• International Journal of Control, Automation, and Systems
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• 제5권1호
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• pp.93-98
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• 2007

A class of new observers in descriptor linear systems, proportional-derivative(PD) observers, are proposed. A parametric design approach for such observers is proposed based on a complete parametric solution to the generalized Sylvester matrix equation. The approach provides complete parameterizations for all the observer gains, gives the parametric expression for the corresponding left eigenvector matrix of the observer system matrix, realizes elimination of impulsive behaviors, and guarantees the regularity of the observer system.

• International Journal of Control, Automation, and Systems
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• 제3권2호
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• pp.159-165
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• 2005

This paper designs observers for matrix second-order linear systems on the basis of generalized eigenstructure assignment via unified parametric approach. It is shown that the problem is closely related with a type of so-called generalized matrix second-order Sylvester matrix equations. Through establishing two general parametric solutions to this type of matrix equations, two unified complete parametric methods for the proposed observer design problem are presented. Both methods give simple complete parametric expressions for the observer gain matrices. The first one mainly depends on a series of singular value decompositions, and is thus numerically simple and reliable; the second one utilizes the right factorization of the system, and allows eigenvalues of the error system to be set undetermined and sought via certain optimization procedures. A spring-mass system is utilized to show the effect of the proposed approaches.

• Investigative Magnetic Resonance Imaging
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• 제25권4호
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• pp.300-312
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• 2021

Compressed sensing (CS) has been investigated in magnetic resonance (MR) parametric mapping to reduce scan time. However, the relatively long reconstruction time restricts its widespread applications in the clinic. Recently, deep learning-based methods have shown great potential in accelerating reconstruction time and improving imaging quality in fast MR imaging, although their adaptation to parametric mapping is still in an early stage. In this paper, we proposed a novel deep learning-based framework DEMO for fast and robust MR parametric mapping. Different from current deep learning-based methods, DEMO trains the network in an unsupervised way, which is more practical given that it is difficult to acquire large fully sampled training data of parametric-weighted images. Specifically, a CS-based loss function is used in DEMO to avoid the necessity of using fully sampled k-space data as the label, thus making it an unsupervised learning approach. DEMO reconstructs parametric weighted images and generates a parametric map simultaneously by unrolling an interaction approach in conventional fast MR parametric mapping, which enables multi-tasking learning. Experimental results showed promising performance of the proposed DEMO framework in quantitative MR T1ρ mapping.

• International Journal of Control, Automation, and Systems
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• 제3권1호
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• pp.109-116
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• 2005

The design of reconfiguring a class of second-order dynamic systems via proportional plus derivative (P-D) feedback is considered. The aim is to resynthesize a P-D feedback controller such that the eigenvalues of the reconfigured closed-loop system can completely recover those of the original close-loop system, and make the corresponding eigenvectors of the former as close to those of the latter as possible. Based on a parametric result of P-D feedback eigenstructure assignment in second-order dynamic systems, parametric expressions for all the P-D feedback gains and all the closed-loop eigenvector matrices are established and a parametric algorithm for this reconfiguration design is proposed. The parametric algorithm offers all the degrees of design freedom, which can be further utilized to satisfy some additional performances in control system designs. This algorithm involves manipulations only on the original second-order system matrices, thus it is simple and convenient to use. An illustrative example and the simulation results show the simplicity and effect of the proposed parametric method.

• International Journal of Naval Architecture and Ocean Engineering
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• 제7권1호
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• pp.142-156
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• 2015

A new method for ship Inner Shell optimization, which is called Parametric Inner Shell Optimization Method (PISOM), is presented in this paper in order to improve both hull performance and design efficiency of transport ship. The foundation of PISOM is the parametric Inner Shell Plate (ISP) model, which is a fully-associative model driven by dimensions. A method to create parametric ISP model is proposed, including geometric primitives, geometric constraints, geometric constraint solving etc. The standard optimization procedure of ship ISP optimization based on parametric ISP model is put forward, and an efficient optimization approach for typical transport ship is developed based on this procedure. This approach takes the section area of ISP and the other dominant parameters as variables, while all the design requirements such as propeller immersion, fore bottom wave slap, bridge visibility, longitudinal strength etc, are made constraints. The optimization objective is maximum volume of cargo oil tanker/cargo hold, and the genetic algorithm is used to solve this optimization model. This method is applied to the optimization of a product oil tanker and a bulk carrier, and it is proved to be effective, highly efficient, and engineering practical.

• 기술혁신학회지
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• 제6권3호
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• pp.279-297
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• 2003

The purpose of this paper is to analyze the determinants of company R＆D investment with zero observations by using the data of R＆D Scoreboard published by Ministry of Science and Technology(2002). Conventional parametric approach to dealing with zero investments is not robust to heteroscedastic and/or non-normal error structure. Thus, this study applies symmetrically trimmed least squares(STLS) estimation as a semi-parametric approach to dealing with zero R&D investments. The result of specification test indicates the semi-parametric approach outperforms the parametric approach significantly. Moreover, the results of the study provide various implications as summarized below. The R&D investment of IT company is larger than that of non-IT company. The R&D investment has a positive relation to foreigners' investment ratio. The higher degree of financial self-reliance is, the larger the R&D investment is. Firm size variables such as sales amount and the number of workers are positively related to R&D investment. The sales elasticity of R&D investment is larger than one. However, the workers elasticity of R&D investment is smaller than one.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 춘계 학술발표회
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• pp.1358-1365
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• 2010

Estimating condition of slope is difficult because of nonlinear time dependency and seasonal effects, which affect the displacements. Displacements and displacement patterns of landslides are highly variable in time and space, and a unique approach cannot be defined to model landslide movements. Characteristics of movements are obtained by using a statistical method called Principal Component Analysis(PCA). The PCA is a non-parametric method to separate unknown, statistically uncorrelated source processes from observed mixed processes. In the non-parametric approaches, no physical assumptions of target systems are required. Instead, since the "best" mathematical relationship is estimated for given data sets of the input and output measured from target systems. As a consequence, non-parametric approaches are advantageous in modeling systems whose geomechanical properties are unknown or difficult to be measured. Non-parametric approaches are consequently more flexible in modeling than parametric approaches. This method is expected to be a useful tool for the slope management of and alarm systems.

• Current Optics and Photonics
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• 제5권1호
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• pp.59-65
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• 2021

This paper reports a tunable diode-pumped folded intracavity Q-switched singly resonant optical parametric oscillator based on multi-period MgO:PPLN. A wide tuning mid-infrared parametric light from 2.78 ㎛ to 4.17 ㎛ was obtained in real time by changing the poled periods and temperatures. The maximum output power of 1.89 W at 3.2 ㎛, 1.53 W at 3.5 ㎛, 0.87 W at 3.8 ㎛ and 0.486 W at 4.1 ㎛ were achieved. The highest optical-optical conversion efficiency was 7.89%. During experiments, a range tunable output of 2.78-4.17 ㎛ in the mid-infrared range was achieved.

• 수산해양기술연구
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• 제23권4호
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• pp.189-197
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• 1987

Parametric 음원을 어탐에 응용하기 위한 기초연구로써 본 실험에서는 parametric 음원의 특성을 조사하고 이 음원으로 어체에 대한 표적 강도를 측정하여 그 결과를 200KHz의 단일주파수 음원으로 측정한 결과와 비교.검토하였다. 그 결과를 요약하면 다음과 같다. 1. 200KHz인 단일주파수로 구동할 때의 지향각은 5.0$^{\circ}$였고, parametric 음원의 주파수가 5KHz, 10KHz, 16KHz, 20KHz일 때의 지향각은 각각 4.3$^{\circ}$, 2.2$^{\circ}$, 3.0$^{\circ}$, 2.5$^{\circ}$로서 주파수 저감비가 감소할수록 지향각이 예리하였으며 부엽은 전혀 나타나지 않았다. 2. parametric 음원의 주파수가 5KHz, 10KHz, 16KHz, 20KHz일 때의 음파변환효율은 각각 0.9%(Parametric 이득은 -41dB), 0.55%(parametric 이득은 -45dB), 0.1%(parametric 이득은 -60 dB), 0.04%(parametric 이득은 -68 dB)로 주파수 저감비가 감소할수록 음파변환효율은 급격히 낮아졌다. 3. parametric 음원으로 측정한 어체의 표적강도는 200KHz의 단일주파수 음원으로 측정한 표적강도에 비하여 단일어체일 때는 머리부분과 꼬리부분에서 5 dB씩 낮았으며 어체수가 2~3마리 일때는 머리부분과 꼬리부분에서 1~3 dB 정도 낮았으나 측면부분은 비슷하였다

• International Journal of Aeronautical and Space Sciences
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• 제13권3호
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• pp.332-348
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• 2012

The present study deals with the parametric resonance behaviour of laminated composite curved shell panels in a hygrothermal environment using Bolotin's approach. A simple laminated model is developed using first order shear deformation theory (FSDT) for the vibration and dynamic stability analysis of laminated composite shells subjected to hygrothermal conditions. A computer program based on the finite element method (FEM) in a MATLAB environment is developed to perform all necessary computations. Quantitative results are presented to show the effects of curvature, ply-orientations, degree of orthotropy and geometry of laminates on the parametric instability of composite curved shell panels for different temperature and moisture concentrations. The excitation frequencies of laminated composite panels decrease with the increase of temperature and moisture due to reduction of stiffness for all laminates.