• Journal of Navigation and Port Research
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• v.36 no.10
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• pp.787-793
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• 2012

A hull form design technique to enhance the wave-making resistance performance for a medium size high speed Ro-Pax ship was studied introducing an optimization method and an automatic hull form modification method. SQP(sequential quadratic programming) was applied as the optimization algorithm and the geometry of hull surface was represented and modified using the NURBS(Non-Uniform Rational B-Spline). The wave-making resistance performance as an objective function in the optimization procedure was evaluated using the Rankine source panel method in which nonlinearity of the free surface boundary conditions and the trim and sinkage of the ship was fully taken into account. Using the Ro-Pax ship as a base hull, the hull-form optimization method was applied to obtain the hull shape that produced the lower wave-making resistance. To verify the validity of the hull-form optimization method, the numerical results was compared with the model test results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2373-2377
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• 2009

In this paper, the threshold voltage characteristics have been analyzed using three dimensional Poisson's equation for FinFET. The FinFET is extensively been studing since it can reduce the short channel effects as the nano device. We have presented the short channel effects such as subthreshold swing and threshold voltage for PinFET, using the analytical three dimensional Poisson's equation. We have analyzed for channel length, thickness and width to consider the structural characteristics for FinFET. Using this model, the subthreshold swing and threshold voltage have been analyzed for FinFET since the potential and transport model of this analytical three dimensional Poisson's equation is verified as comparing with those of the numerical three dimensional Poisson's equation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7B
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• pp.675-684
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• 2004

There have been several efforts to avoid unnecessary retransmission timeouts (RTOs), which is the main cause for TCP throughput degradation. Unnecessary RTOs can be classified into three groups according to their cause. RTOs due to multiple packet losses in the same window for TCP Reno, the most prevalent TCP version, can be avoided by TCP NewReno or using selective acknowledgement (SACK) option. RTOs occurring when a packet is lost in a window that is not large enough to trigger fast retransmit can be avoided by using the Limited Transmit algorithm. In this Paper, we comparatively analyze these schemes to cope with unnecessary RTOs by numerical analysis and simulations. On the basis of the results in this paper, TCP performance can be quantitatively predicted from the aspect of loss recovery probability. Considering that overall performance of TCP is largely dependent upon the loss recovery performance, the results shown in this paper are of great importance.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.271-278
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• 2011

Storm and flood such as torrential rains and major typhoons has often caused damages on a large scale in Korea and damages from storm and flood have been increasing by climate change and warming. Therefore, it is an essential work to maneuver preemptively against risks and damages from storm and flood by predicting the possibility and scale of the disaster. Generally the research on numerical model based on statistical methods, the KDF model of TCDIS developed by NIDP, for analyzing and predicting disaster risks and damages has been mainstreamed. In this paper, we introduced the model for prediction of damage cost from storm and flood by the neural network algorithm which outstandingly implements the pattern recognition. Also, we compared the performance of the neural network model with that of KDF model of TCDIS. We come to the conclusion that the robustness and accuracy of prediction of damage cost on TCDIS will increase by adapting the neural network model rather than the KDF model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.61-68
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• 2019

Currently many companies are interested in reduction of the carbon emissions associated with their supply chain activities such as transportation and operations. Operational decisions, such as modifications in order quantities could an effective way in reducing carbon emissions in the supply chain. Cap-and-trade regulation, sometimes called emissions trading, is a market-based tool to limit greenhouse gas emissions. Under cap-and-trade regulation, emission credits are allocated to the firms and the firms trades emissions under cap-and-trade schemes. In this paper, we propose a single-manufacturer single-buyer two-echelon supply chain problem under the cap-and-trade mechanism incorporating the carbon emissions caused by transportation and warehousing activities where a single manufacturer produces a family of items in order to deliver a family of items to a single buyer at a fixed interval of time for effective implementation of Just-In-Time (JIT) Purchasing. An integrated multi-product lot-splitting model of facilitating multiple shipments in small lots between buyer and manufacturer is developed in a JIT Purchasing environment. Also, an iterative heuristic algorithm is developed to derive the common order interval, the number of intervals for each product and the number of shipments between the buyer and the manufacturer during the common interval. A numerical example is given to illustrate the savings in reduction of total cost and carbon emissions by the inventory model incorporating cap-and-trade mechanism compared to the classical inventory model. The proposed inventory model could be useful for the practical solution of two-echelon supply chain inventory problem under cap-and-trade mechanism.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.11
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• pp.979-987
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• 2012

This paper implements and integrates algorithms for terrain following of UCAVs (Unmanned Combat Aerial Vehicles): trajectory generation, guidance, and navigation. Terrain following is very important for UCAVs because they perform very dangerous missions such as Suppression of Enemy Air Defences while the terrain following can improve the survivability of UCAVs against from the air defence systems of the enemy. To deal with the GPS jamming, terrain referenced navigation based on nonlinear filter is chosen. For the trajectory generation, Voronoi diagram is adopted to generate horizontal plane path to avoid the air defense system. Cubic spline method is used to generate vertical plane path to prevent collisions with ground while flying sufficiently close to surface. Follow-the-Carrot and pure pursuit tracking methods, which are look-ahead point based guidance algorithms, are applied for the guidance. Numerical simulation is performed to verify the performance of the integrated terrain following algorithm.

• Wind and Structures
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• v.18 no.6
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• pp.693-715
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• 2014

Stochastic processes are used to represent phenomena in many diverse fields. Numerical simulation method is widely applied for the solution to stochastic problems of complex structures when alternative analytical methods are not applicable. In some practical applications the stochastic processes show non-Gaussian properties. When the stochastic processes deviate significantly from Gaussian, techniques for their accurate simulation must be available. The various existing simulation methods of non-Gaussian stochastic processes generally can only simulate super-Gaussian stochastic processes with the high-peak characteristics. And these methodologies are usually complicated and time consuming, not sufficiently intuitive. By revealing the inherent coupling effect of the phase and amplitude part of discrete Fourier representation of random time series on the non-Gaussian features (such as skewness and kurtosis) through theoretical analysis and simulation experiments, this paper presents a novel approach for the simulation of non-Gaussian stochastic processes with the prescribed amplitude probability density function (PDF) and power spectral density (PSD) by amplitude modulation and phase reconstruction. As compared to previous spectral representation method using phase modulation to obtain a non-Gaussian amplitude distribution, this non-Gaussian phase reconstruction strategy is more straightforward and efficient, capable of simulating both super-Gaussian and sub-Gaussian stochastic processes. Another attractive feature of the method is that the whole process can be implemented efficiently using the Fast Fourier Transform. Cases studies demonstrate the efficiency and accuracy of the proposed algorithm.

• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.2
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• pp.1-13
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• 2010

This paper proposes an optimal design method for the nonlinear seismic isolated bridge. The probabilities of failure at the pier and the seismic isolator are considered as objective functions for optimal design, and a multi-objective optimization technique is employed to efficiently explore a set of multiple solutions optimizing mutually-conflicting objective functions at the same time. In addition, a stochastic linearization method is incorporated into the multi-objective optimization framework in order to effectively estimate the stochastic responses of the bridge without performing numerous nonlinear time history analyses during the optimization process. As a numerical example to demonstrate the efficiency of the proposed method, the Nam-Han river bridge is taken into account, and the proposed method and the existing life-cycle-cost based design method are both applied for the purpose of comparing their seismic performances. The comparative results demonstrate that the proposed method not only shows better seismic performance but also is more economical than the existing cost-based design method. The proposed method is also proven to guarantee improved performance under variations in seismic intensity, in bandwidth and in the predominant frequency of the seismic event.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.2 s.72
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• pp.125-138
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• 2006

The use of system identification approaches for damage detection has been expanded in recent years owing to the advancements in data acquisition system andinformation processing techniques. Soft computing techniques such as neural networks and genetic algorithm have been utilized increasingly for this end due to their excellent pattern recognition capability. In this study, damage detection of bridge structures using neural networks technique based on the modal properties is presented, which can effectively consider the modeling uncertainty in the analysis model from which the training patterns are to be generated. The differences or the ratios of the mode shape components between before and after damage are used as the input to the neural networks in this method, since they are found to be less sensitive to the modeling errors than the mode shapes themselves. Two numerical example analyses on a simple beam and a multi-girder bridge are presented to demonstrate the effectiveness and applicability of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2058-2074
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• 2017

Dense Heterogeneous Cellular Networks(HCNs) offer a promising approach to meet the target of 1000x increase in aggregate data rates in 5G wireless communication systems. However how to best utilize the available radio resources at densely deployed small cells remains an open problem as those small cells are typically unplanned. In this paper we focus on balancing loads across macro cells and small cells by offloading users to small cells, as well as dynamically switching off underutilized small cells. We propose a joint user association and base station(BS) sleep mangement(UA-BSM) scheme that proactively offloads users to a fraction of the densely deployed small cells. We propose a heuristic algorithm that iteratively solves the user association problem and puts BSs with low loads into sleep. An interference relation matrix(IRM) is constructed to help us identify the candidate BSs that can be put into sleep. User associations are then aggregated to selected small cells that remain active. Simulation results show that our proposed approach achieves load balancing across macro and small cells and reduces the number of active BSs. Numerical results show user signal to interference ratio(SINR) can be improved by small cell sleep control.