• Clinical and Experimental Reproductive Medicine
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• v.36 no.3
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• pp.187-197
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• 2009

Objective: Phosphorylation and dephosphorylation of proteins are important in regulating cellular signaling pathways. Bead-based multiplex phosphorylation assay was conducted to detect the phosphorylation of seven proteins to maximize the information obtained from a single lysate of stage-specific mouse oocytes at a time. Methods: Cumulus-oocyte complexes (COCs) were cultured for 2 h, 8 h, and 16 h, respectively to address phosphorylation status of seven target proteins during oocyte maturation process. We analyzed the changes in phosphorylation at germinal vesicle (GV, 0 h), germinal vesicle breakdown (GVBD, 2 h), metaphase I (MI, 8 h), and metaphase II (MII, 16 h in vitro or in vivo) mouse oocytes by using Bio-Plex phosphoprotein assay system. We chose seven target proteins, namely, three mitogen-activated protein kinases (MAPKs), ERK1/2, JNK, and p38 MAPK, and other 4 well known signaling molecules, Akt, GSK-$3{\alpha}/{\beta}$, $I{\kappa}B{\alpha}$, and STAT3 to measure their phosphorylation status. Western blot analysis and kinase inhibitor treatment for ERK1/2, JNK, and Akt during in vitro maturation of oocytes were conducted for the confirmation. Results: Phosphorylation of ERK1/2, JNK, p38 MAPK and STAT3 was increased over 3 folds up to 20 folds, while phosphorylation of the other three signal molecules, Akt, GSK-$3{\alpha}/{\beta}$, and $I{\kapa}B{\alpha}$ was less than 3 folds. All of these results except for Akt were statistically significant (p<0.05). Conclusion: This is the first report on the new and valuable method measuring many phosphoproteins simultaneously in one minute sample such as oocyte lysates. All of the three MAPKs, ERK1/2, JNK, and p38 MAPK are involved in the process of mouse oocyte maturation. In addition, STAT3 might be important regulator of oocyte maturation, while Akt phosphorylation at Serine 473 may not be involved in the regulation of oocyte maturation.

• Journal of Soil and Groundwater Environment
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• v.14 no.3
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• pp.1-13
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• 2009

Alkalinity and total carbon contents were measured by acid neutralizing titration (ANT), back titration (BT), gravitational weighing (GW), non-dispersive infrared-total carbon (NDIR-TC) methods for assessing precision and accuracy of alkalinity and total carbon concentration in $CO_2$-rich water. Artificial $CO_2$-rich water(ACW: pH 6.3, alkalinity 68.8 meq/L, $HCO_3^-$ 2,235 mg/L) was used for comparing the measurements. When alkalinity measured in 0 hr, percent errors of all measurement were 0~12% and coefficient of variation were less than 4%. As the result of post-hoc analysis after repeated measure analysis of variance (RM-AMOVA), the differences between the pair of methods were not significant (within confidence level of 95%), which indicates that the alkalinity measured by any method could be accurate and precise when it measured just in time of sampling. In addition, alkalinity measured by ANT and NDIR-TC were not change after 24 and 48 hours open to atmosphere, which can be explained by conservative nature of alkalinity although $CO_2$ degas from ACW. On the other hand, alkalinity measured by BT and GW increased after 24 and 48 hours open to atmosphere, which was caused by relatively high concentration of measured total carbon and increasing pH. The comparison between geochemical modeling of $CO_2$ degassing and observed data showed that pH of observed ACW was higher than calculated pH. This can be happen when degassed $CO_2$ does not come out from the solution and/or exist in solution as $CO_{2(g)}$ bubble. In that case, $CO_{2(g)}$ bubble doesn't affect the pH and alkalinity. Thus alkalinity measured by ANT and NDIR-TC could not detect the $CO_2$ bubble although measured alkalinity was similar to the calculated alkalinity. Moreover, total carbon measured by ANT and NDIR-TC could be underestimated. Consequently, it is necessary to compare the alkalinity and total carbon data from various kind of methods and interpret very carefully. This study provide technical information of measurement of dissolve $CO_2$ from $CO_2$-rich water which could be natural analogue of geologic sequestration of $CO_2$.

• Korean Journal of Food Science and Technology
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• v.53 no.6
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• pp.799-808
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• 2021

This study was performed to investigate the extent of microbial contamination, the presence of enterotoxin genes, and the antibiotic susceptibility of Bacillus cereus in 58 red pepper plants and 43 environmental samples (soil, irrigation water, and gloves) associated with the plant cultivation. The detected counts of total aerobic bacteria, coliform bacteria, Escherichia coli, Bacillus cereus, and Staphylococcus aureus were lower in these samples, as compared to the regulations of standards for foods; moreover, pathogens, such as E. coli, E. coli O157:H7, Listeria monocytogenes, and Salmonella spp., were not detected. Genes encoding hemolysin BL enterotoxins (hblA, hblC, and hblD) as well as non-hemolytic enterotoxins (nheA, nheB, and nheC) were detected in 23 B. cereus specimens that were isolated from the test samples and had β-hemolytic activity. Interestingly, B. cereus is resistant to β-lactam and susceptible to non-β-lactam antibiotics. However, in this case, the isolated B. cereus specimens exhibited a shift from resistant to intermediate in response to cefotaxime and from susceptible to intermediate in case of rifampin, trimethoprim-sulfamethoxazole, vancomycin, clindamycin, and erythromycin. Therefore, the levels of B. cereus should be monitored to detect changes in antibiotic susceptibility and guarantee their safety.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1329-1340
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• 2021

The intertidal zone, which is a transitional zone between the ocean and the land, requires continuous monitoring as various changes occur rapidly due to artificial activity and natural disturbance. Monitoring of coastal topography changes using remote sensing method is evaluated to be effective in overcoming the limitations of intertidal zone accessibility and observing long-term topographic changes in intertidal zone. Most of the existing coastal topographic monitoring studies using remote sensing were conducted through high spatial resolution images such as Landsat and Sentinel. This study extracted the waterline using the NDWI from the GOCI-II (Geostationary Ocean Color Satellite-II) data, identified the changes in the intertidal area in Gyeonggi Bay according to various tidal heights, and examined the utility of DEM generation and topography altitude change observation over a short period of time. GOCI-II (249 scenes), Sentinel-2A/B (39 scenes), Landsat 8 OLI (7 scenes) images were obtained around Gyeonggi Bay from October 8, 2020 to August 16, 2021. If generating intertidal area DEM, Sentinel and Landsat images required at least 3 months to 1 year of data collection, but the GOCI-II satellite was able to generate intertidal area DEM in Gyeonggi Bay using only one day of data according to tidal heights, and the topography altitude was also observed through exposure frequency. When observing coastal topography changes using the GOCI-II satellite, it would be a good idea to detect topography changes early through a short cycle and to accurately interpolate and utilize insufficient spatial resolutions using multi-remote sensing data of high resolution. Based on the above results, it is expected that it will be possible to quickly provide information necessary for the latest topographic map and coastal management of the Korean Peninsula by expanding the research area and developing technologies that can be automatically analyzed and detected.

• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.265-271
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• 2021

The pattern of the tree's internal swelling depends on many causes. Since it is difficult to detect these various causes of swelling with a general method, if the state of swelling for a long time cannot be confirmed, serious damage to the trees may occur due to enlargement of the swelling area. In the method of acquiring a tree tomography image, an impulse passing through the tree is generated by tapping the sensor with a rubber mallet, and the moving speed is recorded. In this paper, to measure cracks, cavities, and swelling due to physical damage, we developed a 3D viewer that can know the internal state of a tree using a tree cross-section image acquired from Arbotom to determine the degree of swelling inside the tree. Based on this, we tried to present data that can be referred to when surgical operation of trees is required. In order to acquire a tomographic image of a tree, 6 sensors were attached to the three Yangpala and Maple trees, and a 1 m-long tree was measured using the Arbotom program, and a 3D image was implemented through the 3D Viewer created using MATLAB. In addition to simply acquiring images, the cross-sectional length and volume of the tree were measured. In the actually produced 3D Viewer, the length of the part where the swelling of the maple tree occurred was 33.12 cm, and the swelling of the yangpala tree was measured as 21.41 cm. The volume of the maple tree was measured to be 78.832 ㎤. As a result of comparing the cross-sectional image of the Arbotom and the 3D image, the same result as the real aspect of the tree was obtained, so it can be judged that the reliability of the manufactured software is also secured, and data to be applied to the surgical tree operation through the created Viewer is provided. It is believed that the damage will be minimized.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.648-657
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• 2021

This study was conducted to estimate the volume growth by forest type and major species using the national forest resource inventory and to predict the final age of maturity by deriving the mean annual increment (MAI) and the current annual increment (CAI). We estimated the volume growth using the Chapman-Richards model. In the volume estimation equations by forest type, coniferous forests exhibited the highest growth. According to the estimation formula for each major species, Larix kaempferi will grow the highest among coniferous tree species and Quercus mongolica among broad-leaved tree species. And these estimation formulas showed that the fitness index was generally low, such as 0.32 for L. kaempferi and 0.21 for Quercus variabilis. In the analysis of residual amount, which indicates the applicability of the volume estimation formula, the estimates of the estimation formula tended to be underestimated in about 30 years or more, but most of the residuals were evenly distributed around zero. Therefore, these estimation formulas have no difficulty estimating the volume of actual forest species in Korea. The maximum age attained by calculating MAI was 34 years for P. densiflora, 35 years for L. kaempferi, and 31 years for P. rigida among coniferous tree species. In broad-leaved tree species, we discovered that the maximum age was 32 years for Q. variabilis, 30 years for Q. acutissima, and 29 years for Q. mongolica. We calculated MAI and CAI to detect the point at which these two curves intersected. This point was defined by the maximum volume harvesting age. These results revealed no significant difference between the current standard cutting age in public and private forests recommended by the Korea Forest Service, supporting the reliability of forestry policy data.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1757-1766
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• 2021

The green coverage ratio is the ratio of the land area to green coverage area, and it is used as a practical urban greening index. The green coverage ratio is calculated based on the land cover map, but low spatial resolution and inconsistent production cycle of land cover map make it difficult to calculate the correct green coverage area and analyze the precise green coverage. Therefore, this study proposes a new method to calculate green coverage area using aerial images and deep neural networks. Green coverage ratio can be quickly calculated using manned aerial images acquired by local governments, but precise analysis is difficult because components of image such as acquisition date, resolution, and sensors cannot be selected and modified. This limitation can be supplemented by using an unmanned aerial vehicle that can mount various sensors and acquire high-resolution images due to low-altitude flight. In this study, we proposed a method to calculate green coverage ratio from manned or unmanned aerial images, and experimentally verified the proposed method. Aerial images enable precise analysis by high resolution and relatively constant cycles, and deep learning can automatically detect green coverage area in aerial images. Local governments acquire manned aerial images for various purposes every year and we can utilize them to calculate green coverage ratio quickly. However, acquired manned aerial images may be difficult to accurately analyze because details such as acquisition date, resolution, and sensors cannot be selected. These limitations can be supplemented by using unmanned aerial vehicles that can mount various sensors and acquire high-resolution images due to low-altitude flight. Accordingly, the green coverage ratio was calculated from the two aerial images, and as a result, it could be calculated with high accuracy from all green types. However, the green coverage ratio calculated from manned aerial images had limitations in complex environments. The unmanned aerial images used to compensate for this were able to calculate a high accuracy of green coverage ratio even in complex environments, and more precise green area detection was possible through additional band images. In the future, it is expected that the rust rate can be calculated effectively by using the newly acquired unmanned aerial imagery supplementary to the existing manned aerial imagery.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1773-1784
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• 2021

In order to minimize damage to oil spill accidents in the ocean, it is essential to collect a spilled area as soon as possible. Thus satellite-based remote sensing is a powerful source to detect oil spills in the ocean. With the recent rapid increase in the number of available satellites, it has become possible to generate a status report of marine oil spills soon after the accident. In this study, the oil spill area was calculated using various satellite images for the Symphony oil spill accident that occurred off the coast of Qingdao Port, China, on April 27, 2021. In particular, improving the accuracy of oil spill area determination was applied using high-resolution commercial satellite images with a spatial resolution of 2m. Sentinel-1, Sentinel-2, LANDSAT-8, GEO-KOMPSAT-2B (GOCI-II) and Skysat satellite images were collected from April 27 to May 13, but five images were available considering the weather conditions. The spilled oil had spread northeastward, bound for coastal region of China. This trend was confirmed in the Skysat image and also similar to the movement prediction of oil particles from the accident location. From this result, the look-alike patch observed in the north area from the Sentinel-1A (2021.05.01) image was discriminated as a false alarm. Through the survey period, the spilled oil area tends to increase linearly after the accident. This study showed that high-resolution optical satellites can be used to calculate more accurately the distribution area of spilled oil and contribute to establishing efficient response strategies for oil spill accidents.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.535-544
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• 2021

Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.