• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.1005-1016
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• 2004

The conventional traffic light loses the function of optimal traffic signal cycle. And so, 30-45% of conventional traffic signal cycle is not matched to the present traffic signal cycle. In this paper proposes electro sensitive traffic light using fuzzy rules which will reduce the average vehicle waiting time and improve average vehicle speed. This paper is researching the storing method of 40 different kinds of sensor input conditions. Such as, car speed, delay· in starting time and the volume of cars in the real traffic situation. It will estimate the optimal green time in the 10 different intersections using Intelligent fuzzy method. Computer simulation results prove that reducing the average vehicle waiting time and offset better than fixed signal method which doesn't consider vehicle length.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.591-595
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• 1998

This paper proposes a new concept of optimal shortest path algorithm which reduce average vehicle wating time and improve average vehicle speed, Electro sensitive traffic system can extend the traffic cycle when three are many vehicles on the road or it can reduce the traffic cycle when there are small vehicles on the road. But electro sensitive traffic light system doesn't control that kind of function when the average vehicle speed is 10km -20km. Therefore, in this paper to reduce vehicle waiting time we developed design of traffic cycle software tool that can arrive destinination as soon as possible using optimal shortest pass algorithm. Computer simulation result proved 10%-32% reducing average vehicle wating time and average vehicle speed which can select shortest route using built in G.P.S. vehicle is better than not being able to select shortest route function.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.198-207
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• 1996

Electro sensitive traffic system can't consider passenger car unit, so, it causes start up delay time and passenger waiting time. In this paper, it antecedently creates optimal traffic cycle of passenger car unit at the bottom traffic intersection. But, sometimes it can make mistakes due to changes in car weight, car speed, and control of feed-back data. Moreover, to prevent spillback, it can adapt control even though upper traffic intersection has a different saturation rate, road length, road slope and road width.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.573-588
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• 2023

Purpose: This study presents a research approach that utilizes deep reinforcement learning to construct optimal portfolios based on the business cycle for stocks and other assets. The objective is to develop effective investment strategies that adapt to the varying returns of assets in accordance with the business cycle. Methods: In this study, a diverse set of time series data, including stocks, is collected and utilized to train a deep reinforcement learning model. The proposed approach optimizes asset allocation based on the business cycle, particularly by gathering data for different states such as prosperity, recession, depression, and recovery and constructing portfolios optimized for each phase. Results: Experimental results confirm the effectiveness of the proposed deep reinforcement learning-based approach in constructing optimal portfolios tailored to the business cycle. The utility of optimizing portfolio investment strategies for each phase of the business cycle is demonstrated. Conclusion: This paper contributes to the construction of optimal portfolios based on the business cycle using a deep reinforcement learning approach, providing investors with effective investment strategies that simultaneously seek stability and profitability. As a result, investors can adopt stable and profitable investment strategies that adapt to business cycle volatility.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.573-584
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• 2010

This paper considers the differences in the software execution environments in the testing phase and the operational phase to determine the optimal release time and warranty period of software systems. We formulate equations for the total expected software cost until the end of the software life cycle based on the NHPP. In addition, we derive the optimal release time that minimizes the total expected software cost for an imperfect debugging software reliability model. Finally, we analyze the sensitivity of the optimal testing and maintenance design related to variation of the cost model parameters based on the fault data observed in the actual testing process, and discuss the quantitative properties of the proposed model.

• International Journal of Quality Innovation
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• v.9 no.3
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• pp.71-91
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• 2008

The definition of cycle time is the time from the wafer start to the wafer output. It usually takes one or two months to get the product since customer decides to produce it. The cycle time is a critical factor for customer satisfaction because it represents the response time to the market. Long cycle time reflects the ineffective investment for the capital. The cycle time is very important for foundry because long cycle time will cause customer unsatisfied and the order loss. Consequently, all of the foundries put lots of human source in the cycle time improvement. Usually, we make decisions based on the experience in the cycle time management. We have no mechanism or theory for cycle time management. We do work-in-process (WIP) management based on turn rate and standard WIP (STD WIP) set by experiences. But the experience didn't mean the optimal solution, when the situation changed, the cycle time or the standard WIP will also be changed. The experience will not always be applicable. If we only have the experience and no mechanism, management will not be work out. After interview several foundry fab managers, all of the fab can't reflect the situation. That is, all of them will have an impact period after product mix or utilization varied. In this study, we want to develop a formula for standard WIP and use statistical process control (SPC) concept to set WIP upper/lower limit level. When WIP exceed the limit level, it will trigger action plans to compensate WIP Profile. If WIP Profile balances, we don't need too much WIP. So WIP level could be reduced and cycle time also could be reduced.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.387-390
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• 2008

The importance of the life cycle cost analysis for construction projects of bridge has been recognized over the last decades. Accordingly, theoretical models, guidelines, and supporting softwares have been developed for the life cycle cost analysis of bridges. However, it is difficult to predict life cycle cost considering uncertainties precisely. This paper presents methodology for optimal design of substructure for a steel box bridge. Total life cycle cost for the service life is calculated as sum of initial cost, damage cost considering uncertainty, maintenance cost, repair and rehabilitation cost. The optimization method is applied to design of a bridge substructure with minimal cost, in which the objective function is set to life cycle cost and constraints are formulated on the basis of Korean Bridge Design Specification. Initial cost is calculated based on standard costs of the Korea Construction Price Index and damage cost on the damage probabilities to consider the uncertainty of load and resistance. An advanced first-order second moment method is used as a practical tool for reliability analysis using damage probability. Maintenance cost and cycle is determined by a stochastic method and user cost includes traffic operation costs and time delay costs.

• Journal of Applied Reliability
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• v.12 no.2
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• pp.57-66
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• 2012

In this paper, we consider the periodic preventive maintenance model for a repairable system following the expiration of replacement-repair warranty. Under this preventive maintenance model, we derive the expressions for the expected cycle length, the expected total cost and the expected cost rate per unit time. Also, we determine the optimal preventive maintenance period and the optimal preventive maintenance number by minimizing the expected cost rate per unit time. Finally, the optimal periodic preventive maintenance policy is given for Weibull distribution case.

• Journal of Korean Institute of Industrial Engineers
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• v.8 no.1
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• pp.29-39
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• 1982

This paper presents a practical guidence for determining an optimal traffic control system at intersections in the urban areas in Korea. Two alternative systems, unsignalized and signalized, are considered. For analyzing the unsignalized system, two kinds of simulation model are developed ; gap acceptance model and first -in -first - out model. For the signalized system the total delay function for general arrival distribution is developed under the assumption that departure time is constant and it is used to find an optimal cycle time. Finally, the results in these two alternative systems are compared under the minimum average delay criterion and an optimal traffic control system is determined. This approach supports the decision making whether to install a traffic signal system in an intersection with given traffic flows and, if installed, determines what is the optimal cycle time and how the traffic signal phases are divided. And it also gives upper bounds of traffic flows to be passed in the unsignalized and the signalized system, which can be effectively used whenever an intersection is designed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.9-17
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• 2010

Decision problem called an optimal release policies, after testing a software system in development phase and transfer it to the user, is studied. The applied model of release time exploited infinite non-homogeneous Poisson process. This infinite non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used superposition which has various intensity, if the system is complicated. Thus, software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time. Through this study, in terms of superposition model and simply model, the optimal time to using superposition model release the software developer to determine how much could count will help.