• Geotechnical Engineering
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• v.10 no.4
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• pp.17-28
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• 1994

It is well known that human brain has the advantage of handling disperse and parallel distributed data efficiently. On the basic of this fact, artificial neural networks theory was developed and has been applied to various fields of science successfully. In this study, error back propagation algorithm which is one of the teaching technique of artificial neural networks is applied to predict ultimate bearing capacity of pile foundations. For the verification of applicability of this system, a total of 28 data of model pile test results are used. The 9, 14 and 21 test data respectively out of the total 28 data are used for training the networks, and the others are used for the comparison between the predicted and the measured. The results show that the developed system can provide a good matching with model pile test results by training with data more than 14. These limited results show the possibility of utilizing the neural networks for pile capacity prediction problems.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.5
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• pp.803-812
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• 2002

Reverse engineering has been widely used for the shape reconstruction of an object without CAD data and the measurement of clay or wood models for the development of new products. To generate a surface from measured points by a laser scanner, typical steps include the scanning of a clay or wood model and the generation of manufacturing data like STL file. A laser scanner has a great potential to get geometrical data of a model for its fast measuring speed and higher precision. The data from a laser scanner are composed of many line stripes of points. A new approach to remove point data with Delaunay triangulation is introduced to deal with problems during reverse engineering process. The selection of group of triangles to be triangulated based on the angle between triangles is used for robust and reliable implementation of Delaunay triangulation as preliminary steps. Developed software enables the user to specify the criteria for the selection of group of triangles either by the angle between triangles or the percentage of triangles reduced. The time and error for handling point data during modelling process can be reduced and thus RP models with accuracy will be helpful to automated process.

• Korean Journal of Optics and Photonics
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• v.19 no.6
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• pp.422-428
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• 2008

The pitch tool provides superior surface roughness compared to other types of polishing tool. However, because of difficulty in handling the pitch tool, pitch tool polishing has rarely been analysed, which led many craftsman to eliminate the pitch tool from their experiences. We found that it was possible to use a pitch tool in the well-determined material removal after the completion of computer simulation and experiment. We could simulate the TIF of the pitch tool with 79% accuracy. Also, after five successive simulations of polishing process on a 280 mm optical flat, the surface p-v error was found to be reduced from $1{\mu}m$ to 168 nm.

• The Korean Journal of Malacology
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• v.30 no.4
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• pp.383-390
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• 2014

The multiplex PCR system including six microsatellites from Haliotis discus hannai, consisting of dinucleotide and trinucleotide repeat units, is developed. The six loci were coamplified in a single reaction employing dye-labeled primers. Alleles from these loci were sized using an internal standard by automated sample processing in an ABI3100 Genetic Analyser. Amplified alleles in profiles containing selected microsatellites were typed clearly, providing easily interpretable results. In this results suggest that the presented multiplex PCR system may be a useful tool in a selective breeding program of H. discus hannai in which genetic identification will allow different genotypes to be reared together from fertilization. This should have a great impact as it will make selective breeding more efficient. Moreover, it will be useful in a variety of applications, including strain and hybrid identification, parentage assignment, pedigree reconstruction, estimating genetic diversity and/or inbreeding.

• Proceedings of the Korean System Dynamics Society
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• 2002.02a
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• pp.19-40
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• 2002

The intent of this study is to develop system dynamics model for assessment of organizational and human factors in nuclear power plant which can contribute to secure the nuclear safety. Previous studies are classified into two major approaches. One is engineering approach such as ergonomics and probability safety assessment(PSA). The other is social science approach such like sociology, organization theory and psychology. Both have contributed to find organization and human factors and to present guideline to lessen human error in NPP. But, since these methodologies assume that relationship among factors is independent they don't explain the interactions among factors or variables in NPP. To overcome these limits, we have developed system dynamics model which can show cause and effect among factors and quantify organizational and human factors. The model we developed is composed of 16 functions of job process in nuclear power, and shows interactions among various factors which affects employees' productivity and job quality. Handling variables such like degree of leadership, adjustment of number of employee, and workload in each department, users can simulate various situations in nuclear power plant in the organization side. Through simulation, user can get insight to improve safety in plants and to find managerial tools in the organization and human side. Analyzing pattern of variables, users can get knowledge of their organization structure, and understand stands of other departments or employees. Ultimately they can build learning organization to secure optimal safety in nuclear power plant.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.2
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• pp.98-103
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• 2002

In case of power demand forecasting, the most important problems are to deal with the load of special-days. Accordingly, this paper presents the method that forecasting long (the Lunar New Year, the Full Moon Festival) and short(the Planting Trees Day, the Memorial Day, etc) special-days peak load using neural networks and regression models. long and short special-days peak load forecast by neural networks models uses pattern conversion ratio and four-order orthogonal polynomials regression models. There are using that special-days peak load data during ten years(1985∼1994). In the result of special-days peak load forecasting, forecasting % error shows good results as about 1 ∼2[%] both neural networks models and four-order orthogonal polynomials regression models. Besides, from the result of analysis of adjusted coefficient of determination and F-test, the significance of the are convinced four-order orthogonal polynomials regression models. When the neural networks models are compared with the four-order orthogonal polynomials regression models at a view of the results of special-days peak load forecasting, the neural networks models which uses pattern conversion ratio are more effective on forecasting long special-days peak load. On the other hand, in case of forecasting short special-days peak load, both are valid.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.321-340
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• 2016

The Compressive Video Sensing (CVS) is a useful technology for wireless systems requiring simple encoders but handling more complex decoders, and its rate-distortion performance is highly affected by the quantization of measurements and reconstruction of video frame, which motivates us to presents the Space-Time Quantization (ST-Q) and Motion-Aligned Reconstruction (MA-R) in this paper to both improve the performance of CVS system. The ST-Q removes the space-time redundancy in the measurement vector to reduce the amount of bits required to encode the video frame, and it also guarantees a low quantization error due to the fact that the high frequency of small values close to zero in the predictive residuals limits the intensity of quantizing noise. The MA-R constructs the Multi-Hypothesis (MH) matrix by selecting the temporal neighbors along the motion trajectory of current to-be-reconstructed block to improve the accuracy of prediction, and besides it reduces the computational complexity of motion estimation by the extraction of static area and 3-D Recursive Search (3DRS). Extensive experiments validate that the significant improvements is achieved by ST-Q in the rate-distortion as compared with the existing quantization methods, and the MA-R improves both the objective and the subjective quality of the reconstructed video frame. Combined with ST-Q and MA-R, the CVS system obtains a significant rate-distortion performance gain when compared with the existing CS-based video codecs.

• Structural Engineering and Mechanics
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• v.74 no.6
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• pp.771-787
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• 2020

The paper provides an inside look into experimental measurements, followed by numerical simulations and their related uncertainties. The goal of the paper is to present findings related to blast loading and the handling of defects that are inherent in experiments. Very often it might seem that experiments are simplified reflections of real-life conditions. In most cases this is true, but there is a good reason for that. The more complex an experiment is, the larger the amount of uncertainties that can be expected. This especially applies when the blast loading of concrete is the subject of research. When simulations fail to reproduce the results of experimental measurements, it does not necessarily mean there is something wrong with the numerical model. The problem could be missing information. Put differently, the numerical simulation may lack information that seemed irrelevant with regard to the experiment. In the presented case, a reference simulation with a proven material model unexpectedly failed to replicate the results of an experiment where concrete slabs were exposed to blast loading. This resulted in a search for possible unknowns. When all of the uncertainties were examined, the missing information turned out to be the orientation of the charge to the concrete slab. Since the experiment was burdened with error, a sensitivity study had to take place so the influence of this factor could be better understood. The findings point to the fact that even the smallest defect during experiments must somehow be taken into account when designing numerical simulations. Otherwise, the simulations are not correlated to the experiments, but merely to some expectations.

• Journal of the Korean Society of Safety
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• v.22 no.2 s.80
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• pp.59-66
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• 2007

As the need of handling heavy materials increases, various cranes are used in industries. However, the effectiveness of crane also entails industrial accidents such as falling, constriction etc. In fact, the number of fatal accidents caused by crane is still high in Korea. To find out the causes of the accidents in terms of human error, we developed a man-machine system model that consists of two axes; human information processing and crane life cycle. In the human information processing dimension, we simplified it as five functions; sensing and perception, decision making and memory, response etc. In the crane life cycle dimension, we divided it into nine phases; design, production, operation etc. For the 152 fatal accident records during 1999-2006 years, we classified them into 45 cells made by two axes. Then we identified the preceding causes of the classified crane accident based on performance shaping factors. As the results of statistical analysis, the overall trend of crane fatal accidents was described. For the cause analysis, wrong decision making in work plan phase shows the highest frequency. Next, the poor information input in crane operation followed in accident frequency. In ergonomics view, the problems of interface design in displays and controls made 11.8% of fatal accidents. Following the analysis, several ergonomic design guidelines to prevent crane accidents were suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.247-250
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• 2018

The remote diagnostic system has been developed for enhancing operability of Data Service Platform(DSP) of Korean e-Navigation Project performed by Ministry of Oceans and Fisheries(MOF) since 2016. It plays a critical role to find and handling logical, physical error in early time in order to maximize operability of DSP, which makes DSP to provide seamless service to various ships voyaging in the sea. Therefore, as developing a system to diagnose resource and operation status of DSP immediately in a remote place, and a system to feed it back to operator or to recover it on its own, DSP can have short period of MTTR as well as high chance of providing proper service to ships in voyage.