• Journal for History of Mathematics
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• v.20 no.1
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• pp.83-102
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• 2007

A math class in Korean university was taught in English for one semester and the students' improvement was measured in math content and English proficiency. Pre and post test in 9 week intervals showed that math content loaming in the immersion class was superior to the non-immersed class. Especially, the immersion class showed remarkable improvement in difficult problems among math content test problems. The immersion class improved in math-related English, but not in general English. It is discussed that the particular English expressions for math are hardly separable from the math content knowledge in English because understanding and using those expressions correctly means the students' understanding of math concept in English and thus the math concept itself.

• Journal of Biomedical Engineering Research
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• v.36 no.5
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• pp.211-220
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• 2015

Recently, model-based iterative reconstruction (MBIR) has played an important role in transmission tomography by significantly improving the quality of reconstructed images for low-dose scans. MBIR is based on the penalized-likelihood (PL) approach, where the penalty term (also known as the regularizer) stabilizes the unstable likelihood term, thereby suppressing the noise. In this work we further improve MBIR by using a more expressive regularizer which can restore the underlying image more accurately. Here we used a spline regularizer derived from a linear combination of the two-dimensional splines with first- and second-order spatial derivatives and applied it to a non-quadratic convex penalty function. To derive a PL algorithm with the spline regularizer, we used a separable paraboloidal surrogates algorithm for convex optimization. The experimental results demonstrate that our regularization method improves reconstruction accuracy in terms of both regional percentage error and contrast recovery coefficient by restoring smooth edges as well as sharp edges more accurately.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2634-2648
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• 2020

In this paper, an adaptive sparse singular value decomposition (ASSVD) algorithm is proposed to estimate the signal matrix when only one data matrix is observed and there is high dimensional white noise, in which we assume that the signal matrix is low-rank and has sparse singular vectors, i.e. it is a simultaneously low-rank and sparse matrix. It is a structured matrix since the non-zero entries are confined on some small blocks. The proposed algorithm estimates the singular values and vectors separable by exploring the structure of singular vectors, in which the recent developments in Random Matrix Theory known as anisotropic Marchenko-Pastur law are used. And then we prove that when the signal is strong in the sense that the signal to noise ratio is above some threshold, our estimator is consistent and outperforms over many state-of-the-art algorithms. Moreover, our estimator is adaptive to the data set and does not require the variance of the noise to be known or estimated. Numerical simulations indicate that ASSVD still works well when the signal matrix is not very sparse.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.77-83
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• 2014

Over-sampled discrete wavelet transformation is one way to overcome the disadvantages of the standard wavelet transform of shift invariance even though it increases the number of subband signals. Non-separable based discrete wavelet transform is efficient that it satisfies shift invariance and directional selectivity. In this paper, since efficient over-sampled wavelet transform is possible in a two-dimensional image processing, we show that the proposed method is well applied with performance improvement of digital image and noise removal.

• BMB Reports
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• v.29 no.6
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• pp.540-544
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• 1996

Ferritins from germinated pumpkin seeds were isolated by ammonium sulfate precipitation (0.55 saturation), ion-exchange chromatography on DEAE-cellulose, and gel filtration chromatographies on Sephacryl S-300 and Sephadex G-100. Pumpkin ferritin contains less iron than soybean ferritin. Pumpkin ferritin cross-reacted with anti-soybean ferritin antiserum made in rabbit, and showed two distinct antibody reactive bands, both of equal intensity. The pumpkin ferritins corresponding to the two bands were separable by centrifugation in a sucrose gradient (20~50%). The molecular weights of the native pumpkin ferritins based on the estimation of sucrose gradient centrifugation, gel filtration on Sephacryl S-300 and non-denaturing polyacrylamide gel electrophoresis appeared to be: 530~580 KD (the large molecular weight pumpkin ferritin) and 330-360 KD (the small molecular weight pumpkin ferritin) The large molecular weight pumpkin ferritin contains less iron. Both pumpkin ferritins cross-reacted with anti-soybean ferritin antibody with a spur formation suggesting partial antigenic recognition.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2508-2513
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• 2003

This paper presents a nuclear steam generator tube inspection/maintenance robot system. The robot assists in automatic non-destructive testing and the repair of nuclear steam generator tubes welded into a thick tube sheet that caps a hemispherical or quarter-sphere plenum which is a high-radiation area. For easy carriage and installation, the robot system consists of three separable parts: a manipulator, a water-chamber entering and leaving device for the manipulator and a manipulator base pose adjusting device. A software program to control and manage the robotic system has been developed on the NT based OS to increase the usability. The software program provides a robot installation function, a robot calibration function, a managing and arranging function for the eddy-current test, a real time 3-D graphic simulation function which offers remote reality to operators and so on. The image information acquired from the camera attached to the end-effecter is used to calibrate the end-effecter pose error and the time-delayed control algorithm is applied to calculate the optimal PID gain of the position controller. The developed robotic system has been tested in the Ulchin NPP type steam generator mockup in a laboratory.

• Polymer(Korea)
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• v.25 no.4
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• pp.536-544
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• 2001

We investigate, in the viewpoint of mathematical stability, the validity of the time-strain separability hypothesis employed in polymer viscoelasticity on the basis of experimental results. There have been suggested two distinct stability criteria such as Hadamard related to quick response and dissipative stability conditions, and in the limit of high deformation rate we have proved that separable constitutive equations are either Hadamard or dissipative unstable. The fact that the separability is not valid in the short time region in stress relaxation experiments exactly coincides with the results of our analysis. Therefore, since the application of the separability hypothesis incurs thermodynamic inconsistency as well as mathematical instability, such application should be avoided in the formulation of constitutive equations. In addition, careful attention should be paid to the limit of its validity even in experiments. It is also proved that there is neither theoretical nor physical validity of using the damping function.

• The Journal of the Acoustical Society of Korea
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• v.38 no.2
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• pp.177-183
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• 2019

In this paper, we proposed an application method of ICA (Independent Component Analysis) to passive line array sonar to separate interferences from target signals in low frequency band and compared performance of three conventional ICA algorithms. Since the low frequency signals are received through larger bearing angles than other frequency bands, neighboring beam signals can be used to perform ICA as measurement signals of the ICA. We use three ICA algorithms such as Fast ICA, NNMF (Non-negative Matrix Factorization) and JADE (Joint Approximation Diagonalization of Eigen-matrices). Through experiments on real data obtained from passive line array sonar, it is verified that the interference can be separable from target signals by the suggested method and the JADE algorithm shows the best separation performance among the three algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.407-412
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• 2003

An effective methodology is .reported for determining the optimal capacity (lot-size) of batch processing and storage networks which include material recycle or reprocessing streams. We assume that any given storage unit can store one material type which can be purchased from suppliers, be internally produced, internally consumed and/or sold to customers. We further assume that a storage unit is connected to all processing stages that use or produce the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. The objective for optimization is to minimize the total cost composed of raw material procurement, setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory hold-up. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two subproblems. The first yields analytical solutions for determining batch sizes while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks. For the special case in which the number of storage is equal to the number of process stages and raw materials storage units, a complete analytical solution for average flow rates can be derived. The analytical solution for the multistage, strictly sequential batch-storage network case can also be obtained via this approach. The principal contribution of this study is thus the generalization and the extension to non-sequential networks with recycle streams. An illustrative example is presented to demonstrate the results obtainable using this approach.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.3
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• pp.259-266
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• 2011

We present a new dual sequential approximate optimization (SAO) algorithm called SD-TDQAO (sequential dual two-point diagonal quadratic approximate optimization). This algorithm solves engineering optimization problems with a nonlinear objective and nonlinear inequality constraints. The two-point diagonal quadratic approximation (TDQA) was originally non-convex and inseparable quadratic approximation in the primal design variable space. To use the dual method, SD-TDQAO uses diagonal quadratic explicit separable approximation; this can easily ensure convexity and separability. An important feature is that the second-derivative terms of the quadratic approximation are approximated by TDQA, which uses only information on the function and the derivative values at two consecutive iteration points. The algorithm will be illustrated using mathematical and topological test problems, and its performance will be compared with that of the MMA algorithm.