• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.514-522
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• 2022

Non-destructive testing (NDT) technology is a widely used inspection method for agricultural products. Compared with the conventional inspection method, there is no extensive sample preparation for NDT technology, and the sample is not damaged. In particular, NDT technology is used to inspect the internal structure of agricultural products infested by pests. The introduction and spread of pests during the import and export process can cause significant damage to the agricultural environment. Until now, pest detection in agricultural products and quarantine processes have been challenging because they used external inspection methods. However, NDT technology is advantageous in these inspection situations. In this pilot study, we investigated the feasibility of X-ray computed tomography (X-ray CT) and magnetic resonance imaging (MRI) to identify pest infestation in agricultural products. Three kinds of artificially pest-infested fruits (mango, tangerine, and chestnut) were non-destructively inspected using X-ray CT and MRI. X-ray CT was able to identify all pest infestations in fruits, while MRI could not detect the pest-infested chestnut. In addition, X-ray CT was superior to the quarantine process than MRI based on the contrast-to-noise ratio (CNR), image acquisition time, and cost. Therefore, X-ray CT is more appropriate for the pest quarantine process of fruits than MRI.

• Food Science of Animal Resources
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• v.42 no.1
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• pp.1-17
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• 2022

Lipids are one of the major macronutrients essential for adequate growth and maintenance of human health. Their structure is not only complex but also diverse, which makes systematic and holistic analyses challenging; consequently, little is known regarding the relationship between phenotype and mechanism of action. In recent years, rapid advancements have been made in the fields of lipidomics and bioinformatics. In comparison with traditional approaches, mass spectrometry-based lipidomics can rapidly identify as well as quantify >1,000 lipid species at the same time, facilitating comprehensive, robust analyses of lipids in tissues, cells, and body fluids. Accordingly, lipidomics is now being widely applied in various fields, particularly food and nutrition science. In this review, we discuss lipid classification, extraction techniques, and detection and analysis using lipidomics. We also cover how lipidomics is being used to assess food obtained from livestock and poultry. The information included herein should serve as a reference to determine how to characterize lipids in animal food samples, enhancing our understanding of the application of lipidomics in the field in animal husbandry.

• Journal of IKEEE
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• v.26 no.3
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• pp.364-372
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• 2022

This paper proposes the design and implementation results for human and object classification systems utilizing frequency modulated continuous wave (FMCW) radar sensor. Such a system requires the process of radar sensor signal processing for multi-target detection and the process of deep learning for the classification of human and object. Since deep learning requires such a great amount of computation and data processing, the lightweight process is utmost essential. Therefore, binary neural network (BNN) structure was adopted, operating convolution neural network (CNN) computation in a binary condition. In addition, for the real-time operation, a hardware accelerator was implemented and verified via FPGA platform. Based on performance evaluation and verified results, it is confirmed that the accuracy for multi-target classification of 90.5%, reduced memory usage by 96.87% compared to CNN and the run time of 5ms are achieved.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.5
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• pp.1-7
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• 2021

This study attempted to detect possible collapse and fire accidents in facilities for disaster monitoring of large facilities, and to develop a customized beacon to recognize the internal situation of an IoT-based facility when a disaster occurs. In the case of data measurement using the existing strain gauge sensor, the strain gauge sensor was connected by wire to measure it, but this study changed it to wireless so that the presence and absence of structural deformation can be monitored in real time. In this process, in order to use the Wheatstone bridge, a strain sensor module that can be connected to a customized beacon was manufactured, and a system configuration was conducted to remotely check the measurement data. To verify measurement data, 10 customized beacons and 2 gateways were installed on the 15th floor of the Advanced Institue of Convergence Technology, and as a result of analysis of measurement data, it was confirmed that the strain data values were distributed between 7 and 8.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.6
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• pp.594-602
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• 2022

Cast-resin transformers are widely installed in various electrical power systems because of their low operating cost and low influence on external environmental factors. However, when they have an internal defect during the manufacturing process or operation, a partial discharge (PD) occurs, and eventually destroys the insulation. In this paper, a Rogowski-type PD sensor was studied to replace commercial PD sensors used for the insulation diagnosis of power apparatus. The proposed PD sensor was manufactured with four different types of PCB-based winding structures, and it was analyzed in terms of the detection characteristics for standard calibration pulses and the changes of the output voltage according to the distance. The output increased linearly in accordance with the applied discharge amount. It was confirmed that the hexagon structure sensor had the highest sensitivity, because the winding cross-sectional area of the sensor was larger than others. In addition, as the distance from the defect increased, the output voltage of the sensors decreased by 7.32% on average. It was also confirmed that the attenuation rate according to the distance decreased as the input discharge amount increased. For the application of this new type sensor, PD electrode system was designed to simulate the void defect. Waveforms and PRPD patterns measured by the proposed PD sensors at DIV and 120% of DIV were the same as the results measured by MPD 600 based on IEC 60270. The proposed PD sensors can be installed on the inner wall of the transformer tank by coating its surfaces with a non-conductive material; therefore, it is possible to detect internal defects more effectively at a closer distance from the defect than the conventional sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.639-641
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• 2022

With the increasing of aging population, a lot of researches on monitoring systems for solitary senior citizens are under study. In general, a monitoring system provides a monitoring service by computing the information of vision, sensors, and measurement values on a server. Design considering data security is essential because a risk of data leakage exists in the structure of the system employing the server. In this paper, we propose a intelligent monitoring system for solitary senior citizens with vision-based security architecture. The proposed system protects privacy by ensuring high security through an architecture that blocks communication between a camera module and a server by employing an edge AI module. The edge AI module was designed with Verilog HDL and verified by implementing on a Field Programmable Gate Array (FPGA). We tested our proposed system on 5,144 frame data and demonstrated that a dangerous detection signal is generated correctly when human motion is not detected for a certain period.

• Current Optics and Photonics
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• v.7 no.1
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• pp.38-46
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• 2023

Optical Fourier-domain reflectometry (OFDR) sensors have been widely used to measure distances with high resolution and speed in a noncontact state. In the electroplating process of a printed circuit board, it is critically important to monitor the copper-plating thickness, as small deviations can lead to defects, such as an open or short circuit. In this paper we employ a phase-based OFDR sensor for in situ relative distance sensing of a sample with nanometer-scale resolution, during electroplating. We also develop an optical-path difference (OPD)-regulated sensing probe that can maintain a preset distance from the sample. This function can markedly facilitate practical measurements in two aspects: Optimal distance setting for high signal-to-noise ratio OFDR sensing, and protection of a fragile probe tip via vertical evasion movement. In a sample with a centimeter-scale structure, a conventional OFDR sensor will probably either bump into the sample or practically out of the detection range of the sensing probe. To address this limitation, a novel OPD-regulated OFDR system is designed by combining the OFDR sensing probe and linear piezo motors with feedback-loop control. By using multiple OFDR sensors, it is possible to effectively monitor copper-plating thickness in situ and uniformize it at various positions.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.65.2-66
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• 2021

Observational studies of supernova (SN) feedback are limited. In our galaxy, most supernova remnants (SNRs) are located in the Galactic plane, so there is contamination from foreground/background sources. SNRs located in other galaxies are too far, so we cannot study them in detail. The Large Magellanic Cloud (LMC) is a unique place to study the SN feedback due to their proximity, which makes possible to study the structure of individual SNRs in some detail together with their environment. Recently, we carried out a systematic study of 13 LMC SNRs using [P II] (1.189 ㎛) and [Fe II] (1.257 ㎛) narrowband imaging with SIRIUS/IRSF, four SNRs (SN 1987A, N158A, N157B and N206), show [P II]/[Fe II] ratio much higher than the cosmic abundance. While the high ratio of SN 1987A could be due to enhanced abundance in SN ejecta, we do not have a clear explanation for the other cases. We investigate the [P II] knots found in SNRs N206, N157B and N158A, using optical spectra obtained last November with GMOS-S mounted on Gemini-South telescope. We detected several emission lines (e.g., H I, [O I], He I, [O III], [N II] and [S II]) that are present in all three SNRs, among other lines that are only found in some of them (e.g., [Ne III], [Fe III] and [Fe II]). Various line ratios are measured from the three SNRs, which indicate that the ratios of N157B tend to differ from those of other two SNRs. We will use the abundances of He and N (from the detection of [N II] and He I emission lines), together with velocity measurements to tell whether the origin of the [P II] knots are SN ejecta or CSM/ISM. For this purpose we have built a family of radiative shock with self-consistent pre-ionization using MAPPINGS 5.1.18, with shock velocities in the range of 100 to 475 km/s. We will compare the observed and modeled line fluxes for different depletion factors.

• 한국체육학회지인문사회과학편
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• v.54 no.5
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• pp.207-219
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• 2015

The purpose of this study was to test the validation of the Korean version of the Talent Development Environment Questionnaire for sport(TDEQ; Martindale et al., 2010), developed through the conceptual and statistical verification stages(substantive stage-structural stage-external stage). In accordance with the procedure of translation, the substantive concepts of the items were reviewed. The data were collected from a sample of 244 ; 117 high school student-athletes and 127 university student-athletes. In order to test the internal structure of TDEQ, EFA/CFA, and internal consistency were performed. As a result, Korean version of the TDEQ had 5 factors with 38 items. External relationship by correlation analysis and group differentiation analysis were obtained to enhance the validity of the test. Overall, the Korean TDEQ will be used as a diagnostic and evaluation tool at the stage of detection, identification, selection, and development of Sport Talent.

• Smart Structures and Systems
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• v.31 no.1
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• pp.57-68
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• 2023

Bridge hangers, such as those in suspension and cable-stayed bridges, suffer from cumulative fatigue damage caused by dynamic loads (e.g., cyclic traffic and wind loads) in their service condition. Thus, the identification of damage to hangers is important in preserving the service life of the bridge structure. This study develops a new method for condition assessment of bridge hangers. The tension force of the bridge and the damages in the element level can be identified using the Bayesian optimization method. To improve the number of observed data, the additional mass method is combined the Bayesian optimization method. Numerical studies are presented to verify the accuracy and efficiency of the proposed method. The influence of different acquisition functions, which include expected improvement (EI), probability-of-improvement (PI), lower confidence bound (LCB), and expected improvement per second (EIPC), on the identification of damage to the bridge hanger is studied. Results show that the errors identified by the EI acquisition function are smaller than those identified by the other acquisition functions. The identification of the damage to the bridge hanger with various types of boundary conditions and different levels of measurement noise are also studied. Results show that both the severity of the damage and the tension force can be identified via the proposed method, thereby verifying the robustness of the proposed method. Compared to the genetic algorithm (GA), particle swarm optimization (PSO), and nonlinear least-square method (NLS), the Bayesian optimization (BO) performs best in identifying the structural damage and tension force.