• Fire Science and Engineering
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• v.22 no.1
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• pp.68-75
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• 2008

In this paper, we introduce a fire-detection system which is robust to light sources and environment changing. We can decide the threshold values that classify the regions between a fire flame and light sources by analyzing them in RGB color space. But we could not discriminate quasi-flame region from fire flame region with the value. The difference of mean-histogram technique make it possible to extract flame region more efficient because fire flame is continuously changing after it occurs. In order to validate real fire, this paper uses regional compactness in the end of process. Computer simulation show that proposed method make more robust to light sources and environment changing.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.4 s.109
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• pp.404-413
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• 2006

Induction motors are the workhorse of our industry because of their versatility and robustness. The diagnosis of mechanical load and power transmission system failures is usually carried out through mechanical signals such as vibration signatures, acoustic emissions, motor speed envelope. The motor faults including mechanical rotor imbalances, broken rotor bar, bearing failure and eccentricities problems are reflected in electric, electromagnetic and mechanical quantities. The recent research has been directed toward electrical monitoring of the motor with emphasis on inspecting the stator current of the motor, The stator current spectrum has been widely used for fault detection in induction motor systems. The motor current signature analysis is the useful technique to assess machine electrical condition. This paper describes the motor condition detected by the current signatures Paralleled with vibration signatures analysis of induction motors with the roller bearing and the journal bearing type for large vertical pumps in power plant as examples to discuss for motor fault detection and diagnosis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4567-4587
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• 2017

With the growth of the Internet and the extensive applications of image editing software, it has become easier to manipulate digital images without leaving obvious traces. Copy-move is one of the most common techniques for image forgery. Image blind forensics is an effective technique for detecting tampered images. This paper proposes an improved copy-move forgery detection method based on the discrete cosine transform (DCT). The quantized DCT coefficients, which are feature representations of image blocks, are truncated using a truncation factor to reduce the feature dimensions. A method for judging whether two image blocks are similar is proposed to improve the accuracy of similarity judgments. The main transfer vectors whose frequencies exceed a threshold are found to locate the copied and pasted regions in forged images. Several experiments are conducted to test the practicability of the proposed algorithm using images from copy-move databases and to evaluate its robustness against post-processing methods such as additive white Gaussian noise (AWGN), Gaussian blurring, and JPEG compression. The results of experiments show that the proposed scheme effectively detects both copied region and pasted region of forged images and that it is robust to the post-processing methods mentioned above.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.4
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• pp.411-420
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• 1999

Coastal development and reclamation work make environment of shore destroy, such as rapid change of land use and destruction of wet-land and ocean ecosystem. Therefore new technique to detect change have been needed. This study designed new change detection method and applied to study area. The change detection image and quantitative change area by each classes are calculated. Also, this study can use the basic idea-determination data for coastal development and city plan as the sense of sight by changed images that changed from any land-cover to any land-cover between two dates.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.517-524
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• 2015

The fast and accurate spectrum sensing over an ultra-wide bandwidth is a big challenge for the radio environment cognition. Considering sparse signal feature, two novel compressed sensing schemes are proposed, which can reduce compressed sampling rate in contrast to the traditional scheme. One algorithm is dynamically adjusting compression ratio based on modulation recognition and identification of symbol rate, which can reduce compression ratio. Furthermore, without priori information of the modulation and symbol rate, another improved algorithm is proposed with the application potential in practice, which does not need to reconstruct the signals. The improved algorithm is divided into two stages, which are the approaching stage and the monitoring stage. The overall sampling rate can be dramatically reduced without the performance deterioration of the spectrum detection compared to the conventional static compressed sampling rate algorithm. Numerous results show that the proposed compressed sensing technique can reduce sampling rate by 35%, with an acceptable detection probability over 0.9.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.131-137
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• 2013

In this paper we propose an improved voice activity detection (VAD) algorithm using statistical models in the signal subspace domain. A uncorrelated signal subspace is generated using embedded prewhitening technique and the statistical characteristics of the noisy speech and noise are investigated in this domain. According to the characteristics of the signals in the signal subspace, a new statistical VAD method using GGD (Generalized Gaussian Distribution) is proposed. Experimental results show that the proposed GGD-based approach outperforms the Gaussian-based signal subspace method at 0-15 dB SNR simulation conditions.

• Journal of the Optical Society of Korea
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• v.13 no.3
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• pp.392-397
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• 2009

We designed a wavelength interrogation-based surface plasmon resonance (SPR) biosensor to detect avian influenza DNA (AI-DNA). Hybridization reactions between target AI-DNA probes and capture probes immobilized on a gold surface were monitored quantitatively by measuring the resonance wavelength in the visible waveband. The experimental results were consistent with numerical calculations. Although the SPR detection technique does not require the DNA to be labeled, we also evaluated fluorescently-labeled targets to verify the hybridization behavior of the AI-DNA. Changes in resonance were found to be linearly proportional to the amount of bound analyte. A wavelength interrogation-type SPR biosensor can be used for rapid measurement and high-throughput detection of highly pathogenic AI viruses.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.365-372
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• 1996

The researches to acquire diagnostic parameters from ultrasonic images are advanced with the progress of the digital image processing technique. Especially, the detection of endocardial boundary is very important in ultrasonic images, because endocardial boundary is used as a clinical parameter to estimate both the cardiac area and the variation of cardiac volume. Various methods to detect cardiac boundary are proposed, but these are insufficient to detect boundary. In this paper, an algorithm that detects the endocardial boundary, expanding the cavity region from the center using statistical information, is proposed The value of mean and sty:nd, wd deviation in cavity region is lower than those in muscle re- gion. Therefore, if we define the multiplication of mean and standard deviation as homogeneous coefficient, it can lead to conclusion that the pixels with small variation of these coefficleno are cavity region, and extraction of endocardial boundary from cavity region is possible. The proposed method detected endocardial boundary more effectively than edge based or threshold based method and is robuster to noise than radial searching method that has high dependency for center position.

• Journal of Microbiology and Biotechnology
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• v.22 no.6
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• pp.849-855
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• 2012

Plant growth-promoting rhizobacteria (PGPR) pseudomonads have a large number of lipopolysaccharides on the cell surface, which induces immune responses. Cd-resistant PGPR prevalent at the Cd-affected sites under biophytostabilization was monitored. Transmissiom electron microscopy was used to the study the behavior of tolerance of PGPR to cadmium level and its effect on pseudomonad strains (Z9, S2, KNP2, CRPF, and NBRI). An immunosensor was developed by immobilizing antibody (anti-Z9 or anti-S2) against selected PGPR on a piezoelectric quartz crystal microbalance (QCM). Immunosensors were found to supplement the inherent specificity of antigen-antibody reactions with the high sensitivity of a physical transducer. On comparison of the efficiency of detection with ELISA, the spectrophotometric technique, the developed immunosensor was found to be more sensitive, fast, and reliable even after regeneration for several times. Thus, the immunosensor may be used for future detection of PGPR strains after automation of the screening process.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.57-69
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• 2000

A moving window technique for detecting a lane and obstacles using the Images captured by a CCD camera attached in an automobile, is proposed in this paper To process the dynamic images in real time, there could be many constraints on the hardware To overcome these hardware constraints and to detect the lane and obstacles in real time, the optimal size of window IS determined based upon road conditions and automobile states. By utilizing the sub-Images inside the windows, detection of the lane and obstacles become possible m real time. For each Image frame, the moving windows are re-determined following the predicted directions based on Kalman filtering theory to Improve detection accuracy, as well as efficiency The feasibility of proposed algorithm IS demonstrated through the simulated experiments of highway driving.