• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.677-685
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• 2007

The objective of this study is to evaluate the applicability of multi-objective genetic algorithm(MOGA) in order to calibrate the parameters of conceptual rainfall-runoff model, Tank model. NSGA-II, one of the most imitating MOGA implementations, is combined with Tank model and four multi-objective functions such as to minimize volume error, root mean square error (RMSE), high flow RMSE, and low flow RMSE are used. When NSGA-II is employed with more than three multi-objective functions, a number of Pareto-optimal solutions usually becomes too large. Therefore, selecting several preferred Pareto-optimal solutions is essential for stakeholder, and preference-ordering approach is used in this study for the sake of getting the best preferred Pareto-optimal solutions. Sensitivity analysis is performed to examine the effect of initial genetic parameters, which are generation number and Population size, to the performance of NSGA-II for searching the proper paramters for Tank model, and the result suggests that the generation number is 900 and the population size is 1000 for this study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.672-682
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• 2020

The Korea Nowadays, which is research on digital twin technology for efficient operation in various industrial/manufacturing sites, is being actively conducted, and gradual depletion of fossil fuels and environmental pollution issues require new renewable/eco-friendly power generation methods, such as wave power plants. In wave power generation, however, which generates electricity from the energy of waves, it is very important to understand and predict the amount of power generation and operational efficiency factors, such as breakdown, because these are closely related by wave energy with high variability. Therefore, it is necessary to derive a meaningful correlation between highly volatile data, such as wave height data and sensor data in an oscillating water column (OWC) chamber. Secondly, the methodological study, which can predict the desired information, should be conducted by learning the prediction situation with the extracted data based on the derived correlation. This study designed a workflow-based training model using a machine learning framework to predict the pressure of the OWC. In addition, the validity of the pressure prediction analysis was verified through a verification and evaluation dataset using an IoT sensor data to enable smart operation and maintenance with the digital twin of the wave generation system.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.716-727
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• 2004

Component-based software development (CBD) technology has been widely accepted as a new effective paradigm for building software systems with reusable components, consequently reducing efforts and shortening time-to-market. Hence, components should provide standard or common functionalities in a domain, yielding a higher level of reusability. Especially, micro-level variability within the commonality should also be modeled so that a product member-specific business logic or requirement can be supported through component tailoring or customization The importance of commonality and variability (C&V) analysis has been emphasized in several CBD methods, but they lack of well-defined systematic process, detailed instructions, and standard artifact templates. As the result, the development of components has been carried out in ad-hoc fashion, depending on developer's experience. In this paper, we propose a systematic process and work instructions to design components. The process consists of phases and their activities and each activity is specified with detailed instructions and artifact templates in order to facilitate effective development of components. To verify a feasibility of the propose method, a case study in a banking domain and comparison and assessment between the proposed method and other methods are additionally provided. With proposed processes and instructions, reusability and efficiency of developing components can be better supported.

• Journal of KIISE
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• v.42 no.3
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• pp.307-319
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• 2015

Current ontology studies use the Hadoop distributed storage framework to perform map-reduce algorithm-based reasoning for scalable ontologies. In this paper, however, we propose a novel approach for scalable Web Ontology Language (OWL) Horst Lite ontology reasoning, based on distributed cluster memories. Rule-based reasoning, which is frequently used for scalable ontologies, iteratively executes triple-format ontology rules, until the inferred data no longer exists. Therefore, when the scalable ontology reasoning is performed on computer hard drives, the ontology reasoner suffers from performance limitations. In order to overcome this drawback, we propose an approach that loads the ontologies into distributed cluster memories, using Spark (a memory-based distributed computing framework), which executes the ontology reasoning. In order to implement an appropriate OWL Horst Lite ontology reasoning system on Spark, our method divides the scalable ontologies into blocks, loads each block into the cluster nodes, and subsequently handles the data in the distributed memories. We used the Lehigh University Benchmark, which is used to evaluate ontology inference and search speed, to experimentally evaluate the methods suggested in this paper, which we applied to LUBM8000 (1.1 billion triples, 155 gigabytes). When compared with WebPIE, a representative mapreduce algorithm-based scalable ontology reasoner, the proposed approach showed a throughput improvement of 320% (62k/s) over WebPIE (19k/s).

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.493-503
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• 2014

A hierarchical classification scheme, which can reduce the spectral ambiguity and also reflect crop cultivation patterns from past land-cover maps, is presented for the purpose of the early production of crop classification maps in large-scale crop areas. Specifically, the effects of mixed pixels are minimized not only by applying a hierarchical classification approach based on different spectral characteristics from crop growth cycles, but also by considering temporal contextual information derived from past crop cultivation patterns. The applicability of the presented classification scheme was evaluated by a case study of Iowa State in USA with time-series MODIS 250 m Normalized Difference Vegetation Index(NDVI) data sets and past Cropland Data Layers(CDLs). Corn and soybean, which are major crop types in the study area and also display spectral similarity, could be properly classified by applying different classification stages and accounting for past crop cultivation patterns. The classification result by the presented scheme showed increases of minimum 7.68%p and maximum 20.96%p in overall accuracy, compared with one based on purely spectral information. In addition, the combination of temporal contextual information during classification was less affected by the number of NDVI data sets and the best overall accuracy of 86.63% was achieved. Thus, it is expected that this classification scheme can be effectively used for the early production of large-area crop classification maps in major feed-grain importing countries.

• Journal of Korean Society of Transportation
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• v.19 no.5
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• pp.49-59
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• 2001

In the transportation planning process, origin and destination(O-D) trip matrix is one of the most important elements. There have been developments and applications of the methodology to adjust old matrices using link traffic counts. Commonly, the accuracy of an adjusted O-D matrix depends very much on the reliability of the input data such as the numbers and locations of traffic counting points in the road network. In the real application of the methodology, decisions on the numbers and locations of traffic counting points are one of the difficult problems, because usually as networks become bigger, the numbers of traffic counting points are required more. Therefore, this paper investigates these issues as an experiment using a nationwide network in Korea. We have compared and contrasted the set of link flows assigned by the old and the adjusted O-D matrices with the set of observed link flows. It has been analyzed by increasing the number of the traffic counting points on the experimental road network. As a result of these analyses, we can see an optimal set of the number of counting links through statistical analysis, which are approximately ten percentages of the total link numbers. In addition, the results show that the discrepancies between the old and the adjusted matrices in terms of the trip length frequency distributions and the assigned and the counted link flows are minimized using the optimal set of the counted links.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.119-128
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• 2017

This study estimated the optimal nursing workforce and financial costs of providing comprehensive nursing services at hospitals under the national health insurance system. Data on registered nurses, nursing aids, medical institutions, and number of patients were obtained from the Health Insurance Review and Assessment Service. The optimal size of the nursing workforce was calculated using the workload model. A bottom-up approach was used to estimate the annual total financial cost of comprehensive nursing services. The number of registered nurses and nursing aids would need to be increased by 81.75% and 83.23%, respectively, in order to fully apply comprehensive nursing care on a national scale. The additional financial costs for comprehensive nursing services at all hospitals was estimated to be as much as 110.39% of the current cost. For the comprehensive nursing service, nurses with a career and newcomers need to be retained at their hospitals, and the validity of the nurse-patient ratio should be continuously checked. The financial shock to the national health insurance system could be minimized by gradually extending the system to all hospitals.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.444-453
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• 2018

The study addresses the analysis on the financial determinants of corporate research and development (R&D) expenditure in finance. Overall level of R&D spending was estimated as one of the top-tier on a global basis and a majority of the expenditure was invested by large domestic firms in private sector. Consequently, financial factors that influence R&D intensity were empirically tested in the first hypothesis by using conditional quantile regression model for firms listed in KOSPI stock market in the post-era of the global financial turmoil. Firms in the groups of high- and low-R&D intensity were statistically compared to detect financial differences in the second hypothesis which was accompanied by the test of multi-logit model that included firms without R&D outlay. Concerning the results of the hypothesis tests, R&D spending of the prior fiscal year, firm size, business risk and advertising expense overall showed statistically significant impacts to determine the level. As an extended study of [1] that had examined financial factors of R&D intensity at the macro-level, the results of the present study are anticipated to contribute to maximizing shareholders' wealth in advance or emerging capital markets, when applied to find an optimal level of R&D expenditure.

• Journal of the Korean Regional Science Association
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• v.31 no.4
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• pp.25-45
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• 2015

The government has implemented the projects of restoring the ecological integrity of streams to improve its water quality and provide resting places with local residents. Because the projects require huge public investments, their economic feasibility should be investigated through ex-post examination of their benefits. This study attempts to analyze the economic feasibility of restoring the ecological integrity using specific cases of Namyang stream in Hwaseong, Gyeonggi and Yugu stream in Gongju, Chungnam. The contingent valuation (CV) method is employed to measure the benefits. To this end, a professional polling firm conducted two CV surveys of 210 and 209 households for Hwaseong and Gongju, respectively. The willingness to pay (WTP) model used in the study is based on utility difference approach and the single-bounded dichotomous choice spike model. The results reveal that the WTP for restoring ecological integrity of the Namyang and Yugu streams are estimated to be 3,140 and 10,121 won per household per year. Interestingly, the latter is about three times greater than the former. The quantitative information can be used in economic feasibility analysis of the projects of restoring the ecological integrity of the Namyang and Yugu streams.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.714-721
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• 2018

In this study, we investigate a design technology intended to radically increase the buckling strength of vertically curved panels. Recent studies proposed a buckling strength formula which properly reflects the effect on the local plate buckling strength of flat plates when they are stiffened by closed section ribs. Herein, we attempted to quantitatively evaluate this effect on curved panels and to reveal the correlations with the design parameters. The commercial finite element software, ABAQUS, was used to build a three dimensional numerical model and numerical parametric studies were conducted to evaluate the variation of the buckling strength. In the case of flat panels, the local buckling strength of stiffened curved panels increases proportionally with increasing rotational stiffness of the closed-section ribs. After attaining a limiting value, an obvious tendency was found that the local buckling strength of the stiffened curved panel would converge towards a fixed value when the panels are supported along both sides. The parametric studies performed using the influential design parameters confirmed that the estimated partially-restrained curved panel strength is well correlated with the proposed formula.