• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.255-257
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• 2011

본 연구에서는 각종 웹사이트와 이메일을 통해 전달되는 회의공지에 포함된 회의장소를 나타내는 문자열로부터 실제 위치를 추정하는 시스템을 설계 및 구현하였다. 직접 구현한 NER과 Relation-type Classification 모듈을 사용하였으며, 장소에 대한 모델은 기존의 지리정보시스템들과의 상호 운용성을 위하여 OpenStreetMap[6]과 Geonames[7]의 데이터 구조를 참조하여 설계되었고, 실제 위치를 구하기 위하여 내부자원 외에도, 각종 오픈API들을 외부자원으로 활용하였다.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.964-965
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• 2000

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.3
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• pp.219-228
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• 2001

The research into the field of managing urban utility information (such as gas pipes, power line, telecommunication utilities) is growing ever more important as the efficient management of social infra-structure gets higher and also with the fast technological progress made in nationwide scale of geo-spatial information systems. This research is focused on the collection of street utilities information in urban areas using aerial ortho-images. Until now this has been carried out by on site investigation and ground surveying methods. The result of this research shows that the geometric accuracy was obtainable within 12 cm referenced to 1/1,000 digital map. It was also possible to collect the street utilities which were described in the digital map as well as other information which were not.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.439-446
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• 2015

Recently, semantic trajectories which combine GPS positions and POIs(Point of Interests) become more popular in order to expand location based services. To construct semantic trajectories, the existing algorithms exploit the extent information of POIs described as polygons and find overlapping regions between GPS positions and the extents. However, the algorithms are not applicable in the condition where the extent information is not provided such as in Google Map, Naver Map, OpenStreetMap and most of the open geographic information systems. In this paper, we provide a novel algorithm to construct semantic trajectories only with GPS positions and POI points but without POI extents.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.217-220
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• 2005

Internal cities such as gray level been enclosed to building forest are paying a lot of efforts and expenses to change to green city toot park and street tree get put together. By the example, 'GREEN CITY of PUSAN 21' progress to decorate army facilities like the park, and to plant street trees in several places of city plan in Pusan. And urban environment that big citys of advanced nation are agreeable is making in the large park and road street trees at several places in downtown. Because price of tree for the park is very expensive, tree management system was all-important. In this paper, Motes deliver the sensor information in each tree through radio sensor network by server side. This information can use in state grasping of tree, harmful insects courtesy call etc and this system design was suggested to inform to mode of life administration scholars.

• Journal of the Korean Home Economics Association
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• v.37 no.12 s.142
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• pp.1-11
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• 1999

The purpose of this study is to investigate the color preference of women living in Seoul, to provide materials which is useful for setting up the color plan for a better costume, and to suggest new information in the apparel study. This study is done on the basis of color preference only by age and the range of this study restricted on womens' clothes. The subjects of this research are 1,100 young adult women and 1,244 elderly women photographed in the street. The data are analyzed by frequency and percentage. The results of this study are as follows ; The preference of chromatic color and achromatic color, tint and tone, pattern of textiles are different mainly by age. 1. Elderly women prefer achromatic colors to chromatic colors. The most preferred achromatic color is black, especially elderly women prefer black. 2. Analysis of tint shows that blue, red and yellow red are commonly preferred by women. Especially blue is preferred by young women : red and yellow red are preferred by elderly women. 3. Analysis of tone shows that vivid, pale, dark tones are commonly preferred by women. Especially vivid tone is preferred by elderly women, while pale tone is preferred by young women 4. Analysis of pattern of textiles shows at, pattern textiles are preferred by elderly women rather than by young women. The most preferred pattern for elderly women is a flower pattern, and for young women a stripe pattern.

• Korean Security Journal
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• no.51
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• pp.199-219
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• 2017

This research examined the degree to which open-street closed-circuit television (CCTV) systems reduced crime in the vicinity of elementary schools. Information including crime dates, locations, and types around nine elementary schools in the city of Chuncheon in South Korea where the cameras had been installed was gathered and assessed. By employing the Poisson regression with "month" as the unit of analysis and controlling for the days in each month, the average monthly temperatures, and crime trends, the research results show that the CCTV installations had an impact on the reduction of total crime and serious crime. However, the same reduction effect was not observed for disorder crime. Therefore, the results of this study suggest that the employing CCTV is an effective way to control overall crime rates, especially serious crime.

• Journal of Fashion Business
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• v.12 no.3
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• pp.1-15
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• 2008

The purpose of this study is to analyze women's street fashion in Shenyang and to understand the regional design preference. The city, Shenyang is not only known as the one of three major northeastern province in China, but also known as the city where large numbers of Korean fashion companies have launched in. The observation focused mainly on young/young adults and missy in Oe Market and ZungJie(中街) which are the most busy streets in Shenyang. A digital camera or a camcorder were used to take photos of these women. In addition, video captures or photos were analyzed by three fashion experts. Finally, the photos were classified by item and data was coded for statistics and reviewed through frequency and percentage. As a result, it was found that most young women in Shenyang liked to wear a casual style such as easy t-shirt, denim pants or skirt and a feminine style such as a one-piece dress in summer. Top items that were favoured by young women in Shenyang were t-shirts and blouse types, while they favoured to wear denim pants of indigo blue for bottom items. Frequently found colors among these womens' clothing were white, black, vivid blue, red and red purple. I strongly believe this study will provide basic but significant information for the establishment of design and marketing strategies to the Korean fashion brands, who is trying to access Chinese fashion market.

• Korea Science and Art Forum
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• v.20
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• pp.255-265
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• 2015

When it comes to how to define history·culture streets, people think of the streets as street environments that would create local identity in association with this local community's particular historical and cultural resources as well as urban streets. In order to build such streets, any relevant fields first need to apply some original design based on understanding on historical and cultural resources. With Street of Gaya in Gimhae selected as a research subject, this study aims to look into components and color characteristics of the history·culture street and finds ways to create other streets of that kind. As a frame to understand the history·culture streets, what this study would come up with is considered significant in that it helps the value to be re-recognized and promoted. In order to achieve the research goal, the study (1) extracted components of streetscapes referring to relevant previous researches and then, (2) analyzed a current status of these components of Street of Gaya via field investigation. (3) The study examined color characteristics of each of the components. Findings of the research are summarized as follows. (1) From a comprehensive point of view, the study categorized and subdivided the components of the history·culture street into nonphysical and physical elements. (2) After analyzing the current status of the components, the study learned that Street of Gaya basically consists of historical and cultural remains and sculptures as well as street facilities. (3) Results of the color investigation reported that the plan on designing of Street of Gaya had been processed with a focus laid on harmony of historical remains and cultural remains which are told to be natural components. However, the study also figured out that as long as relevant fields want to create different identity in each section and to efficiently deliver information, they should first prepare this smart design system to integrate each pieces of a streetscape as a whole.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.855-870
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• 2020

Windows are key components of building facades. Detecting windows, crucial to 3D semantic reconstruction and scene parsing, is a challenging task in computer vision. Early methods try to solve window detection by using hand-crafted features and traditional classifiers. However, these methods are unable to handle the diversity of window instances in real scenes and suffer from heavy computational costs. Recently, convolutional neural networks based object detection algorithms attract much attention due to their good performances. Unfortunately, directly training them for challenging window detection cannot achieve satisfying results. In this paper, we propose an approach for window detection. It involves an improved Faster R-CNN architecture for window detection, featuring in a window region proposal network, an RoI feature fusion and a context enhancement module. Besides, a post optimization process is designed by the regular distribution of windows to refine detection results obtained by the improved deep architecture. Furthermore, we present a newly collected dataset which is the largest one for window detection in real street scenes to date. Experimental results on both existing datasets and the new dataset show that the proposed method has outstanding performance.