• Review of KIISC
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• v.16 no.3
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• pp.63-74
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• 2006

본 논문에서는 한국 산업규격 KS 표준 블록암호 알고리즘인 ARIA의 핵심논리들을 64비트 프로세서 환경에서 효율적으로 구현하는 방법을 제안하고, 제안된 방법으로 구현된 ARIA를 대표적인 64비트 마이크로프로세서인 Intel Pentium4 x64, Intel Itanium, Intel XEON(EM64T)을 이용하여 그 효율성을 평가하였으며, 32비트 프로세서에 적합하게 구현된 ARIA와 효율성을 비교하고 문제점을 분석하였다.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.441-450
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• 2003

Collaborative filtering is one of the most widely used methodologies for recommendation system. Collaborative filtering is based on a data matrix of each customer's preferences and frequently, there exits missing data problem. We introduced two imputation approach (multiple imputation via Markov Chain Monte Carlo method and multiple imputation via bootstrap method) to improve the prediction performance of collaborative filtering and evaluated the performance using EachMovie data.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.265-267
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• 2000

본 논문에서는 텍스트 문서의 주제어를 추출하고 문서를 주제별로 분류하기 위해 확률적 그래프 모델을 사용하는 방법을 제안하였다. 텍스트 문서 데이터를 문서와 단어의 쌍으로(dyadic)표현하여 확률적 생성 모델을 학습하였다. 확률적 그래프 모델의 학습에는 정의된 likelihood를 최대화하기 위한 EM(Expected Maximization)알고리즘을 사용하였다. TREC-8 AdHoc 텍스트 에이터에 대하여 학습된 확률 그래프 모델의 성능을 실험적으로 평가하였다. 이로부터 찾아 낸 문서에 대한 주제어가 사람이 제시한 주제어와 유사한 지와, 사람이 각 주제에 대해 분류한 문서가 이 확률모델로부터의 분류와 유사한 지를 실험적으로 검토하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.391-392
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• 2022

본 논문에서는 SparkHDE-EM이라는 생태학적 모델 알고리즘에 기반한 하이브리드 DE를 제안한다. 그리고 Spark 기반 아일랜드 모델을 도입하여 다양한 DE 변종의 병렬화를 구현한다. 또한 Monod 모델을 활용하여 자원 간의 균형을 유지하는 방법을 제안한다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.10
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• pp.1021-1030
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• 2009

We propose optimization method of two-inductor loaded small loop antennas using simple genetic algorithm. To optimize the loop antennas for the RFID and the mobile phone band, we changed positions and values of the two inductors in the loop antenna. Visual basic was used to make genetic algorithm and to calculate fitness values by controlling the commercial EM software. The bandwidth of the optimized RFID loop antenna is 10 MHz at the center frequency of 922 MHz and that of the mobile phone antenna are 84 MHz and 266 MHz at the center frequency of 948 MHz(GSM band) and 1.81 GHz(DCS band), respectively.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.183-196
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• 2012

The inference for incomplete data such as missing data, truncated distribution and censored data is a phenomenon that occurs frequently in statistics. To solve this problem, Expectation Maximization(EM), Monte Carlo Expectation Maximization(MCEM) and Stochastic Expectation Maximization(SEM) algorithm have been used for a long time; however, they generally assume known distributions. In this paper, we propose the Metropolis-Hastings Expectation Maximization(MHEM) algorithm for unknown distributions. The performance of our proposed algorithm has been investigated on simulated and real dataset, KOSPI 200.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.21-30
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• 2014

Ordinary survival analysis cannot be applied when a significant fraction of patients may be cured. A cure rate model is the combination of cure fraction and survival model and can be applied to several types of cancer. In this article, the cure rate model is considered in the interval censored data with a cluster effect. A shared frailty model is introduced to characterize the cluster effect and an EM algorithm is used to estimate parameters. A simulation study is done to evaluate the performance of estimates. The proposed approach is applied to the smoking cessation study in which the event of interest is a smoking relapse. Several covariates (including intensive care) are evaluated to be effective for both the occurrence of relapse and the smoke quitting duration.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.493-497
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• 2016

Infrared (IR) imaging is capable of detecting targets that are not visible at night, thus it has been widely used for the security and defense system. However, the quality of the IR image is often degraded by low resolution and noise corruption. This paper addresses target segmentation with the IR image. Multiple regions of interest (ROI) are extracted by the multi-level segmentation and targets are segmented from the individual ROI. Each level of the multi-level segmentation is composed of a k-means clustering algorithm an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering algorithm initializes the parameters of the Gaussian mixture model (GMM) and the EM algorithm iteratively estimates those parameters. Each pixel is assigned to one of clusters during the decision. This paper proposes the selection and the merging of the extracted ROIs. ROI regions are selectively merged in order to include the overlapped ROI windows. In the experiments, the proposed method is tested on an IR image capturing two pedestrians at night. The performance is compared with conventional methods showing that the proposed method outperforms others.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.379-393
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• 2020

A terminal event such as death may censor an intermediate event such as relapse, but not vice versa in semi-competing risks data, which is often seen in medicine, public health, and epidemiology. We propose a Weibull regression model with a normal frailty to analyze semi-competing risks data when all three transition times of the illness-death model are possibly interval-censored. We construct the conditional likelihood separately depending on the types of subjects: still alive with or without the intermediate event, dead with or without the intermediate event, and dead with the intermediate event missing. Optimal parameter estimates are obtained from the iterative quasi-Newton algorithm after the marginalization of the full likelihood using the adaptive importance sampling. We illustrate the proposed method with extensive simulation studies and PAQUID (Personnes Agées Quid) data.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.99-105
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• 2017

Generally, stereo matching methods are used to estimate depth information based on color and spatial similarity. However, most depth estimation methods suffer from the occlusion region because occlusion regions cause inaccurate depth information. Moreover, they do not consider the temporal dimension when estimating the disparity. In this paper, we propose a temporal stereo matching method, considering occlusion and disregarding inaccurate temporal depth information. First, we apply a global stereo matching algorithm to estimate the depth information, we segment the image to occlusion and non-occlusion regions. After occlusion detection, we fill the occluded region with a reasonable disparity value that are obtained from neighboring pixels of the current pixel. Then, we apply a temporal disparity estimation method using the reliable information. Experimental results show that our method detects more accurate occlusion regions, compared to a conventional method. The proposed method increases the temporal consistency of estimated disparity maps and outperforms per-frame methods in noisy images.