• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.1
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• pp.42-48
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• 2009

A design methodology for control strategy and control structure gives a direct impact on wind turbine's performance and life cycle. A baseline control law which is a variable rotor speed and variable pitch control strategy is introduced, and a mathematic performance model of a wind turbine dynamics is derived. By using a numeric optimization algorithm, the steady state operating conditions of wind turbines are identified. Because aerodynamic interaction of winds with rotor blades is basically nonlinear, a linearization procedure is applied to analyze wind turbine dynamic variations for whole operating conditions. It turns out the wind turbine dynamics vary much depending on its operating condition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1373-1387
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• 2012

Contextual advertising is an important revenue source for major service providers on the Web. Ads classification is one of main tasks in contextual advertising, and it is used to retrieve semantically relevant ads with respect to the content of web pages. However, it is difficult for traditional text classification methods to achieve satisfactory performance in ads classification due to scarce term features in ads. In this paper, we propose a novel ads classification method that handles the lack of term features for classifying ads with short text. The proposed method utilizes a vocabulary expansion technique using semantic associations among terms learned from large-scale search query logs. The evaluation results show that our methodology achieves 4.0% ~ 9.7% improvements in terms of the hierarchical f-measure over the baseline classifiers without vocabulary expansion.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.2
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• pp.139-150
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• 1999

The ozone concentrations measured at the National Air Monitoring Stations between 1990 and 1995 were reviewed to detect any anomalies in the measurements. By screening the cases, in which variation of the ozone concentration from the previous measured value is greater than 75ppb, 125 station-days were identified as the test cases for the anomaly test. Historical and parallel consistencies of the measured concentrations were examined by plotting data for each test case. The detected anomalies can be classified into four categories; single outliers, anomalous variations during the startup period, baseline rises, and fluctuations in th diurnal variations. Anomalies were detected in as many as 80 cases among 125 test cases. Because of these anomalies, the number of hours exceeding 100ppb in the areas other than the Greater Seoul Area(GSA) could decrease from 157 to 107. Further studies for developing the methodology for eliminating the abnormal monitoring data are warranted for the data from the National Air Monitoring Stations are official to the both inside and outside of the country.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.764-766
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• 1997

This paper presents a DSM Monitoring Methodology which is able to evaluate the impact of DSM programs under processing. For an effective assessment of DSM programs, it is foremost necessary to examine the market characteristics on the specific end-use appliance according to the customer's adoption of DSM programs. The Proposed Monitoring system contains a diffusion process of high efficient end-use considering major factors of DSM impact such as, price, price elasticity and lifetime of end-use apparatus or appliance. The case study shows the propriety and necessity of DSM monitoring in order to diagnose the current state and provide a baseline of DSM policy

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.71-80
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• 2006

A nonparametric Bayesian multiple comparisons problem (MCP) for dependence parameters in I bivariate exponential populations is studied here. A simple method for pairwise comparisons of these parameters is also suggested. Here we extend the methodology studied by Gopalan and Berry (1998) using Dirichlet process priors. The family of Dirichlet process priors is applied in the form of baseline prior and likelihood combination to provide the comparisons. Computation of the posterior probabilities of all possible hypotheses are carried out through Markov Chain Monte Carlo method, namely, Gibbs sampling, due to the intractability of analytic evaluation. The whole process of MCP for the dependent parameters of bivariate exponential populations is illustrated through a numerical example.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.253-255
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• 1998

This paper presents the methodology of DSM potential evaluation and estimation of commercial sector in Korea. In general, the estimation process of the potential savings of DSM activities include the determination of baseline electricity consumption, the instantaneous technical potential (ITP), the phased technical potential (PTP), the economic potential (EP), and the achievable potential(AP). The purpose of this paper is to provide evaluation process of those DSM potential savings based on top-down approach and apply it to commercial sector.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.1009-1018
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• 2012

Persistence homology (a type of methodology in computational algebraic topology) can be used to capture the topological characteristics of functional data. To visualize the characteristics, a persistence diagram is adopted by plotting baseline and the pairs that consist of local minimum and local maximum. We use the bottleneck distance to measure the topological distance between two different functions; in addition, this distance can be applied to multidimensional scaling(MDS) that visualizes the imaginary position based on the distance between functions. In this study, we use handwriting data (which has functional forms) to get persistence diagram and check differences between the observations by using bottleneck distance and the MDS.

• Smart Structures and Systems
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• v.24 no.5
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• pp.597-606
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• 2019

Damage detection based on dynamic characteristics of a structure is one of important roles in structural damage identification. It is difficult to detect local structural damage using traditional dynamic experimental methods due to a limited number of sensors used in an experiment. In this work, a non-contact test stand of fan blades is established, and a full-field noncontact test method, combined with three-dimensional digital image correlation, Bayesian operational modal analysis, and damage indices, is used to detect local damage of a fan blade under ambient excitation without use of baseline information before structural damage. The methodology is applied to detect invisible local damage on the fan blade. Such a method has a seemingly high potential as an alternative to detect local damage of blades with complex high-precision surfaces under extreme working conditions because it is a noncontact test method and can be used under ambient excitation without human participation.

• Structural Engineering and Mechanics
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• v.91 no.6
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• pp.591-606
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• 2024

This article proposes a new methodology for identifying beam damage based on changes in modal parameters using the Double Stage Extended Improved Particle Swarm Optimization (DSEIPSO) technique. A finite element code is first developed in MATLAB to model an ideal beam structure based on classical beam theory. An experimental study is then performed on a laboratory-scale beam, and the modal parameters are extracted. An improved version of the PSO algorithm is employed to update the finite element model based on the experimental measurements, representing the real structure and forming the baseline model for all further damage detection. Subsequently, structural damages are introduced in the experimental beam. The DSEIPSO algorithm is then utilized to optimize the objective function, formulated using the obtained mode shapes and the natural frequencies from the damaged and undamaged beams to identify the exact location and extent of the damage. Experimentally obtained resultsfrom a simple cantilever beam are used to validate the effectiveness of the proposed method. The illustrated results show the effectiveness of the proposed method for structural damage detection in the SHM field.

• Korean Journal of Construction Engineering and Management
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• v.16 no.2
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• pp.65-76
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• 2015

The Clean Development Mechanism (CDM) is the multi-lateral 'cap and trade' system endorsed by the Kyoto Protocol. CDM allows developed (Annex I) countries to buy CER credits from New and Renewable (NE) projects of non-Annex countries, to meet their carbon reduction requirements. This in effect subsidizes and promotes NE projects in developing countries, ultimately reducing global greenhouse gases (GHG). To be registered as a CDM project, the project must prove 'additionality,' which depends on numerous factors including the adopted technology, baseline methodology, emission reductions, and the project's internal rate of return. This makes it difficult to determine ex ante a project's acceptance as a CDM approved project, and entails sunk costs and even project cancellation to its project stakeholders. Focusing on hydro power projects and employing UNFCCC public data, this research developed a prediction model using logistic regression and CART to determine the likelihood of approval as a CDM project. The AUC for the logistic regression and CART model was 0.7674 and 0.7231 respectively, which proves the model's prediction accuracy. More importantly, results indicate that the emission reduction amount, MW per hour, investment/Emission as crucial variables, whereas the baseline methodology and technology types were insignificant. This demonstrates that at least for hydro power projects, the specific technology is not as important as the amount of emission reductions and relatively small scale projects and investment to carbon reduction ratios.