• The Transactions of the Korea Information Processing Society
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• v.5 no.7
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• pp.1943-1950
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• 1998

Irregular addressing scheme of gray scale control for the memory type flat panel plasma display is proposed in this paper. Opposed to the conventional addressing method. the scan electrodes are addressed in non-sequential manner. The addressing order for this irregular addressing is resolved to make the pixel duty factor above 90%. This addressing scheme can achieve the prolxJsed peformance regardless of the panel and cell structure and can be implemented without increasing the chive voltage, current or frequency .

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.665-666
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• 2022

반려동물의 이상행동 탐지를 위한 센서 데이터를 수집하는 과정에서 발생하는 시간과 비용의 문제로 인해 데이터 증강이 요구되고 있다. 본 논문에서는 통계적 변형과 GAN 기반의 데이터 증강을 통해 반려동물의 정상행동과 이상행동으로 분류하는 방법을 제안한다. 통계적 변형은 회전, 순열, 조합 등을 이용하며, GAN을 통해 원본 데이터에 노이즈가 포함된 유사한 데이터를 생성한다. 증강된 모든 데이터는 원본 데이터와 함께 학습 데이터로 사용한다. 최종적으로, LSTM의 단점을 보완한 Convolutional LSTM 모델을 통해 반려동물의 정상행동 인식의 범주를 넓혀 보다 정확한 이상행동을 인식하고자 한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.647-657
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• 2006

Probabilistic Risk Assessment considering statistically random variables is performed for the preliminary design of a Cable Stayed Bridge, which is Prestressed Concrete Bridge consisted of cable and plate girders, based on the method of Working Stress Design and Strength Design. Component reliabilities of cables and girders have been evaluated using the response surface of the design variables at the selected critical sections based on the maximum shear, positive and negative moment locations. Response Surface Method (RSM) is successfully applied for reliability analyses for this relatively small probability of failure of the complex structure, which is hard to obtain through Monte-Carlo Simulations. or through First Order Second Moment Method that can not easily calculate the derivative terms of implicit limit state functions. For the analysis of system reliability, parallel resistance system consisting of cables and plate girder is changed into series connection system and the result of system reliability of total structure is presented. As a system reliability, the upper and lower probabilities of failure for the structural system have been evaluated and compared with the suggested prediction method for the combination of failure modes. The suggested prediction method for the combination of failure modes reveals the unexpected combinations of element failures in significantly reduced time and efforts compared with the previous permutation method or system reliability analysis method, which calculates upper and lower bound failure probabilities.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.51-70
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• 2017

The reliability of broadcasting over vehicular ad hoc networks (VANETs) is one of the most critical factors for driving safety applications. There exists limitations to improve the reliability of broadcast transmissions in saturated VANETs where previous proposals in literature tackle the problem by heuristically adapting the size of the contention window (CW). This paper considers improving the reliability by proposing a new probability model based on the counting methods of permutations and combinations, which counts all the possible cases of broadcast failures in a single-hop broadcast transmission for a given CW. From the model, we calculate the best CW size given the number of contention nodes, which significantly improves the reliability and satisfying the timely dissemination of emergency broadcasting messages. Through extensive VANET simulations with varying densities, we show that our model maintains near 100 percent success rate for single-hop broadcast as well as multi-hop broadcast (e.g. 40 hops) and achieves minimal broadcast delay.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.536-543
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• 2023

Speaker diarization, which labels for "who spoken when?" in speech with multiple speakers, has been studied on a deep neural network-based end-to-end method for labeling on speech overlap and optimization of speaker diarization models. Most deep neural network-based end-to-end speaker diarization systems perform multi-label classification problem that predicts the labels of all speakers spoken in each frame of speech. However, the performance of the multi-label-based model varies greatly depending on what the threshold is set to. In this paper, it is studied a speaker diarization system using single-label classification so that speaker diarization can be performed without thresholds. The proposed model estimate labels from the output of the model by converting speaker labels into a single label. To consider speaker label permutations in the training, the proposed model is used a combination of Permutation Invariant Training (PIT) loss and cross-entropy loss. In addition, how to add the residual connection structures to model is studied for effective learning of speaker diarization models with deep structures. The experiment used the Librispech database to generate and use simulated noise data for two speakers. When compared with the proposed method and baseline model using the Diarization Error Rate (DER) performance the proposed method can be labeling without threshold, and it has improved performance by about 20.7 %.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.585-594
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• 2009

Researchers of microarray experiment transpose processed images of raw data to possible data of statistical analysis: it is preprocessing. Preprocessing of microarray has image filtering, imputation and normalization. There have been studied about several different methods of normalization and imputation, but there was not further study on the order of the procedures. We have no further study about which things put first on our procedure between normalization and imputation. This study is about the identification of differentially expressed genes(DEG) on the order of the preprocessing steps using two-dye cDNA microarray in colon cancer and gastric cancer. That is, we check for compare which combination of imputation and normalization steps can detect the DEG. We used imputation methods(K-nearly neighbor, Baysian principle comparison analysis) and normalization methods(global, within-print tip group, variance stabilization). Therefore, preprocessing steps have 12 methods. We identified concordance measure of DEG using the datasets to which the 12 different preprocessing orders were applied. When we applied preprocessing using variance stabilization of normalization method, there was a little variance in a sensitive way for detecting DEG.