• Journal of KIISE:Computer Systems and Theory
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• v.28 no.5
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• pp.213-217
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• 2001

Excessive memory buffer requirement in continuous media playback is a serious impediment of wide spread usage of on-line multimedia service. Skewed access frequency of available video files provides an opportunity of re-using the date blocks which has been loaded by one session for later usage. We present novel algorithm which minimizes the buffer requirement in multiple sessions of multimedia playbacks. In continuous media playback originated from the disk, a certain amount of memory buffer is required to synchronize asynchronous disk. Read operation and synchronous playback operation. As aggregate playback bandwodth increases, larger amount of buffer needs to be allocated for this synchronization purpose. The focus of this work is to study the asymptotic behavior of the synchronization buffer requirement and to develop an algorithm coping with this excessive buffer requirement under bandwidth congestioon. We argue that in a large scale continuous media server, it may not be necessary to read the blocks for each session directly from the disk. The beauty of our work lies in the fact that it dynamically adapts to disk utilization of the server and finds the optimal way of servicinh the individual sessions while minimizing the overall buffer space requirement. Optimality of the proposed algorithm is shown by proof. The effectiveness and performance of the proposed scheme is examined via simulation.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.155-163
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• 2009

In text-to-speech systems, the conversion of text into prosodic parameters is necessarily composed of three steps. These are the placement of prosodic boundaries. the determination of segmental durations, and the specification of fundamental frequency contours. Prosodic boundaries. as the most important and basic parameter. affect the estimation of durations and fundamental frequency. Break prediction is an important step in text-to-speech systems as break indices (BIs) have a great influence on how to correctly represent prosodic phrase boundaries, However. an accurate prediction is difficult since BIs are often chosen according to the meaning of a sentence or the reading style of the speaker. In Japanese, the prediction of an accentual phrase boundary (APB) and major phrase boundary (MPB) is particularly difficult. Thus, this paper presents a method to complement the prediction errors of an APB and MPB. First, we define a subtle BI in which it is difficult to decide between an APB and MPB clearly as a variable break (VB), and an explicit BI as a fixed break (FB). The VB is chosen using the classification and regression tree, and multiple prosodic targets in relation to the pith and duration are then generated. Finally. unit-selection is conducted using multiple prosodic targets. In the MOS test result. the original speech scored a 4,99. while proposed method scored a 4.25 and conventional method scored a 4.01. The experimental results show that the proposed method improves the naturalness of synthesized speech.

• Journal of Navigation and Port Research
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• v.35 no.1
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• pp.45-49
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• 2011

The recent trend for numerical experiment requires more higher resolution and accuracy. Generally, in the wave field calculation, it starts with a large region formulation first and follows by a separated detailed region formulation by more denser grids for the main interest area considering the geographical and bathymetrical variation. The wave fields resulted from the large region calculation is being introduced into the detail region calculation as the incident waves. In this process there exists a problem of continuity. In order to get over such problem, method of variable gridding system or spectrum sampling, etc., is being used. However, it seems not enough to examine and analyze the related numerical errors. Therefore, it is investigated in this study the field applicability of the most pervasive use of wave model, the nested SWAN model. For this purpose, we made model experiment for two coastal harbours with different tidal environment, and compared and analyzed the result. From the analysis, it was found that both the extracted values, near the boundaries of the large and detail region and the nested formulation of SWAN model, show almost the same and no different between those with different tidal environment conditions. However it is necessary for reducing the numerical errors to set the boundaries for the detailed region outside of the rapid bathymetric change and deeper region.

• Proceedings of the Korean Reliability Society Conference
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• 2000.11a
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• pp.257-267
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• 2000

Mostly, the economic analyses for replacement of major components of nuclear power Plants(NPPs) have been performed in deterministic ways. However, the analysis results are more or less affected by the uncertainties associated with input variables. Therefore, it is desirable to use a probabilistic economic analysis method to properly consider uncertainty of real problem. In this paper, the probabilistic economic analysis method and decision analysis technique are briefly described. The probabilistic economy analysis method using decision analysis will provide efficient and accurate way of economic analysis for the repair and/or replace mai or components of NPPs.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.2
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• pp.217-229
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• 2000

Adsorption equilibrium experiments for the phenol on granular activated carbon(16~25 mesh) and powder activated carbon(325 mesh) were carried out at $25{\pm}1^{\circ}C$ and the results were expressed with Freundlich isotherm. Adsorption rate experiments were executed in batch adsorption system under the condition that can be neglecting mass transfer resistance at the external surface of the particle. The results were analysed with the Miller's method to evaluate the linear driving force(LDF) adsorption rate constant. Fixed bed adsorption experiments were performed by adopting different flow rates in the activated carbon-phenol system at $25{\pm}1^{\circ}C$. The theoretical breakthrough curves were estimated with the simple constant pattern solution. The adsorption rate constant of LDF model was not a fixed value but variable with adsorption amount. The experimental results were better agreed with the estimation of breakthrough curve using the variable adsorption rate constant than the results estimated using the average fixed adsorption rate constant.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.5
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• pp.243-254
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• 2005

Soft real-time applications such as multimedia feature highly variable processor requirements and probabilistic guarantees on deadline misses, meaning that each task in the application meets its deadline with a given probability. Thus, for such soft real-time applications, a system designer may want to improve the system utilization by allocating to each task a processor time less than its worst-case requirement, as long as the imposed probabilistic timing constraint is met. In this case, however, we have to address how to schedule jobs of a task that require more than (or, overrun) the allocated processor time to the task. In this paper, to address the overrun problem, we propose an overrun control method, which probabilistically controls the execution of overrunning jobs. The proposed overrun control method probabilistically allows overrunning jobs to complete for better system utilization, and also probabilistically prevents the overrunning jobs from completing so that the required probabilistic timing constraint for each task can be met. In the paper, we show that the proposed method outperforms previous methods proposed in the literature in terms of the overall deadline miss ratio, and that it is possible to synthesize the scheduling parameters of our method so that all tasks can meet the given probabilistic timing constraints.

• The Journal of the Acoustical Society of Korea
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• v.22 no.6
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• pp.457-462
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• 2003

In this paper, we propose a speaker pruning method for real-time processing and improving performance of speaker identification system based on GMM(Gaussian Mixture Model). Conventional speaker identification methods, such as ML (Maximum Likelihood), WMR(weighting Model Rank), and MWMR(Modified WMR) we that frame likelihoods are calculated using the whole frames of each input speech and all of the speaker models and then a speaker having the biggest accumulated likelihood is selected. However, in these methods, calculation cost and processing time become larger as the increase of the number of input frames and speakers. To solve this problem in the proposed method, only a part of speaker models that have higher likelihood are selected using only a part of input frames, and identified speaker is decided from evaluating the selected speaker models. In this method, fm can be applied for improving the identification performance in speaker identification even the number of speakers is changed. In several experiments, the proposed method showed a reduction of 65% on calculation cost and an increase of 2% on identification rate than conventional methods. These results means that the proposed method can be applied effectively for a real-time processing and for improvement of performance in speaker identification.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.261-261
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• 2020

물관리의 기본이 되는 연속적인 유량 자료 확보를 위해서는 정확도 높은 수위-유량 관계 곡선식 개발이 필수적이다. 수위-유량 관계곡선식은 모든 수문시설 설계의 기초가 되며 홍수, 가뭄 등 물재해 대응을 위해서도 중요한 의미를 가지고 있다. 그러나 일반적으로 유량 측정은 많은 비용과 시간이 들고, 식생성장, 단면변화 등의 통제특성(control)이 변함에 따라 구간분리, 기간분리와 같은 비선형적인 양상이 나타나 자료 해석에 어려움이 존재한다. 특히, 국내 하천의 경우 자연적 및 인위적인 환경 변화가 다양하여 지점 및 기간에 따라 세밀한 분석이 요구된다. 머신러닝(Machine Learning)이란 데이터를 통해 컴퓨터가 스스로 학습하여 모델을 구축하고 성능을 향상시키는 일련의 과정을 뜻한다. 기존의 수위-유량 관계곡선식은 개발자의 판단에 의해 데이터의 종류와 기간 등을 설정하여 회귀식의 파라미터를 산출한다면, 머신러닝은 유효한 전체 데이터를 이용해 스스로 학습하여 자료 간 상관성을 찾아내 모델을 구축하고 성능을 지속적으로 향상 시킬 수 있다. 머신러닝은 충분한 수문자료가 확보되었다는 전제 하에 복잡하고 가변적인 수자원 환경을 반영하여 유량 추정의 정확도를 지속적으로 향상시킬 수 있다는 이점을 가지고 있다. 본 연구는 머신러닝의 대표적인 알고리즘들을 활용하여 유량을 추정하는 모델을 구축하고 성능을 비교·분석하였다. 대상지역은 안정적인 수량을 확보하고 있는 한강수계의 거운교 지점이며, 사용자료는 2010~2018년의 시간, 수위, 유량, 수면폭 등 이다. 프로그램은 파이썬을 기반으로 한 머신러닝 라이브러리인 사이킷런(sklearn)을 사용하였고 알고리즘은 랜덤포레스트 회귀, 의사결정트리, KNN(K-Nearest Neighbor), rgboost을 적용하였다. 학습(train) 데이터는 입력자료 종류별로 조합하여 6개의 세트로 구분하여 모델을 구축하였고, 이를 적용해 검증(test) 데이터를 RMSE(Roog Mean Square Error)로 평가하였다. 그 결과 모델 및 입력 자료의 조합에 따라 3.67~171.46로 다소 넓은 범위의 값이 도출되었다. 그 중 가장 우수한 유형은 수위, 연도, 수면폭 3개의 입력자료를 조합하여 랜덤포레스트 회귀 모델에 적용한 경우이다. 비교를 위해 동일한 검증 데이터를 한국수문조사연보(2018년) 내거운교 지점의 수위별 수위-유량 곡선식을 이용해 유량을 추정한 결과 RMSE가 3.76이 산출되어, 머신러닝이 세분화된 수위-유량 곡선식과 비슷한 수준까지 성능을 내는 것으로 확인되었다. 본 연구는 양질의 유량자료 생산을 위해 기 구축된 수문자료를 기반으로 머신러닝 기법의 적용 가능성을 검토한 기초 연구로써, 국내 효율적인 수문자료 측정 및 수위-유량 곡선 산출에 도움이 될 수 있을 것으로 판단된다. 향후 수자원 환경 및 통제특성에 영향을 미치는 다양한 영향변수를 파악하기 위해 기상자료, 취수량 등의 입력 자료를 적용할 필요가 있으며, 머신러닝 내 비지도학습인 딥러닝과 같은 보다 정교한 모델에 대한 추가적인 연구도 수행되어야 할 것이다.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.3
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• pp.98-106
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• 1997

In this paper, a new method of position synchronizing control is proposed for multi-axes driving system. The proposed position synchronizing control system is constituted with speed and synchronizing controller. The speed controller is aimed at the following to speed reference. Furthermore, it is designed to guarantee low sensitivity under some disturbance as well as robustness against model uncertainties using $H_{\infty}$technique. The synchronizing controller is designed to keep minimizing the position error using PID control law which is considered to reduce the dimension of transfer function in the control system. Especially, the proposed method can be easily conducted by controlling only slave axis speed, because it, has variable structure which is decided to master and slave axis by the sign of synchronizing error. Therfore, the master axis which is smaller influenced than another axes by disturbance can be controlled without reducing or increasing its speed for precise position synchronization. The effectiveness of the proposed method is sucessfully confirmed through many experiments.s.

• Journal of the Korea Computer Industry Society
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• v.6 no.5
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• pp.801-812
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• 2005

H.264/AVC is the international video coding standard which has significant improvements of coding efficiency. ITU-T(International Telecommunication Union-Telecommunication standardization sector) and MPEG(Moving Picture Experts Group) adopts various complex coding tool such as variable block size motion, multiple reference frames, quarter-pel motion estimation/compensation (ME/MC) and rate-distortion(RD) optimization, etc. H.264 reference model employs complex mode decision technique based on RD optimization which requires high computational complexity. In this paper, we propose an efficient coding mode decision based on the cost distribution of RD in the macroblock coding mode sequence. Simulation results show that the proposed method reduces encoding time by 34% on average and save the number of computing RD cost by 82%.