• Journal of The Korean Society of Grassland and Forage Science
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• v.12 no.3
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• pp.3-12
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• 1992

Forage grasses and legumes ar$\varepsilon$ the mam component of livestock diets in Canada. There are over 30 million ha of grassland in Canada and there is a large, undeveloped land base in fringe areas suitable for forage production. The short growing s season limits the grassland farming to the southern p parts of Canada. The win!er season is long and in most parts of Canada cold temperatures, fr$\varepsilon$ezmg, and thawing, and diseases exert sever$\varepsilon$ stress on overwintering forage plants. The development of persistent cultivars is essential for sustained production particularly in the fringe areas with short growmg s$\varepsilon$ason. The seasonality of dry matter production is a result of high growth rates in early summ$\varepsilon$r and low dry matter accumulation in late summer and fall. Innovative management practIces a and cultivars with improved regrowth capacity are n necessary to overcome such skewed production pattern and to extend effiectlVe grazmg season l Improved pasture production is an important part of reducing costs in livestock operations and remaining competitive. It is suggested that applying available technology would increase pasture productivity and reduce d$\varepsilon$pendence on stored feeds thus improving profitability of small producers in particeular. Reducing nutrient losses during harv$\varepsilon$stmg, s storage, and feeding is essential for improved production efficiency during confinement. The devclopment of low cost and labor saving methods of ensiling is critical for improved efficiency and profitability of forage based enterprises Livestock industries must respond to consumer preferences for low fat and cholesterol foods. Research and development of entire production systems is emphasized for dev$\varepsilon$loping viabl$\varepsilon$ enterprises. It is increasingly difficult to secure resources for r$\varepsilon$search, education, and extension, and alliane$\varepsilon$s and cooperation must expand among organizations with interests in forage based livestock systems.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.45-67
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• 2017

According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.