• Publications of The Korean Astronomical Society
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• v.36 no.3
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• pp.47-63
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• 2021

Variability is one of the major characteristics of Active Galactic Nuclei (AGN), and it is used for understanding the energy generation mechanism in the center of AGN and/or related physical phenomena. It it known that there exists a time lag between AGN light curves simultaneously observed at different wavelengths, which can be used as a tool to estimate the size of the area that produce the radiation. In this paper, We present long term near-infrared variability of optically bright type 1 AGN using the Wide-field Infrared Survey Explorer data. From the Milliquas catalogue v6.4, 73 type 1 QSOs/AGN and 140 quasar candidates are selected that are brighter than 18 mag in optical and located within 5 degree around the ecliptic poles. Light curves in the W1 band (3.4 ㎛) and W2 band (4.6 ㎛) during the period of 2010-2019 were constructed for these objects by extracting multi-epoch photometry data from WISE and NEOWISE all sky survey database. Variability was analyzed based on the excess variance and the probability P_var. Applying both criteria, the numbers of variable objects are 19 (i.e., 26%) for confirmed AGN and 12 (i.e., 9%) for AGN candidates. The characteristic time scale of the variability (τ) and the variability amplitude (σ) were derived by fitting the DRW model to W1 and W2 light curves. No significant correlation is found between the W1/W2 magnitude and the derived variability parameters. Based on the subsample that are identified in the X-ray source catalog, there exists little correlation between the X-ray luminosity and the variability parameters. We also found four AGN with changing W1-W2 color.

• 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.

• 한국노년학
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• v.28 no.4
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• pp.1279-1295
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• 2008

This study was done to find out the effects that group art therapy would have on low rank cognitive functions and the self-esteem of the elderly with dementia. The study subjects were four elderly females with light dementia symptoms who scored lower than 19 points on the MMSE-K(Mini Mental State Examination-Korea) test. They were chosen from the ${\bigcirc}{\bigcirc}$ Senior Welfare Service Center located in Seoul. A total of 15 sessions of a group art therapy were given once a week for 60 minutes from January 15th to April 30th of 2008, the research tools employed were the MMSE-K and the Rosenberg Self-Esteem Scale on which a pre-test and a post-test were given. The results obtained are as follows. First, it was shown that group art therapy is effective to improve the cognitive functions of the elderly with dementia. According to the pre-tests and post -tests based on MMSE-K, the average score improved from 16.75 to 19.75, using Wilcoxon non-parameter statistics, verification resultant p-value which significant difference exhibited as .046, from the pre-tests and post-test, the average score improved in the subordinate areas of Orientation, Registration, Attention and Calculation, language function, understanding and judgment but there was no significant difference, memory recollection improved by a score of 0.70 according to the pre-test and post-test. using Wilcoxon non-parameter statistics, the verification resultant p-value which significant difference exhibited as .043. Second, it appeared with the fact that group art therapy effects the Self-Esteem of the elderly with dementia. From the verifications of a pre-test and post-test on Self-Esteem, the average score improved from 20.75 to 24.25, the effectiveness of the program was given proven by statistically considering the statistical resultant p-value of .048.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.1
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• pp.54-63
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• 2019

As a part of the national marine ecosystem monitoring program, the temporal and spatial variation of sedimentary environment and pollution of organic matters and trace metals from four major tidal flats, i.e., Ganghwa Is., Garolim bay, Jeung Is., Suncheon bay, was investigated for 3 yerars from 2015 to 2017. The mean grain size of the sediment was $5.0-5.3{\varnothing}$ at Ganghwa Is, $4.5-4.8{\varnothing}$ at Garolim bay, $6.1-6.5{\varnothing}$ at Jeung Is, and $8.6-8.7{\varnothing}$ at Suncheon bay. The mean grain size (Mz) tended to decrease from the north (Ganghwa Is.) to the south (Suncheon bay). The ignition loss (IL) was 15.5% in Suncheon bay in 2015, which was relatively high compared to other sites, but gradually decreased over time from 8.3% in 2016 to 7.0% in 2017. In Jeung Is. and Suncheon bay, the concentration of Zn and As exceeded the threshold effect level (TEL) at some stations, but the range of trace metals in the other sites was below the level. In Jeung Is., the Mz and concentration of trace metals except Hg was positively correlated (r= 0.40-0.88, P<0.05). On the other hand, Mz was negatively correlated with trace metals (P<0.05) in Suncheon bay. The geoaccumulation index ($I_{geo}$) to evaluate contamination status of sediments for trace metal was less than 1(not contaminated) for Cu, Zn, Pb, Cd and Hg, and 2-3 (moderately to strongly polluted) for As at several stations in Suncheon bay and Jeung Is.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.39 no.3
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• pp.33-41
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• 2021

This study identified the scale that traditional landscape design has taken up by analyzing a total of 1037 services for design of cultural heritage that had been ordered by the government agencies from 2018 to 2020, and has drawn characteristics of traditional landscape design focusing on major cases. The results are as follows. First, the number of order cases for traditional landscape design has shown differences annually in the services of design of cultural heritage, but the design amount has been found to have the similar average annually, which confirmed that the same level has been maintained each year. It was found that the number of cases of traditional landscape design requiring responsibilities or participations of landscape engineers for 3 years in the entire design had a high proportion of approximately 26%. Second, the traditional landscape design has required professional knowledge and experiences of landscape engineers that could not be replaced by the business operator for design of cultural heritage consisting of architects. The expertise has been shown differently depending on types of construction. First, the topographical design for the work to build a foundation has required understanding of ground shapes and its elevations and professional knowledge on calculation of the amount of the earth work and the remains maintenance technique etc. The plantation design has required basic knowledge on growth characteristics of trees and the environment for growth and understanding of the vegetation landscape of the past. Meanwhile, the design for traditional pavement and traditional landscape structures and facilities has required the expertise on traditional materials that are different from the modern ones and their processing and construction methods. The understanding of changes to water paths and ecosystem, the principles of fluids, and characteristics of each type of fluid was essential for the design for the ecological landscape work including the maintenance of a water system such as rivers etc. As such, the traditional landscape design has a scale accounting for approximately one fourth of the entire cultural heritage design and requires the expertise differentiated from other fields. This improves the provisions of the current law on limiting the actual design, suggesting the need for the establishment of a traditional landscape design company so that all traditional landscape designs can be carried out by landscape engineers.

• Journal of Nutrition and Health
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• v.54 no.2
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• pp.165-178
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• 2021

Purpose: This study examined the eating-out patterns of Korean infants and school-aged children and compared diet quality. Methods: Data were obtained from the 2016-2018 Korea National Health and Nutrition Examination Survey. The subjects were 306 children aged 3 to 11 years old that ate dinner at restaurants. Percentage energy intakes of 24 food groups were calculated, and cluster analysis was used to identify eating-out patterns. Diet quality was assessed by calculating percentage energy and nutrient intakes using one-third of the 2015 Dietary Reference Intakes for Korean (KDRIs), nutrient adequacy ratio (NAR), mean adequacy ratio (MAR), and index of nutritional quality (INQ). Results: Cluster analysis identified 2 eating-out patterns, that is, a 'rice-centered' (53%) and a 'mixed diet' (47%) pattern. For those with the mixed diet pattern, ratios of carbohydrates, protein, and fat to total calories were 48:20:31, whereas for the rice-centered pattern, ratios were 62:15:21 (p < 0.001). Intakes of energy and most nutrients in the mixed diet pattern were excessive, but the intakes of the most nutrients in the rice-centered pattern were much lower than their KDRIs. MARs were higher for the mixed diet pattern than the rice-centered pattern (0.74 vs. 0.66) (p < 0.001), and INQs for vitamin C (p = 0.007) and calcium (p = 0.018) were lower for the rice-centered pattern, whereas INQ for iron (p = 0.003) was lower for the mixed diet pattern. Conclusion: The quality of meals for infants and school-aged children depended on eating-out patterns, but the rice-centered and mixed diet patterns both failed to provide an appropriately balanced meal pattern. The results of this study suggest that healthy menus need to be developed for children in restaurants.

• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.4
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• pp.5-13
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• 2022

The current environmental problem is that environmental pollution is accelerating due to the generation of large amounts of waste and indiscriminate consumption of energy. Fossil fuels, a representative energy production fuel, are burned in the process of producing energy, generating a large amount of greenhouse gases and eventually causing climate change. In addition, the amount of waste generated worldwide is continuously increasing, and environmental pollution is occurring in the process of waste treatment. One of the methods for simultaneously solving these problems is the energy recovery from and reduction of organic wastes. Sewage sludge generated in sewage treatment plants has been treated in various ways since ocean disposal was completely prohibited, but the amount generated has been continuously increasing. Since the sewage sludge contains a large amount of organic materials, it is desirable to recover energy from the sewage sludge and reduce the final discharged waste through anaerobic digestion. However, most of the excess sludge is a mass of microorganisms used in sewage treatment, and in order for the excess sludge to be anaerobically digested, the cell walls of the microorganisms must be destroyed first, but it takes a lot of time to destroy the cell walls, so high rates of biogas production and waste reduction cannot be achieved only by anaerobic digestion. Therefore, the pre-treatment process of solubilizing excess sludge is required, and the thermal solubilization process is verified to be the most efficient among various solubilization methods, and high rates of biogas production and waste reduction can be achieved by anaerobic digestion after destroying cell walls the thermal solubilization process. In this study, when pretreating TS 10% thickened excess sludge through a thermal solubilization system, a study was conducted on solubilization characteristics according to retention time and operating temperature variables. The experimental variables for the retention time of the thermal solubilization system were 30 minutes, 60 minutes, 90 minutes, and 120 minutes, respectively, while the operating temperature was fixed at 160℃. The soulbilization rates calculated through TCOD and SCOD derived from the experimental results increased in the order of 12.11%, 20.52%, 28.62%, and 31.40%, respectively. And the variables according to operating temperature were 120℃, 140℃, 160℃, 180℃, and 200℃, respectively, while the operating retention time was fixed at 60 minutes. And the solubilization rates increased in the order of 7.14%, 14.52%, 20.52%, 40.72%, and 57.85%, respectively. In addition, TS, VS, T-N, T-P, NH₄⁺-N, and VFAs were analyzed to evaluate thermal solubilization characteristics of thickened excess sludge. As a result, in order to obtain 30% or more solubilization rate through thermal solubilization of TS 10% thickened excess sludge, 120 minutes of retention time is required when the operating temperature is fixed to 160℃, and 170℃ or more of operating temperature is needed when the operating time is fixed to 60 minutes.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.589-600
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• 2020

Effective conservation and management of protected areas require monitoring the settlement of invasive alien species and reducing their dispersion capacity. We simulated the potential distribution of invasive alien plant species (IAPS) using three representative species distribution models (Bioclim, GLM, and MaxEnt) based on the IAPS distribution in the forest genetic resource reserve (2,274ha) in Uljin-gun, Korea. We then selected the realistic and suitable species distribution model that reflects the local region and ecological management characteristics based on the simulation results. The simulation predicted the tendency of the IAPS distributed along the linear landscape elements, such as roads, and including some forest harvested area. The statistical comparison of the prediction and accuracy of each model tested in this study showed that the GLM and MaxEnt models generally had high performance and accuracy compared to the Bioclim model. The Bioclim model calculated the largest potential distribution area, followed by GLM and MaxEnt in that order. The Phenomenological review of the simulation results showed that the sample size more significantly affected the GLM and Bioclim models, while the MaxEnt model was the most consistent regardless of the sample size. The optimal model overall for predicting the distribution of IAPS among the three models was the MaxEnt model. The model selection approach based on detailed flora distribution data presented in this study is expected to be useful for efficiently managing the conservation areas and identifying the realistic and precise species distribution model reflecting local characteristics.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1465-1483
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• 2020

Evapotranspiration is a concept that includes the evaporation from soil and the transpiration from the plant leaf. It is an essential factor for monitoring water balance, drought, crop growth, and climate change. Actual evapotranspiration (AET) corresponds to the consumption of water from the land surface and the necessary amount of water for the land surface. Because the AET is derived from multiplying the crop coefficient by the reference evapotranspiration (ET0), an accurate calculation of the ET0 is required for the AET. To date, many efforts have been made for gridded ET0 to provide multiple products now. This study presents a comparison between the ET0 products such as FAO56-PM, LDAPS, PKNU-NMSC, and MODIS to find out which one is more suitable for the local-scale hydrological and agricultural applications in Korea, where the heterogeneity of the land surface is critical. In the experiment for the period between 2016 and 2019, the daily and 8-day products were compared with the in-situ observations by KMA. The analyses according to the station, year, month, and time-series showed that the PKNU-NMSC product with a successful optimization for Korea was superior to the others, yielding stable accuracy irrespective of space and time. Also, this paper showed the intrinsic characteristics of the FAO56-PM, LDAPS, and MODIS ET0 products that could be informative for other researchers.