• Smart Structures and Systems
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• v.18 no.5
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• pp.983-1004
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• 2016

Nowadays, there are two classes of methods for damage detection in structures consisting of static and dynamic. The dynamic methods are based on studying the changes in structure's dynamic characteristics. The theoretical basis of this method is that damage causes changes in dynamic characteristics of structures. The dynamic methods are divided into two categories: signal based and modal based. The modal based methods utilize the modal properties consisting of natural frequencies, modal damping and mode shapes. As the modal properties are sensitive to changes in the structure, these can be used for detecting the damages. In this study, using dynamic method and modal based approach (natural frequencies and mode shapes), the objective function is formulated. Then, detection of damages of truss structures is addressed by using Simplified Dolphin Echolocation algorithm and solving inverse optimization problem. Many scenarios are used to simulate the damages. To demonstrate the ability of the algorithm, different truss structures with several multiple elements scenarios are tested using a few runs. The influence of the two different levels of noise in the modal data for these scenarios is also considered. The last example of this article is investigated using a different mutation. This mutation obtains the exact answer with fewer loops and population by limited computational effort.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.388-396
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• 2009

This paper proposes a new fire-smoke detection method by using extracted features from camera images and pattern recognition technique. First, moving regions are detected by analyzing the frame difference between two consecutive images and generate candidate smoke regions by applying smoke color model. A smoke region generally has a few characteristics such as similar color, simple texture and upward motion. From these characteristics, we extract brightness, wavelet high frequency and motion vector as features. Also probability density functions of three features are generated using training data. Probabilistic models of smoke region are then applied to observation nodes of our proposed Dynamic Bayesian Networks (DBN) for considering time continuity. The proposed algorithm was successfully applied to various fire-smoke tasks not only forest smokes but also real-world smokes and showed better detection performance than previous method.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.7
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• pp.521-526
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• 2018

In particular, gas sensors require characteristics such as high speed, sensitivity, and selectivity. In this study, we fabricated a $NO_X$ gas sensor by using a multi-walled carbon nanotube (MWCNT)/zinc oxide (ZnO) composite film. The fabricated MWCNT/ZnO gas sensor was then treated by a $450^{\circ}C$ temperature process to increase its detection sensitivity for NOx gas. We compared the detection characteristics of a ZnO film gas sensor, MWCNT film gas sensor, and the MWCNT/ZnO composited film gas sensor with and without the heat-treatment process. The fabricated gas sensors were used to detect $NO_X$ gas at different concentrations. The gas sensor absorbed $NO_X$ gas molecules, exhibiting increased sensitivity. The sensitivity of the gas sensor was increased by increasing the gas concentration. Additionally, while changing the temperature inside the chamber for the MWCNT/ZnO composite film gas sensor, we obtained its sensitivity for detecting $NO_X$ gas. Compared with ZnO, the MWCNT film gas sensor is excellent for detecting $NO_X$ gas. From the experimental results, we confirmed the enhanced gas sensor sensing mechanism. The increased effect by electronic interaction between the MWCNT and ZnO films contributes to the improved sensor performance.

• Journal of Radiation Protection and Research
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• v.42 no.1
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• pp.48-55
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• 2017

Background: Simultaneous detection of neutrons and gamma rays have become much more practicable, by taking advantage of good gamma-ray discrimination properties using pulse shape discrimination (PSD) technique. Recently, we introduced a commercial CLYC system in Korea, and performed an initial characterization and simulation studies for the CLYC detector system to provide references for the future implementation of the dual-mode scintillator system in various studies and applications. Materials and Methods: We evaluated a CLYC detector with 95% $^6Li$ enrichment using various gamma-ray sources and a $^{252}Cf$ neutron source, with validation of our Monte Carlo simulation results via measurement experiments. Absolute full-energy peak efficiency values were calculated for gamma-ray sources and neutron source using MCNP6 and compared with measurement experiments of the calibration sources. In addition, behavioral characteristics of neutrons were validated by comparing simulations and experiments on neutron moderation with various polyethylene (PE) moderator thicknesses. Results and Discussion: Both results showed good agreements in overall characteristics of the gamma and neutron detection efficiencies, with consistent ~20% discrepancy. Furthermore, moderation of neutrons emitted from $^{252}Cf$ showed similarities between the simulation and the experiment, in terms of their relative ratios depending on the thickness of the PE moderator. Conclusion: A CLYC detector system was characterized for its energy resolution and detection efficiency, and Monte Carlo simulations on the detector system was validated experimentally. Validation of the simulation results in overall trend of the CLYC detector behavior will provide the fundamental basis and validity of follow-up Monte Carlo simulation studies for the development of our dual-particle imager using a rotational modulation collimator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1355-1362
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• 2004

In this paper, we present the performance analysis of a multi-path searcher operating over Rayleigh fading channels when multiple transmit antennas are employed in the down-link of W-CDMA system. The simulation results for the receiver operating characteristics (ROC) for 1, 2, and 4 transmit antennas are presented to corroborate the theoretical analyses. We also propose a procedure to find the optimum parameters of double-dwell serial searcher according to the number of the multiple transmit antennas. Our analyses and simulations indicate that post-detection integration is not necessary when the number of transmit antennas is more than two. Finally, we found that increasing transmit diversity order does not necessarily improve the detection performance when the received pilot signal strength is relatively low. Therefore, this gives us a practical criterion on increasing transmit diversity order.

• Journal of Sensor Science and Technology
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• v.29 no.6
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• pp.407-411
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• 2020

In this study, we propose an array-type gas sensor with high selectivity and response using multiple oxide semiconductors. The sensor array was composed of SnO₂ and In₂O₃, and the detection characteristics were improved by using Pt, Au, and Pd catalysts. All samples were deposited directly on the Pt interdigitated electrode (IDE) through the e-beam evaporator glancing angle deposition (GAD) method. They grew in the form of well-aligned nanorods at off-axis angles. The prepared SnO₂ and In₂O₃ nanorod samples were exposed to CH₃COCH₃, C₇H₈, and NO₂ gases in a 300℃ dry condition. Au-decorated SnO₂, Au-decorated In₂O₃, and Pd-decorated In₂O₃ exhibited high selectivity for CH₃COCH₃, C₇H₈, and NO₂, respectively. They demonstrated a high detection limit of the sub ppb level computationally. In addition, measurements from each sensor were executed in the 40% relative humidity condition. Although there was a slight reduction in detection response, high selectivity and distinguishable detection characteristics were confirmed.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.481-487
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• 2020

Radiation measurement technology has steadily improved and its usage is expanding in various industries such as nuclear medicine, security search, satellite, nondestructive testing, environmental industries and the domain of nuclear power plants (NPPs). Especially, the simultaneous measurements of gamma rays and neutrons can be even more critical for nuclear safety management of spent nuclear fuel and monitoring of the nuclear material. A semiconductor detector comprising cadmium, zinc, and tellurium (CZT) enables to detect gamma-rays due to the significant atomic weight of the elements via immediate neutron and gamma-ray detection. Semiconductor sensors might be used for nuclear safety management by monitoring nuclear materials and spent nuclear fuel with high spatial resolution as well as providing real-time measurements. We aim to introduce a portable nuclide-analysis device that enables the simultaneous measurements of neutrons and gamma rays using a CZT sensor. The detector has a high density and wide energy band gap, and thus exhibits highly sensitive physical characteristics and characteristics are required for performing neutron and gamma-ray detection. Portable nuclide-analysis device is used on NPP-decommissioning sites or the purpose of nuclear nonproliferation, it will rapidly detect the nuclear material and provide radioactive-material information. Eventually, portable nuclide-analysis device can reduce measurement time and economic costs by providing a basis for rational decision making.

• Journal of IKEEE
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• v.26 no.3
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• pp.488-493
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• 2022

In manufacturing sites, bearing fault in eletrically driven motors cause the entire system to shut down. Stopping the operation of this environment causes huge losses in time and money. The reason of this bearing defects can be various factors such as wear due to continuous contact of rotating elements, excessive load addition, and operating environment. In this paper, a motor driving environment is created which is similar to the domestic manufacturing sites. In addition, based on the established environment, we propose a dataset for bearing fault detection by collecting changes in vibration characteristics that vary depending on normal and defective conditions. The sensor used to collect the vibration characteristics is Microphone G.R.A.S. 40PH-10. We used various machine learning models to build a prototype bearing fault detection system trained on the proposed dataset. As the result, based on the deep neural network model, it shows high accuracy performance of 92.3% in the time domain and 98.3% in the frequency domain.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.6
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• pp.912-917
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• 2021

We investigated the distribution, molecular characteristics, and antimicrobial resistance of Vibrio vulnificus isolated from seawater at Gadeok Island, the Republic of Korea between June to October. Interestingly no isolates were detected between December to February. The detection rate of V. vulnificus was high (80-100%) from July to September 2019 and from June to September 2020. This coincided with the relatively low salinity of the seawater, which ranged from 7.8-29.9 practical salinity units for that period. Additionally, V. vulnificus had a high detection rate at sampling stations near the Nakdong river. The detection rates of virulence genes, such as vvhA, viuB, and vcgC, among the isolates were 97.1%, 44.1%, and 57.4% in 2019 and 100%, 43.0%, and 50.0% in 2020, respectively. Notably, viuB and vcgC were detected in V. vulnificus isolated between June to October when water temperature was above 20℃. The antimicrobial susceptibility analysis of 80 isolates revealed that most of the strains were susceptible to most antimicrobial agents. However, some isolates showed intermediate resistance to cefepime (18.8%), cefoxitin (58.8%), and erythromycin (22.5%). Of note, 3.8% of the tested strains were resistant to cefoxitin. The minimum inhibitory concentration of highly cefoxitin-resistant strains was determined to be less than 32 ㎍/mL.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.47-57
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• 2009

Event detection and recognition is an active and challenging topic recent in Computer Vision. This paper describes a new method for recognizing events caused by human motion from video sequences in an office environment. The proposed approach analyzes human motions using Motion History Image (MHI) sequences, and is invariant to body shapes. types or colors of clothes and positions of target objects. The proposed method has two advantages; one is thant the proposed method is less sensitive to illumination changes comparing with the method using color information of objects of interest, and the other is scale invariance comparing with the method using a prior knowledge like appearances or shapes of objects of interest. Combined with edge detection, geometrical characteristics of the human shape in the MHI sequences are considered as the features. An advantage of the proposed method is that the event detection framework is easy to extend by inserting the descriptions of events. In addition, the proposed method is the core technology for event detection systems based on context-aware computing as well as surveillance systems based on computer vision techniques.