• Journal of Welding and Joining
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• v.28 no.4
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• pp.26-32
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• 2010

The purpose of this study is to evaluate the residual stresses at the multi-pass FCA weldment using the finite element analysis (FEA). In order to do it, an H-type specimen was selected as a test specimen. The variable used was in-plane restraint intensity. The temperature distribution at the multi-pass FCA butt weldment was evaluated in accordance with the relevant guidance recommended by the KWJS. The effective conductivity for the weld metal corresponding to each welding pass was introduced to control the maximum temperature below the vaporization temperature of weld metal. The heat flux caused by welding arc was assumed to be applied to the weld metal corresponding to welding pass. With heat transfer analysis results, the distribution of transverse residual stresses was evaluated using the thermo-mechanical analysis and compared with the measured results by XRD and uniaxial strain gage. In thermo-mechanical analysis, the plastic strain resetting at the temperature above melting temperature of $1450^{\circ}C$ was considered and the weld metal and base metal was assumed to be bilinear kinematics hardening continuum. According to the comparison between FEA and experiment, transverse residual stresses at the multi-pass FCA butt weldment obtained by FEA had a good agreement with the measured results, regardless of in-plane rigidity. Based on the results, it was concluded that thermo-mechanical FE analysis based on temperature distribution calculated in accordance with the KWJS’s guidance could be used as a tool to predict the distribution of residual stress of the multi-pass FCA butt weldment.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.185-189
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• 2004

For face recognition system, a face detector which can find exact face region from complex image is needed. Many face detection algorithms have been developed under the assumption that background of the source image is quite simple . this means that face region occupy more than a quarter of the area of the source image or the background is one-colored. Color-based face detection is fast but can't be applicable to the images of which the background color is similar to face color. And the algorithm using neural network needs so many non-face data for training and doesn't guarantee general performance. In this paper, A multi-scale, multi-face detection algorithm using PCA is suggested. This algorithm can find most multi-scaled faces contained in static images with small number of training data in reasonable time.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2511-2520
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• 2018

In this study, Multi-Radial Basis Function Support Vector Machine (Multi-RBF SVM) classifier is introduced based on a composite kernel function. In the proposed multi-RBF support vector machine classifier, the input space is divided into several local subsets considered for extremely nonlinear classification tasks. Each local subset is expressed as nonlinear classification subspace and mapped into feature space by using kernel function. The composite kernel function employs the dual RBF structure. By capturing the nonlinear distribution knowledge of local subsets, the training data is mapped into higher feature space, then Multi-SVM classifier is realized by using the composite kernel function through optimization procedure similar to conventional SVM classifier. The original training data set is partitioned by using some unsupervised learning methods such as clustering methods. In this study, three types of clustering method are considered such as Affinity propagation (AP), Hard C-Mean (HCM) and Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA). Experimental results on benchmark machine learning datasets show that the proposed method improves the classification performance efficiently.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.347-347
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• 2011

Secondary ion mass spectrometry (SIMS) was fascinated by a quantitative analysis and a depth profiling and it was convinced of a in-depth analysis of multi-layer films. Precision determination of the interfaces of multi-layer films is important for conversion from the original SIMS depth profiling to the compositional depth profiling and the investigation of structure of multi-layer films. However, the determining of the interface between two kinds of species of the SIMS depth profile is distorted from original structure by the several effects due to sputtering with energetic ions. In this study, the feasibility of 50 atomic % definition for the determination of interface between two kinds of species in SIMS depth profiling of multilayer films was investigated by Si/Ge and Ti/Si multi-layer films. The original SIMS depth profiles were converted into compositional depth profiles by the relative sensitivity factors from Si-Ge and Si-Ti alloy reference films. The atomic compositions of Si-Ge and Si-Ti alloy films determined by Rutherford backscattering spectroscopy (RBS).

• Structural Engineering and Mechanics
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• v.30 no.3
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• pp.331-350
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• 2008

A framework for multi-platform analytical and multi-component hybrid (testing-analysis) simulations is described in this paper and illustrated with several application examples. The framework allows the integration of various analytical platforms and geographically distributed experimental facilities into a comprehensive pseudo-dynamic hybrid simulation. The object-oriented architecture of the framework enables easy inclusion of new analysis platforms or experimental models, and the addition of a multitude of auxiliary components, such as data acquisition and camera control. Four application examples are given, namely; (i) multi-platform analysis of a bridge with soil and structural models, (ii) multiplatform, multi-resolution analysis of a high-rise building, (iii) three-site small scale frame hybrid simulation, and (iv) three-site large scale bridge hybrid simulation. These simulations serve as illustrative examples of collaborative research among geographically distributed researchers employing different analysis platforms and testing equipment. The versatility of the framework, ease of including additional modules and the wide application potential demonstrated in the paper provide a rich research environment for structural and geotechnical engineering.

• Korean Management Science Review
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• v.31 no.3
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• pp.61-76
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• 2014

There are three methods for calculating the optimal level for spare part inventories in a MIME (Multi Indenture and Multi Echelon) system : marginal analysis, Lagrangian relaxation method, and genetic algorithm. However, their solutions are sub-optimal solutions because the MIME system is neither convex nor separable by items. To be more specific, SRUs (Shop Replaceable Units) are required to fix a defected LRU (Line Replaceable Unit) because one LRU consists of several SRUs. Therefore, the level of both SRU and LRU cannot be calculated independently. Based on the limitations of three existing methods, we proposes a improved algorithm applying marginal analysis on determining LRU stock level and genetic algorithm on determining SRU stock level. It can draw optimal combinations on LRUs through separating SRUs. More, genetic algorithm enables to extend the solution search space of a SRU which is restricted in marginal analysis applying greedy algorithm. In the numerical analysis, we compare the performance of three existing methods and the proposed algorithm. The research model guarantees better results than the existing analytical methods. More, the performance variation of the proposed method is relatively low, which means one execution is enough to get the better result.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.430-439
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• 2016

Estimation and analysis of traffic jams plays a vital role in an intelligent transportation system and advances safety in the transportation system as well as mobility and optimization of environmental impact. For these reasons, many researchers currently mainly focus on the brilliant machine learning-based prediction approaches for traffic prediction systems. This paper primarily addresses the analysis and comparison of prediction accuracy between two machine learning algorithms: Naïve Bayes and K-Nearest Neighbor (K-NN). Based on the fact that optimized estimation accuracy of these methods mainly depends on a large amount of recounted data and that they require much time to compute the same function heuristically for each action, we propose an approach that applies multi-threading to these heuristic methods. It is obvious that the greater the amount of historical data, the more processing time is necessary. For a real-time system, operational response time is vital, and the proposed system also focuses on the time complexity cost as well as computational complexity. It is experimentally confirmed that K-NN does much better than Naïve Bayes, not only in prediction accuracy but also in processing time. Multi-threading-based K-NN could compute four times faster than classical K-NN, whereas multi-threading-based Naïve Bayes could process only twice as fast as classical Bayes.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.4
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• pp.375-382
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• 2016

The mechanical property of a carbon-fiber-reinforced plastic (CFRP) is subjected to two elements, carbon fiber and polymer resin, in a first step and the selection of multi-layered structure is second one. Many combination of fabric layers, i.e. plainweave, twillweave, can be derived for candidates of test specimen used for a basic mechanical components so that a reliable identification of dynamic nature of possible multi-layered structures are essential during the development of CFRP based component system. In this paper, three kinds of multi-layered structure specimens were prepared and the dynamic characteristics of service specimens were conducted through classical modal test process with impact hammer. In addition, the design sensitivity analysis based on transmissibility function was applied for the measured response data so that the response sensitivity for each resonance frequency were compared for three CFRP test specimens. Finally, the evaluation of CFRP specimen over different multi-layered fabric structures are commented from the experimental consequences.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.5
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• pp.764-774
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• 2009

The purpose of this study is to investigate the differences in consumer clothing shopping orientation and shopping behaviors by the multi-selection of internet and offline stores. The data were collected from 201 men and women in their twenties and the respondents were grouped into three as internet-store users, multi-store users, and offline-store users. The data were analyzed using factor analysis, ANOVA, post-hoc analysis, frequency analysis, and chi-square analysis. The results are as following. First, the clothing shopping orientation was partly different among the groups. Regarding the offline shopping orientation, the groups showed difference in the impulsive orientation, and regarding the online shopping orientation, the groups showed differences in the goal oriented and enjoying orientation. In all the three cases, the internet users showed strongest orientation, and the next were multi-store users and offline-store users. The cause of these results were explained as the familiarity and experience with the channel. Second, the clothing shopping behaviors were also partly different among the groups. The groups showed no differences in the preferred store type and benefits sought, but showed significant difference in the attitude toward the internet shopping. The internet-store users showed most positive attitude, and the next were multi-store users and offline-store users.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.515-517
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• 2004

Although sustainable development of a city should in theory be based on updated spatial information like land cover/use changes, in practice there are no effective tools to get such information. However the development of satellite and sensor technologies has increased the supply of high resolution satellite data, allowing cost-effective, multi-temporal monitoring. Especially KOMPSAT-1(KOrea Multi-Purpose SATellite) acquired a large number of images of the whole Korean peninsula and covering some large cities a number of times. In this study land-use patterns and trends of Daejeon from the year 2000 to the year 2003 will be considered using land use maps which are generated by manual interpretation of multi-temporal KOMPSAT EOC imagery and to show the possibility of using high resolution satellite remote sensing data for urban analysis.