• Korean Chemical Engineering Research
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• v.46 no.3
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• pp.585-597
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• 2008

The aim of this study was to find an analytic solution to the problem of determining the optimal capacity (lot-size) of a batch-storage network to meet demand for a finished product in a system undergoing random failures of operating time and/or batch material. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to short-term random variations in the cycle time and batch size as well as long-term variations in the average trend. Some of the production processes have random variations in product quantity. The spoiled materials are treated through regeneration or waste disposal processes. All other processes have random variations only in the cycle time. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis, the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced.

• Journal of the Korean association of regional geographers
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• v.3 no.2
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• pp.151-162
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• 1997

Although modern versions of the traditional Von $Th{\ddot{u}}nen$ theory have contributed to a description of spatial organization in agriculture, they did not incorporate the market mechanism as an integral part of location theory. This deficiency has been indicated and new mathematical structure has been proposed elsewhere by the author. The closed model, which simultaneously considered a basic principle of supply and demand, exposed a computational complexity. Based on the problem, this study attempts to extend market mechanism in order to consider the influence of city (market) size in agricultural location theory. To theoretically explore the economic relationship in a location theory, this study simplifies agricultural activity as just two activities in one-dimensional spatial economy. The problem has been solved by equating total supply and demand of agricultural products, and then by determining each agricultural price from the relationship. All of the mathematical problems have been arranged in matrix form. First, the traditional model and closed model have been compared by quantitative comparative statics which provides the sensitivity test for each model. The results have shown that the traditional model shows a relatively excessive change in land use, besides the deficiency of a constant agricultural price. Second, the effects of the size of market town and its population increase were examined, using the closed model. In this case, the price of agricultural product is increased, and the land use is extended outward. This proves that locational rent is related to the expansion of land use. Third, environmental uncertainty was associated with the closed model, in order to further consider the difference of farmers attitude in strategic perspective. In this study, two extreme attitudes, which reflects the maximum average expected returns and the maximum guaranteed returns, were examined in their land use and their effects on the prices of agricultural products. It was shown that the two farmers attitudes can be interconnected with location theory. Due to the exogenous data, the differences in the area of land use and total quantities of agricultural products were not clearly shown in this study. However, it was shown that the land use pattern is very different. That is, maximum guaranteed return model reveals a mixed land use pattern around the market town. Basically, this study shows some spatial and economic implications related to Von $Th{\ddot{u}}nen$ model.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.2
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• pp.156-172
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• 2018

Recently, Korea suffered serious social conflicts between generations due to population aging. Anxiety about depletion of the National Pension Fund is one of the social problem to young generation, because of the uncertainty that they will not able to receive the pension they paid. At the same time, due to the high housing rent in Seoul metropolitan area, the demand for housing welfare and supply of public rental housing for young generation was increased. There are some opinions about using National Pension Fund to supplying public rental houses in the society. In this research, we were concentrated on finding the suitable areas for the public rental house using National Pension Fund. First, verifying the validity of the investment using National Pension Fund for the public rental housing was done. And spatial statistical methods were applied to explore the suitable areas for the public rental housing in Seoul metro area. Finally, this study divided young people into three groups and analyzed ways to supply public rental housing for each group in proper areas by their demand. This research's ultimate goals are mitigating the conflicts between the generations and achieving both profitability and publicness of National Pension Fund.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.47-63
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• 2021

Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.45-58
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• 2024

Drought risk is expected to increase as the frequency, intensity, and duration of droughts increase due to climate change. Drought risk is related to not only hydro-meteorological factors, but also water supply and demand. Recently, along with climate change, socioeconomic factors have also been recognized to increase drought risk. Therefore, it is necessary to outlook the drought risk considering various conditions for coping with future extreme droughts in a timely manner. In addition, considering various drought scenarios help reduce the uncertainty in future drought outlook. In this study, drought scenarios considering climate change scenarios, population, and water demand were created to outlook drought risk for 160 administrative districts in Korea, then new levels of drought risk were assigned based on the results of drought risk outlook to suggest drought management measures. The results showed that the drought risk will increase in the future in 2020, 2025, and 2030, compared to past. Especially the drought risk is likely twice as high in 2030 under the baseline and high scenarios. Applying the drought outlook results from this study to the new methodology for setting the risk levels shows that most regions are in Response (V) in 2020 and 2030 for baseline and high scenarios.

• Journal of Mechanical Science and Technology
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• v.17 no.7
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• pp.999-1010
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• 2003

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. This maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system using electro-hydraulic manipulators because hydraulic manipulators have the advantage of electric insulation and power/mass density. Meanwhile an electro-hydraulic manipulator using hydraulic actuators has many nonlinear elements, and its parameter fluctuations are greater than those of an electrically driven manipulator. So it is relatively difficult to realize not only stable contact work but also accurate force control for the autonomous assembly tasks using hydraulic manipulators. In this paper, the robust force control of a 6-link electro-hydraulic manipulator system used in the real maintenance task of active electric lines is examined in detail. A nominal model for the system is obtained from experimental frequency responses of the system, and the deviation of the manipulator system from the nominal model is derived by a multiplicative uncertainty. Robust disturbance observers for force control are designed using this information in an H$\_$$\infty$/ framework, and implemented on the two different setups. Experimental results show that highly robust force tracking by a 6-link electro-hydraulic manipulator could be achieved even if the stiffness of environment and the shape of wall change.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.9-10
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• 2001

Simulation has been evolved with the advance of computer and technique of modeling application systems. Early simulations were numerical analysis of engineering models known as continuous simulation, analysis of random events using various random number generators thus named as Monte Carlo simulation, iud analysis o(\\\\`queues which are prevalent in many real world systems including manufacturing, transportation, telecommunication. Discrete-event simulation has been used far modeling and analyzing the systems with waiting lines and inefficient delays. These simulations, either discrete-event, continuous, or hybrid, have played a key role in industrial age by helping to design and implement the efficient real world systems. In the information age which has been brought up by the advent of Internet, e-business has emerged. E-business, any business using Internet, can be characterized by the network of extended enterprises---extended supply and demand chains. The extension of value chains spans far reaching scope in business functions and space globally. It also extends to the individual customer, customer preferences and behaviors, to find the best service and product fit for each individual---mass customization. Simulation should also play a key role in analyzing and evaluating the various phenomena of e-business where the phenomena can be characterized by dynamics, uncertainty, and complexity. In this tutorial, applications of simulation to e-business phenomena will be explained and illustrated. Examples are the dynamics of new economy, analysis of e-business processes, virtual manufacturing system, digital divide phenomena, etc. Partly influenced by e-business, a new trend of simulation has emerged called agent-based simulation, Agent-based simulation is a technique of simulation using software agent that have autonomy and proactivity which are useful in analyzing and integrating numerous individual customer's behavior. One particular form of agent-based simulation is swarm. This tutorial concludes with the illustration of swarm or swarm Intelligence applied to various e-business applications, and future directions and implications of this new trend of simulation.

• Ocean Systems Engineering
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• v.9 no.3
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• pp.287-328
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• 2019

Comprehensive understanding of the flood risk assessments via frequency analysis often demands multivariate designs under the different notations of return periods. Flood is a tri-variate random consequence, which often pointing the unreliability of univariate return period and demands for the joint dependency construction by accounting its multiple intercorrelated flood vectors i.e., flood peak, volume & durations. Selecting the most parsimonious probability functions for demonstrating univariate flood marginals distributions is often a mandatory pre-processing desire before the establishment of joint dependency. Especially under copulas methodology, which often allows the practitioner to model univariate marginals separately from their joint constructions. Parametric density approximations often hypothesized that the random samples must follow some specific or predefine probability density functions, which usually defines different estimates especially in the tail of distributions. Concentrations of the upper tail often seem interesting during flood modelling also, no evidence exhibited in favours of any fixed distributions, which often characterized through the trial and error procedure based on goodness-of-fit measures. On another side, model performance evaluations and selections of best-fitted distributions often demand precise investigations via comparing the relative sample reproducing capabilities otherwise, inconsistencies might reveal uncertainty. Also, the strength & weakness of different fitness statistics usually vary and having different extent during demonstrating gaps and dispensary among fitted distributions. In this literature, selections efforts of marginal distributions of flood variables are incorporated by employing an interactive set of parametric functions for event-based (or Block annual maxima) samples over the 50-years continuously-distributed streamflow characteristics for the Kelantan River basin at Gulliemard Bridge, Malaysia. Model fitness criteria are examined based on the degree of agreements between cumulative empirical and theoretical probabilities. Both the analytical as well as graphically visual inspections are undertaken to strengthen much decisive evidence in favour of best-fitted probability density.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.35-42
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• 2014

The purpose of this study is to analyze job stress factors of hospital workers, which has an effect on their turnover intention. For identifying the influences on turnover intention, types of hospitals (university hospital, general hospital, private hospital) and types of workers(office workers, technical workers, and nursing staffs) were categorized. We went to the hospitals and carried out the survey under the cooperation with the concerned hospitals. The period of survey was from 23. Sep. 2013 to 30. Oct. 2013, and 293 worker participated in the survey. On the basis of the previous study, the measurement of job stress factors and turnover intention was set up as the survey method, and its reliability and validity were measured. The stress factors were subdivided into seven factors; occupational climate, organizational system, autonomy job control, uncertainty of getting a new job, job ability to perform, job demand, job ambiance. The value of job stress factors by the measuring instrument, Cronbach's Alpha, was 0.805 and the value of the subordination variable of turnover intention was 0.881. IBM SPSS Statistics 21 was used as the statistic analysis tool and the descriptive statistics about job stress factors. As a result, the turnover intention were analyzed depending on the types of hospitals, job groups, working years, and gender. Result shows that the job stress factors are differed according to the types of hospitals, and these job stress factors have influence on turnover intention. Therefore, it could be considered that, if the hospital managers find out the major job stress factors of their employees and resolve them in advance, the job stress of the hospital workers and their turnover intention can be reduced.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.150-156
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• 2004

Though the concept of Life-Cycle Cost (LCC) itself is not new, its effectiveness for planning, design, rehabilitation and maintenance/management of civil infrastructures is becoming increasingly recognized. For the decision problems as in the case of the LCC of plant facilities, equipments, bridge decks, pavements, etc., the Life-Cycle Cost Analysis (LCCA) is relatively simple, and thus its practical implementation is rather straightforward. However, when it comes to major infrastructures such as bridge, tunnels, underground facilities, etc., the LCCA problem becomes extremely complex because lack of cost data associated with various direct and indirect losses, and the absence of uncertainty data available for the assessment as well. As a result, the LCC studies have been largely limited only to those relatively simple LCCA problems of planning or conceptual design for making decisions. Accordingly, in the recent years, the researchers have pursued extensive studies on the LCC effectiveness mostly related to LCC models and frameworks for civil infrastructures. Moreover, recently the demand on the practical application of LCC effective decisions in design and maintenance is rapidly growing unprecedently in civil engineering practice. Indirction cost is very important on LCC formulation. But that is very difficult and complicate the estimation every LCC. The objective of this paper is to suggest efficient regression model for the estimation of indirect cost approach to the practical application of LCC for the design and rehabilitation of civil. infrastructures considering traffic, traffic network, detour condition, and workzone condition. In this paper, it performed the sensitivity analysis and correlation analysis of parameter for development of regression model of inflection cost.