• 한국비블리아학회지
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• 제24권1호
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• pp.149-169
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• 2013

본 연구는 이용자의 요구에 필요한 자원을 확보하기 위해 지역사회 내의 작은도서관들이 연계 및 협력하는 네트워크의 특성을 탐색적으로 분석하였다. 이를 위해 부천지역 내의 60개의 작은도서관을 대상으로 협력네트워크에 관한 관계데이터를 수집하였다. 네트워크의 구조적인 특성을 분석하기 위해 사회연결망분석법을 사용하였다. 분석 결과 공립작은도서관 간에는 연계가 긴밀하게 이루어지고 있었다. 중심성에서도 공립작은도서관이 상위그룹을 형성하였고 지방자치단체 등 외부 행위자를 포함한 네트워크에서도 공공도서관과 공립작은도서관이 중심적인 역할을 수행하고 있는 것으로 나타났다. 반면에 사립작은도서관은 대부분 고립되어 있어 연계가 미약한 것으로 분석되었다.

• 인터넷정보학회논문지
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• 제25권4호
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• pp.73-86
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• 2024

With the acceleration of regional economic integration, the agricultural trade network within the RCEP region presents new opportunities and challenges for member countries. This study focuses on agricultural trade among RCEP members from 2011 to 2020, utilizing social network analysis to explore the structural characteristics and evolutionary trends of the trade network. Additionally, an extended gravity model is employed to empirically analyze the key factors influencing South Korea's agricultural trade with other member countries. The findings reveal that: (1) Agricultural trade relationships within the RCEP region are stable and mature, with high interconnectivity in the trade network, indicating a trend towards balanced development. (2) The positions of member countries within the agricultural trade network are characterized by both high density and heterogeneity. (3) South Korea's agricultural trade with RCEP member countries is positively influenced by the economic size, population size, and governance level of its trading partners, while South Korea's own indicators show no significant effect. The trade distance between South Korea and member countries also has a positive impact on agricultural trade. By combining social network analysis with an extended gravity model, this study provides a multi-faceted quantitative analysis of the RCEP agricultural trade network, offering new insights into regional agricultural trade. It also provides empirical evidence for agricultural trade cooperation between South Korea and other RCEP countries.

• 한국생산제조학회지
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• 제20권3호
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• pp.232-238
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• 2011

In the present study, Taguchi method is used to determine the rough region first, followed by RSM technique to determine the exact optimum value during milling on a machining center. A region reducing algorithm is applied to narrow down the region of the Taguchi method for RSM. The result from the Taguchi method is fed to train the artificial neural network (ANN), whose optimum value is used to drive the region reducing algorithm. The proposed algorithm is tested under different cutting condition and results show that the introduced algorithm works well during milling process. It is also shown that theoretically obtained optimal cutting condition is very close to experimentally obtained result.

• 무역상무연구
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• 제27권
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• pp.69-95
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• 2005

East Asia has played an important role in the economic and social development in the Asian pacific region and in the global arena. In the region the impact of companies centralizing their logistics activities around a few distribution centers has already led some leading ports such as Singapore, Hong Kong to transform and expand their functions and business activities to provide port users with value added logistics services. Other ports in the region also have an important part to play in the total logistics Chain. In these environments, the maritime activities of Jang BoGo, who was the maritime king of the commercial maritime empire in East Asia in the 9th century, give many implications to the international logistics network strategy that Korea has to take in order to become a power of International Logistics. Though the trading and economic environments at that time may be quite different from today, the super-national maritime management pattern that Jang Bo-go, founder of the Northeast Asian maritime trading kingdom devised, gives us many implications in the global trading and economic environments, in the respects of overseas direct investment and international logistics. Accordingly, the paper aims to examine the establishment of hub port in Northeast Asia, modelled after the maritime network management strategy of Jang BoGo.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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• pp.327-334
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• 2003

Thermal Prestressing Method for continuous composite girder bridges is a new design and construction method developed to induce initial composite stresses in the concrete slab at negative bending regions. Due to the induced initial stresses, prevention of tensile cracks at concrete slab, reduction of steel girder section, and reduction of reinforcing bars are possible. Thus, economical and construction efficiency can be improved. Method for determining optimum heating region of Thermal Prestressing Method, has not been established although such method is essential for increasing efficiency of the designing process. Trial-and-error method used in previous studies is far from efficient and more rational method for computing optimal heating region is required. In this study, efficient method for determining optimum heating region in the use of Thermal Prestressing Method is developed based on artificial neural network algorithm, which is widely adopted to pattern recognition, optimization, diagnosis, and estimation problems in various fields. Back-propagation algorithm, which is commonly used as a learning algorithm in neural network problems, is used for training of the neural network. Through case studies of 2-span continuous and 3-span continuous composite girder bridges using the developed process, the optimal heating regions are obtained.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.849-850
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• 2006

This thesis presents a new analysis method of Vegas network model in single link single source and a new version of Vegas for expanding asymptotically stable region. Actually since original Vegas model is difficult to analysis, we use a modified Vegas network model. Since there is a few tools to analyze nonlinear system with delay, developing other methods is very important and useful. We used state space model in discrete time. Using by Jury's criterion, we could find asymptotically stable region of Vegas network model. And it was a if and only if condition. Moreover, we proposed a new version of Vegas algorithm. To expand asymptotically stable region we modified the original Vegas model. The new analysis method and new Vegas algorithm were justified by ns-2 simulation. And as compare with other result, we could know our method has many advantages.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부A
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• pp.248-252
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• 1998

The ACE Engineering, Inc. (ACE) of Seoul, Korea and The Energy Systems Institute (SEI) of Irkutsk, Russia has extensively studied the formation of an interconnected electric power systems throughout the North Eastern Asia Region(NEAR). The region encompasses East Siberia (ESR), Far East of Russia(FER), North East China(NEC), Mongolia(MON), North Korea(NKOR), South Korea(SKOR). Although geographically adjacent to each other, these countries and territories have different levels and rates of economic development, possess different reserves of energy resources which complement each other and hence, can interact to their mutual benefits. This Project is called Peace Network Project (PNP) because it seems to contribute for development of power economy and clean environment. In a word, the PEACE Network is expected to serve as "Power Economy And Clean Environment Network" and to promote the international cooperation. to expedite the peaceful reunification of North & South Korea and to revive the Korean culture in the North, and eventually contribute to the human prosperity.

• Smart Structures and Systems
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• 제24권6호
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• pp.745-757
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• 2019

Road surface deteriorations such as potholes have caused motorists heavy monetary damages every year. However, effective road condition monitoring has been a continuing challenge to road owners. Depth cameras have a small field of view and can be easily affected by vehicle bouncing. Traditional image processing methods based on algorithms such as segmentation cannot adapt to varying environmental and camera scenarios. In recent years, novel object detection methods based on deep learning algorithms have produced good results in detecting typical objects, such as faces, vehicles, structures and more, even in scenarios with changing object distances, camera angles, lighting conditions, etc. Therefore, in this study, a Deep Learning Pothole Detector (DLPD) based on the deep region-based convolutional neural network is proposed for autonomous detection of potholes from images. About 900 images with potholes and road surface conditions are collected and divided into training and testing data. Parameters of the network in the DLPD are calibrated based on sensitivity tests. Then, the calibrated DLPD is trained by the training data and applied to the 215 testing images to evaluate its performance. It is demonstrated that potholes can be automatically detected with high average precision over 93%. Potholes can be differentiated from manholes by training and applying a manhole-pothole classifier which is constructed using the convolutional neural network layers in DLPD. Repeated detection of the same potholes can be prevented through feature matching of the newly detected pothole with previously detected potholes within a small region.

• 정보처리학회논문지B
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• 제9B권3호
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• pp.311-318
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• 2002

문서영상 구조분석은 문서영상을 세부 영역으로 분할하는 과정과 분할된 영역을 문자, 그림, 표 등으로 분류하는 과정을 포함한다. 이 중 영역분류 과정에서 영역의 크기, 흑화소 밀도, 화소 분포의 복잡도는 영역을 분류하는 기준이 된다. 그러나 그림의 경우 이러한 기준들의 범위가 넓어 경계를 정하기 어려우므로 다른 형태에 비해 상대적으로 오분류의 비율이 높다. 본 논문에서는 그림과 문자를 분류하는 과정에서 영역의 크기, 흑화소 밀도, 화소 분포의 복잡도에 의한 영향을 줄이기 위하여 메디안 필터를 이용하고, 영역확장 필터(region expanding filter)와 제한 조건들을 이용하여 영역분류에서의 오분류를 수정함으로써 상용제품을 포함한 기존 방법에 비해 그림과 문자의 분류가 우수한 문서영상 구조 분석 방법을 제안한다.

• 인터넷정보학회논문지
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• 제5권2호
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• pp.75-84
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• 2004

지오캐스팅(geocasting)이란 멀티캐스팅의 특별한 한 종류로서, 어떤 특정한 지역(지오캐스트 영역이라 함)에 있는 모든 노드들에게 데이터를 전송하는 통신형태를 말하며, location-based multicasting(LBM) 이라고 부르기도 한다(1). Ad-hoc 네트워크는 중앙 집중화된 관리나 표준화된 지원 서비스 없이 배터리를 에너지원으로 사용하는 휴대용 기기들이 동적으로 연결되어 구성되는 임시적인 망이다. 따라서, 제한된 에너지 자원을 효율적으로 관리하는 것은 네트워크 활동시간(lifetime)을 최대화하기 위한 중요한 문제가 된다. 본 논문에서는 Ad-hoc 네트워크 환경에서 라우팅 설정시 에너지 값을 고려하여 중간 노드를 선택하는 LBPA(Location-Based Power Aware) 지오캐스팅 알고리즘을 제안한다. 전송 에너지를 균형있게 소비하여 각 이동 호스트의 잔여 에너지의 비율을 일정하게 유지시키는 방법으로 네트워크 활동시간 측면에서 볼 때 기존의 LBM 알고리즘보다 평균적으로 49%, 더 좋은 결과를 실험을 통하여 보여주었다.