• Korean Journal of Computational Design and Engineering
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• v.6 no.2
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• pp.89-100
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• 2001

Swept volume is the sweeping region of moving objects. It is used in various applications such as interference detection in assembly design, visualization of manipulator motions in robotics, simulation of the volume removal by a cutter in NC machining. The shape of swept volume is defined by the envelope, which is determined by the boundary of moving objects and its direction of motion. In order to implement the generation of swept volume, researchers have taken much effort to develop the techniques how to generate the envelope. However, their results are confined to envelope generated only in simple shape objects, such as polyhedra or quadric surfaces. This study provided the envelope generation algorithm of NURBS objects. Characteristic points were obtained by applying the geometric conditions of envelope to NURBS equations, and then characteristic curves were created by means of interpolating those points. Silhouette edges were determined in the following procedures. First, two adjacent surfaces which have the same edge were found from B-Rep data. Then, by taking the scalar product of velocity vector of a point on that edge with each normal vector on two surfaces, silhouette edges were discriminated. Finally, envelope was generated along moving direction in the form of ruled surfaces by using both the partial information between initial and final position of objects affecting envelope along with characteristic curves and silhouette edge. Since this developed algorithm can be applied not only to NURBS objects but also to their Boolean objects, it can be used effectively in various applications.

• Korean Journal of Computational Design and Engineering
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• v.6 no.2
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• pp.101-110
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• 2001

The maximum intersection of spherical convex polygons are to find spherical regions owned by the maximum number of the polygons, which is applicable for determining the feasibility in manufacturing problems such mould design and numerical controlled machining. In this paper, an efficient method for partitioning a sphere with the polygons into faces is presented for the maximum intersection. The maximum intersection is determined by examining the ownerships of partitioned faces, which represent how many polygons contain the faces. We take the approach of edge-based partition, in which, rather than the ownerships of faces, those of their edges are manipulated as the sphere is partitioned incrementally by each of the polygons. Finally, gathering the split edges with the maximum number of ownerships as the form of discrete data, we approximately obtain the centroids of all solution faces without constructing their boundaries. Our approach is analyzed to have an efficient time complexity Ο(nv), where n and v, respectively, are the numbers of polygons and all vertices. Futhermore, it is practical from the view of implementation since it can compute numerical values robustly and deal with all degenerate cases.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.3
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• pp.163-171
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• 2016

Lane detection is a widely researched topic. Although simple road detection is easily achieved by previous methods, lane detection becomes very difficult in several complex cases involving noisy edges. To address this, we use a Convolution neural network (CNN) for image enhancement. CNN is a deep learning method that has been very successfully applied in object detection and recognition. In this paper, we introduce a robust lane detection method based on a CNN combined with random sample consensus (RANSAC) algorithm. Initially, we calculate edges in an image using a hat shaped kernel, then we detect lanes using the CNN combined with the RANSAC. In the training process of the CNN, input data consists of edge images and target data is images that have real white color lanes on an otherwise black background. The CNN structure consists of 8 layers with 3 convolutional layers, 2 subsampling layers and multi-layer perceptron (MLP) of 3 fully-connected layers. Convolutional and subsampling layers are hierarchically arranged to form a deep structure. Our proposed lane detection algorithm successfully eliminates noise lines and was found to perform better than other formal line detection algorithms such as RANSAC

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.79-84
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• 1992

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the optimal collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy and a traveling salesman problem strategy (TSP). The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Hopfield Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is used to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.599-605
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• 2018

Fault diagnosis depends critically on the selection of sensors monitoring crucial process variables. Boolean network (BN) is composed of nodes and directed edges, where the node state is quantized to the Boolean values of True or False and is determined by the logical functions of the network parameters and the states of other nodes with edges directed to this node. Since BN can describe the fault propagation in a sensor network, it can be applied to propose sensor selection strategy for fault diagnosis. In this article, a sufficient condition for parameter identifiability of BN is first proposed, based on which the sufficient condition for fault identifiability of a sensor network is given. Then, the fault identifiability condition induces a sensor selection strategy for sensor selection. Finally, the theoretical result is applied to the fault diagnosis-oriented sensor selection for a nuclear heating reactor plant, and both the numerical computation and simulation results verify the feasibility of the newly built BN-based sensor selection strategy.

• Journal of radiological science and technology
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• v.8 no.2
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• pp.71-72
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• 1985

This study was performed on the dose distribution of various field size and the effect of penumbra shield in the telecobalt unit. The results obtained are as follows. 1. Errors of the light and ${\gamma}-ray$ field size was below the regulation as 0.52 percentage. 2. The coefficient of field area was increased with the larger field area, and this coefficient was showed the more difference in larger SSD. 3. The rectangular field areas, which were described by level of the same percentage depth does, were decreased with the more elongation factor. At the same elongation factor, the compensating factor was decreased with the larger field size. 4. The lead block or extension collimator was able to shield r-ray exposure of outside field size from 50 to 80 percentage. 5. On the matching adjacent fields, while the gap between beam edges are contacted, that overlapped beam edges indicated up to 140 percentage, and while the gap was 1 cm, it could be reduced to 90 Percentage. The lead-libocking on the overlapped area was more effective to lower dose, as 80 percentage in this case. 6. Percentage depth dose of various trimming field sizes were increased linearlly according to area 1 perimeter size, but the center split field size did not maintain linearlly.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.422-433
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• 2001

In this paper, we propose a flew edge detection method based on water flow model, in which gradient image surface is considered as a 3-dimensional (3-D) geographical feature. The edges of the objects in the background can be detected by the large gradient magnitude areas and to make the edges immersed it is required to invert the gradient image. The proposed edge detector uses a water flow model based enhancement and locally adaptive thresholding technique applied to the inverted gradient image resulting in better noise performance. Computer simulations with a few synthetic and real images show that the Proposed method can extract edge contour effectively.

• Structural Engineering and Mechanics
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• v.75 no.2
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• pp.247-269
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• 2020

A finite strip formulation was developed for buckling and free vibration analysis of laminated composite plates based on different shear deformation plate theories. The different shear deformation theories such as Zigzag higher order, Refined Plate Theory (RPT) and other higher order plate theories by variation of transverse shear strains through plate thickness in the parabolic form, sine and exponential were adopted here. The two loaded opposite edges of the plate were assumed to be simply supported and remaining edges were assumed to have arbitrary boundary conditions. The polynomial shape functions are applied to assess the in-plane and out-of-plane deflection and rotation of the normal cross-section of plates in the transverse direction. The finite strip procedure based on the virtual work principle was applied to derive the stiffness, geometric and mass matrices. Numerical results were obtained based on various shear deformation plate theories to verify the proposed formulation. The effects of length to thickness ratios, modulus ratios, boundary conditions, the number of layers and fiber orientation of cross-ply and angle-ply laminates were determined. The additional results on the same effects in the interaction of biaxial in-plane loadings on the critical buckling load were determined as well.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.179-184
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• 2004

This paper presents an image segmentation algorithm to obtain the 3D body shape data that the grid pattern and the body contour lute in the background image are extracted using the new proposed hybrid method. The body contour line is extracted based on maximum biased anisotropic recognition(MaxBAR) algorithm which recognizes the most strong and robust edges in the image since the normal derivative at the edges is large, while the tangential derivatives can be small. The grid patterns within body contour lines are extracted by grid pattern detection (GPD). The body contour lilies and the grid patterns are combined. The consecutive run test based on heuristic method is used to link the disconnected line and reduce noise line. This proposed segmentation method is more effective than the conventional method which uses a gradient and a laplacian operator, verified with application two conventional method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.338-340
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• 2012

In images, the edge is an important element to analyze characteristics of the image and has been used selectively at several applications. Even now, many researches to detect and take advantage of theses edges are underway and in initially to detect edges, methods using the relation of adjacent pixels are proposed. Characteristic of these methods is that the processing speed of the algorithms is fast, but the specific weighted values are applied to all the pixels regardless of the images equally. In recent years, the research of the edge detection algorithm to adapt according to the image has been actively underway, in order to complement the drawbacks of the existing methods. Therefore, in order to detect the edge excellent characteristics In this paper, we proposed algorithm using adaptive mask.