• Journal of the Korean Recycled Construction Resources Institute
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• v.4 no.4
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• pp.388-395
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• 2016

This paper explores the photocatalytic sensitivity of cement mortar incorporated with recycled $TiO_2$ from waste water sludge. Basically, $TiO_2$ cluster sank down slowly to the bottom of cement mortar specimen before setting and hardening process. This leads the mismatch of $TiO_2$ concentration on the top and the bottom faces of a specimen. This poorly dispersed $TiO_2$-cement mortar naturally exhibits poor NOx removal efficiency especially on the top of cementitious structure. In architectural engineering application such as building or housing structures, one can simply filp over from the bottom so that more $TiO_2$ concentrated surface can be placed outward into the air. However, in highway pavement case, this could not be applicable due to in-situ installation of concrete pavement. Hence, the dispersion of $TiO_2$ cluster inside the cementitous material is getting important issue onto road construction application. To elaborate this issue, according to our results, silica fume, high-ranged water reducer, viscosity agent, blast furnace slag were not enhanced much of dispersion characteristics of $TiO_2$ cluster. The combination of foaming agent and accelerator of hardening with viscosity agent and small grain size of fine aggregate may help the dispersion of $TiO_2$ inside cementitious materials. Even though the enhanced dispersion were applied to the specimen, NOx removal efficiency doest not change much for the top surface of the specimen. This concurrently affected by the presence of tiny air voids and the dispersion of $TiO_2$ in that these voids could easily adsorbed NOx gas with the aid of large surface area.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.30 no.1
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• pp.125-134
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• 2012

This study is determined by tree vigor of analyzing of each object's growth condition in Locational Characteristics and compare the result with impediment extent rate in crown area to provide the management Study about the influence of man-made structures in numbers of protected trees. 68 places where are in the list of Kimpo protected trees were researched in Natural environments, vital degree of trees, number of trees. Crown area was calculated surveying it around the directions of North, East, South and West branching out. Impediment in the area was analyzed after classified into artificial impediment like paved surface(ascon, concrete, block, etc.), a building and a breast wall and natural impediment like soil, stonework and gravel and conclusions are as follow. In analyzing of natural environments, he ground where protected trees have located is consist of 72.05 of manmade structure and artificial in all. There are many protected trees which have less space than crown area for growth suggested by Woo-kyung Sim and Se-kyun Shin in 1992. And it was analyzed that making growth space for protected trees and management of impediment are urgently needed because of that the proportion of impediment covering the crown area has increased as cities are becoming more urbanized results in transforming of trees and weakness of tree vigor. This research shows that under 20% of in crown area is tree vigor determination 1-2 grade 21-50% under is 2-3 grade, higher than 50% is 3-5 grade. More impediment have more difficulty for growing, with the management of root system of protected trees need to be under 20% of rate of land is necessary was improved. As follows are suggested about the standard of management in artificial impediment which influence the number of trees. Firstly, impediment in crown area must be restricted under 20%, but in case outside of the area is not artificial the rate could be higher considerable. Secondly, protected trees growth space secured as much as crown area and impediment must be installed outside the crown area. Thirdly, to move the protected trees, condition of growth space secure must be considered. Fourthly, to develope land, the area around protected trees should be utilized in a park, the area of impediment installation in crown area should be limited as well. Fifthly, As many shown in previous research, for the improvement of old big trees and protected trees, need the tax favor of landowner and purchase of around land, to manage, it needs the budget of local government and advice of expert. Also the study on how various kind of impediment nearby protected trees influence on them has to be continued.

• Cross-Cultural Studies
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• v.42
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• pp.451-474
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• 2016

Analysis of the syntactic structure of the modern Chinese adverbs for time 'Cengjing (曾經)' and 'Yijing (已經)' was performed to examine the tenses and aspects of the terms. The corresponding Korean words were examined and the terms in both languages were compared. The syntactic structures used in China and South Korea were found to be different. We hope the study of the Chinese language will help Korean students. 'Cengjing (曾經)' specific projects with 'aspect' of, 'Past experience aspect', 'Past continuous aspect', 'Past continuous aspect' in the past tense. [ED: unclear, please reword] These correspond to '_었 (았)_', '_었었_' in the Korean language. 'Yijing (已經)' has 'finished phase' of concrete projects, 'Past experience aspect', 'Past continuous aspect', also has a specific project tense, the 'past tense', 'present tense', 'future tense', and so tense. [ED: unclear, please reword] Adjectives can also be modified with a 'change of status'. These correspond to '_었 (았)_', '_고_', '_었었_', '곧' etc. in Korean. 'Cengjing (曾經)' and the dynamic auxiliary 'Guo (過)' were compared to determine whether they have the aspect and tense features. However, 'Guo (過)' can only modify the predicate verb, so it possesses only aspect characteristics. 'Cengjing (曾經)' modifies the range more widely. 'Yijing (已經)' may be modified by the adverb 'Zai (在)' whereas 'Cengjing (曾經)' may not. Additionally, 'Yijing (已經)' can be modified by predicate adjectives and noun predicates, while 'Cengjing (曾經)' cannot.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.