• Bulletin of the Korean Chemical Society
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• v.35 no.4
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• pp.1149-1153
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• 2014

Real-time monitoring of hourly atmospheric radon (Rn-222) concentration was performed throughout 2011 at Gosan station, Jeju Island, one of the least polluted regions in Korea, in order to characterize the background levels, and temporal variations on diurnal to seasonal time-scales. The annual mean radon concentration for 2011 was $2527{\pm}1356$ mBq $m^{-3}$, and the seasonal cycle was characterized by a broad winter maximum, and narrow summer minimum. Mean monthly radon concentrations, in descending order of magnitude, were Oct > Sep > Feb > Nov > Jan > Dec > Mar > Aug > Apr > Jun > May > Jul. The maximum monthly mean value (3595 mBq $m^{-3}$, October), exceeded the minimum value (1243 mBq $m^{-3}$, July), by almost a factor of three. Diurnal composite hourly concentrations increased throughout the night to reach their maximum (2956 mBq $m^{-3}$) at around 7 a.m., after which they decreased to their minimum value (2259 mBq $m^{-3}$) at around 3 p.m. Back trajectory analyses indicated that the highest radon events typically exhibited long-term continental fetch over Asia before arriving at Jeju. In contrast, low radon events were generally correlated with air mass fetch over the North Pacific Ocean. Radon concentrations typical of predominantly continental, and predominantly oceanic fetch, differed by a factor of 3.8.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.42
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• pp.31-38
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• 1997

The main objective of this research is to develop a model to select the optimal input service level for a distribution center - multi branch inventory distribution system. With the continuous review policy, the distribution center places an order for specific order quantity to an outside supplier, and the order quantity is replenished after a certain lead time. Also, each branch places an order for particular order quantity to the distribution center to satisfy the customer demands, and receives the replenishment after a lead time. When an out of stock condition occurs during an order cycle, a backorder is placed to the upper level to fill the unfilled demands. With these situation, variable demand and variable lead time are used for better industrial practice. Further, actual lead times with a generic lead time distribution are used in developing the control model. Under the actual lead time model, the customer service measures actually attained for the distribution center and each branch are explained as the effective customer service measures. Thus, throughout the optimal control (using computer search procedures), we can select the optimal input service levels for the distribution center and each branch to attain the effective service level for each branch which is consistent with the goal level of service for each branch. At the same time, the entire distribution system keeps minimum inventories.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.477-480
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• 1996

The main objective of this research is to develop the optimal control method for a Distribution Center - multi Branch inventory distribution system. With the continuous review policy, the distribution center places an order for specific order quantity to an outside supplier, and the order quantity is replenished after a certain lead time. Also, each branch places an order for particular order quantity to the distribution center to satisfy the customer demands, and receives the replenishment after a lead time. When an out of stock condition occurs during an order cycle, a backorder is placed to the upper level to fill the unfilled demands. With these situation, variable demand and variable lead time are used for better industrial practice. Futher, actual lead times with a generic lead time distribution are used in developing the control model. Under the actual lead time model, the customer service measures actually attained for the distribution center and each branch are explained as the effective customer service measures. Thus, throughout the optimal control (using computer search procedures), we can set the desired service levels for the distribution center and each branch to produce the effective service level for each branch which is consistent with the goal level of service for each branch. At the same time, the entire distribution system keeps minimum inventories.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.55-64
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• 2001

The main objective of this research is to develop a model to select the optimal input service level for a distribution center-multi branch inventory distribution system. With the continuous review policy, the distribution center places an order for specific order quantity to an outside supplier, and the order quantity is replenished after a certain lead time Also, each branch places an order for particular order quantity to the distribution center to satisfy the customer demands, and receives the replenishment after a lead time. When an out of stock condition occurs during an order cycle, a backorder is placed to the upper level to fill the unfilled demands. With these situation, variable demand and variable lead time are used for better industrial practice. Further, actual lead times with a generic lead time distribution are used in developing the control model. Under the actual lead time model, the customer service measures actually attained for the distribution center and each branch are explained as the effective customer service measures. Thus, throughout the optimal control (using computer search procedures), we can select the optimal input service levels for the distribution center and each branch to attain the effective service levels for each branch which is consistent with the goal level of service for each branch. At the same time, the entire distribution system keeps minimum inventories.

• Plant Journal
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• v.17 no.4
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• pp.35-40
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• 2021

In this study, a technical characteristic test was conducted on the gas turbine generator system of Seoincheon Combined cycle no.6 to derive and verify the model constants. As a result of the generator maximum/minimum reactive power limit test, the maximum reactive power limit is 80 MVar and the minimum is -30 MVar. The generator uses the GENROU model, the field time constant (T'do) is 4.077 s, and the inertial constant (H) is 5.461 P.U. Excitation system used ESST4B model to derive and verify model constants by simulating no-load 2% AVR step test, PSS modeling derived from PSS2A model constants, and simulated and compared measurement data measured when PSS off/on Did. The GGOV1 model was used for the governor-turbine, and the numerical stability of the determined governor-turbine model constant was verified by simulating a 10% governor step test through the PSS/E simulation program

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.89-96
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• 2022

This paper suggests heuristic algorithm for single-model cross-over assembly line balancing problem that is a kind of NP-hard problem. The assembly line balance problem is mainly applied with metaheuristic methods, and no algorithm has been proposed to find the exact solution of polynomial time, making it very difficult to apply in practice. The proposed bi-directional clustering algorithm computes the minimum number of worker m^* = ⌈W/c⌉ and goal cycle time c^* = ⌈W/m^*⌉ from the given total assembling time W and cycle time c. Then we assign each workstation i=1,2,…,m^* to T_i=c^* ±α≤ c using bi-directional clustering method. For 7 experimental data, this bi-directional clustering algorithm same performance as other methods.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.3
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• pp.91-105
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• 2011

In this paper, we analyze a logistic system involving a supplier who produces and delivers multiple types of items and a buyer who receives and sells the products to end customers. The buyer controls the inventory level by replenishing each product item up to a given order-up-to-level to cope with stochastic demand of end customers. In response to the buyer's order, the supplier produces or outsources the ordered item and delivers them at the start of each period. For the system described above, a mathematical model for a single type of item was developed from the buyer's perspective. Based on the model, an efficient method to find the cycle length and safety factor which correspond to a local minimum solution is proposed. This single product model was extended to cover a multiple item situation. From the model, algorithms to decide the base cycle length and order interval of each item were proposed. The results of the computational experiment show that the algorithms were able to determine the global optimum solution for all tested cases within a reasonable amount of time.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.48-53
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• 2012

Due to the customer needs of reducing cost and delivery date shorting, prompt change in the production plan became more important. In the multi period system (For instance, production line.) where target processing time exists, production, idle and delay risks occur repeatedly for multiple periods. In such situations, delay of one process may influence the delivery date of an entire process. In this paper, we discuss the minimum expected cost of the case mentioned above, where the risk depends on the previous situation and occurs repeatedly for multiple periods. This paper considers the optimal switching frequency to minimize the total expected cost of the production process. In this paper, first, the optimal switching frequency model is proposed. Next, the mathematic formulation of the total expectation is presented. Finally, the policy of optimal switching frequency is investigated by numerical experiments.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1528-1533
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• 2009

Infrastructure is provided to the user through long-term project period and large-scale working expenses. Existing facilities are getting old as time goes by. Accordingly, proper maintenance is required and generally more maintenance cost than initial invested cost is needed during life cycle. Therefore, a specific plan that just increases the value of facilities is required by evaluating performance of facilities and inputting minimum maintenance cost. Value engineering that increases the value of object by systemically analyzing Life Cycle Costs and function is actively promoted at the design phase of construction. These efforts can increase the performance of facilities at the maintenance phase of infrastructure. This study is to search how to evaluate the performance of Roadway by utilizing function analysis, as a core part of VE in the maintenance phase. In order to this a new evaluation criteria were proposed by adding an evaluation items to the existing criteria through the research of old documents, status of roadway maintenance and function analysis of VE. The results of this study may promote the effective performance evaluation to determine a resolution of roadway congestion in future. A succeeding study using the proposed evaluation criteria will be required.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.51-61
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• 2012

This paper suggests an algorithm that obtains Directed Graph Minimum Spanning Tree (DMST), using Prim MST algorithm which is Minimum Spanning Tree (MST) of undirected graph. At first, I suggested the Prim DMST algorithm that chooses Minimum Weight Arc(MWA) from out-going nodes from each node, considering differences between undirected graph and directed graph. Next, I proved a disadvantage of Prim DMST algorithm and Chu-Liu/Edmonds DMST (typical representative DMST) of not being able to find DMST, applying them to 3 real graphs. Last, as an algorithm that can always find DMST, an advanced Prim DMST is suggested. The Prim DMST algorithm uses a method of choosing MWA among out-going arcs of each node. On the other hand, the advanced Prim DMST algorithm uses a method of choosing a coinciding arc from the out-going and in-going arcs of each node. And if there is no coinciding arc, it chooses MWA from the out-going arcs from each node. Applying the suggested algorithm to 17 different graphs, it succeeded in finding the same DMST as that found by Chu-Liu/Edmonds DMST algorithm. Also, it does not require such a complicated calculation as that of Chu-Liu/Edmonds DMST algorithm to delete the cycle, and it takes less time for process than Prim DMST algorithm.