• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.321-325
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• 2004

Linear motor feed drive systems have been broadly used in machine tools or precision automatic feed systems. Recently, modem machine tools require high speed and high precision feed drive system to achieve high productivity. Unfortunately, a feed drive system, even though it was optimum designed, may experience severe transient vibrations during high-speed operation if its feed rate control is unsuitable. A rough feed rate curve having discontinuity in its acceleration profile causes a serious vibration problem in the feed slides system. This paper presents a feed rate optimization of a machine tool feed slide system, which is driven by a linear motor, for its minimum vibrations. Firstly, a 4-degree-of-freedom lumped parameter model is proposed for the vibration analysis of a linear motor driven machine tool feed drive system. Next, a feed rate optimization of the feed slide is carried out for minimum vibrations. The feed rate curve optimization strategy is to find out the most appropriate acceleration profile with jerk continuity. Of course, the optimized feed rate should approximate to the desired one as possible. A genetic algorithm with variable penalty function was used in this feed rate optimization.

• 한국광학회지
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• 제8권3호
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• pp.250-253
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• 1997

광선로에 존재하는 분산의 영향은 외부 변조기에서 일어나는 Chirp현상과 비선형 현상인 SPM에 따라서 달라지게 된다. SPM의 영향은 신호 파워에 따라 달라지게 되고, 외부 변조하에서의 Chirp은 외부 변조기의 변조 조건에 따라 달라진다. 따라서 광통신 시스템에서는 분산과 SPM, 그리고 처핑 현상을 적절히 이용하여 수신 감도 저하를 최소화할 수 있게 된다. 주어진 광통신 시스템의 광신호 세기 분포 하에서 SPM과 외부 변조기 Chirp을 고려하여 신호 펄스폭의 변화를 Split Step Fourier 방법을 이용하여 수치해석하였으며, 400 km 전송을 목표로 한 경우 수신 감도 저하를 최소화하는 최저의 Chirp인자 값을 얻을 수 있었다. 또한 실제 전송 실험을 통하여 계산 결과와 비교하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.962-966
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• 2004

Ball screw feed drive systems have been broadly used in machine tools or precision automatic feed systems. Recently, modern machine tools require high speed and high precision and drive system to achieve high productivity. Unfortunately, a feed drive system, even though it was optimum designed, may experience severe transient vibrations during high-speed operation if its feed rate control is unsuitable. A rough feed rate curve having discontinuity in its acceleration profile causes a serious vibration problem in the feed slide system. This paper presents a feed rate optimization of a machine tool feed slide system, which is driven by a ball screw, for its minimum vibrations. Firstly, a 6-degree-of-freedom lumped parameter model was proposed for the vibration analysis of a ball screw driven machine tool feed drive system. Next, a feed rate optimization of the feed slide was carried out for minimum vibrations. The feed rate curve optimization strategy is to find out the most appropriate acceleration profile having finite jerk. Of course, the optimized feed rate should approximate to the desired one as possible. A genetic algorithm with variable penalty function was used in this feed rate optimization.

• Journal of the Optical Society of Korea
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• 제8권2호
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• pp.59-64
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• 2004

The response of a single-mode fiber to a sinusoidally modulated input has been studied to see its utility in measuring system performance in the presence of fiber nonlinearities. The sinusoidally modulated signal models an alternating bit sequence of ones and zeros in on-off keying. The sinusoidal response of normally dispersive fiber shows a strong correlation with eye-opening penalty (EOP) over a wide range of the nonlinearity parameter N (0.1 ＜ N$^2$＜ 100). This result implies that the measurement of the sinusoidal response can be an alternate way of measuring EOP without having a long sequence of randomly modulated input bits. But in the anomalous dispersion region, the sinusoidal response has a much more limited range of application to estimate system performance.

• 한국CDE학회논문집
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• 제9권3호
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• pp.183-191
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• 2004

This paper deals with smooth curve fitting of data corrupt by noise. Most research efforts have been concentrated on employing the smoothness penalty function with the estimation of its optimal parameter in order to avoid the 'overfilling and underfitting' dilemma in noisy data fitting problems. Our approach, called DBSF(Differentiation-Based Smooth Fitting), is different from the above-mentioned method. The main idea is that optimal functions approximately estimating the derivative of noisy curve data are generated first using genetic programming, and then their integral values are evaluated and used to recover the original curve form. To show the effectiveness of this approach, DBSP is demonstrated by presenting two illustrative examples and the application of estimating the principal dimensions of bulk cargo ships in the conceptual design stage.

• 대한기계학회논문집
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• 제19권3호
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• pp.713-723
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• 1995

In intelligent machine tools, a computer based control system, which can adapt the machining parameters in an optimal fashion based on sensor measurements of the machining process, should be incorporated. In this paper, the technology for adaptively optimizing the cutting conditions to maximize the material removal rate in face milling operations is proposed using the exterior penalty function method combined with multilayered neural networks. Two neural networks are introduced ; one for estimating tool were length, the other for mapping input and output relations from experimental data. Then, the optimization of cutting conditions is adaptively implemented using tool were information and predicted process output. The results are demonstrated with respect to each level of machining such as rough, fine and finish cutting.

• 한국안전학회지
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• 제13권1호
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• pp.40-46
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• 1998

This paper is presented that theoretical optimization design method in order to consider mass reduction for the structural safety In this paper, it described methods for reducing vibration in structural safety by the determination of the optimum sizes and locations of tunning masses through formal mathematical optimization techniques. The optimization procedure which employs the tunning masses and corresponding locations is developed. Design variables are systematically changed to achieve low values of shear without a large mass penalty. Three optimization methods ire developed and tested. The first is based on minimizing the modal shaping parameter which indirectly reduce the modal shear amplitudes corresponding to each harmonic of airload. The second method reduces these amplitudes directly and the third method reduces the shear as a function of time during a revolution of the blade. The first method works well for reducing the shear for one mode responding to a single harmonic of the airload but has been found in some bases to be ineffective for more than one mode.

• Journal of applied mathematics & informatics
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• 제29권3_4호
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• pp.573-585
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• 2011

SQP method is one of the most important methods for solving nonlinear programming. But it may fail if the quadratic subproblem is inconsistent. In this paper, we propose a modified nonmonotone filter trust region method in which the QP subproblem is consistent. By means of nonmonotone filter, this method has no demand on the penalty parameter which is difficult to obtain. Moreover, the restoration phase is not needed any more. Under reasonable conditions, we obtain the global convergence of the algorithm. Some numerical results are presented.

• Journal of applied mathematics & informatics
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• 제27권5_6호
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• pp.981-1000
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• 2009

This paper considers asset liability management problems when their deterministic equivalent formulations are general nonlinear optimization problems. The presented approach uses a nonmonotone trust region strategy for solving a sequence of unconstrained subproblems parameterized by a scalar parameter. The objective function of each unconstrained subproblem is an augmented penalty-barrier function that involves both primal and dual variables. Each subproblem is solved approximately. The algorithm does not restrict a monotonic decrease of the objective function value at each iteration. If a trial step is not accepted, the algorithm performs a non monotone line search to find a new acceptable point instead of resolving the subproblem. We prove that the algorithm globally converges to a point satisfying the second-order necessary optimality conditions.

• Communications for Statistical Applications and Methods
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• 제25권5호
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• pp.453-470
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• 2018

We study how to distinguish the parameters of the sparse autoregressive (AR) process from zero using a non-convex penalized estimation. A class of non-convex penalties are considered that include the smoothly clipped absolute deviation and minimax concave penalties as special examples. We prove that the penalized estimators achieve some standard theoretical properties such as weak and strong oracle properties which have been proved in sparse linear regression framework. The results hold when the maximal order of the AR process increases to infinity and the minimal size of true non-zero parameters decreases toward zero as the sample size increases. Further, we construct a practical method to select tuning parameters using generalized information criterion, of which the minimizer asymptotically recovers the best theoretical non-penalized estimator of the sparse AR process. Simulation studies are given to confirm the theoretical results.