• Journal of the Korean Society of Safety
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• v.31 no.1
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• pp.126-131
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• 2016

Although many studies have been conducted to find solutions to deal with human errors effectively, violations have been rarely studied in depth. The violation is a type of human error when an employee takes an action with intention but does not intend harmful outcomes. Violations have characteristics similar to other types of human errors but it is difficult to understand the intention of an employee from accident reports. The objective of this study is to develop a conceptual model of violation errors for preventing accidents/failures in a nuclear power plant from violation errors. Based on the previous studies, the characteristics of violations were collected in 9 categories and 136 items. They were classified into three-kinds of characteristics (human-related, task-related, organization-related characteristics) to construct conceptual models of routine/situational violations. The representative cases of accidents/failures in a nuclear power plant were analyzed to derive the specific types of routine/situational violation occurrence. Three types of conceptual model for each violation were derived according to whether the basic, human-related, and task-related characteristics are included or not. The conceptual models can be utilized to develop guidelines to support employees preventing routine/situational violations and to develop supportive system in nuclear power plant.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.3 no.4
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• pp.73-80
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• 2004

A dual purpose robot automation system is developed for both arc welding and spot welding by one robot within a cell. The need for automation of both arc welding and spot welding processes is urgent while the production volume is not so big as to accommodate separate station for the two processes. Also, space is too narrow for separate station to be settled down in the factory. A spot welding robot is chosen and the function for arc welding are implemented in-house at cost of advanced functions. For the spot welding, a single pole type gun is used and the robot has to push down the plate to be welded, which causes the robot positioning error. Therefore, position error compensation algorithm is developed. The basic functions for the arc welding processes are implemented using the digital I/O board of robot controller, PLC, and A/D conversion PCB. The weaving pattern is taught in meticulously by manual teach. A fixture unit is also developed for dual purpose. The main aspects of the system is presented in this paper especially in the design and implementation procedure. The signal diagrams and sequence logic diagrams are also included. The outcome of the dual purpose welding cell is the increased productivity and good production stability which is indispensable for production volume prediction. Also, it leads to reduction of manufacturing lead time.

• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.173-182
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• 2013

Typographical mistakes made in the writing process of drafts of electronic documents are more common than any other type of errors. The majority of these errors caused by mistyping are regarded as consequently still typo-errors, but a considerable number of them are developed into the grammatical errors and the semantic errors. Pseudo semantic errors among these errors due to typographical errors have more noticeable peculiarities than pure semantic errors between senses of surrounding context words within a sentence. These semantic errors can be detected and corrected by simple algorithm based on the co-occurrence frequency because of their prominent contextual discrepancy. I propose a method for detection and correction based on the co-occurrence frequency in order to detect semantic errors due to typo-errors. The co-occurrence frequency in proposed method is counted for only words with immediate dependency relation, and the cosine similarity measure is used in order to detect pseudo semantic errors. From the presented experimental results, the proposed method is expected to help improve the detecting rate of overall proofreading system by about 2~3%.

• Composite Materials and Engineering
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• v.3 no.3
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• pp.201-220
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• 2021

In this study, potential of three machine learning techniques i.e., M5P, Support vector machines and Gaussian processes were evaluated to find the best algorithm for the prediction of flexural strength of concrete mix with steel fibre. The study comprises the comparison of results obtained from above-said techniques for given dataset. The dataset consists of 124 observations from past research studies and this dataset is randomly divided into two subsets namely training and testing datasets with (70-30)% proportion by weight. Cement, fine aggregates, coarse aggregates, water, super plasticizer/ high-range water reducer, steel fibre, fibre length and curing days were taken as input parameters whereas flexural strength of the concrete mix was taken as the output parameter. Performance of the techniques was checked by statistic evaluation parameters. Results show that the Gaussian process technique works better than other techniques with its minimum error bandwidth. Statistical analysis shows that the Gaussian process predicts better results with higher coefficient of correlation value (0.9138) and minimum mean absolute error (1.2954) and Root mean square error value (1.9672). Sensitivity analysis proves that steel fibre is the significant parameter among other parameters to predict the flexural strength of concrete mix. According to the shape of the fibre, the mixed type performs better for this data than the hooked shape of the steel fibre, which has a higher CC of 0.9649, which shows that the shape of fibers do effect the flexural strength of the concrete. However, the intricacy of the mixed fibres needs further investigations. For future mixes, the most favorable range for the increase in flexural strength of concrete mix found to be (1-3)%.

• Journal of Biosystems Engineering
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• v.31 no.1 s.114
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• pp.52-58
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• 2006

Various robots were developed for harvesting fruits and vegetables. However, each robot was designed for a specific task such as harvesting apples or vegetables. This has been a big hurdle in application of robots to agriculture. A new type of hybrid manipulator with both parallel and serial joints was developed and designed to apply to various kinds of field operations. The hybrid manipulator had 2 extra degree of freedom in serial joints which made it flexible in switching one to the other type of hybrid manipulator, for example, PUMA to SCARA. And it was designed to harvest heavy fruits such as musky melons or water melons even behind leaves or branches of tree. This hybrid manipulator showed less than $\pm1mm$ position error. It was concluded that the hybrid manipulator was an effective and feasible tool to perform various works and to increase working performance.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.788-796
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• 2017

This paper proposes a new measurement method to improve the shortcomings of an existing integral method for measuring heat flux in plug-type heat flux gauges in the high-temperature and high-pressure environments of liquid-rocket combustors. Using the existing integral measurement method, the calculation of the surface area for the heat flux in the gauge exhibits error in relation to the actual surface area. To solve this problem, transient profiles obtained from ANSYS Fluent were used to calculate unsteady heat flux as it adjusted to the measured temperature. First, a heat flux gauge was designed and manufactured specifically for use in the high-temperature and high-pressure conditions that are similar to those of liquid rocket combustors. A calibration test was performed to prove the reliability of the manufactured gauge. Then, a combustion experiment was conducted, in which the gauge was used to measure unsteady heat flux in a liquid rocket combustor that used kerosene and liquid oxygen as propellants. Reasonable heat flux values were obtained using the gauge. Therefore, the proposed measurement method is considered to offer significant improvement over the existing integral method.

• Environmental Engineering Research
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• v.23 no.4
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• pp.406-419
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• 2018

In planning public service systems such as waterworks, the design population is very important factor. Owing to the limitations of the indirect method, two new models, which take into consideration urban characteristics, were developed to accurately predict external migration rate (EMR), which is an essential component in estimating reliably the design population. The root mean square error (RMSE) between the model values and observed values were 10.12 and 15.58 for the metropolitan cities and counties respectively and were lower compared to RMSE values of 27.31 and 28.79 obtained by the indirect method. Thus, the developed models provide a more accurate estimate of EMR than the indirect method. In addition, the major influencing factors for external migration in counties were development type, ageing index, number of businesses. On the other hand, the major influencing migration factors for cities were project scale, distance to city center, manufacturing size, population growth rate and residential environment. Future medium and long-term studies would be done to identify emerging trends to appropriately inform policy making.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.05a
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• pp.383-386
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• 2007

In this study, the analysis was carried out for Electrical Discharge Machining (EDM) characteristics of the Cu electrodes by LIGA process. The shape of electrodes has 324 pins for the cavity of BGA(Ball Grid Array) type test socket mold. BGA test sockets are used in the inspection process of the semi-conductor I.C chip manufacturing. In the work, the machining performance for EDM of the electrodes was analyzed on dimensional accuracy and wear rate. The dimensional accuracy was measured for dimension of the pins, pitch size between the pins and the roundness of corner edge using optical measuring machine.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.971-984
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• 2015

Imputation procedures fill-in missing values, thereby enabling complete data analyses. Fully efficient fractional imputation (FEFI) and multiple imputation (MI) create multiple versions of the missing observations, thereby reflecting uncertainty about their true values. Methods have been described for hypothesis testing with multiple imputation. Fractional imputation assigns weights to the observed data to compensate for missing values. The focus of this article is the development of tests of independence using FEFI for partially classified two-way contingency tables. Wald and deviance tests of independence under FEFI are proposed. Simulations are used to compare type I error rates and Power. The partially observed marginal information is useful for estimating the joint distribution of cell probabilities, but it is not useful for testing association. FEFI compares favorably to other methods in simulations.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.605-613
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• 2015

A three-arm parallel design has been proposed to assess the biosimilarity between a biological product and a reference product using relative distance (Kang and Chow, 2013). The three-arm parallel design consists of two arms for the reference product and one arm for the biosimilar product. This paper extended the three-arm parallel design to a (k + 1)-arm parallel design composed of k (${\geq}3$) arms for the reference product and one arm for the biosimilar product. A new relative distance was defined based on Euclidean distance; consequently, a corresponding test procedure was developed based on asymptotic distribution. Type I error rates and powers were investigated both theoretically and empirically.