• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.85-107
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• 2022

This study is to analyze the induced effect, network connectivity, and network visualization of the water transportation industry on the overall economy in relation to all industries. For this, various inducement coefficients of the water transportation industry are analyzed using industry linkage analysis and unit structure matrix, and network visualization analysis is performed using network connectivity and NetDraw using Ucinet 6 that utilizes unit structure matrix and inverse matrix function. As a result of the study, analysis results of input coefficient, production inducement coefficient, value-added inducement coefficient, and inter-industry chain effect were presented as various inducement coefficients in the water transportation industry. content was presented. Through this study, the current position and status of the water transportation industry and its relationship with all industries were confirmed, and the strategic relationship with which industries it should be presented was presented. In the future, it is necessary to further analyze the current status and trends of various induced effects, connectivity (centrality), and network visualization analysis using industry-related analysis published since the 2000s.

• Structural Engineering and Mechanics
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• v.67 no.4
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• pp.359-368
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• 2018

In this paper, a method is presented to identify the physical and modal parameters of multistory shear building based on substructural technique using block pulse generalized operational matrix and genetic algorithm. The substructure approach divides a complete structure into several substructures in order to significantly reduce the number of unknown parameters for each substructure so that identification processes can be independently conducted on each substructure. Block pulse functions are set of orthogonal functions that have been used in recent years as useful tools in signal characterization. Assuming that the input-outputs data of the system are known, their original BP coefficients can be calculated using numerical method. By using generalized BP operational matrices, substructural dynamic vibration equations can be converted into algebraic equations and based on BP coefficient for each story can be estimated. A cost function can be defined for each story based on original and estimated BP coefficients and physical parameters such as mass, stiffness and damping can be obtained by minimizing cost functions with genetic algorithm. Then, the modal parameters can be computed based on physical parameters. This method does not require that all floors are equipped with sensor simultaneously. To prove the validity, numerical simulation of a shear building excited by two different normally distributed random signals is presented. To evaluate the noise effect, measurement random white noise is added to the noise-free structural responses. The results reveal the proposed method can be beneficial in structural identification with less computational expenses and high accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.56-63
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• 2009

Nowdays, Most of Internet Contents delivered as a compressed file. It gives many advantages like deduction of communication bandwidth and transmission time etc. In case of JPEG Compression, Quantization is the most important procedure which accomplish the compression. In general signal processing, Quantization is the process which converts continuous analog signal to discrete digital signal. As you known already, Quantization over JPEG compression is to reduce magnitude of pixel value in spatial domain or coefficient in frequency domain. A lot of Data Hiding algorithms also developed to applicable for those compressed files. In this paper, we are going to unveil the influence of quantization table which used in the process of JPEG compression. Even thought most of algorithm modify frequency coefficients with considering image quality, they are ignoring the influence of quantization factor corresponding with the modified frequency coefficient. If existing algorithm adapt this result, they can easily evaluate their performances.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.51-60
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• 2002

The Monte-Carlo simulation of statistical analysis is used to investigate the final conditions of states as well as the footprint boundaries resulting from the atmospheric re-entry dispersions. The re-entry dispersions in this paper are specified by a $7\times7$ covariance matrix of latitude, longitude, altitude, bank angle, flight path angle, heading error, and range at entry velocity. The error sources that affect these at re-entry for a deboost are the uncertainties associated with atmospheric density and temperature, initial errors, wind, and estimation error of aerodynamic coefficients. Using $3{\sigma}_n$ deviations of these errors and a nominal flight trajectory, the covariance matrix of state variables can be determined by performing a trajectory error analysis. Major considerations in the application of the Monte-Carlo method are the simulation of perturbed trajectories, bank reversal, and determination of the impact points for each of these trajectories. This paper analyzes the results of uncertainties from the viewpoint of aero-coefficients and bank reversal.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.433-439
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• 2016

In this paper, we propose a optimized steganography how to improve the image degradation of the existing data hiding techniques. This method operates in the compressed domain(JPEG) of an image. Most of the current information concealment methods generally change the coefficients to hide information. And several methods have tried to improve the performance of a typical steganography method such as F5 including a matrix encoding. Those papers achieved the object of reducing the distortion which is generated as hiding data in coefficients of compressed domain. In the proposed paper we analyzed the effect of the quantization table for hiding the data in the compressed domain. As a result, it found that can decrease the distortion that occur in the application of steganography techniques. This paper provides a little (Maximum: approximately 6.5%) further improved results in terms of image quality in a data hiding on compressed domain. Developed algorithm help improve the data hiding performance of compressed image other than the JPEG.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.5 s.347
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• pp.25-33
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• 2006

We have extracted the material parameters such as absorption coefficients of GaN, $Al_{0.2}Ga_{0.8}N$, and Schottky contact metal Ni of Schottky Diode UV-A and B detectors using a transfer matrix method (TMM). The ratios of the absorbed light to the total incident amount at the depletion regions of GaN and $Al_{0.2}Ga_{0.8}N$ have been calculated in order to obtain the spectral responsivity. Absorption coefficients of the materials have been obtained by fitting the simulated data with measured data. The depletion layer thickness has been obtanied by capacitance-voltage measurement. The results pave the way for the optimum design of UV Schottky detectors. Since the absorption coefficient of the Ni electrode is very high, its thickness is a major factor that determines the responsivity. It is possible to attain improved UV detectors using thinnest possible Ni electrodes and wide depletion regions of GaN and $Al_{0.2}Ga_{0.8}N$.

• Journal of the Korean Society of Propulsion Engineers
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• v.4 no.1
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• pp.65-73
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• 2000

Casting of metal matrix composites is an attractive process since it offers a wide selection of materials and processing conditions. Among the casting methods, melt-stirring technology is much attractive route in industrial application because it is more simple and inexpensive compared to squeeze casting or powder metallurgy. In the present work, effects of particle size, volume fraction of particles and mg addition on mechanical properties and thermal expansion coefficients of $\alpha$ -$Al_2O_{3(p)}$/LXA composites were studied. It is shown that $\alpha$ -$Al_2O_3$ particles formed at the interface of $\alpha$ -$Al_2O_3$ particles and matrix made an important role on mechanical properties. Ultimate tensile strength of most composite materials was not increased. But in the case of 5vol% addition of 16$\mu\textrm{m}$ $\alpha$ -$Al_2O_3$ Particle, Ultimate tensile strength of composite materials with 3wt.% Mg was increased. Volume fraction of reinforcements and mg content were thermal expansion coefficients of composite materials were decreased.

• Membrane Journal
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• v.11 no.3
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• pp.116-123
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• 2001

Polyimide-silica hybrid membranes were prepared and the effect of silica content on the structural properties and the gas transport properties was studied. The hybrid membranes were obtained by the sol-gel process starting from 1,2,4,5-benzenetetracarboxylic dianhydride(PMDA), 4,4`-diamino- diphenyl oxide(ODA) and tetraethoxysilane(TEOS) in N,N` dimethylacetatmide (DMAc) solvent. The structural characterizations of the membrane were performed by FT-IR, EDX, TGA and SEM. The gas permeation experiments with ${N_2}, {O_2}, {H_2}, {CO_2}and ${CH_4}$ were carried out at the temperature of $25^{\circ}C$ and in the range of pressure from 3atm to 7atm. the hybrid membranes showed higher thermal stability than PI membranes. The silica patricles were uniformly embedded in the polyimide matrix and the size of silica particles increased with increasing silica content. The permeability coefficients of ${N_2}, {O_2}, {H_2}, {CO_2}and ${CH_4}$ increased with increasing silica content but the diffusion coefficients might appear to be a result of a solubility enhancement. In spite of the permeability enhancement, an increase in the selectivities of ${H_2}/{N_2}, ${H_2}/{O_2} and ${H_2}/{CO_2} was observed.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.47-52
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• 2016

The used digital images in the smart device and small displayer has been a downscaled image. In this paper, the detection of the downscaling image forgery is proposed using the feature vector according to the pixel value's gradients. In the proposed algorithm, AR (Autoregressive) coefficients are computed from pixel value's gradients of the image. These coefficients as the feature vectors are used in the learning of a SVM (Support Vector Machine) classification for the downscaling image forgery detector. On the performance of the proposed algorithm, it is excellent at the downscaling 90% image forgery compare to MFR (Median Filter Residual) scheme that had the same 10-Dim. feature vectors and 686-Dim. SPAM (Subtractive Pixel Adjacency Matrix) scheme. In averaging filtering ($3{\times}3$) and median filtering ($3{\times}3$) images, it has a higher detection ratio. Especially, the measured performances of all items in averaging and median filtering ($3{\times}3$), AUC (Area Under Curve) by the sensitivity and 1-specificity is approached to 1. Thus, it is confirmed that the grade evaluation of the proposed algorithm is 'Excellent (A)'.

• Tunnel and Underground Space
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• v.18 no.6
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• pp.408-417
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• 2008

Rock mass classification methods such as RMR and Q system have different characteristics each other in parameters considered and applications, and so it is very important to prescribe the relationship between parameters for the analysis of correlativity of these methods. With the Held data of RMR and Q estimation in road construction sites, the acquaintance relations between RMR and Q of rock mass classifications are analyzed. The correlation equations between parameters of RMR and Q, matrix of correlation coefficients and the generalized form of acquaintance relation matrix are derived. This acquaintance relation matrix can be further extended to the form of generalized acquaintance relation network, and could be used to analyze the correlativity and to enhance the utility of common rock mass classification methods.