• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2011년 춘계학술대회논문집
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• pp.286-290
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• 2011

This paper introduces the optimum macro-siting of a potential site for an offshore wind farm around Jeju Island using the RDAPS sea wind model. The statistical model was developed by analyzing the sea wind data from RDAPS model, and the meso-scale digital wind map was prepared. To develop the high resolution spatial calibration model, Artificial Neural Network(ANN) models were used to construct the wind and bathymetric maps. Accuracy and consistency of wind/bathymetric spatial calibration models were obtained using analysis of variance. The optimization problem was defined to maximize the energy density satisfying the criteria of maximum water depth and maximum distance from the coastline. The candidate site was selected through Genetic Algorithm(GA). From the results, it is possible to predict roughly a candidate site location for the installation of the offshore wind jam, and to evaluate the wind resources of the proposed site.

• 대한산업공학회지
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• 제28권3호
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• pp.274-282
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• 2002

This paper discusses a multi-dimensional analysis for Customer Relationship Management (CRM). For this, We propose a decision-making methodology which employs three analysis models. The first model is a three-dimension positioning map to derive a strategy which achieves the Process Value Line (PVL). The second model is the web-shape analysis model to visibly understand the individual based on the customer CSI (Customer Satisfactory Index) data. The third model which supports the web-shape analysis model, is the relative satisfactory analysis model. It considers a satisfaction level after purchasing against before purchasing. Then we perform overall analysis based on the three analysis models to provide marketing strategies to decision makers.

• 한국정밀공학회지
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• 제20권5호
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• pp.47-56
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• 2003

Geometric cutting-simulation and verification play an important role in detecting NC machining errors in mold & die manufacturing and thereby reducing correcting time & cost on the shop floor. Current researches in the area may be categorized into view-based, solid-based, and discrete vector-based methods mainly depending on workpiece models. Each methodology has its own strengths and weaknesses in terms of computing speed, representation accuracy, and its ability of numerical inspection. The paper proposes a hybrid modeling scheme for workpiece representation with z-map model and discrete vector model, which performs 3-axis and 5-axis cutting-simulation via tool swept surface construction by connecting a sequence of silhouette curves.

• International Journal of Internet, Broadcasting and Communication
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• 제9권1호
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• pp.9-17
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• 2017

This paper describes a process of developing commercial real time image recognition system with company. In this paper we will make a system that is combining an empirical kernel map method and conjugate least squares support vector machine in order to represent images in a low-dimensional subspace for real time image recognition. In the traditional approach calculating these eigenspace models, known as traditional PCA method, model must capture all the images needed to build the internal representation. Updating of the existing eigenspace is only possible when all the images must be kept in order to update the eigenspace, requiring a lot of storage capability. Proposed method allows discarding the acquired images immediately after the update. By experimental results we can show that empirical kernel map has similar accuracy compare to traditional batch way eigenspace method and more efficient in memory requirement than traditional one. This experimental result shows that proposed model is suitable for commercial real time image recognition system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권4호
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• pp.313-321
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• 2014

In the current era of data-intensive services, the handling of big data is a crucial issue that affects almost every discipline and industry. In this study, we propose a classification method for large volumes of numeric data, which is implemented in a distributed programming framework, i.e., MapReduce. The proposed method partitions the data space into a grid structure and it then models the probability distributions of classes for grid cells by collecting sufficient statistics using distributed MapReduce tasks. The class labeling of new data is achieved by k-nearest neighbor classification based on Bayesian inference.

• 한국멀티미디어학회논문지
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• 제22권9호
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• pp.1122-1131
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• 2019

This paper covers research on terrain construction for unmanned aerial vehicle simulators using spatial information that was distributed by public institutions. Aerial photography, DEM, vector maps and 3D model data were used in order to create a realistic terrain simulator. A data converting method was suggested while researching, so it was generated to automatically arrange and build city models (vWorld provided) and classification methods so that realistic images could be generated by 3D objects. For example: rivers, forests, roads, fields and so on, were arranged by aerial photographs, vector map (land cover map) and terrain construction based on the tile map used by DEM. In order to verify the terrain data of unmanned aircraft simulators produced by the proposed method, the location accuracy was verified by mounting onto Unreal Engine and checked location accuracy.

• 인터넷정보학회논문지
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• 제20권1호
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• pp.125-133
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• 2019

Company A should maintain myriad conversion tools for the purpose of making a geometric compilation of navigation maps. Company A is already using complex compilation tools, which are tailored to geographical areas and various GPS models. However, due to frequent requirement and personnel changes, there is an endless challenge for perfect tool configuration and multiple map consolidation. To solve this problem, Company A launched a process automation project using Graphviz, which is an open source workflow graph visualization software. Before implementation, they had to document their current map compilation processes and then match it with the applicable conversion tool. For effective representation of process controls, a new graphical process notation is designed, i.e. Y Block diagram. The authors will compare Y Block diagram with other process notations and explain why Y Block diagram is more useful for tool based business processes such as digital map generation processes.

• 대한원격탐사학회지
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• 제24권2호
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• pp.179-188
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• 2008

본 연구는 3차원 소음지도 제작에 요구되는 도시공간 모델을 생성하고자한다. 이를 위해 센서데이터를 사용하지 않고 기 구축된 수치지도와 도화원도만을 이용하여 지면 및 건물의 3차원 모델을 생성하는 효율적인 방법을 제시하였다. 지면모델은 수치지도의 표고점과 등고선의 고도값을 격자로 내삽하여 생성한다. 건물모델은 수치지도에서 추출한 건물의 2차원 경계와 도화원도에 취득한 건물의 고도를 융합하여 생성한다. 제안된 방법은 영등포구 전역을 포함하는 수치지도와 서로 다른 시기에 생성된 3 set의 도화원도에 적용하였다. 생성된 도시공간모델은 소음분석 및 분석결과의 3차원 가시화에 성공적으로 활용되었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.735-739
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• 2005

This paper presents a new system to estimate the head pose of human in interactive indoor environment that has dynamic illumination change and large working space. The main idea of this system is to suggest a new morphological feature for estimating head angle from stereo disparity map. When a disparity map is obtained from stereo camera, the matching confidence value can be derived by measurements of correlation of the stereo images. Applying a threshold to the confidence value, we also obtain the specific morphology of the disparity map. Therefore, we can obtain the morphological shape of disparity map. Through the analysis of this morphological property, the head pose can be estimated. It is simple and fast algorithm in comparison with other algorithm which apply facial template, 2D, 3D models and optical flow method. Our system can automatically segment and estimate head pose in a wide range of head motion without manual initialization like other optical flow system. As the result of experiments, we obtained the reliable head orientation data under the real-time performance.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.527-534
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• 2004

This study is a paper relating to between road traffic noise(RTN) and sound power level(PWL). At present to prediction of RTN is used to many experimental models and prediction methods. RTN is computed PWL using existing experimental models and prediction methods. Then, computed PWL is compared with it of measurement value, in them, it is selected model most similar to measurement value. And then, this results will watch for make Noise Map, as application field applied to computed results.