• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.1907-1910
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• 2003

This paper describes a method of stereo image composition for mixed reality without camera calibration or complicate tracking algorithm. The proposed system tracks the panel which has blob makers, and composes virtual objects naturally using the method of texture mapping which is often used in geological computer graphics mapping when we do mapping 2D computer graphic data or man-made 2D images. The proposed algorithm makes it possible for us to compose virtual data even in the case that the panel is bent. For composing 3D object, the system uses depth information obtained from stereo image so that we do not need cumbersome procedure of camera calibration.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2006년도 춘계학술대회
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• pp.203-213
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• 2006

대량의 정보를 취급하는 현대사회에서는 획득하는 정보를 모두 처리할 수 없어 이용자의 요구에 맞는 정보를 얻기 위해 정보 필터링 시스템을 사용한다. 그러나 정보 필터링 시스템이 이용자의 의도와 다르게 정보를 분류하거나 이용자의 다양한 요구를 반영하지 못할 때는 정보 필터링을 사용하지 않은 경우 보다 못할 수 있다. 본 연구에서는 정보 필터링의 정확도를 향상시키기 위해 인간의 뇌에서의 정보처리 과정을 시뮬레이션하는 인지적 매핑의 정보 필터링 시스템을 제안하고자 한다. 본 연구에서 제안하는 시스템은 특정 단어 또는 패턴만을 이용하여 필터링하는 기존 시스템과는 달리 단어의 존재, 단어와 단어의 연결이 창출하는 의미와 단어의 가중치를 종합하여 정보를 필터링하는 점에서 의의가 있다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2010년 춘계학술발표회 논문집
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• pp.69-71
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• 2010

In this paper, we focus on the accuracy estimation of laser scanning mobile mapping system using Lynx Mobile Mapper. For this, we surveyed checkpoints(181 points) in study areas. A method to estimate the accuracy of laser scanning mobile mapping system based on the measurement range, interval of control points and gps signal environments. As a result, to ensure reliable measurement results, we must be made a plan considering Measure range(60m or under) and operation. The estimation results showed the need for improving accuracy using control points about 150m interval according to environment error source.

• 한국산업융합학회 논문집
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• 제24권1호
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• pp.69-77
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• 2021

The widely used low-cost design methodology for IoT devices is very popular. In such a networked device, memory is composed of flash memory, SRAM, DRAM, etc., and because it processes a large amount of data, memory design is an important factor for system performance. Therefore, each device selects optimized design factors such as function, performance and cost according to market demand. The design of a memory architecture available for low-cost IoT devices is very limited with the configuration of SRAM, flash memory, and DRAM. In order to process as much data as possible in the same space, an architecture that supports parallel processing units is usually provided. Such parallel architecture is a design method that provides high performance at low cost. However, it needs precise software techniques for instruction and data mapping on the parallel architecture. This paper proposes an instruction/data mapping method to support optimized parallel processing performance. The proposed method optimizes system performance by actively using hardware and software parallelism.

• 대한수학회논문집
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• 제36권1호
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• pp.103-119
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• 2021

In this article, we study a system of generalized set-valued parametric ordered variational inclusion problems with operator ⊕ in ordered Banach spaces. We introduce the concept of the resolvent operator associated with (α, λ)-ANODSM set-valued mapping and establish the existence theorem of solution for the system of generalized set-valued parametric ordered variational inclusion problems in ordered Banach spaces. In order to prove the existence of solution, we suggest an iterative algorithm and discuss the convergence analysis under some suitable mild conditions.

• Nonlinear Functional Analysis and Applications
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• 제26권4호
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• pp.749-780
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• 2021

In this paper, we give the notion of M(., .)-𝜂-proximal mapping for a nonconvex, proper, lower semicontinuous and subdifferentiable functional on Banach space and prove its existence and Lipschitz continuity. As an application, we introduce and investigate a new system of variational-like inclusions in Banach spaces. By means of M(., .)-𝜂-proximal mapping method, we give the existence of solution for the system of variational inclusions. Further, propose an iterative algorithm for finding the approximate solution of this class of variational inclusions. Furthermore, we discuss the convergence and stability analysis of the iterative algorithm. The results presented in this paper may be further expolited to solve some more important classes of problems in this direction.

• 대한수학회지
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• 제38권1호
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• pp.87-99
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• 2001

We prove that the germ of a CR mapping f between real analytic real hypersurfaces has a holomorphic extension and satisfies a complete system of finite order if the source is of finite type in the sense of Bloom-Graham and the target is k-nondegenerate under certain generic assumptions on f.

• East Asian mathematical journal
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• 제24권1호
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• pp.57-65
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• 2008

The approximate solvability of a generalized system for non-linear variational inequality in Hilbert spaces was studied, based on the convergence of projection methods. But little research was done in Banach space. The primary reason was that projection mapping lacked preferably property in Banach space. In this paper, we introduced the generalized projection methods. By using these methods, the results presented in this paper extended the main results of S. S. Chang [3] from Hilbert spaces to Banach space.

• 대한원격탐사학회지
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• 제31권2호
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• pp.171-182
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• 2015

본 연구는 실내 정밀 매핑과 정교한 영상 기반 서비스에 활용 가능한 실내의 입체 전방위 영상을 취득하는 시스템과 이에 대한 캘리브레이션 방법을 제안한다. 제안된 시스템은 회전식 스테레오 라인 카메라 방식으로 구성되며, 안정적인 입체시와 객체점의 정밀한 결정에 적합한 입체 전방위 영상을 제공한다. 또한, 제안된 시스템의 투영모델을 기반으로 캘리브레이션을 위한 수학적 모델을 도출한다. 이를 통해 캘리브레이션을 수행하여, 실내 공간에 대해 ${\pm}16cm$ 이내의 정확도로 객체점을 추정할 수 있었다. 제안된 시스템과 캘리브레이션 방법은 실내의 정밀한 3차원 모델링에 활용될 것이다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2488-2491
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• 2000

A Neural network is possible to nonlinear function mapping and parallel processing. Therefore It has been developing for a Diagnosis system of nuclear plower plant. In general Neural Networks is a static mapping but Dynamic Neural Network(DNN) is dynamic mapping. When a fault occur in system, a state of system is changed with transient state. Because of a previous state signal is considered as a information. DNN is better suited for diagnosis systems than static neural network. But a DNN has many weights, so a real time implementation of diagnosis system is in need of a rapid network architecture. This paper presents a algorithm for RCP monitoring Alarm diagnosis system using Self Dynamic Neural Network(SDNN). SDNN has considerably fewer weights than a general DNN. Since there is no interlink among the hidden layer. The effectiveness of Alarm diagnosis system using the proposed algorithm is demonstrated by applying to RCP monitoring in Nuclear power plant.