• The KIPS Transactions:PartB
• /
• v.17B no.2
• /
• pp.115-124
• /
• 2010

Stereo matching techniques are categorized in two major schemes, local and global matching techniques. In global matching schemes, several investigations are introduced, where cost accumulation is performed in multiple matching lines. In this paper, we introduce a new multi-line stereo matching techniques which expands a conventional single-line matching scheme to multiple one. Matching cost is based on simple normalized cross correlation. We expand the scan-line optimization technique to a multi-line scan-line optimization technique. The proposed technique first generates a reliability image, which is iteratively updated based on the previous reliability measure. After some number of iterations, the reliability image is completed by a hole-filling algorithm. The hole-filling algorithm introduces a disparity score table which records the disparity score of the current pixel. The disparity of an empty pixel is determined by comparing the scores of the neighboring pixels. The proposed technique is tested using the Middlebury and CMU stereo images. The error analysis shows that the proposed matching technique yields better performance than using conventional global matching algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.33 no.1
• /
• pp.39-47
• /
• 2005

In this paper, a method of station keeping strategy using relative orbital motion and numerical optimization technique is presented for geostationary spacecraft. Relative position vector with respect to an ideal geostationary orbit is generated using high precision orbit propagation, and compressed in terms of polynomial and trigonometric function. Then this relative orbit model is combined with optimization scheme to propose a very efficient and flexible method of station keeping planning. Proper selection of objective and constraint functions for optimization can yield a variety of station keeping methods improved over the classical ones. Results from the nonlinear simulation have been shown to support such concept.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.34 no.9
• /
• pp.1-10
• /
• 2006

An optimization study on a small turbopump impeller operating at the low specific speed is conducted to obtain high output head at the impeller exit. Its specific speed in SI unit (RPM, m3/sec, m) is 4.0, and the outer diameter is 56mm. On the optimization, the outer diameter of the impeller is maintained constant to restrict the pump size, and an objective function of pressure head is maximized with eight design variables, which are related with designing an impeller shape. The response surface method is used to the optimization scheme, and the commercial code CFX-10 is applied for numerical analysis. The pressure head of the objective function obtained with an optimized impeller is increased by 9.7% compared with that obtained on an impeller designed with typically recommended design parameters. This increment is caused by reducing the recirculation region within the impeller passage.

• Structural Engineering and Mechanics
• /
• v.56 no.5
• /
• pp.707-726
• /
• 2015

There is a growing trend of considering uncertainty in optimization process since last few decades. In this regard, Robust Design Optimization (RDO) scheme has gained increasing momentum because of its virtue of improving performance of structure by minimizing the variation of performance and ensuring necessary safety and feasibility of constraint under uncertainty. In the present study, RDO of reinforced concrete folded plate and shell structure has been carried out incorporating uncertainty in the relevant parameters by Monte Carlo Simulation. Folded plate and shell structures are among the new generation popular structures often used in aesthetically appealing constructions. However, RDO study of such important structures is observed to be scarce. The optimization problem is formulated as cost minimization problem subjected to the force and displacements constraints considering dead, live and wind load. Then, the RDO is framed by simultaneously optimizing the expected value and the variation of the performance function using weighted sum approach. The robustness in constraint is ensured by adding suitable penalty term and through a target reliability index. The RDO problem is solved by Sequential Quadratic Programming. Subsequently, the results of the RDO are compared with conventional deterministic design approach. The parametric study implies that robust designs can be achieved by sacrificing only small increment in initial cost, but at the same time, considerable quality and guarantee of the structural behaviour can be ensured by the RDO solutions.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.4B
• /
• pp.178-185
• /
• 2005

NEMO basic support is a solution that provides network mobility in the Internet topology. Yet, when multiple mobile networks are nested, this basic solution suffers ken pinball-routing and a severe routing overhead. Therefore, several solutions for route optimization in a nested mobile network have already been suggested by the IETF NEMO WG. However, the current paper proposes Regional Information-based Route Optimization (RIRO) in which mobile routers maintain a Nested Router List (NRL) to obtain next-hop information, and packets are transmitted with a new routing header called an RIRO Routing Header (RIRO-RH). We showed that RIRO had the minimum packet overhead that remained constant, irrespective of how deep the mobile network was nested, in comparison with two earlier proposed schemes - Reverse Routing Header (RRH) and Bi-directional tunnel between HA and Top-Level mobile router (BHT).

• The KIPS Transactions:PartB
• /
• v.11B no.2
• /
• pp.213-220
• /
• 2004

Evolutionary algorithms are well-suited for multi-objective optimization problems involving several. often conflicting objective. Pareto-based evolutionary algorithms, in particular, have shown better performance than other multi-objective evolutionary algorithms in comparison. Recently, pareto-based evolutionary algorithms uses a density information in fitness assignment scheme for generating uniform distributed global pareto optimal front. However, the usage of density information is not Important elements in a whole evolution path but plays an auxiliary role in order to make uniform distribution. In this paper, we propose an evolutionary algorithms for multi-objective optimization which assigns the fitness using pareto dominance rank and density weighting, and thus pareto dominance rank and density have similar influence on the whole evolution path. Furthermore, the experimental results, which applied our method to the six multi-objective optimization problems, show that the proposed algorithms show more promising results.

• Nuclear Engineering and Technology
• /
• v.55 no.4
• /
• pp.1382-1399
• /
• 2023

Pressure relief valve (PRV) is one of the important control valves used in nuclear power plants, and its sealing performance is crucial to ensure the safety and function of the entire pressure system. For the sealing performance improving purpose, an explicit function that accounts for all design parameters and can accurately describe the relationship between the multi-design parameters and the seal performance is essential, which is also the challenge of the valve seal design and/or optimization work. On this basis, a surrogate model-based design optimization is carried out in this paper. To obtain the basic data required by the surrogate model, both the Finite Element Model (FEM) and the Computational Fluid Dynamics (CFD) based numerical models were successively established, and thereby both the contact stresses of valve static sealing and dynamic impact (between valve disk and nozzle) could be predicted. With these basic data, the polynomial chaos expansion (PCE) surrogate model which can not only be used for inputs-outputs relationship construction, but also produce the sensitivity of different design parameters were developed. Based on the PCE surrogate model, a new design scheme was obtained after optimization, in which the valve sealing stress is increased by 24.42% while keeping the maximum impact stress lower than 90% of the material allowable stress. The result confirms the ability and feasibility of the method proposed in this paper, and should also be suitable for performance design optimizations of control valves with similar structures.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.6
• /
• pp.2429-2449
• /
• 2018

Dynamic data possession verification is a common requirement in cloud storage systems. After the client outsources its data to the cloud, it needs to not only check the integrity of its data but also verify whether the update is executed correctly. Previous researches have proposed various schemes based on Merkle Hash Tree (MHT) and implemented some initial improvements to prevent the tree imbalance. This paper tries to take one step further: Is there still any problems remained for optimization? In this paper, we study how to raise the efficiency of data dynamics by improving the parts of query and rebalancing, using a new data structure called Rank-Based Merkle AVL Tree (RB-MAT). Furthermore, we fill the gap of verifying multiple update operations at the same time, which is the novel batch updating scheme. The experimental results show that our efficient scheme has better efficiency than those of existing methods.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10b
• /
• pp.179-184
• /
• 1993

In this paper, an optimal motion control scheme is proposed for robot manipulators. A simple explicit solution to the Hamilton-Jacobi equation is presented. The optimization of motion control is based on the mininization of the torque term affecting the kinetic energy and the augmented error which has the first-order stable dynamics for the position and velocity tracking error. In the presence of parametric uncertainty, an adaptive control scheme using the optimal principle is proposed. The global stability of the closed-loop system is guaranteed by the Lyapunov stability approach, The effectiveness and feasibility of the proposed control schemes are shown by simulation results.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.6
• /
• pp.58-69
• /
• 1998

This paper introduces a novel neuro-fuzzy system based on the polynomial fuzzy neural network(PFNN) architecture. The PFNN consists of a set of if-then rules with appropriate membership functions whose parameters are optimized via a hybrid genetic algorithm. A polynomial neural network is employed in the defuzzification scheme to improve output performance and to select appropriate rules. A performance criterion for model selection, based on the Group Method of DAta Handling is defined to overcome the overfitting problem in the modeling procedure. The hybrid genetic optimization method, which combines a genetic algorithm and the Simplex method, is developed to increase performance even if the length of a chromosome is reduced. A novel coding scheme is presented to describe fuzzy systems for a dynamic search rang in th GA. For a performance assessment of the PFNN inference system, three well-known problems are used for comparison with other methods. The results of these comparisons show that the PFNN inference system outperforms the other methods while it exhibits exceptional robustness characteristics.