• Journal of the Korean association of regional geographers
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• v.10 no.4
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• pp.787-799
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• 2004

The industrial community in a metropolis has played an essential role to keep business in a large city. This paper aims to analyze the realities of trade network among enterprises at Buksungro Tools Commercial Cooperative in Daegu. The urban style industrial community is found at Buksungro in Daegu. There are more than one hundred small-sized enterprises. Major trades among enterprises are occurred within and/or by the area. The long-term trade networks within the Buksungro Tools Commercial Cooperative have played the key role to maintain the industrial community. The trade relationship has depended on business networks based on social capital rather than commercial mechanism. The trade networks have been established through credit transactions as well as handling troublesome orders. The trade networks help to transfer technology and to learn the tacit knowledge among firms. The long-term trade networks are more influenced by the social accessibility than spatial accessibility.

• Journal of the Economic Geographical Society of Korea
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• v.4 no.1
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• pp.19-35
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• 2001

This paper is concerned with the relationships between large firms with global reaches in their markets and subcontracting firms, mostly small and medium-sized firms. It then attempts to focus in more detail on the dynamic relational dimensions between the two. In doing so, we draw upon the secondary data and the results of interviewing survey with some senior managers. The empirical study shows that the localisation of subcontracting networks have been increasingly reinforced thanks to the increasing tendency of vertical disintegration by LC. However, it is identified that there is a tendency that local subcontractors are specialised in producing relatively low value-added and low technology-intensive electronic parts/components. Based on these results, the author suggests the implications of regional economic development in the context of innovation and learning.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.535-544
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• 2018

Autonomous driving can be limited by only using sensors if the sensor is blocked by sudden changes in surrounding environments or large features such as heavy vehicles. In order to overcome the limitations, the precise road-map has been used additionally. This study was conducted to segment and classify road objects using 3D point cloud data acquired by terrestrial mobile mapping system provided by National Geographic Information Institute. For this study, the original 3D point cloud data were pre-processed and a filtering technique was selected to separate the ground and non-ground points. In addition, the road objects corresponding to the lanes, the street lights, the safety fences were initially segmented, and then the objects were classified using the support vector machine which is a kind of machine learning. For the training data for supervised classification, only the geometric elements and the height information using the eigenvalues extracted from the road objects were used. The overall accuracy of the classification results was 87% and the kappa coefficient was 0.795. It is expected that classification accuracy will be increased if various classification items are added not only geometric elements for classifying road objects in the future.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.4
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• pp.16-21
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• 2023

Although the global number of landmines is on a declining trend, the damages caused by previously buried landmines persist. In light of this, the present study contemplates solutions to issues and constraints that may arise due to the improvement of mine detection equipment and the reduction in the number of future soldiers. Current mine detectors lack data storage capabilities, posing limitations on data collection for research purposes. Additionally, practical data collection in real-world environments demands substantial time and manpower. Therefore, in this study, gprMax simulation was utilized to generate data. The lightweight CNN-based model, MobileNet, was trained and validated with real data, achieving a high identification rate of 97.35%. Consequently, the potential integration of technologies such as deep learning and simulation into geographical detection equipment is highlighted, offering a pathway to address potential future challenges. The study aims to somewhat alleviate these issues and anticipates contributing to the development of our military capabilities in becoming a future scientific and technological force.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.82-98
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• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.715-722
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• 1999

This paper was studied on developmental direction of Telecommunications system for aged welfare policy. The results of this study is as follow: An economic needs must development of home shopping system, home banking system and telecommuting system. A medical needs must development of medical support system, medical information system and telemedical support system. A house needs must development of home automatic system, internet system. A culture needs must development of event system, leisure information system. A traffic needs must development of automatic traffic geographical system, automatic operating system. An education needs must development of teleeducation system, knowledge studying support system.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.4
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• pp.647-660
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• 2008

The main thrusts of Canadian regional innovation policy lies in the two tract system. Federal government decides only the strategic research and development sectors and priorities, and then researchers and stockholders in the regions decide and implement the specific networking relationships and appropriate governance system. This paper reviewed the decentralized and market-friendly Canadian regional innovation support system and the characteristics of Canadian innovation clusters: Learning, Labour, Location, Leadership, Legislation/ Labs. finally, policy implications for Korean regional innovation system such as networking, formation of social capital, and business support systems are offered.

• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.65-65
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• 2010

지구상의 광물, 암석, 화석 그리고 지질구조, 지형 등의 개개의 지형 지질학적 요소의 특성과 다른 대상과의 상호관계를 지질다양성이라고 한다. 지질다양성은 지형 지질에 내재되어 있는 본질적, 문화적, 심미적, 경제적, 기능적, 연구 및 교육적 가치를 이해하고 보전함으로써 유지 할 수 있다. 이 연구는 지질다양성에 대한 흥미와 이해를 높이기 위해 학술적 보전 가치가 있는 강원도 영월지역을 선정하여 그 특징을 분석하고 지질다양성을 효율적으로 활용하는 방안을 제언하고자 한다. 강원도 영월지역의 지질다양성에 대한 조사는 지형경관 자원과 지질특성의 희소성, 대표성, 학문적 가치 및 활용가치에 중점을 두고 전문가와 협의하여 보존가치가 있고 지리적으로 접근하기 편리한 노두 8곳을 선별하였다. 선별된 8곳의 노두는 고생대의 암석과 지층, 뚜렷한 퇴적구조, 화석, 규모가 크고 전형적인 하천지형이 나타나는 곳으로 지질유산(지형 지질)의 내재적 가치와 지구과학적 이해를 도울 수 있는 대상지이다. 대상지의 지질다양성에 대한 조사를 토대로 야외 지질학습장과 지질공원 및 지질명소, 과학적 특별흥미지역 등을 개발하여 제공함으로써 지형 지질에 대한 자기주도적 학습 능력 신장과 지구과학에 대한 흥미와 이해를 증진시키는 장을 마련해 줄 수 있을 것이다. 또한 과학적 가치와 더불어 사회적, 문화적 가치를 부여하여 보전함으로써 지질유산(지형 지질)에 대한 새로운 시각이 생길 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.484-484
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• 2023

지진해일은 해저지진, 화산활동, 해저 산사태 등에 의해 발생되는 장주기 파랑이다. 지진해일은 발생빈도가 낮지만, 한번 발생하면 많은 에너지가 연안으로 유입되어 인명 및 재산피해를 야기 시킬 수 있다. 따라서, 과거 수십년동안 지진해일에 대한 연구는 지진해일의 역학관계를 이해하고, 이를 바탕으로 한 수치모델 개발에 초점을 두어 연구가 진행되어 왔다. 더욱이, 지진해일 실험적 연구는 많은 경제적 비용을 지불해야 하기에 수치모델개발 연구가 더욱 중점적으로 수행되어 왔다. 지리학적으로 우리나라는 지진해일에 안전하지 못하다. 하나의 예로, 1983년 5월 26일, 일본 서해안에서 발생한 지진해일은 동해로 전파되어 동해안 지역에 커다란 피해를 야기시켰다. 이 당시, 강원도삼척시 원덕읍에 위치한 임원항에서는 2명의 사상자와 2명의 부상자가 발생하였고, 당시 금액으로 약3억원의 재산피해가 발생하였다. 이 연구는 인공지능 기법 중 하나인 인공신경망을 이용하여 인명과 재산피해가 발생한 임원항에서 최대지진해일고를 예측하고자 하였다. 지진해일 수치모델은 뛰어난 정확도를 나타내는 반면, 결과를 산출하는데 상당한 시간을 필요로 한다. 이에 반해, 인공신경망은 수치모델과 유사한 정확도 및 결과를 신속하게 제공할 수 있다는 장점을 가지고 있다. 지진해일 인공신경망 모델 개발은 지진의 단층파라미터를 바탕으로 작성된 지진해일의 시나리오를 토대로 연구가 진행되었고, 우리나라 동해에 위치한 외해 관측 지점의 지진해일고 자료를 통해, 임원항에서의 최대 지진해일고가 예측되도록 개발되었다. 이를 위하여, 인공신경망의 학습 및 검증 과정을 수행하였고, 향후 발생 가능한 다양한 지진해일에 대해 평가함으로써, 인공신경망 모델의 예측성능을 확인하였다.

• Journal of the Korean earth science society
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• v.34 no.3
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• pp.235-248
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• 2013

The purpose of this study is to investigate a feasibility of a small mountain as a field work site on geological features in Earth sciences classes at all levels. Mt. Geumdang with the height of 305 meters from the sea level is located in the metropolitan city of Gwangju, southern part of Korea. The study reviews the human and natural geography, geological features, geomorphic resources, landscapes, and conveniences of the mountain for a possibility of meaningful field work. The population within the distance of 5 km from the mountain stands at about 620,000 and 170,000 of them are students and teachers. Mt. Geumdang has a warm temperature climate with low rainfall throughout the year, so it seems suitable for a field survey. Road network and public transportation system around the area are well-developed and easily accessible. Mt. Geumdang shows various rock type and geological structures. The basement rock is Gwangju granite, which is plutonic body of the Jurassic period. Also, granophyre (micrographic granite) and various volcanic rocks distributed as bedded tuff, lapilli tuff, and rhyolite of the Cretaceous period. Many andesitic and felsic dykes were intruded into the rock by joint system. In Mt. Geumdang, many geomorphic resources are found such as U shaped mountain, joint, fault, lamination, gnamma, tor, cliff, groove, block stream and block field, regolith, and saprolite. It has a beautiful mountain scenery including the view of whole shape of Mt. Mudeung, panoramic view of the town, Pungam lake, World Cup stadium and sunrise and sunset. Furthermore, the area has ecologic study facilities related to geology, emergency medical and convenience facilities for field works. In conclusion, Mt. Geumdang is highly feasible for geological field studies at all levels.