• Proceedings of the Korean Geotechical Society Conference
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• 1999.03a
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• pp.3-46
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• 1999

A new method called SRICOS is proposed to predict the scour depth z versus time t around a cylindrical bridge pier of diameter D founded in clay. The steps involved are ; 1. taking samples at the bridge pier site, 2. testing them in an Erosion Function Apparatus called the EFA to obtain the scour rate z versus the hydraulic shear stress applied $\tau$, 3. predicting the maximum shear stress r max which will be induced around the pier by the water flowing at ν Ο before the scour hole starts to develop, 4. using the measured z versus r curve to obtain the initial scour rate zi corresponding to r max , 5. predicting the maximum depth of scour zmax for the pier, 6. using zi and zmarx to develop the hyperbolic function describing the scour depth z versus time t curve, and 7. reading the z vs. t curve at a time corresponding to the duration of the flood to find the scour depth which will develop around the pier. A new apparatus is developed to measure the z vs t curve of step 2, a series of advanced numerical simulations are performed to develop an equation for the $\tau$ max value of step 3, and a series of flume tests are performed to develop an equation for the zmax value of step 5. The method is evaluated by comparing predictions and measurements in 42 flume experiments.

• Interaction and multiscale mechanics
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• v.1 no.2
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• pp.231-250
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• 2008

The statistical two-order and two-scale method is developed for predicting the mechanics parameters, such as stiffness and strength of core-shell particle-filled polymer composites. The representation and simulation on meso-configuration of random particle-filled polymers are stated. And the major statistical two-order and two-scale analysis formulation is briefly given. The two-order and two-scale expressions for the strains and stresses of conventionally strength experimental components, including the tensional or compressive column, the twist bar and the bending beam, are developed by means of their classical solutions with orthogonal-anisotropic coefficients. Then a new effective mesh generation algorithm is presented. The mechanics parameters of core-shell particle-filled polymer composites, including the expected stiffness parameters, minimum stiffness parameters, and the expected elasticity limit strength and the minimum elasticity limit strength, are defined by means of the stiffness coefficients and elasticity strength criterions for core, shell and matrix. Finally, the numerical results for predicting both stiffness and elasticity limit strength parameters are compared with the experimental data.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1058-1065
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• 2015

This paper present a current predicting control method for PMSM (permanent magnet synchronous motor) to improve the tracking performance of stator current, which regards the current vector as the control target. Solving the model state equation in the static frame (α-β frame), the dynamic change of current vector will be gained as three independent terms. These change terms, which contain the prediction of current vector, are discretized and simplified by Taylor series expansion and used to get the voltage vector as the predictive control quantity. SVPWM will transform the control voltage to the switching signal of inverter, which is newly deduced for the current vector. Simulation and experiment results are given to testy and verify the performance of this method.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.2
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• pp.14-24
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• 2021

This study aims to examine probable human errors when landing an airplane by the use of SHERPA(systematic human error reduction and prediction approach) and propose methods for preventing the predictive human errors. It has been reported that human errors are concerned with a lot of accidents or incidents of an airplane. It is significant to predict presumable human errors, particularly in the operation mode of human-automation interaction, and attempt to reduce the likelihood of predicted human error. By referring to task procedures and interviewing domain experts, we analyzed airplane landing task by using HTA(hierarchical task analysis) method. In total, 6 sub-tasks and 19 operations were identified from the task analysis. SHERPA method was used for predicting probable human error types for each task. As a result, we identified 31 human errors and predicted their occurrence probability and criticality. Based on them, we suggested a set of methods for minimizing the probability of the predicted human errors. From this study, it can be said that SHERPA can be effectively used for predicting probable human error types in the context of human-automation interaction needed for navigating an airplane.

• Journal of the Korea Safety Management & Science
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• v.16 no.3
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• pp.145-154
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• 2014

Performance based design(PBD) is the method to make a fire safety design against them after predicting the factors of fire risk in a building. Therefore, predicting fire risk in a building is very important process in PBD. For predicting fire risk of a building, an engineer of PBD must consider various factors such as ignition location, ignition point, ignition source, first ignited item, second ignited item, flash over, the state of door and fire suppression system. But, it is difficult to trust fire safety capacity of the design because the process in Korea' PBD is unprofessional and unreasonable. This paper had surveyed some cases of PBD that had been made in Korea to find the problems of the process to predict fire risk. And it have proposed the improvements of process to predict fire risk of a building.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.325-333
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• 1996

This study was conducted to develop neural networks of predicting the sugar content of fruits based on the optical densities obtained from a spectrophotometer. Pear, apple and peach were used in investigating the feasbility of the developed neural networks as a nondestructive measurement. A spectrophotometer was used to measure the optical densities of test fruits. The neural networks suggested in this study consisted of multi-layers having one hidden layer and one output layer. The correlation coefficients between the predicted and the measured sugar content for most fruits were high. The neural networks using 2nd derivatives of optical density spectrum produced a better results in predicting the sugar content of fruits. This study contributed to develop a method for nondestructively predicting the sugar content of fruits.

• 한국IT서비스학회:학술대회논문집
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• 2007.11a
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• pp.145-156
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• 2007

In the previous e-government studies, there was no study in which the ambitious problem of assessing the expected performance of an e-government software when it is adopted in other country. This study was motivated to propose a new method to resolve this research question. With using the KIPONet (Korean Intellectual Property Office Net) as a target e-government software, which has been successfully implemented and operated by the Republic of Korea government since Jan 1999 for the purpose of managing the intellectual property rights (IPRs), we propose a Hybrid Qualitative Reasoning (HQR) approach to predicting the expected performance of the KIPONet. The main recipes of the HQR are that the HQR considers causal relationships existing among both qualitative and quantitative variables of the KIPONet, and that uncertainties embedded in some variables are handled by using Monte Carlo mechanism. The application of the proposed HQR to predicting the expected performance of the KIPONet results in statistically significant outcomes with 95% confidence level.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.223-227
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• 2002

Wind tunnel test or CFD is used for predicting aerodynamic drag coefficient in domestic motor companies. But, wind tunnel test requires much cost and time, and CFD has a relatively large error. In this study a predicting program of the aerodynamic drag coefficient based on empirical techniques was developed. Also GRG method was added to the program in order to decide optimal values of some parameters. The program was applied to 24 cars and the aerodynamic drag coefficients were predicted with 4.82% average error. Optimization was also accomplished to 6 cars. Some parameters to be modified were determined (1) to reduce the afterbody drag coefficient to the value established by a designer and (2) to preserve the same drag coefficient as the original automotive when some parameters have to be changed in the viewpoint of design. It was verified that the developed program can predict the aerodynamic drag coefficient appropriately and determine optimal values of some parameters.

• Journal of Integrative Natural Science
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• v.12 no.1
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• pp.14-19
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• 2019

In this paper, we propose a system for controlling the brightness of street lights by predicting pedestrian paths, identifying the position of pedestrians with motion sensing sensors and obtaining motion vectors based on past walking directions, then predicting pedestrian paths through the route prediction smart street lighting system. In addition, by using motion vector data, the pre-treatment process using linear interpolation method and the fuzzy system and neural network system were designed in parallel structure to increase efficiency and the rough set was used to correct errors. It is expected that the system proposed in this paper will be effective in securing the safety of pedestrians and reducing light pollution and energy by predicting the path of pedestrians in the detection of movement of pedestrians and in conjunction with smart street lightings.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.304-307
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• 2013

Various programs have been developed to predict the energy consumption of a building as a result of recent increased social interest in the environmental friendliness of construction as measured by energy efficiency. The goal of environmental-friendliness, which is achieved by predicting the energy consumption of a building, can be realized in the design stage by applying a variety of technologies, planning factors and planning systems. However, most energy analyzing engines are only suitable for use in the advanced stages of design because of the large amount of design information that must be entered. Thus, because the simulation programs currently used are not suitable for use in the early stages of design, this study suggests a prediction logic that provides an overview of the energy consumption of a building according to its size, scope, and purpose by analyzing statistics collected by government agencies.