• Journal of Mechanical Science and Technology
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• v.15 no.8
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• pp.1090-1096
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• 2001

In this paper, new methods for efficiently solving linear acceleration equations of multibody dynamic simulation exploiting sparsity for real-time simulation are presented. The coefficient matrix of the equations tends to have a large number of zero entries according to the relative joint coordinate numbering. By adequate joint coordinate numbering, the matrix has minimum off-diagonal terms and a block pattern of non-zero entries and can be solved efficiently. The proposed methods, using sparse Cholesky method and recursive block mass matrix method, take advantages of both the special structure and the sparsity of the coefficient matrix to reduce computation time. The first method solves the η$\times$η sparse coefficient matrix for the accelerations, where η denotes the number of relative coordinates. In the second method, for vehicle dynamic simulation, simple manipulations bring the original problem of dimension η$\times$η to an equivalent problem of dimension 6$\times$6 to be solved for the accelerations of a vehicle chassis. For vehicle dynamic simulation, the proposed solution methods are proved to be more efficient than the classical approaches using reduced Lagrangian multiplier method. With the methods computation time for real-time vehicle dynamic simulation can be reduced up to 14 per cent compared to the classical approach.

• Journal of the Korean Society for information Management
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• v.18 no.2
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• pp.105-124
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• 2001

The purpose of this study is to develop a Korean word analysis system, which can improve performance of IRS, based on various methods of word analysis. In this study we focused on maximizing the speed of Korean word analysis, modulizing each functional system and analyzing Korean morpheme precisely. The system, developed in this study, implemented optimal algorithm to increase the speed of word analysis and to verify speed and performance of each subsystem. In addition, the numeral analysis processing was achieved to reduce a system burden by avoiding recursive analysis of compound nouns, based on numeral pattern recognition.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.601-614
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• 2012

Since the optimized use of sonar systems available for detection is a very practical problem for a given ocean environment, the measure of mission achievability is needed for operating the sonar system efficiently. In this paper, a theory on Measure Of Effectiveness(MOE) for specific mission such as detection is described as the measure of mission achievability, and a recursive Cumulative Detection Probability(CDP) algorithm is found to be most efficient from comparing three CDP algorithms for discrete glimpses search to reduce computation time and memory for complicated scenarios. The three CDPs which are MOE for sonar-maneuver pattern are calculated as time evolves for comparison, based on three different formula depending on the assumptions as follows; dependent or independent glimpses, unimodal or non-unimodal distribution of Probability of Detection(PD) as a function of observation time interval for detection. The proposed CDP algorithm which is made from unimodal formula is verified and applied to OASPP(Optimal Acoustic Search Path Planning) with complicated scenarios.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.2058-2065
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• 2010

This paper presents the sensor location and step estimation algorithm for personal navigation system (PNS). PNS has the disadvantage in that the position of the sensor must be fixed on a human body. Three-axis acceleration sensor is used to solve the disadvantage and to consider the real situation. We simplify the measurement data by using the band pass filter, witch It has the advantage in the detection of characteristic point. Through the detected characteristic points, it is possible to setup the parameter for the pattern detection. Depending on the sensor location, the parameters have the different type of noise covariance. Particularly, when the position of the sensor is changed, the impulse noise shows up. Considering the noise, we apply the recursive least square algorithm using the variable forgetting factors, which can classify the sensor location based on the estimated parameters. We performed the experiment for the verification of the proposed algorithm in the various environments. Through the experimental results, the effectiveness of the proposed method is verified.

• Korean Journal of Applied Biomechanics
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• v.17 no.4
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• pp.149-156
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• 2007

The purpose of this study was to compare the world class women's hurdlers with kinematic variables Lee Yeon-Kyoung's in the 100m hurdle. Among korea elite female hurdler, Lee Yeon-Kyoung was participated as a subject. Eight JVC video cameras(GR-HD1KR) were used to film the performance of Lee Yeon-Kyoung at a frame rate of 60fields/s. The real-life three-dimensional coordinate data of digitized body landmarks were smoothed using a fourth order Butterworth low pass recursive digital filter with an estimated optimum cutoff frequency of 7.4Hz. After analyzing and comparing Lee Yeon Kyung's kinematic variables with the world top class hurdlers in the woman's 100m hurdle run, the following conclusions were obtained. 1. Lee should be able to increase the speed with over 5.4m/s from start to first hurdle and then maintain the speed range from 8.33m/s to 8.67m/s until 10th hurdle. Lee should have to maintain the speed with 8.51m/s from 10th hurdle to finish line. 2. Lee has to reach her maximum running speed at 5th hurdle and then has to shorten running time with 0.5sec between hurdles. 3. Lee should be able to run around 2.5sec from start to frist hurdle and then maintain under 1.00sec following phases. Lee should be able to maintain under 1.10sec from 10th hurdle to finish line. 4. Lee needs to control a consistent takeoff and landing distance pattern, Lee needs to lower the height of the center of gravity of the body with 0.33m when she clears the hurdles.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.2
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• pp.55-64
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• 1990

This paper concerned about a study on the direct pole placement PID self-tuning controller design for DC servo motor control system. The method of a direct pole placement self-tuning PID control for a DC servo motor of Robot manipulator tracks a reference velocity in spite of the parameters uncertainties in nonminimum phase system. In this scheme, the parameters of classical controller are estimated by the recursive least square (RLS)identification algorithm, the pole placement method and diophantine equation. A series of simulation in which minimum phase system and nonminimum phase system are subjected to a pattern of system parameter changes is presented to show some of the features of the proposed control algorithm. The proposed control algorithm which shown are effective for the practical application, and experiments of DC servo motor speed control for Robot manipulator by a microcomputer IBM-PC/AT are performed and the results are well suited.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.155-162
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• 2008

Biological sequences such as DNA sequences and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological dataset with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with the fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. As the result, the experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

• Journal of Korean Neurosurgical Society
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• v.60 no.1
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• pp.21-29
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• 2017

Objective : The purpose of this study was to analyze outcomes and identify prognostic factors in patients with cerebral metastases from non-small cell lung cancer (NSCLC) treated with gamma knife radiosurgery (GKS) particularly, focusing on associations of biomarkers and systemic treatments. Methods : We retrospectively reviewed the medical records of 134 patients who underwent GKS for brain metastases due to NSCLC between January 2002 and December 2012. Representative biomarkers including epidermal growth factor receptor (EGFR) mutation, K-ras mutation, and anaplastic lymphoma kinase (ALK) mutation status were investigated. Results : The median overall survival after GKS was 22.0 months (95% confidence interval [CI], 8.8-35.1 months). During follow-up, 63 patients underwent salvage treatment after GKS. The median salvage treatment-free survival was 7.9 months (95% CI, 5.2-10.6 months). Multivariate analysis revealed that lower recursive partition analysis (RPA) class, small number of brain lesions, EGFR mutation (+), and ALK mutation (+) were independent positive prognostic factors associated with longer overall survival. Patients who received target agents 30 days after GKS experienced significant improvements in overall survival and salvage treatment-free survival than patients who never received target agents and patients who received target agents before GKS or within 30 days (median overall survival: 5.0 months vs. 18.2 months, and 48.0 months with p-value=0.026; median salvage treatment-free survival: 4.3 months vs. 6.1 months and 16.6 months with p-value=0.006, respectively). To assess the influence of target agents on the pattern of progression, cases that showed local recurrence and new lesion formation were analyzed according to target agents, but no significant effects were identified. Conclusion : The prognosis of patients with brain metastases of NSCLC after GKS significantly differed according to specific biomarkers (EGFR and ALK mutations). Our results show that target agents combined with GKS was related to significantly longer overall survival, and salvage treatment-free survival. However, target agents were not specifically associated with improved local control of the lesion treated by GKS either development of new lesions. Therefore, it seems that currently popular target agents do not affect brain lesions themselves, and can prolong survival by controlling systemic disease status.