• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.107-119
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• 2020

This study analyzed past drought characteristics based on the observed rainfall data and performed a long-term outlook for future extreme droughts using Representative Concentration Pathways 8.5 (RCP 8.5) climate change scenarios. Standardized Precipitation Index (SPI) used duration of 1, 3, 6, 9 and 12 months, a meteorological drought index, was applied for quantitative drought analysis. A single long-term time series was constructed by combining daily rainfall observation data and RCP scenario. The constructed data was used as SPI input factors for each different duration. For the analysis of meteorological drought observed relatively long-term since 1954 in Korea, 12 rainfall stations were selected and applied 10 general circulation models (GCM) at the same point. In order to analyze drought characteristics according to climate change, trend analysis and clustering were performed. For non-stationary frequency analysis using sampling technique, we adopted the technique DEMC that combines Bayesian-based differential evolution ("DE") and Markov chain Monte Carlo ("MCMC"). A non-stationary drought frequency analysis was used to derive Severity-Duration-Frequency (SDF) curves for the 12 locations. A quantitative outlook for future droughts was carried out by deriving SDF curves with long-term hydrologic data assuming non-stationarity, and by quantitatively identifying potential drought risks. As a result of performing cluster analysis to identify the spatial characteristics, it was analyzed that there is a high risk of drought in the future in Jeonju, Gwangju, Yeosun, Mokpo, and Chupyeongryeong except Jeju corresponding to Zone 1-2, 2, and 3-2. They could be efficiently utilized in future drought management policies.

• Korean Journal of Breeding Science
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• v.42 no.1
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• pp.40-49
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• 2010

This study was conducted to examine genetic variation on leaf characteristics of Zelkova serrata populations. Leaf samples were obtained from eighteen populations and fourteen leaf characteristics such as leaf blade length, leaf width, leaf area and etc. were measured. In all leaf characteristics, there were significant differences among populations and among individuals within population. Most variance of leaf characteristics was contributed to among individuals within population except for length from leaf base to maximum width (x3) and the ratio of x3 to leaf blade length (x10). The relatively high variations of leaf characteristics were found at Gurye, Jungeup and Gyungju populations while Youngwol, Cheongsong, Youngchun populations showed the lower variation. There was high correlation among leaf characteristics related to leaf size, but not among the variables of ratio between leaf characteristics. Length from leaf base to maximum width(x3) and the ratio of x3 to x10 showed significant positive correlation with latitude and altitude of populations, which reflect the differences of mean annual temperature among populations. Mean annual rainfall of populations showed negative correlation with leaf blade length, leaf width, length from apex to first serration and leaf area. Four principal components (PC) were deduced from principal component analysis, which explain the 88.5% of total variance of leaf characteristics. Leaf area, length from leaf base to maximum width, serration number and petiole length showed the highest contribution to PC1, PC2, PC3, PC4, respectively. According to cluster analysis, the populations of Z. serrata were divided into two groups, which reflect the difference of mean annual temperature between groups. Within group, however, specific tendency of clustering was not observed among populattions.

• Journal of Life Science
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• v.26 no.3
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• pp.282-288
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• 2016

Protein-protein interactions regulate the subcellular localization and function of receptors, enzymes, and cytoskeletal proteins. Proteins containing the postsynaptic density-95/disks large/zonula occludens-1 (PDZ) domain have potential to act as scaffolding proteins and play a pivotal role in various processes, such as synaptic plasticity, neural guidance, and development, as well as in the pathophysiology of many diseases. Multi-PDZ domain protein 1 (MUPP1), which has 13 PDZ domains, has a scaffolding function in the clustering of surface receptors, organization of signaling complexes, and coordination of cytoskeletal dynamics. However, the cellular function of MUPP1 has not been fully elucidated. In the present study, a yeast two-hybrid system was used to identify proteins that interacted with the N-terminal PDZ domain of MUPP1. The results revealed an interaction between MUPP1 and Wdpcp (formerly known as Fritz). Wdpcp was identified as a planar cell polarity (PCP) effector, which is known to have a role in collective cell migration and cilia formation. Wdpcp bound to the PDZ1 domain but not to other PDZ domains of MUPP1. The C-terminal end of Wdpcp was essential for the interaction with MUPP1 in the yeast two-hybrid assay. This interaction was further confirmed in a glutathione S-transferase (GST) pull-down assay. When coexpressed in HEK-293T cells, Wdpcp was coimmunoprecipitated with MUPP1. In addition, MUPP1 colocalized with Wdpcp at the same subcellular region in cells. Collectively, these results suggest that the MUPP1-Wdpcp interaction could modulate actin cytoskeleton dynamics and polarized cell migration.

• Journal of the Korean Society of Food Science and Nutrition
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• v.35 no.2
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• pp.199-204
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• 2006

This study was conducted to investigate the quality characteristics of noodles prepared with the addition of nanofiltered (NF) powder of sunmul. Noodles were prepared with different levels $(0\%,\;1.5\%,\;3\%\;and\;5\%,\;w/w)$ of NF powder and physico-chemical properties were examined. Results of rapid visco analyzer showed that peak, trough, final viscosity and set back decreased as the NF powder level increased. The weight and volume of cooked noodles increased with the addition of NF powder. Turbidity of soup also increased as the amount of NF powder increased, indicating higher cooking loss. The color of wet and cooked noodles became greenish yellow as the NF powder level increased. Hardness, springiness, gumminess and brittleness of cooked noodles decreased with the increasing amount of NF powder. Results of sensory evaluation showed that noodles prepared with up to $3\%$ addition of NF powder was considered to be as acceptable as noodles prepared without NF powder.

• Korean Journal of Plant Resources
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• v.34 no.4
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• pp.297-310
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• 2021

Lonicera harae is a species of shrub in the Caprifoliaceae family, mostly distributed in East asia. So far, the related research on the genus of Lonicera is insufficient compared to the Lonicera japonica belonging to the same genus, which requires attention to domestic native plants. Therefore, this study aims to provide baseline data for cultivation and utilization through the growth environment and vegetation structure of the natural habitat. Lonicera harae, which plant found throughout the Korean Peninsula. The natural habitats of Lonicera harae is the forest, valley and lowland areas of the southern region. study examined 24 quadrats in 11 regions, including Gwangju, Wanju and Namhae. As a result, environmental condition of Lonicera harae was 8 to 483 m above sea level, normally distributed over 173 m, Slope was 5 to 25 degree with 8.5 degree on average. The list of plants were classified as a total of 229 taxa comprising 80 families, 166 genus, 198 species, 3 subspecies, 24 varieties, 4 forma. As a result of the clustering analysis, the three clusters were divided into three groups; Robinia pseudoacacia, Zelkova serrata, Larix kaempferi. Species diversity was 1.399 and Dominance and Evenness were found to be 0.978 and 0.022 respectively.

• Korean Journal of Plant Resources
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• v.36 no.5
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• pp.496-507
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• 2023

The in vitro organogenesis is one of important issues in plant embryology, and somaclonal variations are existing in calli and/or regenerants induced from a process of the organogenesis with in vitro circumstances. In this study, expressions of organogenesis-related genes were evaluated and genetic stability of regenerants derived from the process of in vitro organogenesis were measured using ISSR markers in Imperata cylindrica 'Rubra', Poaceae. The expressions of organogenesis-related genes were detected all of regenerants at the process of the organogenesis. All ISSR markers produced with an average of 71 bands per in vitro-cultured regenerants, and the scorable bands were varied from two to eight with an average of 5.14 bands per a primer. The polymorphism rates of the in vitro regenerants were higher than that of mother plants (1.4%), showing 4.1% (pot-cultured regenerants), 4.3% (field-cultured regenerants), 4.2% (in vitro-cultured regenerants), 5.6% (calli with green shoots) and 1.4% (calli), respectively. The genetic similarity matrix (GSM) among all accessions ranged from 0.747 to 1.0 with a mean of 0.868. GSM of the regenerants showed differences (from 0.972 to 1.00) compared with that of mother plants (0.991). According to the clustering analysis, two independent groups were divided into; the one is mother plants and regenerants cultured at room and open field, the other is regenerants cultured in vitro. The results give a new insight for understanding the dynamics of organogenesis in monocot plant.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.

• Journal of Korea Game Society
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• v.4 no.4
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• pp.11-18
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• 2004

The on-line games in the past were played by only two persons exchanging data based on one-to-one connections, whereas recent ones (e.g. MMORPG: Massively Multi-player Online Role-playings Game) enable tens of thousands of people to be connected simultaneously. Specifically, Korea has established an excellent network infrastructure that can't be found anywhere in the world. Almost every household has a high-speed Internet access. What made this possible was, in part, high density of population that has accelerated the formation of good Internet infrastructure. However, this rapid increase in the use of on-line games may lead to surging traffics exceeding the limited Internet communication capacity so that the connection to the games is unstable or the server fails. expanding the servers though this measure is very costly could solve this problem. To deal with this problem, the present study proposes the load distribution technology that connects in the form of local clustering the game servers divided by their contents used in each on-line game reduces the loads of specific servers using the load balancer, and enhances performance of sewer for their efficient operation. In this paper, a cluster system is proposed where each Game server in the system has different contents service and loads are distributed efficiently using the game server resource information such as CPU utilization. Game sewers having different contents are mutually connected and managed with a network file system to maintain information consistency required to support resource information updates, deletions, and additions. Simulation studies show that our method performs better than other traditional methods. In terms of response time, our method shows shorter latency than RR (Round Robin) and LC (Least Connection) by about 12%, 10% respectively.

• Journal of the Korean association of regional geographers
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• v.7 no.3
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• pp.107-120
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• 2001

This study is concerned with providing a reliable procedure of calibrating a set of places specific distance parameters and with applying it to U.S. inter-State migration flows between 1985 and 1900. It attempts to conform to recent advances in quantitative geography that are characterized by an integration of ESDA(exploratory spatial data analysis) and local statistics. ESDA aims to detect the spatial clustering and heterogeneity by visualizing and exploring spatial patterns. A local statistic is defined as a statistically processed value given to each location as opposed to a global statistic that only captures an average trend across a whole study region. Whereas a global distance parameter estimates an averaged level of the friction of distance, place-specific distance parameters calibrate spatially varying effects of distance. It is presented that a poisson regression with an adequately specified design matrix yields a set of either origin-or destination-specific distance parameters. A case study demonstrates that the proposed model is a reliable device of measuring a spatial dimension of migration, and that place-specific distance parameters are spatially heterogeneous as well as spatially clustered.

• Korean Journal of Poultry Science
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• v.50 no.1
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• pp.41-50
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• 2023

Over the last decade, avian influenza (AI) has been considered an emerging disease that would become the next pandemic, particularly in countries like South Korea, with continuous animal outbreaks. In this situation, risk assessment is highly needed to prevent and prepare for human infection with AI. Thus, we developed the risk assessment matrix for a high-risk area of human infection with AI in South Korea based on the notion that risk is the multiplication of hazards with vulnerability. This matrix consisted of highly pathogenic avian influenza (HPAI) in poultry farms and the number of poultry-associated production facilities assumed as hazards of avian influenza and vulnerability, respectively. The average number of HPAI in poultry farms at the 229-municipal level as the hazard axis of the matrix was predicted using a negative binomial regression with nationwide outbreaks data from 2003 to 2018. The two components of the matrix were classified into five groups using the K-means clustering algorithm and multiplied, consequently producing the area-specific risk level of human infection. As a result, Naju-si, Jeongeup-si, and Namwon-si were categorized as high-risk areas for human infection with AI. These findings would contribute to designing the policies for human infection to minimize socio-economic damages.