• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1407-1415
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• 2008

Recently, there has been growing interest in Gyongin Line demand estimation, because SMRT(Seoul Metropolitan Rapid Transit Corporation) Line 7 will be extended west by 9.8km from Onsu to meet the Gyongin Line at Bupyeong-gu Office. This study was designed to estimate the change of traffic demand in Gyongin Line before and after the completion year 2011, also provide against the economic loss caused by the derived demand from Gyongin Line to SMRT Line 7. In this paper we give preliminary results for the strategic plans for traffic demand estimation and train operating plan in Gyongin Line by analyzing transport performance of Seoul metropolitan subway, and an additional study on the transportation market and the urban development plan is needed for more accurate results.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.2
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• pp.97-109
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• 2014

This paper considers a reverse supply chain with simultaneous recovery of used products and manufacturing of brand-new ones. Recovered products are downgraded and have to be sold in a market different from that of brand-new products at a different price. In case of a shortage of recovered product inventory, a brand-new item, if available, can be offered at the price of a recovered product. In other words, one-way demand substitution is allowed. We address the joint decision of when to manufacture brand-new product, when to recover returned product, and how to control demand substitution to maximize the hybrid production system's profits. To this end, we propose a Markov decision Process model and investigate the structure of the optimal policy. Performance comparison is numerically implemented between the models with and without downward demand substitution option under different operating conditions of the system parameters.

• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.115-123
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• 2006

The main focus of this study is to investigate the performance of a clark-scarf type multi-echelon serial supply chain operating with a base-stock policy and to optimize the inventory levels in the supply chains so as to minimize the systemwide total inventory cost, comprising holding and backorder costs as all the nodes in the supply chain. The source of supply of raw materials to the most upstream node, namely supplier, is assumed to have an infinite raw material availability. Retailer faces random customer demand, which is assumed to be stationary and normally distributed. If the demand exceeds on-hand inventory, the excess demand is backlogged. Using the echelon stock and demand quantile concepts and an efficient simulation technique, we derive near optimal inventory policy. Additionally we discuss the derived results through the extensive experiments for different supply chain settings.

• Journal of Industrial Technology
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• v.24 no.A
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• pp.185-194
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• 2004

To evaluate seismic performance of reinforced concrete piers two procedures for capacity spectrum method are presented. The capacity spectrum procedures include the reduction factor-ductility-period($R_{\mu}-{\mu}-T$)relationship in order to construct the inelastic demand spectra from the elastic demand spectra. Application of the procedures are illustrated by example analysis. Maximum displacements estimated by the procedures are compared to those by inelastic time history analysis for several artificial earthquakes. The results show that the maximum displacements estimated by the procedures are, on overall, smaller than those by the inelastic time history analysis.

• The Journal of Sustainable Design and Educational Environment Research
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• v.3 no.1
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• pp.46-59
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• 2003

In this study, analyzing class method, curriculum and demand performance of materials and user according to the 7th educational curriculum which, it is surveyed that materials design performance standards of floor and window suitable to future educational environment. Based on this study, It is needed for development of special materials suitable educational facilities, making standards fitting demand, study of variable and special field for educational facilities, study for security of objective data of materials, study of performance evaluation method subdivided, and desirable positive use of intimate environmental materials.

• Journal of Technology Innovation
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• v.23 no.2
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• pp.33-54
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• 2015

Supercomputing performance demand forecasting at the national level is an important information to the researchers in fields of the computational science field, the specialized agencies which establish and operate R&D infrastructure, and the government agencies which establish science and technology infrastructure. This study derived the factors affecting the scientific and technological capability through the analysis of supercomputing performance prediction research, and it proposed a hybrid forecasting model of applying the super-computer technology trends. In the cross-sectional analysis, multiple regression analysis was performed using factors with GDP, GERD, the number of researchers, and the number of SCI papers that could affect the supercomputing performance. In addition, the supercomputing performance was predicted by multiplying in the cross-section analysis with technical progress rate of time period which was calculated by time series analysis using performance(Rmax) of Top500 data. Korea's performance scale of supercomputing in 2016 was predicted using the proposed forecasting model based on data of the top500 supercomputer and supercomputing performance demand in Korea was predicted using a cross-sectional analysis and technical progress rate. The results of this study showed that the supercomputing performance is expected to require 15~30PF when it uses the current trend, and is expected to require 20~40PF when it uses the trend of the targeting national-level. These two results showed significant differences between the forecasting value(9.6PF) of regression analysis and the forecasting value(2.5PF) of cross-sectional analysis.

• Earthquakes and Structures
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• v.10 no.6
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• pp.1467-1486
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• 2016

This research focuses on seismic performance of a class of single pier skewed bridges with three different pier-deck connections; skew angles vary from $0^{\circ}$ to $60^{\circ}$. A well-documented four span continuous deck bridge has been modeled and verified. Seat-type connections with fixed and sliding bearings plus monolithic pier-deck connections are studied. Shear keys are considered either fully operational or ineffective. Seismic performances of the bridges and the structural components are investigated conducting bidirectional nonlinear time history analysis in OpenSees. Several global and intermediate engineering demand parameters (EDP) have been studied. On the basis of results, the values of demand parameters of skewed bridges, such as displacement and rotation of the deck plus plastic deformation and torsional demand of the piers, increase as the skew angle increases. In order to eliminate the deck collapse probability, the threshold skew angle is considered as $30^{\circ}$ in seat-type bridges. For bridges with skew angles greater than $30^{\circ}$, monolithic pier-deck connections should be applied. The functionality of shear keys is critical in preventing large displacements in the bearings. Pinned piers experience considerable ductility demand at the bottom.

• Journal of Korean Society on Water Environment
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• v.23 no.2
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• pp.188-192
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• 2007

The biochemical oxygen demand (BOD) test is widely used to determine the pollution strength of water, to evaluate the performance of wastewater treatment plants and to judge compliance with discharge permits. However, nitrification is a cause of significant errors in measuring BOD, particularly when a large population of nitrifying organisms is existing in water such as effluents from biological treatment plants. In order to investigate the amount of nitrogenous oxygen demand (NOD), BOD with and without inhibitor was measured as samples in the biological treatment plants. About 81% of effluent BOD from the biological treatment plant used in this experiment was comprised of NOD. In the case of influents, the NOD accounted for about 9% of BOD. The inhibited 5-day BOD (Carbonaceous BOD) test must be considered in evaluating the performance of wastewater treatment plant and judging compliance with discharge permit limitations.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.885-895
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• 2022

Since the supply and demand of agricultural products are unstable, which causes instability in farm income and consumer prices, the government has sought to mitigate the problems caused by unstable supply and demand by generating and providing agricultural outlook information. However, research should be carried out to increase the quality and utilization of agricultural observation information, because the value of agricultural observation information increases only when more users use this information and apply it to their decisions. In this study, a survey was conducted targeting producers and experts who are users or potential users of agricultural outlook information, and the results were analyzed through quantitative model, specifically importance-performance analysis (IPA) and analytic hierarchy process (AHP). The results show that improvement of promptness was required among the seven items evaluated with regard to agricultural outlook. Also, measures for dissemination of agricultural outlook information and the contents of outlook information should be improved to increase its use. If the quality level and use of agricultural observation information are increased by reflecting the results of the above analysis, decision-making on the supply and demand of agricultural products in Korea will be improved, and it is thought that it will be possible to increase farm household income and stabilize consumer prices through stabilization of supply and demand of agricultural products.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.307-314
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• 2022

Recently, researches using deep learning-based models are being actively conducted to replace statistical-based time series forecast techniques to predict electric power demand. The result of analyzing the researches shows that the performance of the LSTM-based prediction model is acceptable, but it is not sufficient for long-term regional-wide power demand prediction. In this paper, we propose a WaveNet deep learning model to predict electric power demand 24-hour-ahead with temperature data in order to achieve the prediction accuracy better than MAPE value of 2% which statistical-based time series forecast techniques can present. First of all, we illustrate a delated causal one-dimensional convolutional neural network architecture of WaveNet and the preprocessing mechanism of the input data of electric power demand and temperature. Second, we present the training process and walk forward validation with the modified WaveNet. The performance comparison results show that the prediction model with temperature data achieves MAPE value of 1.33%, which is better than MAPE Value (2.33%) of the same model without temperature data.