• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.904-914
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• 2017

For efficient energy usage, the concept of demand response has been emerged and thereby Open Automated D emand Response(OpenADR) protocol is developed as a standard protocol to provide automated demand response. There have been emerging trends on the demand response services using the Internet of Things(IoT) for smart h ome energy management. In this smart home energy IoT environment, a lightweight protocol is needed rather tha n the existing HTTP/ XML based OpenADR protocol for demand response services since many small devices wi ll be interconnected. In this paper, we propose a lightweight OpenADR protocol based on CoAP protocol for pro viding demand response service in Smart Energy IoT environment, implement the proposed CoAP-based protocol, and analyzed the performance compared to existing HTTP/ XML-based OpenADR 2.0b protocol.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.349-371
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• 2022

Purpose: Compared to the rapid growth rate of the domestic automotive LED industry so far, the predictive analysis method for demand forecasting or market outlook was insufficient. Accordingly, product characteristics are analyzed through the life trend of LEDs for automotive exterior lamps and the relative strengths of p and q using the Bass model. Also, future demands are predicted. Methods: We used sales data of a leading company in domestic market of automotive LEDs. Considering the autocorrelation error term of this data, parameters m, p, and q were estimated through the modified estimation method of OLS and the NLS(Nonlinear Least Squares) method, and the optimal method was selected by comparing prediction error performance such as RMSE. Future annual demands and cumulative demands were predicted through the growth curve obtained from Bass-NLS model. In addition, various nonlinear growth curve models were applied to the data to compare the Bass-NLS model with potential market demand, and an optimal model was derived. Results: From the analysis, the parameter estimation results by Bass-NLS obtained m=1338.13, p=0.0026, q=0.3003. If the current trend continues, domestic automotive LED market is predicted to reach its maximum peak in 2021 and the maximum demand is $102.23M. Potential market demand was $1338.13M. In the nonlinear growth curve model analysis, the Gompertz model was selected as the optimal model, and the potential market size was $2864.018M. Conclusion: It is expected that the Bass-NLS method will be applied to LED sales data for automotive to find out the characteristics of the relative strength of q/p of products and to be used to predict current demand and future cumulative demand.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.918-923
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• 2021

The Korean government is developing a 10-year master plan pertaining to the Public Waters Management and Reclamation Act. However, it was observed that implementation of the reclamation project through frequent changes would occupy a significant proportion. Thus, questions are being raised about the effectiveness of the master plan. In view of this, the need for a trend analysis on long-term reclamation demand is growing. Accordingly, in this study, a trend analysis of reclamation demand was carried out using the annual reclamation performance data. The results of the analysis indicate that the demand for reclamation of public waters continued to decline, and the trend has been particularly evident since the 1990s, when it was converted into a reclamation master plan. In addition, the total demand for reclamation during 2021-2030 was calculated to be at a maximum of 13.8 km² and minimum of 1.7 km².

• Journal of Korean Society of Water and Wastewater
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• v.37 no.6
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• pp.363-373
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• 2023

Numerous studies have established a correlation between sociodemographic characteristics and water usage, identifying population as a primary independent variable in mid- to long-term demand forecasting. Recent dramatic sociodemographic changes, including urban concentration-rural depopulation, low birth rates-aging population, and the rise in single-person households, are expected to impact water demand and supply patterns. This underscores the necessity for operational and managerial changes in existing water supply systems. While sociodemographic characteristics are regularly surveyed, the conducted surveys use aggregate units that do not align with the actual system. Consequently, many water demand forecasts have been conducted at the administrative district level without adequately considering the water supply system. This study presents an upward water demand forecasting model that accurately reflects real water facilities and consumers. The model comprises three key steps. Firstly, Statistics Korea's SGIS (Statistical Geological Information System) data was reorganized at the DMA level. Secondly, DMAs were classified using the SOM (Self-Organizing Map) algorithm to consider differences in water facilities and consumer characteristics. Lastly, water demand forecasting employed the PCR (Principal Component Regression) method to address multicollinearity and overfitting issues. The performance evaluation of this model was conducted for DMAs classified as rural areas due to the insufficient number of DMAs. The estimation results indicate that the correlation coefficients exceeded 0.9, and the MAPE remained within approximately 10% for the test dataset. This method is expected to be useful for reorganization plans, such as the expansion and contraction of existing facilities.

• Korean System Dynamics Review
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• v.13 no.1
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• pp.81-112
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• 2012

This study investigate the impact of supply chain contracts on supply chain performance. This study employed Price adjustment contract(PAC) and Quantity adjustment contract(QAC) as two main types of a vertical coordination mechanism. We simulate different types of coordination mechanisms with various degrees of demand uncertainties and several capacity tightness scenarios. This study shows that PAC and QAC significantly enhance the supply chain profits and fill rates suggesting that supply chain performance can be improved by implementing a proper coordination mechanism depends on the level of a capacity tightness and demand uncertainty.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1105-1108
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• 2005

Media service model is divided into 3 models that are Client Pull, Server Push, and IPP(Interleaving Pull & Push) model. In most single VOD(Video On Demand) environment, Client Pull model was sufficient to play the movie Because most media contents has a low bitrate and resolution. But according to an increment of the demand of the high definition media, Client Pull model is not sufficient. Parallel VOD environment is made of several of VOD servers and provides the parallel media stream simultaneously for one client. We compared and analyzed the performance of service models with respect to network delay and data size in buffer in the single and parallel VOD environment and we found that IPP service model keeps the least network delay and stable client buffer state in the parallel VOD environment.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.675-683
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• 2015

In the 21st century, we now face the serious problems of the enormous consumption of the energy resources. Depending on the power consumption increases, both China and South Korea face a reduction in available resources. This paper considers the regression models and time-series models to compare the performance of the forecasting accuracy based on Mean Absolute Percentage Error (MAPE) in order to forecast the electricity demand accurately on the short-term period (68 months) data in Northeast China and find the relationship with Korea. Among the models the support vector regression (SVR) model shows superior performance than time-series models for the short-term period data and the time-series models show similar results with the SVR model when we use long-term period data.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.4
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• pp.33-53
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• 2010

When purchase prices of a raw material fluctuate over time, the total purchasing cost is mainly affected by reordering time. Existing researches focus on deciding the right time when the demand for each period is replenished at the lowest cost. However, the decision is based on expected future prices which usually turn out to include some error. This discrepancy between expected prices and actual prices deteriorates the performance of inventory models dealing with fluctuating purchase prices. In this paper, we propose a new inventory model which incorporates not only cost but also risk into making up a replenishment schedule to meet each period's demand. For each replenishment schedule, the risk is defined to be the variance of its total cost. By introducing the risk into the objective function, the variability of the total cost can be mitigated, and eventually more stable replenishment schedule will be obtained. According to experimental results from crude oil inventory management, the proposed model showed better performance over other models in respect of variability and cost.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.1-13
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• 2002

We study a multi-component production/inventory system in which individual components are made to meet various demand types. We assume that the demands arrive according to a Poisson process, but there is a fixed probability that a demand requests a particular kit of different components. Each component is produced by a flow line with several stations. The production of each component is operated by the CONWIP control mechanism. To analyse this system, we propose an approximation method based on aggregation method. In application of the aggregation method, a product-form approximation technique as well as a matrix-geometric method is used. Comparisons with simulation show that the approximation method provides fairly good results.

• IE interfaces
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• v.25 no.4
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• pp.405-415
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• 2012

The reliability performance measures for low and high or continuous demand modes of operation of safety instrumented systems(SISs) are examined and compared by analyzing the official definitions in IEC 61508 standard. This paper also presents a status of common cause factor(CCF) models used in IEC 61508 and problems relating CCF modelling are discussed and ideas to solve these ones are suggested. An example with mixed M-out-of-N architecture is carried out to illustrate the proposed methods.