• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9A
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• pp.1535-1541
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• 2001

TCP is the most widely-used transport layer protocol in current Internet, while ATM technology is used to increase the data communication speed at data link layer and network layer. In the TCP-over-ATM architecture, the most significant problems are (i) the partial packet discarding problem, and (ii) the TCP window timeout problem. Several approaches have been proposed to solve the partial packet discard problem and the timeout problem individually, but none of them considered the two problems together. In this paper, we propose an enhanced UBR+ scheme which supports fairness among the TCP connections using UBR+ scheme, and provides protection of damaged VC from the multiple packet losses in the same TCP sliding window. To analyze its performance, we simulate the proposed scheme using OPNET. The simulation results show that the proposed scheme supports fairness, and also increases the throughput by reducing the probability of multiple cell losses in the same TCP window.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.139-145
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• 1996

The input estimation method estimates maneuvering input acceleration in order to track a maneuvering target. In this paper, the optimal input estimator is derived by choosing the MAP hypothesis among maneuvering input transition hypotheses under the assumption that a maneuvering input acceleration is a semi-Markov process. The optimal input estimation method cannot be realized because the optimal filter should consider every maneuver onset time hypothesis from filter starting time to current time which increase rapidly. Hence the suboptimal filter using a sliding window is proposed. Since the proposed method can consider all hypotheses of input transitions inside the window, it is general enough to include Bogler's input estimation method. Simulation results show, however, that we can obtain a good performance even when the filter considering just one input transition in the window is used. (author). 9 refs., 3 figs., 1 tab.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.25-31
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• 2005

In this paper, we present a face detection system using the Support Vector Domain Description (SVDD) in color images. Conventional face detection algorithms require a training procedure using both face and non-face images. In SVDD however we employ only face images for training. We can detect faces in color images from the radius and center pairs of SVDD. We also use Entropic Threshold for extracting the facial feature and sliding window for improved performance while saving processing time. The experimental results indicate the effectiveness and efficiency of the proposed algorithm compared to conventional PCA (Principal Component Analysis)-based methods.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.275-284
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• 2016

Accurate electricity demand forecasts is essential in reducing energy spend and preventing imbalance of the power supply. In forcasting electricity demand, we considered double seasonal Holt-Winters model and TBATS model with sliding window. We selected a specific time zone as the reference line of daily electric demand because it is least likely to be influenced by external factors. The forecasting performance have been evaluated in terms of RMSE and MAPE criteria. We used the observations ranging January 4, 2009 to December 31 for testing data. For validation data, the records has been used between January 1, 2012 and December 29, 2012.

• Journal of Korea Multimedia Society
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• v.18 no.11
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• pp.1289-1301
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• 2015

Pedestrian detection (PD) is an essential task in various applications and sliding window-based methods utilizing HOG (Histogram of Oriented Gradients) or HOG-like descriptors have been shown to be very effective for accurate PD. However, due to exhaustive search across images, PD methods based on sliding window usually require heavy computational time. In this paper, we propose a real-time PD method for embedded visual surveillance with fixed backgrounds. The proposed PD method employs HOG descriptors as many PD methods does, but utilizes selective search so that it can save processing time significantly. The proposed selective search is guided by restricting searching to candidate regions extracted from Adaptive Gaussian Mixture Model (AGMM)-based background subtraction technique. Moreover, approximate computation of HOG descriptor and implementation in fixed-point arithmetic mode contributes to reduction of processing time further. Possible accuracy degradation due to approximate computation is compensated by applying an appropriate one among three offline trained SVM classifiers according to sizes of candidate regions. The experimental results show that the proposed PD method significantly improves processing speed without noticeable accuracy degradation compared to the original HOG-based PD and HOG with cascade SVM so that it is a suitable real-time PD implementation for embedded surveillance systems.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.450-453
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• 2011

고화질의 디지털 카메라 및 스마트폰, 감시용 카메라의 보급 등으로 인해 최근 패턴 인식 및 이미지 프로세싱 분야에서 고화질의 이미지 및 비디오를 처리해야 하는 경우가 많아지고 있다. 특히 차량 번호판 감지 등과 같은 객체 인식 분야의 경우, 고화질의 이미지로 인해 그만큼 인식에 필요한 계산 비용이 증가하게 되었는데 따라서 이러한 계산 비용을 효율적으로 줄이기 위한 기법이 요구되고 있다. 또한 기존의 차량 번호판 감지의 도메인과는 다르게 도로 상에서의 실시간 차량 번호판 감지의 필요성이 대두되고 있기에 본 논문에서는 도로 상에서의 실시간 번호판 감지 시스템을 위한 차량 번호판 주변정보 기반의 효율적인 윈도우 슬라이딩(window sliding) 방법을 제안한다. 본 논문의 시스템은 총 3단계로, (1) SVM(Supported Vector Machine) 을 통한 차량 번호판 주위 정보에 대한 학습, (2) 도로 상의 번호판 위치 확률 모델링을 통한 탐색 공간의 감소, (3) $context_{plate}$분류기를 통한 OCS(operator context scanning)의 수행이다. 이와 같은 $context_{plate}$분류기와 OCS를 통해 번호판 검출을 위한 윈도우 슬라이딩의 수가 크게 줄었음을 알 수 있었으며, 또한 번호판의 정보를 건너뛰지 않고, 신뢰성 있게 접근함을 알 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.336-339
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• 2007

A new query model is required to match requirements of stream-based applications such as patient monitoring system, since traditional DBMSs are not designed to provide continuous queries over stream data. In the patient monitoring system, there are many types of biomedical signals such as blood pressure and temperature, and these signals gathered by biomedical sensors should be treated as a stream, that is an ordered set of signals. In this paper, we categorized all possible queries to be used in patient monitoring system by four types of queries. Then, we have proposed a new sliding window query model which is capable of expressing these four types of queries.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.649-652
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• 2015

Previous marking policy for the AF service of TCP traffic in the Diffserv network have no sufficient consideration on the effect of RTT and target rate. In this paper, in order to improve fairness Index by the effect RTT difference of TCP traffic, we propose the modified TSW3CDM(Time Sliding Window Three Color Dynamic Marker) based on average transfer rate estimation and the flow state. The proposed algorithm is dynamic marking policy that do allocate band width in proportion to transmission rate. To evaluate the performance of the proposed algorithm, We accomplished a computer simulation using NS-2. From simulation results, the proposed TSW3CDM algorithm improves fairness index by comparison with TSW3CM.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.9 no.6
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• pp.768-775
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• 1998

The equalizer is the central part of the receiver and its performance significantly affects the overall performance of the system in the mobile communication. A proposed equalizer is composed of the channel estimator, MLSE based on the Viterbi algorithm and GMSK decoder. The approximation of GMSK with QPSK has great impact on the equalizer design, because it allows us to use the existing simple and efficient algorithms for designing optimal QPSK equalizer. In order to estimate efficiently channel, we use a sliding window algorithm based on energy calculation and cross-correlator. And also a tuning scheme is presented in order to improve the equalizer performance. Simulation results indicate that a proposed equalizer meets the GSM standards easily in terms of performance.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.196-204
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• 2017

Behavior of intelligent video surveillance system is recognized by analyzing the pattern of the object of interest by using the frame information of video inputted from the camera and analyzes the behavior. Detection of object's certain behaviors in the crowd has become a critical problem because in the event of terror strikes. Recognition of object's certain behaviors is an important but difficult problem in the area of computer vision. As the realization of big data utilizing machine learning, data mining techniques, the amount of video through the CCTV, Smart-phone and Drone's video has increased dramatically. In this paper, we propose a multiple-sliding window method to recognize the cumulative change as one piece in order to improve the accuracy of the recognition. The experimental results demonstrated the method was robust and efficient learning units in the classification of certain behaviors.