• 한국CDE학회논문집
• /
• 제11권6호
• /
• pp.455-463
• /
• 2006

Hidden line removal(HLR) algorithms can be devised either in the image space or in the object space. This paper describes a hidden line removal algorithm in the object space specifically for the CAD viewer data. The approach is based on the Appel's 'Quantitative Invisibility' algorithm and fundamental concept of 'back face culling'. Input data considered in this algorithm can be distinguished from those considered for HLR algorithm in general. The original QI algorithm can be applied for the polyhedron models. During preprocessing step of our proposed algorithm, the self intersecting surfaces in the view direction are divided along the silhouette curves so that the QI algorithm can be applied. By this way the algorithm can be used for any triangulated freeform surfaces. A major advantage of this algorithm is the applicability to general CAD models and surface-based visualization data.

• 한국CDE학회논문집
• /
• 제2권1호
• /
• pp.28-34
• /
• 1997

A swept volume is a useful tool for solving various types of interference problems. Previous works have concentrated on sweeping an object along an arbitrary path, that results in complex algorithms. This paper concerns the volume swept by translating an object along a linear path. After analyzing the structure of the swept volume, we present an incremental algorithm for constructing a swept volume. Our algorithm takes O(n/sup 2/ *.alpha.(n)+T/sub c/) time where n is the number of vertices in the original object and T/sub c/ is time for handling face cycles.

• 대한산업공학회지
• /
• 제20권3호
• /
• pp.3-14
• /
• 1994

In this study, two reliability computational algorithms which respectively utilize a factoring method are proposed for a system represented by reliability block diagram. First, vertex factoring algorithm is proposed. In this algorithm, a reliability block diagram is considered as a network graph with vertex reliabilities. Second algorithm is mainly concerned with conversion of a reliabilities block diagram into a network graph with edge reliabilities. In this algorithm, the independence of edges is preserved by eliminating replicated edges, and in computing the reliability of a converted network graph, existing edge factoring algorithm is applied. The efficiency of two algorithms are compared for example systems with respect to computing times. The results shows that the second algorithm is shown to be more efficient than the first algorithm.

• 한국멀티미디어학회논문지
• /
• 제16권11호
• /
• pp.1338-1347
• /
• 2013

Face recognition is a science of automatically identifying individuals based their unique facial features. In order to avoid overfitting and reduce the computational reduce the computational burden, a new face recognition algorithm using PCA-fisher linear discriminant (PCA-FLD) and fuzzy radial basis function neural network (RBFNN) is proposed in this paper. First, face features are extracted by the principal component analysis (PCA) method. Then, the extracted features are further processed by the Fisher's linear discriminant technique to acquire lower-dimensional discriminant patterns, the processed features will be considered as the input of the fuzzy RBFNN. As a widely applied algorithm in fuzzy RBF neural network, BP learning algorithm has the low rate of convergence, therefore, an improved learning algorithm based on Levenberg-Marquart (L-M) for fuzzy RBF neural network is introduced in this paper, which combined the Gradient Descent algorithm with the Gauss-Newton algorithm. Experimental results on the ORL face database demonstrate that the proposed algorithm has satisfactory performance and high recognition rate.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회 2006년도 추계학술대회
• /
• pp.417-420
• /
• 2006

This paper suggests that resource allocation algorithm in multiuser orthogonal frequncy divisioin multiplexing (OFDM). The proposed algorithm considers throughput maximization with power constraint and quality of service (QoS) constraint. This problem has a optimal solution with using well known water-filling algorithm but the algorithm requires high computational complexity. Therefore the problem needs a sub-optimal algorithm for decreasing computational complexity. We propose a sub-optimal joint subcarrier and power allocation algorithm for multiuser OFDM system and compare with previous resource allocation algorithm.

• 한국CDE학회논문집
• /
• 제4권3호
• /
• pp.269-283
• /
• 1999

Surface/surface intersection is a common and important problem in geometric modeling and CAD/CAM. Several methods have been used to approach this problem. All possible intersection curves can be obtained by using the subdivision algorithm, while it requires a great deal of memory and is somewhat inefficient. The tracing algorithm is much faster than the subdivision algorithm, and can find points on the intersection curve sequentially. But, the tracing algorithm has some problems in the intersection curves on surface boundaries. In this paper, an Improved tracing algorithm that includes some ideas such as a new trace-terminating condition for the intersection curves on surface boundaries, detecting closed intersections and extension for composite surfaces is suggested. This algorithm consists of three step: generating state points for curve tracing, tracing intersection curves and sorting pieces of the intersection curves. The results of this algorithm and comparisons to the 'DESIGNBASE' and 'ACIS' system are presented.

• Journal of Computational Design and Engineering
• /
• 제3권1호
• /
• pp.24-36
• /
• 2016

During the past decade, solving complex optimization problems with metaheuristic algorithms has received considerable attention among practitioners and researchers. Hence, many metaheuristic algorithms have been developed over the last years. Many of these algorithms are inspired by various phenomena of nature. In this paper, a new population based algorithm, the Lion Optimization Algorithm (LOA), is introduced. Special lifestyle of lions and their cooperation characteristics has been the basic motivation for development of this optimization algorithm. Some benchmark problems are selected from the literature, and the solution of the proposed algorithm has been compared with those of some well-known and newest meta-heuristics for these problems. The obtained results confirm the high performance of the proposed algorithm in comparison to the other algorithms used in this paper.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2002년도 ITC-CSCC -1
• /
• pp.188-191
• /
• 2002

To reduce the bit-rate of video sequences by removing temporal redundancy, motion estimation techniques have been developed. However, the high computational complexity of the problem makes such techniques very difficult to be applied to high-resolution applications in a real time environment. For this reason, low computational complexity motion estimation algorithms are viable solutions. If a priori knowledge about the motion of the current block is available before the motion estimation, a better starting point for the search of n optimal motion vector on be selected and also the computational complexity will be reduced. In this paper, we present an adaptive block matching algorithm based on temporal correlations of consecutive image frames that defines the search pattern and the location of initial starting point adaptively to reduce computational complexity. Experiments show that, comparing with DS(Diamond Search) algorithm, the proposed algorithm is about 0.1∼0.5(㏈) better than DS in terms of PSNR and improves as much as 50% in terms of the average number of search points per motion estimation.

• 대한임베디드공학회논문지
• /
• 제12권4호
• /
• pp.231-238
• /
• 2017

Detecting small infrared targets from the low-SCR images at a long distance is very hard. The previous Local Contrast Method (LCM) algorithm based on the human visual system shows a superior performance of detecting small targets by a background suppression technique through local contrast measure. However, its slow processing speed due to the heavy multi-scale processing overhead is not suitable to a variety of real-time applications. This paper presents a lightweight real-time small target detection algorithm, called by the Improved Selective Local Contrast Method (ISLCM), to reduce the scale-invariant computational overhead. The proposed ISLCM applies the improved local contrast measure to the predicted selective region so that it may have a comparable detection performance as the previous LCM while guaranteeing low scale-invariant computational load by exploiting both adaptive scale estimation and small target feature feasibility. Experimental results show that the proposed algorithm can reduce its computational overhead considerably while maintaining its detection performance compared with the previous LCM.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제14권4호
• /
• pp.256-267
• /
• 2014

An automatic switch among ensembles of clustering algorithms is proposed as a part of the bibliographic big data retrieval system by utilizing a fuzzy inference engine as a decision support tool to select the fastest performing clustering algorithm between fuzzy C-means (FCM) clustering, Newman-Girvan clustering, and the combination of both. It aims to realize the best clustering performance with the reduction of computational complexity from O($n^3$) to O(n). The automatic switch is developed by using fuzzy logic controller written in Java and accepts 3 inputs from each clustering result, i.e., number of clusters, number of vertices, and time taken to complete the clustering process. The experimental results on PC (Intel Core i5-3210M at 2.50 GHz) demonstrates that the combination of both clustering algorithms is selected as the best performing algorithm in 20 out of 27 cases with the highest percentage of 83.99%, completed in 161 seconds. The self-adapted FCM is selected as the best performing algorithm in 4 cases and the Newman-Girvan is selected in 3 cases.The automatic switch is to be incorporated into the bibliographic big data retrieval system that focuses on visualization of fuzzy relationship using hybrid approach combining FCM and Newman-Girvan algorithm, and is planning to be released to the public through the Internet.