction study about the areal extent of disaster area in case of landslides. In this study, the diffusion model of the landslide disaster area was established based on Cellular Automata(CA) to analyze the physical diffusion forms of landslide. This study compared the accuracy with the Seocho-dong landslide case, which occurred in July 2011, applying the SCIDDICA model and the CAESAR model. The SCIDDICA model involves the following variables, such as the movement rules and the topographical obstacles, and the CAESAR model is also applied to this process to simulate the changes of deposition and erosion.