• Clean Technology
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• v.29 no.4
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• pp.327-332
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• 2023

This study investigated synthesis gas production via steam reforming of biogas. Ni-Al₂O₃ and Ni-CeO₂ catalysts were synthesized using the co-precipitation method, with controlled precipitation agent injection rates. Catalytic performances were tested at various temperatures, with a gas composition ratio of CH₄:CO₂:H₂O = 1:0.67:3 and a gas hourly space velocity (GHSV) of 647,000 mL h^-1 gcat^-1. The rate of precipitation agent injection influenced the characteristics of the catalysts depending on the type of support used. As the temperature increased, both the CO₂ reforming of methane and the reverse water gas shift reactions occurred. The Ni-Al₂O₃ catalyst, synthesized with a single injection of the precipitation agent, exhibited the best catalytic activity under conditions with sufficient steam supply among the prepared catalysts, due to its high Ni dispersion.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.642-652
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• 2009

In order to improve the performance of the existing relation extraction approaches, we propose a method for combining two pivotal concepts which play an important role in classifying semantic relationships between entities in text. Having built a composite kernel-based relation extraction system, which incorporates both entity features and syntactic structured information of relation instances, we define nine classes of lexical features and synthetically apply them to the system. Evaluation on the ACE RDC corpus shows that our approach boosts the effectiveness of the existing composite kernels in relation extraction. It also confirms that by integrating the three important features (entity features, syntactic structures and contextual lexical features), we can improve the performance of a relation extraction process.

• Journal of the Korean GEO-environmental Society
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• v.21 no.12
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• pp.17-21
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• 2020

Over 60% of South Korea's land consists of mountainous topography, and recently, due to earthquakes, localized heavy rains and road development, the risks of rockfalls are getting higher. As of now, rockfall prevention facilities are being constructed in 70% of Korean roads cut slope and rockfall protections account for about 20% of them. Rockfall protection's supporting capacity is defined by combining performance of wire mesh, pillars and wire ropes. For the existing constructed rockfall protection, standards of pillars that can absorb 48~61 kJ amount of energy, wire ropes and wire mesh are presented in Guidelines for the installation and management of traffic safety facilities, Rockfall prevention facilities by Ministry of Land, Transport and Maritime Affairs (2008). However, each factor's correlation of absorption energy is not presented so it is uncertain. This study will conduct vertical drop test and identify adequacy of rockfall protection net of displacement quantity calculation factor which is delta and evaluate rockfall protection net's absorbable energy through standards of overseas performance evaluation criteria.

• Journal of KIISE:Software and Applications
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• v.36 no.6
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• pp.491-497
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• 2009

This paper proposes a new feature weighting method for document sentiment classification. The proposed method considers the difference of sentiment intensities among sentences in a document. Sentiment features consist of sentiment vocabulary words and the sentiment intensity scores of them are estimated by the chi-square statistics. Sentiment intensity of each sentence can be measured by using the obtained chi-square statistics value of each sentiment feature. The calculated intensity values of each sentence are finally applied to the TF-IDF weighting method for whole features in the document. In this paper, we evaluate the proposed method using support vector machine. Our experimental results show that the proposed method performs about 2.0% better than the baseline which doesn't consider the sentiment intensity of a sentence.

• Fire Science and Engineering
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• v.23 no.2
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• pp.27-35
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• 2009

In this study, the fire resistance performance of a simple support composite beam, which was sprayed with fire protection coatings, was evaluated. Primary valuables of the study are loading and unloading, shape of composite beam and metal lath of the web. The thickness of the fire protection coating to the three hour resistance is 40mm, but the fire resistance test was performed with 25mm coatings. The test result showed that TSC composit beams with 25mm fire protection coatings can resist on fire for three hours at the both loading and unloading tests. Average and maximum temperatures were less than $250^{\circ}C$ and $310^{\circ}C$ respectively, compared with the standard temperatures for fire resistance on the loading and unloading tests.

• Journal of Korean Society of Steel Construction
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• v.22 no.6
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• pp.533-541
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• 2010

H-shaped beams, which are constructed between columns, are used widely as slaves in steel structures. The bending moments that occur on both ends of an H-shaped beam, however, are about twice the bending moment that occurs at the center of the H-shaped beam. Because such beam is designed with maximum bending moment, it is deeper and has smaller spaces. To improve these features, if both ends of an H-shaped beam that have maximum bending moments are merely reinforced, the beams could be designed by the bending moment at the center of the H-shaped beam. To analyze the structural performance of the proposed end-reinforced beams (eco-girders). Four specimens were prepared with the following parameters: end-reinforced steel plate, reinforced bars, and reinforced studs and experimental tests of the specimens were performed.

• Journal of the Korean Society for information Management
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• v.22 no.3 s.57
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• pp.261-287
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• 2005

The purpose of this paper is to explore the ways to improve the performance of SVM (Support Vector Machines) text classifier using inter-document similarities. SVMs are powerful machine learning systems, which are considered as the state-of-the-art technique for automatic document classification. In this paper text categorization via SVMs approach based on feature representation with document vectors is suggested. In this approach, document vectors instead of index terms are used as features, and vector similarities instead of term weights are used as feature values. Experiments show that SVM classifier with document vector features can improve the document classification performance. For the sake of run-time efficiency, two methods are developed: One is to select document vector features, and the other is to use category centroid vector features instead. Experiments on these two methods show that we can get improved performance with small vector feature set than the performance of conventional methods with index term features.

• Journal of the Korean Society for information Management
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• v.35 no.2
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• pp.37-62
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• 2018

This study examined the factors affecting the performance of automatic classification based on machine learning for domestic journal articles in the field of LIS. In particular, In view of the classification performance that assigning automatically the class labels to the articles in "Journal of the Korean Society for Information Management", I investigated the characteristics of the key factors(weighting schemes, training set size, classification algorithms, label assigning methods) through the diversified experiments. Consequently, It is effective to apply each element appropriately according to the classification environment and the characteristics of the document set, and a fairly good performance can be obtained by using a simpler model. In addition, the classification of domestic journals can be considered as a multi-label classification that assigns more than one category to a specific article. Therefore, I proposed an optimal classification model using simple and fast classification algorithm and small learning set considering this environment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.115-122
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• 2011

Adaptive arrays suffer from severe performance degradation when there are errors in the steering vector. The DCRCB (doubly constrained robust Capon beamformer) overcomes such a problem, introducing a spherical uncertainty set of the steering vector together with a norm constraint. However, in the standard DCRCB, it is a difficult task to determine the bound for the uncertainty, the radius of the spherical set, such that a near best solution is obtained. A novel beamforming method is presented which has no difficulty of the uncertainty bound setting, employing a recursive search for the steering vector. Though the basic idea of recursive search has been known, the conventional recursive method needs to set a parameter for the termination of the search. The proposed method terminates it by using distances to the signal subspace, without the need for parameter setting. Simulation demonstrates that the proposed method has better performance than the conventional recursive method and than the non-recursive standard DCRCB, even the one with the optimum uncertainty bound.

• Journal of the Korean GEO-environmental Society
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• v.10 no.5
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• pp.41-47
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• 2009

In this paper, the long-term performance of highway embankment using tire shred-sandy soil mixture as a lightweight fill material was evaluated through the field monitoring and field test programs. A tire shred-sandy soil embankment was constructed to support a four-lane highway in Indiana, which was built with a 50 : 50 volumetric ratio of tire shreds (maximum particle dimension of 76 mm) and sandy soil (SP, USCS). After opening of the road for traffic, no noticeable differential settlement and lateral deformation were observed, and no adverse environmental impact on temperature was detected as a result of the construction of the tire shred-sandy soil embankment. Moreover, FWD test results showed that tire shred-sandy soil mixture provides bearing capacity comparable to that of conventional fill and meets the criterion for a design life of 20 years.