• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.103-113
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• 2019

License plate recognition camera is dedicated device designed for acquiring images of the target vehicle for recognizing letters and numbers in a license plate. Mostly, it is used as a part of the system combined with server and image analysis module rather than as a single use. However, building a system for vehicle license plate recognition is costly because it is required to construct a facility with a server providing the management and analysis of the captured images and an image analysis module providing the extraction of numbers and characters and recognition of the vehicle's plate. In this study, we would like to develop an embedded type convergent camera (Edge Base) which can expand the function of the camera to not only the license plate recognition but also the security CCTV function together and to perform two functions within the camera. This embedded type convergence camera equipped with a high resolution 4K IP camera for clear image acquisition and fast data transmission extracted license plate area by applying YOLO, a deep learning software for multi object recognition based on open source neural network algorithm and detected number and characters of the plate and verified the detection accuracy and recognition accuracy and confirmed that this camera can perform CCTV security function and vehicle number plate recognition function successfully.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.263-268
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• 2019

Methanol is a toxic alcohol used in various products such as antifreeze, detergent, disinfectant and industrial solvent. In the human body, methanol is oxidized to formaldehyde and formic acid, which can lead to metabolic acidosis, optic nerve impairment, and death. In this study, the methanol levels in detergents (n=191) and rinse aids (n=13) were analyzed by gas chromatography-headspace-mass spectrometry (GC-HS-MS). Limit of detection was 1.09 mg/kg, accuracy and precision were 91.1-97.9% and <10%, and it was suitable for quantitative analysis. This analysis method was simple and fast with a higher recovery rate than the conventional MFDS (Ministry of Food and Drug Safety) method of diluting the sample in water and putting it in a headspace vial.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.73-80
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• 2021

In this paper, we propose a packet processing method capable of handling large-capacity traffic over 20Gbps using multi-core and huge page memory approaches. As ICT technology advances, the global average monthly traffic is expected to reach 396 exabytes by 2022. With the increase in network traffic, cyber threats are also increasing, increasing the importance of traffic analysis. Traffic analyzed as an existing high-cost foreign product simply stores statistical data and visually shows it. Network administrators introduce and analyze many traffic analysis systems to analyze traffic in various sections, but they cannot check the aggregated traffic of the entire network. In addition, since most of the existing equipment is of the 10Gbps class, it cannot handle the increasing traffic every year at a fast speed. In this paper, as a method of processing large-capacity traffic over 20Gbps, the process of processing raw packets without copying from single-core and basic SMA memory approaches to high-performance packet reception, packet detection, and statistics using multi-core and NUMA memory approaches suggest When using the proposed method, it was confirmed that more than 50% of the traffic was processed compared to the existing equipment.

• Korean Journal of Agricultural Science
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• v.48 no.2
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• pp.299-310
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• 2021

Glycerol is a non-volatile compound with no aromatic properties that contributes significantly to the quality of wine by providing sweetness and richness of taste. In addition, it is also the third most significant byproduct of alcoholic fermentation in terms of quantity after ethanol and carbon dioxide. In this study, Fourier transform infrared (FT-IR) spectroscopy was employed as a fast non-destructive method in conjugation with multivariate regression analysis to build a model for the quantitative analysis of glycerol concentration in wine samples. The samples were prepared by using three varieties of red wine samples (i.e., Shiraz, Merlot, and Barbaresco) that were adulterated with glycerol in concentration ranges from 0.1 to 15% (v·v^-1), and subjected to analysis together with pure wine samples. A net analyte signal (NAS)-based methodology, called hybrid linear analysis in the literature (HLA/GO), was applied for predicting glycerol concentrations in the collected FT-IR spectral data. Calibration and validation sets were designed to evaluate the performance of the multivariate method. The obtained results exhibited a high coefficient of determination (R²) of 0.987 and a low root mean square error (RMSE) of 0.563% for the calibration set, and a R² of 0.984 and a RMSE of 0.626% for the validation set. Further, the model was validated in terms of sensitivity, selectivity, and limits of detection and quantification, and the results confirmed that this model can be used in most applications, as well as for quality assurance.

• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.305-312
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• 2021

Even though various types of sensors are being used for security applications, radar sensors are being suggested as an alternative due to the privacy issues. Among those radar sensors, PD radar has high-complexity receiver, but, FMCW radar requires fewer resources. However, FMCW has disadvantage from the use of 2D-FFT which increases the complexity, and it is difficult to distinguish people from objects those are stationary. In this paper, we present the design and the implementation results of the radar signal processor (RSP) that can distinguish between people and object by respiration measurement using phase estimation without 2D-FFT. The proposed RSP is designed with Verilog-HDL and is implemented on FPGA device. It was confirmed that the proposed RSP includes 6,425 LUT, 4,243 register, and 12,288 memory bits with 92.1% accuracy for target's breathing status.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.71-80
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• 2022

In the past, fish diseases were bacterial in aqua farms, but in recent years, the frequency of fish diseases has increased as they have become viral and mixed. Viral diseases in an enclosed space called a aqua farm have a high spread rate, so it is very likely to lead to mass death. Fast identification of fish diseases is important to prevent group death. However, diagnosis of fish diseases requires a high level of expertise and it is difficult to visually check the condition of fish every time. In order to prevent the spread of the disease, an automatic identification system of diseases or fish is needed. In this paper, in order to improve the performance of the disease identification system of Paralichthys olivaceus based on deep learning, the existing pre-processing method is compared and tested. Target diseases were selected from three most frequent diseases such as Scutica, Vibrio, and Lymphocystis in Paralichthys olivaceus. The RGB, HLS, HSV, LAB, LUV, XYZ, and YCRCV were used as image pre-processing methods. As a result of the experiment, HLS was able to get the best results than using general RGB. It is expected that the fish disease identification system can be advanced by improving the recognition rate of diseases in a simple way.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.409-418
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• 2022

In this paper, we propose SAAnnot-C3Pap, a semi-automatic annotation method for obtaining ground truth of a player's posture. In order to obtain ground truth about the two-dimensional joint position in the existing music domain, openpose, a two-dimensional posture estimation method, was used or manually labeled. However, automatic annotation methods such as the existing openpose have the disadvantages of showing inaccurate results even though they are fast. Therefore, this paper proposes SAAnnot-C3Pap, a semi-automated annotation method that is a compromise between the two. The proposed approach consists of three main steps: extracting postures using openpose, correcting the parts with errors among the extracted parts using supervisely, and then analyzing the results of openpose and supervisely. Perform the synchronization process. Through the proposed method, it was possible to correct the incorrect 2D joint position detection result that occurred in the openpose, solve the problem of detecting two or more people, and obtain the ground truth in the playing posture. In the experiment, we compare and analyze the results of the semi-automated annotation method openpose and the SAAnnot-C3Pap proposed in this paper. As a result of comparison, the proposed method showed improvement of posture information incorrectly collected through openpose.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.1-11
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• 2023

Breast cancer is the disease that affects women the most worldwide. Due to the development of computer technology, the efficiency of machine learning has increased, and thus plays an important role in cancer detection and diagnosis. Deep learning is a field of machine learning technology based on an artificial neural network, and its performance has been rapidly improved in recent years, and its application range is expanding. In this paper, we propose a DNN-SVM hybrid model that combines the structure of a deep neural network (DNN) based on transfer learning and a support vector machine (SVM) for breast cancer classification. The transfer learning-based proposed model is effective for small training data, has a fast learning speed, and can improve model performance by combining all the advantages of a single model, that is, DNN and SVM. To evaluate the performance of the proposed DNN-SVM Hybrid model, the performance test results with WOBC and WDBC breast cancer data provided by the UCI machine learning repository showed that the proposed model is superior to single models such as logistic regression, DNN, and SVM, and ensemble models such as random forest in various performance measures.

• Analytical Science and Technology
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• v.25 no.3
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• pp.171-177
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• 2012

A determination method of aromatic amino acids such as trytophan (Trp), tyrosine (Tyr), and phenylalanine (Phe) using luminol-$H_2O_2$-Cu(II) system has been presented. In the presence of an aromatic amino acid, the enhanced chemiluminescence (CL) intensity of luminol-$H_2O_2$-Cu(II) system was obtained by forming a complex between Cu(II) and the amino acid. Based on the above phenomenon, a sensitive and fast determination of three aromatic amino acids was performed using the CL method in batch-type detection system. To optimize determination conditions, the kinetic influence of an aromatic amino acid on the luminol-$H_2O_2$-Cu(II) system and the effects of $H_2O_2$ and Cu(II) concentration, pH, and buffers were investigated. Under the optimized conditions, the calibration curve was linear over the range from $1.0{\times}10^{-6}$ to $2.0{\times}10^{-5}\;M$ for Trp, $1.0{\times}10^{-6}$ to $2.0{\times}10^{-5}\;M$ for Try, and $2.0{\times}10^{-6}$ to $2.0{\times}10^{-5}\;M$ for Phe, respectively. In this range, reproducibility (RSD, n = 4) of Trp, Try, and Phe were 3.21%, 2.64%, and 2.48%, respectively. The limit of detection ($3{\sigma}/s$) was calculated to be $6.8{\times}10^{-7}\;M$ for Trp, $5.7{\times}10^{-7}\;M$ for Try, and $9.6{\times}10^{-7}\;M$ for Phe.

• Korean Security Journal
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• no.26
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• pp.29-58
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• 2011

Since 11 September 2001, warnings of risk in the nexus of terrorism and nuclear weapons and materials which poses one of the gravest threats to the international community have continued. The purpose of this study is to analyze the aim, principles, characteristics, activities, impediments to progress and developmental recommendation of the Global Initiative to Combat Nuclear Terrorism(GICNT). In addition, it suggests implications of the GICNT for the ROK policy. International community will need a comprehensive strategy with four key elements to accomplish the GICNT: (1) securing and reducing nuclear stockpiles around the world, (2) countering terrorist nuclear plots, (3) preventing and deterring state transfers of nuclear weapons or materials to terrorists, (4) interdicting nuclear smuggling. Moreover, other steps should be taken to build the needed sense of urgency, including: (1) analysis and assessment through joint threat briefing for real nuclear threat possibility, (2) nuclear terrorism exercises, (3) fast-paced nuclear security reviews, (4) realistic testing of nuclear security performance to defeat insider or outsider threats, (5) preparing shared database of threats and incidents. As for the ROK, main concerns are transfer of North Korea's nuclear weapons, materials and technology to international terror groups and attacks on nuclear facilities and uses of nuclear devices. As the 5th nuclear country, the ROK has strengthened systems of physical protection and nuclear counterterrorism based on the international conventions. In order to comprehensive and effective prevention of nuclear terrorism, the ROK has to strengthen nuclear detection instruments and mobile radiation monitoring system in airports, ports, road networks, and national critical infrastructures. Furthermore, it has to draw up effective crisis management manual and prepare nuclear counterterrorism exercises and operational postures. The fundamental key to the prevention, detection and response to nuclear terrorism which leads to catastrophic impacts is to establish not only domestic law, institution and systems, but also strengthen international cooperation.