• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.6
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• pp.453-458
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• 2001

The Rural Development Administration (RDA) of Korea now operates a system called Rice Variety Selection Tests (RVST), which are now being implemented in eight Agricultural Research and Extension Services located in eight province RVST's objective is to provide accurate yield estimates and to select well-adapted varieties to each province. Systematic evaluation of entries included in RVST is a highly important task to select the best-adapted varieties to specific location and to observe the performance of entries across a wide range of test sites within a region. The rice yield data in RVST for ordinary transplanting in Kangwon province during 1997-2000 were analyzed. The experiments were carried out in three replications of a random complete block design with eleven entries across five locations. Additive Main effects and Multiplicative Interaction (AMMI) model was employed to examine the interaction between genotype and environment (G$\times$E) in the biplot form. It was found that genotype variability was as high as 66％, followed by G$\times$E interaction variability, 21％, and variability by environment, 13％. G$\times$E interaction was partitioned into two significant (P＜0.05) principal components. Pattern analysis was used for interpretation on G$\times$E interaction and adaptibility. Major determinants among the meteorological factors on G$\times$E matrix were canopy minimum temperature, minimum relative humidity, sunshine hours, precipitation and mean cloud amount. Odaebyeo, Obongbyeo and Jinbubyeo were relatively stable varieties in all the regions. Furthermore, the most adapted varieties in each region, in terms of productivity, were evaluated.

• Analytical Science and Technology
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• v.17 no.6
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• pp.496-513
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• 2004

This study was carried out to evaluate the performance of sampling and analytical methodology used for the measurement of toxic volatile organic compounds (VOCs) in the ambient air. VOCs were determined by the adsorbent tube sampling and automatic thermal desorption coupled with GC/MSD analysis. Target analytes were 33 compounds including major aromatic compounds such as BTEX, and halogenated compounds. The methodology was investigated with a wide range of different adsorbents which are commercially available and have been frequently adopted for the VOC measurement. A total of 10 adsorbents were tested in this study: 6 carbon-based adsorbents such as Carbotrap, Carbopack B, Carbosieve S-III, Carboxen 1000, Carbotrap C, Activated Charcoal; and 4 polymer-based adsorbents including Tenax, Porapak Q, Chromosorb 102, and Chromosorb 106. The sampling performance was evaluated with respect to the sampling capacity of VOCs with single-adsorbent and multiple-adsorbents methods for standard samples and field samples. As a result, the best adsorbents for single-adsorbent method in the sampling of toxic organic compounds (including benzene, toluene, xylenes etc.) appeared to be Carbotrap, Carbopack B and Tenax TA. On the other hand, Chromosorb 102, Chromosorb 106 and Porapak Q were found to be unsuitable adsorbents for VOC measurement based on thermal desorption method. Multi-adsorbent packings were evaluated with 4 carbon-based adsorbents, which classified by 3 combination sets of double adsorbents and 2 combination sets of triple adsorbents. The results indicated that the most suitable combination for toixc VOC measurements is Carbotrap C with Carbotrap. Multi-sorbents tubes packed with a strong adsorbent such as Carbosieve S-III or Carboxen 1000 were found to be relatively unsuitable for several compounds, not only owing to the effect of migration of adsorbed compounds from weaker adsorbent to stronger adsorbent, but to hydrophobic nature of the adsorbents. Therefore, it should be addressed that selection of a proper adsorbent (or combination of multi sorbents) is extremely important to obtain reliable data for the concentrations of toxic VOCs in indoor and outdoor environments.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Korean Journal of Soil Science and Fertilizer
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• v.30 no.1
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• pp.56-61
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• 1997

A study was carried out to find out the basic information in physical properties for selection and manufacturing the good seedling media through the analysis of the physical properties, such as particle size, water retention and three phases of the major horticultural substrates. Easily available water(EAW), the water contents between 1kPa and 5kPa water potental, was highest in peatmoss with 39%, and perlite 34.0%, vermiculite 16.9%, but the values of osmunda and bark were lower than 4.8%. Water buffering capacity(WBC), the water content between 5kPa and 10kPa, was 6.1% in peatmoss and 2.3% in vermiculite but it was lower than 1.0% in other substrates. To adjust the suitable range of water potential at crossing point of water and air curves to 1.5~2.5kPa, more finer materials were needed in osmunda and bark, and more coarser materials must be added to peatmoss, perlite and vermiculite. Water potentials of substrates in saturated pot condition were equivalent to 2.2kPa in peatmoss and others were ranged in 1.0kPa to 4.3kPa of water potential in pressure chamber.

• Journal of Wetlands Research
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• v.17 no.2
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• pp.124-129
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• 2015

In order to get as ecological basic data for river restoration, vegetation investigation was conducted in natural river and analysed it synecological methods, such as ordination cluster. 29 plant communities units were identified and the major dominant plant communites were Quercus mongolica community, Pinus densiflora community, Populus davidiana community, Q. variabilis community and Prunus sargentii community. River vegetations were classified into ravine and gorge forest type and riverine softwood forest type. Ravine and gorge forest was dominanted by hardwood which located in steep slope and in high elevation, and riverine softwood forest by softwood, salix spp. Naturality was an important criterion for the selection of rivers, so many of the selected rivers are located in the upper stream and mid stream rather than the lower stream, where more human intervention is involved. Plant communities were consisted of hardwood forest(44 plots, 92%) and softwood forest(4 plot, 8%), respectively. PCA with total layer data showed 5 groups of communities: Q. mongolica community group, Prunus sargentii community group, Pinus densiflora community group, Prunus sargentii community - Pinus densiflora community group and the rest communities group. PCA with tree layer showed 3 groups: Q. mongolica community group, Prunus sargentii community group, and the rest community group. Cluster analysis also a showed a similar communities group to PCA ordination, but Magnolia sieboldii community and Prunus sargentii community were distinguished from the PCA result. From the result, it can be concluded that the plant communities of riparian be divided into hardwood and softwood forest by statistical techniques. It was appropriate to plant species such as Quercus mongolica, Pinus densiflora, Populus davidiana, Quercus variabilis and Prunus sargentii, at levee zone and high water level. And Sliax spp. were appropriate for planted plants at waterfront and low water level. The herb species to be planted on the floodplain were recommanded in the species composition co-occurred with the woody species.

• Journal of Life Science
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• v.23 no.11
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• pp.1325-1335
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• 2013

Working dogs, such as rescue dogs, military watch dogs, guide dogs, and search dogs, are selected by in-training examination of desired traits, including concentration, possessiveness, and boldness. In recent years, genetic information has been considered to be an important factor for the outstanding abilities of working dogs. To characterize the molecular features of the canine genes related to phenotypes for working dogs, we investigated the 24 previously reported genes (AR, BDNF, DAT, DBH, DGCR2, DRD4, MAOA, MAOB, SLC6A4, TH, TPH2, IFT88, KCNA3, TBR2, TRKB, ACE, GNB1, MSTN, PLCL1, SLC25A22, WFIKKN2, APOE, GRIN2B, and PIK3CG) that were categorized to personality, olfactory sense, and athletic/learning ability. We analyzed the chromosomal location, gene-gene interactions, Gene Ontology, and expression patterns of these genes using bioinformatic tools. In addition, variable numbers of tandem repeat (VNTR) or microsatellite (MS) polymorphism in the AR, MAOA, MAOB, TH, DAT, DBH, and DRD4 genes were reviewed. Taken together, we suggest that the genetic background of the canine genes associated with various working dog behaviors and skill performance attributes could be used for proper selection of superior working dogs.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.77-100
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• 2009

Information Systems (IS) is an essential tool for any organizations. The last decade has seen an increasing body of knowledge on IS usage. Yet, IS often fails because of its misuse or non-use. In general, decisions regarding the selection of a system, which involve the evaluation of many IS vendors and an enormous initial investment, are made not through the consensus of employees but through the top-down decision making by top managers. In situations where the selected system does not satisfy the needs of the employees, the forced use of the selected IS will only result in their resistance to it. Many organizations have been either integrating dispersed legacy systems such as archipelago or adopting a new ERP (Enterprise Resource Planning) system to enhance employee efficiency. This study examines user resistance prior to the adoption of the selected IS or ERP system. As such, this study identifies the importance of managing organizational resistance that may appear in the pre-adoption context of an integrated IS or ERP system, explores key factors influencing user resistance, and investigates how prior experience with other integrated IS or ERP systems may change the relationship between the affecting factors and user resistance. This study focuses on organizational members' resistance and the affecting factors in the pre-adoption context of an integrated IS or ERP system rather than in the context of an ERP adoption itself or ERP post-adoption. Based on prior literature, this study proposes a research model that considers six key variables, including perceived benefit, system complexity, fitness with existing tasks, attitude toward change, the psychological reactance trait, and perceived IT competence. They are considered as independent variables affecting user resistance toward an integrated IS or ERP system. This study also introduces the concept of prior experience (i.e., whether a user has prior experience with an integrated IS or ERP system) as a moderating variable to examine the impact of perceived benefit and attitude toward change in user resistance. As such, we propose eight hypotheses with respect to the model. For the empirical validation of the hypotheses, we developed relevant instruments for each research variable based on prior literature and surveyed 95 professional researchers and the administrative staff of the Korea Photonics Technology Institute (KOPTI). We examined the organizational characteristics of KOPTI, the reasons behind their adoption of an ERP system, process changes caused by the introduction of the system, and employees' resistance/attitude toward the system at the time of the introduction. The results of the multiple regression analysis suggest that, among the six variables, perceived benefit, complexity, attitude toward change, and the psychological reactance trait significantly influence user resistance. These results further suggest that top management should manage the psychological states of their employees in order to minimize their resistance to the forced IS, even in the new system pre-adoption context. In addition, the moderating variable-prior experience was found to change the strength of the relationship between attitude toward change and system resistance. That is, the effect of attitude toward change in user resistance was significantly stronger in those with prior experience than those with no prior experience. This result implies that those with prior experience should be identified and provided with some type of attitude training or change management programs to minimize their resistance to the adoption of a system. This study contributes to the IS field by providing practical implications for IS practitioners. This study identifies system resistance stimuli of users, focusing on the pre-adoption context in a forced ERP system environment. We have empirically validated the proposed research model by examining several significant factors affecting user resistance against the adoption of an ERP system. In particular, we find a clear and significant role of the moderating variable, prior ERP usage experience, in the relationship between the affecting factors and user resistance. The results of the study suggest the importance of appropriately managing the factors that affect user resistance in organizations that plan to introduce a new ERP system or integrate legacy systems. Moreover, this study offers to practitioners several specific strategies (in particular, the categorization of users by their prior usage experience) for alleviating the resistant behaviors of users in the process of the ERP adoption before a system becomes available to them. Despite the valuable contributions of this study, there are also some limitations which will be discussed in this paper to make the study more complete and consistent.

• Horticultural Science & Technology
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• v.28 no.3
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• pp.449-455
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• 2010

'Moulinrouge' was selected as the best regenerating cultivar among 18 different spray-type chrysanthemum cultivars bred in the Gyeongnam Flowers Breeding Research Institute. When the leaf explants from standard- and spray-type chrysanthemum 'Jinba' and 'Moulinrouge' were incubated on MS basal medium supplemented with $0.5mg{\cdot}L^{-1}$ BA and $1.0mg{\cdot}L^{-1}$ NAA, both 'Jinba' and 'Moulinrouge' induced adventitious shoots that can be regenerated into plantlets. Based on these regeneration conditions, we developed an efficient $Agrobacterium$-mediated chrysanthemum 'Moulinrouge' transformation method by using sequential selection of shoots from low ($10mg{\cdot}L^{-1}$) to high ($30mg{\cdot}L^{-1}$) concentrations of kanamycin after co-cultivation of leaf explants with $Agrobacterium$ for 10 days and induction of shoots. All kanamycin resistant plants investigated with genomic PCR analysis carried the report gene, $AtSICKLE$, in their genome. Although expression levels of the report gene in the transgenic plants investigated with RT-PCR were relatively low because of inefficiency of CaMV 35S promoter in chrysanthemum, transgenic lines expressing $AtSICKLE$ efficiently showed leaf epinasty phenotype. We expect that our results will provide a useful method that can perform a high-throughput investigation of genes isolated and studied well in model plants for molecular breeding of chrysanthemum.

• Horticultural Science & Technology
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• v.31 no.1
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• pp.80-88
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• 2013

Carrot (Daucus carota L. var. sativa) is one of the most extensively used vegetable crops in the world and a significant source of nutrient because of its high content of ${\beta}$-carotene, well known as the precursor of vitamin A carotenoid. However, seed-hairs generated and elongated from the epidermal cell of seeds inhibit absorption and germination by various factors such as carotol and so on. Accordingly, mechanical hair removal process is essential before commercialization of carrot seeds. Because of this process, producers will have additional losses such as time consuming, manpower, capital and so on. Furthermore, physical damage of seeds causes irregular germination rate. To overcome such cumbersome weaknesses, new breeding program for developing hairless-seed carrot cultivar has been needed and studies for molecular markers related to seed-hair characteristic is needed for a new breeding program. Therefore, in this study, cDNA libraries from seeds of short-hair seed phenotype CT-SMR 616 OP 659-1 line, hairy-seed phenotype CT-SMR 616 OP 677-14 line and short-hair seed phenotype CT-ATR 615 OP 666-13 line, hairy-seed phenotype CT-ATR 615 OP 671-9 were constructed, respectively. Furthermore, 1,248 ESTs in each line, total 4,992 ESTs were sequenced. As a result, 19 SNP sites and 14 SNP sites in each of 2 combinations were confirmed by analyzing these EST sequences from short-hair and hairy-seed lines. Then we designed SNP primer sets from EST sequences of SNP sites for high resolution melting (HRM) analysis. Designed HRM primers were analyzed using hairy seed phenotype CT-SMR 616 OP 1040 line and short-hair seed phenotype CT-SMR 616 OP 1024, 1025, 1026 lines. One set of HRM primers showed specific difference between the melting curves of hairy and short-hair seed phenotype lines. Based on this result, allele-specific (AS) PCR primers were designed for easier selection between hairy-seed carrot and hairless seed carrot. These results of HRM and AS-PCR are expected to be useful in breeding of hairless seed carrot cultivar as a molecular marker.

• Korean Journal of Ecology and Environment
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• v.48 no.3
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• pp.176-187
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• 2015

In this study, we hypothesized that the size of wintering crane population would change due to the climate factors. We assumed that wintering population size would differ by climate values in January, which is the coldest period in year. Especially, White-naped cranes were able to choose wintering site between Cheorwon and other alternative place where snow coverage had low influence, differing from Red crowned cranes. For this reason, we predicted the population size of White-naped cranes would fluctuate according to the extent of snow coverage in Cheorwon. Therefore we used snow coverage data based on MODIS and climate data from KMA (Korea Meteorological Administration) that are generally used. We analyzed the crane's population size in Cheorwon in January from 2002 to 2014. The temperature in the Cheorwon increased from 2002 to wintering period in 2007~ 2008 and went down, showing the lowest temperature in 2011~ 2012. With this phenomenon, warmth index showed the similar pattern with temperature. Amount of newly accumulated snow (the amount of snow that fallen from 0:01 am to 11:29 pm in a day) was low after 2002, but rapidly increased in 2010~ 2011 and 2011~ 2012. The area of snow coverage rapidly declined from 2002 to 2005~ 2006 but suddenly expanded in wintering period in 2009~ 2010 and 2010~ 2011. Wintering population size of the White-naped cranes decreased as snow coverage area increased in January and the highest correlation was found between them, compared to the other climatic factors. However, the number of individuals of Red crowned cranes had little relationship with general climate factors including snow cover range. Therefore it seems that population size of the Red crowned crane varied by factors related with habitat selection such as secure roosting site and area of foraging place, not by climatic factors. In multiple regression analysis, wintering population of White-naped cranes showed significant relationship with logarithmic value of snow cover range and its period. Therefore, it suggests that the population size of the White-naped crane was affected by snow cover range n wintering period and this was because it was hard for them to find out rice grains which are their main food items, buried in snow cover. The population size variation in White-naped cranes was caused by some individuals which left Cheorwon for Izumi where snow cover had little influence on them. The wintering population in Izumi and Cheorwon had negative correlation, implying they were mutually related.