• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.259-265
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• 2004

In this study, a hybrid genetic algorithm merged with simulated annealing is presented to solve nonlinear channel blind equalization problems. The equalization of nonlinear channels is more complicated one, but it is of more practical use in real world environments. The proposed hybrid genetic algorithm with simulated annealing is used to estimate the output states of nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. By using the desired channel states derived from these estimated output states of the nonlinear channel, the Bayesian equalizer is implemented to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm(GA) and a simplex GA. In particular, we observe a relatively high accuracy and fast convergence of the method.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.385-392
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• 2012

Logistic regression is a well known binary classification method in the field of statistical learning. Mixed-effect regression models are widely used for the analysis of correlated data such as those found in longitudinal studies. We consider kernel extensions with semiparametric fixed effects and parametric random effects for the logistic regression. The estimation is performed through the penalized likelihood method based on kernel trick, and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of optimal hyperparameters, cross-validation techniques are employed. Numerical results are then presented to indicate the performance of the proposed procedure.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.35-41
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• 2007

In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. In its searching procedure, all of the possible desired channel states are constructed with the elements of estimated channel output states. The desired state with the maximum Bayesian fitness is selected and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.456-458
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• 2019

정보보안을 달성하기 위해서 컴퓨터가 보급된 이래로 많은 노력이 이루어졌다. 그중 메모리 보호 기법에 대한 연구가 가장 많이 이루어졌지만, 컴퓨터의 성능 향상으로 이전의 메모리 보호 기법들의 문제들이 발견되고, 부채널 공격의 등장으로 새로운 방어책이 필요 되었다. 본 논문에서는 프로그램에 정적 바이너리 재작성(Static Binary Rewriting) 기법을 통해 페이지(Page)마다 4~8byte 의 난수를 삽입하여 메모리 공유 기반 부채널 공격을 방어할 수 있는 2 가지 방법을 제시한다. 최근 아키텍처는 분기 예측(Branch Prediction)을 통해 jmp 명령어에 대한 분기처리가 매우 빠르고 정확하게 처리되기 때문에 난수를 삽입할 때 사용하는 jmp+rand 방식은 오버헤드가 매우 낮다. 또한 특정 프로그램에만 난수 삽입이 가능하므로 특히 클라우드 환경에서 중복제거 기능과 함께 사용하면 높은 효율성을 보일 수 있다고 예상한다.

• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.315-323
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• 2019

Panel data sets have recently been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Often a dichotomous dependent variable occur in survival analysis, biomedical and epidemiological studies that is analyzed by a generalized linear mixed effects model (GLMM). The most common estimation method for the binary panel data may be the maximum likelihood (ML). Many statistical packages provide ML estimates; however, the estimates are computed from numerically approximated likelihood function. For instance, R packages, pglm (Croissant, 2017) approximate the likelihood function by the Gauss-Hermite quadratures, while Rchoice (Sarrias, Journal of Statistical Software, 74, 1-31, 2016) use a Monte Carlo integration method for the approximation. As a result, it can be observed that different packages give different results because of different numerical computation methods. In this note, we discuss the pros and cons of numerical methods compared with the exact computation method.

• Current Optics and Photonics
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• v.6 no.3
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• pp.288-296
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• 2022

We propose and experimentally demonstrate a novel photonic compressive sensing (CS) scheme for acquiring sparse radio frequency signals with adjustable compression ratio in this paper. The sparse signal to be measured and a pseudo-random binary sequence are modulated on consecutively connected chirped pulses. The modulated pulses are compressed into short pulses after propagating through a dispersive element. A programmable optical filter based on spatial light modulator is used to realize spectral segmentation and demultiplexing. After spectral segmentation, the compressed pulses are transformed into several sub-pulses and each of them corresponds to a measurement in CS. The major advantage of the proposed scheme lies in its adjustable compression ratio, which enables the system adaptive to the sparse signals with variable sparsity levels and bandwidths. Experimental demonstration and further simulation results are presented to verify the feasibility and potential of the approach.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.91-100
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• 2023

As SDN devices and systems hit the market, security in SDN must be raised on the agenda. SDN has become an interesting area in both academics and industry. SDN promises many benefits which attract many IT managers and Leading IT companies which motivates them to switch to SDN. Over the last three decades, network attacks becoming more sophisticated and complex to detect. The goal is to study how traffic information can be extracted from an SDN controller and open virtual switches (OVS) using SDN mechanisms. The testbed environment is created using the RYU controller and Mininet. The extracted information is further used to detect these attacks efficiently using a machine learning approach. To use the Machine learning approach, a dataset is required. Currently, a public SDN based dataset is not available. In this paper, SDN based dataset is created which include legitimate and non-legitimate traffic. Classification is divided into two categories: binary and multiclass classification. Traffic has been classified with or without dimension reduction techniques like PCA and LDA. Our approach provides 98.58% of accuracy using a random forest algorithm.

• Korean Journal of Optics and Photonics
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• v.31 no.5
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• pp.223-230
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• 2020

In this paper, we have studied the characteristics of stimulated Brillouin scattering (SBS) and mode instability (MI) in a ytterbium-doped polarization-maintaining fiber laser with master oscillator power amplifier configuration. We measured the laser output power and back-reflection spectrum for a variety of ytterbium-doped fibers and seed lights, to investigate the power-scaling limits of fiber lasers. By optimizing the laser structure, we demonstrated an all-fiber high-power polarization-maintaining fiber laser with near-diffraction-limited beam quality. The output power of 1.5 kW was achieved with a linewidth of 10 GHz, generated by pseudo-random binary sequence (PRBS) phase modulation. The beam quality M² was about 1.15 at the maximum output power. The polarization extinction ratio (PER) was greater than 17 dB.

• Current Optics and Photonics
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• v.1 no.2
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• pp.107-112
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• 2017

An adaptive optics system can be simulated or analyzed to predict its closed-loop performance. However, this type of prediction based on various assumptions can occasionally produce outcomes which are far from actual experience. Thus, every adaptive optics system is desired to be tested in a closed loop on an optical test bench before its application to a telescope. In the close-loop test bench, we need an atmospheric simulator that simulates atmospheric disturbances, mostly in phase, in terms of spatial and temporal behavior. We report the development of an atmospheric turbulence simulator consisting of two point sources, a commercially available deformable mirror with a $12{\times}12$ actuator array, and two random phase plates. The simulator generates an atmospherically distorted single or binary star with varying stellar magnitudes and angular separations. We conduct a simulation of a binary star by optically combining two point sources mounted on independent precision stages. The light intensity of each source (an LED with a pin hole) is adjustable to the corresponding stellar magnitude, while its angular separation is precisely adjusted by moving the corresponding stage. First, the atmospheric phase disturbance at a single instance, i.e., a phase screen, is generated via a computer simulation based on the thin-layer Kolmogorov atmospheric model and its temporal evolution is predicted based on the frozen flow hypothesis. The deformable mirror is then continuously best-fitted to the time-sequenced phase screens based on the least square method. Similarly, we also implement another simulation by rotating two random phase plates which were manufactured to have atmospheric-disturbance-like residual aberrations. This later method is limited in its ability to simulate atmospheric disturbances, but it is easy and inexpensive to implement. With these two methods, individually or in unison, we can simulate typical atmospheric disturbances observed at the Bohyun Observatory in South Korea, which corresponds to an area from 7 to 15 cm with regard to the Fried parameter at a telescope pupil plane of 500 nm.

• Korean Journal of Optics and Photonics
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• v.32 no.3
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• pp.120-125
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• 2021

We have developed a linearly polarized high-power Yb-doped fiber laser in the master oscillator power amplifier (MOPA) scheme for efficient spectral beam combining. We modulated the phase of the seed laser by pseudo-random binary sequence (PRBS), with the bit length optimized to suppress stimulated Brillouin scattering (SBS), and subsequently amplified seed power in a 3-stage amplifier system. We have constructed by coiling the polarization-maintaining (PM) Yb-doped fiber, with core and cladding diameters of 20 ㎛ and 400 ㎛ respectively, to a diameter of 9-12 cm for suppression of the mode instability (MI). Finally, we obtained an output power of 1.004 kW with a slope efficiency of 83.7% in the main amplification stage. The beam quality factor M² and the polarization extinction ratio (PER) were measured to be 1.12 and 21.5 dB respectively. Furthermore, the peak-intensity difference between the Rayleigh signal and SBS signal was observed to be 2.36 dB in the backward spectra, indicating that SBS is successfully suppressed. In addition, it can be expected that the MI does not occur because not only there is no decrease in slope efficiency, but also the beam quality for each amplified output is maintained.