• Journal of Environmental Science International
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• v.27 no.11
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• pp.1141-1154
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• 2018

Numerical experiments were carried out to investigate the effect of data assimilation of observational data on weather and PM (particulate matter) prediction. Observational data applied to numerical experiment are aircraft observation, satellite observation, upper level observation, and AWS (automatic weather system) data. In the case of grid nudging, the prediction performance of the meteorological field is largely improved compared with the case without data assimilations because the overall pressure distribution can be changed. So grid nudging effect can be significant when synoptic weather pattern strongly affects Korean Peninsula. Predictability of meteorological factors can be expected to improve through a number of observational data assimilation, but data assimilation by single data often occurred to be less predictive than without data assimilation. Variation of air pressure due to observation nudging with high prediction efficiency can improve prediction accuracy of whole model domain. However, in areas with complex terrain such as the eastern part of the Korean peninsula, the improvement due to grid nudging were only limited. In such cases, it would be more effective to aggregate assimilated data.

• Journal of Environmental Impact Assessment
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• v.22 no.1
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• pp.39-50
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• 2013

Occurrence of landslides has been increasing due to extreme weather events(e.g. heavy rainfall, torrential rains) by climate change. Pyeongchang, Korea had seriously been damaged by landslides caused by a typhoon, Ewiniar in 2006. Moreover, the frequency and intensity of landslides are increasing in summer due to torrential rain. Therefore, risk assessment and adaptation measure is urgently needed to build resilience. To support landslide adaptation measures, this study predicted landslides occurrence using MaxEnt model and suggested susceptibility map of landslides. Precipitation data of RCP 8.5 Climate change scenarios were used to analyze an impact of increase in rainfall in the future. In 2050 and 2090, the probability of landslides occurrence was predicted to increase. These were due to an increase in heavy rainfall and cumulative rainfall. As a result of analysis, factors that has major impact on landslide appeared to be climate factors, prediction accuracy of the model was very high(92%). In the future Pyeongchang will have serious rainfall compare to 2006 and more intense landslides area expected to increase. This study will help to establish adaptation measure against landslides due to heavy rainfall.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.199-208
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• 2008

Prediction the performance of pavement provides proper information to an agency on decision-making process; especially evaluating the pavement performance and prioritizing the work plan. To date, there are a number of approaches to predict the future deterioration of pavements. However, there are some limitation to proper prediction of the pavement service life. In this paper, pavement performance model and pavement condition prediction model are developed in order to improve pavement condition prediction method. The prediction model of pavement condition through the regression analysis of real pavement condition is based on the probability distribution of pavement condition, which set to 5%, 15%, 25% and 50%, by condition of the pavement and traffic volume. The pavement prediction model presented from the behavior of individual pavement condition which are set to 5%, 15%, 25% and 50% of probability distribution. The performance of the prediction model is evaluated from analyzing the average, standard deviation of HPCI, and the percentage of HPCI which is lower than 3.0 of comparable section. In this paper, we will suggest the more rational method to determine the future pavement conditions, including the probabilistic duration and deterministic modeling methods regarding the impact of traffic volume, age, and the type of the pavement.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.35-44
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• 2020

In this study, we analyze how stock trend determination affects trend prediction accuracy. In stock markets, successful investment requires accurate stock price trend prediction. Therefore, a volume of research has been conducted to improve the trend prediction accuracy. For example, information extracted from SNS (social networking service) and news articles by text mining algorithms is used to enhance the prediction accuracy. Moreover, various machine learning algorithms have been utilized. However, stock trend determination has not been properly analyzed, and conventionally used methods have been employed repeatedly. For this reason, we formulate the trend determination as a moving average-based procedure and analyze its impact on stock trend prediction accuracy. The analysis reveals that trend determination makes prediction accuracy vary as much as 47% and that prediction accuracy is proportional to and inversely proportional to reference window size and target window size, respectively.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.61-68
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• 2022

In this paper, we propose a system to predict the GPS trajectory of a pedestrian based on a deep learning model. Pedestrian trajectory prediction is a study that can prevent pedestrian danger and collision situations through notifications, and has an impact on business such as various marketing. In addition, it can be used not only for pedestrians but also for path prediction of unmanned transportation, which is receiving a lot of spotlight. Among various trajectory prediction methods, this paper is a study of trajectory prediction using GPS data. It is a deep learning model-based study that predicts the next route by learning the GPS trajectory of pedestrians, which is time series data. In this paper, we presented a data set construction method that allows the deep learning model to learn the GPS route of pedestrians, and proposes a trajectory prediction deep learning model that does not have large restrictions on the prediction range. The parameters suitable for the trajectory prediction deep learning model of this study are presented, and the model's test performance are presented.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.3
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• pp.237-242
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• 2014

Recently much research are has been done into the compositions of lead-free solders. As a result, there has been a rapid increase in the number of new compositions. In the past, the properties of these new compositions were determined and verified through drop-impact tests. However, these drop tests were expensive and it took a long time to obtain a result. The main goal of this study was to establish an analytical method capable of predicting the impact life-time of a new solder composition for board-level flip chips though the application of drop simulations using LS-DYNA. Based on the reaction load obtain with LS-DYNA, the drop-impact fracture cycles were predicted. The study was performed using a Sn-3.0Ag-0.5Cu solder (305 composition). To verify the reliability of the proposed analytical method, the results of the drop-impact tests and life-time analysis were compared, and were found to be in good agreement. Thus, the new analytical method was shown to be very useful and effective.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.102-103
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• 2014

Due to the nature of the existing load, the criteria of assessing the intensity of the lightweight wall's impact resistance has been though of as obscure. The current study, therefore, focuses on the standardized assessment of the impact resistance to the force of the large soft body applying to the lightweight wall. The gypsum board wall showed a low level of the maximum residual displacement. It is, however, required to be careful about the selection of the finishing process since the high level of the maximum displacement is likely to cause harm to finishing materials. Unlike the gypsum board, the ALC block wall displayed a considerable rigidity while showing almost no maximum residual displacement. Even with the low level of the maximum displacement due to the stiffness, the ALC block wall is still likely to be affected by the vibration derived from any impact on the surface, which demands a need for additional study. The future experimental study, accordingly, will focus on the impact of the vibration on finishing materials, consequently leading to the accurate prediction of the possibility of potential damage to the lightweight wall caused by the large soft body.

• Ocean Systems Engineering
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• v.8 no.2
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• pp.223-246
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• 2018

In this paper the results of CFD simulations, that were carried out to study the impact pressures acting on a symmetric wedge during water entry under the influence of gravity, are presented. The simulations were done using a solver implementing finite volume discretization and using the VOF scheme to keep track of the free surface during water entry. The parameters such as pressure on impact, displacement, velocity, acceleration and net hydrodynamic forces, etc., which govern the water entry process are monitored during the initial stage of water entry. In addition, the results of the complete water entry process of wedges covering the initial stage where the impact pressure reaches its maximum as well as the late stage that covers the rebound process of the buoyant wedge are presented. The study was conducted for a few touchdown velocities to understand its influence on the water entry phenomenon. The simulation results are compared with the experimental measurements available in the literature with good accuracy. The various computational parameters (e.g., mesh size, time step, solver, etc.) that are necessary for accurate prediction of impact pressures, as well as the entry-exit trajectory, are discussed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.676-684
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• 2012

Numerical analysis was performed to investigate the heavy-weight impact noise of apartment houses. The FEM is practical method for prediction of low-frequency indoor noise. The results of numerical analysis, the shape of the acoustic modes in room-2 are similar to that of acoustic pressure field at the fundamental frequency of acoustic modes. And the acoustic pressure was amplified at the natural frequency of the acoustic modes and structural modes. The numerical analysis result of sound pressure level at 63 Hz and 125 Hz octave-band center frequency are similar to the test results, but at 250 Hz and 500 Hz have some errors. Considering most of bang-machine force spectrum exists below 100 Hz, the noise at 250 Hz and 500 Hz are not important for heavy-weight impact noise. Thus, the FEM numerical analysis method for heavy-weight impact noise can apply to estimate heavy-weight impact noise for various building systems.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.96-100
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• 2002

The purpose of this paper is presented a rational method of predicting dynamic/impact tensile strength of high tensile steel materials widely used fur structural material of automobiles. It is known that the ultimate strength is related with the loading speed and the Lethargy Coefficient from the tensile test. The Dynamic Lethargy Coefficient is proportional to the disorientation of the molecular structure and indicates the magnitude of defects resulting from the probability of breaking the bonds responsible for its strength. The coefficient is obtained from the simple tensile test such as failure time and stresses at fracture. These factors not only affect the static strength but also have a great influence on the dynamic/impact characteristics of the joist and the adjacent structures. This strength is used to analyze the failure life prediction of mechanical system by virtue of its material fracture. The impact tensile test is performed to evaluate the life parameters due to loading speed with the proposed method. Also the evaluation of the dynamic/impact effect on the material tensile strength characteristics is compared with the result of Campbell-Cooper equation to verify the proposed method.