• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.802-809
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• 2005

A hybrid genetic algorithm is proposed for the problem of generating laser torch paths to cut a stock plate nested with free-formed parts each having a set of sub-parts. In the problem, the total unproductive travel distance of the torch is minimized. The problem is shown to be formulated as a special case of the standard travelling salesman problem. The hybrid genetic algorithm for solving the problem is hierarchically structured: First, it uses a genetic algorithm to find the cutting path f3r the parts and then, based on the obtained cutting path, sequence of sub-parts and their piercing locations are optimally determined by using a combined genetic and heuristic algorithms. This process is repeated until any progress in the total unproductive travel distance is not achieved. Computational results are provided to illustrate the validity of the proposed algorithm.

• The Pure and Applied Mathematics
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• v.19 no.1
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• pp.23-35
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• 2012

Given a set ${\Omega}$ and the notion of bipolar valued fuzzy sets, the concept of a bipolar ${\Omega}$-fuzzy sub-semigroup in semigroups is introduced, and related properties are investigated. Using bipolar ${\Omega}$-fuzzy sub-semigroups, bipolar fuzzy sub-semigroups are constructed. Conversely, bipolar ${\Omega}$-fuzzy sub-semigroups are established by using bipolar fuzzy sub-semigroups. A characterizations of a bipolar ${\Omega}$-fuzzy sub-semigroup is provided, and normal bipolar ${\Omega}$-fuzzy sub-semigroups are discussed. How the homomorphic images and inverse images of bipolar ${\Omega}$-fuzzy sub-semigroups become bipolar ${\Omega}$-fuzzy sub-semigroups are considered.

• ETRI Journal
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• v.14 no.4
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• pp.19-27
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• 1992

Since. as is well known, direct computation of the reliability for a large-scaled and complex net work generally requires exponential time, a variety of alternative methods to estimate the network reliability using simulation have been proposed. Monte Carlo sampling is the major approach to estimate the network reliability using simulation. In the paper, a dynamic Monte Carlo sampling method, called conditional minimal cut set (CMCS) algorithm, is suggested. The CMCS algorithm simulates a minimal cut set composed of arcs originated from the (conditional) source node until s-t connectedness is confirmed, then reduces the network on the basis of the states of simulated arcs. We develop the importance sampling estimator and the total hazard estimator and compare the performance of these simulation estimators. It is found that the CMCS algorithm is useful in reducing variance of network reliability estimator.

• Journal of Mechanical Science and Technology
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• v.17 no.9
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• pp.1287-1296
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• 2003

In this paper the dynamic analysis of the Macpherson strut motor-vehicle suspension system is presented. The equations of motion are formulated using a two-step transformation. Initially, the equations of motion are derived for a dynamically equivalent constrained system of particles that replaces the rigid bodies by applying Newton's second law The equations of motion are then transformed to a reduced set in terms of the relative joint variables. Use of both Cartesian and joint variables produces an efficient set of equations without loss of generality For open chains, this process automatically eliminates all of the non-working constraint forces and leads to an efficient solution and integration of the equations of motion. For closed loops, suitable joints should be cut and few cut-joints constraint equations should be included for each closed chain. The chosen suspension includes open and closed loops with quarter-car model. The results of the simulation indicate the simplicity and generality of the dynamic formulation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.63
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• pp.33-43
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• 2001

To estimate the reliability of a large and complex network with a small variance, we propose two dynamic Monte Carlo sampling methods: the sequential minimal cut set (SMCS) and the sequential minimal path set (SMPS) methods. These methods do not require all minimal cut sets or path sets to be given in advance and do not simulate all arcs at each trial, which can decrease the valiance of network reliability. Based on the proposed methods, we develop the importance sampling estimators, the total hazard (or safety) estimator and the hazard (or safety) importance sampling estimator, and compare the performance of these simulation estimators. It is found that these estimators can significantly reduce the variance of the raw simulation estimator and the usual importance sampling estimator. Especially, the SMCS algorithm is very effective in case that the failure probabilities of arcs are low. On the contrary, the SMPS algorithm is effective in case that the success Probabilities of arcs are low.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1255-1265
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• 2018

The need for a PSA (Probabilistic Safety Assessment) for a multi-unit at a site is growing after the Fukushima accident. Many countries have been studying issues regarding a multi-unit PSA. One of these issues is the problem of many combinations of accident sequences in a multi-unit PSA. This paper deals with the methodology and software to quantify a PSA scenarios for a multi-unit site. Two approaches are developed to quantify a multi-unit PSA. One is to use a minimal cut set approach, and the other is to use a Monte Carlo approach.

• The Pure and Applied Mathematics
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• v.26 no.3
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• pp.199-208
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• 2019

A necessary and sufficient condition in terms of lower cut sets is given for the insertion of a Baire-.5 function between two comparable real-valued functions on the topological spaces that whose $F_{\sigma}$-kernel of sets are $F_{\sigma}$-sets.

• The Pure and Applied Mathematics
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• v.26 no.1
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• pp.1-12
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• 2019

Necessary and sufficient conditions in terms of lower cut sets are given for the strong insertion of a Baire-.5 function between two comparable real-valued functions on the topological spaces that $F_{\sigma}-kernel$ of sets are $F_{\sigma}-sets$.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.211-217
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• 2012

Conventional GrabCut algorithm is semi-automatic algorithm that user must be set rectangle window surrounds the object. This paper studied automatic object detection to solve these problem by detecting salient region based on Human Visual System. Saliency map is computed using Lab color space which is based on color opposing theory of 'red-green' and 'blue-yellow'. Then Saliency Points are computed from the boundaries of Low-Frequency region that are extracted from Saliency Map. Finally, Rectangle windows are obtained from coordinate value of Saliency Points and these windows are used in GrabCut algorithm to extract objects. Through various experiments, the proposed algorithm computing rectangle windows of salient region and extracting objects has been proved.

• Proceedings of the Korean Nuclear Society Conference
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• 2005.10a
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• pp.544-545
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• 2005