• Journal of KSNVE
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• v.8 no.2
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• pp.361-368
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• 1998

Complex and large lattice type structures are frequently used in design of bridge, tower, crane and aerospace structures. In general, in order to analyze these structures we have used the finite element method(FEM). This method is the most widely used and powerful tool for structural analysis. However, it is necessary to use a large amount of computer memory and computation time because the FEM resuires many degrees of freedom for solving dynamic problems exactly for these complex and large structures. For overcoming this problem, the authors developed the transfer stiffness coefficient method(TSCM). This method is based on the concept of the transfer of the nodal dynamic stiffness coefficient which is related to force and displacement vector at each node. In this paper, the authors formulate vibration analysis algorithm for a complex and large lattice type structure using the transfer of the nodal dynamic stiffness coefficient. And we confirmed the validity of TSCM through numerical computational and experimental results for a lattice type structure.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.1-8
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• 2012

Video FRUC (Frame Rate Up Conversion) has been a technique of great interest due to its diversified applications in consumer electronics. Most advanced FRUC algorithms adopt a motion interpolation technique to determine the motion vector field of interpolated frames. But, in some applications, it is necessary to evaluate how well the MCI (Motion Compensated Interpolation) frame is reconstructed. For this aim, this paper proposes a distortion estimation for motion compensated interpolation frame using frame-adaptive distortion estimation. The proposed method is applied for the symmetric motion estimation and compensated scheme and then analyzed by three different approaches, that is, forward estimation, backward estimation and adaptive bi-directional estimation schemes. Through computer simulations, it is shown that the proposed bi-directional estimation method outperforms others and can be effectively applied for FRUC.

• Journal of Biomedical Engineering Research
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• v.30 no.2
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• pp.153-161
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• 2009

Mammogram is one of the important techniques for mass detection, which is the early diagnosis stage of a breast cancer. Especially, the CAD(Computer Aided Diagnosis) using mammogram improves the working performance of radiologists as it offers an effective mass detection. There are two types of CAD systems using mammogram; automatic and semi-automatic CAD systems. However, the automatic segmentation is limited in performance due to the difficulty of obtaining an accurate segmentation since mass occurs in the dense areas of the breast tissue and has smoother boundaries. Semi-automatic CAD systems overcome these limitations, however, they also have problems including high FP (False Positive) rate and a large amount of training data required for training a classifier. The proposed system which overcomes the aforementioned problems to detect mass is composed of the suspected area selection, the level set segmentation and SVM (Support Vector Machine) classification. To assess the efficacy of the system, 60 test images from the FFDM (Full-Field Digital Mammography) are analyzed and compared with the previous semi-automatic system, which uses the ANN classifier. The experimental results of the proposed system indicate higher accuracy of detecting mass in comparison to the previous systems.

• Journal of Computing Science and Engineering
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• v.2 no.3
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• pp.301-320
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• 2008

Partial redundancy elimination (PRE) is an interesting compiler optimization because of its effectiveness and generality. Among many PRE algorithms, the one in static single assignment form (SSAPRE) has benefits over other bit-vector-based PRE algorithms. It preserves the properties of the SSA form after PRE and exploits the sparsity of the SSA form, resulting in reduced analysis and optimization time. This paper presents a practical improvement of the SSAPRE algorithm that further reduces the analysis and optimization time. The underlying idea is removing unnecessary ${\Phi}$'s during the ${\Phi}$-Insertion phase that is the first step of SSAPRE. We classify the expressions into three categories: confined expressions, local expressions, and the others. We show that unnecessary ${\Phi}$'s for confined and local expressions can be easily detected and removed. We implement our locality-based SSAPRE algorithm in a C compiler and evaluate its effectiveness with 20 applications from SPEC benchmark suites. In our measurements, on average 91 of ${\Phi}$'s identified by the original demand-driven SSAPRE algorithm are unnecessary for PRE. Pruning these unnecessary ${\Phi}$'s in the ${\Phi}$-Insertion phase makes our locality-based SSAPRE algorithm 1.8 times faster, on average, than the original SSAPRE algorithm.

• Journal of Advanced Navigation Technology
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• v.13 no.2
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• pp.296-301
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• 2009

In the self-directed learning, learner can construct learning course. But it is very difficult for learner to construct learning course with understanding the various learning contents's characteristics. This research proposed the method to support to learner the information of learning contents type to fit the learner as calculate the learner's learning preference when learner construct the learning course. The calculating method of learning preference used preference vector value of topic map. To apply this method, we tested 20 learning sampling group and presented that this method help to learner to construct learning course as getting the high average degree of learning satisfaction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1104-1109
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• 2015

Due to the rapid growth in digital contents, it is important for us to design a high speed and secure encryption algorithm which is able to comply with the existing and future needs. This paper proposes an alternative approach for self-decimated LM-128 summation sequence generator, which will generate a higher throughput if compared to the conventional generator. We design and implement a threshold clock-controlled LM-128 and prove that it has a lower clock cycle and hence giving a higher key stream generation speed. The proposed threshold clock-control LM-128 generator consists of 256 bits inner state with 128 bits secret key and initialization vector. The cipher achieves a security level of 128 bits to be adapted to the digital contents security with high definition and high quality.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.53-61
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• 2017

The preferred feature selection methods for text classification are filter-based. In a common filter-based feature selection scheme, unique scores are assigned to features; then, these features are sorted according to their scores. The last step is to add the top-N features to the feature set. In this paper, we propose an improved global feature selection scheme wherein its last step is modified to obtain a more representative feature set. The proposed method aims to improve the classification performance of global feature selection methods by creating a feature set representing all classes almost equally. For this purpose, a local feature selection method is used in the proposed method to label features according to their discriminative power on classes; these labels are used while producing the feature sets. Experimental results obtained using the well-known 20 Newsgroups and Reuters-21578 datasets with the k-nearest neighbor algorithm and a support vector machine indicate that the proposed method improves the classification performance in terms of a widely known metric ($F_1$).

• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.274-278
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• 2004

This paper presents a strategy to drive built in-type spindle induction motor which is used as CNC (Computer Numerical Control) in the industrial world. The direct vector control which is robust to the changed machine parameters in the high speed range is used in this motor control method. And electrical model of induction motor presents the basic idea based on observer structure, which is composed of voltage model and current model. But the former has the defects in low speed range, the latter has the defects of sensitivity to motor parameter. Thus Gopinath model flux estimator which is the closed loop flux observer based on two models for the rotor flut estimation is used in this paper. Moreover this paper presents to drive the spindle motor in the high speed range by using the flux weakening control.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.173-183
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• 1998

In this paper, an auto-tuning method for fuzzy controller's membership functions based on the neural network is presented. The neural network emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and the reformed fuzzy controller uses for speed control of induction motor. Thus, in the case of motor parameter variation, the proposed method is superior to a conventional method in the respect of operation time and system performance. 32bit micro-processor DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzzy control algorithm. Through computer simulation and experimental results, it is confirmed that the proposed method can provide more improved control performance than that PI controller and conventional fuzzy controller.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.988-998
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• 1999

This paper is to investigate the method of reducing the number of fuzzy rules with the help of LVQ. a large number of training patterns usually leads to a large set of fuzzy rules that require a large computer memory and take a long time to perform classification. so, in order to solve these problems, it is necessary to study to minimize the number of fuzzy rules. However, so as to minimize the performance degradation resulting from the reduction of fuzzy rules, fuzzy rules are generated after training the high-quality initial reference pattern. Through the simulation, we confirm that the proposed method is very effective.