• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.353-364
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• 2011

RAM(Reliability, Availability and Maintainability) is one of the important indicators to show the performance of weapon systems. For analyzing RAM characteristics, RAM simulation is useful and powerful as mathematical techniques. However, it is necessary to build the simulation model to express about the operation environment of weapon systems, and obtain detail input data for reliability and maintainability about the system to get accurate results by RAM simulation. In this paper, we propose a procedure to analyze RAM of the searching system consisting in weapon systems by RAM simulation and we estimate searching system availability by a commercial simulation program, AvSim.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.2
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• pp.228-236
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• 2021

In order to understand the underwater noise source factor of the linear pump type forced ejection system, a reduced-model compressed water experiment device was developed. The reduced-model compressed water experiment device consists of a reverberation tank, a linear pump type forced ejection device, and an underwater vehicle. The underwater noise source was selected from the hydraulic ram moving speed, the hydraulic ram/piston pipe spacing, the ejection pipe inlet/water ram area ratio, and the number of water ram inlets. The underwater vehicle was ejected into the reverberation tank by the device. The source level was derived from the measured sound pressure. The source level tends to increase as the hydraulic ram/piston tube spacing and the hydraulic ram moving speed increase. The source level tended to increase as the area ratio was increased, but the level was weak. The number of water ram inlet did not affect the source level.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.17-32
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• 1995

The objective of this study is to develop a general design and performance evaluation model for the system designers in the initial design phase of the integrated automatic manufacturing system based on the RAM(Reliability, Availability and Maintainability) and life cycle cost(LCC). The methodology proposed in this research includes the following two stages. First, a deterministic approach to the solution of optimal work station arrangement for the initial system configuration is considered under the assumption that the system availability is one(no failure and maintenance), and then a stochastic simulation model based on RAM and LCC is developed. Using the results of these two stage simulation, a system performance index(SPI) was developed for the performance evaluation of the proposed system. Also a computer program is developed.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1996.11a
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• pp.23-25
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• 1996

In this paper aims at studying the minimal test pattem of the RAM. This also propose a scheme of testing faults from the new fault model using the LLB. The length of test patterns are 6N(1-wsf), 9.5N(2-wsf), 7N(3-wsfl, 3N(4-wsf) operations in N-bit RAM. This test techniques can write into memory cell the number of write operations is reduced and then much testing time is saved. A test set which detects all positive-negative static t-ws faults for t=0, 1, 2, 3, 4 and detects all pattern sensitive fault in memory array. A new fault model, which encompasses the existing fault model Is proposed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.143-143
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• 1994

• Journal of Korea Technology Innovation Society
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• v.19 no.4
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• pp.711-735
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• 2016

Drug Development is very important for promoting public health and pharmaceutical industry. There has been many studies on the efficiency of drug development, but there are few studies on the drug development R&D performed by government. Since CCR model assumes unidirectional influence of input and output, it is not appropriate to analyze the efficiency of R&D due to the time-lag and spill-over effect. Also, BBC model which assumes variable returns to scale has difficulty in deriving priorities between decision making units. Recently, Range Adjusted Measure (RAM) model has been suggested in R&D efficiency analysis. RAM model measures the efficincy by eliminating inefficiencies under variable returns to scale assumption, and its strong monotonicity enables to provide clear priorities between decision making units. In this study, we analyzed the efficiency of national R&D programs for drug development using the two-step approach, including RAM model and Tobit regression analysis, and discussed major policy implications.

• Proceedings of the Korean Association for Survey Research Conference
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• 2007.11a
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• pp.55-65
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• 2007

In this research, it will be examined on mathematical model of AMOS software program that ues for Covariance Structure Analysis. if we have not understood to mathematical model of Covariance Structure, we fail to understand Structural equation modeling. Similarly If We were not understand to mathematical model of AMOS Software, we do not use Software adequately. Therefore we examine two sorts of Software that be designed for Structural equation modeling or Covariance Structure Analysis. In this research, We will focus on 8 assumption of Structural equation modeling and compare AMOS(Analysis of MOment Structure) program with LISREL(Linear Structure RELation) program. We found that A Program of AMOS Software have materialized with RAM(Reticular Action Model).

• Journal of Korea Port Economic Association
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• v.27 no.1
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• pp.185-212
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• 2011

The purpose of this paper is to show the empirical analysis way for measuring the seaport efficiency by using the previous radial model and the newly modified non-radial models( panel additive model, panel RAM model, and panel SBM model)with Spearman rank order correlation coefficient(SROCC) for 20 Korean ports during 11 years(1997-2007) for 1 inputs(port investment amount) and 4 outputs(Number of Ship Calls, Port Revenue, Customer Satisfaction Score for Port Service and Container Cargo Throughput). The main empirical results of this paper are as follows. First, consistency ratio of SROCC in terms of efficiency scores between radial and panel Additive model was over about 76% and overall consistency ratio was about 71.6%. Second, an efficiency of panel RAM model was higher than that of radial model with similarity. However, panel SBM model shows the very similar efficiency scores with panel radial model. Third, the slack size of radial model is smaller compared to non-radial model. Models' ranking orders in terms of efficiency scores, number of efficient ports are panel RAM model, panel SBM model, and radial model. The order from the minimum efficiency scores was the same order like just before. The policy implication to the Korean seaports and planner is that Korean seaports should introduce the new methods like non-radial models(panel additive model, panel RAM model, and panel SBM model) for measuring the port performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.1
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• pp.218-230
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• 2000

In the weapon system development/operation stage, the goals of RAM activities are to support the cost effective performance optimization in design and operation supports. In the study, the main contents are as follows; 1) To establish the operational concept and circumstance of the subsequent tank, the combat/operation scenario, the operational mode summary and mission profile for subsequent tank development are analyzed. 2) To evaluate the administrative and logistics down time for subsequent tank, the prefigured logistics circumstance and maintenance system are analyzed. 3) To calculate the RAM object values, a mathematical model for the user are developed. 4) To examinate the propriety of the RAM object values, the combat readiness are reviewed. The obtained RAM object values are provided to predict and analyze for the combat readiness, staying power, mission reliability, equipment availability and the logistic support capability.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.675-696
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• 2023

Terpenoids, also referred to as terpenes, are a large family of naturally occurring chemical compounds present in the essential oils extracted from medicinal plants. In this study, a nondestructive methodology was created by combining ATR-FT-IR (attenuated total reflectance-Fourier transform infrared), and Raman spectroscopy for the terpenoids assessment in medicinal plants essential oils from ten different geographical locations. Partial least squares regression (PLSR) and support vector regression (SVR) were used as machine learning methodologies. However, a deep learning based model called as one-dimensional convolutional neural network (1D CNN) were also developed for models comparison. With a correlation coefficient (R²) of 0.999 and a lowest RMSEP (root mean squared error of prediction) of 0.006% for the prediction datasets, the SVR model created for FT-IR spectral data outperformed both the PLSR and 1 D CNN models. On the other hand, for the classification of essential oils derived from plants collected from various geographical regions, the created SVM (support vector machine) classification model for Raman spectroscopic data obtained an overall classification accuracy of 0.997% which was superior than the FT-IR (0.986%) data. Based on the results we propose that FT-IR spectroscopy, when coupled with the SVR model, has a significant potential for the non-destructive identification of terpenoids in essential oils compared with destructive chemical analysis methods.