• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.949-957
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• 2003

This paper presents a gradient ON-OFF algorithm of which the performance is very robust even when the angle spread increases in the mobile communication environments. The proposed method getting the diversity gain by utilizing the primary and secondary eigenvector, which corresponds to the largest and the second largest eigenvalue of the autocovariance matrix of the received signal vector, outperforms the method which just utilizes one eigenvector. By applying the proposed method to IS-2000 1X signal environments, it is observed that the proposed method shows excellent performance compared to a typical beamforming method using just one eigenvector, which considerably degrades the receiving performance as the angle spread increases.

• Advances in concrete construction
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• v.8 no.2
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• pp.77-90
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• 2019

This paper aims to investigate vibration frequency decrease (vibration period elongation) of reinforced concrete (RC) structure with unreinforced infill wall and reinforced infill wall exposed to progressively increased artificial earthquake load on shaking table. For this purpose, two shaking table experiments were selected as a case study. Shaking table experiments were carried on 1:1 scaled prototype one bay one storey RC structure with infill walls. The purpose of this shaking table experiment sequence is to assess local behavior and progressive collapse mechanism. Frequency decrease and eigen-vector evolution are directly related to in-plane and out-of-plane bearing capacities of infill wall enclosure with reinforced concrete frame. Firstly, frequency decrease-damage relationship was evaluated on the base of experiment results. Then, frequency decrease and stiffness degradation were evaluated with applied Peak Ground Acceleration (PGA) by considering strength deterioration. Lastly, eigenvector evolution-local damage and eigenvector evolution-frequency decrease relationship was investigated. Five modes were considered while evaluating damage and frequency decrease of the tested specimens. The relationship between frequency decrease, stiffness degradation and damage level were presented while comparing with Unreinforced Brick Infill (URB) and Reinforced Infill wall with Bed Joint Reinforcement (BJR) on the base of natural vibration frequency.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.3 s.96
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• pp.251-258
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• 2005

The free vibration of a spinning flexible disk-spindle system supported by hydro dynamic bearings (HDB) in an HDD is analyzed by FEM. The spinning flexible disk is described using Kirchhoff plate theory and von Karman non-linear strain, and its rigid body motion is also considered. It is discretized by annular sector element. The rotating spindle which includes the clamp, hub, permanent magnet and yoke, is modeled by Timoshenko beam including the gyroscopic effect. The flexible supporting structure with a complex shape which includes stator core, housing, base plate, sleeve and thrust pad is modeled by using a 4-node tetrahedron element with rotational degrees of freedom to satisfy the geometric compatibility. The dynamic coefficients of HDB are calculated from the HDB analysis program, which solves the perturbed Reynolds equation using FEM. Introducing the virtual nodes and the rigid link constraints defined in the center of HDB, beam elements of the shaft are connected to the solid elements of the sleeve and thrust pad through the spring and damper element. The global matrix equation obtained by assembling the finite element equations of each substructure is transformed to the state-space matrix-vector equation, and the associated eigen value problem is solved by using the restarted Arnoldi iteration method. The validity of this research is verified by comparing the numerical results of the natural frequencies with the experimental ones. Also the effect of supporting structures to the natural modes of the total HDD system is rigorously analyzed.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.4
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• pp.53-60
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• 2011

In order to augment the robustness of OFDM system to Rayleigh multipath fading, there exist two smart antenna algorithms, namely, Pre-FFT smart antenna and Post-FFT smart antenna. After the mathematical modeling of both smart antenna algorithms, computer simulations have been carried to compare and analyze the performance of generalized eigen problem based Pre-FFT algorithm and the performance of Wiener solution based Post-FFT algorithm. It has been shown that the Post-FFT smart antenna far outperforms the Pre-FFT smart antenna due to the computational complexities. Especially it is so when the multipath signal arrives at beyond the guard interval and a rich co-channel interferer is introduced. Performance of a subcarrier clustering method proposed to lessen the computing load has been compared to that of a typical Wiener solution based Post-FFT smart antenna. Performance comparison between MRC(Maximum Ratio Combining) diversity based Post-FFT algorithm and typical Post-FFT algorithm has also been carried.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.8 no.2
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• pp.116-125
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• 1997

This paper presents a novel method, entitled Orthogonal Weights Searching(OWS), for the Direction-Of-Arrival(DOA) estimation. Utilizing the modified Conjugate Gradient Method(MCGM), the weight vector which is orthogonal to the signal subspace is directly computed from the signal matrix. The proposed method does not require the computation of the eigenvalues and eigenvectors. In addition, the new technique excludes the procedure for the detection of the number of signals under the assumption that the number of weights in the array is greater than the number of input signals. Since the proposed technique can be performed independently of the detection procedure, it shows a good performance in adverse signal environments in which the detection of the number of array inputs cannot be obtained successfully. The performance of the proposed technique is compared with that of the convectional eigen-decomposition method in terms of angle resolution for a given signal-to-noise ratio(SNR) and a required amount of computations.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.95-103
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• 1998

This paper deals with a problem occuring in recognition of tactile images due to the effects of imposed force at a me urement moment. Tactile image of a contact surface, used for recognition of the surface type, varies depending on the forces imposed so that a false recognition may result in. This paper fuzzifies two parameters of the contour of a tactile image with the membership function formed by considering the imposed force. Two fuzzifed paramenters are fused by the average Minkowski's dist; lnce. The proposed algorithm was implemented on the multisensor system cnmposed of an optical tact le sensor and a 6 axes forceltorque sensor. By the experiments, the proposed algorithm has shown average recognition ratio greater than 869% over all imposed force ranges and object models which is about 14% enhancement comparing to the case where only the contour information is used. The pro- ~oseda lgorithm can be used for end-effectors manipulating a deformable or fragile objects or for recognition of 3D objects by implementing on multi-fingered robot hand.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.79-86
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• 2011

Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.

• Journal of the Korean Chemical Society
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• v.31 no.6
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• pp.567-575
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• 1987

Fourty five ancient Korean glass pieces have been determined for 19 elements such as Ag, As, Br, Ce, Co, Cr, Eu, Fe, Hf, K, La, Lu, Na, Ru, Sb, Sc, Sm, Th and Zn, and for one such as Pb by instrumental neutron activation analysis and by atomic absorption spectrometry, respectively. The multivariate data have been analyzed for the relation among elemental contents through the variance-covariance matrix. The data have been further analyzed by a principal component mapping method. As the results training set of 5 class have been chosen, based on the spread of sample points in an eigen vector plot and archaeological data. The 5 training set consisting of 36 species and a test set consisting of 9 species bave finally been analyzed for the assignment to certain classes or outliers through the statistical isolinear multiple component analysis (SIMCA). The results have showed the whole species for 5 training set and 3 species in the test set are assigned appropriately and these are in accord with the results by principal component mapping.

• Journal of the Society of Naval Architects of Korea
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• v.57 no.1
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• pp.23-34
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• 2020

This paper covers the development of prediction techniques for ice load on ice-breakers operating in continuous ice-breaking under level ice conditions using particle-based continuum mechanics. Ice is assumed to be a linear elastic material until the fracture occurs. The maximum normal stress theory is used for the criterion of fracture. The location of the crack can be expressed using a local scalar function consisting of the gradient of the first principal stress and the corresponding eigen-vector. This expression is used to determine the relative position of particle pair to the new crack. The Hertz contact model is introduced to consider the collisions between ice fragments and the collisions between hull and ice fragments. In order to verify the developed technique, the simulation results for the three-point bending problems of ice-specimen and the continuous ice-breaking problem around a wedge-type model ship with bow angle of 20° are compared with the experimental results carrying out at Korea Research Institute of Ships and Ocean Engineering (KRISO).

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.79-84
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• 2021

A feature extraction method capable of reflecting features well while mainaining the properties of data is required in order to process high-dimensional data. The principal component analysis method that converts high-level data into low-dimensional data and express high-dimensional data with fewer variables than the original data is a representative method for feature extraction of data. In this study, we propose a principal component analysis method based on adaptive correlation when selecting principal component variables in principal component analysis for data feature extraction when the data is high-dimensional. The proposed method analyzes the principal components of the data by adaptively reflecting the correlation based on the correlation between the input data. I want to exclude them from the candidate list. It is intended to analyze the principal component hierarchy by the eigen-vector coefficient value, to prevent the selection of the principal component with a low hierarchy, and to minimize the occurrence of data duplication inducing data bias through correlation analysis. Through this, we propose a method of selecting a well-presented principal component variable that represents the characteristics of actual data by reducing the influence of data bias when selecting the principal component variable.