• Journal of Radiation Protection and Research
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• v.45 no.3
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• pp.117-129
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• 2020

Background: Radiation portal monitors (RPMs) involving plastic scintillators installed at the border inspection sites can detect illicit trafficking of radioactive sources in cargo containers within seconds. However, RPMs may generate false alarms because of the naturally occurring radioactive materials. To manage these false alarms, we previously suggested an energy-weighted algorithm that emphasizes the Compton-edge area as an outstanding peak. This study intends to evaluate the identification of radioactive sources using an improved energy-weighted algorithm. Materials and Methods: The algorithm was modified by increasing the energy weighting factor, and different peak combinations of the energy-weighted spectra were tested for source identification. A commercialized RPM system was used to measure the energy-weighted spectra. The RPM comprised two large plastic scintillators with dimensions of 174 × 29 × 7 ㎤ facing each other at a distance of 4.6 m. In addition, the in-house-fabricated signal processing boards were connected to collect the signal converted into a spectrum. Further, the spectra from eight radioactive sources, including special nuclear materials (SNMs), which were set in motion using a linear motion system (LMS) and a cargo truck, were estimated to identify the source identification rate. Results and Discussion: Each energy-weighted spectrum exhibited a specific peak location, although high statistical fluctuation errors could be observed in the spectrum with the increasing source speed. In particular, ¹³⁷Cs and ⁶⁰Co in motion were identified completely (100%) at speeds of 5 and 10 km/hr. Further, SNMs, which trigger the RPM alarm, were identified approximately 80% of the time at both the aforementioned speeds. Conclusion: Using the modified energy-weighted algorithm, several characteristics of the energy weighted spectra could be observed when the used sources were in motion and when the geometric efficiency was low. In particular, the discrimination between ⁶⁰Co and ⁴⁰K, which triggers false alarms at the primary inspection sites, can be improved using the proposed algorithm.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.4
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• pp.294-302
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• 2019

As a series of fundamental researches on the development of an automatic identification monitoring system for fishing gear. Firstly, the study on the installation method of automated identification buoy for the coastal improvement net fishing net with many loss problems on the west coast was carried out. Secondly, the study was conducted find out how to install an automatic identification buoy for coastal gill net which has the highest loss rate among the fisheries. GPS for fishing was used six times in the coastal waters around Seogwipo city in Jeju Island to determine the developmental status and underwater behavior to conduct a field survey. Next, a questionnaire was administered in parallel on the type of loss and the quantity and location of fishing gear to be developed and the water transmitter. In the field experiment, the data collection was possible from a minimum of 13 hours, ten minutes to a maximum of 20 hours and ten minutes using GPS, identifying the development status and underwater behavior of the coastal gillnet fishing gear. The result of the survey showed that the loss of coastal net fishing gear was in the following order: net (27.3%), full fishing gear (24.2%), buoys, and anchors (18.2%). The causes were active algae (50.0%), fish catches (33.3%) and natural disasters (12.5%). To solve this problem, the installation method is to attach one and two electronic buoys to top of each end of the fishing gear, and one underwater transmitter at both ends of the float line connected to the anchor. By identifying and managing abnormal conditions such as damage or loss of fishing gear due to external factors such as potent algae and cutting of fishing gear, loss of fishing gear can be reduced. If the lost fishing gear is found, it will be efficiently collected.

• Journal of Oriental Neuropsychiatry
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• v.32 no.1
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• pp.1-11
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• 2021

Objectives: To investigate the prevalence of acute stress disorder (ASD) and post-traumatic stress disorder (PTSD) in patients with traffic injuries. In addition, PTSD patients was classified using 'pattern identification for jing ji and zheng chong'. Methods: Questionnaires such as the primary care PTSD screen for DSM-5(PC-PTSD-5), Korean version of PTSD checklist-5 (PCL-5-K), and the instrument of pattern identification for jing ji and zheng chong were conducted on 195 patients within 3 days to 1 year after traffic accidents. Patients were recruited from six medical institutions. Collected data were used to determine the prevalence of acute stress disorder and post-traumatic stress disorder. Results: On PC-PTSD-5, the prevalence was 39.1% for ASD and 50% for PTSD. On PCL-5-K, the prevalence was 20.4% for ASD and 29.3% for PTSD. Satisfying both PC-PTSD-5 and PCL-5-K, the prevalence was 18.2% for ASD and 25.8% for PTSD. As a result of pattern identification for jing ji and zheng chong, 'weakness of heart and gall bladder type' accounted for the highest proportions in both ASD and PTSD groups. Conclusions: In this study, the prevalence was 39.1% for ASD and 50% for PTSD by PC-PTSD-5. Satisfying both PC-PTSD-5 and PCL-5-K, the prevalence was 18.2% for ASD and 25.8% for PTSD. Further large-scale prospective studies are needed to analyze the prevalence of ASD and PTSD, the rate of progression from ASD to PTSD, and the type of pattern identification.

• Journal of Microbiology and Biotechnology
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• v.24 no.9
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• pp.1189-1195
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• 2014

A strain-specific identification method is required to secure Chlorella strains with useful genetic traits, such as a fast growth rate or high lipid productivity, for application in biofuels, functional foods, and pharmaceuticals. Microsatellite markers based on simple sequence repeats can be a useful tool for this purpose. Therefore, this study developed five novel microsatellite markers (mChl-001, mChl-002, mChl-005, mChl-011, and mChl-012) using specific loci along the chloroplast genome of Chlorella vulgaris. The microsatellite markers were characterized based on their allelic diversities among nine strains of C. vulgaris with the same 18S rRNA sequence similarity. Each microsatellite marker exhibited 2~5 polymorphic allele types, and their combinations allowed discrimination between seven of the C. vulgaris strains. The two remaining strains were distinguished using one specific interspace region between the mChl-001 and mChl-005 loci, which was composed of about 27 single nucleotide polymorphisms, 13~15 specific sequence sites, and (T)n repeat sites. Thus, the polymorphic combination of the five microsatellite markers and one specific locus facilitated a clear distinction of C. vulgaris at the strain level, suggesting that the proposed microsatellite marker system can be useful for the accurate identification and classification of C. vulgaris.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.1
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• pp.10-18
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• 2017

In this paper, we designed and implemented a visible light identification(VLID) system consisting of a VLID reader and a tag which backscatters incident lights from the reader. A VLID tag sends its ID to the reader by switching an LCD shutter which is located on its surface. The VLID reader consists of six LEDs and a photodiode(PD). The LEDs emit visible light and a PD located in a center position of LEDs receives backscattered light from the VLID tag. A microcontroller and a commercial liquid crystal display(LCD) shutter for 3D-TV glasses are used to implement a VLID tag. Experiments were conducted to confirm VLID system performance. We successfully demonstrated experiments to send NRZ-OOK signal of 100 bps over a distance of 35 cm at daytime. Also, we suggested the theoretical maximum transmission rate and the various methods to enhance the separation distance between a VLID reader and a tag.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.109-116
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• 2019

This study proposed a robust detection algorithm. It detects face more stably with respect to changes in light and rotation for the identification of a face shape. Also it satisfies both efficiency of calculation and the function of detection. The algorithm proposed segmented the face area through pre-processing using a face shape as input information in an environment with a single camera and then identified the shape using a Self Organized Feature Map(SOFM). However, as it is not easy to exactly recognize a face area which is sensitive to light, it has a large degree of freedom, and there is a large error bound, to enhance the identification rate, rotation information on the face shape was made into a database and then a principal component analysis was conducted. Also, as there were fewer calculations due to the fewer dimensions, the time for real-time identification could be decreased.

• 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.

• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.13-24
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• 2008

A next generation video based car navigation is researched to supplement the drawbacks of existed 2D based navigation and to provide the various services for safety driving. The components of this navigation system could be a load object database, identification module for load lines, and crossroad identification module, etc. In this paper, we proposed the traffic lights and road sign recognition method which can be effectively exploited for crossroad recognition in video-based car navigation systems. The method uses object color information and other spatial features in the video image. The results show average 90% recognition rate from 30m to 60m distance for traffic lights and 97% at 40-90m distance for load sign. The algorithm also achieves 46msec/frame processing time which also indicates the appropriateness of the algorithm in real-time processing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1031-1039
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• 2015

Present guided missiles are equipped with infrared seeker to find the infrared sources radiating from target plane and then chase, which results in an improvement of the hitting success rate when in striking target objects. To interrupt the chases from the guided missile, the target plane spreads the flare, avoiding the missile attracts. Our research is to develop a 2-color infrared identification technique to discern the flare and real thermal source from target plane. Considering flare radiation properties and EM atmosphere transmission rates, two channels were selected, in which main channel (MC) was in a range of 3.7 μm∼4.8 μm and auxiliary channel (AC) in 1.7 μm∼2.3 μm. A 2500K heat source was used for an artificial flare source, while a 570K heat source was utilized for airplane infrared source in experimental testing. Two infrared sensors detectable only at each chanel were employed in order to measure the voltage ratio from two channels, identifying the flare and real target plane via comparison the voltage ratio. Several experimental conditions were imported in order to prove that our proposed 2-color infrared identification technique is very efficient way to discern heat sources from aircraft and flare, demonstrating that our proposed technique is very promising means for our force’s InfraRed Counter Counter Measure (IRCCM) in order to countermeasure opposite force’s InfraRed Counter Measures (IRCM).