• Journal of Radiation Industry
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• v.6 no.2
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• pp.119-123
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• 2012

The detection properties of gamma-irradiated (0~10 kGy) dried seaweed, dried shrimp, and seasoned dried filefish were investigated by photo-stimulated luminescence (PSL) and electron spin resonance (ESR). PSL could be used as a detection method on irradiated dried seaweed and dried shrimp as they showed photon counts greater than 5,000 counts/60 s (positive) in the irradiated samples with doses above l kGy. However, PSL could not be applied to detect irradiated seasoned dried filefish, because gamma-irradiated sample at 10 kGy even yielded photon counts less than 700 counts/60 s (negative). The ESR spectroscopy for only dried shrimp revealed specific signals derived from free radicals captured in the shell of shrimp. As a result, it is considered that PSL or ESR methods for detection of gamma-irradiated dried shrimp and only PSL can be used to detect gamma-irradiated seaweed. Furthermore, it is considered that hydrocarbon analysis of seasoned dried filefish containing fat by GC/MS and Thermo Luminance (TL) analysis of dried seaweed should be studied for detection of irradiation.

• Proceedings of the Materials Research Society of Korea Conference
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• 2009.05a
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• pp.7.2-7.2
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• 2009

Polyvalent nanoparticle-DNA conjugates exhibit a variety of unique features such as programmable assembly and disassembly, sharp melting transitons, intense optical properties, high stability, enhanced binding properties, and easy fabrication of the surface nature by chemical and physical modification. The unique properties of nanoparticle-DNA conjugates enable one to build up a number of versatile assay schemes for the detection of various targets. In addition, nanoparticle-RNA conjugates also demonstrate great promise of therapeutic applications in the context of RNA interference when combined with polymeric materials. In this presentation, representative examples of each aspect of nanoparticle-oligonucleotide conjugates will be discussed.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.215-220
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• 2013

They are well-known geometric properties of a circle that the perpendicular bisector of a chord passes through the center of a circle, and the intersection of the perpendicular bisectors of any two chords is its center. This paper is related to a fast pupil detection method capable of detecting the center and the radius of a pupil using these geometric properties at high speed when detecting the pupil region for iris segmentation. The proposed method is characterized as rapidly detecting the center and the radius of the pupil, extracting the candidate points of the circle in human eye images using morphological operations, and finding two chords using four points on the circular edge, and taking the intersection of the perpendicular bisectors of these two chords for its center. The proposed method can not only detect the center and the radius of a pupil rapidly but also find partially occluded pupils in human eye images.

• Journal of the Korean Society for Nondestructive Testing
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• v.35 no.1
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• pp.31-38
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• 2015

Intelligent leak detection is an essential component of a underground water supply pipeline network such as a smart water grid system. In this network, numerous leak detection sensors are needed to cover all of the pipelines in a specific area installed at specific regular distances. It is also necessary to determine the existence of any leaks and estimate its location within a short time after it occurs. In this study, the leak signal properties and feasibility of leak location detection were investigated when concurrent leaks occurred at two points in a pipeline. The straight distance between the two leak sensors in the 100A sized cast-iron pipeline was 315.6 m, and their signals were measured with one leak and two concurrent leaks. Each leak location was described after analyzing the frequency properties and cross-correlation of the measured signals.

• Smart Structures and Systems
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• v.11 no.6
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• pp.589-604
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• 2013

Identification of damage has become an evolving area of research over the last few decades with increasing the need of online health monitoring of the large structures. The visual damage detection can be impractical, expensive and ineffective in case of large structures, e.g., offshore platforms, offshore pipelines, multi-storied buildings and bridges. Damage in a system causes a change in the dynamic properties of the system. The structural damage is typically a local phenomenon, which tends to be captured by higher frequency signals. Most of vibration-based damage detection methods require modal properties that are obtained from measured signals through the system identification techniques. However, the modal properties such as natural frequencies and mode shapes are not such good sensitive indication of structural damage. Identification of damaged jacket type offshore platform members, based on wavelet packet transform is presented in this paper. The jacket platform is excited by simple wave load. Response of actual jacket needs to be measured. Dynamic signals are measured by finite element analysis result. It is assumed that this is actual response of the platform measured in the field. The dynamic signals first decomposed into wavelet packet components. Then eliminating some of the component signals (eliminate approximation component of wavelet packet decomposition), component energies of remained signal (detail components) are calculated and used for damage assessment. This method is called Detail Signal Energy Rate Index (DSERI). The results show that reduced wavelet packet component energies are good candidate indices which are sensitive to structural damage. These component energies can be used for damage assessment including identifying damage occurrence and are applicable for finding damages' location.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.153-153
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• 2012

Endpoint detection with plasma impedance monitoring and self-plasma optical emission spectroscopy is demonstrated for dielectric layers etching processes. For in-situ detecting endpoint, optical-emission spectroscopy (OES) is used for in-situ endpoint detection for plasma etching. However, the sensitivity of OES is decreased if polymer is deposited on viewport or the proportion of exposed area on the wafer is too small. To overcome these problems, the endpoint was determined by impedance signal variation from I-V monitoring (VI probe) and self-plasma optical emission spectroscopy. In addition, modified principal component analysis was applied to enhance sensitivity for small area etching. As a result, the sensitivity of this method is increased about twice better than that of OES. From plasma impedance monitoring and self-plasma optical emission spectroscopy, properties of plasma and chamber are analyzed, and real-time endpoint detection is achieved.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.41-47
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• 2012

MANET has vulnerable structure on security owing to structural characteristics as follows. MANET consisted of moving nodes is that every nodes have to perform function of router. Every node has to provide reliable routing service in cooperation each other. These properties are caused by expose to various attacks. But, it is difficult that position of environment intrusion detection system is established, information is collected, and particularly attack is detected because of moving of nodes in MANET environment. It is not easy that important profile is constructed also. In this paper, conformal predictor - support vector machine(CP-SVM) based intrusion detection technique was proposed in order to do more accurate and efficient intrusion detection. In this study, IDS-agents calculate p value from collected packet and transmit to cluster head, and then other all cluster head have same value and detect abnormal behavior using the value. Cluster form of hierarchical structure was used to reduce consumption of nodes also. Effectiveness of proposed method was confirmed through experiment.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.305-306
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• 2006

To avoid the large scale of damage when fire occurs in the tunnel, it is necessary to have a system to minimize the damage, and early discovery of the problem. In this paper, we have proposed algorithm using the image processing, which is the high-speed detection for the occurrence of fire or smoke in the tunnel. The fire detection is different to the forest fire detection as there are elements such as car and tunnel lightings and other variety of elements different from the forest environment. Therefore, an indigenous algorithm should be developed.The two algorithms proposed in this paper, are able to complement with each other and also they can detect the exact position, at the earlier stay of detection. In addition, by comparing properties of each algorithm throughout this experiment, we have proved the propriety of algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.9-21
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• 2010

In this paper, optimum design of distributed detection is considered for a parallel sensor network system consisting of a fusion center and multiple passive sonar nodes. Nonrandom fusion rules are employed as the fusion rules of the sensor network. For the nonrandom fusion rules, it is shown that a threshold rule of each sensor node has uniformly most powerful properties. Optimum threshold for each sensor is investigated that maximizes the probability of detection under a constraint on energy consumption due to false alarms. It is also investigated through numerical experiments how signal strength, false alarm probability, and the distance between three sensor nodes affect the system detection performances.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.425-448
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• 2012

In this paper, a new damage detection and quantification method has been presented to perform detection and quantification of structural damage under ambient vibration loadings. To extract modal properties of the structural system under ambient excitation, natural excitation technique (NExT) and eigensystem realization algorithm (ERA) are employed. Sensitivity matrices of the dynamic residual force vector have been derived and used in the parameter subset selection method to identify multiple damaged locations. In the sequel, the steady state genetic algorithm (SSGA) is used to determine quantified levels of the identified damage by minimizing errors in the modal flexibility matrix. In this study, performance of the proposed damage detection and quantification methodology is evaluated using a finite element model of a truss structure with considerations of possible experimental errors and noises. A series of numerical examples with five different damage scenarios including a challengingly small damage level demonstrates that the proposed methodology can efficaciously detect and quantify damage under noisy ambient vibrations.