• Weed & Turfgrass Science
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• v.5 no.2
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• pp.51-59
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• 2016

The study was conducted to get a information on the dominance and distribution of weeds occurred in major orchards including apple, grape, peach, pear, and plum at 631 sites of Gyeongsangbuk-do during winter and summer season. The weeds classified by family and life cycle occurred in the five orchards were summarized as 36 family and 105 species in apple orchard, 34 family and 126 species in grape orchard, 34 family 126 species in peach orchard, 33 family 98 species in pear orchards, and 36 family 111 species in plum orchard. In addition to life cycle of weeds, most orchards except for pear orchard were dominant to biennial weeds. The most dominant importance value was observed in pear orchards as 6.57%. In winter's season, the weeds were summarized as 31 family and 89 species in apple orchard, 28 family and 71 species in grape orchard, 32 family 111 species in peach orchard, 27 family 68 species in pear orchards, and 33 family 83 species in plum orchard. In summer's season, the weeds were distributed as 31 family and 101 species in apple orchard, 27 family and 69 species in grape orchard, 29 family 91 species in peach orchard, 31 family 94 species in pear orchard, and 31 family 97 species in plum orchard. In winter season, the most dominant weeds in apple, grape, peach, pear, and plum orchard were Capsella bursa-pastoris, Laria media, Capsella bursa-pastoris, Capsella bursa-pastoris, and Erigeron canadensis, in turn. In summer season, the most dominant weeds in apple, grape, peach, pear, and plum orchard were Acalypha australis, Acalypha australis, Setaria viridis, Setaria viridis, and Setaria viridis, respectively.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.357-368
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• 2017

To establish new metal groundwater standard, 5 metals such as aluminum, chromium, iron, manganese, and selenium were evaluated by Chemical Ranking Of groundWater pollutaNts (CROWN) including possibility of exposure, toxicity, interest factor, connection standard for other media, and data reliability. 430 groundwater samples in 2013 and 2014 were collected semiannually from 110 groundwater wells and they were analyzed for selenium, manganese, iron, chromium, and aluminum. For this study, 430 groundwater samples were categorized into 3 geological distribution features, such as igneous, metamorphic, and sedimentary rock region and geological background levels were divided by pre-selection methods. For the results, the average concentrations of aluminum, chromium, iron, manganese, and selenium in 430 groundwater samples were $0.0008mg\;L^{-1}$, $0.0001mg\;L^{-1}$, $0.174mg\;L^{-1}$, $0.083mg\;L^{-1}$, and $0.0004mg\;L^{-1}$, respectively. In addition, among various geologies, average concentration of selenium was the highest in igneous rock region, average concentrations of chromium, manganese and aluminum were the greatest in sedimentary rock region, and average concentration of iron was the most high in metamorphic rock region. As a result of the geological background concentration with pre-selection method, background concentrations of selenium and aluminum in groundwater samples were the highest from sedimentary rock as $0.0010mg\;L^{-1}$ and $0.0029mg\;L^{-1}$ and background concentrations of manganese and iron in groundwater samples were the greatest from metamorphic rock as $0.460mg\;L^{-1}$ and $1.574mg\;L^{-1}$, and no chromium background concentration in groundwater samples was found from all geology.

• Journal of Environmental Science International
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• v.19 no.5
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• pp.549-563
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• 2010

The environmental behaviors of polycyclic aromatic hydrocarbons (PAHs) are mainly governed by their solubility and partitioning properties on soil media in a subsurface system. In surfactant-enhanced remediation (SER) systems, surfactant plays a critical role in remediation. In this study, sorptive behaviors and partitioning of naphthalene in soils in the presence of surfactants were investigated. Silica and kaolin with low organic carbon contents and a natural soil with relatively higher organic carbon content were used as model sorbents. A nonionic surfactant, Triton X-100, was used to enhance dissolution of naphthalene. Sorption kinetics of naphthalene onto silica, kaolin and natural soil were investigated and analyzed using several kinetic models. The two compartment first-order kinetic model (TCFOKM) was fitted better than the other models. From the results of TCFOKM, the fast sorption coefficient of naphthalene ($k_1$) was in the order of silica > kaolin > natural soil, whereas the slow sorbing fraction ($k_2$) was in the reverse order. Sorption isotherms of naphthalene were linear with organic carbon content ($f_{oc}$) in soils, while those of Triton X-100 were nonlinear and correlated with CEC and BET surface area. Sorption of Triton X-100 was higher than that of naphthalene in all soils. The effectiveness of a SER system depends on the distribution coefficient ($K_D$) of naphthalene between mobile and immobile phases. In surfactant-sorbed soils, naphthalene was adsorbed onto the soil surface and also partitioned onto the sorbed surfactant. The partition coefficient ($K_D$) of naphthalene increased with surfactant concentration. However, the $K_D$ decreased as the surfactant concentration increased above CMC in all soils. This indicates that naphthalene was partitioned competitively onto both sorbed surfactants (immobile phase) and micelles (mobile phase). For the mineral soils such as silica and kaolin, naphthalene removal by mobile phase would be better than that by immobile phase because the distribution of naphthalene onto the micelles ($K_{mic}$) increased with the nonionic surfactant concentration (Triton X-100). For the natural soil with relatively higher organic carbon content, however, the naphthalene removal by immobile phase would be better than that by mobile phase, because a high amount of Triton X-100 could be sorbed onto the natural soil and the sorbed surfactant also could sorb the relatively higher amount of naphthalene.

• Journal of Distribution Science
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• v.13 no.1
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• pp.71-81
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• 2015

Purpose - This study aims to examine the effect of audience attitude toward product placement, or PPL, on product attitude and purchase intention. PPL has increasingly been prevailing in TV dramas since the revision of the Broadcasting Act in January 2010, and it is quite widespread in today's society. Therefore, this study intends to investigate how the audience would take a particular attitude toward PPL in TV dramas and how their attitude would affect their product attitude and purchase intention. Research design, data, and methodology - The sample for the current study was drawn from college students in Seoul in December 2013, as the main targets of the products and brands that were advertised by PPL are young people. The questionnaire for this study comprised nine parts, such as the knowledge of PPL, experience of PPL, TV drama watching time, impulsive buying propensity, celebrity imitating buying propensity, attitude toward PPL, attitude toward product, purchase intention, and demographic characteristics. The questionnaire items were measured by 5-point Likert scales. Whether the demographic characteristics and propensity to consume would affect PPL attitude was analyzed and how the PPL attitude would affect purchase intention through product attitude was analyzed as well. To analyze the relationship between variables, structural equation modeling analysis was performed with Amos 18.0. Results - The major findings of the study were as follows. First, whether the demographic characteristics and propensity to consume would affect PPL attitude was analyzed, and it is found that out of the demographic characteristics, only gender and knowledge of PPL exerted an influence on PPL attitude. In addition, celebrity-imitating buying propensity had an impact on PPL attitude. Second, whether PPL attitude would affect purchase intention through product attitude was analyzed by structural equation modeling. Consequently, it is found that PPL attitude impacted purchase intention through product attitude. Conclusions - The findings of the study had the following implications. First, in theoretical aspects, previous studies have proven only that attitude toward PPL influenced attitude toward product and purchase intention separately; however, the current study has investigated the mediated role of attitudes toward PPL. Second, regarding the practical aspects, as PPL attitude exercised an effect on purchase intention as well as product attitude, PPL should be utilized in a manner to stimulate the audience to take a positive attitude to it. Finally, gender, PPL knowledge, and celebrity-imitating buying orientation were identified as influential factors for PPL attitude. Specifically, female consumers showed a lower attitude toward PPL than males, and the consumers who have no knowledge showed a lower attitude toward PPL. The consumers who have celebrity imitating buying propensity expressed a higher attitude toward PPL. These factors should consequently be taken into account when PPL is planned and conducted. The current study has limitations such as the sample object, non- experimental method, and media biases. Therefore, future research should be conducted to address these limitations.

• Journal of Distribution Science
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• v.12 no.8
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• pp.5-15
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• 2014

Purpose - The method of TV home shopping is a kind of retail method that provides the viewer with information about products and, further, sells the products to consumers through the media of television. The domestic home-shopping industry has been expanding since 1995, and there are six companies in this arena as of 2012. In this study, we evaluate the management efficiency of TV home-shopping companies and provide suggestions for improving efficiency, using the DEA (data envelopment analysis) model. Hence, we expect to contribute to the progress of the companies' efficiency and the development of the TV home-shopping industry, where deepening competition is inevitable because it is experiencing the maturing market stage in its life cycle. Research design, data, and methodology - Efficiency is the ratio of the quantity of input to the quantity of output of a product or service. It is necessary to estimate aggregate inputs and aggregate outputs, which are calculated by applying a weighting to a number of input and output factors, to measure the efficiency. The DEA model is divided into the CCR model and the BCC model. The CCR model is a basic model that assumed constant returns to scale (CRS), and the BCC model extends the CCR model to accommodate technologies exhibiting variable returns to scale (VRS), and concerns only the technical efficiency without considering the efficiency of returns to scale. In this study, we consider six companies each year from 2008 to 2012 as a DMU (Decision Making Unit) and analyze the differences in efficiency for each company in each year. Furthermore, we evaluate the operating characteristics of TV home-shopping companies, using three models, in accordance with the overall performance, profitability, and marketability of the business. Results - The result of the analysis, using DEA models, shows that Hyundai Home Shopping (2009, 2010, 2011), GS Home Shopping (2011), NS Home Shopping (2011) and CJ O Shopping (2012) possess MPSS (most productive scale size), with a score 1.0 in CCR, BCC, and scale efficiency. Particularly, Hyundai Home Shopping is shown to be the most efficient in terms of overall business performance, marketability, and profitability. The overall efficiency of the home shopping industry has displayed an increasing trend since 2008, even though it decreased marginally in 2012; further, we can observe that home shopping companies operate with increasing efficiency with the passage of time. Conclusions - Home shopping companies have focused on market expansion rather than profits, as they displayed better efficiency in marketability than increase in profitability during the period 2008-2012. In addition, the main reason for the increased efficiency in the home shopping industry is the market expansion through the revenue increase of each home shopping company. This study can be used as a reference when home shopping companies attempt to devise future strategies, as it suggests efficiency benchmarks and development levels for each home shopping company.

• The Journal of Natural Sciences
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• v.11 no.1
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• pp.131-135
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• 1999

The objective of this research was to improve moisture retention capacity of pine bark. To achieve this, barks were ground with Wiley mill of hammer mill and were blended with recycled rockwool. Then, changes of soil physical properties were determined. The percentage of particles larger than 5.6 mm was 86.5% in raw materials. The percentage of particles larger than 1 mm decreased and those of particles smaller than 1 mm increased by grinding with Wiley mill or hammer mill. Grinding with Wiley mill showed better effect than those of hammer mill in decreasing particle size distribution. Grinding resulted in decreased total porosity (TP) and air space (AS) and increased container capacity (CC) and residual water content (RW), indication improved moisture retention capacity. The material ground with Wiley mill, than blended with 50% recycled rockwool had 81.1%, 67.7%, 13.5% and 235 ml in TP, CC, AS and RW, respectively. These results indicated that moisture retention capacity was improved by blending with recycled rockwood, but aeration of root media was much better than those of peat+vermiculite(1:1, v/v), which is commonly used in commercial production.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.296-307
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• 2021

A digital hologram (DH) is an ultra-high value-added video content that includes 3D information in 2D data. Therefore, its intellectual property rights must be protected for its distribution. For this, this paper proposes a watermarking method of DH using a deep neural network. This method is a watermark (WM) invisibility, attack robustness, and blind watermarking method that does not use host information in WM extraction. The proposed network consists of four sub-networks: pre-processing for each of the host and WM, WM embedding watermark, and WM extracting watermark. This network expand the WM data to the host instead of shrinking host data to WM and concatenate it to the host to insert the WM by considering the characteristics of a DH having a strong high frequency component. In addition, in the training of this network, the difference in performance according to the data distribution property of DH is identified, and a method of selecting a training data set with the best performance in all types of DH is presented. The proposed method is tested for various types and strengths of attacks to show its performance. It also shows that this method has high practicality as it operates independently of the resolution of the host DH and WM data.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1235-1249
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• 2022

This study applied the web crawling technique for extracting big data news on water quality accidents in the water supply system and presented the algorithm in a procedural way to obtain accurate water quality accident news. In addition, in the case of a large-scale water quality accident, development patterns such as accident recognition, accident spread, accident response, and accident resolution appear according to the occurrence of an accident. That is, the analysis of the development of water quality accidents through key keywords and sentiment analysis for each stage was carried out in detail based on case studies, and the meanings were analyzed and derived. The proposed methodology was applied to the larval accident period of Incheon Metropolitan City in 2020 and analyzed. As a result, in a situation where the disclosure of information that directly affects consumers, such as water quality accidents, is restricted, the tone of news articles and media reports about water quality accidents with long-term damage in the event of an accident and the degree of consumer pride clearly change over time. could check This suggests the need to prepare consumer-centered policies to increase consumer positivity, although rapid restoration of facilities is very important for the development of water quality accidents from the supplier's point of view.

• Korean Journal of Animal Reproduction
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• v.24 no.2
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• pp.155-161
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• 2000

The morphological changes on nuclear phase of the germinal vesicle of porcine follicular oocytes during in vitro culture were examined. The high rates (75~77%) of the oocytes collected from follicles of 1~2mm or 6~100mm in diameter were at the GV-I to GV-II stages. When oocytes with or without cumulus cells after collection from follicles of 2~6mm in diameter were cultured for 5 h, the rates of oocytes at GV-IV to GV-Ⅵ stages were higher in oocytes with (52%) than in oocytes without (30%) cumulus cells. After 1 h of oocyte culture, there was no differences in the distribution of GV-IV to GV - Ⅵ stages in the media with or without catalase, xanthine and catalase＋xanthine. After 5 h of culture, however, the distribution of GV-IV to GV-Ⅵ stages were 46, 69, 69 and 70% for medium with none, catalase, xanthine and catalase＋xanthine. The highest rate of GVBD was also observed in the medium with catalase＋xanthine (6%). These results indicate that exposure of porcine follicular oocytes to catalase＋xanthine excels maturation to GV stage and enhances oocyte nuclear maturation.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.593-601
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• 2017

In this paper, we constructed the model of production/investment, distribution, and screening by using variables that can be considered at each stage according to the value chain stage of the movie industry. To increase the predictive power of the model, a regression analysis was used to derive meaningful variables. Based on the given variables, we compared the difference in predictive power between the artificial neural network, which is a machine learning analysis method, and the decision tree analysis method. As a result, the accuracy of artificial neural network was higher than that of decision trees when all variables were added in production/ investment model and distribution model. However, decision trees were more accurate when selected variables were applied according to regression analysis results. In the screening model, the accuracy of the artificial neural network was higher than the accuracy of the decision tree regardless of whether the regression analysis result was reflected or not. This paper has an implication which we tried to improve the performance of movie prediction model by using machine learning analysis. In addition, we tried to overcome a limitation of linear approach by reflecting the results of regression analysis to ANN and decision tree model.