• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 추계학술대회 논문집 전력기술부문
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• pp.241-243
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• 2002

Recently, great efforts are concentrated on the autonomous, adaptive protection schemes with advanced artificial intelligence and digital technology. It is highly required for a next generation protective system not only to detect and to clear a fault, but also to fit itself to the changing environment. In this paper it is suggested an evaluation method for the protection ability of a protective system in a distributed system. The suggested method is of bottom-up scheme, in other words, protection ability is estimated from the lowest level of parameters in each protective devices to the highest level of the whole protective system. This feature makes it possible to evaluate the protection ability either for the protective device(or a system), or for a protected system. And, in addition, it is enabled that the protectability concept can be applied in the design stage of a protective system for a distribution network. The proposed method is applied to a simple distributed network to show its effectiveness.

• 대한의용생체공학회:의공학회지
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• 제27권3호
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• pp.110-116
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• 2006

Finite element method (FEM) provides several advantages over other numerical methods such as boundary element method, since it allows truly volumetric analysis and incorporation of realistic electrical conductivity values. Finite element mesh generation is the first requirement in such in FEM to represent the volumetric domain of interest with numerous finite elements accurately. However, conventional mesh generators and approaches offered by commercial packages do not generate meshes that are content-adaptive to the contents of given images. In this paper, we present software that has been implemented to generate content-adaptive finite element meshes (cMESHes) based on the contents of MR images. The software offers various computational tools for cMESH generation from multi-slice MR images. The software named as the Content-adaptive FE Mesh Generation Toolbox runs under the commercially available technical computation software called Matlab. The major routines in the toolbox include anisotropic filtering of MR images, feature map generation, content-adaptive node generation, Delaunay tessellation, and MRI segmentation for the head conductivity modeling. The presented tools should be useful to researchers who wish to generate efficient mesh models from a set of MR images. The toolbox is available upon request made to the Functional and Metabolic Imaging Center or Bio-imaging Laboratory at Kyung Hee University in Korea.

• Nuclear Engineering and Technology
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• 제33권5호
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• pp.457-467
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• 2001

It is well known that the performance of a fuzzy neural network strongly depends on the input features selected for its training. In its applications to sensor signal estimation, there are a large number of input variables related with an output As the number of input variables increases, the training time of fuzzy neural networks required increases exponentially. Thus, it is essential to reduce the number of inputs to a fuzzy neural network and to select the optimum number of mutually independent inputs that are able to clearly define the input-output mapping. In this work, principal component analysis (PCA), genetic algorithms (CA) and probability theory are combined to select new important input features. A proposed feature selection method is applied to the signal estimation of the steam generator water level, the hot-leg flowrate, the pressurizer water level and the pressurizer pressure sensors in pressurized water reactors and compared with other input feature selection methods.

• 반도체디스플레이기술학회지
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• 제19권2호
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• pp.11-15
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• 2020

In a typical initial setup of a PCB component inspection system, operators should manually input various information such as category, position, and inspection area for each component to be inspected, thus causing much inconvenience and longer setup time. Although there are many deep learning based object detectors, RetinaNet is regarded as one of best object detectors currently available. In this paper, a method using an extended RetinaNet is proposed that automatically detects its component category and position for each component mounted on PCBs from a high-resolution color input image. We extended the basic RetinaNet feature pyramid network by adding a feature pyramid layer having higher spatial resolution to the basic feature pyramid. It was demonstrated by experiments that the extended RetinaNet can detect successfully very small components that could be missed by the basic RetinaNet. Using the proposed method could enable automatic generation of inspection areas, thus considerably reducing the setup time of PCB component inspection systems.

• 방송공학회논문지
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• 제20권5호
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• pp.728-737
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• 2015

스티칭 기법은 여러 영상에서 추출한 특징점의 디스크립터를 생성하고, 특징점들간의 정합 과정을 통해 하나의 영상으로 만드는 것이다. 각각의 특징점은 128 차원의 정보를 가지고 있고, 특징점의 개수가 증가 할수록 데이터 처리 시간이 증가하게 된다. 본 논문에서는 비디오 영상을 입력 했을 때 고속 파노라마 생성을 위한 특징점 추출 및 정합 기법을 제안한다. 빠른 속도로 특징점 추출을 위해서 FAST(Features from Accelerated Segment Test) 기법을 사용한다. 특징점 정합과정은 기존의 방법과는 다른 새로운 방법을 제안한다. Mean shift를 통해 특징점이 포함된 영역을 추적하여 벡터(vector)를 구하고 이 벡터를 사용하여 추출한 특징점들을 정합하는데 사용한다. 마지막으로 이상점(outlier)을 제거하기 위해 RANSAC(RANdom Sample Consensus) 기법을 사용한다. 입력된 두 영상의 호모그래피(homography) 변환 행렬을 구하여 하나의 파노라마 영상을 생성한다. 실험을 통해 제안하는 기법이 기존의 기법보다 속도가 향상되는 것을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 A
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• pp.149-151
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• 2005

A new approach considering CO2 air pollution constraints in the long-term generation mix is proposed under uncertain circumstances. A characteristic feature of the presented approach in this paper is what effects give the air pollution constraints in long term best generation mix. Best generation mix problem is formulated by linear programming with fuel and construction cost minimization with load growth, reliability (reserve margin rate) and air pollutionconstraints. The proposed method accommodates the operation of pumped-storage generator. It was assumed in this study that the construction planning of the hydro power plants is given separately from the other generation plans. The effectiveness of the proposed approach is demonstrated by applying to the best generation mix problem of KEPCO-system, which contains nuclear, coal, LNG, oil and pumped-storage hydro plant multi-years.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 학술발표 논문집
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• pp.11-14
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• 1995

A Fuzzy Classifier which deals with very confusing objects is proposed. Naturally this classifier heavily relies on the nulti-feature decision-making procedure. For a simple example, this classifier is applied to the recognition of confusing handwritten numerals 4,6 and 9 The characteristic variables used in this paper are the existence of a loop and the relative location of the starting or ending points(SEP). Thus each sample of handwritten numerals 4, 6 and 9 is classified in one of the 6 groups which are divided according to the sample structure. Each group has its own classifying rules. Also the method of rule-generation using genetic algorithms in each group is proposed.

• 대한산업공학회지
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• 제17권2호
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• pp.1-16
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• 1991

This paper deals with some critical activities of CAPP system such as generation of part description database, part feature recognition, process and operation selection, and sequencing method for turning operation of symmetric rotational parts. The part description database is generated by data conversion module from CAD data, and the part feature is recognized by using both pattern primitives and feature recognition rules. Machining processes and operations are selected based on machining surface features and its sequence is determined by rules acquired from process planning expert. AutoCAD is employed as CAD system and computer program is developed by using Turbo-C on IBM PC/AT compatible system.

• 한국정밀공학회지
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• 제10권4호
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• pp.236-247
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• 1993

An davanced method for the automatic generation of parametric models in computer- aided design systems is required for most of two-dimensional model which is represented as a set of geometric elements, and constraining scheme formulas. The development system uses geometric constraints and support of topology parameters from feature recognition and grouping the design entities into optimal ones from pre-designed drawings. The aim of this paper is to present guidelines for the application and development of parametric design modules for the standard parts in mechanical system, the basic constitutional part of mold base, and other 2D features.

• Journal of Multimedia Information System
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• 제6권2호
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• pp.91-98
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• 2019

Many researchers have attempted to recognize three-dimensional faces using feature points extracted from two-dimensional facial photographs. However, due to the limit of flat photographs, it is very difficult to recognize faces rotated more than 15 degrees from original feature points extracted from the photographs. As such, it is difficult to create an algorithm to recognize faces in multiple angles. In this paper, it is proposed a new algorithm to recognize three-dimensional face recognition based on feature points extracted from a flat photograph. This method divides into six feature point vector zones on the face. Then, the vector value is compressed and expanded according to the rotation angle of the face to recognize the feature points of the face in a three-dimensional form. For this purpose, the average of the compressibility and the expansion rate of the face data of 100 persons by angle and face zone were obtained, and the face angle was estimated by calculating the distance between the middle of the forehead and the tail of the eye. As a result, very improved recognition performance was obtained at 30 degrees of rotated face angle.