• 한국정보처리학회논문지
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• 제7권5S호
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• pp.1666-1675
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• 2000

본 논문에서는 전자상거래 시스템에서 요구하는 상호운용성과 실시간 요구사항들을 지원할 수 있는 실시간 웹 미들웨이(RTWM Real-Time Web Middleware) 프레임워크를 제안한다. RTWM시스템은 전자상거래 시스템의 실시간 요구사항들을 지원하기 위해CORBA 객체 서비스 구조를 확장하여 이벤트 모니터, 실시간 스케줄러, 실시간 이벤트 서비스 등의 객체 컴포넌트를 포함하는 구조를 가진다. 특히, 본 논문에서는 전자상거래 사용자의 실시간 요구사항을 지원할 수 있는 실시간 이벤트 필터링을 제공하는 것에 중점을 두었다. 사용자로부터 시간적 제약조건과 원하는 이벤트 정보를 입력받아 QoS저장소에 저장하고, 실시간 이벤트가 발생하며RTFA(Real-Time Fitering Agent)를 통해 소비자가 원하는 이벤트를 필터링하여 제공하게 된다. 이로써 사용자는 보다 높은 서비스를 제공받게 되고 이 과정을 통해 전체적인 네트워크 트래픽이 감소되는 효과를 얻을 수 있다.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.336-343
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• 2017

We propose a real time personalized recommendation algorithm on the mobile device. We use a unified collaborative filtering with reduced data. We use Fuzzy C-means clustering to obtain the reduced data and Konohen SOM is applied to get initial values of the cluster centers. The proposed algorithm overcomes data sparsity since it extends data to the similar users and similar items. Also, it enables real time service on the mobile device since it reduces computing time by data clustering. Applying the suggested algorithm to the MovieLens data, we show that the suggested algorithm has reasonable performance in comparison with collaborative filtering. We developed Android-based smart-phone application, which recommends restaurants with coupons and restaurant information.

• 한국멀티미디어학회논문지
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• 제22권6호
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• pp.695-705
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• 2019

The level of psychological damage caused by verbal abuse among cyberbully victims is very serious. It is going to introduce a system that determines the level of sanctions against chatting in real time using the automatic prohibited words filtering based on artificial neural network. In this paper, we propose a keyword filtering method that detects the modified prohibited words and determines whether the corresponding chat should be sanctioned in real time, and a real-time chatting screening system using it. The accuracy of filtering through machine learning was improved by processing data in advance through coding techniques that express consonants and vowels of similar pronunciation at close distances. After comparing and analyzing Mahalanobis-based clustering algorithms and artificial neural network-based algorithms, algorithms that utilize artificial neural networks showed high performance. If it is applied to Internet chatting, comments or online games, it is expected that it will be able to filter more effectively than the existing filtering method and that this will ease communication inconvenience due to existing indiscriminate filtering methods.

• ETRI Journal
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• 제28권4호
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• pp.509-512
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• 2006

In a real environment, sound recordings are commonly distorted by channel and background noise, and the performance of audio identification is mainly degraded by them. Recently, Philips introduced a robust and efficient audio fingerprinting scheme applying a differential (high-pass filtering) to the frequency-time sequence of the perceptual filter-bank energies. In practice, however, the robustness of the audio fingerprinting scheme is still important in a real environment. In this letter, we introduce alternatives to the frequency-temporal filtering combination for an extension method of Philips' audio fingerprinting scheme to achieve robustness to channel and background noise under the conditions of a real situation. Our experimental results show that the proposed filtering combination improves noise robustness in audio identification.

• International Journal of Quality Innovation
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• 제2권1호
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• pp.30-49
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• 2001

This paper considers a recent environment in the manufacturing process in which data in large amounts can be obtained on-line in real-time. Under this environment an on-line real-time Statistical Process Control (SPC) scheme equipped with detection of a process change, change-point estimation, and recognition of the change pattern is proposed. The proposed SPC scheme is composed of a Cusum chart, filtering methods and Akaike Information Criterion (AIC). We examine the performance of this scheme by Monte Carlo simulation and show its usefulness.

• 한국지능시스템학회논문지
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• 제17권4호
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• pp.488-493
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• 2007

추천 시스템은 일반적으로 서비스를 추천하기 위해 협력적 필터링 단계에서 실시간으로 얻어진 컨텍스트 정보를 정량화하여 사용하고 있다. 하지만 이러한 추천시스템은 컨텍스트 정보의 부족으로 부정확한 추천 결과를 가져오거나, 정량화 단계의 단순한 분류과정으로 인해 사용자를 부정확한 그룹으로 분류하는 문제점이 발생한다. 본 논문에서는 실시간으로 획득되는 컨텍스트 정보 부족 문제를 내용 기반 필터링에서 사용하는 사용자 프로파일 정보와 실시간으로 획득된 컨텍스트 정보를 결합하여 해결하였다. 그리고 정량화 단계의 분류 과정을 절대적인 방법이 아니라 상대적인 방법으로 개선하여 협력적 필터링하였다. 실험 결과, pure P2P 환경에서 컨텍스트 정보를 이용한 실시간 추천 시스템보다 예측 선호도가 5.8% 향상되었다.

• 대한음성학회지:말소리
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• 제51호
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• pp.85-98
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• 2004

It is almost impossible to generate the sound field effect in real time with the time-domain linear convolution because of its large multiplication operation requirement. To solve this, three methods are introduced to reduce the number of multiplication operations in this paper. Firstly, the time-domain linear convolution is replaced with the frequency-domain circular convolution. In other words, the linear convolution result can be derived from that of the circular convolution. This technique reduces the number of multiplication operations remarkably, Secondly, a subframe concept is introduced, i.e., one original frame is divided into several subframes. Then the FFT is executed for each subframe and, as a result, the number of multiplication operations can be reduced. Finally, the QFT is used in stead of the FFT. By combining all the above three methods into our final the SFE generation algorithm, the number of computations are reduced sufficiently and the real-time SFE generation becomes possible with a general PC.

• 대한교통학회지
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• 제14권3호
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• pp.7-26
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• 1996

The estimation of real-time Origin-Destination(O-D) parameters, which gives travel demand between combinations of origin and destination points on a urban freeway network, from on-line surveillance traffic data is essential in developing an efficient ATMS strategy. On this need a real-time O-D parameter estimation model is formulated as a parameter adaptive filtering model based on the extended Kalman Filter. A Monte Carlo test have shown that the estimation of time-varying O-D parameter is possible using only traffic counts. Tests with field data produced the interesting finding that off-ramp volume predictions generated using a constant freeway O-D matrix was replaced by real-time estimates generated using the parameter adaptive filter.

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.456-465
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• 2006

The problem of recursive filtering far linear discrete-time systems with uncertainties is considered. A new suboptimal filtering algorithm is herein proposed. It is based on the fusion formula, which represents an optimal mean-square linear combination of local Kalman estimates with weights depending on cross-covariances between local filtering errors. In contrast to the optimal weights, the suboptimal weights do not depend on current measurements, and thus the proposed algorithm can easily be implemented in real-time. High accuracy and efficiency of the suboptimal filtering algorithm are demonstrated on the following examples: damper harmonic oscillator motion and vehicle motion constrained to a plane.

• International Journal of Control, Automation, and Systems
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• 제1권4호
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• pp.515-519
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• 2003

This paper proposes a new image sequence stabilization (ISS) scheme based on filtering of absolute frame positions. The proposed ISS scheme removes undesired motion effects in real-time, while preserving desired gross camera displacements. The well-known finite impulse response (FIR) filter is adopted for filtering. The proposed ISS scheme provides a filtered position and velocity with fine inherent properties. It is demonstrated that the filtered position is not affected by the constant velocity. It is also shown that the filtered velocity is separated from the position. Via numerical simulations, the performance of the proposed scheme is shown to be superior to the existing Kalman filtering scheme.