• Journal of the Korea Safety Management & Science
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• v.15 no.1
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• pp.217-229
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• 2013

As customers' demands for diversified small-quantity products have been increased, there have been great efforts for a firm to respond to customers' demands flexibly and minimize the cost of inventory at the same time. To achieve that goal, in SCM perspective, many firms have tried to control the inventory efficiently. We present an mathematical model to determine the near optimal (s, S) policy of the supply chain, composed of multi suppliers, a warehouse and multi retailers. (s, S) policy is to order the quantity up to target inventory level when inventory level falls below the reorder point. But it is difficult to analyze inventory level because it is varied with stochastic demand of customers. To reflect stochastic demand of customers in our model, we do the analyses in the following order. First, the analysis of inventory in retailers is done at the mathematical model that we present. Then, the analysis of demand pattern in a warehouse is performed as the inventory of a warehouse is much effected by retailers' order. After that, the analysis of inventory in a warehouse is followed. Finally, the integrated mathematical model is presented. It is not easy to get the solution of the mathematical model, because it includes many stochastic factors. Thus, we get the solutions after the stochastic demand is approximated, then they are verified by the simulations.

• The Journal of Bigdata
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• v.5 no.2
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• pp.111-120
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• 2020

Despite the recent economic contraction caused by the Corona 19 incident, interest in the residential environment is growing as more people live at home due to the increase in telecommuting, thereby increasing demand for remodeling. In addition, the government's real estate policy is also expected to have a visible impact on the sales of the interior and furniture industries as it shifts from regulatory policy to the expansion of housing supply. Accurate demand forecasting is a problem directly related to inventory management, and a good demand forecast can reduce logistics and inventory costs due to overproduction by eliminating the need to have unnecessary inventory. However, it is a difficult problem to predict accurate demand because external factors such as constantly changing economic trends, market trends, and social issues must be taken into account. In this study, LSTM model and 1D-CNN model were compared and analyzed by artificial intelligence-based time series analysis method to produce reliable results for manufacturers producing furniture components.

• Journal of Korean Society of Transportation
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• v.29 no.6
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• pp.107-116
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• 2011

In this paper, we implement an algorithm of transit signal priority control that not only maximizes service quality and efficiency of bus, but also minimizes the control delay of passenger cars using UTIS currently being deployed and operated in Seoul national capital area. For this purpose, we propose an algorithm that coordinates the strength of TSP by estimating bus demand. Typically, the higher the strength of TSP is on main street, the bigger the control delay is on the cross street. Motivated by this practical difficulty, we proposes an algorithm that coordinates TSP's strength by checking the degree of saturation of cross street. Also, we verify the possibility of field implementation via simulation analysis using CORSIM RTE based HILS (Hardware In the Loop Simulation). The result shows that travel time of bus improves about 10 percent without increasing control delay of passenger cars by TSP. We expect the result of this research to contribute to increasing the overall transit ridership in this country.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.233-239
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• 2015

The demand of remote control and monitoring for efficiency and applications of LED streetlight is increasing continuously because the demand of LED streetlight was increase last few years. Existing street light remote control system is wired using a power line network. The wireless connection exists, but due to its low data transmission rate, it cannot support specialized applications. It can only support simple control and monitoring. In this paper, we propose a system that uses a IEEE 802.11s wireless mesh network based on WLAN, as a backbone network for remote control and monitoring of the LED street lights along with other specialized applications. Using the wireless mesh network for remote control and monitoring the LED street lights, the same can be used to act like a public Wi-Fi access point. We have designed Wi-Fi integrated LED streetlight controller and implemented our system. We evaluated the performance of our system on a real test bed. Our proposed system is expected to perform the role of a U-city infrastructure by utilizing the wireless mesh network.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.4
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• pp.302-311
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• 2016

This paper proposes a hybrid ESS that integrates an energy storage system (ESS) with an uninterruptible power supply (UPS). The hybrid ESS has a demand management and emergency power supply function while increasing the battery utilization of the UPS, which has just been used in a power failure. In addition to the critical load, the proposed system augments the capacity of emergency generation using an additional load, which has voltage and frequency-dependent characteristics to the grid side. The control algorithm of the AC-DC converter and bidirectional DC-DC converter is proposed for demand management and emergency power supply. Furthermore, seamless and autonomous transfer methods to alleviate the transient during mode transfer are proposed. To validate the proposed control scheme, experimental results from a 5 kW prototype are provided.

• Journal of Energy Engineering
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• v.20 no.3
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• pp.216-223
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• 2011

This paper presents an effective energy saving algorithm for lighting control systems using M&V method in various buildings and factories. It is important to aggregate a various demand side resource which is controllable at the peak power time to reduce the energy cost. Previous demand side algorithm appropriate for building is based on peak power. In this paper, we develop the new energy saving algorithm using M&V method to reduce the quantity of power consumption. The simulation results show that the proposed method is very effective.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.10
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• pp.381-386
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• 2016

An optimization algorithm is developed based on a simulation case of a single family house model equipped with PV arrays. To increase the nationwide use of PV power generation facilities, a market-competitive electricity price needs to be introduced, which is determined based on the time of use. In this study, quadratic programming optimization was applied to minimize the electricity bill while maintaining the indoor temperature within allowable error bounds. For optimization, it is assumed that the weather and electricity demand are predicted. An EnergyPlus-based house model was approximated by using an equivalent RC circuit model for application as a linear constraint to the optimization. Based on the RC model, model predictive control was applied to the management of the cooling load and electricity for the first week of August. The result shows that more than 25% of electricity consumed for cooling can be saved by allowing excursions of temperature error within an affordable range. In addition, profit can be made by reselling electricity to the main grid energy supplier during peak hours.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.1
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• pp.117-129
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• 2009

The bullwhip effect is known as the significant factor which causes unnecessary inventory, lost sales or cost increase in supply chains. Therefore, the causes of the bullwhip effect must be examined and removed. In this paper, we develop two analytical tools for the bullwhip effect control in supply chains. First, we develop the quantitative models for computing the bullwhip effect in a three-stage supply chain consisted of a single retailer, a single distributor and a single manufacturer when the fixed-interval replenishment policy is applied at each stage. The quantitative models are developed under the different conditions for the demand forecasting and share of customer demand information. They are validated through the computational experiments. Second, we develop a simulation-based decision support system for the bullwhip effect control in a more diverse dynamic supply chain environment. The system includes a what-if analysis function to examine the effects of varying input parameters such as operating policies and costs on the bullwhip effect.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.351-360
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• 2016

Rapid population growth with high living standards and high electronics use for personal comfort has raised the electricity demand exponentially. To fulfill this elevated demand, conventional energy sources are shifting towards low production cost and long term usable alternative energy sources. Hybrid renewable energy systems (HRES) are becoming popular as stand-alone power systems for providing electricity in remote areas due to advancement in renewable energy technologies and subsequent rise in prices of petroleum products. Wind and solar power are considered feasible replacement to fossil fuels as the prediction of the fuel shortage in the near future, forced all operators involved in energy production to explore this new and clean source of power. Presented paper proposes fuzzy logic based Energy Management System (EMS) for Wind Turbine (WT), Photo Voltaic (PV) and Diesel Generator (DG) hybrid micro-grid configuration. Battery backup system is introduced for worst environmental conditions or high load demands. Dump load along with dump load controller is implemented for over voltage and over speed protection. Fuzzy logic based supervisory control system performs the power flow control between different scenarios such as battery charging, battery backup, dump load activation and DG backup in most intellectual way.

• Earthquakes and Structures
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• v.3 no.3_4
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• pp.413-434
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• 2012

This paper presents a displacement-based seismic design method with damage control, in which the targets for the considered performance level are set as displacements and a damage distribution is proposed by the designer. The method is based on concepts of basic structural dynamics and of a reference single degree of freedom system associated to the fundamental mode with a bilinear behaviour. Based on the characteristics of this behaviour curve and on the requirements of modal spectral analysis, the stiffness and strength of the structural elements of the structure satisfying the target design displacement are calculated. The formulation of this method is presented together with the formulations of two other existing methods currently considered of practical interest. To illustrate the application of the proposed method, 5 reinforced concrete plane frames: 8, 17 and 25 storey regular, and 8 and 12 storey irregular in elevation. All frames are designed for a seismic demand defined by single earthquake record in order to compare the performances and damage distributions used as design targets with the corresponding results of the nonlinear step by step analyses of the designed structures subjected to the same seismic demand. The performances and damage distributions calculated with these analyses show a good agreement with those postulated as targets.