• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.237-246
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• 2020

Recently, as high resolution satellites data have been serviced, frequent DSM (Digital Surface Model) generation over urban areas has been possible. In addition, it is possible to detect changes using a high-resolution DSM at building level such that various methods of building change detection using DSM have been studied. In order to detect building changes using DSM, we need to generate a DSM using a stereo satellite image. The change detection method using D-DSM (Differential DSM) uses the elevation difference between two DSMs of different dates. The D-DSM method has difficulty in applying a precise vertical threshold, because between the two DSMs may have elevation errors. In this study, we focus on the urban structure change detection using D-nDSM (Differential nDSM) based on nDSM (Normalized DSM) that expresses only the height of the structures or buildings without terrain elevation. In addition, we attempted to reduce noise using a morphological filtering. Also, in order to improve the roadside buildings extraction precision, we exploited the urban road network extraction from nDSM. Experiments were conducted for high-resolution stereo satellite images of two periods. The experimental results were compared for D-DSM, D-nDSM, and D-nDSM with road extraction methods. The D-DSM method showed the accuracy of about 30% to 55% depending on the vertical threshold and the D-nDSM approaches achieved 59% and 77.9% without and with the morphological filtering, respectively. Finally, the D-nDSM with the road extraction method showed 87.2% of change detection accuracy.

• Ultrasonography
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• v.32 no.2
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• pp.132-142
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• 2013

Purpose: The purpose of this study is to investigate the correlations of various kinetic parameters derived from the time intensity curve in a xenograft mouse model injected with a prostate cancer model (PC-3 and LNCaP) using an ultrasound contrast agent with histopathologic parameters. Materials and Methods: Twenty nude mice were injected with human prostate cancer cells (15 PC-3 and five LNCaP) on their hind limbs. A bolus of $500{\mu}L$ ($1{\times}10^8$ microbubbles) of second-generation US contrast agent (SonoVue) was injected into the retroorbital vein. The region of interest was drawn over the entire tumor. The time intensity curve was acquired and then fitted to a gamma variate function. The maximal intensity (A), time to peak (Tp), maximal wash-in rate (washin), washout rate (washout), area under the curve up to 50 sec ($AUC_{50}$), area under the ascending slope ($AUC_{in}$), and area under the descending slope ($AUC_{out}$) were derived from the parameters of the gamma variate fit. Immunohistochemical staining for VEGF and CD31 was performed. Tumor volume, the area percentage of VEGF stained in a field, and the count of CD31 (microvessel density, MVD) positive vessels showed correlation with the parameters from the time intensity curve. Results: No significant differences were observed between the kinetic and histopathological parameters from each group. MVD showed positive correlation with A (r=0.625, p=0.003), washin (r=0.462, p=0.040), $AUC_{50}$ (r=0.604, p=0.005), and $AUC_{out}$ (r=0.587, p=0.007). Positive correlations were also observed between tumor volume and $AUC_{50}$ (r=0.481, p=0.032), washin (r=0.662, p=0.001), and $AUC_{out}$ (r=0.547, p=0.012). Washout showed negative correlations with MVD (r=-0.454, p=0.044) and tumor volume (r=-0.464, p=0.039). The area percentage of VEGF did not show any correlation with calculated data from the curve. Conclusion: MVD showed correlations with several of the kinetic parameters. CEUS has the potential for prediction of tumor vascularity in a prostate cancer animal model.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.5
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• pp.605-611
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• 2015

A synthetic strain of ducks (Anas platyrhynchos) was developed by introducing genes for long duration of fertility to be used as mother of mule ducklings and a seven-generation selection experiment was conducted to increase the number of fertile eggs after a single artificial insemination (AI) with pooled Muscovy semen. Reciprocal crossbreeding between Brown Tsaiya LRI-2 (with long duration of fertility) and Pekin L-201 (with white plumage mule ducklings) ducks produced the G0. Then G1 were intercrossed to produce G2 and so on for the following generations. Each female duck was inseminated 3 times, at 26, 29, and 32 weeks of age. The eggs were collected for 14 days from day 2 after AI. Individual data regarding the number of incubated eggs (Ie), the number of fertile eggs at candling at day 7 of incubation (F), the total number of dead embryos (M), the maximum duration of fertility (Dm) and the number of hatched mule ducklings (H) with plumage colour were recorded. The selection criterion was the breeding values of the best linear unbiased prediction animal model for F. The results show high percentage of exhibited heterosis in G2 for traits to improve (19.1% for F and 12.9% for H); F with a value of 5.92 (vs 3.74 in the Pekin L-201) was improved in the G2. Heritabilities were found to be low for Ie ($h^2=0.07{\pm}0.03$) and M ($h^2=0.07{\pm}0.01$), moderately low for Dm ($h^2=0.13{\pm}0.02$), of medium values for H ($h^2=0.20{\pm}0.03$) and F ($h^2=0.23{\pm}0.03$). High and favourable genetic correlations existed between F and Dm ($r_g=0.93$), between F and H ($r_g=0.97$) and between Dm and H ($r_g=0.90$). The selection experiment showed a positive trend for phenotypic values of F (6.38 fertile eggs in G10 of synthetic strain vs 5.59 eggs in G4, and 3.74 eggs in Pekin L-201), with correlated response for increasing H (5.73 ducklings in G10 vs 4.86 in G4, and 3.09 ducklings in Pekin L-201) and maximum duration of the fertile period without increasing the embryo mortality rate. The average predicted genetic response for F was 40% of genetic standard deviation per generation of selection. The mule ducklings' feather colour also was improved. It was concluded that this study provided results for a better understanding of the genetics of the duration of fertility traits in the common female duck bred for mule and that the selection of a synthetic strain was effective method of improvement.

• Journal of Distribution Science
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• v.9 no.2
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• pp.131-140
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• 2011

On 1 July 2000, as the over-65 year-old population numbered 3,371,000 and accounted for over 7.1% of Korea's total population, an aging society was revealed. The over-65 percentage climbed to 11.0% by late 2010. A truly aged society is expected soon, by 2019. This aging society requires marketing research concerning the consumer behaviour and well-being of the elderly, because the 'silver generation' is emerging as a large part of the consumer market. The purpose of this study is to empirically analyse one effect among several satisfaction factors in the consuming cycle of various health functional products on consumer's well-being and the effect of product knowledge on the relationship between product satisfaction and well-being. To achieve this purpose, we established a research model after reviewing previous studies on product satisfaction, product knowledge, and consumer's well-being. The following hypotheses were developed from the research model. Hypothesis 1: When elderly consumers' satisfaction with health functional products increases, their well-being will increase. Hypothesis 2: The effect of their satisfaction with health functional products on their well-being will be strengthened according to the level of their knowledge of the products. Those hypotheses were tested by multiple and moderated regressions to the empirical data through a questionnaire survey. As a result, Hypothesis 1 was totally adopted, and Hypothesis 2 was only partially adopted. The study has many practical implications for well-being marketing. First, in order to heighten the elderly consumer's well-being, the level of his or her satisfaction with the health functional products has to be raised in every stage: during the acquisition, preparation, use, maintenance, and disposition of the consumption cycle. Moreover, promoting positive emotional experiences while diminishing negative ones requires effort because a consumer's well-being is made up of various needs. Second, the marketing of health functional products should be invigorated in order to raise the level of elderly consumers' knowledge of them. In other words, it is important to give them an expertise in the health functional products through different channels. A statistical analysis showed, however, that their knowledge has a decisive effect on only two satisfaction stages, preparation and maintenance. Nevertheless, this merely confirmed the intuitive assumption that the knowledge of health functional products is most relevant to their preparation and maintenance. In conclusion, this study is timely because few empirical studies exist on the relationships between silver consumer behaviour and well-being marketing. It contributes to our understanding of this subject by revealing the causality between the silver consumer's satisfaction and his or her well-being in the consumption cycle and by discovering the moderating influence of knowledge in that process.

• Journal of Korean Society of Forest Science
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• v.89 no.5
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• pp.655-665
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• 2000

Taking account of the structural variation on species composition by topography, the successional trends were comparatively analyzed for the three topographic positions (valley, mid-slope, and ridge) in the natural deciduous forest of Mt. Chumbong area. The analysis was based upon the subsequent process of generation replacement by understory saplings and seedlings over the overstory trees which will be eventually fallen down. This study adopted the plot sampling method, establishing twenty $20m{\times}20m$ quadrats and collecting vegetation and site data on each different topographic position. The transition matrix model, which was modified from the mathematical theory of Markov chain, was employed to analyze the successional trends and thereafter to predict the overstory species composition in the future for each different topographic position. In valley, the simulation indicated the remarkable decrease in the proportion of species composition of present dominants Quercus mongolica and Fraxinus mandshurica from current 23% and 21% to around 4% of each at the steady state, which is predicted to take less than 200 years. On the other hand, the proportion of such species as Abies holophylla, Acer mono, Tilia amurensis, and Ulmus laciniata will increase at the steady state. In mid-slope, the result showed the remarkable decrease in the proportion of Juglans mandshurica, Kalopanax pictus, and Tilia amurensis from current 15%, 8%, and 15% to 2%, 1%, and 5%, respectively, at steady state predicted to take more than 250 years. In ridge, the current dominant Quercus mongolica was predicted to be decreased dramatically from 58% to 8% at steady state which could be achieved about 200 years. On the contrary, the proportion of Acer mono and Tilia amurensis will be increased from current 4% and 3% to more than 20% and 40%, respectively, at the steady state. Overall results suggested that the study forest is more likely seral rather than climax community. Even though a lot of variation is inevitable due to various kinds of site and vegetation development, the study forest is considered to be more than 200 years away from the steady state or climax in terms of overstory species composition.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.583-590
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• 2015

Submarine cable installation is essentials for grid connection between existing power grid and newly produced electricity which will be from offshore wind farm in Southwest sea area of Korea. Especially, submarine cable route and protection method is designed in order to ensure the economical efficiency, workability and stability of submarine cable installation. On this paper, we will give the basic information about the submarine cable route and protection method of offshore wind farm which will be built in Southwest sea area of Korea. For this, we have a numerical simulation at high and low tide based on the third-generation wave model SWAN(Simulating WAves Nearshore) using the long term wave data from Korea Institute of Ocean Science and Technology(KIOST). The results of the study, year mean Hs is 1.03m, Tz is 4.47s and dominant wave direction is NW and SSW When the incident wave direction is NW(Hs: 7.0 m, Tp: 11.76s), the distribution of shallow water design wave height Hs was calculated about 4.0~5.0m at high tide and 2.0~3.0m at low tide. When the incident wave direction is SSW(Hs: 5.84 m, Tp: 11.15s), the distribution of shallow water design wave height Hs was calculated about 3.5~4.5m at high tide and 1.5~2.5m at low tide. The wave direction on a dominant influence in the section of longitude UTM 249749~251349(about 1.6 km) and UTM 251549~267749(about 16.2 km) in the submarine cable route are each NW and SSW. Prominently, wave focusing phenomenon appears between Wi-do and Hawangdeung-do, in this sea area is showing a relatively high wave hight than the surrounding sea areas.

• Journal of Bio-Environment Control
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• v.32 no.1
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• pp.48-56
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• 2023

High-pressure sodium (HPS) lamps have been widely used as a useful supplemental light source to emit sufficient photosynthetically active radiation and provide a radiant heat, which contribute the heat requirement in greenhouses. The objective of this study to analyze the thermal characteristics of HPS lamp and thermal behavior in supplemented greenhouse, and evaluate the performance of a horizontal leaf temperature of sweet pepper plants using computational fluid dynamics (CFD) simulation. We simulated horizontal leaf temperature on upper canopy according to three growth stage scenarios, which represented 1.0, 1.6, and 2.2 plant height, respectively. We also measured vertical leaf and air temperature accompanied by heat generation of HPS lamps. There was large leaf to air temperature differential due to non-uniformity in temperature. In our numerical calculation, thermal energy of HPS lamps contributed of 50.1% the total heat requirement on Dec. 2022. The CFD model was validated by comparing measured and simulated data at the same operating condition. Mean absolute error and root mean square error were below 0.5, which means the CFD simulation values were highly accurate. Our result about vertical leaf and air temperature can be used in decision making for efficient thermal energy management and crop growth.

• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.152-171
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• 2019

In this study, we analyzed the characteristics of the cold air generated in Hannamgeumbuk and Geumbuk-Jeongmaek and proposed their management strategies. We also suggested management strategies after analyzing detailed cold airflows for Cheongju located Hannamgeumbuk-Jeongmaek and we compared the degree of nighttime temperature reduction of the Jeongmaek by using data obtained from observatories located on Cheongju. We used KALM(Kaltluftabflussmodell), a cold air simulation model developed in Germanay and identified both cold airflows and altitude of cold air layers generated during 360minutes at night. As a result, the cold airflow generated in the Jeongmaek became strong and the cold air was appeared clearly in the western part of the Hannamgeumbuk-Jeongamek and in the northern part of the Geumbuk-Jeongmaek. The average velocity of cold airflow was recorded at 0.45m/s, and the maximum speed of cold airflow was recorded at 2.70m/s. The average height of the cold air layer was 104.27m/s and the maximum thickness was 255.0m. The average velocity of cold airflows in Cheongju was 0.51m/s and the average height of cold air layer was 48.87m high. The highest degree of nighttime temperature reduction appeared in the Cheongnamdae observatory($-3.8^{\circ}C$), where the altitude of the cold air layer is high. The results showed that cooling effect of Jeongmaek actually affected the temperature reduction during nighttime. Based on the results, we designated the main mountain area of the Jeongmaek with active cold air generation as "cold air conservation areas" and proposed the current forest and topography conservation. We also proposed to designate areas that facilitate the cold airflows as "cold air management areas" and to complement the function of Jeongmaek. This study could support the establishment of systematic management plans of the Jeongmaek. In addition, it is expected that the results can be applied as basic data for ventilation paths of Cheongju.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.