• Journal of Internet Computing and Services
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• v.5 no.4
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• pp.11-22
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• 2004

Works that improve the process and notify the improved process, the product and the change of tasks to all users are essential in achieving project. Existent project management tools support the definition and the change of project activities, and configuration management tools support version check, workspace management. build management. etc. It costs too much to buy each tool. as well as, it is burdensome to learn usage for various tools. Therefore the web-based integrated tool is proposed to manage the process and artifacts at a time in this paper. The proposed tool defines component based development process model. and achieves recording of process progression, processing the request of change, reporting the progression of each task, product registering and change, version recording, artifact or form search, etc. using ebXML. Furthermore, the stakeholders get the systematic management and standardization by sharing information that are necessary in process achievement and configuration management in distributed environment using the integrated management tool.

• Advances in aircraft and spacecraft science
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• v.7 no.6
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• pp.553-570
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• 2020

To address the problems caused by the strong coupling of an airbreathing hypersonic vehicle's airframe and propulsion to the integrated control system design, an integrated airframe-propulsion model is established, and the coupling characteristics between the aircraft and engine are analyzed. First, the airframe-propulsion integration model is established based on the typical nonlinear longitudinal dynamical model of an air-breathing hypersonic vehicle and the one-dimensional dual-mode scramjet model. Thrust, moment, angle of attack, altitude, and velocity are used as transfer variables between the aircraft model and the engine model. The one-dimensional scramjet model can accurately reflect the working state of the engine and provide data to support the coupling analysis. Second, owing to the static instability of the aircraft model, the linear quadratic regulator (LQR) controller of the aircraft is designed to ensure attitude stability and height tracking. Finally, the coupling relationship between the aircraft and the engine is revealed through simulation examples. The interaction between vehicle attitude and engine working condition is analyzed, and the influence of vehicle attitude on engine safety is considered. When the engine is in a critical working state, the attitude change of the aircraft will not affect the engine safety without considering coupling, whereas when coupling is considered, the attitude change of the aircraft may cause the engine unstart, which demonstrates the significance of considering coupling characteristics.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1668-1673
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• 2011

Recent power industries are to be progressed as moving into horizontal markets and expanding of competitive systems through promoting SmartGrid. In these environments, the information on power consumers leads to establish a part of power markets through active and real-time participations instead of participating it as a passive manner presented by a vertical integration. Also, such information should be established as a way that effectively reflects changes and market behaviors occurred in power market participants. Therefore, in this study, a method that develops consumer information models, performs integrated managements, implements registration and distribution, and forms integrated management centers is presented to commonly use the consumer information according to the change in the environment of power industries.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.160-170
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• 2008

This paper proposes a mathematical model for converting conveyor assembly line to cellular manufacturing in complex production environments. Complex production environments refer to the situations with multi-products, variant demand, different batch sizes and the worker abilities varying with work stations and products respectively. The model proposed in this paper aims to determine (1) how many cells should be formatted; (2) how many workers should be assigned in each cell; (3) and how many workers should be rested in shortened conveyor line when a conveyor assembly line should be converted, in order to optimize system performances which are defined as the total throughput time and total labor power. We refer the model to a new production system. Such model can be used as an evaluation tool in the cases of (i) when a company wants to change its production system (usually a belt conveyor line) to a new one (including cell manufacturing); (ii) when a company wants to evaluate the performance of its converted system. Simulation experiments based on the data collected from the previous documents are used to estimate the marginal impact that each factor change has had on the estimated performance improvement resulting from the conversion.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.35 no.4
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• pp.48-56
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• 2003

In this work an integrated model for paper plants combining wet-end and dry section is developed and a model predictive control scheme based on the plant model is proposed. Closed-loop process identification method is employed to produce a state-space model. Thick stock, filler flow, machine speed and steam pressure are selected as input variables and basis weight, ash content and moisture content are considered as output variables. The desired output trajectory is constructed in the form of 1st-order dynamics. Results of simulations for control of grade change operations are compared with plant operation data collected during the grade change operations under the same conditions as in simulations. From the comparison, we can see that the proposed model predictive control scheme reduces the grade change time and achieves stable steady-state.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.37-39
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• 2000

The purpose of this paper is to present a neural network model based on change-point detection for the prediction of the U.S. Treasury Securities. Interest rates have been studied by a number of researchers since they strongly affect other economic and financial parameters. Contrary to other chaotic financial data, the movement of interest rates has a series of change points due to the monetary policy of the U.S. government. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in interest rates forecasting. The proposed model consists of three stages. The first stage is to detect successive change points in the interest rates dataset. The second stage is to forecast the change-point group with the backpropagation neural network (BPN). The final stage is to forecast the output with BPN. This study then examines the predictability of the integrated neural network model for interest rates forecasting using change-point detection.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.123-128
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• 2007

In order to apply a static fault-tree (FT) method to a system or a plant whose configuration changes dynamically, condition gates and a post processing method are used to effectively accommodate these changes. An operator's performance change, which can be caused by these configuration changes, should also be considered to assess the risk to a plant in a more realistic manner. This study aims to develop an integrated framework to accommodate various configuration changes and their effect on an operator’s performance by using the FT model. We applied a condition-based human reliability assessment (CBHRA) method to consider various conditions endured by an operator. That is, we integrated the CBHRA method with the conventional post processing method for modeling the system configuration changes. The effect of the condition monitoring systems installed in a plant is also considered. In this study, we show an example application of the integrated framework to a probabilistic safety assessment for the shutdown phase of a nuclear power plant.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.723-729
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• 2005

Traditional statistical process control(SPC) applied to discrete part industry in the form of control charts can look for and eliminate assignable causes by process monitoring. On the other hand, engineering process control(EPC) applied to the process industry in the form of feedback control can maintain the process output on the target by continual adjustment of input variable. This study presents controlling and monitoring rules adopted variable sampling interval(VSI) to change sampling intervals in a predetermined fashion on the predicted process levels for integrated EPC and SPC systems. Twelve rules classified by EPC schemes(MMSE, constrained PI, bounded or deadband adjustment policy) and type of sampling interval combined with EWMA chart of SPC are proposed under IMA(1,1) disturbance model and zero-order (responsive) dynamic system. The properties of twelve control rules under three patterns of process change(sudden shift, drift and random shift) are evaluated and discussed through simulation and control rules for integrated VSI EPC and SPC systems are recommended.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.210-218
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• 2006

Traditional statistical process control (SPC) applied to discrete part industry in the form of control charts can look for and eliminate assignable causes by process monitoring. On the other hand, engineering process control (EPC) applied to the process industry in the form of feedback control can maintain the process output on the target by continual adjustment of input variable. This study presents controlling and monitoring rules adopted by variable sampling interval (VSI) to change sampling intervals in a predetermined fashion on the predicted process levels under integrated EPC and SPC systems. Twelve rules classified by EPC schemes(MMSE, constrained PI, bounded or deadband adjustment policy) and type of sampling interval combined with EWMA chart of SPC are proposed under IMA (1,1) disturbance model and zero-order (responsive) dynamic system. Properties of twelve control rules under three patterns of process change (sudden shift, drift and random shift) are evaluated and discussed through simulation and control rules for integrated VSI EPC and SPC systems are recommended.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.417-426
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• 2000

This study suggests integrated neural network models for Interest rate forecasting using change-point detection, classifiers, and classification functions based on structural change. The proposed model is composed of three phases with tee-staged learning. The first phase is to detect successive and appropriate structural changes in interest rare dataset. The second phase is to forecast change-point group with classifiers (discriminant analysis, logistic regression, and backpropagation neural networks) and their. combined classification functions. The fecal phase is to forecast the interest rate with backpropagation neural networks. We propose some classification functions to overcome the problems of two-staged learning that cannot measure the performance of the first learning. Subsequently, we compare the structured models with a neural network model alone and, in addition, determine which of classifiers and classification functions can perform better. This article then examines the predictability of the proposed classification functions for interest rate forecasting using structural change.