• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.3
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• pp.433-440
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• 2019

In order to detect toxic chemical spread on field ground, we developed stand-off Raman spectrometer system which employed a deep UV laser. In this paper, the design and specification of various components in the spectrometer system are described. Some results when the detection system was tested on the outdoor roads are shown, which may help researching stand-off chemical detectors based on Raman spectroscopy.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.302-309
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• 2020

Early-detection and monitoring of toxic chemical gas cloud with chemical detector is essential for reducing the number of casualties. Conventional method for chemical detection and reconnaissance has the limitation in approaching to chemically contaminated site and prompt understanding for the situation. Stand-off detector can detect and identify the chemical gas at a long distance but it cannot know exact distance and position. Chemical detection UAV is an emerging platform for its high mobility and operation safety. In this study, we have conducted chemical gas cloud detection with the stand-off chemical detector and the chemical detection UAV. DMMP vapor was generated in the area where the cloud can be detected through the field of view(FOV) of stand-off chemical detector. Monitoring the vapor cloud with standoff detector, the chemical detection UAV moved back and forth at the area DMMP vapor being generated to detect the chemical contamination. The hybrid detection system with standoff cloud detection and point detection by chemical sensors with UAV seems to be very efficient as a new concept of chemical detection.

• Bulletin of the Korean Chemical Society
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• v.34 no.6
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• pp.1668-1672
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• 2013

We developed a standoff Raman detection system for explosive molecules (EMs). Our system was composed of reflective telescope with 310 mm diameter lens, 532 nm pulse laser, and Intensified Charge-Coupled Device (ICCD) camera. In order to remove huge background noise coming from ambient light, laser pulses with nanosecond time width were fired to target sample and ICCD was gated to open only during the time when the scattered Raman signal from the sample arrived at ICCD camera. We performed standoff experiments with military EMs by putting the detector at 10, 20 and 30 m away from the source. The standoff results were compared with the confocal Raman results. Based on our standoff experiments, we were able to observe the peaks in the range of 1200 and $1600cm^{-1}$, where vibrational modes of nitro groups were appeared. The wave numbers and shapes of these peaks may serve as good references in detecting and identifying various EMs.

• Progress in Superconductivity and Cryogenics
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• v.17 no.4
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• pp.38-42
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• 2015

In terms of food safety,mixture of contaminants in food is a serious problem for not only consumers but also manufacturers. In general, the target size of the metallic contaminant to be removed is 0.5 mm. However, it is a difficult task for manufacturers to achieve this target, because of lower system sensitivity. Therefore, we developed a food contaminant detection system based on high-Tc RF superconducting quantum interference devices (SQUIDs), which are highly sensitive magnetic sensors. This study aims to improve the signal to noise ratio (SNR) of the system and detect a 0.5 mm diameter steel ball. Using a real time digital signal processing technique along with analog band-pass filters, we improved the SNR of the system. Owing to the improved SNR, a steel ball with a diameter as small as 0.3 mm, with stand-off distance of 117 mm was successfully detected. These results suggest that the proposed system is a promising candidate for the detection of metallic contaminants in food products.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2C
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• pp.181-187
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• 2012

Millimeter wave (MMW) readily penetrates fabrics, thus it can be used to detect objects concealed under clothing. A passive MMW imaging system can operate as a stand-off type sensor that scans people in both indoors and outdoors. However, because of the diffraction limit and low signal level, the imaging system often suffers from low image quality. Therefore, suitable statistical analysis and computational processing would be required for automatic analysis of the images. In this paper, a real-time concealed object detection is addressed by means of the multi-level segmentation. The histogram of the image is modeled with a Gaussian mixture distribution, and hidden object areas are segmented by a multi-level scheme involving $k$-means, the expectation-maximization algorithm, and a decision rule. The complete algorithm has been implemented in C++ environments on a standard computer for a real-time process. Experimental and simulation results confirm that the implemented system can achieve the real-time detection of concealed objects.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.451-457
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• 2011

A short laser pulse irradiates a sample to create the highly energetic plasma that emits light of a specific wavelength peak according to the material. By identifying different peaks for the analyzed samples, its chemical composition can be rapidly determined. The LIBS (Laser-Induced Breakdown Spectroscopy) has great advantages as an elemental analyzer on board a space rover, namely real-time rapid analysis and stand-off detection. The LIBS signal intensity is remarkably increased by using double-pulse LIBS system for component analysis of lunar environments where the surrounding pressure is low. Also the angle of target is adjusted for replicating arbitrary shapes of the specimen.

• Current Optics and Photonics
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• v.2 no.2
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• pp.153-164
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• 2018

In semiconductor manufacturing, critical dimensions indicate the features of patterns formed by the semiconductor process. The purpose of measuring critical dimensions is to confirm whether patterns are made as intended. The deposition process for an organic light emitting diode (OLED) forms a luminous organic layer on the thin-film transistor electrode. The position of this organic layer greatly affects the luminescent performance of an OLED. Thus, a system for measuring the position of the organic layer from outside of the vacuum chamber in real-time is desired for monitoring the deposition process. Typically, imaging from large stand-off distances results in low spatial resolution because of diffraction blur, and it is difficult to attain an adequate industrial-level measurement. The proposed method offers a new superresolution single-image using a conversion formula between two different optical systems obtained by a deep learning technique. This formula converts an image measured at long distance and with low-resolution optics into one image as if it were measured with high-resolution optics. The performance of this method is evaluated with various samples in terms of spatial resolution and measurement performance.