• Journal of Advanced Marine Engineering and Technology
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• v.32 no.5
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• pp.785-790
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• 2008

A technique for determining the feedback gain of the states feedback controller using a real-coded genetic algorithm(RCGA) is presented. It is concerned with the states error to the performance index of a RCGA. As for assessing the performance of the controller three performance criteria (ISE. IAE and ITAE) are adopted. And designing the controller involves a constrained optimization problem. Therefore a real-coded genetic algorithm incorporating the penalty strategy is used. The performance of the proposed method is demonstrated through a set of simulation about an inverted pendulum system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.11
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• pp.1225-1232
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• 2009

This study suggests a structural design process for the upper control arm installed at a vehicle. Static strength and durability are the most important responses in the structural design of a control arm. This study considers the static strength in the optimization process. The inertia relief method for FE analysis is utilized to simulate the static loading conditions. According to the classification of structural optimization, the structural design of a control arm is included in the category of shape optimization. In this study, the metamodel technique using the kriging method is adopted to obtain the minimum weight satisfying the strength constraint. Then, the final design is suggested by considering the durability criteria. The durability assessment is obtained by the index of fatigue durability called the SWT (Smith-Watson-Topper) index. The final optimum shape has been proposed by trial and error method.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.288-293
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• 2005

In this study, SWAT model was applied to the Soyang Dam upstream watershed in order to evaluate the model applicability for estimating runoff, sediment, and nutrients loadings from the watershed. By trial and error method, the model parameters related with runoff, sediment, nitrogen and phosphorus were calibrated step by step. Then the simulated runoff, sediment, and nutrients loadings by the model were compared with the observed data measured at the Soyang Dam, the outlet of the watershed. And several statistical criteria were calculated to evaluate the model performance. From the comparison and statistical criteria, good agreement between simulated and observed stream flows was found. For sediment and nutrients, it was not reliable to quantitatively model the observed values, but the model could simulate the trend with reasonable accuracy. Hence, it was concluded that the model can be applied for the long-term non-point modeling in a large watershed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.3
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• pp.417-424
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• 2001

This paper proposes new symbol mapping method that can enhance the performance of trellis coded M-ary PSK compared with conventional symbol mapping methods in AWGN environment. Since the basic criteria of TCM design is Maximum Euclidean distance in AWGN, conventional symbol mapping method keep this basic criteria. In this paper, proposed new symbol mapping method uses both Euclidean distance and Hamming distance to design, while conventional methods make use of only optimal Euclidean distance. New symbol mapping method show the better BER performance than the other through computer simulation and error equations.

• Advances in concrete construction
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• v.10 no.6
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• pp.509-514
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• 2020

In the preliminary design phase of explosion-proof structures, the use of P-I diagram is useful. Based on the fact that the deformation criteria at failure or heavy damage is significantly larger than the yield deformation, a closed form solution of normalized P-I diagram is proposed using the complete plastic resistance curve. When actual sizes and material properties of RC structural component are considered, the complete plasticity assumption shows only a maximum error of 6% in terms of strain energy, and a maximum difference of 9% of the amount of explosives in CWSD. Thru comparison with four field test results, the same damage pattern was predicted in all four specimens.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.485-493
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• 2021

Groundwater is an important water resource that can be used along with surface water. In particular, in the case of island regions, research on groundwater level variability is essential for stable groundwater use because the ratio of groundwater use is relatively high. Researches using artificial intelligence models (AIs) for the prediction and analysis of groundwater level variability are continuously increasing. However, there are insufficient studies presenting evaluation criteria to judge the appropriateness of groundwater level prediction. This study comprehensively analyzed the research results that predicted the groundwater level using AIs for various regions around the world over the past 20 years to present the range of allowable groundwater level prediction errors. As a result, the groundwater level prediction error increased as the observed groundwater level variability increased. Therefore, the criteria for evaluating the adequacy of the groundwater level prediction by an AI is presented as follows: less than or equal to the root mean square error or maximum error calculated using the linear regression equations presented in this study, or NSE ≥ 0.849 or R² ≥ 0.880. This allowable prediction error range can be used as a reference for determining the appropriateness of the groundwater level prediction using an AI.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.25-37
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• 2017

A study on factors influencing measurement error of Ground-based LiDAR(Light Detection And Ranging) system was conducted in Kimnyeong wind turbine test site on Jeju Island. Three properties of wind including inclined angle, turbulence intensity and power law exponent were taken into account as factors influencing the measurement error of Ground-based LiDAR. In order to calculate LiDAR measurements error, 2.5-month wind speed data collected from LiDAR (WindCube v2) were compared with concurrent data from the anemometer on a nearby 120m-high meteorological mast. In addition, data filtering was performed and its filtering criteria was based on the findings at previous researches. As a result, at 100m above ground level, absolute LiDAR error rate with absolute inclined angle showed 4.58~13.40% and 0.77 of the coefficients of determination, $R^2$. That with turbulence intensity showed 3.58~23.94% and 0.93 of $R^2$ while that with power law exponent showed 4.71~9.53% and 0.41 of $R^2$. Therefore, it was confirmed that the LiDAR measurement error was highly affected by inclined angle and turbulence intensity, while that did not much depend on power law exponent.

• Journal of the Korean Society of Safety
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• v.33 no.1
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• pp.66-72
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• 2018

This study analyses the types, related operations, facilities, and causes of chemical accidents in Korea based on the RISCAD classification taxonomy. In addition, human error analysis was carried out employing different human error classification criteria. Explosion and fire were major accident types, and nearly half of the accidents occurred during maintenance operation. In terms of related facility, storage devices and separators were the two most frequently involved ones. Results of the human error-based analysis showed that latent human errors in management level are involved in many accidents as well as active errors in the field level. Action errors related to unsafe behavior leads to accidents more often compared with the checking behavior. In particular, actions missed and inappropriate actions were major problems among the unsafe behaviors, which implicates that the compliance with the work procedure should be emphasized through education/training for the workers and the establishment of safety culture. According to the analysis of the causes of the human error, the frequency of skill-based mistakes leading to accidents were significantly lower than that of rule-based and knowledge based mistakes. However, there was limitation in the analysis of the root causes due to limited information in the accident investigation report. To solve this, it is suggested to adopt advanced accident investigation system including the establishment of independent organization and improvement in regulation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.137-143
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• 2004

The electronic distance measurement(EDM) instrument, introduced first in the 1950s since those early days has, undergone continual refinement. Rapid advances established in related technologies have made it lighter, smaller and more precise equipment. Understanding for the principle, the standardized observation technique and the precision of EDM instrument is mostly important to improve the quality and the reliability of by-product in the field of engineering and industrial surveying. Periodical and accurate calibration is necessary to maintenance the precision of EDM instrument. This paper describes the calculated example of zero error and scale error as a correction of EDM by applying the least square method to baseline observations in test area. Also here we deal with the testing criteria for precision instrument testing according to different types of EDM instruments.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.78-96
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• 2023

Urban traffic information is collected by various systems such as VDS, DSRC, and radar. Recently, with the development of deep learning technology, smart intersection systems are expanding, are more widely distributed, and it is possible to collect a variety of information such as traffic volume, and vehicle type and speed. However, as a result of reviewing related literature, the performance evaluation criteria so far are rbs-based evaluation systems that do not consider the deep learning area, and only consider the percent error of 'reference value-measured value'. Therefore, a new performance evaluation method is needed. Therefore, in this study, individual error, interval error, and overall error are calculated by using a formula that considers deep learning performance indicators such as precision and recall based on data ratio and weight. As a result, error rates for measurement value 1 were 3.99 and 3.54, and rates for measurement value 2 were 5.34 and 5.07.