• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.4
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• pp.380-389
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• 2013

Application of linear electric motors to automation of manufacturing processes, gantry robots, machining processes, machining centers, additive manufacturing and laser scribing has been discussed. The paper focuses on replacement of ball lead screw mechanisms with linear electric motors, linear motor driven positioning stages, linear motor driven gantries, machining centers, machining of large objects and industrial lasers. The best linear electric motors for application to machining processes are permanent magnet (PM) linear synchronous motors (LSMs), especially those without PMs in the reaction tail, e.g., high thrust density linear (HDL) LSMs and PM flux switching (FS) LSMs.

• Communications of the Korean Mathematical Society
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• v.20 no.1
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• pp.161-168
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• 2005

In this paper, we obtain strong law of large numbers for linear process generated by asymptotically linear negative quadrant dependence processes.

• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.603-611
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• 1996

In this article we consider a sequential procedure for the fixed width interval estimation of the means of two mutually independent linear processes. It is shown that the proposed stopping rule is asymptotically efficient as in iid samples (cf. Robbins, Simons and Starr(l967)).

• Journal of the Chungcheong Mathematical Society
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• v.26 no.3
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• pp.615-623
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• 2013

In this paper we establish a central limit theorem for weighted sums of $Y_n={\sum_{i=1}^{n}}a_n,_iX_i$, where $\{a_{n,i},\;n{\in}N,\;1{\leq}i{\leq}n\}$ is an array of nonnegative numbers such that ${\sup}_{n{\geq}1}{\sum_{i=1}^{n}}a_{n,i}^2$ < ${\infty}$, ${\max}_{1{\leq}i{\leq}n}a_{n,i}{\rightarrow}0$ and $\{X_i,\;i{\in}N\}$ is a sequence of linear negatively quadrant dependent random variables with $EX_i=0$ and $EX_i^2$ < ${\infty}$. Using this result we will obtain a central limit theorem for partial sums of linear processes.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.124.3-124
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• 2001

The nonlinearity of several chemical processes is usually approximated by a series of the nonlinear static element and the linear subsystem. In the case of the model that the nonlinear static element precedes the linear subsystem, it is called a Hammerstein model. It is a Wiener model when the order is reserved. Here we investigate a relay feedback identification method for Hammerstein type nonlinear processes. The proposed method separates the identification of the nonlinear static function from that of the linear subsystem by using a relay feedback method. From two times activation of nonlinear processes, we identify he whole range of the nonlinear static function as well as the ultimate information of the linear subsystem.

• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.504-512
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• 1994

A simple proof for the random central limit theorem is given for a family of stationary linear lattice processes, which belogn to a class of 2 dimensional random fields, applying the Beveridge and Nelson decomposition in time series context. The result is an extension of Fakhre-Zakeri and Fershidi (1993) dealing with the linear process in time series to the case of the linear lattice process with 2 dimensional indices.

• Molecules and Cells
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• v.45 no.7
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• pp.444-453
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• 2022

Multivalent macromolecular interactions underlie dynamic regulation of diverse biological processes in ever-changing cellular states. These interactions often involve binding of multiple proteins to a linear lattice including intrinsically disordered proteins and the chromosomal DNA with many repeating recognition motifs. Quantitative understanding of such multivalent interactions on a linear lattice is crucial for exploring their unique regulatory potentials in the cellular processes. In this review, the distinctive molecular features of the linear lattice system are first discussed with a particular focus on the overlapping nature of potential protein binding sites within a lattice. Then, we introduce two general quantitative frameworks, combinatorial and conditional probability models, dealing with the overlap problem and relating the binding parameters to the experimentally measurable properties of the linear lattice-protein interactions. To this end, we present two specific examples where the quantitative models have been applied and further extended to provide biological insights into specific cellular processes. In the first case, the conditional probability model was extended to highlight the significant impact of nonspecific binding of transcription factors to the chromosomal DNA on gene-specific transcriptional activities. The second case presents the recently developed combinatorial models to unravel the complex organization of target protein binding sites within an intrinsically disordered region (IDR) of a nucleoporin. In particular, these models have suggested a unique function of IDRs as a molecular switch coupling distinct cellular processes. The quantitative models reviewed here are envisioned to further advance for dissection and functional studies of more complex systems including phase-separated biomolecular condensates.

• Communications of the Korean Mathematical Society
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• v.10 no.4
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• pp.963-974
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• 1995

We formulate central limit theorems for non-linear functionals of stationary Gaussian vector processes with long-range dependence.

• Journal of the Korean Mathematical Society
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• v.37 no.1
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• pp.1-19
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• 2000

We formulate a non-central limit theorem for non-linear functionals of stationary Gaussian vector processes with dependence.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.435-441
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• 1999

A 'convergence in probability' rate of the empirical distributions and quantiles of linear processes is obtained. As an application of the limit theorems, a trimmed mean for the location of the linear process is considered. It is shown that the trimmed mean is asymptotically normal. A consistent estimator for the asymptotic variance of the trimmed mean is provided.