• Journal of Ocean Engineering and Technology
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• v.17 no.6
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• pp.16-22
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• 2003

In this paper, the method of determining the economically-optimal design section of rubble mound breakwater, using ADS program, was studied to supplement the deterministic approach. First of all, the design waves are computed, according to the return periods, using the Weibull distribution from the data of waves at the location of the breakwater. In order to take an optimal section, according to the return periods, the ADS program was used. The restriction conditions and objective functions are decided from the references of the specifications and standard manuals for Coastal and Harbor Construction Work. Results from this study support the ADS program as an appropriate method for determining the economically-optimal section of rubble mound breakwater, comparing the construction costs and the initial and damage repair costs for its life time.

• The Journal of the Korea institute of electronic communication sciences
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• v.3 no.2
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• pp.65-70
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• 2008

Digital signal processing (DSP) is the process of taking a signal and performing an algorithm on it to analyze, modify, or better identify that signal.[1] To take advantage of DSP advances, one must have at least a basic understanding of DSP theory along with an understanding of the hardware architecture designed to support these new advances. There are several programming techniques that maximize the efficiency of the DSP hardware, as well as a few fundamental concepts used to implement DSP software. This article introduced some of these underlying functions that are the building blocks of complex signal processing functions, and It will touch on the fundamental concepts of DSP theory and algorithms and also provide an overview of the implementation and optimization of DSP software, and discuss the development of DSP.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.4
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• pp.598-609
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• 2014

The increased use of online shopping by older consumers means that online retailers need to consider older consumers when designing websites. We investigated the specific characteristics of commercial websites (i.e., perceptual fluency) through an online experiment. Guided by perceptual fluency and affect optimization literature, hypotheses highlighting older consumers' responses to websites were proposed and tested. Results confirmed that older consumers (in their 50s) are more generous in evaluating online retailers' websites than younger consumers (in their 20s) and that responses to websites are dependent on perceptual fluency. The findings are consistent with previous research and provide additional support for theories that deal with an online apparel shopping context. Practical implications and limitations are discussed.

• Korean Management Science Review
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• v.25 no.2
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• pp.25-42
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• 2008

CDMA/TOD with asymmetric capacity allocation between uplink and downlink is a highly attractive solution to support the next generation mobile systems. This is because flexible asymmetric allocation of capacity to uplink and downlink usually improves the utilization of the limited bandwidth. In this paper, we mathematically formulate an optimal timeslot and code allocation problem, which is to maximize the total utility considering the numbers of codes(channels) allocated to each data class and the forced terminations of previously allocated codes. We also suggest a real-time integrated timeslot and code allocation scheme using Lagrangean relaxation and subgradient optimization techniques. Experimental results show that the proposed scheme provides high-quality solutions in a fast time.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.347-356
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• 2000

This paper compares four models of artificial neural networks (ANN) supported by genetic algorithms the prediction of stock price index. Previous research proposed many hybrid models of ANN and genetic algorithms(GA) in order to train the network, to select the feature subsets, and to optimize the network topologies. Most these studies, however, only used GA to improve a part of architectural factors of ANN. In this paper, GA simultaneously optimized multiple factors of ANN. Experimental results show that GA approach to simultaneous optimization for ANN (SOGANN3) outperforms the other approaches.

• Structural Engineering and Mechanics
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• v.8 no.5
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• pp.465-476
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• 1999

A structural optimization process is presented for arches with varying cross-section. The optimality criteria method is used to develop a recursive relationship for the design variables considering displacement, stresses and minimum depth constraints. The depth at the crown and at the support are taken as design variables first. Then the approach is extended by taking the depth values of each joint as design variable. The curved beam element of constant cross section is used to model the parabolic and circular arches with varying cross section. A number of design examples are presented to demonstrate the application of the method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.613-616
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• 1997

MDO(Multidisciplinary Design Optimization) methodology is an emerging new technology to solve a complicate structural analysis and design problem with a number of design variables and constraints. In this paper MDO methodology is adopted through the use of computer aided engineering(CAE) system. And this paper treats the structural design problem of RIROB(Reactor Inspection Robot) through the application of MDO methodology. In a MDO methodology application to the structural design of RIBOS, kinetodynamic analysis is done using a simple fluiddynamic analysis model for the warter flow over the sensor support surface instead of difficult fluid dynamic analysis. Simultaneously the structural static analysis is done to obtain the optimum structural condition. The minimum thickness (0.8cm) of the RIROB housing is obtained for the safe design of RIROB. The kinetodynamic analysis of RIROB. The kinetodynamic analysis of RIROB is done using ADAMS and the static structural analysis of RIROB is done using NISA.

• Computers and Concrete
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• v.19 no.5
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• pp.589-597
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• 2017

Strut-and-tie modeling method, which evolved on truss-model approach, has generally been preferred for the design of complex reinforced concrete structures and structural elements that have critical shear behavior. Some structural members having disturbed regions require exceptional detailing for all support and loading conditions, such as the beam-column connections, deep beams, short columns or corbels. Considering the general expectation of exhibiting brittle behavior, corbels are somewhat dissimilar to other shear critical structures. In this study, reinforcement layout of a corbel model was determined by the participation of structural optimization and strut-and-tie modeling methods, and an experimental comparison was performed against a conventionally designed model.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.51-58
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• 2006

In rapid prototyping, the optimal part orientation during fabrication is critical as it can improve part accuracy, minimize the requirement for supports and reduce the production time. Through investigating the geometric issues of STL model and process planning of RPM, This paper establishes optimizing model based on the considerations of staircase effect, support area and production time. The general satisfactory degree function is constructed employing the multi-objective optimization theory based on the general satisfactory degree principle. The best part-building orientation is obtained by solving the function employing generic algorithm. Experiment shows that the methods can effective resolve the part-building orientation in RP.

• Computers and Concrete
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• v.21 no.5
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• pp.505-511
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• 2018

This paper investigates the potential of a hybrid model which combines the least squares support vector machine (LSSVM) and an improved particle swarm optimization (IMPSO) techniques for prediction of concrete compressive strength. A modified PSO algorithm is employed in determining the optimal values of LSSVM parameters to improve the forecasting accuracy. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed IMPSO-LSSVM model. Further, predictions from five models (the IMPSO-LSSVM, PSO-LSSVM, genetic algorithm (GA) based LSSVM, back propagation (BP) neural network, and a statistical model) were compared with the experimental data. The results show that the proposed IMPSO-LSSVM model is a feasible and efficient tool for predicting the concrete compressive strength with high accuracy.