• Proceedings of the Korean Society for Language and Information Conference
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• 2002.02a
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• pp.103-112
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• 2002

This paper aims to give an explanation of the combination of certain nouns and the verb ha-'do'. Although the verb ha-'do'normally takes an event type argument, it takes some substantival nouns such as paiolin 'violin', umsikcem 'restaurant', and so on. A substantival noun undergoes type shifting, because the governing verb ha-'do'coerces an entity type noun to an event reading, taking missing information from the qualia of the entity type noun. In addition, some nouns like ppallay 'laundry'are dot objects. The verb laking a dot objects selects a proper type between multiple subtypes of the dot object. Type pumping operation makes that selection possible.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.41 no.3
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• pp.8-12
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• 2009

According to a previous study, talc as a coating pigment can improve the viscosity and the water retention of coating color, the compressibility of coating layer, and hence gravure printability. Talc is also well known for its larger particle size than other pigments, which implies that less binder may be need due to its smaller specific surface area. This study investigated the possibility of reducing binder content for matte grade paper. Coating color was prepared with the Cotalc-2000, which showed the best properties in the previous study. The binder content was varied and the effect of binder content on the physical properties of coated paper and the gravure printability was investigated. It was shown that binder content could be reduced when talc was used as a coating pigment. The reduction in binder content did not influence gloss, roughness and the print density of coated paper but showed improvement in paper porosity, compressibility and missing dot.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.41 no.3
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• pp.1-7
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• 2009

Talc as a coating pigment has been developed in order to replace GCC and clay for matte grade and has received much attention due to various advantages including good gravure printability. In order to elucidate the effects of talc on gravure printability, model papers were produced with three kinds of coating talc whose particle size and brightness are different. Physical properties related to surface and structure and the gravure printability of the sample were tested. Coating color with talc showed lower viscosity than that with clay. For both matte and art grades, talc tended to give lower gloss than day. The smaller the particle size of talc, the better properties in the coating color viscosity and water retention. When the particle size of talc was small enough, the surface roughness of the coated paper produced with talc was similar to that with clay while larger talcs produced rougher surface than clay. On top of that, application of talc improved compressibility and gravure printability of coated paper.

• Journal of the Korean Society for Railway
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• v.13 no.1
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• pp.71-77
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• 2010

It is increasing annually that the cost for bridge Maintenance Repair & Rehabilitation (MR&R) in developed countries. Based on Intelligent Technology, Bridge Management System (BMS) is developed for optimization of Life Cycle Cost (LCC) and reliability to predict long-term bridge deteriorations. However, such data are very limited amongst all the known bridge agencies, making it difficult to reliably predict future structural performances. To alleviate this problem, an Artificial Neural Network (ANN) based Backward Prediction Model (BPM) for generating missing historical condition ratings has been developed. Its reliability has been verified using existing condition ratings from the Maryland Department of Transportation, USA. The function of the BPM is to establish the correlations between the known condition ratings and such non-bridge factors as climate and traffic volumes, which can then be used to obtain the bridge condition ratings of the missing years. Since the non-bridge factors used in the BPM can influence the variation of the bridge condition ratings, well-selected non-bridge factors are critical for the BPM to function effectively based on the minimized discrepancy rate between the BPM prediction result and existing data (deck; 6.68%, superstructure; 6.61%, substructure; 7.52%). This research is on the generation of usable historical data using Artificial Intelligence techniques to reliably predict future bridge deterioration. The outcomes (Long-term Bridge deterioration Prediction) will help bridge authorities to effectively plan maintenance strategies for obtaining the maximum benefit with limited funds.