• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.3
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• pp.453-462
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• 2002

Discrete-sizing or standardized steel profiles are used in steel design and construction practice. However, most of numerical optimization methods follow additional step(round-up discrete-sizing routine) to use the standardized steel section profiles, and accordingly the optimality of the resulting design nay be doubtful. Thus, in this paper, an efficient multi-level optimization algorithm is proposed to improve the shortcoming of the conventional optimization methods using the round-up discrete-sizing routine. Also, multi-level optimization technique with a decomposition method that separates both system-level and element-level is incorporated in the algorithm to enhance the performance of the proposed algorithms. The proposed algorithm is expected to achieve considerable improvement on both the efficiency of the numerical process and the accuracy of the global optimum.

• Proceeding of KASS Symposium
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• 2006.05a
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• pp.233-238
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• 2006

This paper provides a new topology optimization technique which is intended to maximize the fundamental frequency with simultaneous consideration of other natural frequencies in the form of multi-frequency problems. The modal strain energy is considered as the objective function to be minimized and the initial volume of structures is used as the constraint function. The resizing algorithm based on the optimality criteria is adopted to update the hole size existing inside the material. From numerical tests, the proposed technique is found to be very effective to maximize the fundamental frequency of the structure and it can also successfully consider several higher mode effects into the optimum topology of structure through the introduction of weights.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.741-744
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• 2015

최근 소셜 미디어를 이용한 대량의 데이터로부터 사용자의 의사결정을 지원하기위한 맞춤형 데이터 추천 서비스가 관심을 받고 있으며 사용자의 선호도에 근접한 데이터 추천기법으로 스카이라인 질의가 연구되어왔다. 그러나 기존의 스카이라인 질의는 데이터의 정적속성(위도, 경도, 가격 등)만을 기준으로 모든 사용자에게 동일한 데이터를 반환하기 때문에 맞춤형 데이터를 추천하기 어렵다. 본 논문에서는 사용자의 기호에 대한 정밀도를 높이기 위해 정적속성에서 동적속성(계산속성)을 유도하는 분기한정 동적 스카이라인 질의 기법(Branch and Bound Dynamic Skyline, BBDS)을 구현하였다. 시뮬레이션에서는 대규모 데이터 및 다양한 분포에 따른 실험을 수행한 결과 BBDS가 기존 기법에 비해 데이터 탐색과 추천에 있어서 향상된 성능을 나타내는 것으로 평가되었다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.5
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• pp.379-387
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• 2019

The complexity of path planning for visiting multiple mission points is even larger than that of single pair path planning. Deciding a path for visiting n mission points requires conducting $n^2+n$ times of single pair path planning. We propose Multiple Mission $D^*$ Lite($MMD^*L$) which is an optimal path planning algorithm for visiting multiple mission points in dynamic environments. $MMD^*L$ reduces the complexity by reusing the computational data of preceding single pair path planning. Simulation results show that the complexity reduction is significant while its path optimality is not compromised.

• Korean Circulation Journal
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• v.54 no.9
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• pp.519-533
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• 2024

The outstanding development in contemporary medicine, highlighted by percutaneous coronary intervention (PCI), was achieved through the adoption of drug-eluting stents (DESs). Although DES is the established therapy for patients undergoing PCI for de novo coronary artery disease (CAD), their drawbacks include restenosis, stent thrombosis, and the requirement for dual antiplatelet therapy (DAPT) with an uncertain duration regarding its optimality. Drug-coated balloon (DCB) treatment leaves nothing behind on the vessel wall, providing the benefit of avoiding stent thrombosis and not necessitating obligatory extended DAPT. After optimizing coronary blood flow, DCB treatment delivers an anti-proliferative drug directly coated on a balloon. Although more evidence is needed for the application of DCB treatment in de novo coronary lesions, recent studies suggest the safety and effectiveness of DCB treatment for diverse conditions including small and large vessel diseases, complex lesions like bifurcation lesions or diffuse or multivessel diseases, chronic total occlusion lesions, acute myocardial infarctions, patients at high risk of bleeding, and beyond. Consequently, we will review the current therapeutic choices for managing de novo CAD using DCB and assess the evidence supporting their concurrent application. Additionally, it aims to discuss future important perspectives.

• Asia Marketing Journal
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• v.15 no.3
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• pp.141-157
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• 2013

Managing customers based on customer equity (CE) has emerged as the most effective way of doing business because of its ability to foster profitable customer relationship management (CRM) through appropriate marketing activities. Most research studies provide conceptual and empirical evidence of the positive link between CE and firm performance. However, regarding this possibility, it has been suggested by some researchers that this link may not hold true for other firms with different firmographic factors, such as firm growth rate, size, and resources. As previous research emphasizes that marketing managers should implement a strategy based on their unique business environment, our study addresses this issue by extending the framework to a different industry setting to investigate the impact of CE on firm performance. We develop a model for examining the relationship between the firm's estimated CE and firm performance by each time period using a distributed lagged model. Then, we investigate the effect of CE on the firm's profitability using a regression analysis. Finally, even though CRM is in increasing demand and firms are focusing on the customer as an asset, we conclude that there is a limited condition for this positive effect of CE. When the life cycle was divided by growth rate, CE was shown to have a distinctive effect on profit. In the case of a high-growth stage, the effect of CE on profit is positive because of its potential customer base, whereas the effect is not significant in a low-growth stage. That is, when the business environment is saturated and the firms are no longer competing in the market, CRM may not be effective. In other words, a long-term performance orientation may not be as effective as previously believed. This research contributes to the previous literature, providing a counterintuitive suggestion that firm managers should be cautious about implementing a CRM strategy and should allocate resources properly in terms of their resource capabilities and ability depending on their situation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.83-86
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• 1996

In this paper we study the problem of augmenting a physical network to improve the topology for new survivable network architectures. We are given a graph G=(V,E,F), where V is a set of nodes that represents transmission systems which be interconnected by physical links, and E is a collection of edges that represent the possible pairs of nodes between which a direct transmission link can be placed. F, a subset of E is defined as a set of the existing direct links, and E/F is defined as a set of edges for the possible new connection. The cost of establishing network $N_{H}$=(V,H,F) is defined by the sum of the costs of the individual links contained in new link set H. We call that $N_{H}$=(V,H,F) is feasible if certain connectivity constrints can be satisfied in $N_{H}$=(V,H,F). The computational goal for the suggested model is to find a minimum cost network among the feasible solutions. For a k edge (node) connected component S .subeq. F, we charactrize some optimality conditions with respect to S. By this characterization we can find part of the network that formed by only F-edges. We do not need to augment E/F edges for these components in an optimal solution. Hence we shrink the related component into a node. We study some good primal heuristics by considering construction and exchange ideas. For the construction heuristics, we use some greedy methods and relaxation methods. For the improvement heuristics we generalize known exchange heuristics such as two-optimal cycle, three-optimal cycle, pretzel, quezel and one-optimal heuristics. Some computational experiments show that our heuristic is more efficient than some well known heuristics.stics.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.170-178
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• 2017

This paper proposes an improved path-planning technique based on the $A^*$ algorithm. The conventional $A^*$ algorithm only considers the optimality of the planned path and sometimes produces a path that an unmanned underwater vehicle (UUV) cannot navigate due to its dynamic constraint such as the limit of the radius of gyration. It is because that the previous method evaluate the moving cost based on the straight distance between nodes. We enhance the conventional method by evaluating the moving cost on the basis of the practically navigable trajectory, which is generated by the waypoint-tracking control of the UUV dynamics. The simulation examples indeed show the effectiveness of the proposed technique.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.351-356
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• 2022

Among the path planning methods used to generate the ship's path, the graph search-based method is widely used because it has the advantage of its completeness, optimality. In order to apply the graph-based search method to the berthing path plan, the deviation from the path must be minimized. Path following suitability should be considered essential, since path deviation during berthing can lead to collisions with berthing facilities. However, existing studies of graph search-based berthing path planning are dangerous for application to real-world navigation environments because they produce results with a course change just before berthing. Therefore, in this paper, we develop a cost function suitable for path following, and propose a 3D A* algorithm that applies it. In addition, in order to evaluate the suitability for the actual operating environment, the results of the path generation of the algorithm are compared with the trajectory of the data collected by manned operations.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.6
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• pp.56-66
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• 1998

This paper investigates a neuro-controller combined in parallel with a conventional linear controller of PID type in order to control nonminimum phase systems more efficiently. The objective is to minimize overall position errors as well as to maintain small undershooting. A costfunction is proposed with two conflict objectives. The neuro-controller is trained off-line with evolutionary programming(EP) in such a way that it becomes optimal by minimizing the given cost function through global evaluation based on desired control performance during the whole training time interval. However, it is not easy to find an optimal solution which satisfies individual objective simultaneously. With the concept of Pareto optimality and EP, we train the proposed controller more effectively and obtain a valuable set of optimal solutions. Simulation results show the efficacy of the proposed controller in a viewpoint of improvement of performance of a step response like fast settling time and small undershoot or overshoot compared with that of a conventional linear controller.