• Journal of Practical Agriculture & Fisheries Research
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• v.13 no.1
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• pp.35-46
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• 2011

The effects of organic calcium agent(ECa) tree-spray on the mineral nutrition concentration of petiole and fruit skin and quality in grapevines were studied. The calcium concentration of petiole and fruit skin at harvest in 'Campbell Early' by tree-spray after flowering 14days of calcium agent were increased significantly in calcium chloride 0.4%, ECa 250X and MCa 500X compared to control. The calcium concentration of petiole and fruit skin at harvest by ECa tree-spray after 7 days and 14 days flowering were increased significantly compared to control and 21 days after flowering treatment. Also, The calcium concentration of petiole and fruit skin at harvest by tree-spray of ECa 250X and 125X after flowering were increased significantly compared to control and 500X treatment. Fruit quality, fruit cluster weight, cracking fruit and Bitter rot occurrence by ECa tree-spray of treatment time and concentration different showed no difference between control. Phytotoxicity by tree-spray of ECa concentration different not occur to leaf and fruit.

• Journal of Practical Agriculture & Fisheries Research
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• v.5 no.1
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• pp.28-35
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• 2003

This study was conducted to investigate the nutrition status, growth and fruit quality of 'Campbell Early' grapes in Hwaseong area. Organic matter content of 3 vineyard soils was significantly lower than standard value. P₂O₅ and K contents of Y vineyard and P₂O₅ of C vineyard were very high. But there were no significant differences in contents of Ca, Mg and CEC. Compared to the standard value. T-N, Ca and Mg contents of petiole were adequate. P₂O₅ contents of Y and C vineyard and K contents of Y vineyard were significantly higher than standard value. Berry firmness, color and bloom occurrence on fruit skin showed no differences among 3 vineyard. Soluble solids content poorly, yield per tree and goods fruit of C vineyard decreased significantly compared to the fruit in Y and H vineyards. Russetted fruit of Y vineyard, colored fruit of H vineyard, and unfertilized fruit, cracked fruit, and bitter rot were observed frequently.

• Korean Journal of Environmental Agriculture
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• v.41 no.4
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• pp.335-343
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• 2022

BACKGROUND: Antibiotics used in animal husbandry for disease prevention and treatment have resulted in the rapid progression of antibiotic resistant bacteria which can be introduced into the environment through livestock feces/manure, disseminating antibiotic resistant genes (ARGs). In this study, fecal samples were collected from the livestock farms located in Jeju Island to investigate the relationship between microbial communities and ARGs. METHODS AND RESULTS: Illumina MiSeq sequencing was applied to characterize microbial communities within each fecal sample. Using quantitative PCR (qPCR), ten ARGs encoding tetracycline resistance (tetB, tetM), sulfonamide resistance (sul1, sul2), fluoroquinolone resistance (qnrD, qnrS), fluoroquinolone and aminoglycoside resistance (aac(6')-Ib), beta-lactam resistance (bla_TEM, bla_CTX-M), macrolide resistance (ermC), a class 1 integronsintegrase gene (intI1), and a class 2 integrons-integrase gene (intI2) were quantified. The results showed that Firmicutes and Bacteroidetes were dominant in human, cow, horse, and pig groups, while Firmicutes and Actinobacteria were dominant in chicken group. Among ARGs, tetM was detected with the highest number of copies, followed by sul1 and sul2. Most of the genera belonging to Firmicutes showed positive correlations with ARGs and integron genes. There were 97, 34, 31, 25, and 22 genera in chicken, cow, pig, human, and horse respectively which showed positive correlations with ARGs and integron genes. In network analysis, we identified diversity of microbial communities which correlated with ARGs and integron genes. CONCLUSION(S): In this study, antibiotic resistance patterns in human and livestock fecal samples were identified. The abundance of ARGs and integron genes detected in the samples were associated with the amount of antibiotics commonly used for human and livestocks. We found diverse microbial communities associated with antibiotics resistance genes in different hosts, suggesting that antibiotics resistance can disseminate across environments through various routes. Identifying the routes of ARG dissemination in the environment would be the first step to overcome the challenge of antibiotic resistance in the future.

• Korean Journal of Culture and Social Issue
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• v.25 no.4
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• pp.325-351
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• 2019

The present study examined patterns of co-occurrence between DSM-5 posttraumatic stress disorder(PTSD) symptoms and posttraumatic growth(PTG) among Korean populations(n= 860). Latent profile analysis was used to identify subclasses and suggested that the 3-class model fit best: (1) Low PTSD/Mild PTG group (2) Low PTSD/High PTG group; (3) High PTSD/High PTG group. Class membership was predicted by demographic variables, social isolation, and frequency of traumatic experiences. Classes also differed with respect to self-destructive behaviors(binge eating, non-suicidal self-injury, and problem drinking). These findings contribute to future research about the coexisting patterns of PTSD and PTG, and to identify high-risk individuals who suffer from trauma-related problems in clinical practice.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.4
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• pp.29-54
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• 2023

This study aimed to analyze the research trends of journal articles published by medical schools representing Korean modern. A total of 682 were selected from two journals published by Medical College in Keijo and Keijo Imperial University Medical Faculty. In results, the affiliations of authors who participated in Acta Medicinalia in Keijo included various schools and hospitals, and the authors' major was found to be similar in basic medicine and clinical medicine. In The Keijo Journal of Medicine, only school-affiliated authors participated, and 96.33% of the authors were majors in basic medicine. Co-occurrence network analysis was conducted on MeSH terms from the title of the article using MeSH on Demand, and the keyword that derived in both journals was 'erythrocytes', which analyzed the condition of red blood cells according to organs and diseases. In frequency analysis, a common area of research in both journals was the study focusing on blood and blood cells, and the study of anemia and tuberculosis, which were prevalent diseases at the time. As for comparing each journal, Acta Medicinalia in Keijo has focused on inflammatory diseases and clinical pathological studies in humans, and The Keijo Journal of Medicine has focused on anatomical studies on animals and pharmacological studies on medicines. Through this study, it was possible to identify the research topics and major keywords in two medical schools with different founding goals.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.19-32
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• 2023

The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.27-33
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• 2023

Recently, water shortages have occurred due to climate change, and the need for water management of agricultural water has increased due to the occurrence of algal blooms in reservoirs. Existing algae prevention is operated by putting many people on site and misses the optimal spraying time due to movement through boats. In order to solve this problem, it is necessary to block contamination in advance and move within time to uniformly spray complex microorganisms uniformly. Control drones are used for pesticide spraying and can be applied to algae prevention work by utilizing control drones. In this paper, basic research for the establishment of a marine control system was conducted for application to the reservoir environment, and as one of the results, the characteristics of a drone nozzle, a core technology that can be used for control drones, were calculated. In particular, it was found that the existing agricultural control drones had a disadvantage that the concentration was non-uniform within the suggested spraying interval, and to compensate for this, nozzle positioning and nozzle spraying uniformity were calculated. Based on the experimental results, we develop a core algorithm for establishing an algal bloom monitoring system in the reservoir environment and propose a precision control technology that can be used for marine control work in the future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.141-156
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• 2023

Due to the unprecedented worldwide pandemic of the new Covid-19 infection, business trends of companies have changed significantly. Therefore, it is strongly required to monitor the rapid changes of innovation trends to design and plan future businesses. Since the pandemic, many studies have attempted to analyze business changes, but they are limited to specific industries and are insufficient in terms of data objectivity. In response, this study aims to analyze business trends after Covid-19 using Crunchbase, a global startup data. The data is collected and preprocessed every two years from 2018 to 2021 to compare the business trends. To capture the major trends, a network analysis is conducted for the industry groups and industry information based on the co-occurrence. To analyze the minor trends, LDA-based topic modelling and word2vec-based clustering is used. As a result, e-commerce, education, delivery, game and entertainment industries are promising based on their technological advances, showing extension and diversification of industry boundaries as well as digitalization and servitization of business contents. This study is expected to help venture capitalists and entrepreneurs to understand the rapid changes under the impact of Covid-19 and to make right decisions for the future.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.413-426
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• 2023

Species distribution model (SDM) is used to preserve biodiversity and climate change impact. To evaluate biodiversity, various studies are being conducted to utilize and apply SDM. However, there is insufficient research to provide useful information by identifying the current status and recent trends of SDM research and discussing implications for future research. This study analyzed the trends and flow of academic papers, in the use of SDM, published in academic journals in South Korea and provides basic information that can be used for related research in the future. The current state and trends of SDM research were presented using philological methods and text-mining. The papers on SDM have been published 148 times between 1998 and 2023 with 115 (77.7%) papers published since 2015. MaxEnt model was the most widely used, and plant was the main target species. Most of the publications were related to species distribution and evaluation, and climate change. In text mining, the term 'Climate change' emerged as the most frequent keyword and most studies seem to consider biodiversity changes caused by climate change as a topic. In the future, the use of SDM requires several considerations such as selecting the models that are most suitable for various conditions, ensemble models, development of quantitative input variables, and improving the collection system of field survey data. Promoting these methods could help SDM serve as valuable scientific tools for addressing national policy issues like biodiversity conservation and climate change.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.177-193
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• 2014

Over the past decade, there has been a rapid diffusion of electronic commerce and a rising number of interconnected networks, resulting in an escalation of security threats and privacy concerns. Electronic commerce has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction, and the risk of negative consequences from providing such information. More recently, the frequent disclosure of private information has raised concerns about privacy and its impacts. This has motivated researchers in various fields to explore information privacy issues to address these concerns. Accordingly, the necessity for information privacy policies and technologies for collecting and storing data, and information privacy research in various fields such as medicine, computer science, business, and statistics has increased. The occurrence of various information security accidents have made finding experts in the information security field an important issue. Objective measures for finding such experts are required, as it is currently rather subjective. Based on social network analysis, this paper focused on a framework to evaluate the process of finding experts in the information security field. We collected data from the National Discovery for Science Leaders (NDSL) database, initially collecting about 2000 papers covering the period between 2005 and 2013. Outliers and the data of irrelevant papers were dropped, leaving 784 papers to test the suggested hypotheses. The co-authorship network data for co-author relationship, publisher, affiliation, and so on were analyzed using social network measures including centrality and structural hole. The results of our model estimation are as follows. With the exception of Hypothesis 3, which deals with the relationship between eigenvector centrality and performance, all of our hypotheses were supported. In line with our hypothesis, degree centrality (H1) was supported with its positive influence on the researchers' publishing performance (p<0.001). This finding indicates that as the degree of cooperation increased, the more the publishing performance of researchers increased. In addition, closeness centrality (H2) was also positively associated with researchers' publishing performance (p<0.001), suggesting that, as the efficiency of information acquisition increased, the more the researchers' publishing performance increased. This paper identified the difference in publishing performance among researchers. The analysis can be used to identify core experts and evaluate their performance in the information privacy research field. The co-authorship network for information privacy can aid in understanding the deep relationships among researchers. In addition, extracting characteristics of publishers and affiliations, this paper suggested an understanding of the social network measures and their potential for finding experts in the information privacy field. Social concerns about securing the objectivity of experts have increased, because experts in the information privacy field frequently participate in political consultation, and business education support and evaluation. In terms of practical implications, this research suggests an objective framework for experts in the information privacy field, and is useful for people who are in charge of managing research human resources. This study has some limitations, providing opportunities and suggestions for future research. Presenting the difference in information diffusion according to media and proximity presents difficulties for the generalization of the theory due to the small sample size. Therefore, further studies could consider an increased sample size and media diversity, the difference in information diffusion according to the media type, and information proximity could be explored in more detail. Moreover, previous network research has commonly observed a causal relationship between the independent and dependent variable (Kadushin, 2012). In this study, degree centrality as an independent variable might have causal relationship with performance as a dependent variable. However, in the case of network analysis research, network indices could be computed after the network relationship is created. An annual analysis could help mitigate this limitation.