• Korean Journal of Veterinary Service
• /
• v.34 no.2
• /
• pp.159-166
• /
• 2011

This study was carried out to develope enzyme-linked immunosorbent assay (ELISA) for detection of canine brucellosis in dogs experimentally inoculated with Brucella abortus 1119-3 and B. canis RM666. Groups A, B and C of dogs (each group consisting of three dogs) were orally inoculated with approximately $5{\times}10^9$ colony-forming units of B. abortus and B. canis, and with sterile pyrogen-free PBS, respectively. The animals were monitored at regular intervals upto the 12th week post inoculation (PI) by standard tube agglutination test (STAT), plate agglutination test (PAT), Rose Bengal test (RBT), 2-mercaptoethanol rapid slide agglutination test (2ME-RSAT) and ELISA. The induced antibody titers in group A dogs were detected from the first week PI to the eighth week PI in STAT, PAT and RBT using the inactivated whole cells of B. abortus 1119-3 as antigens, while no sera in groups B and C dogs reacted with the antigens. In 2ME-RSAT using whole cells of B. canis M-strain as antigens, the induced antibody titers in group B dogs were observed at the second week PI and persisted for the 12th week PI, while sera of groups A and C dogs did not react with the whole cells. In ELISA using cytoplasmic fractions antigen of B. abortus 1119-3, the mean optical density of antibodies in groups A and B was detected from the first and second weeks PI, respectively, and persisted for 12th week PI, while sera of group C did not cross-react with the fractions antigen. However, in ELISA using the hot saline extracts of B. canis M- as an antigen, the induced antibody titers in only group B dogs were detected from second week PI and persisted for until the end of this study. These results indicate that the ELISA using B. abortus 1119-3 cytoplasmic fractions as antigens can be a good candidate for detection of brucellosis by B. abortus as well as B. canis in dogs.

• Journal of Gastric Cancer
• /
• v.3 no.2
• /
• pp.97-103
• /
• 2003

Purpose: This study aims to determine the infection rate of Helicobacter pylori (H. pylori) in gastric cancer patients who received gastrectomies, and to compare the rates of H.pylori infection detected by serological test and that of histopathological test, and to evaluate its clinical meaning. Materials and Methods: Fifty two patients were selected from those who underwent gastrectomies at the Department of Surgery, Samsung Medical Center, from March 1997 to May 1997. The control group consisted of healthy 103 persons visited the center for health promotion in Samsung Medical Center. In both groups, we quantitatively checked serum level of IgG anti H. pylori antibody titer by ELISA using GAP IgG test kit (BioRad, USA) for the serological test, and we microscopically examined the surgical specimen stained by Warthin-Starry silver staining method for the histopathological test. Results: The seropositive rate of H. pylori in the patients' group was $71.2\%$ (37/52), and the control group was $65.0\%$ (67/103). The difference between two groups was statistically significant. However the histopathological study showed that the overall detection rate of H. pylori was $61.5\%$ (32/52) in the patients' group and $61.2\%$ (63/103) in the control group; nd this difference was not statistically significant Conclusion: We could confirm that H.pylori infection rate in the gastric cancer resected patients was statistically higher than in the normal healthy persons even in small population. And the detection method for the H. pylori infection by serological test was presumed to be better than that of histopathological test using surgical specimen. Further study for the larger population by well-organized multicenters will be needed.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1235-1243
• /
• 2023

This study proposes the detection algorithm for the cold water mass (CWM) along the eastern coast of the Korean Peninsula using sea surface temperature (SST) data provided by the Korea Institute of Ocean Science and Technology (KIOST). Considering the occurrence and distribution of the CWM, the eastern coast of the Korean Peninsula is classified into 3 regions("Goseong-Uljin", "Samcheok-Guryongpo", "Pohang-Gijang"), and the K-means clustering is first applied to SST field of each region. Three groups, K-means clusters are used to determine CWM through applying a double threshold filter predetermined using the standard deviation and the difference of average SST for the 3 groups. The estimated sea area is judged by the CWM if the standard deviation in the sea area is 0.6℃ or higher and the average water temperature difference is 2℃ or higher. As a result of the CWM detection in 2022, the number of CWM occurrences in "Pohang-Gijang" was the most frequent on 77 days and performance indicators of the confusion matrix were calculated for quantitative evaluation. The accuracy of the three regions was 0.83 or higher, and the F1 score recorded a maximum of 0.95 in "Pohang-Gijang". The detection algorithm proposed in this study has been applied to the KIOST SST system providing a CWM map by email.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.27 no.4
• /
• pp.299-304
• /
• 2007

There are to be some cracks on the material degradation part or the stress concentration parts of the main members, which carry on over-loads, of structures. Because these cracks can be used to evaluate the structural health status, it is important to monitor the crack growth for maintaining the structural safety. In this study, the fiber Bragg grating sensor with a drop ball was developed as a sensor for crack growth detection of an existing crack. The crack growth detection sensor was constructed with three parts: a probe part, a wavelength controling light source and receiver part, and an impact part. The probe part was just formed with a fiber Bragg grating optical fiber The wavelength controling light source part was composed of a current supplying circuit, a DFB laser diode, and a TEC controling circuit for wavelength control. Also, the impact part was just implemented by dropping a steel ball. The performance of this sensor was confirmed by the experiments of the crack detection with an aluminum plate having one existing crack. According to these experiments, the difference of the sensor signal outputs was correlated with the crack length. So, it was confirmed that this sensor could be applied to monitor the crack growth.

• Restorative Dentistry and Endodontics
• /
• v.48 no.1
• /
• pp.9.1-9.11
• /
• 2023

Objectives: This study evaluated the effect of adjacent gingival blood flow on detection of pulpal blood flow (PBF) using ultrasound Doppler flowmetry (UDF) through animal study. Materials and Methods: The study included 36 right and left maxillary the third incisors and canines in 9 experimental dogs. The study included 2 main steps: In the first step, the pulse sound level (PSL) was recorded on the cervical part of each tooth without flap elevation (Group 1), with flap elevation (Group 2), and after it was repositioned in place (Group 3). In the second step, the PSL was recorded on the cervical part of each tooth (Group 4), after pulpotomy (Group 5), after partial pulp extirpation (Group 6), after complete extirpation (Group 7), and after canal filling (Group 8). In Groups 5-8, the study was performed with and without flap elevation in the left and right teeth, respectively. The PSL was graded as follows: 0, inaudible; 1, heard faintly; and 2, heard well. The difference between each group was analyzed using Friedman's test with Wilcoxon signed-rank tests (α = 0.05). Results: In step 1, the PSL results were Group 1 > 2 and 3. In step 2, there was no significant difference between the groups when the flap was not elevated, while PSL results were Group 4 > 5 ≥ 6 and 7 ≥ 8 when the flap was elevated. Conclusions: PBF is affected by gingival blood flow when measured with UDF. UDF measurements require isolation of gingiva from the tooth.

• Journal of Convergence for Information Technology
• /
• v.10 no.8
• /
• pp.40-46
• /
• 2020

As interest in traffic safety increases, research on autonomous driving, which reduces the incidence of traffic accidents, is increased. Object recognition and detection are essential for autonomous driving. Therefore, research on object recognition and detection through traffic image big data is being actively conducted to determine the road conditions. However, because most existing studies use only daytime data, it is difficult to recognize objects on night roads. Particularly, in the case of a light source object, it is difficult to use the features of the daytime as it is due to light smudging and whitening. Therefore, this study proposes Yolo based light source object detection for traffic image big data processing. The proposed method performs image processing by applying color model transitions to night traffic image. The object group is determined by extracting the characteristics of the object through image processing. It is possible to increase the recognition rate of light source object detection on a night road through a deep learning model using candidate group data.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.10 no.4
• /
• pp.59-71
• /
• 2000

Due to the advance of computer and communication technology, intrusions or crimes using a computer have been increased rapidly while various information has been provided to users conveniently. As a results, many studies are necessary to detect the activities of intruders effectively. In this paper, a new association algorithm for the anomaly detection model is proposed in the process of generating user\`s normal patterns. It is that more recently observed behavior get more affection on the process of data mining. In addition, by clustering generated normal patterns for each use or a group of similar users, it is possible to identify the usual frequency of programs or command usage for each user or a group of uses. The performance of the proposed anomaly detection system has been tested on various system Parameters in order to identify their practical ranges for maximizing its detection rate.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.85-88
• /
• 2009

In this paper, we propose a DRF-based object detection method using the object adaptive patch in the satellite imagery. It is a Discriminative Random Fields (DRF) based work, so the detection is done by labeling to the possible patches in the image. For the feature information of each patch, we use the multi-scale and object adaptive patch and its texton histogram, instead of using the single scale and fixed grid patch. So, we can include contextual layout of texture information around the object. To make object adaptive patch, we use "superpixel lattice" scheme. As a result, each group of labeled patches represents the object or object's presence region. In the experiment, we compare the detection result with a fixed grid scheme and shows our result is more close to the object shape.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.262-265
• /
• 2007

Preliminary results are reported on ship detection using coherence images computed from cross-correlating images of multi-look-processed dual-polarization data (HH and HV) of ENVISAT ASAR. The traditional techniques of ship detection by radars such as CFAR (Constant False Alarm Rate) rely on the amplitude data, and therefore the detection tends to become difficult when the amplitudes of ships images are at similar level as the mean amplitude of surrounding sea clutter. The proposed method utilizes the property that the multi-look images of ships are correlated with each other. Because the inter-look images of sea surface are covered by uncorrelated speckle, cross-correlation of multi-look images yields the different degrees of coherence between the images and water. The polarimetric information of ships, land and intertidal zone are first compared based on the cross-correlation between HH and HV. In the next step, we examine the technique when the dual-polarization data are split into two multi-look Images.

• Proceedings of the KSRS Conference
• /
• 2008.03a
• /
• pp.180-184
• /
• 2008

Preliminary results are reported on ship detection using coherence images computed from crosscorrelating images of multi-look-processed dual-polarization data (HH and HV) of ENVISAT ASAR. The traditional techniques of ship detection by radars such as CFAR (Constant False Alarm Rate) rely on the amplitude data, and therefore the detection tends to become difficult when the amplitudes of ships images are at similar level as the mean amplitude of surrounding sea clutter. The proposed method utilizes the property that the multi-look images of ships are correlated with each other. Because the inter-look images of sea surface are covered by uncorrelated speckle, crosscorrelation of multi-look images yields the different degrees of coherence between the images and water. The polarimetric information of ships, land and intertidal zone are first compared based on the cross-correlation between HH and HV. In the next step, we examine the technique when the dual-polarization data are split into two multi-look images.