• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1939-1943
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• 2012

In this paper we presented the detection of the explosive material RDX using a parallel plate waveguide (PPWG) THz time domain spectroscopy (TDS). Normally the explosive materials have been characterized through identification of vibrational fingerprint spectra. Until now, most of all THz spectroscopic measurements have been made using pellet samples where disorder effects contribute to line broadening such that individual resonances merge into relatively broad absorption features. In order to avoid such disadvantages we used the technique of PPWG THz-TDS to achieve sensitive characterization of explosive material RDX. The PPWG THz-TDS used in this work well established ultrafast optoelectronic techniques to generate and detect sub-picosecond THz pulses. The explosive material was analyzed as powder layers in $112{\mu}m$ gap of metal PPWG. The thin later mass was estimated to be about $700{\mu}g$. Finally, we showed spectra of explosives from 0.2 to 2.4 THz measured using PPWG THz-TDS.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.11-19
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• 2022

This paper is a study to evaluate the performance when classifying explosive components by capacity using a convolutional neural network (CNN). Among the existing explosive classification methods, the IMS steam detector method determines the presence or absence of an explosive only when the explosive concentration exceeds the threshold set by the user. The IMS steam detector has a problem of determining that even if an explosive exists, the explosive does not exist in an amount that does not exceed the threshold. Therefore, it is necessary to detect the explosive component even when the concentration of the explosive component does not exceed the threshold. Accordingly, in this paper, after imaging explosive time series data with the Gramian Angular Field (GAF) algorithm, it is possible to determine whether there are explosive components and the amount of explosive components even when the concentration of explosive components does not exceed a threshold.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.4
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• pp.376-386
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• 2015

MOFs(Metal-Organic Frameworks) are new kinds of materials comprised of metal ions and functional organic ligands, and have large pores in its rigid structures which give the materials various functionalities, including gas absorption, separation, drug delivery etc. Recently photoluminescence properties of MOFs and possibilities of its application to high explosive sensing technologies are drawing attentions from scientists and engineers, because these methods are simple, cheap and easy to perform detection operations. In this article the author reviews the mechanisms of photoluminescence of MOFs, the detection methods of high explosives using MOFs and recent research progresses based on the papers published mainly during last 10 years.

• Analytical Science and Technology
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• v.33 no.2
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• pp.86-97
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• 2020

Reconstruction and separation of explosive-contaminated overlapping fingerprints constitutes an analytical challenge of high significance in forensic sciences. Laser-induced breakdown spectroscopy (LIBS) allows real-time chemical mapping by detecting the light emissions from laser-induced plasma and can offer powerful means of fingerprint classification based on the chemical components of the sample. During recent years LIBS has been studied one of the spectroscopic techniques with larger capability for forensic sciences. However, despite of the great sensitivity, LIBS suffers from a limited detection due to difficulties in reconstruction of overlapping fingerprints. Here, the authors propose a simple, yet effective, method of using chemical mapping to separate and reconstruct the explosive-contaminated, overlapping fingerprints. A Q-switched Nd:YAG laser system (1064 nm), which allows the laser beam diameter and the area of the ablated crater to be controlled, was used to analyze the chemical compositions of eight samples of explosive-contaminated fingerprints (featuring two sample explosive and four individuals) via the LIBS. Then, the chemical validations were further performed by applying the Raman spectroscopy. The results were subjected to principal component and partial least-squares multivariate analyses, and showed the classification of contaminated fingerprints at higher than 91% accuracy. Robustness and sensitivity tests indicate that the novel method used here is effective for separating and reconstructing the overlapping fingerprints with explosive trace.

• Proceedings of the Korean Nuclear Society Conference
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• 2001.05a
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• pp.510.2-510
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• 2001

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.120-125
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• 2014

Conventional handheld metal detectors use a single induction coil to detect the metallic parts of explosive objects, and the detector generates an acoustic signal from its magnetic response to a metallic object so that an operator can confirm the existence of mines. Though metal detectors have very useful detection mechanisms to find mines, it is easy to cause a high false alarm ratio due to the detection of non-explosive metallic items such as cans, nails and other pieces of metal, etc. Also, because of the physical characteristic of a metal detector it is hard to detect non-metallic objects such as mines made of wood or plastic. Furthermore, the operator must move it to the left and right slowly and repeatedly to attain enough sensor signals to confirm the existence of mines using only a monotonous acoustic signal. To resolve the disadvantages of handheld detectors, many new approaches have been attempted, such as an arrayed detector and a visualization algorithm based on metal/non-metal sensor. In this paper, we introduce a visualization algorithm with a metal/non-metal complex sensor, an arrayed metal/non-metal sensor and the their testing and evaluation.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.90.1-90.1
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• 2013

Nature utilizes various of the colorization process. Some species of birds can express their mood of tempers by changing their collagen structures on skin. For example, turkey can change their skin color by expansion of the collagen structures, which are associated with the distinct color changes. Here, we developed bioinspired virus-based colorimetric sensors which can be genetically tuned for target molecule. Using M 13 bacteriophage, we fabricated responsive self-assembled color matrices composed of quasi-ordered fiber bundle structures. These virus matrices can exhibit color change by stimuli through fiber bundle structure modulation. Upon exposure of volatile organic compounds, the resulting multi-colored matrices exhibited distinct color changes with different ratios that can be recognized by the naked eyes. Using the directed evolutionary approaches, we genetically engineered the virus matrix to incorporate binding motif for explosive detection (i.e., trinitrotoluene (TNT)). Through utilizing a common handheld device (i.e., iPhone), we could distinguish TNT molecules down to 20 ppb in a selective manner. Our novel biomimetic virus colorimetric sensor can overcome current limitation for low response selectivity.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.395-408
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• 2020

Purpose: This study was performed for advancement of aviation security equipments certification system. Methods: We investigated aviation security equipments certification-related registrations and the latest research trends of explosive detection technologies. Based on the literature studies, we draw the critical issues of the aviation security equipment certification system and suggested improvement direction. Results: We found some inaccuracies of the definition of explosive trace detection equipments, accreditation review committee, and performance evaluation test method. These problems should be modified to suit being practical. Conclusion: The present results would be useful for basic data for modifying aviation security equipments certification systems.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.793-810
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• 2022

Purpose: As improving the search performance of aviation security equipment is considered essential, this study proposes the need for research on how to find an optimized test sequence that can reduce test time and operator power during the search function test of explosive detection systems. We derive the weights and work difficulty adjustment factor required to find the optimized test order. Methods: First, after setting the test factors, the time of each test and the difficulty scale determined by the worker who performed the test directly were used to derive weights. Second, the work difficulty adjustment coefficient was determined by combining the basic weight adjustment factor and corresponding to the body part used by the test using objective rating. Then the final standard time was derived by calculating the additional weights for the changeability of the test factors. Results: The order in which the final standard time is minimized when 50 tests are performed was defined as the optimized order. 50 tests should be conducted without duplication and the optimal order of tests was obtained when compared to previously numbered tests. As a result of minimizing the total standard time by using Excel's solver parameters, it was reduced by 379.14 seconds, about 6.32 minutes. Conclusion: We tried to express it in mathematical formulas to propose a method for setting an optimized test sequence even when testing is performed on other aviation security equipment. As a result, the optimal test order was derived from the operator's point of view, and it was demonstrated by minimizing the total standard time.

• Analytical Science and Technology
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• v.10 no.5
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• pp.325-331
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• 1997

Among various CE separation methods, micellar electrokinetic capillary chromatography(MECC) method using sodium dodecylsulfate(SDS) provides rapid and accurate separation of organic explosive constituents with easy. The running buffer was composed with 2.5 mM borate and 25mM SDS(pH 8.5). Addition of 1M urea and 10% organic modifiers (acetonitrile, methanol and ethanol) improves the resolution of adjacent explosive constituents. When 15 explosive constituents were developed in MECC, most constituents were separated successively while RDX/TNB and DNN/DEP were not, and detection limits of separated compounds are in range of 1 to 4 ppm.