• 한국통신학회논문지
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• 제21권2호
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• pp.383-393
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• 1996

This paper considers the evaluation of the ecquistion performance for an accesschannel preamble based on a random access procedure of direct sequence code division multiple access(DS/CDMA) reverse link. The parallel acquistion technique that employs the single-well detection scheme and the multiple-dwell(double-dwell) detection scheme is mentioned. The acquisition performance for two detection schemes is compared in therms of the acquisition probability and the acquisition time. The parallel acquisition is done by a bank of N parallel I/Q noncoherent correlators. Expressions on the detection, false alarm, and miss probabilities of the single-dwell and multiple-dwell(double-well) detection schemes are derived for multiple H$_{1}$ cells and multipath Rayleight fading channel. comparing the single-dwell detection scheme with the multiple-dwell(double-dwell) detection scheme in the case of employing the parallel acquisition technique in the reverse link,the numerical results show that the single-dwell detection scheme deomonstrates a better performance.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제5B권2호
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• pp.103-110
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• 2005

Broken rotor bars in induction motors can be detected by monitoring any abnormality of the spectrum amplitudes at certain frequencies in the motor current spectrum. Broken rotor bar fault detection schemes should rely on multiple signatures in order to overcome or reduce the effect of any misinterpretation of the signatures that are obscured by factors such as measurement noises and different load conditions. Multiple Discriminant Analysis (MDA) and Artificial Neural Networks (ANN) provide appropriate environments to develop such fault detection schemes because of their multi-input processing capabilities. This paper describes two fault detection schemes for broken rotor bar fault detection with multiple signature processing, and demonstrates that multiple signature processing is more efficient than single signature processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.272-287
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• 2016

Recently, various and effective contrast based salient object detection models to focus on a single target have been proposed. However, there is a lack of research on detection of multiple objects, and also it is a more challenging task than single target process. In the multiple target problem, we are confronted by new difficulties caused by distinct difference between properties of objects. The characteristic of existing models depending on the global maximum distribution of data point would become a drawback for detection of multiple objects. In this paper, by analyzing limitations of the existing methods, we have devised three main processes to detect multiple salient objects. In the first stage, regional features are extracted from over-segmented regions. In the second stage, the regional features are categorized into homogeneous cluster using the mean-shift algorithm with the kernel function having various sizes. In the final stage, we compute saliency scores of the categorized regions using only spatial features without the contrast features, and then all scores are integrated for the final salient regions. In the experimental results, the scheme achieved superior detection accuracy for the SED2 and MSRA-ASD benchmarks with both a higher precision and better recall than state-of-the-art approaches. Especially, given multiple objects having different properties, our model significantly outperforms all existing models.

• 전자공학회논문지A
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• 제31A권4호
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• pp.39-46
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• 1994

In this paper, the idea of using a multiple symbol obervation interval to improve error probability performance is applied to differential detection of MTCM(multiple trellis code modulation) with ${\Pi}$/4 shift QPSK, 8DPSK and 16DPSK. We propose two types of sliding multiple symbol differential detection algorithm, type 1 and type 2. The two types of sliding detection scheme are examined and compared with conventional(symbol-by-symbol) detection and bolck detection with these modulation formats in an additive white Gaussian noise(AWGN) using the Monte Carlo simulation. We show that the amount of improvement over conventional and block detection depends on the number of phases and the number of additional symbol intervals added to the observation. Computer simulagtion results are presented for 2,4,8 states in AWGN channel.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.163-166
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• 2000

Real-time traffic detection scheme based on Computer Vision is capable of efficient traffic control using automatically computed traffic information and obstacle detection in moving automobiles. Traffic information is extracted by segmenting vehicle region from road images, in traffic detection system. In this paper, we propose the advanced segmentation of vehicle from road images using multiple local region information. Because multiple local region overlapped in the same lane is processed sequentially from small, the traffic detection error can be corrected.

• Journal of the Korean Statistical Society
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• 제36권4호
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• pp.457-469
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• 2007

Many procedures are available to identify a single outlier or an isolated influential point in linear regression and logistic regression. But the detection of influential points or multiple outliers is more difficult, owing to masking and swamping problems. The multiple outlier detection methods for logistic regression have not been studied from the points of direct procedure yet. In this paper we consider the direct methods for logistic regression by extending the $Pe\tilde{n}a$ and Yohai (1995) influence matrix algorithm. We define the influence matrix in logistic regression by using Cook's distance in logistic regression, and test multiple outliers by using the mean shift model. To show accuracy of the proposed multiple outlier detection algorithm, we simulate artificial data including multiple outliers with masking and swamping.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.13-17
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• 2005

In recent years, many people use R as a statistics system. R is frequently updated by many R project teams. We are interested in the method of multiple outlier detection and know that R is not supplied the method of multiple outlier detection. In this talk, we review these procedures for detecting multiple outliers and provide more efficient procedures combined with direct methods and indirect methods using R.

• Journal of Positioning, Navigation, and Timing
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• 제8권3호
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• pp.129-138
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• 2019

In this work, we propose detection method for ionosphere storm that occurs locally using widespread GNSS reference stations. For ionosphere storm detection, we compare ionosphere condition with other reference stations and estimate direction of movement based on ionosphere time variation. The method use carrier phase measurement of dual frequency, for accuracy and precision of test statistics, are evaluated with multiple GNSS reference stations data.

• 한국전자통신학회논문지
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• 제11권6호
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• pp.619-626
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• 2016

침입 탐지 모델은 침입 행위가 발생할 때 침입을 탐지하기 위해 사용하는 모델로서 침입 패턴을 잘 표현하기 위해서는 먼저 침입 패턴의 유형에 대해 분석하고 각 유형별로 침입 패턴에 대한 표현 방법을 제공할 수 있어야 한다. 특히 하나의 호스트 레벨의 침입뿐만 아니라 다중 호스트를 이용한 네트워크 레벨의 침입을 탐지하기 위해서는 이러한 다중 침입의 유형을 정의하고 다중 침입에 대한 표현 방법을 제공해야 한다. 본 논문에서는 침입 탐지 시스템의 안전성에 대한 검증 방법을 제공하는 다중 침입 탐지 모델을 제안하고 제안한 모델의 안전성을 검증하며 다른 모델들과 비교 평가한다.

• 한국정보전자통신기술학회논문지
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• 제4권3호
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• pp.189-196
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• 2011

본 논문에서는 다중입출력 (MIMO : multiple-input multiple-output) 시스템에서 순차적 간섭 제거 기반 (SIC : successive interference cancellation) 신호 검출 기법의 성능을 분석한다. 고려되는 신호검출 기법들은 SIC 기법와 LR-SIC 기법이며, 이러한 신호 검출 기법들의 블록오류확률 (BLER; block error ratio) 성능을 나타내는 식을 유도 하고, 모의실험 결과를 통해 유도된 식과 성공적으로 일치함을 확인한다.