• KIPS Transactions on Software and Data Engineering
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• v.2 no.4
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• pp.273-280
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• 2013

This paper presents novel OCS-LBP (Oriented Center Symmetric Local Binary Patterns) based on orientation of pixel gradient and image retrieval system based on BoF (Bag-of-Feature) and random forest classifier. Feature vectors extracted from training data are clustered into code book and each feature is transformed new BoF feature using code book. BoF features are applied to random forest for training and random forest having N classes is constructed by combining several decision trees. For testing, the same OCS-LBP feature is extracted from a query image and BoF is applied to trained random forest classifier. In contrast to conventional retrieval system, query image selects similar K-nearest neighbor (K-NN) classes after random forest is performed. Then, Top K similar images are retrieved from database images that are only labeled K-NN classes. Compared with other retrieval algorithms, the proposed method shows both fast processing time and improved retrieval performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.837-842
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• 2010

In this paper, quantum cryptography systems used in the design process inevitably open bit stream of pseudo-random number that exists multiple open channels between them and the need to share information on the part of the situation exposes a pair of bit stream. In this paper, the base test of pseudo-random number I tested out this process and the merge bit binary column look out for randomness.

• Journal of the Korean Mathematical Society
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• v.59 no.2
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• pp.217-233
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• 2022

Although machine learning shows state-of-the-art performance in a variety of fields, it is short a theoretical understanding of how machine learning works. Recently, theoretical approaches are actively being studied, and there are results for one of them, margin and its distribution. In this paper, especially we focused on the role of margin in the perturbations of inputs and parameters. We show a generalization bound for two cases, a linear model for binary classification and neural networks for multi-classification, when the inputs have normal distributed random noises. The additional generalization term caused by random noises is related to margin and exponentially inversely proportional to the noise level for binary classification. And in neural networks, the additional generalization term depends on (input dimension) × (norms of input and weights). For these results, we used the PAC-Bayesian framework. This paper is considering random noises and margin together, and it will be helpful to a better understanding of model sensitivity and the construction of robust generalization.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.589-598
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• 2015

In longitudinal studies missing data are common and require a complicated analysis. There are two popular modeling frameworks, pattern mixture model (PMM) and selection models (SM) to analyze the missing data. We focus on the PMM and we also propose Bayesian pattern mixture models using generalized linear mixed models (GLMMs) for longitudinal binary data. Sensitivity analysis is used under the missing not at random assumption.

• Korean Journal of Optics and Photonics
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• v.33 no.6
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• pp.267-274
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• 2022

In this paper, we report the design and fabrication of binary diffractive optical elements (DOEs) for random-dot-pattern projection for Schlieren imaging. We selected the binary phase level and a pitch of 10 ㎛ for the DOE, based on cost effectiveness and ease of manufacture. We designed the binary DOE using an iterative Fourier-transform algorithm with binary phase optimization. During initial optimization, we applied a computer-generated pseudorandom dot pattern of uniform intensity as a target pattern, and found significant intensity nonuniformity across the field. Based on the evaluation of the initial optimization, we weighted the target random dot pattern with Gaussian profiles to improve the intensity uniformity, resulting in the improvement of uniformity from 52.7% to 90.8%. We verified the design performance by fabricating the designed binary DOE and a beam projector, to which the same was applied. The verification confirmed that the projector produced over 10,000 random dot patterns over 430 mm × 430 mm at a distance of 5 meters, as designed, but had a slightly less uniformity of 84.5%. The fabrication errors of the DOE, mainly edge blurring and spacing errors, were strong possibilities for the difference.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.9-17
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• 2004

We present a performance improvement of Binary CDMA by flattening the correlation values. A Binary CDMA system, in which multi-leveled transmission signal of multi-code CDMA is clipped into a binary value, is cost-efficient since the strict linearity of the power amplifier is relieved. However, a loss of orthogonality among user channels due to the clipping causes the correlation values at the receiver to have a random distribution. If the correlation value for even a single channel goes too low, the average BER drops considerably. We developed a method of correlation flattening, where the binary chip pattern at the transmitter is adjusted so that the correlation values have averaged magnitude. Experimental results on several spreading codes show that the correlation flattening method increases the number of available channels at reduced BER.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1A
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• pp.49-57
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• 2011

Random access method for Wibro system is proposed using the Bayesian Technique, which can estimate the number of bandwidth request messages in a frame only based on the number of successful slots. The performance measures such as the maximum average throughput, the mean delay time and the collision ratio are investigated to evaluate the performance of the proposed method. The proposed method shows better performance than the binary exponential backoff algorithm used currently.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1147-1152
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• 2012

In this paper, it is key issue about analysis of characteristics processing of digital random output stream of hardware random number generator, which is applied in medical area. The output stream of random number generator based on hardware binary random number is effected from factors such as delay, jitter, temperature, and so on. In this paper, it presents about major factor, which effects hardware output random number stream, and the randomness of output stream data, which are combined output stream and postprocessing data such as encryption algorithm, encoding algorithm, is analyzed. the analyzed results are evaluated by major test items of randomness.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.28-36
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• 2017

The medium access control (MAC) protocol based on dynamic time division multiple access/time division duplex (TDMA/TDD) is responsible for random access control and radio resource allocation in dynamic traffic environments. These functions of random access and resource allocation are very important to prevent wastage of resources and improve MAC performance according to various network conditions. In this paper, we propose new random access and resource allocation schemes to guarantee quality of service (QoS) and provide priority services in a dynamic TDMA/TDD system. First, for the QoS guarantee, we propose an adaptive random access and resource allocation scheme by introducing an access probability. Second, for providing priority service, we propose a priority-based random access and resource allocation scheme by extending the first adaptive scheme in both a centralized and a distributed manner. The analysis and simulation results show that the proposed MAC protocol outperforms the legacy MAC protocol using a simple binary exponential backoff algorithm, and provides good differential performance according to priorities with respect to the throughput and delay.

• Journal of Korean Ophthalmic Optics Society
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• v.10 no.4
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• pp.305-312
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• 2005

In this thesis, Lohmann's algorithm and FFT (fast Fourier transform) are used to synthesize binary-phase holograms. FFT computing is carried out for the calculation of complex wavefronts of $128{\times}128$ sampling points of an object that is numerically specified. Then using the Lohmann's algorithm, the amplitude and the phase of complex wavefronts are encoded in binary holograms on each sampling points. PC (personal computer) and laser printer are used to plot binary-phase holograms and CGH (computer generated holograms) films are obtained from this plot by photographic reduction. Holographic images of numerically specified objects are reconstructed from the He-Ne laser and the inverse Fourier optics system. We estimate the quality of holographic images according to the sampling number, application of random phase, amplitude clipping and bleaching the CGH film. We derive optimized conditions to reconstruct better holographic images and to reduce the speckle noise. FFT and Lohmann's algorithm are implemented with MS Visual BASIC 6.0 for the programming of binary-phase hologram.