• Title/Summary/Keyword: 공간군집화

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Analysis of the Inflow of Independently-located Manufacturing Factories in Non-urbanized Area of the Capital Region (수도권 비도시지역으로의 개별입지 제조업체 유입 실태 분석)

  • Yang, Wontak;Lee, Heeyeon
    • Journal of the Economic Geographical Society of Korea
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    • v.19 no.2
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    • pp.209-224
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    • 2016
  • The purpose of this study are to analyze the realities and characteristics of the inflow manufacturing factories located in non-urbanized area in the Capital region, and to extract the problems from locational point of view during the last 10 years. Using the raw data of factory registration statistics from 2006 to 2015, this study has intended to show the distributional characteristics of the independently-located manufacturing factories by various mapping methods. As a result, about 90% of the factories are heavily concentrated into 10 adjacent regions to Seoul and large cities. This study carried out questionaire surveys and in-depth interview to the leaders of Janganmyeon, Hwaseong-shi which have experienced the rapid increase of manufacturing factories. The independently-located factories have caused environmental pollution, destroyed rural village landscape, and affected the negative impact of the neighborhood community. The results of this study provide some implications to establish a desirable industrial location policy of non-urban areas in Capital region.

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Study on Water Stage Prediction by Artificial Neural Network and Genetic Algorithm (인공신경망과 유전자알고리즘을 이용한 수위예측에 관한 연구)

  • Yeo, Woon-Ki;Jee, Hong-Kee;Lee, Soon-Tak
    • Proceedings of the Korea Water Resources Association Conference
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    • 2010.05a
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    • pp.1159-1163
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    • 2010
  • 최근의 극심한 기상이변으로 인하여 발생되는 유출량의 예측에 관한 사항은 치수 이수는 물론 방재의 측면에서도 역시 매우 중요한 관심사로 부각되고 있다. 강우-유출 관계는 유역의 수많은 시 공간적 변수들에 의해 영향을 받기 때문에 매우 복잡하여 예측하기 힘든 요소이다. 과거에는 추계학적 예측모형이나 확정론적 예측모형 혹은 경험적 모형 등을 사용하여 유출량을 예측하였으나 최근에는 인공신경망과 퍼지모형 그리고 유전자 알고리즘과 같은 인공지능기반의 모형들이 많이 사용되고 있다. 하지만 유출량을 예측하고자 할 때 학습자료 및 검정자료로써 사용되는 유출량은 수위-유량 관계곡선식으로부터 구하는 경우가 대부분으로 이렇게 유도된 유출량의 경우 오차가 크기 때문에 그 신뢰성에 문제가 있을 것으로 판단된다. 따라서 본 논문에서는 선행우량 및 수위자료로부터 단시간 수위예측에 관해 연구하였다. 신경망은 과거자료의 입 출력 패턴에서 정보를 추출하여 지식으로 보유하고, 이를 근거로 새로운 상황에 대한 해답을 제시하도록 하는 인공지능분야의 학습기법으로 인간이 과거의 경험과 훈련으로 지식을 축적하듯이 시스템의 입 출력에 의하여 연결강도를 최적화함으로서 모형의 구조를 스스로 조직화하기 때문에 모형의 구조에 적합한 최적 매개변수를 추정할 수 있다. 따라서 정확한 예측이 어려운 하천수위를 과거의 자료로 부터 학습된 신경망의 수학적 알고리즘을 통해 유출량의 예측에 적용할 수 있을 것이다. 유전자 알고리즘은 적자생존의 생물학 원리에 바탕을 둔 최적화 기법중의 하나로 자연계의 생명체 중 환경에 잘 적응한 개체가 좀 더 많은 자손을 남길 수 있다는 자연선택 과정과 유전자의 변화를 통해서 좋은 방향으로 발전해 나간다는 자연 진화의 과정인 자연계의 유전자 메커니즘에 바탕을 둔 탐색 알고리즘이다. 즉, 자연계의 유전과 진화 메커니즘을 공학적으로 모델화함으로써 잠재적인 해의 후보들을 모아 군집을 형성한 뒤 서로간의 교배 혹은 변이를 통해서 최적 해를 찾는 계산 모델이다. 따라서 본 연구에서는 인공신경망의 가중치를 유전자 알고리즘에 의해 최적화시킨후 오류역전파알고리즘에 의해 신경망의 학습을 진행하는 모형으로 감천유역의 선산수위표지점의 수위를 1시간~6시간까지 예측하였다.

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Key Point Extraction from LiDAR Data for 3D Modeling (3차원 모델링을 위한 라이다 데이터로부터 특징점 추출 방법)

  • Lee, Dae Geon;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.5
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    • pp.479-493
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    • 2016
  • LiDAR(Light Detection and Ranging) data acquired from ALS(Airborne Laser Scanner) has been intensively utilized to reconstruct object models. Especially, researches for 3D modeling from LiDAR data have been performed to establish high quality spatial information such as precise 3D city models and true orthoimages efficiently. To reconstruct object models from irregularly distributed LiDAR point clouds, sensor calibration, noise removal, filtering to separate objects from ground surfaces are required as pre-processing. Classification and segmentation based on geometric homogeneity of the features, grouping and representation of the segmented surfaces, topological analysis of the surface patches for modeling, and accuracy assessment are accompanied by modeling procedure. While many modeling methods are based on the segmentation process, this paper proposed to extract key points directly for building modeling without segmentation. The method was applied to simulated and real data sets with various roof shapes. The results demonstrate feasibility of the proposed method through the accuracy analysis.

Spatial Variations of Salt Marsh Plants Induced by Sandy Sediment in Hampyeong Tidal Flat (함평만 갯벌의 모래 퇴적물로 인한 염습지 식물의 공간적 변이)

  • Minki, Hong;Jaeyeon, Lee;Jeong-Soo, Park;Hyohyemi, Lee
    • Ecology and Resilient Infrastructure
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    • v.9 no.4
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    • pp.247-258
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    • 2022
  • Hampyeong Bay has a narrow seawater channel and a complex topographical structure. The sand content of the tidal flat soil is increasing due to asymmetrical sedimentation. Through the investigation of the vegetation distribution and the use of the line-transect method, sand flats were observed to gradually change the vegetation distribution of salt marshes. Comparing the vegetation area between 2016 and 2022, the obligate halophyte Suaeda maritima decreased by 74% and Zoysia sinica increased by 75%. Z. sinica seems to support the robustness of the dune environment by trapping sediments such as sand in the colony, because the underground rhizomes and stems are highly developed. To establish an effective conservation management plan for tidal flats, an integrated study should be conducted to assess the impact of changes in tidal flat soil and the interaction of vegetation communities in Hampyeong Bay.

Technology Trends in CubeSat-Based Space Laser Communication (큐브위성 기반 우주 레이저 통신 기술 동향)

  • Chanil Yeo;Young Soon Heo;Siwoong Park;Hyoung Jun Park
    • Journal of Space Technology and Applications
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    • v.4 no.2
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    • pp.87-104
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    • 2024
  • CubeSats are being utilized in various fields such as Earth observation, space exploration, and verification of space science and technology due to their low cost, short development period, enhanced mission-oriented performance, and ability to perform various missions through constellation and formation flights. Recently, as the availability of CubeSats has increased and their application areas have expanded, the demand for high-speed transmission of large amounts of data obtained by CubeSats has increased unprecedentedly. Laser-based free space optical communication technology is capable of transmitting large amounts of data at high speeds compared to the existing radio communication methods, and provides various advantages such as use of unlicensed spectrum, low cost, low power, high security characteristics, and of use a small communication platform. For this reason, it is suitable as a high-performance communication technology to support CubeSat missions. In this paper, we will present the core components and characteristics of CubeSat-based space laser communication system, and recent research trends, as well as representative technology development results.

Game-bot detection based on Clustering of asset-varied location coordinates (자산변동 좌표 클러스터링 기반 게임봇 탐지)

  • Song, Hyun Min;Kim, Huy Kang
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.5
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    • pp.1131-1141
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    • 2015
  • In this paper, we proposed a new approach of machine learning based method for detecting game-bots from normal players in MMORPG by inspecting the player's action log data especially in-game money increasing/decreasing event log data. DBSCAN (Density Based Spatial Clustering of Applications with Noise), an one of density based clustering algorithms, is used to extract the attributes of spatial characteristics of each players such as a number of clusters, a ratio of core points, member points and noise points. Most of all, even game-bot developers know principles of this detection system, they cannot avoid the system because moving a wide area to hunt the monster is very inefficient and unproductive. As the result, game-bots show definite differences from normal players in spatial characteristics such as very low ratio, less than 5%, of noise points while normal player's ratio of noise points is high. In experiments on real action log data of MMORPG, our game-bot detection system shows a good performance with high game-bot detection accuracy.

Graph Cut-based Automatic Color Image Segmentation using Mean Shift Analysis (Mean Shift 분석을 이용한 그래프 컷 기반의 자동 칼라 영상 분할)

  • Park, An-Jin;Kim, Jung-Whan;Jung, Kee-Chul
    • Journal of KIISE:Software and Applications
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    • v.36 no.11
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    • pp.936-946
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    • 2009
  • A graph cuts method has recently attracted a lot of attentions for image segmentation, as it can globally minimize energy functions composed of data term that reflects how each pixel fits into prior information for each class and smoothness term that penalizes discontinuities between neighboring pixels. In previous approaches to graph cuts-based automatic image segmentation, GMM(Gaussian mixture models) is generally used, and means and covariance matrixes calculated by EM algorithm were used as prior information for each cluster. However, it is practicable only for clusters with a hyper-spherical or hyper-ellipsoidal shape, as the cluster was represented based on the covariance matrix centered on the mean. For arbitrary-shaped clusters, this paper proposes graph cuts-based image segmentation using mean shift analysis. As a prior information to estimate the data term, we use the set of mean trajectories toward each mode from initial means randomly selected in $L^*u^*{\upsilon}^*$ color space. Since the mean shift procedure requires many computational times, we transform features in continuous feature space into 3D discrete grid, and use 3D kernel based on the first moment in the grid, which are needed to move the means to modes. In the experiments, we investigate the problems of mean shift-based and normalized cuts-based image segmentation methods that are recently popular methods, and the proposed method showed better performance than previous two methods and graph cuts-based automatic image segmentation using GMM on Berkeley segmentation dataset.

A ground condition prediction ahead of tunnel face utilizing time series analysis of shield TBM data in soil tunnel (토사터널의 쉴드 TBM 데이터 시계열 분석을 통한 막장 전방 예측 연구)

  • Jung, Jee-Hee;Kim, Byung-Kyu;Chung, Heeyoung;Kim, Hae-Mahn;Lee, In-Mo
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.21 no.2
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    • pp.227-242
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    • 2019
  • This paper presents a method to predict ground types ahead of a tunnel face utilizing operational data of the earth pressure-balanced (EPB) shield tunnel boring machine (TBM) when running through soil ground. The time series analysis model which was applicable to predict the mixed ground composed of soils and rocks was modified to be applicable to soil tunnels. Using the modified model, the feasibility on the choice of the soil conditioning materials dependent upon soil types was studied. To do this, a self-organizing map (SOM) clustering was performed. Firstly, it was confirmed that the ground types should be classified based on the percentage of 35% passing through the #200 sieve. Then, the possibility of predicting the ground types by employing the modified model, in which the TBM operational data were analyzed, was studied. The efficacy of the modified model is demonstrated by its 98% accuracy in predicting ground types ten rings ahead of the tunnel face. Especially, the average prediction accuracy was approximately 93% in areas where ground type variations occur.

A Study on the Satisfaction of Senior Welfare Centers by Senior's Lifestyle (노인의 라이프스타일 유형에 따른 노인복지관에 대한 만족도 연구)

  • Lee, Song Hyun;Eo, Sung Sin;Hwang, Yeon Sook
    • Design Convergence Study
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    • v.15 no.3
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    • pp.171-186
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    • 2016
  • With the continuous rise of elderly population and rapid progression of aging in our society, greater emphasis is placed on the importance of local seniors welfare centers as representative service space that meets the diverse needs of local residents. In addition, there is a growing tendency among current users to seek high-quality service as their educational level, economic ability and lifestyle have changed for the better compared to past generations. Accordingly, this study analyzed the satisfaction of senior welfare centers according to life-style type of the elderly, using a lifestyle measurement tool which incorporates indicators of gerontographics. A survey was conducted with users of seven senior welfare centers located in Seoul. Analysis results are as follows: First, four types of lifestyle were derived through cluster analysis; independent activity type, protective activity type, active challenge type, and passive challenge type. Second, it was found that the overall satisfaction of seniors welfare centers by the life-style of the elderly is highest for the protective activity type followed by the passive challenge type, the active challenge type, and the independent activity type. Third, upon examining the effect of spatial characteristics of welfare centers on the satisfaction of elderly users by type of lifestyle, it was found that the independent activity type and the passive challenge type users are most influenced by intimacy, the protective activity type users by comfort, and the active challenge type users by convenience.

Classification and discrimination of excel radial charts using the statistical shape analysis (통계적 형상분석을 이용한 엑셀 방사형 차트의 분류와 판별)

  • Seungeon Lee;Jun Hong Kim;Yeonseok Choi;Yong-Seok Choi
    • The Korean Journal of Applied Statistics
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    • v.37 no.1
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    • pp.73-86
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    • 2024
  • A radial chart of Excel is very useful graphical method in delivering information for numerical data. However, it is not easy to discriminate or classify many individuals. In this case, after shaping each individual of a radial chart, we need to apply shape analysis. For a radial chart, since landmarks for shaping are formed as many as the number of variables representing the characteristics of the object, we consider a shape that connects them to a line. If the shape becomes complicated due to the large number of variables, it is difficult to easily grasp even if visualized using a radial chart. Principal component analysis (PCA) is performed on variables to create a visually effective shape. The classification table and classification rate are checked by applying the techniques of traditional discriminant analysis, support vector machine (SVM), and artificial neural network (ANN), before and after principal component analysis. In addition, the difference in discrimination between the two coordinates of generalized procrustes analysis (GPA) coordinates and Bookstein coordinates is compared. Bookstein coordinates are obtained by converting the position, rotation, and scale of the shape around the base landmarks, and show higher rate than GPA coordinates for the classification rate.