• 한국수학사학회지
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• 제13권2호
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• pp.73-86
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• 2000

This paper introduces an hypermedia program supportable for teaching secondary and upper secondary level geometry. This program links users to files written in other softwares and internet web sites to provide information and exploratory environments with softwares. The linkage with the interactive dynamic software(GSP) files to teach hyperbolic geometry is illustrated with sample screens.

• 대한지리학회:학술대회논문집
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• 대한지리학회 2004년도 춘계학술대회
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• pp.103-103
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• 2004

With the emergency of geographic information systems (GIS), the traditional layer based data model can only contain the spatial geometry and thematic attributes of phenomena. In real world, geographic phenomena have not only spatial geometry and thematic attribute but the temporal situation and the relationship between each phenomenon. (omitted)

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2008년도 한국컴퓨터종합학술대회논문집 Vol.35 No.1 (A)
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• pp.347-348
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• 2008

• 한국컴퓨터정보학회논문지
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• 제6권1호
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• pp.51-59
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• 2001

본 논문에서는 pencil beam 형성에 적합하며, 특정 방향으로 예리한 지향특성을 갖는 이중 원형 배열 안테나의 성능을 분석하였다. N개의 등방성 점원을 평면상에 정방형, 원형 이중원형 구조를 갖도록 등간격으로 배열하여 각 배열 구조에 따른 방사패턴 특성을 비교ㆍ분석 하였다. 결과적으로 이중 원형 배열 안테나가 지향 특성 또는 SLL과 HPBW의 측면에서 정방형과 원형 배열 구조보다 우수한 특성을 나타내고 있음을 확인하였다.

• Journal of the Korean Data and Information Science Society
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• 제18권2호
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• pp.375-384
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• 2007

As teachings that use the ICT are more popular, many studies on the dynamic geometry environment(DGE) are under way. An important factor emphasized in the studies is to practical use learning activities of learners. In this study, we first define the learning history data in DGE. Second we develop a prototype of the DGE that is able to collect and analyze the learning history data automatically. The environment enables not only to grasp leaning history but also to create and manage new learning objects.

• 한국통신학회논문지
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• 제42권5호
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• pp.989-991
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• 2017

본 논문은 다양한 범위의 간섭 및 잡음 영향에서 잘 동작하는 확률 기하 기반의 순방향 다중셀 네트워크 성능 근사화 방안을 제안한다. 제안 방안은 기지국 수 및 송신전력을 변수로 갖는 다중셀 네트워크 설계 문제의 간소화에 용이하게 활용될 수 있다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 추계학술발표회 논문집
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• pp.179-184
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• 2004

High-resolution satellite imagery are used in various application field such as generation of DEM, orthophto, and three dimensional city model. To define the relation between image and object space, sensor modelling and generation of the epipolar image is essential processes. As the header information or physical sensor model becomes unavailable for the end users due to the national security or commercial purpose, generation of epipolar images without these information becomes one of important processes. In this study, epipolar geometry is generated and analysed by applying two generalized sensor models; parallel and parallel-perspective model Epipolar equation of the parallel model has linear property which is relatively simple; Epipolar geometry of the parallel-perspective model is non-linear. This linear property enable us to generate epipolar image efficiently.

• 한국통신학회논문지
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• 제40권5호
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• pp.857-859
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• 2015

본 논문은 다중-홉 해양통신망의 종단간 경로 설정을 위한 ad-hoc on-demand vector (AODV) 기반의 flooding에서 발생하는 다중 복제 오버헤드를 줄이기 위해 제시된 지향성 라우팅 프로토콜을 다룬다. 확률 기하(stochastic geometry) 분석 기법을 이용하여 목표 라우팅 성공 확률과 선박국의 밀도에 따라 적응적으로 라우팅 오버헤드를 최소화하는 방식을 제안한다.

• Journal of Information Science Theory and Practice
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• 제7권2호
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• pp.32-39
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• 2019

A convolutional neural network (CNN) has been widely used in facial expression recognition (FER) because it can automatically learn discriminative appearance features from an expression image. To make full use of its discriminating capability, this paper suggests a simple but effective method for CNN based FER. Specifically, instead of an original expression image that contains facial appearance only, the expression image with facial geometry visualization is used as input to CNN. In this way, geometric and appearance features could be simultaneously learned, making CNN more discriminative for FER. A simple CNN extension is also presented in this paper, aiming to utilize geometric expression change derived from an expression image sequence. Experimental results on two public datasets (CK+ and MMI) show that CNN using facial geometry visualization clearly outperforms the conventional CNN using facial appearance only.

• 한국CDE학회논문집
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• 제4권1호
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• pp.43-51
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• 1999

Producing the relevant information (features) from the CAD models of CAM, called feature recognition or extraction, is the essential stage for the integration of CAD and CAM. Most feature recognition methods, however, have problems in the recognition of intersecting features because they do not handle the intersection geometry properly. In this paper, we propose a machining feature recognition algorithm, which has a solid model consisting of orthogonal primitives as input. The algorithm calculates candidate features and constitutes the Intersection Geometry Matrix which is necessary to represent the spatial relation of candidate features. Finally, it recognizes machining features from the proposed candidate features dividing and growing systems using half space and Boolean operation. The algorithm has the following characteristics: Though the geometry of part is complex due to the intersections of design primitives, it can recognize the necessary machining features. In addition, it creates the Maximal Feature Volumes independent of the machining sequences at the feature recognition stage so that it can easily accommodate the change of decision criteria of machining orders.