• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1624-1627
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• 2005

We proposed a design technique for auto-landing guidance and control system. This technique utilizes linear controller and neural network. Main features of this technique is to use conventional linear controller and compensate for the error coming from the model uncertainties and/or reference model mismatch. In this study, the multi-perceptron neural network with single hidden layer is adopted to compensate for the errors. Glide-slope capture logic for auto-landing guidance and control system is designed in this technique. From the simulation results, it is observed that the responses of velocity and pitch angle to commands are fairly good, which are directly related to control inputs of throttle and elevator, respectively.

• Korean Journal of Remote Sensing
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• v.5 no.2
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• pp.133-145
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• 1989

This paper describes an implementation of linear feature extraction algorithms for satellite images and a method of automatic GCP(Ground Control Point) filing using the extracted linear feature. We propose a new linear feature extraction algorithm which uses magnitude and direction information of edges. The result of applying the proposed algorithm to satellite images are presented and compared with those of the other algorithms. By using the proposed algorithm, automatic GCP filing was successfully performed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.147-157
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• 2017

In recent years, Super-pixels have become very popular for use in computer vision applications. Super-pixel algorithm transforms pixels into perceptually feasible regions to reduce stiff features of grid pixel. In particular, super-pixels are useful to depth estimation, skeleton works, body labeling, and feature localization, etc. But, it is not easy to generate a good super-pixel partition for doing these tasks. Especially, super-pixels do not satisfy more meaningful features in view of the gestalt aspects such as non-sum, continuation, closure, perceptual constancy. In this paper, we suggest an advanced algorithm which combines simple linear iterative clustering with fuzzy clustering concepts. Simple linear iterative clustering technique has high adherence to image boundaries, speed, memory efficient than conventional methods. But, it does not suggest good compact and regular property to the super-pixel shapes in context of gestalt aspects. Fuzzy similarity measures provide a reasonable graph in view of bounded size and few neighbors. Thus, more compact and regular pixels are obtained, and can extract locally relevant features. Simulation shows that fuzzy similarity based super-pixel building represents natural features as the manner in which humans decompose images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.2
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• pp.129-137
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• 2008

This study focuses on the radiometric normalization, which is one of the pre-processing steps to apply the change detection technique fur hyperspectral images. The PIFs which had radiometric consistency under the time interval were automatically extracted by applying spectral angle, and used as sample pixels for linear regression of the radiometric normalization. We also dealt with the problem about the number of PIFs for linear regression with iteratively quantitative methods. The results were assessed in comparison with image regression, histogram matching, and FLAASH. In conclusion, we show that linear regression method with PIFs can carry out the efficient result for radiometric normalization.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.441-452
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• 2017

Drones are increasingly being used to investigate disaster damage because they can quickly capture images in the air. It is necessary to extract the damaged area by registering the drones and the existing ortho-images in order to investigate the disaster damage. In this process, we might be faced the problem of registering two images with different time and spatial resolution. In order to solve this problem, we propose a new methodology that performs initial image transformation using line pairs extracted from images and association matrix, and final registration of images using linear features to refine the initial transformed result. The applicability of the newly proposed methodology in this study was evaluated through experiments using artifacts and the natural terrain areas. Experimental results showed that the root mean square error of artifacts and the natural terrain was 1.29 pixels and 4.12 pixels, respectively, and relatively high accuracy was obtained in the region with artifacts extracted a lot of linear information.

• Korea-Australia Rheology Journal
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• v.13 no.4
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• pp.205-217
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• 2001

This review article summarizes results of recent viscoelastic and dielectric studies for entangled cis-polyisoprene (PI) chains. The PI chains have the so-called type-A dipoles parallel along the chain backbone, and their slow viscoelastic and dielectric relaxation processes reflect the same global chain motion. However, this motion is differently averaged in the viscoelastic and dielectric properties, the former representing the isochronal orientational anisotropy of individual entanglement segments while the latter detecting the orientational correlation of the segments at two separate times (0 and t). On the basis of this difference, the viscoelastic and dielectric data of the entangled PI chains were compared to elucidate detailed features of the chain dynamics. Specifically, the molecular picture of dynamic tube dilation (DTD) incorporated in recent models was tested for linear and star PI chain. The comparison revealed that the DTD picture was valid for linear PI chains but failed for the star PI chains in the dominant part of the terminal relaxation. The failure for the star chains was related to the pre-requisite for the DTD process, rapid equilibration of successive entanglement segments through their constraint release (CR) motion: For the star chains, the dilated tube diameter expected in the terminal regime was considerably large because of a broad distribution of motional modes of the chains, so that the CR-equilibration required for DTD could not occur in time. The terminal relaxation of the star chain appeared to occur through the CR process before the expected DTD process was completed. The situation was different for the linear chain exhibiting narrowly distributed motional modes. The dilated tube expected for the linear chain was rather thin and the required CR-equilibration occurred in time, resulting in the success of the DTD picture. These detailed features of the chain dynamics was revealed only when the viscoelastic and dielectric properties were compared, demonstrating the importance of this comparison.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.92-100
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• 2006

In many common control charting situations, the statistic to be charted can be viewed as the output of a linear filter applied to the sequence of process measurement data. In recent work that has generalized this concept, the charted statistic is the output of a general linear filter in impulse response form, and the filter is designed by selecting its impulse response coefficients in order to optimize its average run length performance. In this work, we restrict attention to the class of all second-order linear filters applied to the residuals of a time series model of the process data. We present an algorithm for optimizing the design of the second-order filter that is more computationally efficient and robust than the algorithm for optimizing the general linear filter. We demonstrate that the optimal second-order filter performs almost as well as the optimal general linear filter in many situations. Both methods share a number of interesting characteristics and are tuned to detect any distinct features of the process mean shift, as it manifests itself in the residuals.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.3
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• pp.145-151
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• 2000

The topological investigations regarding magnetic circuit geometry and winding form of the transverse flux machine have brought up a variety of constructable arrangements with different features for several types of application[1, 2]. Here with, a novel PM-exited linear motor with inner mover, based on the transverse flux configuration leads to a considerable increase in power density for moving part. In this study we designed PM-exited transverse flux linear motor for ropeless elevator, whose output power density is higher and weight is lighter than conventional linear synchronous motors. When the designed motor in this study is applied to ropeless elevator, it is possible to increase power density more than 400% comparing with PM exited linear synchronous motor. The result of this study can be utilized for ropeless elevator or gearless direct linear moving system with high output[3].

• Nuclear Engineering and Technology
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• v.52 no.5
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• pp.947-955
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• 2020

Predicting the sloshing motion of a coolant during a seismic assessment of a rectangular spent fuel pool is of critical concern. Linear theory, which provides a simple analytical method, has been used to predict the sloshing motion in rectangular pools and tanks. However, this theory is not suitable for the high-frequency excitation problem. In this study, the authors developed a simple analytical method for predicting the sloshing motion in a rectangular pool for a wide range of excitation frequencies. The correlation among the linear theory parameters, influencing on excitation and convective waves, and the excitation frequency is investigated. Sloshing waves in a rectangular pool with several liquid heights are predicted using the original linear theory, a modified linear theory and computational fluid dynamics analysis. The results demonstrate that the developed method can predict sloshing motion over a wide range of excitation frequencies. However, the developed method has the limitations of linear solutions since it neglects the nonlinear features of sloshing motion. Despite these limitations, the authors believe that the developed method can be useful as a simple analytical method for predicting the sloshing motion in a rectangular pool under various external excitations.

• 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.