• Korean Journal of Agricultural Science
• /
• v.38 no.2
• /
• pp.219-225
• /
• 2011

Changes in biota, species distribution range shift and catastrophic climate influence due to recent global warming have been observed during the last century. Since global warming affects various sectors, such as agriculture and vegetation, it is important to predict more accurate impact of future climate change. The purpose of this study is to examine the observed distribution of Abeliophyllum distichum in the Korean peninsula. For this purpose, two period (present and future) climate data were used. Mean data between 1950 and 2000, were used as the present value and the year 2050 and 2080 data from A1B senario in IPCC SRES were used for the future value. Potential habitation is analyzed by MaxEnt(Maximum Entropy model), and Abeliophyllum distichum's coordinates data were used as a dependent variable and independent variables are composed of environmental data such as BioClim, altitude, aspect and slope. The result of six types GCM mean calculation, the potential habitability decreased by 40-60% of the average existing distribution. The methodogies and results of this research can be applicable to the climate changing adaptation stratiegies for the biodiversity conservation.

• Health Policy and Management
• /
• v.23 no.1
• /
• pp.78-89
• /
• 2013

This study empirically analyze efficiency and productivity changes of public hospitals of Korea using data envelopment analysis/Window model and global Malmquist indices model. We use the ten-year data from 2001 to 2010 of 30 regional public hospitals listed database from the Association of Korean Regional Public Hospitals. The main focuses are to reveal whether the technical inefficiency are improved as time goes by, and efficiency and productivity are affected by environmental factors. The results can be summarized as follows. First, the efficiencies of public hospitals rise in trend as time passes. Second, regional public hospitals show the different average efficiencies according to their regional type, hospital type, operational type, medicaid type, and demand and supply conditions by Mann-Whitney U-tests. Third, technical efficiency changes mainly contribute to 4.4% annual average growth rate of productivity of regional public hospitals during that period. Our findings have some policy implications. It is confirmed that there exist some environmental inefficiencies, and those inefficiencies can not be overcome through just improving the inner management system. Thus, policy and institutional changes are necessary for regional public hospitals to improve efficiency and productivity overall.

• Journal of Korean Society for Atmospheric Environment
• /
• v.22 no.6
• /
• pp.940-953
• /
• 2006

The major source of carbon monoxide (CO) at the Earth's surface is the incomplete combustion of biomass and fossil fuels. Because the global lifetime of CO is about two months, it can be used as a tracer for pollution from anthropogenic activities and biomass hurtling. In this paper, we introduced the principle and algorithm of the Measurement of Pollution in the Troposphere (MOPITT) instrument for global CO monitoring. The MOPITT instrument, which was launched on the Satellite Terra in 1999, measures CO column and mixing ratio based on gas correlation radiometry. CO levels can be determined by a retrieval algorithm based on the maximum likelihood method minimizing the difference between observed and modeled radiances. MOPITT level 2 data (HDF format) can be downloaded through the Earth Observing System (EOS) data gateway of NASA. ASCII files of CO parameters can be extracted from HDF files, and then temporal and spatial distributions can be obtained. Finally, we showed an example of CO monitoring in April 2000. The locations of forest fires and distribution of MOPITT CO clearly indicated that not only anthropogenic emissions but also forest fires play an important role in CO levels and global CO distribution. Our introduction to MOPITT and the example of MOPITT data interpretation would be helpful for scientists who want to use the EOS data.

• Atmosphere
• /
• v.29 no.2
• /
• pp.219-226
• /
• 2019

Generally, the weather forecast system has been run using prescribed ocean condition. As it is widely known that coupling between atmosphere and ocean process produces consistent initial condition at all-time scales to improve forecast skill, there are many trials on the application of data assimilation of coupled model. In this study, we implemented a weakly coupled data assimilation (short for WCDA) system in global NWP model with low horizontal resolution for coupled forecast with uncoupled initialization, following WCDA system at the Met Office. The experiment is carried out for a typhoon evolution forecast in 2017. Air-sea exchange process provides SST cooling and gives a substantial impact on tendency of central pressure changes in the decaying phase of the typhoon, except the underestimated central pressure. Coupled data assimilation is a challenging new area, requiring further work, but it would offer the potential for improving air-sea feedback process on NWP timescales and finally contributing forecast accuracy.

• International Journal of Computer Science & Network Security
• /
• v.22 no.9
• /
• pp.403-413
• /
• 2022

Classification and analysis are improved factors for the realtime automation system. In the field of agriculture, the cultivation of different paddy crop depends on the atmosphere and the soil nature. We need to analyze the moisture level in the area to predict the type of paddy that can be cultivated. For this process, Ensemble Modulation Pattern system and Block Probability Neural Network based classification models are used to analyze the moisture and temperature of land area. The dataset consists of the collections of moisture and temperature at various data samples for a land. The Ensemble Modulation Pattern based feature analysis method, the extract of the moisture and temperature in various day patterns are analyzed and framed as the pattern for given dataset. Then from that, an improved neural network architecture based on the block probability analysis are used to classify the data pattern to predict the class of paddy crop according to the features of dataset. From that classification result, the measurement of data represents the type of paddy according to the weather condition and other features. This type of classification model assists where to plant the crop and also prevents the damage to crop due to the excess of water or excess of temperature. The result analysis presents the comparison result of proposed work with the other state-of-art methods of data classification.

• Journal of the Korean earth science society
• /
• v.41 no.6
• /
• pp.599-616
• /
• 2020

Sea-surface temperature (SST) is one of the most important oceanic variables for understanding air-sea interactions, heat flux variations, and oceanic circulation in the global ocean. Extremely low SSTs from 0℃ down to -2℃ should be more important than other normal temperatures because of their notable roles in inducing and regulating global climate and environmental changes. To understand the temporal and spatial variability of such extremely low SSTs in the global ocean, the long-term SST climatology was calculated using the daily SST database of satellites observed for the period from 1982 to 2018. In addition, the locations of regions with extremely low surface temperatures of less than 0℃ and monthly variations of isothermal lines of 0℃ were investigated using World Ocean Atlas (WOA) climatology based on in-situ oceanic measurements. As a result, extremely low temperatures occupied considerable areas in polar regions such as the Arctic Ocean and Antarctic Ocean, and marginal seas at high latitudes. Six earth science textbooks were analyzed to investigate how these extremely low temperatures were visualized. In most textbooks, illustrations of SSTs began not from extremely low temperatures below 0℃ but from a relatively high temperature of 0℃ or higher, which prevented students from understanding of concepts and roles of the low SSTs. As data visualization is one of the key elements of data literacy, illustrations of the textbooks should be improved to ensure that SST data are adequately visualized in the textbooks. This study emphasized that oceanic literacy and data literacy could be cultivated and strengthened simultaneously through visualizations of oceanic big data by using satellite SST data and oceanic in-situ measurements.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.5
• /
• pp.1063-1076
• /
• 2013

The power of modern technology is opening a new era of big data. The size of the datasets affords us the opportunity to answer many open scientific questions but also presents some interesting challenges. High-dimensional data such as microarray are common in big data. In this paper, we give an overview of recent development of multiple testing including global and simultaneous testing and its applications to high-dimensional data.

• Journal of Distribution Science
• /
• v.11 no.12
• /
• pp.25-37
• /
• 2013

Purpose - The structure of retailing has changed as retailers develop markets in response to business environment changes. This study aims to analyze the general situation of retailers in order to predict future global strategy using case studies of overseas expansion strategy and the Metro Group's global strategy. Research design, data, and methodology - The backgrounds to the new retail business model and retailer classification are analyzed as theoretical data. In addition, the key success point of the Metro Group's "cash and carry" strategy is analyzed as is the Metro Group's global CFAR (collaborative planning, forecasting, and replenishment) strategy. Finally, the plan for cooperation and precise forecasting under the Metro Group's supply chain management are analyzed from the promotion environment viewpoint. Related materials analyzed included the 2012 annual report, the Metro Group's web page, and a video interview with the executive in charge of global strategy and the new market development department. Some data were revised to avoid disrupting essential aspects of the case studies. Results - The important finding was that the Metro Group could be a world-class retail company with its successful global expansion strategy. The Metro Group's global strategy's primary goal is to have a leading business position in Eastern and Western Europe. The "cash and carry" strategy is highest priority in its overseas expansion strategy. Moreover, the Metro Group has standardized product planning capacity, which could be applied in various countries with different structural and cultural backgrounds. This is the main reason that the Metro Group could rapidly become successful in the Eastern Europe and Asian markets through its structural overseas expansion strategies. In addition, the Metro Group emphasizes the importance of supply chain management. Conclusions - First, retailers should create additional value through utilizing the domestic market, market power, and economies of scale to launch a global strategy to maximize benefits from diversification. Second, the political, economic, and cultural background of the target country needs to be understood to successfully implement the overseas expansion strategy. Third, the main factor of successful cooperation with a local partner is how quickly the company gains total understanding of the business resources and core competence of its partner. All organizations should focus on the achievement of goals in order to successfully operate the partnership. Fourth, retailers should improve their business, financial and organizational structure. Moreover, the work processes and company culture should also be improved to respond strongly in the competitive global market. Fifth, the essential point of a successful retail business is the control capacity of its branding and format. The retailer could avoid forecasting errors through supply chain management by perfectly distributing the actual amount of its inventory. In addition, the risks along the supply chain are effectively shared between the supply chain partners. Finally, the central tendency of the market is to gain in strength with this taking place across all parts of the business.

• Journal of Computing Science and Engineering
• /
• v.12 no.1
• /
• pp.24-35
• /
• 2018

Deep convolutional neural network (DCNN) is an advanced technology in image recognition. Because of extreme computing resource requirements, DCNN implementation with software alone cannot achieve real-time requirement. Therefore, the need to implement DCNN accelerator hardware is increasing. In this paper, we present a field programmable gate array (FPGA)-based hardware accelerator design of DCNN targeting handwritten Hangul character recognition application. Also, we present design optimization techniques in SDAccel environments for searching the optimal FPGA design space. The techniques we used include memory access optimization and computing unit parallelism, and data conversion. We achieved about 11.19 ms recognition time per character with Xilinx FPGA accelerator. Our design optimization was performed with Xilinx HLS and SDAccel environment targeting Kintex XCKU115 FPGA from Xilinx. Our design outperforms CPU in terms of energy efficiency (the number of samples per unit energy) by 5.88 times, and GPGPU in terms of energy efficiency by 5 times. We expect the research results will be an alternative to GPGPU solution for real-time applications, especially in data centers or server farms where energy consumption is a critical problem.

• Archives of design research
• /
• v.14 no.2
• /
• pp.107-116
• /
• 2001

Nowadays, The market environment is not static, but dynamic, it therefore requires global competition for the competitive advantage of product design in global market across boundaries. So if companies do not thoroughly understand core values, needs of consumers, and do not properly meet them, they cannot get the competitive advantage in global market for consumers. Therefore, the goal of this research is to develop a new design process for global markets through developing the on-line research analysis program and data-base. For this study, the researchers established a research framework associated with values, benefits and design attributes and developed a Global Design Process program through empirical researches. This research program is a upgraded system adapted to the digital period drastically.