• Particle and aerosol research
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• v.7 no.3
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• pp.99-108
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• 2011

To establish area specific control strategies for the reduction of the ozone concentration, the Ozone Isopleth Plotting Package for Research(OZIPR) model has been widely used. However, the model results tend to changed by various input parameters such as the background concentration, emission amount of NOx and volatile organic compounds (VOCs), and meteorological condition. Thus, sensitivity analysis should be required to ensure the reliability of the result. The OZIPR modeling results for five local government districts in the Seoul Metropolitan Area (SMA) in June 2000 were used for the sensitivity analysis. The sensitivity analysis result showed that the modeling result of the SMA being VOC-limited region be still valid for a wide range of input parameters' variation. The estimated ozone concentrations were positively related with the initial VOCs concentrations while were negatively related with the initial NOx concentrations. But, the degree of the variations at each local district was different suggesting area specific characteristics being also important. Among the five local governments, Suwon was chosen to identify other variance through the period from April to September in 2000. The monthly modeling results show different ozone values, but still showing the characteristics of VOCs-limited region. Limitations due to not considering long range transport and transfer from neighbor area, limitation of input data, error between observed data and estimated data are all discussed.

• Aerospace Engineering and Technology
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• v.7 no.2
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• pp.187-195
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• 2008

Generation of accurate ground coordinates from high resolution satellite image are becoming increasingly of interest. The primary focus of this paper is to compute satellite direct sensor model (DSM) and rational function model (RFM) for accurate generation of ground coordinates from high resolution satellite images. Being based on this we presented an algorithm to be able to efficiently ground coordinates about large area with introducing RFM(rational function model) method applied to rigorous sensor modeling standing on basis of satellite orbit dynamics and collinearity equation, and sensor modeling of high-resolution satellite data like IKONOS, QuickBird, KOMPSAT-2 and others. The general high resolution satellite measures the position, velocity and attitude data of satellite using star, gyro, and GPS sensors.

• Journal of Construction Engineering and Project Management
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• v.5 no.4
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• pp.16-22
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• 2015

This paper presents an automated computer vision-based system to update BIM data by leveraging multi-modal visual data collected from existing buildings under inspection. Currently, visual inspections are conducted for building envelopes or mechanical systems, and auditors analyze energy-related contextual information to examine if their performance is maintained as expected by the design. By translating 3D surface thermal profiles into energy performance metrics such as actual R-values at point-level and by mapping such properties to the associated BIM elements using XML Document Object Model (DOM), the proposed method shortens the energy performance modeling gap between the architectural information in the as-designed BIM and the as-is building condition, which improve the reliability of building energy analysis. Several case studies were conducted to experimentally evaluate their impact on BIM-based energy analysis to calculate energy load. The experimental results on existing buildings show that (1) the point-level thermography-based thermal resistance measurement can be automatically matched with the associated BIM elements; and (2) their corresponding thermal properties are automatically updated in gbXML schema. This paper provides practitioners with insight to uncover the fundamentals of how multi-modal visual data can be used to improve the accuracy of building energy modeling for retrofit analysis. Open research challenges and lessons learned from real-world case studies are discussed in detail.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.3073-3084
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• 2022

The propagation of radiation source uncertainties in spent nuclear fuel (SNF) cask shielding calculations is presented in this paper. The uncertainty propagation employs the depletion and source term outputs of the deterministic code STREAM as input to the transport simulation of the Monte Carlo (MC) codes MCS and MCNP6. The uncertainties of dose rate coming from two sources: nuclear data and modeling parameters, are quantified. The nuclear data uncertainties are obtained from the stochastic sampling of the cross-section covariance and perturbed fission product yields. Uncertainties induced by perturbed modeling parameters consider the design parameters and operating conditions. Uncertainties coming from the two sources result in perturbed depleted nuclide inventories and radiation source terms which are then propagated to the dose rate on the cask surface. The uncertainty analysis results show that the neutron and secondary photon dose have uncertainties which are dominated by the cross section and modeling parameters, while the fission yields have relatively insignificant effect. Besides, the primary photon dose is mostly influenced by the fission yield and modeling parameters, while the cross-section data have a relatively negligible effect. Moreover, the neutron, secondary photon, and primary photon dose can have uncertainties up to about 13%, 14%, and 6%, respectively.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.532-536
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• 2015

This paper presents an automated computer vision-based system to update BIM data by leveraging multi-modal visual data collected from existing buildings under inspection. Currently, visual inspections are conducted for building envelopes or mechanical systems, and auditors analyze energy-related contextual information to examine if their performance is maintained as expected by the design. By translating 3D surface thermal profiles into energy performance metrics such as actual R-values at point-level and by mapping such properties to the associated BIM elements using XML Document Object Model (DOM), the proposed method shortens the energy performance modeling gap between the architectural information in the as-designed BIM and the as-is building condition, which improve the reliability of building energy analysis. The experimental results on existing buildings show that (1) the point-level thermography-based thermal resistance measurement can be automatically matched with the associated BIM elements; and (2) their corresponding thermal properties are automatically updated in gbXML schema. This paper provides practitioners with insight to uncover the fundamentals of how multi-modal visual data can be used to improve the accuracy of building energy modeling for retrofit analysis. Open research challenges and lessons learned from real-world case studies are discussed in detail.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.343-356
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• 2024

Super app is an application that provides a variety of services in a unified interface within a single platform. With the acceleration of digital transformation, super apps are becoming more prevalent. This study aims to suggest service enhancement measures by analyzing the user review data before and after the transition to a super app. To this end, user review data from a payment-based super app(Shinhan Play) were collected and studied via topic modeling. Moreover, a matrix for assessing the importance and usefulness of topics is introduced, which relies on the eigenvector centrality of the inter-topic network obtained through topic modeling and the number of review recommendations. This allowed us to identify and categorize topics with high utility and impact. Prior to the transition, the factors contributing to user satisfaction included 'payment service,' 'additional service,' and 'improvement.' Following the transition, user satisfaction was associated with 'payment service' and 'integrated UX.' Conversely, dissatisfaction factors before the transition encompassed issues related to 'signup/installation,' 'payment error/response,' 'security authentication,' and 'security error.' Following the transition, user dissatisfaction arose from concerns regarding 'update/error response' and 'UX/UI.' The research results are expected to be used as a basis for establishing strategies to strengthen service competitiveness by making super app services more user-oriented.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.91-101
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• 2011

This research aims to suggest web-based 3D face modeling system for hairline modification surgery. As public interests in beauty regarding face escalate with era of wide persoanl mobile smart iCT devices, need for medical information system is urgent and increasing demand. This research attempted to build 3D facing modeling library deploying conventional technology and proprietary software available. Implications from the our experiment found that problems and requirement for developing new web based standard. We suggest new system from our experiment and literature review regarding relevant technologies. Main features of our suggested systems is based on studies regarding hair loss treatment such as medical science, beauty studies and information technology. This system processes input images of 2D frontal and profile pictures of face into 3D face modeling with mesh-data. The mesh data is compatible with web standard technology including SVG and Canvas Tag supported natively by HTML5.

• Journal of Korea Water Resources Association
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• v.38 no.11
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• pp.907-916
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• 2005

For an urban watershed modeling, the ILLVDAS and SWMM model were the popular rainfall-runoff models using in Korea. However, combined sewerage systems in urban area produce some problems when a flood event happens because of the surcharged precipitation amounts which drain to streams directly. Also, rack of pipe line data and difficulties of modeling yield inappropriate modeling results in urban runoff analysis. In addition, rainfall-runoff models in an urban which using channel routing could be inaccurate and complicated processes. In this paper, the MIKE SWMM model has been applied for a stable urban area runoff analysis. Watershed and pipe line data were established by using past inundated records, DEM data and numerical pipe line data. For a runoff modeling, the Runoff block was adapted to a basin and the Extran block using dynamic equation was applied for sewerage system. After a comparisons against existing models yield that the MIKE SWMM model produce reliable and consistence results without distorting parameter of the model.