• Journal of Information Processing Systems
• /
• 제6권1호
• /
• pp.79-90
• /
• 2010

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. The continuous characteristic of streaming data necessitates the use of algorithms that require only one scan over the stream for knowledge discovery. Data mining over data streams should support the flexible trade-off between processing time and mining accuracy. In many application areas, mining frequent itemsets has been suggested to find important frequent itemsets by considering the weight of itemsets. In this paper, we present an efficient algorithm WSFI (Weighted Support Frequent Itemsets)-Mine with normalized weight over data streams. Moreover, we propose a novel tree structure, called the Weighted Support FP-Tree (WSFP-Tree), that stores compressed crucial information about frequent itemsets. Empirical results show that our algorithm outperforms comparative algorithms under the windowed streaming model.

• 한국멀티미디어학회논문지
• /
• 제22권4호
• /
• pp.424-431
• /
• 2019

In this paper, we propose a real-time hand gesture recognition algorithm to eliminate the inconvenience of using hand controllers in VR applications. The user's 3D hand coordinate information is detected by leap motion sensor and then the coordinates are generated into two dimensional image. We classify hand gestures in real-time by learning the imaged 3D hand coordinate information through SSD(Single Shot multibox Detector) model which is one of CNN(Convolutional Neural Networks) models. We propose to use all 3 channels rather than only one channel. A sliding window technique is also proposed to recognize the gesture in real time when the user actually makes a gesture. An experiment was conducted to measure the recognition rate and learning performance of the proposed model. Our proposed model showed 99.88% recognition accuracy and showed higher usability than the existing algorithm.

• Journal of Power Electronics
• /
• 제10권2호
• /
• pp.203-209
• /
• 2010

This paper describes the development of a three-phase line-interactive DVR with a new sag detection algorithm. The developed detection algorithm has a hybrid structure composed of an instantaneous detector and RMS-variation detectors. The source voltage passes through the sliding-window DFT and RMS calculator, and the instantaneous sag detector. If an instantaneous sag is detected, the RMS variation detector-1 is selected to calculate the RMS variation. The RMS variation detector-2 is selected when the instantaneous sag occurs under the operation of the RMS variation detector-1. The feasibility of the proposed algorithm is verified through computer simulations and experimental work with a prototype of a line-interactive DVR with a 3kVA rating. The line-interactive DVR with the proposed algorithm can compensate for an input voltage sag or an interruption within a 2ms delay. The developed DVR can effectively compensate for a voltage sag or interruption in sensitive loads, such as computers, communications equipment, and automation equipment.

• 전기전자학회논문지
• /
• 제24권1호
• /
• pp.147-153
• /
• 2020

기존의 차선 검출 방법들은 곡률과 날씨 변화가 큰 도로 환경에서 검출률이 낮다. 확률적 허프 변환을 이용한 방법은 에지와 직선의 각도를 이용해서 차선을 검출함으로 곡선과 악천후일 때 검출률이 낮다. 슬라이딩 윈도우 방법은 윈도우로 이미지를 분할해서 검출하기 때문에 곡선 형태의 차선도 검출하지만 어파인 변환을 사용하기 때문에 도로의 경사율에 영향을 받는다. 본 논문에서는 다양한 외부 환경에서도 차선을 강인하게 검출하고 장애물을 회피하기 위한 딥러닝 기반의 주행 보조 시스템을 제안한다. VGG-16기반의 SegNet으로 입력 영상을 의미론적으로 분할해서 차선을 검출한다. 검출한 차선과의 이격거리를 계산하고 안전범위를 산출해서 차량이 차선의 중앙을 주행하도록 제어한다. 또한, 전방의 미확인 물체와 충돌이 예상되면 운전자에게 경보를 주고 Adaptive-MPC로 차량을 제어해서 충돌을 회피하는 알고리즘도 제안한다. CARLA로 시뮬레이션한 결과 제안한 알고리즘은 곡률이 큰 차선과 다양한 환경에서도 강인하게 차선을 검출하고 전방의 안전범위를 계산하여 충돌을 회피하는 것을 볼 수 있다.

• 한국정보통신학회논문지
• /
• 제9권1호
• /
• pp.165-171
• /
• 2005

본 논문에서는 중앙집중형 동적부하균등을 효율적으로 처리하기 위하여 네트워크기반 병렬 유전자 알고리즘을 이용하였다. 기존의 유전자 알고리즘을 적용한 경우와는 달리 클라이언트들에서 최적작업 할당의 탐색을 분산처리하여 중앙 스케줄러의 성능을 향상시킬 수 있었다. 최적해의 수렴속도를 향상시키기 위해 선택연산은 룰렛휠 선택과 엘리트 보존전략을 함께 사용하였고, 염색체 인코딩은 슬라이딩윈도우기법을 이용하였으며 교차연산은 주기교차방법을 이용하였다. 부하균등기법의 유연성 변화에 따른 중앙 스케줄러의 성능을 모의실험한 결과 기존의 방법보다 성능이 향상됨을 확인하였다.

• ETRI Journal
• /
• 제22권4호
• /
• pp.40-50
• /
• 2000

We apply a "sliding-window" Maximum Likelihood(ML) estimator to estimate traffic parameters On-Off source and develop a method for estimating stochastic predicted individual cell arrival rates. Based on these results, we propose a simple Connection Admission Control(CAC)scheme for delay sensitive services in broadband onboard packet switching satellite systems. The algorithms are motivated by the limited onboard satellite buffer, the large propagation delay, and low computational capabilities inherent in satellite communication systems. We develop an algorithm using the predicted individual cell loss ratio instead of using steady state cell loss ratios. We demonstrate the CAC benefits of this approach over using steady state cell loss ratios as well as predicted total cell loss ratios. We also derive the predictive saturation probability and the predictive cell loss ratio and use them to control the total number of connections. Predictive congestion control mechanisms allow a satellite network to operate in the optimum region of low delay and high throughput. This is different from the traditional reactive congestion control mechanism that allows the network to recover from the congested state. Numerical and simulation results obtained suggest that the proposed predictive scheme is a promising approach for real time CAC.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
• /
• pp.188-190
• /
• 2006

A multistage hierarchical clustering technique, which is an unsupervised technique, was suggested in this paper for classifying large remotely-sensed imagery. The multistage algorithm consists of two stages. The local segmentor of the first stage performs regiongrowing segmentation by employing the hierarchical clustering procedure of CN-chain with the restriction that pixels in a cluster must be spatially contiguous. This stage uses a sliding window strategy with boundary blocking to alleviate a computational problem in computer memory for an enormous data. The global segmentor of the second stage has not spatial constraints for merging to classify the segments resulting from the previous stage. The experimental results show that the new approach proposed in this study efficiently performs the segmentation for the images of very large size and an extensive number of bands

• 한국통신학회논문지
• /
• 제22권1호
• /
• pp.104-115
• /
• 1997

This paper investigates PN code acquistion algorithm and demodulation performance of the RAKE receiver in the DS/CDMA(direct sequence code division multiple access) sysytems under a multipath fading channel with multiusers. To speed up the acquisition process, PN matched filter is applied and postdetection integration technique comable withthe dynamic threshold set method is proposed. the Maximum-Likelihood algorithmin serial fashion is able to find PN code delay estimates for the RAKE branches using sliding window in a multipath fading channel. The correct acquistion probability and mean acquistion time are used as a performance measure of the system using the Monte Carlo method. The performance of the RAKEreceiver, afte the code acquisition is achieved is the CDMA systems, is also investigated for three major combining techniques.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2023년도 추계학술발표대회
• /
• pp.1157-1158
• /
• 2023

자율주행 시스템에서 차선 인지는 주행의 성능과 안전에 중요한 역할을 한다. 차선 인지 분야에서는 다양한 알고리즘이 사용된다. 본 논문에서는 슬라이딩 윈도우 기법을 사용한 알고리즘을 기반으로, 더 정확하고 효율적인 차선 인지를 위한 개선 방안을 소개한다.

• International Journal of Naval Architecture and Ocean Engineering
• /
• 제8권3호
• /
• pp.243-251
• /
• 2016

Autonomous Underwater Vehicles (AUVs) generally work in complex marine environments. Any fault in AUVs may cause significant losses. Thus, system reliability and automatic fault diagnosis are important. To address the actuator failure of AUVs, a fault diagnosis method based on the Gaussian particle filter is proposed in this study. Six free-space motion equation mathematical models are established in accordance with the actuator configuration of AUVs. The value of the control (moment) loss parameter is adopted on the basis of these models to represent underwater vehicle malfunction, and an actuator failure model is established. An improved Gaussian particle filtering algorithm is proposed and is used to estimate the AUV failure model and motion state. Bayes algorithm is employed to perform robot fault detection. The sliding window method is adopted for fault magnitude estimation. The feasibility and validity of the proposed method are verified through simulation experiments and experimental data.