• Journal of the Korean Society of Radiology
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• v.16 no.2
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• pp.131-139
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• 2022

The purpose of this study was to insert a pedicle screw into a pig thoracic vertebrae, a general CT scan(Non MAR), and a thoracic axial image obtained with the Metallic Artifact Reduction for Orthopedic Implants (O-MAR) to reduce artifacts. The image obtained by reconstructing the algorithm (Standard, Soft, Bone, Detail) was used using the image J program. Signal to noise ratio(SNR) and contrast to noise ratio(CNR) were compared and analyzed by obtaining measured values based on the given equation. And this study was to investigate tube voltage and algorithm suitable for CT scan for thoracic pedicle screw insertion. As a result, when non-MAR was used, the soft algorithm showed the highest SNR and CNR at 80, 100, 120, and 140 kVp, On the other hand, when MAR was used, the standard algorithm showed the highest at 80 kVp, and the standard and soft algorithms showed similar values at 100 kVp. At 120 kVp, the Soft and Standard algorithms showed similar values, and at 140 kVp, the Soft algorithm showed the highest SNR and CNR. Therefore, when comparing Non-MAR and MAR, even if MAR was used, SNR and CNR did not increase in all algorithms according to the change in tube voltage. In conclusion, it is judged that it is advantageous to use the Soft algorithm at 80, 100, 120, and 140 kVp in Non MAR, the Standard algorithm at 80 and 100 kVp in MAR, and the Soft algorithm at 120 and 140 kVp. This study is expected to serve as an opportunity to further improve the quality of images by using selective tube voltage and algorithms as basic data to help evaluate images of pedicle screw CT scans in the future.

• Journal of the Korean School Mathematics Society
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• v.25 no.2
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• pp.105-124
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• 2022

The contents of fraction division in textbooks are important because there were changes in situations and problem solving methods in textbooks according to the revision of the curriculum and the contents of textbooks affect students' learning directly. So, this study analyzed the achievement standards of the curriculum and formula types and situations, and the introduction process of non-standard and standard algorithms presented in Korean mathematics textbooks. The results are follows: there was little difference in the achievement standards of the curriculum, but there was a difference in the arrangement of contents by grades in textbooks. There was a difference in the types of formula according to textbooks. And the situation became more diverse; recent textbooks have changed to the direction of using the non-standard and the standard algorithm in parallel. In conclusion, I proposed categorizing rather than splitting the types of fraction division, the connection of non-standard and standard algorithm, and the need to prepare methods to pursue generalization and justification according to the common characteristics in the process of introducing standard algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.4
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• pp.233-240
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• 2022

The smart weapon system is a new weapon system of the future battlefield environment as a miniature guided weapon that performs precision strike missions through terminal phase guidance. However, it has small coverage to guide due to its low maneuverability because the smart weapon is controlled by using actuator of piezoelectric drive type due to the structural limitations. In this paper, we propose a firing data calculation algorithm under non-standard conditions to increase the effectiveness of the smart weapon. The proposed algorithm calculates firing data under non-standard conditions by calibrating firing data under standard conditions using information acquired in battlefield environments. The performance of the proposed algorithm is verified by numerical simulations under various conditions.

• Steel and Composite Structures
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• v.4 no.6
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• pp.453-469
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• 2004

In this article, a genetic algorithm based optimum design method is presented for non-linear steel frames with semi-rigid connections. The design algorithm obtains the minimum weight frame by selecting suitable sections from a standard set of steel sections such as European wide flange beams (i.e., HE sections). A genetic algorithm is employed as optimization method which utilizes reproduction, crossover and mutation operators. Displacement and stress constraints of Turkish Building Code for Steel Structures (TS 648, 1980) are imposed on the frame. The algorithm requires a large number of non-linear analyses of frames. The analyses cover both the non-linear behaviour of beam-to-column connection and $P-{\Delta}$ effects of beam-column members. The Frye and Morris polynomial model is used for modelling of semi-rigid connections. Two design examples with various type of connections are presented to demonstrate the application of the algorithm. The semi-rigid connection modelling results in more economical solutions than rigid connection modelling, but it increases frame drift.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.218-221
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• 2000

In this paper, we propose a new algorithm to detect human faces for controling a camera used in video conference. We model the distribution of skin color and set up the standard skin color in YIQ color space. An input video frame image is segmented into skin and non-skin segments by comparing the standard skin color and each pixels in the input video frame. Then, shape filler is applied to select face segments from skin segments. Our algorithm detects human faces in real time to control a camera to capture a human face with a proper size and position.

• Steel and Composite Structures
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• v.9 no.6
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• pp.535-555
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• 2009

The harmony search method based optimum design algorithm is presented for geometrically non-linear semi-rigid steel frames. Harmony search method is recently developed metaheuristic algorithm which simulates the process of producing a musical performance. The optimum design algorithm aims at obtaining minimum weight steel frames by selecting from standard set of steel sections such as European wide flange beams (HE sections). Strength constraints of Turkish Building Code for Steel Structures (TS648) specification and displacement constraints were used in the optimum design formulation. The optimum design algorithm takes into account both the geometric non-linearity of the frame members and the semi-rigid behaviour of the beam-to-column connections. The Frye-Morris polynomial model is used to calculate the moment-rotation relation of beam-to-column connections. The robustness of harmony search algorithm, in comparison with genetic algorithms, is verified with two benchmark examples. The comparisons revealed that the harmony search algorithm yielded not only minimum weight steel frames but also required less computational effort for the presented examples.

• Journal of Communications and Networks
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• v.15 no.5
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• pp.486-495
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• 2013

In this article, we suggest a two-dimensional genetic algorithm (GA) method that applies a cognitive radio (CR) decision engine which determines the optimal transmission parameters for multicarrier communication systems. Because a CR is capable of sensing the previous environmental communication information, CR decision engine plays the role of optimizing the individual transmission parameters. In order to obtain the allowable transmission power of multicarrier based CR system demands interference analysis a priori, for the sake of efficient optimization, a two-dimensionalGA structure is proposed in this paper which enhances the computational complexity. Combined with the fitness objective evaluation standard, we focus on two multi-objective optimization methods: The conventional GA applied with the multi-objective fitness approach and the non-dominated sorting GA with Pareto-optimal sorting fronts. After comparing the convergence performance of these algorithms, the transmission power of each subcarrier is proposed as non-interference emission with its optimal values in multicarrier based CR system.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.181-186
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• 2005

Many data sets obtained from surveys or medical trials often include missing observations. When these data sets are analyzed, it is general to use only complete cases. However, it is possible to have big biases or involve inefficiency. In this paper, we consider a method for estimating parameters in logistic linear models involving non-ignorable missing data mechanism. A binomial response and normal exploratory model for the missing data are used. We fit the model using the EM algorithm. The E-step is derived by Metropolis-hastings algorithm to generate a sample for missing data and Monte-carlo technique, and the M-step is by Newton-Raphson to maximize likelihood function. Asymptotic variances of the MLE's are derived and the standard error and estimates of parameters are compared.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3E
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• pp.124-132
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• 2003

We propose a new method for speech/non-speech classifiers based on concepts of the adaptive boosting (AdaBoost) algorithm in order to detect speech for robust speech recognition. The method uses a combination of simple base classifiers through the AdaBoost algorithm and a set of optimized speech features combined with spectral subtraction. The key benefits of this method are the simple implementation, low computational complexity and the avoidance of the over-fitting problem. We checked the validity of the method by comparing its performance with the speech/non-speech classifier used in a standard voice activity detector. For speech recognition purpose, additional performance improvements were achieved by the adoption of new features including speech band energies and MFCC-based spectral distortion. For the same false alarm rate, the method reduced 20-50% of miss errors.

• Journal of Communications and Networks
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• v.9 no.1
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• pp.18-27
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• 2007

The conventional normalized least mean square (NLMS) algorithm is the most widely used for adaptive identification within a non-stationary input context. The convergence of the NLMS algorithm is independent of environmental changes. However, its steady state performance is impaired during input sequences with low dynamics. In this paper, we propose a new NLMS algorithm which is, in the steady state, insensitive to the time variations of the input dynamics. The square soot (SR)-NLMS algorithm is based on a normalization of the LMS adaptive filter input by the Euclidean norm of the tap-input. The tap-input power of the SR-NLMS adaptive filter is then equal to one even during sequences with low dynamics. Therefore, the amplification of the observation noise power by the tap-input power is cancelled in the misadjustment time evolution. The harmful effect of the low dynamics input sequences, on the steady state performance of the LMS adaptive filter are then reduced. In addition, the square root normalized input is more stationary than the base input. Therefore, the robustness of LMS adaptive filter with respect to the input non stationarity is enhanced. A performance analysis of the first- and the second-order statistic behavior of the proposed SR-NLMS adaptive filter is carried out. In particular, an analytical expression of the step size ensuring stability and mean convergence is derived. In addition, the results of an experimental study demonstrating the good performance of the SR-NLMS algorithm are given. A comparison of these results with those obtained from a standard NLMS algorithm, is performed. It is shown that, within a non-stationary input context, the SR-NLMS algorithm exhibits better performance than the NLMS algorithm.