• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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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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• v.5B no.2
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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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• v.10 no.1
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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.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.4
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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.

• Proceedings of the IEEK Conference
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• 2000.06d
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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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• v.36 no.4
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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.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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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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• v.8 no.3
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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.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.6
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• pp.619-626
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• 2016

Intrusion detection model detects a intrusion when intrusion behaviour occurred. The model analyzes a variety of intrusion pattern and supports a modeling method to represent for a intrusion pattern efficiently. Particularly, the model defines classes of intrusion pattern and supports modeling method that detects a network level intrusion through multiple hosts for multiple intrusions. In this paper, proposes a multiple intrusion detection model that support a verification method for intrusion detection systems and verifies a safeness of proposed model and compares with other models.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.3
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• pp.189-196
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• 2011

In this paper, we analyze the error performance of SIC-based signal detection methods in MIMO systems. Considered detection methods are SIC signal detection and LR-SIC signal detection. We derive BLER performance of the methods and the performance is confirmed by computer simulations.