• Journal of Soil and Groundwater Environment
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• v.17 no.5
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• pp.56-67
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• 2012

In the present study, an enhanced subsurface prediction algorithm based on a non-parametric geostatistical model and a history matching technique through Gibbs sampler is developed and the iterative prediction improvement procedure is proposed. The developed model is applied to a simple two-dimensional synthetic case where domain is composed of three different hydrogeologic media with $500m{\times}40m$ scale. In the application, it is assumed that there are 4 independent pumping tests performed at different vertical interval and the history curves are acquired through numerical modeling. With two hypothetical borehole information and pumping test data, the proposed prediction model is applied iteratively and continuous improvements of the predictions with reduced uncertainties of the media distribution are observed. From the results and the qualitative/quantitative analysis, it is concluded that the proposed model is good for the subsurface prediction improvements where the history data is available as a supportive information. Once the proposed model be a matured technique, it is believed that the model can be applied to many groundwater, geothermal, gas and oil problems with conventional fluid flow simulators. However, the overall development is still in its preliminary step and further considerations needs to be incorporated to be a viable and practical prediction technique including multi-dimensional verifications, global optimization, etc. which have not been resolved in the present study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.260-266
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• 2017

The global economy, including Korea, has continuously searched for various market-friendly policies and new economic systems in pursuit of the forth industrial revolution. As a result, economic markets have grown, and factors affecting markets have diversified. Therefore, as for many company's decision makers, it has become an important issue to analyze and forecast markets accurately and effectively for rapid and appropriate decision making. In this study, we aim to improve the accuracy and validity of forecast models by applying extended information criteria in existing restricted information criteria to determine optimized modeling for the accurate analysis and prediction of complex market environments. In order to verify the practical use of the extended information criteria adopted in this study, we compare this study employing KOSPI data with previous studies. Experimental results show that applying extended information criteria is more accurate than using the existing information criteria.

• Review of Culture and Economy
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• v.19 no.2
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• pp.51-72
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• 2016

This research dwells on categorization and industrialization of cultural heritage resources using marketing. Since many organization would not grab the chance of business while doing marketing using cultural heritage, the paper intend to suggest proper way to develop strategy. For that purpose, this research analyzed some advanced cases of corporate like Google and other national endeavors. This paper founded out 4 models of marketing using cultural heritage resources. These are re-creation, patron, capitalization and media. Also we got practical implications of the case analysis and modeling which are collaboration partnership scheme between marketers and filed expert group. Marketers better find fitful information and right person utilizing more reliable sources such as national archives, and academic achievements. If the marketers implement such strategic program, really abundant types of cultural heritage resources using marketing could bring more favorable profit which means business chance and new horizon for global culture industry.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.579-593
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• 2010

Low-power radio frequency (RF) chip transceiver technology and the associated structural health monitoring platforms have matured recently to enable high-rate, lossless transmission of measurement data across large-scale sensor networks. The intrinsic value of these advanced capabilities is the allowance for high-quality, rapid operational modal analysis of in-service structures using distributed accelerometers to experimentally characterize the dynamic response. From the analysis afforded through these dynamic data sets, structural identification techniques can then be utilized to develop a well calibrated finite element (FE) model of the structure for baseline development, extended analytical structural evaluation, and load response assessment. This paper presents a case study in which operational modal analysis is performed on a three-span prestressed reinforced concrete bridge using a wireless sensor network. The low-power wireless platform deployed supported a high-rate, lossless transmission protocol enabling real-time remote acquisition of the vibration response as recorded by twenty-nine accelerometers at a 256 Sps sampling rate. Several instrumentation layouts were utilized to assess the global multi-span response using a stationary sensor array as well as the spatially refined response of a single span using roving sensors and reference-based techniques. Subsequent structural identification using FE modeling and iterative updating through comparison with the experimental analysis is then documented to demonstrate the inherent value in dynamic response measurement across structural systems using high-rate wireless sensor networks.

• Journal of the Korea Society for Simulation
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• v.25 no.4
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• pp.93-108
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• 2016

Electric vehicle car sharing (EV-sharing) system is noted as an eco-friendly system of transportation in global warming crisis and has been practically implemented in some cities around the world. However, methodologies to find the efficient operation conditions of EV-sharing systems reflecting a typical characteristic 'charging' have not been fully investigated yet. In the paper a generalized model has been developed to identify optimal level of infrastructure for EV-sharing system which provides the optimum operation efficiency under service level constraints. From the simulation analysis based on the developed model the relationships between the operational variables to describe EV-sharing system have been identified and optimal capacity to maximize the operational efficiency have been found. From the analysis of simulation results it has been found that increases in the number of vehicles and chargers improve the service level until certain value beyond which increasing rate and the efficiency have been reduced. From the cost-revenue analysis the optimal numbers of vehicles and chargers have been identified which maximizes the annual operational profit.

• STI Policy Review
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• v.8 no.2
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• pp.75-93
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• 2017

Recently, global competition in the manufacturing sector is driving firms in the manufacturing sector to conduct product innovation projects to maintain their competitive edge. The key points of product innovation projects are 1) what the purpose of the project is and 2) what expected results in the target market can be achieved by implementing the innovation. Therefore, this study focuses on the performance of innovation projects with a business viewpoint. In this respect, this study proposes the "achievement rate" of product innovation projects as a measurement of project performance. Then, this study finds the best strategies from various innovation activities to optimize the achievement rate of product innovation projects. There are three major innovation activities for the projects, including three types of R&D activities: Internal, joint and external R&D, and five types of non-R&D activities - acquisition of machines, equipment and software, purchasing external knowledge, job education and training, market research and design. This study applies decision tree modeling, a kind of data-mining methodology, to explore effective innovation activities. This study employs the data from the 'Korean Innovation Survey (KIS) 2014: Manufacturing Sector.' The KIS 2014 gathered information about innovation activities in the manufacturing sector over three years (2011-2013). This study gives some practical implication for managing the activities. First, innovation activities that increased the achievement rate of product diversification projects included a combination of market research, new product design, and job training. Second, our results show that a combination of internal R&D, job training and training, and market research increases the project achievement most for the replacement of outdated products. Third, new market creation or extension of market share indicates that launching replacement products and continuously upgrading products are most important.

• Fashion & Textile Research Journal
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• v.23 no.4
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• pp.458-468
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• 2021

In the context of Sustainable development, China, the world's second-largest apparel market, is also concerned about the environmental impact of fiber waste. Currently, there is a great interest in sustainable fashion in both supply and demand in China. Based on the theory of planned behavior(TPB), the determinants of sustainable fashion consumption(SFC) of Chinese consumers were evaluated in this study: man-nature orientation(MNO) and environmental knowledge(EK) as motivation and perceived online-store accessibility(POA) and perceived money availability(PMA) as barriers. Wenjuanxing, a Chinese professional survey collection agency, conducted an online survey of millennials in Shanghai, China. The final sample size for the survey was 215. Partial least squares structural equation modeling was employed to test the proposed hypotheses. The results indicated that attitudes, subjective norms, and perceived behavioral control significantly affected the purchase intention towards sustainable fashion products. MNO and EK influenced the attitude, whereas EK, POA, and PMA influenced perceived behavioral control. This study contributes to the TPB literature through the examination of four antecedents: MNO, EK, POA, and PMA. The findings provide valuable insights for retailers and markets based on the identification of the motivations and barriers that enhance the purchasing intention of Chinese millennials toward SFC.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.1-9
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• 2021

Although interest in the metaverse increases due to the pandemic, the understanding of the metaverse interest factor, which is an essential element for the sustainability of any metaverse platform, is lacking. This study aims to reveal the interest factors of metaverse services by analyzing user community discourse. We collected user community discourses from and applied LDA to extract topics. Further, we categorize the factors into growth and verifiable indicators, various levels of interaction, self-expression and freedom, and connection with the real world. The content planning direction of the game-based metaverse of utilization was derived. This study is meaningful in that it analyzes the interest factors of the metaverse based on the empirical evidence of user discourse data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.343-349
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• 2021

In The process from design to construction in the existing construction work was less efficient due to the contradictory approach of identifying the 3D state in the plan view and the repeated generation of surveys, floor plans, drawings. Accurate 3D design data is essential for smart construction. However, most of the existing related studies have focused on explaining the development method and main functions of equipment or improving the productivity of smart construction. Therefore, in this study, the utility of 3D design model generation for smart construction and construction survey using 3D laser scanner was evaluated. Plane and vertical road alignment were created using the specifications of the road. The generated road alignment was created as a three-dimensional corridor design using cross-sections at intervals of 20m. In addition, it was possible to create a DTM (Digital Terrain Model) using a digital map and effectively create a 3D design model for the study area through overlapping. Construction survey using a 3D laser scanner showed accuracy within 10cm as a result of the accuracy evaluation. These results proved that construction surveying using a 3D laser scanner is possible because it satisfies the acceptable accuracy of the relevant regulations modeling of target areas using 3D design and construction survey using 3D laser scanner can be a way to address shortcomings of existing GNSS (Global Navigation Satellite System) methods. And accurate 3D data will be used as essential data as basic data for smart construction.

• Journal of Preventive Medicine and Public Health
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• v.54 no.3
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• pp.161-165
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• 2021

Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads heterogeneously, disproportionately impacting poor and minority communities. The relationship between poverty and race is complex, with a diverse set of structural and systemic factors driving higher rates of poverty among minority populations. The factors that specifically contribute to the disproportionate rates of SARS-CoV-2 infection, however, are not clearly understood. Methods: We evaluated SARS-CoV-2 test results from community-based testing sites in Los Angeles, California, between June and December, 2020. We used tester zip code data to link those results with United States Census report data on average annual household income, rates of healthcare coverage, and employment status by zip code. Results: We analyzed 2 141 127 SARS-CoV-2 test results, of which 245 154 (11.4%) were positive. Multivariable modeling showed a higher likelihood of SARS-CoV-2 test positivity among Hispanic communities than among other races. We found an increased risk for SARS-CoV-2 positivity among individuals from zip codes with an average annual household income