• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.11
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• pp.549-557
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• 2000

This study proposes a new numerical analysis method for assessing the outage cost of the composite power system with considering transmission system at load points. The proposed method comes from combination of the expected energy not served curve(EENSC) with the marginal outage cost function obtained at load points. Uncertainty of the outages of the generation and transmission systems was also included in this study. This study can be categorized into three processing parts as like as follows. Firstly, EENSC at load points was developed newly from the composite power system effective load duration curve which has been proposed by the authors. Secondly, this study proposes a new technical method for determining the coefficients of the marginal outage cost functions at load points in the composite power system(Generation and Transmission systems). It is a main key point that the mathematical expression for the marginal outage cost function at a load point is formulated and evaluated using relations between the GNP (or GDP) and the electrical energy demand at the load pint. Finally, the outage cost was calculated in this paper by combining the proposed EENSC with the marginal outage cost function evaluated at each load point. It is another important feature that the average costs for future at load points can be forescasted using the proposed approach. The effectiveness of the proposed new approach is demonstrated by the case studies with the IEEE-RTS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.656-658
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• 2013

Due to increasing demand of new technology, the complexity of hardware and software consisting embedded systems is rapidly growing. Consequently, it is getting hard to design complex devices only with traditional methodology. In this contribution, I introduce a new approach of designing complex hardware with SystemVerilog. I adopted the idea of object oriented implementation of the SystemVerilog to the design of an elliptic curve crypto-engine server farm. I successfully implemented the whole system including the test bench in one integrated environment, otherwise in the traditional way it would have cost Verilog simulation and C/SystemC verification which means much more time and effort.

• Journal of IKEEE
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• v.4 no.2 s.7
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• pp.233-240
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• 2000

This paper presents fuzzy clustering and wavelet transform analysis based technique for the industrial hourly load forecasting fur the purpose of peak demand control. Firstly, one year of historical load data were sorted and clustered into several groups using fuzzy clustering and then wavelet transform is adopted using the Biorthogonal mother wavelet in order to forecast the peak load of one hour ahead. The 5-level decomposition of the daily industrial load curve is implemented to consider the weather sensitive component of loads effectively. The wavelet coefficients associated with certain frequency and time localization is adjusted using the conventional multiple regression method and the components are reconstructed to predict the final loads through a five-scale synthesis technique. The outcome of the study clearly indicates that the proposed composite model of fuzzy clustering and wavelet transform approach can be used as an attractive and effective means for the industrial hourly peak load forecasting.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.331-338
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• 2005

In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS). In competitive power markets, electricity prices are determined by the balance between demand and supply through electric power exchanges or by bilateral contracts. Therefore, in decision makings, it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling approach, firstly, electricity prices over the targeted period are forecasted based on Artificial Neural Network (ANN) and also a newly proposed aggregated bidding curve. Secondary, the maintenance scheduling is formulated as a combinatorial optimization problem with a novel objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss by Maintenance (OLM) is adopted to maximize the profit of generation companies (GENCOS). Thirdly, the combinatorial optimization maintenance scheduling problem is solved by using Reactive Tabu Search in the light of the objective functions and forecasted electricity prices. Finally, the proposed maintenance scheduling is applied to a practical test power system to verify the advantages and practicability of the proposed method.

• Structural Engineering and Mechanics
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• v.88 no.4
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• pp.311-322
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• 2023

Riverine flood is one of the critical natural threats to river-crossing bridges. As floods are the most-occurred natural hazard worldwide, survival probability of bridges due to floods must be assessed in a speedy but precise manner. In this regard, the paper presents a reliability-based approach for a rapid assessment of failure probability of vulnerable bridge components under floods. This robust method is generic in nature and can be applied to both concrete and steel girder bridges. The developed methodology essentially utilizes limit state performance functions, expressed in terms of capacity and flood demand, for probable failure modes of various vulnerable components of bridges. Advanced First Order Reliability Method (AFORM), Monte Carlo Simulation (MCS), and Latin Hypercube Simulation (LHS) techniques are applied for the purpose of reliability assessment and developing flood fragility curves of bridges in which flow velocity and water height are taken as flood intensity measures. Upon validating the proposed method, it is applied to a case study bridge that experiences the flood scenario of a river in Gujarat, India. Research outcome portrays how effectively and efficiently the proposed reliability-based method can be applied for a quick assessment of flood vulnerability of bridges in any flood-prone region of interest.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.3
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• pp.123-131
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• 2015

With a prospective of rapid deployment of IOT, a systematic approach to derive a business strategy for various possible scenarios of IOT applications is in great demand. In this paper, a conceptual framework that can be utilized for the purpose of assessing the market potential and of setting up an initial business strategy for IOT deployment is suggested. The framework consists of utilization of well-known value curve analysis, ecosystem analysis and house of quality tools. The value curve analysis is utilized to identify value-enhancing components of consumers as well as relative strengths of suppliers. The ecosystem analysis is used to identify relevant players of the supply chain and their mutual relationships. The house of quality is suitable for developing the initial business strategy of the supplier by converting consumer requirements identified by value curve analysis into technical requirements for the supplier. In this paper, we applied our proposed framework to two services that have high potentiality of being benefited by IOT: car-sharing service and telehealth service.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.4
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• pp.575-581
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• 2012

The electrochemical oxygen demand (ECOD) is an additional sum parameter, which has not yet found the attention it deserves. It is defined as the oxygen equivalent of the charge consumed during an electrochemical oxidation of the solution. Only one company has yet developed an instrument to determine the ECOD. This instrument uses $PbO_2$-electrodes for the oxidation and has been successfully implemented in an automatic on-line monitor. A general problem of the ECOD determination is the high overpotential of electrochemical oxidations of most organic compounds at conventional electrodes. Here we present a new approach for the ECOD determination, which is based on the use of a solid composite electrodes with highly efficient electro-catalysts for the oxidation of a broad spectrum of different organic compounds. Lead dioxide as an anode material has found commercial application in processes such as the manufacture of sodium per chlorate and chromium regeneration where adsorbed hydroxyl radicals from the electro-oxidation of water are believed to serve as the oxidizing agent. The ECOD sensors based on the Au/$PbO_2$ electrode were operated at an optimized applied potential, +1.6 V vs. Ag/AgCl/sat. KCl, in 0.01 M $Na_2SO_4$ solution, and reduced the effect of interference ($Cl^-$ and $Fe^{2-}$) and an expended lifetime (more than 6 months). The ECOD sensors were installed in on-line auto-analyzers, and used to analyze real samples.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.3
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• pp.319-325
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• 2015

High-strength steel has replaced mild steel as the material of choice for truck decks or frames, owing to the growing demand for lightweight vehicles. Although studies on the weld fatigue characteristics of mild steel are available, studies on high-strength steels have been seldom conducted. In this study, firstly, we surveyed a chosen number of approaches and selected the Radaj method, which uses the notch factor approach, as the one suitable for evaluating the fatigue life of commercial vehicles. Secondly, we obtained the S-N curves of HARDOX and ATOS60 steel welds, and the F-N curves of the T-weld and overlapped-weld structures. Thirdly, we acquired a general S-N curve of welded structures made of high-strength steel from the F-N curve, using the notch factor approach. Fourthly, we extracted the weld fatigue characteristics of high-strength steel and incorporated the results in the database of a commercial fatigue program. Finally, we compared the results of the fatigue test and the CAE prediction of the example case, which demonstrated sufficiently good agreement.

• Structural Engineering and Mechanics
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• v.59 no.3
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• pp.455-473
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• 2016

Methods for the seismic demands evaluation of structures require iterative procedures. Many studies dealt with the development of different inelastic spectra with the aim to simplify the evaluation of inelastic deformations and performance of structures. Recently, the concept of inelastic spectra has been adopted in the global scheme of the Performance-Based Seismic Design (PBSD) through Capacity-Spectrum Method (CSM). For instance, the Modal Pushover Analysis (MPA) has been proved to provide accurate results for inelastic buildings to a similar degree of accuracy than the Response Spectrum Analysis (RSA) in estimating peak response for elastic buildings. In this paper, a simplified nonlinear procedure for evaluation of the seismic demand of structures is proposed with its applicability to multi-degree-of-freedom (MDOF) systems. The basic concept is to write the equation of motion of (MDOF) system into series of normal modes based on an inelastic modal decomposition in terms of ductility factor. The accuracy of the proposed procedure is verified against the Nonlinear Time History Analysis (NL-THA) results and Uncoupled Modal Response History Analysis (UMRHA) of a 9-story steel building subjected to El-Centro 1940 (N/S) as a first application. The comparison shows that the new theoretical approach is capable to provide accurate peak response with those obtained when using the NL-THA analysis. After that, a simplified nonlinear spectral analysis is proposed and illustrated by examples in order to describe inelastic response spectra and to relate it to the capacity curve (Pushover curve) by a new parameter of control, called normalized yield strength coefficient (${\eta}$). In the second application, the proposed procedure is verified against the NL-THA analysis results of two buildings for 80 selected real ground motions.