• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.2
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• pp.195-212
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• 2017

When back analysis is used for the assessment of an operating subsea tunnel safety in various measurement information such as stress, water pressure and tunnel lining and ground stiffness degradation, the reliable results within tolerable error rate can be obtained. By utilizing a commercial geotechnical analysis program FLAC3D, back analysis can be performed with a DEA which has already been successfully validated in previous studies. However, relative more time-consumption is the drawback of this approach. For this reason, this study introduced beam-spring model-based on FEM solver which uses less analysis time relatively. Beam-spring program capable of structural analysis of a circular tunnel section was developed by using Python language and combined with the built-DEA. From the measurement datum, expected to estimate the stability of an operation tunnel close to real-time.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.5
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• pp.391-395
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• 2015

A 15-Lead ECG has been developed to diagnose posterior wall diseases of the heart that a 12-Lead ECG cannot diagnose. However, 15-Lead ECG data for developing heart-diseases-detecting algorithm are limited, and previous ECG simulators cannot predict the ECG waveform according to the changes in electrode. To solve these problems, the lumped parameter model (LPM), which divides the heart into 15 sections with varying electrical capacitance and electrical resistance. To imitate the electrical conduction in the heart, each node was connected to a current source and delivered the specific current considering the positions and time delay. The purpose of this study is to acquire the waveform that can be used in an ECG by delivering the specific current to LPM.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.259-267
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• 2007

An efficient algorithm for inverting static-shifted magnetotelluric (MT) data has been proposed to produce a three-dimensional (3D) resistivity model. In the Gauss-Newton approach, computational costs associated with construction of a full sensitivity matrix usually make 3D MT inversion impractical. This computational difficulty may be overcome by using approximate sensitivities. We use four kinds of sensitivities in particular orders in the inversion process. These sensitivities are computed 1) analytically for an initial, homogeneous earth, 2) exactly for a current model, 3) approximately by the Broyden method, and 4) approximately using the previous adjoint fields. Inversion experiments with static-shifted synthetic and field MT data indicate that inversion results are highly dependent on characteristics of data and thus applying various combinations of sensitivities is helpful in obtaining a good image of the subsurface structure with reasonable computation time.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.191-201
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• 2005

In this paper, we propose a method to calculate camera motion parameter, which is based on efficient invariant features irrelevant to the camera veiwpoint. As feature information in previous research is variant to camera viewpoint. information content is increased, therefore, extraction of accurate features is difficult. LM(Levenberg-Marquardt) method for camera extrinsic parameter converges on the goat value exactly, but it has also drawback to take long time because of minimization process by small step size. Therefore, in this paper, we propose the extracting method of invariant features to camera viewpoint and two-stage calculation method of camera motion parameter which enhances accuracy and convergent degree by using camera motion parameter by 2D homography to the initial value of LM method. The proposed method are composed of features extraction stage, matching stage and calculation stage of motion parameter. In the experiments, we compare and analyse the proposed method with existing methods by using various indoor images to demonstrate the superiority of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.4
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• pp.292-301
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• 2001

IDDQ Testing is a very effective testing method to detect many kinds of physical defects occurred in CMOS VLSI circuits. In this paper, we consider the most commonly occurring bridging faults in current CMOS technologies and develop pattern generator for IDDQ testing using efficient IDDQ test algorithms. The complete set of bridging faults between every pair of all nodes(internal and external nodes) within circuit under test is assumed as target fault model. The merit of considering the complete bridging fault set is that layout information is not necessary. Implemented test pattern generator uses a new neighbor searching algorithm and fault collapsing schemes to achieve fast run time, high fault coverage, and compact test sets. Experimental results for ISCAS benchmark circuits demonstrate higher efficiency than those of previous methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.19-26
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• 2005

Image interpolation in the wavelet domain usually takes advantage of the probabilistic models for the intrascale statistics and the interscale dependency. In this paper, we adopt the linear model for the absolute values of wavelet coefficients of interpolated image across scale to estimate the variances of extrapolated bands. The proposed algorithm uses randomly generated wavelet coefficients based on the estimated parameters for probabilistic model. Random number generation according to the estimated probabilistic model may induce the 'salt and pepper' noise in subbands. We reduce the noise power by Wiener filtering. We observe that the proposed method generates the histogram of the subband coefficients similar to the that of original image. Experimental results show that our method outperforms the previous wavelet-domain interpolation method as well as the conventional bicubic method.

• Korean Business Review
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• v.15
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• pp.79-97
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• 2002

In this study, an analytical CRM for customer segmentation is exercised by integrating and analyzing the customer profile data and the access data to a particular web site. We believe that effective customer segmentation will be possible with a basis of the understanding of customer characteristics as well as behavior on the web. One of the critical tasks in the web data-mining is concerned with both 'how to collect the data from the web in an efficient manner?' and 'how to integrate the data(mostly in a variety of types) effectively for the analysis?' This study proposes a panel approach as an efficient data collection method in the web. For the customer data analysis, OLAF and a tree-structured algorithm are applied in this study. The results of the analysis with both techniques are compared, confirming the previous work which the two techniques are inter-complementary.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.243-248
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• 2013

In this paper, depth of foreground is analysed by focus and color analysis grouping for 2D/3D video conversion and depth of foreground progressing method is preposed by using focus and motion information. Candidate foreground image is generated by estimated movement of image focus information for extracting foreground from 2D video. Area of foreground is extracted by filling progress using color analysis on hole area of inner object existing candidate foreground image. Depth information is generated by analysing value of focus existing on actual frame for allocating depth at generated foreground area. Depth information is allocated by weighting motion information. Results of previous proposed algorithm is compared with proposed method from this paper for evaluating the quality of generated depth information.

• 전자공학회논문지 IE
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• v.47 no.1
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• pp.41-47
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• 2010

It is very important to prolong the lifetime of wireless sensor networks by using their limited energy efficiently, since it is not possible to change or recharge the battery of sensor nodes after deployment. LEACH protocol is a typical routing protocol based on the clustering scheme for the efficient use of limited energy. It is composed of a few clusters, which consist of head nodes and member nodes. Though LEACH starts from the supposition that all nodes have data transferred to a head, there must be some nodes having useless data in actual state. In this paper we propose a power saving scheme by making a member node dormant if previous sensed data and current data is same. We evaluate the performance of the proposed scheme in comparison with original clustering algorithms. Simulation results validate our scheme has better performance in terms of the number of alive nodes as time evolves.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.2 s.314
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• pp.1-10
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• 2007

Branch prediction accuracy is critical for the overall system performance. Branch miss-prediction penalty is the one of the significant performance limiters for improving processor performance, as the pipeline deepens and the instruction issued per cycle increases. In this paper, we propose "Dynamic Per-Branch History Length Fitting Method" by tracking the data dependencies among the register writing instructions. The proposed solution first identifies the key branches, and then it selectively uses the histories of the key branches. To support this mechanism, we provide a history length adjustment algorithm and a required hardware module. As the result of simulation, the proposed mechanism outperforms the previous fixed static method, up to 5.96% in prediction accuracy. Furthermore, our method introduces the performance improvement, compared to the profiled results which are generally considered as the optimal ones.