• Coupled systems mechanics
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• v.11 no.3
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• pp.259-266
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• 2022

Non-Traditional Optimization methods are successfully used in solving many engineering problems. Shaft is one of important element of machines and it is used to transmit power from a machine which produces power to a machine which absorbs power. In this paper, ten non-traditional optimization methods that are ALO, GWO, DA, FPA, FA, WOA, CSO, PSO, BA and GSA are used to find minimum weight of hollow shaft to get global optimal solution. The problem has two design variables and two inequality constraints. The comparative results show that the Particle Swarm Optimization outperforms other methods and the results are validated using ANSYS.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.285-294
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• 2023

The trade dispute between China and the U.S. began before Corona and is easing at this time by bringing new changes to the pendemic, and the development of the Chinese manufacturing industry has increased interdependence between the U.S. and China. However, the overall global trade should be less than before pendemic, and Korea's response strategy should be made serious at this time.However, new changes are taking place again these days. With the recent outbreak of COVID-19 in Shanghai, China, new changes are expected to occur in China's industrial chain. As the Chinese government strictly creates quarantine figures for COVID-19, many factories and companies among industries are forced to close for a while. As economic globalization and division of labor continue to deepen, multinationals choose suppliers and industrial chains within the world to form a global supply chain structure to pursue cost minimization and profit maximization. China is an indispensable part. Whether it is China, the U.S. or Korea, it can be a risk and an opportunity now.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1891-1896
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• 2006

In this paper, we propose an improved Active Shape Model for extracting lip contour. Lip deformation is modeled by a statistically deformable model based Active Shape Model. Because each point is moved independently using local profile information in Active Shape Model, many error may happen. To use a global information, we define an energy function similar to an energy function in Active Contour Model, and points are moved to positions at which the total energy is minimized. The experiments have been performed for many lip images of Tulip 1 database, and show that our method extracts lip shape than a traditional ASM more exactly.

• Journal of Ocean Engineering and Technology
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• v.18 no.5
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• pp.29-35
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• 2004

A new approach, referred to as a successive zooming genetic algorithm (SZGA), is proposed for identifying a global solution, using continuous zooming factors for optimization problems. In order to improve the local fine-tuning of the GA, we introduced a new method whereby the search space is zoomed around the design variable with the best fitness per 100 generation, resulting in an improvement of the convergence. Furthermore, the reliability of the optimized solution is determined based on the theory of probability, and the parameter used for the successive zooming method is optimized. With parameter optimization, we can eliminate the time allocated for deciding parameters used in SZGA. To demonstrate the superiority of the proposed theory, we tested for the minimization of a multiple function, as well as simple functions. After testing, we applied the parameter optimization to a truss problem and wicket gate servomotor optimization. Then, the proposed algorithm identifies a more exact optimum value than the standard genetic algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.1102-1110
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• 2005

In this paper, we proposed a advanced approach to resolve the trade-off problem for the threshold value determining the photo-consistency in the previous algorithms. The threshold value for the surface voxel is substituted the photo-consistency value of the inside voxel. As iterating the voxel coloring process, the threshold is approached to the optimal value for the individual surface voxel. we present an energy minimization formulation of the binary labeling problem that surface voxels classify into opacity or transparency. The energy formula consists of the data term and the smoothness term. As considering neighboring voxels in the labeling problem, the unevenness of reconstructed surface is reduced. The labeling whose energy is the global minimum can be computed using a graph cut.

• Journal of Power Electronics
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• v.18 no.3
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• pp.789-801
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• 2018

Model predictive direct power control (MPDPC) is a widely recognized high-performance control strategy for a three-phase grid-connected pulse width modulation (PWM) rectifier. Unlike those of conventional grid-connected PWM rectifiers, the active and reactive powers of permanent magnet synchronous generator (PMSG)-connected PWM rectifiers, which are used in electromagnetic transmitters, cannot be calculated as the product of voltage and current because the back electromotive force (EMF) of the generator cannot be measured directly. In this study, the predictive power model of the rectifier is obtained by analyzing the relationship among flux, back EMF, active/reactive power, converter voltage, and stator current of the generator. The concept of duty cycle control in the proposed MPDPC is introduced by allocating a fraction of the control period for a nonzero vector and rest time for a zero vector. When nonzero vectors and their duration in the predefined cost function are simultaneously evaluated, the global power ripple minimization is obtained. Simulation and experimental results prove that the proposed MPDPC strategy with duty cycle control for the PMSG-connected PWM rectifier can achieve better control performance than the conventional MPDPC-SVM with grid-connected PWM rectifier.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.6
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• pp.305-311
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• 2000

This paper presents a hybrid algorithm for solving optimal power flow(OPF) in order to enhance a systems capability to cope with outages, which is based on combined application of evolutionary computation and local search method. The efficient algorithm combining main advantages of two methods is as follows : Firstly, evolutionary computation is used to perform global exploitation among a population. This gives a good initial point of conventional method. Then, local methods are used to perform local exploitation. The hybrid approach often outperforms either method operating alone and reduces the total computation time. The objective function of the security constrained OPF is the minimization of generation fuel costs and real power losses. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). In OPF considering security, the outages are selected by contingency ranking method(contingency screening model). The OPF considering security, the outages are selected by contingency ranking method(contingency screening model). The method proposed is applied to IEEE 30 buses system to show its effectiveness.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.11
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• pp.532-540
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• 2001

In this paper, we propose a probabilistic tabu search strategy for function optimization. It is composed of two procedures, one is Basic search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify search region. In basic search procedure, we use Belief space and Near region to create neighbors. Belief space is made of high-rank neighbors to effectively restrict searching space, so it can improve searching time and local or global searching capability. When a solution is converged in a local area, Restarting procedure works to search other regions. In this time, we use Probabilistic Tabu Strategy(PTS) to adjust parameters such as a reducing rate, initial searching region etc., which makes enhance the performance of searching ability in various problems. In order to show the usefulness of the proposed method, the PTS is applied to the minimization problems such as De Jong functions, Ackley function, and Griewank functions etc., the results are compared with those of GA or EP.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.3
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• pp.509-518
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• 1987

The paper is concerned with the analysis of axisymmetric forward extrusion by using the method of weighted residuals. In the method of weighted residuals, the flow function and the stress functions are assumed so as to cover the global control volume. The derived stress and strain components are used to formulate a constitutive equation in the error form, so that the error is minimized to determine the stress and strain components. The method of least squares is then chosen for the minimization of errors. The distribution of stresses and strains and the forming load are determined for the workhardening material considering the frictional effect at the die surface. The computed results are very similar to those obtained by the finite element method. The method is simpler in application and requires less computational time than the finite element method. Experiments are carried out for aluminum and steel specimens using curved dies. It is found that the experimental observation is mostly in agreement with the computed results by the method of weighted residuals.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.53-60
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• 2008

This paper proposes a new multiobjective optimization method for discriminative training of hidden Markov models (HMMs) used as the recognizer for automatic lipreading. While the conventional Baum-Welch algorithm for training HMMs aims at maximizing the probability of the data of a class from the corresponding HMM, we define a new training criterion composed of two minimization objectives and develop a global optimization method of the criterion based on simulated annealing. The result of a speaker-dependent recognition experiment shows that the proposed method improves performance by the relative error reduction rate of about 8% in comparison to the Baum-Welch algorithm.