• ETRI Journal
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• v.41 no.5
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• pp.619-625
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• 2019

In this paper, we propose an array pattern synthesis scheme using semidefinite programming (SDP) under array excitation power constraints. When an array pattern synthesis problem is formulated as an SDP problem, it is known that an additional rank-one constraint is generated inevitably and relaxed via semidefinite relaxation. If the solution to the relaxed SDP problem is not of rank one, then conventional SDP-based array pattern synthesis approaches fail to obtain optimal solutions because the additional rank-one constraint is not handled appropriately. To overcome this drawback, we adopted a bisection technique combined with a penalty function method. Numerical applications are presented to demonstrate the validity of the proposed scheme.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.141-149
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• 1993

Production of hydro-energy is random in its output amount due to the characteristics of the reservoir inflows. Therefore, it is necessary to provide the rationality in determining the amount of energy for a supply contract. This study presents a methodology for determining reasonably reliable amount of the energy supply considering the energy sale-incomes associated with the penalties which are subject to inflow-reliabilities. The objective function consists of the returns of energy sales and the risk-loss function to reflect statistically relevant risks. A range of the coefficient of the risk-loss function was figured out by its sensitivity analysis. The risk-loss herein means the penalty which should be paid by the energy supplier in case that the level of the energy supply is behind the contracted amount. And the reliability of reservoir inflow is defined by the exceedance probability of the inflow. The log-normal distribution was accepted as the probability density function of monthly inflows on the level of significance at 5%. Golden-ratio searching was applied to identify the optimal reliability and Incremental Dynamic Programming was used to maximize generation of the hydro-power energy in reservoir operation. The algorithm was the applied to the Daechung multi-purpose reservoir and hydro-power plant system in order to verify its usefulness.

• Progress in Medical Physics
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• v.29 no.4
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• pp.150-156
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• 2018

This study aims to develop an improved Feldkamp-Davis-Kress (FDK) reconstruction algorithm using anisotropic total variation (ATV) minimization to enhance the image quality of low-dose cone-beam computed tomography (CBCT). The algorithm first applies a filter that integrates the Shepp-Logan filter into a cosine window function on all projections for impulse noise removal. A total variation objective function with anisotropic penalty is then minimized to enhance the difference between the real structure and noise using the steepest gradient descent optimization with adaptive step sizes. The preserving parameter to adjust the separation between the noise-free and noisy areas is determined by calculating the cumulative distribution function of the gradient magnitude of the filtered image obtained by the application of the filtering operation on each projection. With these minimized ATV projections, voxel-driven backprojection is finally performed to generate the reconstructed images. The performance of the proposed algorithm was evaluated with the catphan503 phantom dataset acquired with the use of a low-dose protocol. Qualitative and quantitative analyses showed that the proposed ATV minimization provides enhanced CBCT reconstruction images compared with those generated by the conventional FDK algorithm, with a higher contrast-to-noise ratio (CNR), lower root-mean-square-error, and higher correlation. The proposed algorithm not only leads to a potential imaging dose reduction in repeated CBCT scans via lower mA levels, but also elicits high CNR values by removing noisy corrupted areas and by avoiding the heavy penalization of striking features.

• ETRI Journal
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• v.35 no.3
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• pp.448-458
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• 2013

This paper presents a generalized post-processing technique for enhancing the pseudorandomness of digital chaotic oscillators through a nonlinear XOR-based operation with rotation and feedback. The technique allows full utilization of the chaotic output as pseudorandom number generators and improves throughput without a significant area penalty. Digital design of a third-order chaotic system with maximum function nonlinearity is presented with verified chaotic dynamics. The proposed post-processing technique eliminates statistical degradation in all output bits, thus maximizing throughput compared to other processing techniques. Furthermore, the technique is applied to several fully digital chaotic oscillators with performance surpassing previously reported systems in the literature. The enhancement in the randomness is further examined in a simple image encryption application resulting in a better security performance. The system is verified through experiment on a Xilinx Virtex 4 FPGA with throughput up to 15.44 Gbit/s and logic utilization less than 0.84% for 32-bit implementations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.514-537
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• 2020

Wireless sensor network (WSN) is a distributed network composed of many sensory nodes. It is precisely due to the clustering unevenness and cluster head election randomness that the energy consumption of WSN is excessive. Therefore, a many-objective optimization WSN energy balance model is proposed for the first time in the clustering stage of LEACH protocol. The four objective is considered that the cluster distance, the sink node distance, the overall energy consumption of the network and the network energy consumption balance to select the cluster head, which to better balance the energy consumption of the WSN network and extend the network lifetime. A many-objective optimization algorithm to optimize the model (LEACH-ABF) is designed, which combines adaptive balanced function strategy with penalty-based boundary selection intersection strategy to optimize the clustering method of LEACH. The experimental results show that LEACH-ABF can balance network energy consumption effectively and extend the network lifetime when compared with other algorithms.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.1
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• pp.122-130
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• 2001

In order to improve the efficiency of the design process and the quality of the resulting design, this study proposes a design method for determining design variables of an automotive wheel-bearing unit of double-row angular-contact ball bearing type by using a genetic algorithm. The desired performance of the wheel-bearing unit is to maximize system life while satisfying geometrical and operational constraints without enlarging mounting spae. The use of gradient-based optimization methods for the design of the unit is restricted because this design problem is characterized by the presence of discrete design variables such as the number of balls and standard ball diameter. Therefore, the design problem of rolling element bearings is a constrained discrete optimization problem. A genetic algorithm using real coding and dynamic mutation rate is used to efficiently find the optimum discrete design values. To effectively deal with the design constraints, a ranking method is suggested for constructing a fitness function in the genetic algorithm. A computer program is developed and applied to the design of a real wheel-bearing unit model to evaluate the proposed design method. Optimum design results demonstrate the effectiveness of the design method suggested in this study by showing that the system life of an optimally designed wheel-bearing unit is enhanced in comparison with that of the current design without any constraint violations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.7
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• pp.429-436
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• 2003

This paper presents a new approach for evaluating the transmission marginal loss factors (MLFs) considering the reactive power. Generally, MLFs are represented as the sensitivity of transmission losses, which is computed from the change of the generation at reference bus by the change of the load at the arbitrary bus-i. The conventional evaluation method for MLFs uses the only H matrix, which is a part of jacobian matrix. Therefore, the MLFs computed by the existing method, don't consider the effect of the reactive power, although the transmission losses are a function of the reactive power as well as the active power. To compensate the limits of the existing method for evaluating MLFs, the power factor at the bus-i is introduced for reflecting the effect of the reactive power in the evaluation method of the MLFs. Also, MLFs calculated by the developed method are applied to energy spot markets to reflect the impacts of reactive power. This method is tested with the sample system with 5-bus, and analyzed how much MLFs have an effect on the bidding/offer price, market clearing price(MCP), and settlement in the competitive energy spot market. This paper compared the results of MLFs calculated by the existing and proposed method for the IEEE 14-bus system, and the KEPCO system.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.3 s.168
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• pp.146-153
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• 2005

In this paper, a multi-step optimization using genetic algorithm with variable penalty function is introduced to the structural design optimization of a grinding machine. The design problem, in this study, is to find out the optimum configuration and dimensions of structural members which minimize the static compliance, the dynamic compliance, and the weight of the machine structure simultaneously under several design constraints such as dimensional constraints, maximum deflection limit, safety criterion, and maximum vibration amplitude limit. The first step is shape optimization, in which the best structural configuration is found by getting rid of structural members that have no contributions to the design objectives from the given initial design configuration. The second and third steps are sizing optimization. The second design step gives a set of good design solutions having higher fitness for lightweight and minimum static compliance. Finally the best solution, which has minimum dynamic compliance and weight, is extracted from the good solution set. The proposed design optimization method was successfully applied to the structural design optimization of a grinding machine. After optimization, both static and dynamic compliances are reduced more than 58.4% compared with the initial design, which was designed empirically by experienced engineers. Moreover the weight of the optimized structure are also slightly reduced than before.

• Journal of Ocean Engineering and Technology
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• v.25 no.4
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• pp.28-35
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• 2011

In this paper, the wave-induced motion characteristics of a floating pendulor are investigated numerically. A floating pendulor is a movable-body-type wave energy converter. This device consists of three main parts (floater, pendulum, and damping plates). In order to obtain the hydrodynamic coefficients and wave exciting forces acting on floating bodies, a higher-order boundary element method (HOBEM) using a wave Green function is applied to the present problems. The hinged motion of a pendulum is simulated by applying the penalty method. In order to obtain a more realistic motion response for a pendulor, numerical body damping is included. First, the wave force and motion characteristics of just a floater are observed with respect to different shape parameters. Then, a coupled analysis of a floater, pendulum, and damping plates is carried out. The relative pitch velocity and wave forces acting on the floating pendulor are compared with those of a fixed pendulor.

• IE interfaces
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• v.17 no.4
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• pp.472-481
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• 2004

In this paper, we propose a linear programming model of supply planning process for the supply chain collaboration strategy of a company. The amount of its supplying quantity relies on outsourcing suppliers heavily. Conversely, the revenues of those suppliers are highly dependent on the supplying quota from the supply network planning of the company. In order to keep the supply stable through collaboration, the company builds such a policy to guarantee the fairness on revenue between the supplies. For this, the supply network plan should keep the capacity utilization ratio even for all the suppliers. But the production capacities are different and the distribution of molds is disproportional through suppliers, so the supply network plan is not easily established with simple arithmetic processes. Therefore, we developed the linear programming model with those target function and constraints minimizing the costs for holding inventory and penalty of delayed delivery, simultaneously guaranteeing the even capacity utilization through suppliers. The proposed model has been applied to real case and the evaluation for the planning result from the model would be followed in order to make sure that our model guarantee on extracting the supply network plan subordinated to the policy. Also we mention about further studies for improvement of the model.