• Journal of the Korean Society of Combustion
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• v.18 no.3
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• pp.44-53
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• 2013

In this study, the economic evaluation for imported coals was conducted for power plant based on thermo-dynamical performance analysis. The number of coal types considered was 1,755 imported by five power generation companies in Korea during the 2010-2012. The higher heating value (HHV) of the coals ranged 4,000-6,500 kcal/kg, mostly sub-bituminous. The 1D thermo-dynamical performance modeling was performed for a 500 MWe standard power plant using PROATES code. It was founded that the low rank coals had negative effects on the plant efficiency mainly due to the increased heat loss by moisture, hydrogen and flue gas. Based on the performance analysis, the economic performance of the coals was evaluated. The apparent price of low-rank coals tended to be significantly lower than design coal; for example, the unit price of coal with a HHV of 4,000 kcal/kg was 57% of the reference coal having 6,080 kcal/kg. Considering the negative effects leading to a decrease in the thermal performance, heating value compensation, and increased parasite load, the corrected unit cost for the coal with 4,000 kcal/kg was 90.7% of the reference coal. Overall, the cost saving by imported coals was not high as expected.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1499-1506
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• 2014

Random walk is used for describing random phenomenon in various areas but tests for random walk developed so far are known to suffer from size distortion and low power. Kim et al. (2014) proposed a sign test for unit root (${\rho}=1$) hypothesis based on slopes. This article proposes a Wilcoxon signed rank test based on slopes for unit root hypothesis, and compares it with the augmented Dickey-Fuller test and the sign test by a simulation study. Our results confirm that the nonparametric tests are better than ADF test for small samples like n = 30. The results also show that the sign test is better than the Wilcoxon signed rank test and that for 0 < ${\rho}$ < 1 (-1 < ${\rho}$ < 0), the nonparametric tests suffer from power loss (improvement) as normal error changes to double exponential error.

• Journal of KIISE
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• v.44 no.5
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• pp.522-536
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• 2017

Keyword extraction can be utilized in text mining of massive documents for efficient extraction of subject or related words from the document. In this study, we proposed a hierarchical graph model based on the co-occurrence relationship, the intrinsic dependency relationship between words, and common sub-word in a single document. In addition, the enhanced TextRank algorithm that can reflect the influences of outgoing edges as well as those of incoming edges is proposed. Subsequently a novel keyword extraction scheme using the proposed hierarchical graph model and the enhanced TextRank algorithm is proposed to extract representative keywords from a single document. In the experiments, various evaluation methods were applied to the various subject documents in order to verify the accuracy and adaptability of the proposed scheme. As the results, the proposed scheme showed better performance than the previous schemes.

• Journal of KIISE:Software and Applications
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• v.36 no.7
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• pp.580-589
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• 2009

Today, most web pages are being created in the blogspace or evolving into the blogspace. A blog entry (blog page) includes non-traditional features of Web pages, such as trackback links, bloggers' authority, tags, and comments. Thus, the traditional rank algorithms are not proper to evaluate blog entries because those algorithms do not consider the blog specific features. In this paper, a new algorithm called "Blog-Rank" is proposed. This algorithm ranks blog entries by calculating bloggers' reputation scores, trackback scores, and comment scores based on the features of the blog entries. This algorithm is also applied to searching for information related to the users' queries in the blogspace. The experiment shows that it finds the much more relevant information than the traditional ranking algorithms.

• Journal of Environmental Health Sciences
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• v.45 no.2
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• pp.164-172
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• 2019

Objectives: This study's purpose is finding children's activity spaces that demand environmental safety management. Methods: The method of this study is analysing children's life patterns based on a questionnaire survey. Results: This study analyzed children's life patterns through a questionnaire survey. In total, 2,447 questionnaires were provided to analyze children's life patterns. The results of the questionnaire indicated a highly simple form because many children generally stayed in their home (66%) or nursery facility (2%). In the case of other facilities, playground was ranked first and amusement park was ranked second. In addition, kids cafe (including play facilities installed in shopping centers, etc.), library, and internet cafe were among the responses. Conclusions: The priority for new high-maintenance children's activity spaces are academy (rank 1), kids cafe (rank 2), indoor playground (rank 3).

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.1-7
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• 2021

In this paper, we propose a feature selection technique for multi-label classification. Many existing feature selection techniques have selected features by calculating the relation between features and labels such as a mutual information scale. However, since the mutual information measure requires a joint probability, it is difficult to calculate the joint probability from an actual premise feature set. Therefore, it has the disadvantage that only a few features can be calculated and only local optimization is possible. Away from this regional optimization problem, we propose a feature selection technique that constructs a low-rank space in the entire given feature space and selects features with sparsity. To this end, we designed a regression-based objective function using Nuclear norm, and proposed an algorithm of gradient descent method to solve the optimization problem of this objective function. Based on the results of multi-label classification experiments on four data and three multi-label classification performance, the proposed methodology showed better performance than the existing feature selection technique. In addition, it was showed by experimental results that the performance change is insensitive even to the parameter value change of the proposed objective function.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.1-7
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• 2017

Korea's domestic construction market and overseas construction order environment are experiencing a decreasing trend, and this trend is expected to continue. Therefore, domestic construction companies are seeking to enter the global construction market. This study analyzes the global construction market and the global competitiveness for global construction companies and provides the results. To this end, this study has developed a model to evaluate the global construction competitiveness level and to evaluated global construction competitiveness in 2016. The evaluation of global construction competitiveness was analyzed based on the competitiveness of construction infrastructure by country, and the evaluation results of competitiveness of construction companies. These assessments were based on 20 detailed international statistics (ENR, Global Insight, Compass, etc.). The evaluation results are as follows. First, in regard to the comprehensive global construction competitiveness by country, America ranked first among 20 countries, followed by China. European countries like Spain, Germany and the Netherlands ranked third to fifth, respectively. Korea ranked sixth, one rank higher than that of the previous year. America and European countries remain strong. Second, in regard to the comprehensive building infrastructure competitiveness by country, America ranked first followed by Germany. Korea ranked twelfth, which is the same rank as that of the previous year. When it comes to stability in the construction market, China ranked first and Korea eighth. For construction systems, Sweden ranked first and Korea thirteenth, and for infrastructure, Japan ranked first and Korea tenth. Third, according to the construction company's capability evaluation by country, America ranked first followed by China. Korea ranked fourth, two ranks higher than that of the previous year because of its building competitiveness (fifth → fourth) and design competitiveness (eleventh → eighth) which has improved. When it comes to building competitiveness, China ranked first and Korea fourth. For design competitiveness, America ranked first and Korea eighth, and for price competitiveness, India ranked first and Korea seventh. However, Korea is still in the middle of the pack rank among the 20 countries considered when it comes to design competitiveness. It is ranked eleventh for design productivity and thirteenth for foreign sales against the total sales (internationalization). Thus, Korea needs to improve technical power and tap into new markets for improved competitiveness, including increased productivity. To do so, more R&D investment is required.

• ETRI Journal
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• v.38 no.4
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• pp.714-723
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• 2016

Considerable attention has been given to processing graph data in recent years. An efficient method for computing the node proximity is one of the most challenging problems for many applications such as recommendation systems and social networks. Regarding large-scale, mutable datasets and user queries, top-k query processing has gained significant interest. This paper presents a novel method to find top-k answers in a node proximity search based on the well-known measure, Personalized PageRank (PPR). First, we introduce a distribution state transition graph (DSTG) to depict iterative steps for solving the PPR equation. Second, we propose a weight distribution model of a DSTG to capture the states of intermediate PPR scores and their distribution. Using a DSTG, we can selectively follow and compare multiple random paths with different lengths to find the most promising nodes. Moreover, we prove that the results of our method are equivalent to the PPR results. Comparative performance studies using two real datasets clearly show that our method is practical and accurate.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.359-363
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• 2008

In this paper, the capacity of MIMO fading channel in the OFDM-based spatial multiplexing systems is analyzed when there is scattering at both transmitter and receiver. The employed MIMO channel model is spanning from the correlated low-rank case to uncorrelated high-rank case at both transmitter and receiver. The effects of spatial fading correlation on the capacity of MIMO channel is examined when the channel is known and unknown at the transmitter. We also evaluate the impacts of a channel estimation error at the transmitter on the MIMO channel capacity.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.2
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• pp.101-108
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• 1986

Computer programs for IBM PC/XT/AT or compatibles, are presented for running 9 nonparametric tests. They include sign test, Wilcoxon signed rank test, Mann-Whitney Wilcoxon test, Kruskal-Wallis test, Kolmogorov-Smirnov one sample and two sample tests, Kendall and Spearman rank correlation coefficient tests, and Chi square test for contingency table. Each program is written with BASIC language and is combined into a statistical package, 'NONPARA'. It is easily accessible through the menu programs. The alogorithms on which each test is based, are also explained and 3 examples are given.