• Journal of agriculture & life science
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• v.50 no.2
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• pp.73-82
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• 2016

Best drought tolerance index was determined through statistics analysis and growth appearance of drought tolerant plants was determined by cultivation in pot and sloping land. For determination of best drought tolerant indicators, RD(Resistant dry days), LD(Leaf area), UTR(Unit transpiration), RWC(Relative water content), RWL(Relative water loss), LA(Leaf area), SN(Stoma unmber) and SA(Stoma area) were carried out by correlation and PCA analysis. RWL and UTR were affected on plant drought tolerance according to comparison among six indices for resistant dry days. The PCs axes separated SA, LA, RD and RWC and SN. UTR was negatively correlated with SA, RWL were also negatively correlated with RWC and SN. RWL and UTR were proved best selection indicator for the selection of drought tolerant species. Ulmus parvifolia, Bidens bipinnata, Patrinia villosa, Kummerowia striata, Arundinella hirta, Artemisia gmelini etc. were selected drought tolerant plants. Shoot growth appearance of drought resistant plants was differed pot and sloping land. Shoot growth and leaf number was no significant differences between the pot and sloping land. However, root growth of drought tolerant plants was all the difference between two cultivation. T/R ratio of drought tolerant plants was also found a big difference. T/R ratio of drought tolerant plants in sloping land was lower than that of pot. These results will be served efficiently plant breeding.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Journal of Technology Innovation
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• v.17 no.1
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• pp.1-48
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• 2009

Recently we have found some symptoms that R&D fiscal incentives might not work well what it has intended through the analysis of current statistics of firm's R&D data. Firstly, we found that the growth rate of R&D investment in private sector during the recent decade has been slowdown. The average of growth rate (real value) of R&D investment is 7.1% from 1998 to 2005, while it was 13.9% from 1980 to 1997. Secondly, the relative share of R&D investment of SME has been decreased to 21%('05) from 29%('01), even though the tax credit for SME has been more beneficial than large size firm, Thirdly, The R&D expenditure of large size firms (besides 3 leading firms) has not been increased since late of 1990s. We need to find some evidence whether fiscal incentives are effective in increasing firm's R&D investment. To analyse econometric model we use firm level unbalanced panel data for 4 years (from 2002 to 2005) derived from MOST database compiled from the annual survey, "Report on the Survey of Research and Development in Science and Technology". Also we use fixed effect model (Hausman test results accept fixed effect model with 1% of significant level) and estimate the model for all firms, large firms and SME respectively. We have following results from the analysis of econometric model. For large firm: i ) R&D investment responds elastically (1.20) to sales volume. ii) government R&D subsidy induces R&D investment (0.03) not so effectively. iii) Tax price elasticity is almost unity (-0.99). iv) For large firm tax incentive is more effective than R&D subsidy For SME: i ) Sales volume increase R&D investment of SME (0.043) not so effectively. ii ) government R&D subsidy is crowding out R&D investment of SME not seriously (-0.0079) iii) Tax price elasticity is very inelastic (-0.054) To compare with other studies, Koga(2003) has a similar result of tax price elasticity for Japanese firm (-1.0036), Hall((l992) has a unit tax price elasticity, Bloom et al. (2002) has $-0.354{\sim}-0.124$ in the short run. From the results of our analysis we recommend that government R&D subsidy has to focus on such an areas like basic research and public sector (defense, energy, health etc.) not overlapped private R&D sector. For SME government has to focus on establishing R&D infrastructure. To promote tax incentive policy, we need to strengthen the tax incentive scheme for large size firm's R&D investment. We recommend tax credit for large size film be extended to total volume of R&D investment.

• Journal of Sericultural and Entomological Science
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• v.25 no.1
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• pp.34-43
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• 1983

These studies have been carried out to find better locations for sericultural service regardless of the international silk market fluctuation in Korea. In order to acieve the purpose, various investigations and analyses have been carried out for more than four hundred sericultural communities to find out the main factors which caused to decrease in cocoon production in spite of a gloomy past silk market. Now, we believe that we have set up some fundamental guide lines in developing sound serviceable sericultural communities in Korea in case the government accepts the written advices, and the results obtained are as follows: 1. The Korean sericulture has been very prosperous from the 60's to the 70's. In 1976 the cocoon production was at its peak, reaching 41,704M/T from which its decline took place with annual averages of 18.5% for total cocoon production and 16.4% for mulberry field. These figures represent a quantitative decrease to one-third of the total amount in 1976. Since then, the Korean sericulture had continuously suffered from a shortage of raw silk resulting in a slow development of sericulture. At present, a steady development through all possible measures is great importance. 2. The downfall of the korean sericulture resulted from two factors of such as the external, which led to the decline in the price of raw silk at the international market and restrain of import and, the internal, resulting in the little increase of cocoon price and a comparatively lower benefits from the sericulture than from other cash crops. 3. The already established sericultural zone collapsed and then reorganized with the outstanding regional specialization so the decline in total cocoon production in the country. Based on the agricultural regions, 1980 cocoon production was very stable in the mountaineaus area of the east-south which used with intercropping. In this area there was small decline of 33% compare with that of the 1979, and with 70% decline in the dry field farming area of Kangwon Do. In an administrative districtwise, six counties beginning with Sanchnung county of Kyungsang Nam Do, showed less than 20% decline of cocoon production, sixteen counties beginning with Samchuck county of Kangwon Do marked above 80% decrease of cocoon production. In the smaller unit area-wise, there was a big difference among them. twenty-five myons rather increased and a hundrd fourty-three myons decreased above 80% of it. 4. The cocoon production was positively correlated with the decreasing percentage of cocoon production per household. It was also affected by the ratio of the mulberry field area to the total cultivated area per household and cocoon productivity per 10a. 5. Four hundred sixty-four villages in the seventeen counties were surveyed on the basis of farm management and techniques concerned ('80/'79), and then the results were evaluated by using of computer. These results are summarized as foolows: (1) Cocoon production per household There was no difference among the agricultural regions in cocoon production. The cocoon production per household in the comparatively stable villages increased from 100.8kg in 1979 to 122kg in 1981. Cocoon yield in the stable villages decreased by 20% of '81/'79. The cocoon production per house hold in while that of the unstable villages decreased by more than 40% from 102.9kg in 1979 to 82kg in 1981. (2) Cocoon yield per 10a mulberry field The cocoon yield per 10a was higher in the plain area than in the mountaineous area. The stable villages had an average of 73.4kg cocoon yield/10a while the unstabe ones had only an average of 55kg. (3) Adoption the mulberry branch rearing method The branch rearing method was more popular in the plain area than in the mountainous area. In the stable vilages adopted 24.2% in spring and 16.7% in autumn of 1979. In 1981 it shwed increases of 34.3% and 10.1% in the two seasons respectivly. However, the unstable villages showed 13.3% and 126% in both seasons, respectively. (4) The patterns of the combined management system in the sericultural farming The popular management system in the sericultural from was combined with rice and other cash crops, showing 55% of the total households surveyed. Fourteen percent of the households combined the management system with rice and other cash crops and 14% of the households combined with rice only. The villages wich earned less than 20% of the total income from the sericulture reached 81% of the total houscholds indicating that they were still far beyond a complete combination system. (5) Damage by agricultural chemicals The damage caused by agricultural chemicals was mainly due to the protection of rice against insectpests and diseases in the plain areas and took place mostly in the autumn season. The chemicals applied was 65% of Iiquid and 35% of powder forms and 35% of damage was from granulat form of the chemicals. The use of the granular chemicals was low because of high cost.