• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.6
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• pp.7-14
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• 2000

This paper describes the synthesis of robust decentralized controllers for uncertain large-scale discrete-time systems with time-delays in subsystem interconnections. Based on the Lyapunov method, a sufficient condition for robust stability, is derived in terms of a linear matrix inequality (LMI). The solutions of the LMI can be easily obtained using various efficient convex optimization techniques. A numerical example is given to illustrate the proposed method.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.897-898
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• 2008

Array comparative genomic hybridization (aCGH) has been used to detect chromosomal regions of amplifications or deletions, which allows identification of new cancer related genes. As aCGH, a large-scale spatial data, contains significant amount of noises in its raw data, it has been an important research issue to segment genomic DNA regions to detect its true underlying copy number aberrations (CNAs). In this study, we focus on applying a segmentation method to multiple data sets. We compare two different threshold values for analyzing aCGH data with CBS method [1]. The proposed threshold values are p-value or $Q{\pm}1.5IQR$ and $Q{\pm}1.5IQR$.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.3
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• pp.45-51
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• 1983

A local suboptimal controller with low sensitivity property is studied for a case of large scale systems. More specifically, necessary conditions for the suboptomal gain matrices are obtained by a parameter optimization technique, from which a design method in the form of an algorithm is suggested. To show the validity of the result and, in particular, to appreciate the effect of adding the sensitivity function, a numerical example is included.

• Journal of KIBIM
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• v.6 no.3
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• pp.24-33
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• 2016

Planning occurs from day-to-day, small-scale decisions to large-scale infrastructure investment decisions. For that reason, various attempts have been made to appropriately assist decision-making process and its optimization. Lately, initiation of a large amount of data, also known as big data has received great attention from diverse disciplines because of versatility and adoptability in its use and possibility to generate new information. Accordingly, implementation of big data and other information management systems, such as geographic information systems (GIS) and building information modeling (BIM) have received enough attention to establish each of its own profession and other associated activities. In this extent, this study illustrates a series of big data implementation cases that can provide a lesson to urban planning domain. In specific, case studies analyze how data was used to extract the most optimized solution and what aspects could be helpful in relation to planning decisions. Also, important notions about GIS and its application in various urban cases are examined.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.1-8
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• 2016

This paper proposes a novel broadcast scheduling algorithm for wireless large-scale networks based on theory of complex networks. In the proposed algorithm, the network topology is formed based on a scale-free network and the probability of link distribution is analyzed. In this paper, the characteristics of complex systems are analyzed (which are not concerned by the existing broadcast scheduling algorithm techniques) and the optimization of network transmission efficiency and network time delay are provided.

• Journal of Mechanical Science and Technology
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• v.20 no.1
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• pp.133-146
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• 2006

Collaborative optimization (CO) is a multi-level decomposed methodology for a large-scale multidisciplinary design optimization (MDO). CO is known to have computational and organizational advantages. Its decomposed architecture removes a necessity of direct communication among disciplines, guaranteeing their autonomy. However, CO has several problems at convergence characteristics and computation time. In this study, such features are discussed and some suggestions are made to improve the performance of CO. Only for the system level optimization, genetic algorithm is used and gradient-based method is used for subspace optimizers. Moreover, response surface models are replaced as analyses in subspaces. In this manner, CO is applied to aero-structural design problems of the aircraft wing and its results are compared with the multidisciplinary feasible (MDF) method and the original CO. Through these results, it is verified that the suggested approach improves convergence characteristics and offers a proper solution.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.321-326
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• 2007

The joined-wing is a new concept of the airplane wing. The fore-wing and the aft-wing arc joined together in the joined-wing. The range and loiter are longer than those of a conventional wing. The joined-wing can lead to increased aerodynamic performances and reduction of the structural weight. The structural behavior of the joined-wing has a high geometric nonlinearity according to the external loads. The gust loads are the most critical loading conditions in the structural design of the joined-wing. The nonlinear behavior should be considered in the optimization of the joined-wing. It is well known that conventional nonlinear response optimization is extremely expensive: therefore, the conventional method is almost impossible to use in large scale structures such as the joined-wing. In this research, geometric nonlinear response structural optimization is carried out using equivalent loads. Equivalent loads are the load sets which generate the same response field in linear analysis as that from nonlinear analysis. In the equivalent loads method, the external loads are transformed to the equivalent loads (EL) for linear static analysis, and linear response optimization is carried out based on the EL.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.608-615
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• 2022

Construction projects are large-scale projects that require extensive construction costs and resources. Especially, scheduling is considered as one of the essential issues for project success. However, the schedule and resource management are challenging to conduct in high-tech construction projects including complex design of MEP and architectural finishing which has to be constructed within a limited workspace and duration. In order to deal with such a problem, this study suggests resource and sequence optimization using constraint programming in construction projects. The optimization model consists of two modules. The first module is the data structure of the schedule model, which consists of parameters for optimization such as labor, task, workspace, and the work interference rate. The second module is the optimization module, which is for optimizing resources and sequences based on Constraint Programming (CP) methodology. For model validation, actual data of plumbing works were collected from a construction project using a five-minute rate (FMR) method. By comparing actual data and optimized results, this study shows the possibility of reducing the duration of plumbing works in construction projects. This study shows decreased overall project duration by eliminating work interference by optimizing resources and sequences within limited workspaces.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.5
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• pp.488-497
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• 2009

The freak wave, also known as New-Year-Wave in the north Atlantic, is relatively large and spontaneous ocean surface wave that can sink even large ships and destroy maritime structures. To understand oceanic conditions that develop freak waves, we simulated and generated two versions of scale-downed waves (1:64 and 1:42) in a numerical wave tank and compared the results with the experiment in wave flume. Both of the breaking and non-breaking waves were generated in the simulation. The numerical simulation was implemented based on the finite volume method and a genetic optimization algorithm. Random values were assigned as the initial values for the parameter in the control function, which produced signals representing the motion of wave-maker. The same signal obtained from the optimization process was used for both of the simulation and the experiment. By varying the object function and restrictions of the simulation, a best profile of design wave was selected based on the characteristics, height and period of simulated waves. Results showed that the simulation and experiment with the scale of 1:42 agreed better with freak waves in the natural condition. The presented simulation method will contribute to saving the time and cost for conducting subsequent response analyses of motion under freak waves in the course of the model test for ship and maritime structure.

• Microbiology and Biotechnology Letters
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• v.48 no.1
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• pp.48-56
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• 2020

This study aimed to optimize the culture conditions to improve the crude biosurfactant activity of Bacillus pumilus IJ-1, using a 3³ full-factorial design of response surface methodology (RSM). It was found that submerged fermentation of B. pumilus improved the activity of the crude biosurfactant. The factors selected for optimization were NaCl concentration, temperature, and tryptone concentration. Response surface analysis revealed that the fitted quadratic model was statistically significant and produced an adequate R² value (0.9898) and a low probability value (<0.0001). The optimum level for each factor was found to be 0.567% (w/v) NaCl, 21.851℃ and 0.765% (w/v) tryptone, respectively. Crude biosurfactant activity was found to be most affected by tryptone concentration; then temperature, and finally NaCl concentration. Our results may potentially facilitate large-scale biosurfactant production from B. pumilus IJ-1.