• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.5
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• pp.787-794
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• 2001

In this paper, the development of large-signal model extractor for GaAs FET device through the Monolithic Microwave integrated Circuit(MMIC) is presented. The measurement program controlled by personal computer is developed for the processing of an amount of measured data, and the de-embedding algorithm is added to the program for voltage dropping as attached series resistance on measurement system. The small-signal model parameters are typically consisted of 7 elements that are considered as complexity of large-signal model and its the accuracy of the small-signal model is verified through comparing with measured data as varied bias point. The fitting function model, one of the empirical model, is used for quick simulation. In the process of large-signal model parameter extraction, one-dimensional optimization method is proposed and optimized parameters are extracted. This study can reduce the modeling and measuring time and can secure a suitable model for circuit.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.32-43
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• 2010

IPTV is an emerging technology that combines both broadcasting and tele-communication technologies, and provides various multi-media contents to the service subscribers. In general, IPTV broadcasters transmit scrambled signals (multi-media contents) to the paying subscribers, and the users within the acknowledged network descramble the signals using the smart-card. That is, users are verified through communication between STB (Set-Top Box) and smart-card. In 2004, Jiang et al. proposed a secure protocol regarding the verification process. The method has been modified and enhanced by several following research works. However, all the methods that have been proposed so far required modular exponentiation operations which may raise the smart-card costs. In this paper, we propose a new efficient mutual authentication and session-key establishment protocol using only hash functions and exclusive-or operations, and show that the proposed protocol is still secure under various security attacks.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.5
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• pp.527-531
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• 2008

For statistical modeling, the model parameters are usually estimated by maximizing a probability measure, such as the likelihood or the posterior. In contrast, a variational Bayesian method treats the parameters of a model as probability distributions and computes optimal distributions for them rather than values. It has been shown that this approach effectively avoids the overfitting problem, which is common with other parameter optimization methods. This paper applies a variational Bayesian technique to surface fitting for height field data. Then, we propose point cloud denoising based on the basic surface fitting technique. Validation experiments and further tests with scan data verify the robustness of the proposed method.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.40-48
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• 1996

In this paper, a 40 dimensional segment vector with 4 frame and 7 frame width in every monosyllable interval was compressed into a 10, 14, 20 dimensional vector using K-L expansion and neural networks, and these was used to speech recognition feature parameter for CHMM. And we also compared them with CHMM added as feature parameter to the discrete duration time, the regression coefficients and the mixture distribution. In recognition test at 100 monosyllable, recognition rates of CHMM +${\bigtriangleup}$MCEP, CHMM +MIX and CHMM +DD respectively improve 1.4%, 2.36% and 2.78% over 85.19% of CHMM. And those using vector compressed by K-L expansion are less than MCEP + ${\bigtriangleup}$MCEP but those using K-L + MCEP, K-L + ${\bigtriangleup}$MCEP are almost same. Neural networks reflect more the speech dynamic variety than K-L expansion because they use the sigmoid function for the non-linear transform. Recognition rates using vector compressed by neural networks are higher than those using of K-L expansion and other methods.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.44-53
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• 2004

This paper aims at presenting high quality at low resolution apply by a new antialiasing method for voxelized implicit surfaces. Implicit surfaces create a unique type of 3D-modeling. Some use of implicit surfaces are scientific and medical visualization, animation, medical simulation and interactive modeling. One of previous antialiasing methods for implicit surfaces presented by raytracing or texture mapping is making use of a stochastic sampling. But this method requires more calculation time and costs which is caused by complicated and difficult implicit functions. In the meanwhile, voxelized implicit surfaces generally use high resolution for good quality images but it costs to generate. In order to this problem, this paper suggests a shifted double Z-buffer which is very simple, more efficient and easy. Tn addition, there are applied box-filter and tent-filter to the double Z-buffer antialiasing method for better images. For results this method generate high quality image and it is easy to apply to various filters and is able to extend to multi Z-buffer.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.5
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• pp.402-409
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• 2018

In this paper, we propose a lunar landing scenario of a robotic lunar landing mission and implements an optimal landing trajectory at the powered descent phase based on the proposed scenario. The change of attitude of the lunar lander in the power descent phase affects not only the amount of fuel used but also sensor operation of image based navigation. Therefore, the attitude angular velocity is included in the cost function of the optimal control problem to minimize the unnecessary attitude change when the optimal landing trajectory generates at powered descent phase of the lunar landing. The influence of the change of attitude angular velocity on the optimal landing trajectory are analyzed by adjusting the weight of the attitude angular velocity. Based on the results, we suggest the proper weight to generate the optimal landing trajectory in order to minimize the influence of the attitude angular velocity.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.6
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• pp.584-591
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• 2000

Power Quality Compensator(PQC) has been installed to protect the sensitive loads against the voltage disturbances, such as voltage sag and interruption. In general, static switch is used for the purpose of link between utility and PQC. So transfer operation of the static switch play a important part in the PQC. Many studies on the structure and control of PQC have been progressed in active, but these researches have been rarely mentioned about any voltage-disturbances-detection method to start the PQC operation. In this paper, a new voltage-disturbances-detection algorithm for computer application loads using the CBEMA/ITIC curve is proposed for transfer operation of the static switch. The proposed detection algorithm is implemented to get fast detecting time through the comparison of instantaneous 3-phase voltage values transferred to DC values in the synchronous reference frame with the operating reference values. To get the robust characteristics against the noise, a first order digital filter is designed. The magnitude falling and phase delay caused by the filter are compensated through the error normalizing and numerical analysis using transfer function, respectively. Finally, the validity of the proposed algorithm is proved by ACSL simulation and experimental results.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2196-2203
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• 1999

This paper describes the bus scheduling problem and register optimization method in datapath synthesis. Scheduling is process of operation allocation to control steps in order to minimize the cost function under the given circumstances. For that purpose, we propose some formulations to minimize the cost function for bus assignment to get an optimal and minimal cost function in hardware allocations. Especially, bus and register minimization technique are fully considered which are the essential topics in hardware allocation. Register scheduling is done after the operation and bus scheduling. Experiments are done with the DFG model of fifth-order digital ware filter to show its effectiveness. Structural integer programming formulations are used to solve the scheduling problems in order to get the optimal scheduling results in the integer linear programming environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.560-568
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• 2012

Spectrum sensing and spectrum decision are the main functions that cognitive radios (CRs) have to perform in order to get the best available spectrum band for the establishment of a wireless communication. These problems are worsened in the presence of users with different demands and spectrum channels with different properties in a heterogeneous network. The primary objective in this work is to design and simulate a new spectrum decision algorithm for heterogeneous cognitive radio system. To this end, first, we consider all cognitive users are separated into different traffic classes according to their Quality of Service (QoS). The cognitive users within one traffic class perform spectrum sensing in centralized group-based cooperative spectrum sensing system and the users of different traffic classes share the sensing results. Second, we propose a novel use of the Analytic Hierarchy Process (AHP) to optimally select available bands according to user requirements and detected spectrum channel characteristics (SCC). In this paper, utility function is used as spectrum decision algorithm. Simulation results demonstrate that the proposed method shows can effectively select the best available spectrum channels with a low complexity.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.29-39
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• 2012

The main objective is to predict the future degradation and maintenance budget for a suspension bridge system. Bayesian inference is applied to find the posterior probability density function of the source parameters (damage indices and serviceability), given ten years of maintenance data. The posterior distribution of the parameters is sampled using a Markov chain Monte Carlo method. The simulated risk prediction for decreased serviceability conditions are posterior distributions based on prior distribution and likelihood of data updated from annual maintenance tasks. Compared with conventional linear prediction model, the proposed quadratic model provides highly improved convergence and closeness to measured data in terms of serviceability, risky factors, and maintenance budget for bridge components, which allows forecasting a future performance and financial management of complex infrastructures based on the proposed quadratic stochastic regression model.