• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.527-533
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• 2013

BCI (Brain-Computer Interface) is a system that transforms a subject's brain signal related to their intention into a control signal by classifying EEG (electroencephalograph) signals obtained during the imagination of movement of a subject's limbs. The BCI system allows us to control machines such as robot arms or wheelchairs only by imaging limbs. With the exact same experiment environment, activated brain regions of each subjects are totally different. In that case, a simple approach is to use as many channels as possible when measuring brain signals. However the problem is that using many channels also causes other problems. When applying a CSP (Common Spatial Pattern), which is an EEG extraction method, many channels cause an overfitting problem, and in addition there is difficulty using this technique for medical analysis. To overcome these problems, we suggest an optimal channel selection method using a BPSO (Binary Particle Swarm Optimization), BPSO with channel impact factor, and GA. This paper examined optimal selected channels among all channels using three optimization methods and compared the classification accuracy and the number of selected channels between BPSO, BPSO with channel impact factor, and GA by SVM (Support Vector Machine). The result showed that BPSO with channel impact factor selected 2 fewer channels and even improved accuracy by 10.17~11.34% compared with BPSO and GA.

• Journal of the Korean Institute of Gas
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• v.16 no.1
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• pp.26-32
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• 2012

The autoignition temperature is one of the most important physical properties used to determine the flammability characteristics of chemical substances. Despite the needs of the experimental autoignition temperature data for the design of chemical plants, it is not easy to get the data. This study have built and compared partial least squares (PLS) and support vector machine (SVM) models to predict the autoignition temperatures of 503 organic compounds out of DIPPR 801. As the independent variables of the models, 59 functional groups were chosen based on the group contribution method. The prediction errors calculated from cross-validation were employed to determine the optimal parameters of two models. And, particle swarm optimization was used to get three parameters of SVM model. The PLS and SVM results of the average absolute errors for the whole data range from 58.59K and 29.11K, respectively, indicating that the predictive ability of the SVM is much superior than PLS.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1A
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• pp.62-69
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• 2005

Efforts for standardization of medium access control (MAC) protocol in IEEE802.11e have been made to support quality of service (QoS) in IEEE802.11e MAC protocol. Enhanced disoibuted coordination function (EDCF) of 802.11e MAC protocol is modified to support QoS for packets that have differentiated priority. However, EDCF still has the problem of throughput optimization and priority support. Therefore, we have proposed a scheme called adaptive EDCF for both supporting priority of packets and throughput optimization. We have derived the relation between the number of nodes and contention window size for throughput optimization. Based on the analytic results, we have evaluated the performance of the proposed scheme using OPNET simulations. The simulation results show that using the proposed scheme can improve the overall throughput regardless of the number of nodes and the decrement of the throughput with increasing the number of nodes can be alleviated. Additionally, we have shown that the adaptive EDCF can support priority of packets more effectively than existing EDCF.

• The Journal of the Acoustical Society of Korea
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• v.41 no.6
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• pp.680-690
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• 2022

Vibrations in the pipe system trigger fatigue-related issues and lead to fatal other problems caused by pipe damage. There are numerous studies to analyze and reduce the cause of pipe vibration, among which a small number of studies are being conducted on pipe vibration reduction using friction supports. The study of friction supports, however, focused only on predicting and evaluating the performance of the friction supports and seldomly considered the design perspective of the install location of the supports. Therefore, this study intends to suggest the optimization process for finding the best installation region of friction support to attenuate the vibration of entire piping system. The optimal position of the friction support is predicted only by linear analysis to guarantee optimization efficiency in the design process. The designed friction support location is verified by time domain analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.65-68
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• 2008

The Mobile IP provides the mobility of Mobile Node, but does not provide the mobility of network. For support the mobility of network, the IETF has proposed NEMO(Network Mobility). Route Optimization is a serious problem in mobile network, so several solutions for route optimization in nested mobile network have been suggested by the IETF NEMO WG. This paper proposes scheme about Route Optimization in nested mobile network.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.209-217
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• 2002

This gaper discusses a multidisciplinary design optimization of the engine mounting system to improve the ride quality of a vehicle and to remove the possibility of the resonance between the powertrain system and vehicle systems. The driveline model attempts to support engine mount development by providing sufficient detail for design modification assessment in a modeling environment. Design variables used in this study are the locations, the angles and the stiffness of an engine mount system. The goal of the optimization is both decoupling the roll mode ova powertrain and minimizing the vibration transmitted to the vehicle including the powertrain, simultaneously. By applying forced vibration analysis for vehicle systems and mode decouple analysis for the engine mount system, it is shown that improved optimization result is obtained.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.1
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• pp.122-128
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• 2007

In this paper, a method of station keeping strategy using relative orbital motion and numerical optimization technique is presented for geostationary satellite. 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. Nonlinear simulation results have been shown to support such concept.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.571-575
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• 2008

An engine cradle is a quite important structural assembly for supporting the engine, suspension and steering parts of vehicle and absorbing the vibrations during the drive and the shock in the car crash. Recently, the engine cradle having structural stiffness enough to support the surrounding parts and absorbing the shock of collision has been widely used. The hydroforming technology may cause many advantages to automotive applications in terms of better structural integrity of parts, reduction of production cost, weight reduction, material saving, reduction in the number of joining processes and improvement of reliability. We focus on increasing the durability and the dynamic performance of engine cradle. For realizing this objective, several optimization design techniques such as shape, size, and topology optimization are performed. This optimization scheme based on the sensitivity can provide distinguished performance improvement in using hydroforming.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.2
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• pp.809-818
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• 2019

The current trend in shipyard industry is to reduce the weight of ships to support the reduction of CO₂ emissions. In this study, the stiffened plate was optimized that is used for building most of the ship-structure. Further, this study proposed the hybrid Genetic Algorithm (GA) technique, which combines a genetic algorithm and subsequent optimization methods. The design variables included the number and type of stiffeners, stiffener spacing, and plate thickness. The number and type of stiffeners are discrete design variables that were optimized using the genetic algorithm. The stiffener spacing and plate thickness are continuous design variables that were determined by subsequent optimization. The plate deformation was classified into global and local displacement, resulting in accurate estimations of the maximum displacement. The optimization result showed that the proposed hybrid GA is effective for obtaining optimal solutions, for all the design variables.

• Journal of the Korean Statistical Society
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• v.33 no.1
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• pp.25-34
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• 2004

In this paper we propose a prediction method on the regression model with randomly censored observations of the training data set. The least squares support vector machine regression is applied for the regression function prediction by incorporating the weights assessed upon each observation in the optimization problem. Numerical examples are given to show the performance of the proposed prediction method.