• Atmosphere
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• v.24 no.3
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• pp.433-444
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• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.884-888
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• 2003

In this paper, we introduce the hybrid data mining mechanism based in association rule and fuzzy neural networks (FNN). Most of data mining mechanisms are depended in the association rule extraction algorithm. However, the basic association rule-based data mining has not the learning ability. In addition, sequential patterns of association rules could not represent the complicate fuzzy logic. To resolve these problems, we suggest the hybrid mechanism using association rule-based data mining, and fuzzy neural networks. Our hybrid data mining mechanism was consisted of four phases. First, we used general association rule mining mechanism to develop the initial rule-base. Then, in the second phase, we used the fuzzy neural networks to learn the past historical patterns embedded in the database. Third, fuzzy rule extraction algorithm was used to extract the implicit knowledge from the FNN. Fourth, we combine the association knowledge base and fuzzy rules. Our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.141-148
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• 2021

Project management is a current trend of management in the public sphere, based on different principles, methods and tools. The tools include information technologies providing control over time, cost, quality and planning process in order to ensure accountability to interested parties. The goal of the research was to examine the impact of the integration of information systems in project management of the public sphere on the quality of public governance and administration using the example of infrastructure projects involving the private sector in developing countries. The methodology of the research is based on the concepts of "digital-era governance" (DEG), "Information governance" and "project governance" to determine the effectiveness of information systems and technologies in the management of infrastructure projects in the public sphere. The data from the countries with Lower middle income (India, Indonesia, Philippines, Ukraine, Vietnam) and Upper middle income (Argentina, Brazil, China, Colombia, Mexico, Peru, Romania, Russian Federation, Thailand, Turkey) for 1996-2020 were used to study the effects of DEG. The results show two main trends in the countries with Lower middle income and Upper middle income. The first trend is the development of digital governance, the concept of "digital-era governance" through information systems and performance measurement of the governance system, forecasting of investment flows of infrastructure projects, measurement of payback and effectiveness parameters for investment management in the public sector, decision support. The second trend is the existence of systemic challenges related to corruption, social and institutional factors through the development of democracy in developing countries and the integration of NPM similar to developed countries. The confidence of interested parties, especially private investors, in public authorities is determined by other factors - the level of return on investment, risks and assignment of responsibility, probability of successful completion of the project. These data still remain limited for a wide range of project participants, including citizens.

• Journal of Korean Academy of Nursing Administration
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• v.19 no.2
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• pp.292-303
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• 2013

Purpose: The purpose of this study was to explore nurses' experience of evidence-based nursing practice in general hospitals. Methods: Data were collected from 13 nurses through in-depth interviews about their experiences with evidence-based practice. The research questions were "What kind of evidence are you using in your practice?" and "What are the barriers to and enablers of evidence-based practice that you have experienced?" Qualitative data from field and transcribed notes were analyzed using qualitative content analysis methodology. Results: Major themes of using evidence were identified as 'research as primary valid evidence', 'information from local context and internet as realistic evidence', and 'clinical experience as pragmatic evidence'. Patient experience was not used as evidence in solving nursing problems. Barriers to and enablers of evidence-based practice were linked. They included both external, organizational factors and individual factors. Main issues were 'lack of evidence and poor work environment', and major facilitating factors were 'improving knowledge and skills related to evidence-based practice' and 'communicating and sharing evidence'. Conclusion: The study findings provide useful information for understanding nurses' experience of using external and internal evidence along with their meaning. A multidimensional approach is needed to overcome barriers to and implement evidence-based practice.

• Atmosphere
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• v.31 no.3
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• pp.311-326
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• 2021

To improve the predictability of high-impact weather phenomena around Seoul, where a larger number of people are densely populated, KMA conducted the intensive observation from 22 June to 20 September in 2020 over the Seoul area. During the intensive observation period (IOP), the dropsonde from NIMS Atmospheric Research Aircraft (NARA) and the radiosonde from KMA research vessel Gisang1 were observed in the Yellow Sea, while, in the land, the radiosonde observation data were collected from Icheon and Incheon. Therefore, in this study, the effects of radiosonde and dropsonde data during the IOP were investigated by Observing System Experiment (OSE) based on Korean Integrated Model (KIM). We conducted two experiments: CTL assimilated the operational fifteen kinds of observations, and EXP assimilated not only operational observation data but also intensive observation data. Verifications over the Korean Peninsula area of two experiments were performed against analysis and observation data. The results showed that the predictability of short-range forecast (1~2 day) was improved for geopotential height at middle level and temperature at lower level. In three precipitation cases, EXP improved the distribution of precipitation against CTL. In typhoon cases, the predictability of EXP for typhoon track was better than CTL, although both experiments simulated weaker intensity as compared with the observed data.

• Korean Management Science Review
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• v.14 no.1
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• pp.87-105
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• 1997

There have been lots of research on temporal data management for the past two decades. Most of them are based on some logical data model, especially on the relational data model, although there are some conceptual data models which are independent of logical data models. Also, many properties or issues regarding temporal data models and temporal query languages have been studied. But some of them were shown to be incompatible, which means there could not be a complete temporal data model, satisfying all the desired properties at the same time. Many modeling issues discussed in the papers, do not have to be done so, if they take object-oriented data model as a base model. Therefore, this paper proposes a temporal data model, which is based on the object-oriented data model, mainly discussing the most essential issues that are common to many temporal data models. Our new temporal data model and query language will be illustrated with a small database, created by a set of sample transaction.

• Food Science and Biotechnology
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• v.27 no.6
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• pp.1865-1869
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• 2018

This study examined the effects of alfalfa seed germination on growth of Salmonella enterica. We investigated the population changes of S. enterica during early sprout development. We found that the population density of S. enterica, which was inoculated on alfalfa seeds was increased during sprout development under all experimental temperatures, whereas a significant reduction was observed when S. enterica was inoculated on fully germinated sprouts. To establish a model for predicting S. enterica growth during alfalfa sprout development, the kinetic growth data under isothermal conditions were collected and evaluated based on Baranyi model as a primary model for growth data. To elucidate the influence of temperature on S. enterica growth rates, three secondary models were compared and found that the Arrhenius-type model was more suitable than others. We believe that our model can be utilized to predict S. enterica behavior in alfalfa sprout and to conduct microbial risk assessments.

• Mycobiology
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• v.49 no.1
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• pp.61-68
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• 2021

Agaricus bisporus, commonly known as the button mushroom, is widely cultivated throughout the world. To breed new strains with more desirable traits and improved adaptability, diverse germplasm, including wild accessions, is a valuable genetic resource. To better understand the genetic diversity available in A. bisporus and identify previously unknown diversity within accessions, a phylogenetic analysis of 360 Agaricus spp. accessions using single-nucleotide polymorphism genotyping was performed. Genetic relationships were compared using principal coordinate analysis (PCoA) among accessions with known origins and accessions with limited collection data. The accessions clustered into four groups based on the PCoA with regard to genetic relationships. A subset of 67 strains, which comprised a core collection where repetitive and uninformative accessions were not included, clustered into 7 groups following analysis. Two of the 170 accessions with limited collection data were identified as wild germplasm. The core collection allowed for the accurate analysis of A. bisporus genetic relationships, and accessions with an unknown pedigree were effectively grouped, allowing for origin identification, by PCoA analysis in this study.

• Atmosphere
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• v.30 no.4
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• pp.319-333
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• 2020

Aircraft observations constitute one of the major sources of temperature observations which provide three-dimensional information. But it is well known that the aircraft temperature data have warm bias against sonde observation data, and therefore, the correction of aircraft temperature bias is important to improve the model performance. In this study, the algorithm of the bias correction modified from operational KMA (Korea Meteorological Administration) global model is adopted in the preprocessing of aircraft observations, and the effect of the bias correction of aircraft temperature is investigated by conducting the two experiments. The assimilation with the bias correction showed better consistency in the analysis-forecast cycle in terms of the differences between observations (radiosonde and GPSRO (Global Positioning System Radio Occultation)) and 6h forecast. This resulted in an improved forecasting skill level of the mid-level temperature and geopotential height in terms of the root-mean-square error. It was noted that the benefits of the correction of aircraft temperature bias was the upper-level temperature in the midlatitudes, and this affected various parameters (winds, geopotential height) via the model dynamics.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.317-323
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• 2009

Recently not even government polices but small town decisions are based on the survey data/information, so the most of government agencies/organizations demand various sample surveys in each fields for more detail information. However in conducting the sample survey, nonresponse problem rises very often and it becomes a major issue on judging the accuracy of survey. For that matters, one solution ran be using the administration data. However unfortunately most of administration data are restricted to the common users. The other solution can be the imputation. Therefore several method, of imputation are studied in various fields. In this study, in stead of the simple regression imputation method which is commonly used, factor score regression method is applied specially to the incomplete data which have the unit and item misting values in survey data. Here for simulation study, Consumer Expenditure Surveys in Korea are used.