• Smart Media Journal
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• v.5 no.1
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• pp.15-23
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• 2016

This paper proposes an effective algorithm of Korean license plate recognition. By applying Haar-like feature and Canny edge detection on a captured vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are classified using neural networks trained by backpropagation algorithm to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

• Analytical Science and Technology
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• v.13 no.1
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• pp.101-107
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• 2000

The automotive paints could be generally differentiated by color, layer sequence and chemistry of the paint layers comprising each of the topcoat and the primer system. The successful identification of hit-andrun a and traffic accidental vehicles from evidential paint fiagments is greatly facilitated with a comprehensive laboratory collection of reference paint samples and the technique for direct analysis without sample preparation. The Pyrolysis-Gas Chromatography(PGC) is a precise and reliable method for performing both quantitative and qualitative analysis of polymeric materials and forensic samples. Our Forensic Laboratory is conducting the examination and identification of 73 reference paint samples; 4 colors of each domestic automotive make that is popular in Korea, by Curie Point Pyrolyzer(JHP-3) and GC with capillary column(ultra alloy-5). This method can be used not only to compare paint traces with their suspected sources, but also to identify the type, make and model of the automotive car.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.593-600
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• 2018

Owing to the advancement of Internet and smart devices, access to various media such as social media became easy; thus, a large amount of big data is being produced. Particularly, the companies that provide various Internet services are analyzing the big data by using the MapReduce-based big data analysis techniques to investigate the customer preferences and patterns and strengthen the security. However, with MapReduce, when the big data is analyzed by defining the number of reducer objects generated in the reduce stage as one, the processing rate of big data analysis decreases. Therefore, in this paper, a MapReduce-based split big data analysis method is proposed to improve the log analysis processing rate. The proposed method separates the reducer partitioning stage and the analysis result combining stage and improves the big data processing rate by decreasing the bottleneck phenomenon by generating the number of reducer objects dynamically.

• Korean Journal of Food Science and Technology
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• v.53 no.2
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• pp.165-173
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• 2021

One of the major sources of air pollution is urban particulate matter (UPM), which causes lung diseases involving oxidative stress, inflammation, and cancer. Codonopsis lanceolata (CL) has been used in East Asia as a traditional oriental medicinal ingredient for lung diseases (e.g., asthma and bronchitis). However, the connection between the impact of CL and UPM in the lungs has rarely been investigated. This study aimed to confirm the inhibitory activity of the ethanol extract of CL (ECL) against oxidative stress and disruption of tight cell junctions in human pulmonary epithelial cells after exposure to UPM. As the lung cells were pre-treated with ECL, the UPM-induced increase in cellular reactive oxygen species production suppressed tight junction proteins (e.g., N-cadherin, fibronectin, occludin, zonula occludens-1, and claudin-4). These results suggest that ECL prevents the possible effects of UPM toxicity on the lungs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.187-192
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• 2021

This study proposes a system for take-off in a forest or similar complex environment using an object detector. In the simulator, a raspberry pi is mounted on a quadcopter with a length of 550mm between motors on a diagonal line, and the experiment is conducted based on edge computing. As for the images to be used for learning, about 150 images of 640⁎480 size were obtained by selecting three points inside Kunsan University, and then converting them to black and white, and pre-processing the binarization by placing a boundary value of 127. After that, we trained the SSD_Inception model. In the simulation, as a result of the experiment of taking off the drone through the model trained with the verification image as an input, a trajectory similar to the takeoff was drawn using the label.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.233-242
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• 2023

The unscented Kalman filter (UKF), which is widely used to estimate the states of nonlinear dynamic systems, can be improved to realize robust system identification by using multiple sigma-point sets. When using Kalman filter methods for system identification, artificial noises must be appropriately selected to achieve optimal estimation performance. Additionally, an appropriate scaling factor for the sigma-points must be selected to capture the nonlinearity of the state-space model. This study entailed the use of Bouc-Wen hysteresis model to examine the nonlinear behavior of a single-degree-of-freedom oscillator. On the basis of the effects of the selected artificial noises and scaling factor, a new UKF method using multiple sigma-point sets was devised for improved robustness of the estimation over various signal-to-noise-ratio values. The results demonstrate that the proposed method can accurately track nonlinear system states even when the measurement noise levels are high, while being robust to the selection of artificial noise levels.

• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.57-64
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• 2023

As the meter reading method of gas meters develops, smart gas meters capable of remote meter reading (leak checking meters and multi-function safety meters) are being used. These meters have a function to judge leakage by utilizing the flow rate and pressure data collected as an additional function. Leakage judgment function using flow rate data has valid cases in the actual field, but the pressure data-based leakage judgment standard is based on not only the pressure value change due to leakage but also various factors (pressure regulator pressure, connection with adjacent meters, usage of adjacent houses, location of meters, etc.). There is a problem with pressure magnitude changes (levels). In this paper, as a technique that can judge leaks by using pressure data collected from smart gas meters, it was developed through preprocessing of pressure data, criteria for pressure value ranges related to leaks, leak judgment techniques, and application case verification.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.81-87
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• 2023

Intrusion detection systems that learn metadata of network packets have been proposed recently. However these approaches require time to analyze packets to generate metadata for model learning, and time to pre-process metadata before learning. In addition, models that have learned specific metadata cannot detect intrusion by using original packets flowing into the network as they are. To address the problem, this paper propose a natural language processing-based intrusion detection system that detects intrusions by learning the packet payload as a single sentence without an additional conversion process. To verify the performance of our approach, we utilized the UNSW-NB15 and Transformer models. First, the PCAP files of the dataset were labeled, and then two Transformer (BERT, DistilBERT) models were trained directly in the form of sentences to analyze the detection performance. The experimental results showed that the binary classification accuracy was 99.03% and 99.05%, respectively, which is similar or superior to the detection performance of the techniques proposed in previous studies. Multi-class classification showed better performance with 86.63% and 86.36%, respectively.

• The korean journal of orthodontics
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• v.34 no.4 s.105
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• pp.325-332
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• 2004

A self-etching primer that combines the etchant and primer in one chemical compound saves time and should be mote cost-effective to the clinician and patient. The purpose of this study was to evaluate the clinical effectiveness of a self-etching primer by measuring shear bond strengths according to various conditions and observing adhesive failure patterns. For this Investigation, 120 upper and lower premolars extracted for orthodontic purposes were used and randomly divided into six groups of twenty teeth each. Human premolars were embedded in a metal cylinder with orthodontic resin. Metal brackets and ceramic brackets were bonded with XT primer and self-etching primer by means of XT adhesive. Upon curing, plasma arc light and visible light were used. After bonding, the shear bond strength was tested by Instron universal testing machine, and the amount of residual adhesive that remained on the tooth after debonding was measured by stereoscope and assessed with an adhesive remnant index. The results were as fellows: 1. When brackets were bonded, if other conditions remained the same, there was no significant difference in shear bond strength due to the type of primer - either self-etching primer or XT primer. 2. When metal brackets were bonded, there was no significant difference in shear bond strength according to the source of light - plasma arc light or visible light - and type of primer. 3. There was a very significant difference in shear bond strength according to the type of brackets - metal or ceramic brackets. The shear bond strength of ceramic brackets was stronger than metal brackets. 4. When the adhesive failure patterns of metal brackets bonded with self-etching primer were observed by using the adhesive remnant index, the bond failure of the metal bracket occurred more frequently at the bracket-adhesive. The failure of the ceramic bracket, however, occurred more frequently at the enamel-adhesive interface. The adhesive failure patterns of metal brackets bonded with XT primer observed the same patterns. The above results suggest that self-etching primer can be clinically useful for bonding the brackets without fear of a decrease in shear bond strength.

• Korean Journal of Medicinal Crop Science
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• v.11 no.3
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• pp.246-251
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• 2003

Angiotensin converting enzyme(ACE) belongs to the class of zinc protease and plays an important role in the regulation of blood pressure. In this experiment, we investigated the inhibitory activities of ninety four plant extracts on ACE. The extracts were prepared by water and refluxing with 70% and 100% methanol. Among the extracts, two plant extracts such as Cassia tora, Persicaria cochinchinensis Kitagawa showed more than 60% inhibitory activities, and Foeniculum vulgare Gaertner, Scutellaria baicalensis Georgl, Caragana sinica (Buchoz) Rehder, Inula britannica var. chinensis showed $45.2{\sim}49.7%$ inhibitory activities. Twenty eight plant extracts such as Hemerocallis fulva L, Camptotheca acuminata Decne, Inula britannica var. chinensis, Xanthium strumarium, Polygonatum odoratum, Phellodendron amurense Rupr, Coix lachryma-jobi var. mayuen, Prunus ansu, Hibiscus mutabilis L, Thchosanthes kirilowii, Helianthus annuus, Juglans sinensis showed $30.3{\sim}39.7%$ Inhibitory activities. These results suggest that plant extracts which contain high ACE inhibitory activities may be useful as anti-hypertension agents and to the treatment of hypertension.