• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.402-405
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• 1991

This paper represents a new method for computing reliability indices by using Large Deviation method which is one of the probabilistic production cost simulations. The reliability measures are based on the models used for the loads and for the generating unit failure states. In computing these measures it has been tacitly assumed that the values of all parameters in the models are precisely known. In fact, however, some of these values must often be chosen with a considerable degree of uncertainty involved. This is particularly true for the forecast peak loads in the load model, where there is an inherent uncertainty in the method of forecasting, which are frequently based on insufficient statistics. In this paper, the effect of load forecasting uncertainty on the LOLP(Loss of Load Probability), is investigated. By applying the Large Deviation method to the IEEE Rilability Test System, it is verified that the proposed method is generally very accurate and very fast for computing system reliability indices.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.171-172
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• 2015

Vinalines is actually known as not only one of Vietnam's state-sponsored economic giants but also the largest shipowner by tonnage in Vietnamese shipping industry. Therefore, a question of how to improve business performance of the corporation is always received deep attention by Vietnamese government, specially after the seriously economic scandal of Vinalines in a last few years. Among development strategies, the study focuses on short-term one in which Vinalines is recommended to restructure its own fleet in order to optimize performance of fleet operation and minimize costs while meeting the customer's shipping demand in near future. The first section is of introduction. Via method of statistical data analysis, section 2 brings to readers a panorama about the development profile and the current situation of development of Vinalines. In section 3, the authors use linear programming for setting a cost-minimization model optimizing Vinalines fleet structure based on available statistics and forecast information by Vinalines. The optimization problem is solved by applying AIMMS software in section 4. Finally, some conclusions and proposals by authors for the development of Vinalines are given.

• Atmosphere
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• v.20 no.4
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• pp.519-530
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• 2010

In this paper we review current research on Atmospheric Brown Clouds (ABCs) with lightweight Unmanned Aerial Vehicles (UAVs) and miniaturized instruments. The UAV technology for in-situ measurements, including aerosol concentration, aerosol size distribution, aerosol absorption, cloud drop size distribution, solar radiation fluxes (visible and broadband), and spectral radiative fluxes, is a leading-edge technology for cost-effective atmospheric sounding, which can fill the gap between the ground measurement and satellite observation. The first experimental observation with UAVs in Korea, Cheju ABC Plume Monsoon Experiment (CAPMEX), conducted during summer 2008 revealed that the Beijing plumes exerted a strong positive influence on the net warming and fossil-fuel-dominated black-carbon plumes were approximately 100% more efficient warming agents than biomass-burning-dominated plumes. Long-term sustainable routine UAV measurements will eventually provide truly three-dimensional data of ABCs, which is necessary for the better understanding of their climate impacts and for the improvement of numerical models for air pollution, weather forecast and climate change.

• Progress in Superconductivity and Cryogenics
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• v.17 no.2
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• pp.18-24
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• 2015

Large wind turbine generators with high temperature superconductors (HTS) are in incessant development because of their advantages such as weight and volume reduction and the increased efficiency compared with conventional technologies. In addition, nowadays the wind turbine market is growing in a function of time, increasing the capacity and energy production of the wind farms installed and increasing the electrical power for the electrical generators installed. As a consequence, it is raising the wind power energy contribution for the global electricity demand. In this study, a forecast of wind energy development will be firstly emphasized, then it continue presenting a recent status of the technology development of large scale HTSG for wind power followed by an explanation of HTS wire trend, cryogenics cooling systems concept, HTS magnets field coil stability and other technological parts for optimization of HTS generator design - operating temperature, design topology, field coil shape and level cost of energy, as well. Finally, the most relevant projects and designs of HTS generators specifically for offshore wind power systems are also mentioned in this study.

• Current Industrial and Technological Trends in Aerospace
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• v.8 no.1
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• pp.12-22
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• 2010

The great recession which caused by financial crisis made steep rise of oil price and the serious problems of the aircraft industry. High oil price increases operating cost and the recession decreases air traffic. After a period of high book order and delivery from global economic recovery, the aircraft order fell down suddenly. Also the Aircraft price and lease rate deceased and the MRO market is reduced, too. But, the air cargo and passenger increase again since late of 2009. So, it is difficult to predict the market movement, most of the forecasters agreed that the air traffic and aircraft demand will grow gradually in long term with the growth of emerging markets like China, India and Africa. And more efficient, safe and clean aircraft is needed and will need in the market.

• Smart Structures and Systems
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• v.26 no.1
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• pp.23-33
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• 2020

Majority of the damage in engineering structures is nonlinear. Damage sensitive features (DSFs) extracted by traditional methods from linear time series models cannot effectively handle nonlinearity induced by structural damage. A new DSF is proposed based on vector space cosine similarity (VSCS), which combines K-means cluster analysis and Bayesian discrimination to detect nonlinear structural damage. A reference autoregressive moving average (ARMA) model is built based on measured acceleration data. This study first considers an existing DSF, residual standard deviation (RSD). The DSF is further advanced using the VSCS, and then the advanced VSCS is classified using K-means cluster analysis and Bayes discriminant analysis, respectively. The performance of the proposed approach is then verified using experimental data from a three-story shear building structure, and compared with the results of existing RSD. It is demonstrated that combining the linear ARMA model and the advanced VSCS, with cluster analysis and Bayes discriminant analysis, respectively, is an effective approach for detection of nonlinear damage. This approach improves the reliability and accuracy of the nonlinear damage detection using the linear model and significantly reduces the computational cost. The results indicate that the proposed approach is potential to be a promising damage detection technique.

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.2
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• pp.82-94
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• 2007

Wireless sensor networking technology is one of the basic infrastructures for ubiquitous environment. It enables us to gather various sensory data such as temperature, humidity, gas leakage, and speed from the remote sensor devices. To support these networking functions, IEEE WPAN working group makes standards for PHY and MAC, while ZigBee Alliance defines the standards for the network, security, and applications. The low-rate WPAN was emerged to have the characteristics of network resilience, low cost, and low power consumption. It has a broad range of applications including, but not limit to industrial control and monitoring, home automation, disaster forecast and monitoring, health care. In order to provide more intelligent and robust services, users want voice-based solutions to accommodate to low-rate WPAN. In this paper, we have evaluated voice quality of an IEEE 802.15.4 standard compliant voice node. Specifically, it includes the design of a voice node and experiments based on the prediction of voice quality using the E-model suggested by ITU-T G.107, and the network communication mechanisms considering beacon-enabled and nonbeacon-enabled networks for real-time voice communications.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.3
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• pp.396-402
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• 2018

Earned Value Management(EVM) has been used to manage and forecast defense project schedule and cost over the last two decades in the world. However to support the lacking ability of schedule analysis in traditional EVM, earned schedule(ES) has been introduced as a tool to more accurately estimate schedule performance. This paper compares which method EVM or ES, provides more accurate schedule predictors in 32 Korean defense research and development projects. As a result of comparison, the ES method can predict the future schedule more reliably than the EVM method. We also analyze early warning function of schedule performance index considering project duration extension point. Through the analysis results, we confirm that both the EVM and the ES method lack the ability of the early warning in terms of the current schedule management criterion.

• Archives of design research
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• v.14 no.1
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• pp.93-101
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• 2001

This study suggested how to apply it decision-making of product development rapidly by design evaluation process to objectify and the result to quantify with viewpoint of design evaluation sets to marketability. Coverage of this method limited to the evaluation stage of design concept. The procedure of study, first of all, referred to some type of design evaluation method and their feature. And next, referred to some kinds of demand forecasting for marketing. Above an, this study focused on the method of demand forecasting by buying intentions surveys proper to the marketability evaluation of new product design. On a case study, I had investigated preference survey and buying intentions surveys about the design proposal of "language master audio". I selected the best design proposal through the conjoint analysis and also investigated demand forecasting. First, on the basis of buying intentions surveys, choose population and had produced buying demand, awareness demand, potential demand. I could estimate some profit to take out expense and cost from the buying demand. This estimated profit is marketability judgement data of product design at the design concept stage and can be utilized to measurable data for decision-making of product development. Through the case study, this method could forecast a target demand, and even if it is some difference between real sales volume, but the case study could verified that this method is effective to the evaluation of marketability in case of completely new product got on the typical category and the product category could be set up the population clearly.

• Environmental and Resource Economics Review
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• v.22 no.1
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• pp.3-29
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• 2013

The purpose of this study is to estimate consumer preferences on hybrid cars and electric cars by employing a choice experiment reflecting the various market conditions, such as different projected market shares of green vehicles and $CO_2$ emission regulations. Depending on different market scenarios, we examine as to which attribute and individual characteristic affect the preferences of potential consumers on green vehicles and further, forecast the potential market shares of green cars. The primary results, estimated by a conditional logit and panel probit models, indicate that sales price, fuel cost, maximum speed, emission of air pollutants, fuel economy, and distance between fuel stations can significantly affect consumer's choice of environment-friendly cars. The second finding is that the unique features of electric cars might better appeal to consumers as the market conditions for electric cars are improved. Third, education, age, and gender can significantly affect individual preferences. Finally, as the market conditions become more favorable toward green cars, the forecasted market shares of hybrid and electric vehicles will increase up to 67% and 14%.