• Journal of computational fluids engineering
• /
• v.20 no.4
• /
• pp.21-27
• /
• 2015

Flow field around the KRISO 3600TEU container ship is computed using a surface generated based on interpolations of station lines, which are given in a body plan of the ship, without using any CAD program. An interpolation method is suggested based on inscribed circles to generate curves between two neighboring station lines. The interpolated surface is saved in a STL format to use the snappyHexMesh utility of the openfoam. Computed resistance of the ship is compared with experimental and other computational results and the effects of the interpolation of neighboring station lines on the computed resistance are investigated. The suggested method is applied to calculate the flow field around a submarine with appendages. The surface triangulations for the hull and the appendages are generated without consideration of each other, then those surface triangulations are simply combined to provide a grid generator with the body boundary. The junctures of the hull and the appendages are identified automatically during the grid generation procedure. Tip vortex is captured, which travels downstream from the tip of the appendages.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.29 no.8 s.239
• /
• pp.1102-1108
• /
• 2005

The integrity of nuclear piping systems has to be maintained sufficiently all the times during operation. In order to maintain the integrity, reliable assessment procedures including fracture mechanics analysis, etc, are required. Up to now, the integrity assessment has been performed using conventional deterministic approach even though there are lots of uncertainties to hinder a rational evaluation. In this respect, probabilistic approach is considered as an appropriate method for piping system evaluation. The objectives of this paper are to develop a probabilistic assessment program using reliability index and simulation technique and to estimate the damage probability of wall-thinned pipes in secondary systems. The probabilistic assessment program consists of three evaluation modules which are first order reliability method, second order reliability method and Monte Carlo simulation method. The developed program has been applied to evaluate damage probabilities of wall-thinned pipes subjected to internal pressure, global bending moment and combined loading. The sensitivity analysis results as well as prototypal evaluation results showed a promising applicability of the probabilistic integrity assessment program.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.1
• /
• pp.94-100
• /
• 2010

Data Mining is mainly used for pattern extracting and information discovery from collected data. However previous methods is difficult to reflect changing patterns with time. In this paper, we introduce Streaming Decision Tree(SDT) analyzing data with continuity, large scale, and changed patterns. SDT defines continuity data as blocks and extracts rules using a Decision Tree's learning method. The extracted rules are combined considering time of occurrence, frequency, and contradiction. In experiment, we applied time series data and confirmed resonable result.

• The Journal of Information Systems
• /
• v.24 no.4
• /
• pp.99-116
• /
• 2015

Purpose One of the main characteristics of Social Network Service(SNS) is that users in an open space makes posts through voluntary participation and sharing among them. This makes SNS a very attractive channel to companies that need to send their messages to consumers. As a matter of fact, there are many companies doing marketing activities through a platform of Fan Page as a space for corporations and consumers to act together. This study defines the values and types of companies' advertising posts on Facebook, empirically analyzes the results of them, and investigates factors that could enhance the customer engagement. Design/methodology/approach A research model was built to demonstrate which values and types of posts were combined by corporations' posts on Facebook and create their messages and which of those combinations would lead to high results of customer engagement. Findings The results show differences in the values of posts between the group of high customer engagement and the other group on Facebook. This study makes its contribution by conducting elaborate analysis of posts on Facebook and thus proposing marketing strategies that companies, which had difficulties with systematic marketing activities due to cost limitations, could use on Facebook.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.8A
• /
• pp.612-617
• /
• 2012

Two phase control (PC) schemes using limited feedback are proposed for multiple-input single-output (MISO) systems. One PC scheme cophases channel gains with respect to the first transmit antenna channel gain, and the other PC scheme cophases channel gains by positioning all the channel gains into a fixed sector. We analyze the combined channel gain for both PC schemes, and find that the PC scheme that cophases with respect to the first transmit antenna channel gain provides 1.2 dB power gain over an orthogonal space-time block code (OSTBC) when the number of transmit antennas is four and the number of feedback bits is three.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.7
• /
• pp.852-857
• /
• 2005

This paper discusses a human body extraction method for intelligent robot system. The intelligent robot system requires more robust silhouette extraction method because it has internal vibration and low resolution. The new hybrid silhouette extraction method is proposed to overcome this constrained environment. The temporal and gradient information is combined as hybrid silhouette. The motion region model is used to adjust combining parameters in hybrid silhouette. Finally, the experimental results show the superiority of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.3
• /
• pp.167-173
• /
• 2002

In this paper, we propose an interactive genetic algorithm (IGA) to implement an automated 2D avatar synthesis. The IGA technique is capable of expressing user's personality in the avatar synthesis by using the user's response as a candidate for the fitness value. Our suggested IGA method is applied to creating avatars automatically. Unlike the previous works, we introduce the concepts of 'hidden population', as well as 'primitive avatar' and 'simplified genotype', which are used to overcome the shortcomings of IGA such as human fatigue or reliability, and reasonable rates of convergence with a less number of iterations. The procedure of designing avatar models consists of two steps. The first step is to detect the facial feature points and the second step is to create the subjectively optimal avatars with diversity by embedding user's preference, intuition, emotion, psychological aspects, or a more general term, KANSEI. Finally, the combined processes result in human-friendly avatars in terms of both genetic optimality and interactive GUI with reliability.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.4
• /
• pp.430-435
• /
• 2011

In this paper, a navigation technology of an unmanned vehicle using relative localization and magnetic guidance is proposed. Magnetic guidance system had been developed as a robust autonomous driving technology as long as magnetic fields on the path are detected. Otherwise, if magnetic fields were not detected due to some reasons, the vehicle could not drive. Therefore, in order to overcome the drawback, we propose that relative localization would be combined to magnetic guidance system. To validate the usefulness of the proposed method, a robotic vehicle was set up with the magnetic guidance system and the relative localization. In addition, the unmanned driving test was realized on the road without the magnetic fields so that the proposed method is verified by the experiment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.10
• /
• pp.1044-1049
• /
• 2006

Multiple sequence alignment is a method to compare two or more DNA or protein sequences. Most of multiple sequence alignment tools rely on pairwise alignment and Smith-Waterman algorithm to generate an alignment hierarchy. Therefore, in the existing multiple alignment method as the number of sequences increases, the runtime increases exponentially. In order to remedy this problem, we adopted a parallel processing suffix tree algorithm that is able to search for common subsequences at one time without pairwise alignment. Also, the cross-matching subsequences triggering inexact-matching among the searched common subsequences might be produced. So, the cross-matching masking process was suggested in this paper. To identify the function of the clusters generated by suffix tree clustering, BLAST and CDD (Conserved Domain Database)search were combined with a clustering tool. Our clustering and annotating tool consists of constructing suffix tree, overlapping common subsequences, clustering gene sequences and annotating gene clusters by BLAST and CDD search. The system was successfully evaluated with 36 gene sequences in the pentose phosphate pathway, clustering 10 clusters, finding out representative common subsequences, and finally identifying functional domains by searching CDD database.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.372-372
• /
• 2000

In this paper, we propose Neuro Fuzzy Polynomial Networks(NFPN) based on Polynomial Neural Network(PNN) and Neuro-Fuzzy(NF) for model identification of complex and nonlinear systems. The proposed NFPN is generated from the mutually combined structure of both NF and PNN. The one and the other are considered as the premise part and consequence part of NFPN structure respectively. As the premise part of NFPN, NF uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. As the consequence part of NFPN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. NFPN is available effectively for multi-input variables and high-order polynomial according to the combination of NF with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. In order to evaluate the performance of proposed models, we use the nonlinear function. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously.