• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.10a
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• pp.78-85
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• 1996

The effect of vertical vibration of a beam is significantly influenced by higher modes of vibration. Therefore, a beam can be modeled using several elements must De used to represent a vibrating beam. As a result, analysis of a space framed structure for vertical vibration requires increase number of elements leading to more complicated model with many degree of freedom which requires large amount of computing resources for dynamic analysis. An efficient analysis method for vertical vibration of space framed structures are proposed in this paper which is presented in three method. The first method is to determine minimum nodes that shall be used to obtain dynamic response with the vertical vibration. Secondly, matrix condensation methods are introduced to reduce the computation efforts used to perform dynamic analysis and the selection of primary degree-of-freedom is proposed. The third method is of using the mass participation factor for the selection of primary degree-of-freedom.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.198-201
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• 2002

It has been well-blown that sandwich structures are efficient to resist bending loads by increasing the moment of inertia of the panel. However, the accurate theoretical prediction of failure load and its optimization of sandwich beams for strength under concentrated loads were so complicated. Moreover, the appropriate selection of the variables, such as face thickness, core density and core thickness of the sandwich beam with many theories has continuously researched to satisfy for the given strength to weight structural requirement. There will be interesting to investigate the effect of those variables with its optimization for the load resistance.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.19-20
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• 2006

In this paper, to reduce uplink feedback information for the beam weight and simultaneously maintaining the performance, we propose a MIMO-OFDM (Multi Input Multi Output-Orthogonal Frequency Division Multiplexing) system based on beamforming with antenna selection. In the proposed system, to perform the beamforming with more useful transmit antennas, the optimal combination of transmit antennas with maximum MRT (Maximum Ratio Transmission) beamforming gain is selected. Simulation results reveal that the proposed MIMO-OFDM system adopting the beamforming with antenna selection can reduce the feedback information for the beam weights as compared to the system using all the transmit antennas without serious degradation of system performance.

• Applied Microscopy
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• v.48 no.4
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• pp.122-125
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• 2018

The focused ion beam (FIB) method is widely used to prepare specimens for observation by transmission electron microscopy (TEM), which offers a wide variety of imaging and analytical techniques. TEM has played a significant role in material investigation. However, the FIB method induces amorphization due to bombardment with the high-energy gallium ($Ga^+$) ion beam. To solve this problem, electron beam induced deposition (EBID) is used to form a protective layer to prevent damage to the specimen surface. In this study, we introduce an optimized TEM specimen preparation procedure by comparing the EBID of carbon and tungsten as protective layers in FIB. The selection of appropriate EBID conditions for preparing specimens for TEM analysis is described in detail.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.391-399
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• 2021

The conformal array sensor has different sub-array depending on different beam steering directions. According to the method to effective the sensor, the performance of the conformal array sensor can be different, where the sub-array selects an effective sensor. Also, due to the figure of the conformal array sensor, the figure of the sub-array can be different each other, which results in different performance on directivity index, beam width and etc. In this paper, two methods to select sub-array which is the criteria for each sensors position vector and directive vector were proposed. For two sub-array selection methods, the performance of the directivity index, horizontal and vertical beam width were compared with the average and variance. In addition, this comparison was conducted when the number of sensors was fixed. When the number of sensors was not fixed, the directional vector method mainly results in high performance, but the performance of vertical beam width was lower or equal. When the number of sensors was fixed, the performance of two methods is similar, but the performance of variance was deteriorated.

• Steel and Composite Structures
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• v.19 no.2
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• pp.405-416
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• 2015

We proposed the concept of nominal rigidity of a long-span V-shaped rigid frame composite arch bridge, analyzed the effects of structural parameters on nominal rigidity, and derived a theoretical nominal rigidity equation. In addition, we discussed the selection of the arch-to-beam rigidity ratio and its effect on the distribution of internal forces, and analyzed the influence of the ratio on the internal forces. We determined the delimitation value between rigid arch-flexible beam and flexible arch-rigid beam. We summarized the nominal rigidity and arch to beam rigidity ratios of existing bridges. The results show that (1) rigid arch-flexible beam and flexible arch-rigid beam can be defined by the arch-to-beam rigidity ratio; (2) nominal rigidities have no obvious differences among the continuous rigid frame composite arch bridge, V-shaped rigid frame bridge, and arch bridge, which shows that nominal rigidity can reflect the global stiffness of a structure.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.156-166
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• 2020

In this paper, to improve spectral efficiency and mitigate interference in coordinated millimeter-wave systems, we proposes an optimal user group and beam selection scheme. The proposed scheme improves spectral efficiency by mitigating intra- and inter-cell interferences (ICI). By examining the effective channel capacity for all possible user combinations, user combinations and beams with minimized ICI can be selected. However, implementing this in a dense environment of cells and users requires highly complex computational abilities, which we have investigated applying multiclass classifiers based on machine learning. Compared with the conventional scheme, the numerical results show that our proposed scheme can achieve near-optimal performance, making it an attractive option for these systems.

• Speech Sciences
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• v.8 no.4
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• pp.17-33
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• 2001

In this paper, we implement the large variable vocabulary speech recognition system, which is characterized by no additional pre-training process and no limitation of recognized word list. We have designed the system in order to achieve the high recognition rate using the decision tree based state tying algorithm and in order to reduce the processing time using the gaussian selection based variable flooring algorithm, the limitation algorithm of the number of nodes and ENNS algorithm. The gaussian selection based variable flooring algorithm shows that it can reduce the total processing time by more than half of the recognition time, but it brings about the reduction of recognition rate. In other words, there is a trade off between the recognition rate and the processing time. The limitation algorithm of the number of nodes shows the best performance when the number of gaussian mixtures is a three. Both of the off-line and on-line experiments show the same performance. In our experiments, there are some differences of the recognition rate and the average recognition time according to the distinction of genders, speakers, and the number of vocabulary.

• Steel and Composite Structures
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• v.21 no.3
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• pp.679-688
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• 2016

Structural design of a composite beam is influenced by two main factors, strength and ductility. For the design to be effective for a composite beam, say an RC slab and a steel I beam, the shear strength of the composite beam and ductility have to carefully estimate with the help of displacements between the two members. In this investigation the shear strengths of steel-concrete composite beams was analyzed based on the respective variable parameters. The methodology used by ANFIS (Adaptive Neuro Fuzzy Inference System) has been adopted for this purpose. The detection of the predominant factors affecting the shear strength steel-concrete composite beam was achieved by use of ANFIS process for variable selection. The results show that concrete compression strength has the highest influence on the shear strength capacity of composite beam.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4102-4102
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• 2001

In multivariate analysis, absorbance spectrum is measured over a band of wavelengths. One does not often pay attention to the size of this wavelength band. However, it is desirable that spectrum is measured at only necessary wavelengths as long as the acceptable accuracy of prediction can be met. In this paper, the method of selecting an optimal band of wavelengths based on the loading vector analysis was proposed and applied for determining total protein in human serum using near-infrared transmission spectroscopy and PLSR. Loading vectors in the full spectrum PLSR were used as reference in selecting wavelengths, but only the first loading vector was used since it explains the spectrum best. Absorbance spectra of sera from 97 outpatients were measured at 1530∼1850 nm with an interval of 2 nm. Total protein concentrations of sera were ranged from 5.1 to 7.7 g/㎗. Spectra were measured by Cary 5E spectrophotometer (Varian, Australia). Serum in the 5 mm-pathlength cuvette was put in the sample beam and air in the reference beam. Full spectrum PLSR was applied to determine total protein from sera. Next, the wavelength region of 1672∼1754 nm was selected based on the first loading vector analysis. Standard Error of Cross Validation (SECV) of full spectrum (1530∼l850 nm) PLSR and selected wavelength PLSR (1672∼1754 nm) was respectively 0.28 and 0.27 g/㎗. The prediction accuracy between the two bands was equal. Wavelength selection based on loading vector in PLSR seemed to be simple and robust in comparison to other methods based on correlation plot, regression vector and genetic algorithm. As a reference of wavelength selection for PLSR, the loading vector has the advantage over the correlation plot since the former is based on multivariate model whereas the latter, on univariate model. Wavelength selection by the first loading vector analysis requires shorter computation time than that by genetic algorithm and needs not smoothing.