• 한국방사선학회논문지
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• 제16권2호
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• pp.131-139
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• 2022

본 연구는 척추경 나사못(Pedicle screw)을 돼지 흉추에 삽입하여 일반적인 CT검사(Non MAR)와 인공물을 줄이기 위한 금속성 인공물 감소기법(Metallic Artifact Reduction for Orthopedic Implants, O-MAR)으로 얻어진 흉추 Axial영상을 4개의 알고리즘(Standard, Soft, Bone, Detail)에 재구성하였다. 이에 얻은 영상을 image J 프로그램을 이용하여 신호대잡음비(Signal Noise Ratio, SNR)와 대조도대잡음비(Contrast to Noise Ratio, CNR)를 주어진 식에 의거하여 측정값을 구하고 흉추 척추경 나사못 삽입술 CT검사에 맞는 관전압과 알고리즘을 알아보고자 하였다. 결과적으로 Non MAR 사용한 경우에는 80, 100, 120, 140 kVp에서 soft 알고리즘이 SNR, CNR이 가장 높게 나타났다. 반면에 MAR를 사용한 경우 80 kVp에서는 Standard 알고리즘이 가장 높게 나타났고 100 kVp에서는 Standard, Soft 알고리즘이 비슷한 값으로 높게 나타났다. 120 kVp에서는 Soft, Standard 알고리즘이 비슷한 값으로 나타났고 140 kVp에서는 Soft 알고리즘에서 SNR, CNR이 가장 높게 나타났다. 따라서 Non MAR와 MAR를 비교했을 경우 MAR를 사용한다고 하더라도 관전압 변화에 따라 모든 알고리즘에서 SNR과 CNR이 증가하는 것은 아니었다. 본 연구는 이후 척추경 나사못 CT검사 영상 평가에 도움이 되는 기초자료로써 선택적인 관전압과 알고리즘 사용으로 영상의 질을 더 높일 수 있는 계기가 될 것으로 사료된다.

• 한국학교수학회논문집
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• 제25권2호
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• pp.105-124
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• 2022

분수 나눗셈은 교육과정에 따른 교과서마다 문제 상황이나 해결 방법에서 변화가 있었고, 교과서 내용은 학생들의 학습에 직접 영향을 주기 때문에 중요하다. 본 연구에서는 우리나라의 최근 3개 교육과정과 그에 따른 교과서에 제시된 분수 나눗셈의 교육과정 성취기준, 수식 유형 및 문제 상황, 비표준 및 표준 알고리즘의 도입 과정을 분석하였다. 분석 결과, 교육과정 성취기준의 차이는 거의 없었으나, 교과서의 학년별 내용 제시에 변화가 있었다. 수식 유형에서는 교육과정별 교과서마다 차이가 있었고, 문제 상황은 다양해지는 변화가 나타났다. 해결 방법은 표준 알고리즘을 강조한 것에서 최근 교과서에서 비표준 알고리즘과 표준 알고리즘을 병행하는 방향으로 변화하였다. 제언으로 나눗셈 유형별로 내용을 세분화하기보다는 문제 상황별로 유목화할 수 있는 방안과 비표준 알고리즘과 표준 알고리즘의 연계 및 표준 알고리즘 도입 과정의 공통적 속성에 따라 일반화와 정당화를 추구하는 방안 마련이 필요함을 제시하였다.

• 한국항공우주학회지
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• 제50권4호
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• pp.233-240
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• 2022

스마트무장은 종말 유도조종을 통해 정밀타격 임무를 수행하는 초소형 유도무기로 미래 전장환경의 신무기체계이다. 하지만 크기로 인한 구조적 제한으로 인해 압전구동 방식의 조종날개를 이용해 제어를 수행하기 때문에 기동력이 작아 유도범위가 제한적이다. 본 논문에서는 스마트무장의 효과도를 높이기 위한 비 표준조건 사격제원 산출 알고리즘을 제안한다. 제안된 알고리즘은 획득한 전장환경 정보를 이용해 표준조건에서의 사격제원을 보정해 비 표준조건의 사격제원을 산출한다. 다양한 조건에서의 수치 시뮬레이션을 통해 제안된 알고리즘의 성능을 검증하였다.

• Steel and Composite Structures
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• 제4권6호
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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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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• 제9권6호
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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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• 제15권5호
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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.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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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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• 제22권3E호
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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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• 제9권1호
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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.