• Journal of The Korean Society of Grassland and Forage Science
• /
• v.41 no.1
• /
• pp.47-55
• /
• 2021

The objective of this study was to access the effect of climate and soil factors on alfalfa dry matter yield (DMY) by the contribution through constructing the yield prediction model in a general linear model considering climate and soil physical variables. The processes of constructing the yield prediction model for alfalfa was performed in sequence of data collection of alfalfa yield, meteorological and soil, preparation, statistical analysis, and model construction. The alfalfa yield prediction model used a multiple regression analysis to select the climate variables which are quantitative data and a general linear model considering the selected climate variables and soil physical variables which are qualitative data. As a result, the growth degree days(GDD) and growing days(GD), and the clay content(CC) were selected as the climate and soil physical variables that affect alfalfa DMY, respectively. The contributions of climate and soil factors affecting alfalfa DMY were 32% (GDD, 21%, GD 11%) and 63%, respectively. Therefore, this study indicates that the soil factor more contributes to alfalfa DMY than climate factor. However, for examming the correct contribution, the factors such as other climate and soil factors, and the cultivation technology factors which were not treated in this study should be considered as a factor in the model for future study.

• Journal of dental hygiene science
• /
• v.18 no.4
• /
• pp.252-264
• /
• 2018

The purpose of this study was to analyze the priorities of oral health education contents for preschool children by targeting teachers and parents using the Borich priority formula and The Locus for Focus Model. The survey was conducted in 212 teachers and 215 parents from December 26, 2017 to January 21, 2018. The priorities of oral health education contents were based on a 3-step analysis method, including the paired sample t-test, Borich priority formula, and The Locus for Focus Model. As a result of this study, the number of items about oral health education for preschool children that were prioritized by teachers was 7, while that by parents was 9. The top priorities that teachers and parents had in common were the following 5 items; "The progression of dental caries," "Symptoms of dental caries," "How to prevent dental caries," "Eruption sequence of permanent teeth," and "Method for emergency management of avulsed teeth." The teachers' priorities of the oral health education contents were the same between teachers and parents; "Eruption sequence of deciduous teeth" and "The function of the permanent teeth" were added. The parents' priorities of the oral health education contents were the same between teachers and parents; "The effect of fluoride application," "The number of permanent teeth," "How to prevent malocclusion," and "The appropriate timing of malocclusion treatment" were added. Based on the results of this study, when developing oral health education programs for teachers and parents, oral health education for teachers should include 7 items and oral health education for parents should include 9 items.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.3 no.1
• /
• pp.1-12
• /
• 1983

The wave and hydrologic climate at a beach location are everchanging and coastal engineers have always been interested in the deformation of the natural beach caused by wave action over short or long interval of time. The drift of sand on a beach particulary manifests itself when blocked construction of seawalls, jetties, breakerwaters and groins etc.${\cdots}$ For this reason, the understanding and evaluation of littoral drift has been especially important to the coastal engineers. The resulting of the sand drift movement, such as the type of beach profile, width of beach, storage volume of the littoral sand over the profile are rapid everchange. We have studied the geological changes due to the littoral drift on a beach with field investigation and model tests in laboratory. But, it is impossible to make quantative correct analysis because of the factors are everchange and complicate. And then, most of study are incline to qualitative analysis. In this paper, authors studied mainly on the transition of beach profile and sediment storage on the profile using statistical field data as qualitative analytical method. The used theoretical beach transition model by Sonu and Beek have developed to obtain the change of HAEUNDAE beach backed with seawall. Results of this study indicate that the transition model are useful in the analysis of beach profile changement and the littoral drift movement on the beach. Qualitative analysises for HAEUNDAE beach are as follows. 1) Transition sequence of profile has 4 major transition for one cycle. 2) Storage sediment model of beach profile by Sonu and Beek well coincided with HAEUNDAE beach. 3) Seasonal cycle has ill-balanced process for the 5-yr. investigation.

• Journal of Digital Convergence
• /
• v.19 no.5
• /
• pp.263-268
• /
• 2021

The purpose of this study was to propose a model which is suitable for the actual delivery system by designing a fetal delivery hospital operation management and fetal health classification model. The number of deaths during childbirth is similar to the number of maternal mortality rate of 295,000 as of 2017. Among those numbers, 94% of deaths are preventable in most cases. Therefore, in this paper, we proposed a model that predicts the health condition of the fetus using data like heart rate of fetuses, fetal movements, uterine contractions, etc. that are extracted from the Cardiotocograms(CTG) test using a random forest. If the redundancy of the data is unbalanced, This proposed model guarantees a stable management of the fetal delivery health management system. To secure the accuracy of the fetal delivery health management system, we remove the outlier which embedded in the system, by setting thresholds for the upper and lower standard deviations. In addition, as the proportion of the sequence class uses the health status of fetus, a small number of classes were replicated by data-resampling to balance the classes. We had the 4~5% improvement and as the result we reached the accuracy of 97.75%. It is expected that the developed model will contribute to prevent death and effective fetal health management, also disease prevention by predicting and managing the fetus'deaths and diseases accurately in advance.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.12
• /
• pp.653-662
• /
• 2016

This paper describes a test case generation algorithm for Simulink/Stateflow models based on the Rapidly exploring Random Tree (RRT) algorithm that has been successfully applied to path finding. An important factor influencing the performance of the RRT algorithm is the metric used for calculating the distance between the nodes in the RRT space. Since a test case for a Simulink/Stateflow (SL/SF) model is an input sequence to check a specific condition (called a test target in this paper) at a specific status of the model, it is necessary to drive the model to the status before checking the condition. A status maps to a node of the RRT. It is usually necessary to check various conditions at a specific status. For example, when the specific status represents an SL/SF model state from which multiple transitions are made, we must check multiple conditions to measure the transition coverage. We propose a unique distance calculation metric, based on the observation that the test targets are gathered around some specific status such as an SL/SF state, named key nodes in this paper. The proposed metric increases the probability that an RRT is extended from key nodes by imposing penalties to non-key nodes. A test case generation algorithm utilizing the proposed metric is proposed. Three models of Electrical Control Units (ECUs) embedded in a commercial vehicle are used for the performance evaluation. The performances are evaluated in terms of penalties and compared with those of the algorithm using a typical RRT algorithm.

• Journal of Korean Society of Disaster and Security
• /
• v.14 no.4
• /
• pp.17-27
• /
• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• Journal of the Korean Geotechnical Society
• /
• v.22 no.9
• /
• pp.45-59
• /
• 2006

The successful performance of any numerical geotechnical simulation depends on the accuracy and efficiency of the numerical implementation of constitutive model used to simulate the stress-strain (constitutive) response of the soil. The corner stone of the numerical implementation of constitutive models is the numerical integration of the incremental form of soil-plasticity constitutive equations over a discrete sequence of time steps. In this paper a well known two-surface soil plasticity model is implemented using a generalized implicit return mapping algorithm to arbitrary convex yield surfaces referred to as the Closest-Point-Projection method (CPPM). The two-surface model describes the nonlinear behavior of coarse-grained materials by incorporating a bounding surface concept together with isotropic and kinematic hardening as well as fabric formulation to account for the effect of fabric formation on the unloading response. In the course of investigating the performance of the CPPM integration method, it is proven that the algorithm is an accurate, robust, and efficient integration technique useful in finite element contexts. It is also shown that the algorithm produces a consistent tangent operator $\frac{d\sigma}{d\varepsilon}$ during the iterative process with quadratic convergence rate of the global iteration process.

• Journal of the Korean Geotechnical Society
• /
• v.25 no.10
• /
• pp.17-30
• /
• 2009

Underground construction such as tunneling can induce damages on the surrounding rock mass, due to the stress concentration of in situ stresses and excessive energy input during construction sequence, such as blasting. The developed damage on the rock mass can have substantial influence on the mechanical and hydraulic behaviors of the rock masses around a tunnel. In this study, investigation on the generation of damage around an opening in a jointed rock model under biaxial compression condition was conducted. The joint dip angles employed are 30, 45, and 60 degrees to the horizontal, and the synthetic rock mass was made using early strength cement and water. From the biaxial compression test, initiation and propagation of tensile cracks at norm to the joint angle were found. The propagated tensile cracks eventually developed rock blocks, which were dislodged from the rock mass. Furthermore, the propagation process of the tensile cracks varies with joint angle: lower joint angle model shows more stable and progressive tensile crack propagation. The development of the tensile crack can be explained under the hypothesis that the rock segment encompassed by the joint set is subjected to the developing moment, which can be induced by the geometric irregularity around the opening in the rock model. The experiment results were simulated by using discrete element method PFC 2D. From the simulation, as has been observed from the test, a rock mass with lower joint angle produces wider damage region and rock block by tensile cracks. In addition, a rock model with lower joint angle shows progressive tensile cracks generation around the opening from the investigation of the interacted tensile cracks.

• Journal of Soil and Groundwater Environment
• /
• v.10 no.5
• /
• pp.52-60
• /
• 2005

The conceptual model of under-sampled study area will include a great amount of uncertainty. In this study, we investigate the applicability of Markov chain model in a spatial domain as a tool for minimizing the uncertainty arose from the lack of data. A new formulation is developed to generalize the previous two-dimensional coupled Markov chain model, which has more versatility to fit any computational sequence. Furthermore, the computational algorithm is improved to utilize more conditioning information and reduce the artifacts, such as the artificial parcel inclination, caused by sequential computation. A generalized 20 coupled Markov chain (GCMC) is tested through applying a hypothetical soil map to evaluate the appropriateness as a substituting model for conventional geostatistical models. Comparing to sequential indicator model (SIS), the simulation results from GCMC shows lower entropy at the boundaries of indicators which is closer to real soil maps. For under-sampled indicators, however, GCMC under-estimates the presence of the indicators, which is a common aspect of all other geostatistical models. To improve this under-estimation, further study on data fusion (or assimilation) inclusion in the GCMC is required.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.18 no.2
• /
• pp.1-15
• /
• 2015

Urban flooding threatens human beings and facilities with chemical and physical hazards since the beginning of human civilization. Recent studies have emphasized the integration of data and models for effective urban flood inundation modeling. However, the model set-up process is tend to be time consuming and to require a high level of data processing skill. Furthermore, in spite of the use of high resolution grid data, inundation depth and velocity are varied with building treatment methods in 2-D inundation model, because undesirable grids are generated and resulted in the reliability decline of the simulation results. Thus, it requires building generalization process or enhancing building orthogonality to minimize the distortion of building before converting building footprint into grid data. This study aims to develop building generalization method for 2-dimensional inundation analysis to enhance the model reliability, and to investigate the effect of building generalization method on urban inundation in terms of geographical engineering and hydraulic engineering. As a result to improve the reliability of 2-dimensional inundation analysis, the building generalization method developed in this study should be adapted using Digital Building Model(DBM) before model implementation in urban area. The proposed building generalization sequence was aggregation-simplification, and the threshold of the each method should be determined by considering spatial characteristics, which should not exceed the summation of building gap average and standard deviation.