• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.135-139
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• 2012

The wide diffusion of internet and the overall increased reliance on technology for information communication, dissemination and gathering have created an unparalleled mass of data. Sifting through this data is defining and will define in the foreseeable future a big part of contemporary computer science. Within this data, a growing proportion is given by personal information, which represents a unique opportunity to study human activities extensively and live. One important recurring challenge in many disciplines is the problem of people re-identification. In its broadest definition, re-identification is the problem of newly recognizing previously identified people, such as following an unknown person while he walks through many different surveillance cameras in different locations. Our goals is to review how several diverse disciplines define and meet this challenge, from person re-identification in video-surveillance to authorship attribution in text samples to distinguishing users based on their preferences of pictures. We further envision a situation where multidisciplinary solutions might be beneficial.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.2
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• pp.1-10
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• 2002

Hull-propeller-rudder interactions are studied by the iterative computational procedures. Hull effects on the propeller are reflected through the effective velocities computed by the vortex ring method which used the measured nominal wake as input data. A potential based panel method has been developed to solve the propeller-rudder interactions using the obtained effective velocities. Steady flow characteristics around the rudder surface can be obtained by computing the induced velocities on the rudder by the propeller and vice versa are computed by the iterative manner until the converged solutions are obtained. Flow characteristics around the propeller and the rudder are measured by Laser Doppler Velocimetry(L.D.V.) in large cavitation tunnel at Samsung Heavy industries. The gap flow model is adopted to solve the characteristics of the horn rudder. Numerical results are compared with the experimental values and the computed velocity fields and pressure distributions with rudder angle on the horn rudder surface show good agreement with measured ones in large cavitation tunnel.

• The Journal of Natural Sciences
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• v.15 no.1
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• pp.11-34
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• 2005

It is no exaggeration to say that the productivity of a research using computer simulations on complex molecular systems like biomolecules depends on the ability of the sampling algorithm to explore the relevant parts of configuration space. In this study, we investigate the properties on the mutiensemble sampling (MES) which is one of the solutions that surmount limitations of conventional sampling algorithms. Works for finding out practical systematic ways of using the MES efficiently to explore distantly separated regions in configuration space are performed. In this work, the more generalized form of weighting function for MES is used and 'cavity formation in water' is simulated using Monte Carlo. investigating the correlation of simulation parameters and the efficiency of the method, we propose a practical way of maximizing the power of the MES. We applied the way to 'cavity formation in water' and were able to explore the parts of configuration space relevant to cavities of radius from 0 to 5.6A in a single simulation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.28-36
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• 2016

Recently, owing to the development of ICT industry and wide spread of smart phone, the number of people who use car sharing service are increased rapidly. Currently two-way car sharing system with same rental and return locations are mainly operated since this system can be easily implemented and maintained. Currently the demand of one-way car sharing service has increase explosively. But this system have several obstacle in operation, especially, vehicle stock imbalance issues which invoke vehicle relocation. Hence in this study, we present an optimization approach to depot location and relocation policy in one-way car sharing systems. At first, we modelled as mixed-integer programming models whose objective is to maximize the profits of a car sharing organization considering all the revenues and costs involved and several constraints of relocation policy. And to solve this problem efficiently, we proposed a new method based on particle swarm optimization, which is one of powerful meta-heuristic method. The practical usefulness of the approach is illustrated with a case study involving satellite cities in Seoul Metrolitan Area including several candidate area where this kind systems have not been installed yet and already operating area. Our proposed approach produced plausible solutions with rapid computational time and a little deviation from optimal solution obtained by CPLEX Optimizer. Also we can find that particle swarm optimization method can be used as efficient method with various constraints. Hence based on this results, we can grasp a clear insight into the impact of depot location and relocation policy schemes on the profitability of such systems.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.2
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• pp.189-197
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• 2013

With the trend of technological advances in electronic communications and the advent of ubiquitous environments, the density of existing electronic equipment in the surroundings is increasing significantly. It is hence great importance to study the numerically efficient and fast algorithm for complex and large environments to identify their electromagnetic compatibility and interference characteristics of equipments installed in those structure. This paper introduces a statistical-based power balance method(PWB) for the analysis of these problems and considers its practical utility. The 2-dimensional lossy rectangular cavity was numerically revisited to clarify its relationship with the classical deterministic analysis solutions based on the Maxwell's equation. It can be shown that the statistical assumptions and analysis results from the power balance method correspond to the volume average over the realistic deterministic domain. This statistical power balance approach should be a sufficiently practical alternative to the electromagnetic problem of complex and large environment since it is apparent that the full-wave analysis methods have some severe limits of its computational burdens under the situation of complex and large environment.

• Computers and Concrete
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• v.19 no.4
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• pp.365-374
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• 2017

With the continuous evolution of the numerical methods and the availability of advanced constitutive models, it became a common practice to use complex physical and geometrical nonlinear numerical analyses to estimate the structural behavior of reinforced concrete elements. Such simulations may yield the complete time history of the structural behavior, from the first moment the load is applied until the total collapse of the structure. However, the evolution of the cracking pattern in geometrical discontinuous zones of reinforced concrete elements and the associated failure modes are relatively complex phenomena and their numerical simulation is considerably challenging. The objective of the present paper is to assess the applicability of the Applied Element Method in simulating the development of distinct failure modes in reinforced concrete walls subjected to monotonic loading obtained in experimental tests. A pushover test was simulated numerically on three distinct RC shear walls, all presenting an opening that guarantee a geometrical discontinuity zone and, consequently, a relatively complex cracking pattern. The presence of different reinforcement solutions in each wall enables the assessment of the reliability of the computational model for distinct failure modes. Comparison with available experimental tests allows concluding on the advantages and the limitations of the Applied Element Method when used to estimate the behavior of reinforced concrete elements subjected to monotonic loading.

• Geomechanics and Engineering
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• v.22 no.4
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• pp.361-374
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• 2020

This paper is concerned with the thermoelastic bending of FG beams resting on two-layer elastic foundations. One of these layers is Winkler springs with a variable modulus while the other is considered as a shear layer with a constant modulus. The beams are considered simply supported and subjected to thermo-mechanical loading. Temperature-dependent material properties are considered for the FG beams, which are assumed to be graded continuously across the panel thickness. The used theories contain undetermined integral terms which lead to a reduction of unknowns functions. Several micromechanical models are used to estimate the effective two-phase FG material properties as a function of the particles' volume fraction considering thermal effects. Analytical solutions for the thermo-mechanical bending analysis are obtained based on Navier's method that satisfies the boundary conditions. Finally, the numerical results are provided to reveal the effect of explicit micromechanical models, geometric parameters, temperature distribution and elastic foundation parameters on the thermoelastic response of FG beams.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.9 s.240
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• pp.1217-1224
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• 2005

To improve the accuracy of a metamodel, additional sample points can be selected by using a specified criterion, which is often called sequential sampling approach. Sequential sampling approach requires small computational cost compared to one-stage optimal sampling. It is also capable of monitoring the process of metamodeling by means of identifying an important design region for approximation and further refining the fidelity in the region. However, the existing critertia such as mean squared error, entropy and maximin distance essentially depend on the distance between previous selected sample points. Therefore, although sufficient sample points are selected, these sequential sampling strategies cannot guarantee the accuracy of metamodel in the nearby optimum points. This is because criteria of the existing sequential sampling approaches are inefficient to approximate extremum and inflection points of original model. In this research, new sequential sampling approach using the sensitivity of metamodel is proposed to reflect the response. Various functions that can represent a variety of features of engineering problems are used to validate the sensitivity approach. In addition to both root mean squared error and maximum error, the error of metamodel at optimum points is tested to access the superiority of the proposed approach. That is, optimum solutions to minimization of metamodel obtained from the proposed approach are compared with those of true functions. For comparison, both mean squared error approach and maximin distance approach are also examined.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.41-48
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• 2011

In feature selection, the selective evaluation scheme for Ant Colony Optimization(ACO) has recently been proposed, which reduces computational load by excluding unnecessary or less promising candidate solutions from the actual evaluation. Its superiority was supported by experimental results. However the experiment seems to be not statistically sufficient since it used only one dataset. The aim of this paper is to analyze convergence characteristics of the selective evaluation scheme and to make the conclusion more convincing. We chose three datasets related to handwriting, medical, and speech domains from UCI repository whose feature set size ranges from 256 to 617. For each of them, we executed 12 independent runs in order to obtain statistically stable data. Each run was given 72 hours to observe the long-time convergence. Based on analysis of experimental data, we describe a reason for the superiority and where the scheme can be applied.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1106-1110
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• 2010

This paper proposes a method of optimizing a stacking strategy for an automated container terminal using multi-objective evolutionary algorithms (MOEAs). Since the yard productivities of seaside and landside are conflicting objectives to be optimized, it is impossible to maximize them simultaneously. Therefore, we derive a Pareto optimal set instead of a single best solution using an MOEA. Preliminary experiments showed that the population is frequently stuck in local optima because of the difficulty of the given problem depending on the yard occupancy rate. To cope with this problem, we propose another method of simultaneously optimizing two problems with different difficulties so that diverse solutions can be preserved in the population. Experimental results showed the proposed method can derive better stacking policies than the compared method solving a single problem given the same computational costs.