• 정보화정책
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• 제26권1호
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• pp.46-61
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• 2019

4차 산업 혁명은 산업도 교육도 대변혁을 예고하고 있다. 본 연구는 부동산 산업을 위한 교육플랫폼 제안연구로써 부동산의 최유효활용을 위해 Smart Space를 구현하는 인재교육을 목적으로 부동산 산업 인재들이 갖추어야 할 기본 RETech(Real Estate Technology)을 학습할 수 있는 SSEP(Smart Space EduPlatform)을 제안하였다. 우선, SSEP의 생태계는 지속가능성이 확보될 수 있는 기부시스템, 콘텐츠 제작도구 및 학습참여도구 등 다양한 기술적 기능, 학습자 교수자 조력자 형태의 자유로운 학습행위체계로 움직인다. 다음으로 SSEP의 서비스는 학습범주 즉, 계획 및 설계, 의사결정, 관리, 경제, 건설, 설비 6개 범주 하에 17개 중요한 RETech 강의학습 서비스와 PBL(Project-Based Learning)기반의 교육과정서비스를 제공한다. 강의서비스는 동영상 학습 콘텐츠, 부가학습자료, 학습관리 서비스가 제공되고 교육과정서비스는 교수자 워크숍, 학습자 모집 및 등록 관리, 교육과정운영 서비스들이 제공된다.

• 대한수학회지
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• 제55권3호
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• pp.735-747
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• 2018

Let M be a real hypersurface of a complex space form with constant curvature c. In this paper, we study the hypersurface M admitting Miao-Tam critical metric, i.e., the induced metric g on M satisfies the equation: $-({\Delta}_g{\lambda})g+{\nabla}^2_g{\lambda}-{\lambda}Ric=g$, where ${\lambda}$ is a smooth function on M. At first, for the case where M is Hopf, c = 0 and $c{\neq}0$ are considered respectively. For the non-Hopf case, we prove that the ruled real hypersurfaces of non-flat complex space forms do not admit Miao-Tam critical metrics. Finally, it is proved that a compact hypersurface of a complex Euclidean space admitting Miao-Tam critical metric with ${\lambda}$ > 0 or ${\lambda}$ < 0 is a sphere and a compact hypersurface of a non-flat complex space form does not exist such a critical metric.

• 대한수학회보
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• 제34권2호
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• pp.173-184
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• 1997

An n-dimensional complex space form $M_n(c)$ is a Kaehlerian manifold of constant holomorphic sectional curvature c. As is well known, complete and simply connected complex space forms are a complex projective space $P_n C$, a complex Euclidean space $C_n$ or a complex hyperbolic space $H_n C$ according as c > 0, c = 0 or c < 0.

• 대한수학회지
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• 제32권4호
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• pp.835-848
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• 1995

Let $M_n$(c) be an n-dimensional complete and simply connected Kahlerian manifold of constant holomorphic sectional curvature c, which is called a complex space form. Then according to c > 0, c = 0 or c < 0 it is a complex projective space $P_nC$, a complex Euclidean space $C^n$ or a complex hyperbolic space $H_nC$.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.3981-4004
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• 2019

This paper proposes a novel method for locating objects in real space from a single remote image and measuring actual distances between them by automatic detection and perspective transformation. The dimensions of the real space are known in advance. First, the corner points of the interested region are detected from an image using deep learning. Then, based on the corner points, the region of interest (ROI) is extracted and made proportional to real space by applying warp-perspective transformation. Finally, the objects are detected and mapped to the real-world location. Removing distortion from the image using camera calibration improves the accuracy in most of the cases. The deep learning framework Darknet is used for detection, and necessary modifications are made to integrate perspective transformation, camera calibration, un-distortion, etc. Experiments are performed with two types of cameras, one with barrel and the other with pincushion distortions. The results show that the difference between calculated distances and measured on real space with measurement tapes are very small; approximately 1 cm on an average. Furthermore, automatic corner detection allows the system to be used with any type of camera that has a fixed pose or in motion; using more points significantly enhances the accuracy of real-world mapping even without camera calibration. Perspective transformation also increases the object detection efficiency by making unified sizes of all objects.

• 한국언론정보학보
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• 제23권
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• pp.189-221
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• 2003

이 연구는 여론 지각이 의견표현에 미치는 영향을 현실공간과 사이버공간에서 비교한 연구이다. 사이버공간은 현실공간과 달리 관계로부터의 고립이 개인에게 가져다줄 위험이 미미하다. 그 결과 사이버공간은 자신의 의견을 소수 의견이라고 지각하는 사람이 다수 의견이라고 지각하는 사람들보다 의견표현을 자제해야한다고 생각할 이유가 별로 없다. 따라서 현실공간에서는 다수 지각자보다 의견표현 수준이 낮은 소수지각자라 하더라도 사이버공간에서는 다수 지각자만큼 적극적으로 의견을 표현할 것이라고 이 연구에서는 예측했다. 분석결과 이 예측은 타당한 것으로 나타났다. 또한 이 연구의 분석결과는, 다수 지각이냐 소수 지각이냐가 아니라 여론 지각과 관련하여 의견표현의 적극성에 더 큰 차이를 가져오는 것은 자신의 의견과 여론의 향방을 비교하는데 성공하느냐 여부 그 자체임을 보여준다. 현실공간에서도 소수 지각자는 최소한 비교에 실패한 사람들 즉, 의견과 지각 차원에서 명확한 판단을 하지 못하는 사람들보다 의견표현에 더 적극적이기 때문이다. 이처럼 다수지각과 소수지각이 의견표현의 적극성 정도에 미치는 영향은 공간에 따라 다르게 나타나지만, 두 공간에서 의견표현에 더 적극적인 사람들은 대체로 유사한 특성을 지닌다. 어떤 공간이든지 이슈를 중요하게 생각하는 사람일수록, 커뮤니케이션에 대한 우려를 적게 하는 사람들일수록, 그리고 나이가 많은 사람들일수록 더 적극적으로 의견을 표현한다. 다면 현실공간에서는 이에 더해 성, 진보보수성향과 같은 인구사회학적 특성이, 사이버공간에서는 온라인 대화 빈도와 같은 특성이 의견표현의 적극성 정도에 영향을 미치는 것으로 나타난다.

• International Journal of Internet, Broadcasting and Communication
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• 제9권3호
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• pp.1-8
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• 2017

Recently, the development of the head mounted display (HMD) device has attracted a great deal of attention to the actual contents. Especially, Augmented Reality (AR), which is a mixture of actual information and virtual world information, is focused on. AR HMD is able to interact by arranging virtual objects in real space through spatial recognition using depth camera. In order to naturally mix virtual space with real space, it is necessary to develop a technology for realizing spatial mapping information with high accuracy. The purpose of this paper is to evaluate the optimal configuration of augmented reality application program by realizing accurate spatial mapping information when mapping a real space and an object placement environment using HoloLens. To do this, we changed the spatial mapping information in real space to three levels, which are the number of meshes used in cubic meters to scan step by step. After that, it was compared with the 3D model obtained by changing the actual space and mesh number. Experimental result shows that the higher the number of meshes used in cubic meters, the higher the accuracy between real space and spatial mapping. This paper is expected to be applied to augmented reality application programs that require scanning of highly mapped spatial mapping information.

• Journal of Astronomy and Space Sciences
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• 제41권2호
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• pp.61-78
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• 2024

This study developed a real-time spacecraft pose estimation algorithm that combined a deep learning model and the least-squares method. Pose estimation in space is crucial for automatic rendezvous docking and inter-spacecraft communication. Owing to the difficulty in training deep learning models in space, we showed that actual experimental results could be predicted through software simulations on the ground. We integrated deep learning with nonlinear least squares (NLS) to predict the pose from a single spacecraft image in real time. We constructed a virtual environment capable of mass-producing synthetic images to train a deep learning model. This study proposed a method for training a deep learning model using pure synthetic images. Further, a visual-based real-time estimation system suitable for use in a flight testbed was constructed. Consequently, it was verified that the hardware experimental results could be predicted from software simulations with the same environment and relative distance. This study showed that a deep learning model trained using only synthetic images can be sufficiently applied to real images. Thus, this study proposed a real-time pose estimation software for automatic docking and demonstrated that the method constructed with only synthetic data was applicable in space.

• 호남수학학술지
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• 제32권4호
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• pp.747-761
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• 2010

It is known that there are no real hypersurfaces with parallel structure Jacobi operator $R_{\xi}$ (cf.[16], [17]). In this paper we investigate real hypersurfaces in a nonflat complex space form using some conditions of the structure Jacobi operator $R_{\xi}$ which are weaker than ${\nabla}R_{\xi}$ = 0. Under further condition $S\phi={\phi}S$ for the Ricci tensor S we characterize Hopf hypersurfaces in a complex space form.

• 대한수학회보
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• 제44권1호
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• pp.195-202
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• 2007

We prove that a real hypersurface M in a complex space form Mn(c), $c{\neq}0$, whose Ricci operator and structure tensor commute each other on the holomorphic distribution and the Ricci operator is ${\eta}-parallel$, is a Hopf hypersurface. We also give a characterization of this hypersurface.