• Proceedings of the KIEE Conference
• /
• 1997.07c
• /
• pp.1118-1120
• /
• 1997

This paper presents a simple method for evaluating of voltage stability using the line flow equation. Line flow equations ($P_{ij}$, $Q_{ij}$) are comprised of state variable, $V_i$, ${\delta}_i$, $V_j$ and ${\delta}_j$, and line parameter, r and x. Using the feature of polar coordinate, these becomes one equation with two variables, $V_i$ and $V_j$. Moreover, if bus j is slack or generater bus, which is specified voltage magnitude, it becomes one equation with one variable $V_i$, that is, may be formulated with the second-order equation for $V_i^2$. Therefore, multiple load flow solutions may be obtained with simple computation, and the formulated equation used for approximately evaluating of voltage stability limit considering line flow sensitivity. The proposed method was validated to 2-bus and IEEE 6-bus system.

• Nuclear Engineering and Technology
• /
• v.43 no.2
• /
• pp.133-140
• /
• 2011

In this paper, a deformation measurement technology for nuclear fuel rods is proposed. The deformation measurement system includes a high-definition CMOS image sensor, a lens, a semiconductor laser line beam marker, and optical and mechanical accessories. The basic idea of the proposed deformation measurement system is to illuminate the outer surface of a fuel rod with a collimated laser line beam at an angle of 45 degrees or higher. For this method, it is assumed that a nuclear fuel rod and the optical axis of the image sensor for observing the rod are vertically composed. The relative motion of the fuel rod in the horizontal direction causes the illuminated laser line beam to move vertically along the surface of the fuel rod. The resulting change of the laser line beam position on the surface of the fuel rod is imaged as a parabolic beam in the high-definition CMOS image sensor. An ellipse model is then extracted from the parabolic beam pattern. The center coordinates of the ellipse model are taken as the feature of the deformed fuel rod. The vertical offset of the feature point of the nuclear fuel rod is derived based on the displacement of the offset in the horizontal direction. Based on the experimental results for a nuclear fuel rod sample with a formation of surface crud, an inspection resolution of 50 ${\mu}m$ is achieved using the proposed method. In terms of the degree of precision, this inspection resolution is an improvement of more than 300% from a 150 ${\mu}m$ resolution, which is the conventional measurement criteria required for the deformation of neutron irradiated fuel rods.

• Journal of KIISE:Software and Applications
• /
• v.36 no.6
• /
• pp.431-442
• /
• 2009

The Software Product Line (SPL) engineering is one of the most promising software development paradigms. With Feature-Oriented Reuse Method (FORM), reusable and flexible components can be built to aid the delivery of various software products such as mobile phone and digital TV applications based on commonalities and variabilities identified during Feature modeling. Model Driven Architecture (MDA) is also an emerging technology which supports developing software products to work on different platforms with platform independent models (PIM). Combining advantages of these two approaches is helpful to build a group of software products which share common Features while working on various platforms. As first step to combine FORM with MDA, we extend UML2.0 with profiles by which FORM architectures and parameterized Statecharts can be modeled. Secondly, we provide rules to examine whether Features are allocated at positions of elements of Statecharts consistently between a Feature model and a parameterized Statechart. Some rules are designed to check the consistency between FORM architectures and parameterized Statecharts. A case study on an elevator control system is provided to demonstrate the feasibility of our modeling approach and consistency checking rules.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.7
• /
• pp.337-352
• /
• 2017

Clone-and-own reuse is an approach to creating new software variants by copying and modifying existing software products. A family of legacy software products developed by clone-and-own reuse often requires high maintenance cost and tends to be error-prone due to patch-ups without refactoring and structural degradation. To overcome these problems, many organizations that have used clone-and-own reuse now want to migrate their legacy products to software product line (SPL) for more systematic reuse and management of software asset. However, with most of existing methods, variation points are embedded directly into design and code rather than modeled and managed separately; variation points are not created ("engineered") systematically based on a variability model. This approach causes the following problems: it is difficult to understand the relationships between variation points, thus it is hard to maintain such code and the asset tends to become error-prone as it evolves. Also, when SPL evolves, design/code assets tend to be modified directly in an ad-hoc manner rather than engineered systematically with appropriate refactoring. To address these problems, we propose a feature-oriented method for extracting a SPL asset from a family of legacy applications. With the approach, we identify and model variation points and their relationships in a feature model separate from implementation, and then extract and manage a SPL asset from legacy applications based on the feature model. We have applied the method to a family of legacy Notepad++ products and demonstrated the feasibility of the method.

• Journal of Korea Multimedia Society
• /
• v.13 no.8
• /
• pp.1115-1127
• /
• 2010

In order to increase the productivity in manufacturing TFT-LCD(thin film transistor-liquid crystal display), it is essential to classify defects that occur during the production and make an appropriate decision on whether the product with defects is scrapped or not. The decision mainly depends on classifying the defects accurately. In this paper, we present an effective classification method for film defects acquired in the panel production line by analyzing the intensity distribution and shape feature of the defects. We first generate a binary image for each defect by separating defect regions from background (non-defect) regions. Then, we extract various features from the defect regions such as the linearity of the defect, the intensity distribution, and the shape characteristics considering intensity, and construct a referential image database that stores those feature values. Finally, we determine the type of a defect by matching a defect image with a referential image in the database through the matching cost function between the two images. To verify the effectiveness of our method, we conducted a classification experiment using defect images acquired from real TFT-LCD production lines. Experimental results show that our method has achieved highly effective classification enough to be used in the production line.

• Journal of Korea Multimedia Society
• /
• v.10 no.7
• /
• pp.923-933
• /
• 2007

In this paper, we present a method for performance enhancement of the marker detection system by using SVM(Support Vector Machine) and LDA(Linear Discriminant Analysis). It converts the input image to a binary image and extracts contours of objects in the binary image. After that, it approximates the contours to a list of line segments. It finds quadrangle by using geometrical features which are extracted from the approximated line segments. It normalizes the shape of extracted quadrangle into exact squares by using the warping technique and scale transformation. It extracts feature vectors from the square image by using principal component analysis. It then checks if the square image is a marker image or a non-marker image by using a SVM classifier. After that, it computes feature vectors by using LDA for the extracted marker images. And it calculates the distance between feature vector of input marker image and those of standard markers. Finally, it recognizes the marker by using minimum distance method. Experimental results show that the proposed method achieves enhancement of recognition rate with smaller feature vectors by using LDA and it can decrease false detection errors by using SVM.

• Journal of Digital Contents Society
• /
• v.16 no.2
• /
• pp.235-244
• /
• 2015

This study proposes a leaf modeling method that uses feature-based warping for efficient generation of various digital leaves. The proposed method uses warping method, one of image processing application techniques that can control various shapes of leaves in an easy, intuitive way, and generate natural patterns of veins efficiently. First, information on approximated contour is detected from a leaf blade image to identify the shape of a blade. Based on this, control line is automatically calculated to be used for feature-based warping. Then, control line-based warping is conducted to modify forms of leaf blade images in an intuitive way, automatically generating leaves of various shapes. And natural vein patterns are generated by applying a contour-based venation growth algorithm from contour information of the modified leaf blade images. This study performs experiments to verify whether various shape of leaves that comprise plants can be efficiently generated using a sample binary image of a blade. Also, we demonstrate that express the natural growth of leaves by applying warping to the growth of the leaf blade.

• Journal of Korea Multimedia Society
• /
• v.12 no.1
• /
• pp.50-57
• /
• 2009

This paper proposes a extraction of feature lines on a polygonal model using local implicit surface fitting technique. To extract feature lines on a polygonal model, the previous technique addressed to compute the curvature and their derivatives at mesh vertices via global implicit surface fitting. It needs a user-specified precision parameter for finding an accurate projection of the mesh vertices onto an approximating implicit surface and requires high-time consumption. But we use a local implicit surface fitting technique to estimate the local differential information near a vertex by means of an approximating surface. Feature vertices are easily detected as zero-crossings, and can then be connected along the direction of principal curvature. Our method, demonstrated on several large polygonal models, produces a good fit which leads to improved visualization.

• Journal of Electrical Engineering and Technology
• /
• v.3 no.2
• /
• pp.167-176
• /
• 2008

Vulnerability assessment of power systems is important so as to determine their ability to continue to provide service in case of any unforeseen catastrophic contingency such as power system component failures, communication system failures, human operator error, and natural calamity. An approach towards the development of on-line power system vulnerability assessment is by means of using an artificial neural network(ANN), which is being used successfully in many areas of power systems because of its ability to handle the fusion of multiple sources of data and information. An important consideration when applying ANN in power system vulnerability assessment is the proper selection and dimension reduction of training features. This paper aims to investigate the effect of using various feature extraction methods on the performance of ANN as well as to evaluate and compare the efficiency of the proposed feature extraction method named as neural network weight extraction. For assessing vulnerability of power systems, a vulnerability index based on power system loss is used and considered as the ANN output. To illustrate the effectiveness of ANN considering various feature extraction methods for vulnerability assessment on a large sized power system, it is verified on the IEEE 300-bus test system.

• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10b
• /
• pp.509-511
• /
• 1999

본 논문에서는 일반적으로 영역 기반형 분할방법보다 우수한 분할결과와 계산의 효율성을 가지는 경계선 기반형 방법의 하나인 scan line approximation 방법을 응용함으로써 경계선의 기하학적 해석이 가능하도록 하는 경계선 강도(edge intensity) 정보를 제공한다. 따라서 면 특성과 국부적인 면 특성인 면 법선과 면 곡률정보 없이 잡음에 강건하고 계산의 효율성에서 우수한 거리영상분할 방법을 제안한다. 합성 거리영상을 대상으로 scan line approximation 방법을 응용하여 얻어진 경계선을 경계선 그룹화의 영역 레이블링을 거쳐서 면 특징을 추출하였다.