• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.14-17
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• 2005

Global latent heat flux data sets are crucial for many studies such as those related to air-sea interaction and climate variation. Currently, various global latent heat flux data sets are constructed using satellite data. Japanese Ocean Flux data sets with Use of Remote sensing Observations (J-OFURO) includes one of the satellite-derived global latent heat flux data (Kubota et aI., 2000). In this study, we review future development of J-OFURO global latent heat flux data set. In particular, we investigate usage of multi-satellite data for estimating accurate global latent heat flux. Accurate estimation of surface wind speeds over the global ocean is one of key factors for the improved estimation of global latent heat flux. First, we demonstrate improvement of daily wind speed estimation using multi-satellites data from microwave radiometers and scatterometers such as DMSP/SSMI, ERS/AMI, QuikSCAT/SeaWinds, AqualAMSR-E, ADEOS2/AMSR etc. Next, we demonstrate improvement of global latent heat flux estimation using the wind speed data derived from multi-satellite data.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.413-422
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• 2012

In this study, we developed the severity-adjusted length of stay (LOS) model for acute myocardial infarction patients using data from the hospital discharge survey and proposed management of medical quality and development of policy. The dataset was taken from 2,309 database of the hospital discharge survey from 2004 to 2006. The severity-adjusted LOS model for the acute myocardial infarction (AMI) patients was developed by data mining analysis. From decision making tree model, the main reasons for LOS of AMI patients were CABG and comorbidity. The difference between severity-adjusted LOS from the ensemble model and real LOS was compared and it was confirmed that insurance type and location of hospital were statistically associated with LOS. And to conclude, hospitals should develop the severity-adjusted LOS model for frequent diseases to manage LOS variations efficiently and apply it into the medical information system.

• Journal of Chest Surgery
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• v.39 no.7 s.264
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• pp.534-543
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• 2006

Background: There are a lot of debates regarding the optimal timing of operation of acute myocardial infarction (AMI). Off pump coronary artery bypass grafting (OPCAB) has benefits by avoiding the adverse effects of the cardio-pulmonary bypass, but its efficacy in AMI has not been confirmed yet. The purpose of this study is to evaluate retrospectively early and mid-term results of OPCAB in patients with AMI according to transmurality and timing of operation. Material and Method: Data were collected in 126 AMI patients who underwent OPCAB between January 2002 and July 2005, Mean age of patients were 61.2 years. Male was 92 (73.0%) and female was 34 (27.2%). 106 patients (85.7%) had 3 vessel coronary artery disease or left main disease. Urgent or emergent operations were performed in 25 patients (19.8%). 72 patients (57.1%) had non-transmural myocardial infarction (group 1) and 52 patients (42.9%) had transmural myocardial infarction (group 2). The incidence of cardiogenic shock and insertion of intra-aortic balloon pump (IABP) was higher in group 2. The time between occurrence of AMI and operation was divided in 4 subgroups (<1 day, $1{\sim}3\;days,\;4{\sim}7\;days$, >8 days). OPCAB was performed a mean of $5.3{\pm}7.1$ days after AMI in total, which was $4.2{\pm}5.9$ days in group 1, and $6,6{\pm}8.3$ days in group 2. Result: Mean distal an-astomoses were 3.21 and postoperative IABP was inserted in 3 patients. There was 1 perioperative death in group 1 due to low cardiac output syndrome, but no perioperative new MI occurred in this study. There was no difference in postoperative major complication between two groups and according to the timing of operation. Mean follow-up time was 21.3 months ($4{\sim}42$ months). The 42 months actuarial survival rate was $94.9{\pm}2.4%$, which was $91.4{\pm}4.7%$ in group 1 and $98.0{\pm}2.0%$ in group 2 (p=0.26). The 42 months freedom rate from cardiac death was $97.6{\pm}1.4%$ which was $97.0{\pm}2.0%$ in group 1 and $98.0{\pm}2.0%$ in group 2 (p=0.74). The 42 months freedom rate from cardiac event was $95.4{\pm}2.0%$ which was $94.8{\pm}2.9%$ in group 1 and $95.9{\pm}2.9%$ in group 2 (p=0.89). Conclusion: OPCAB in AMI not only reduces morbidity but also favors hospital outcomes irrespective of timing of operation. The transmurality of myocardial infarction did not affect the surgical and midterm outcomes of OPCAB. Therefore, there may be no need to delay the surgical off-pump revascularization of the patients with AMI if surgical revascularization is indicated.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.851-858
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• 2021

Due to the increase in renewable energy and distributed resources, not only traditional data but also various energy-related data are being generated in the new energy industry. In other words, there are various renewable energy facilities and power generation data, system operation data, metering and rate-related data, as well as weather and energy efficiency data necessary for new services and analysis. Energy big data processing technology can systematically analyze and diagnose data generated in the first half of the power production and consumption infrastructure, including distributed resources, systems, and AMI. Through this, it will be a technology that supports the creation of new businesses in convergence between the ICT industry and the energy industry. To this end, research on the data analysis system, such as itemized characteristic analysis of the collected data, correlation sampling, categorization of each feature, and element definition, is needed. In addition, research on data purification technology for data loss and abnormal state processing should be conducted. In addition, it is necessary to develop and structure NIFI, Spark, and HDFS systems so that energy data can be stored and managed in real time. In this study, the overall energy data processing technology and system for various power transactions as described above were proposed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2672-2679
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• 2012

The study was done to provide basic data of medical quality evaluation after developing the comorbidity disease mortality measurement modeled on the severity-adjustment method of AMI. This study analyzed 699,701 cases of Hospital Discharge Injury Data of 2005 and 2008, provided by the Korea Centers for Disease Control and Prevention. We used logistic regression to compare the risk-adjustment model of the Charlson Comorbidity Index with the predictability and compatibility of our severity score model that is newly developed for calibration. The models severity method included age, sex, hospitalization path, PCI presence, CABG, and 12 variables of the comorbidity disease. Predictability of the newly developed severity models, which has statistical C level of 0.796(95%CI=0.771-0.821) is higher than Charlson Comorbidity Index. This proves that there are differences of mortality, prevalence rate by method of mortality model calibration. In the future, this study outcome should be utilized more to achieve an improvement of medical quality evaluation, and also models will be developed that are considered for clinical significance and statistical compatibility.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.4
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• pp.43-51
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• 2010

In this paper, we studied line coding technology tendency for high speed data communication at LED-ID (Identification) communication system in indoor environment. A LED-ID technology is a communication using visible ray (RGB) that come out in LED device. It is energy curtailment effect and possible in ubiquitous network service applications. The LED-ID system has the above advantages about that the communication throughout the whole room is enabled by high power lighting and lighting equipment with white colored LED which are easy to install and have good outward appearance. Therefore, the transmission by light waves is more suitable for wireless networks than by radio waves. We compared with the NRZ, AMI, 4B5B, HDB3, 8B10B line coding for efficient in error detection and serves data transmission of high speed.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.346-358
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• 2018

Objectives: The association between obstructive sleep apnea (OSA) and mortality or serious cardiovascular events over a long period of time is not clearly understood. The aim of this observational study was to estimate the clinical effectiveness of continuous positive airway pressure (CPAP) treatment on an outcome variable combining mortality, acute myocardial infarction (AMI), and cerebrovascular insult (CVI) during a follow-up period of 15.5 years ($186{\pm}58$ months). Methods: The data set consisted of 978 patients with an apnea-hypopnea index (AHI) ${\geq}5.0$. One-third had used CPAP treatment. For the first time, a data-driven causal Bayesian network (DDBN) and a hypothesis-driven causal Bayesian network (HDBN) were used to investigate the effectiveness of CPAP. Results: In the DDBN, coronary heart disease (CHD), congestive heart failure (CHF), and diuretic use were directly associated with the outcome variable. Sleep apnea parameters and CPAP treatment had no direct association with the outcome variable. In the HDBN, CPAP treatment showed an average improvement of 5.3 percentage points in the outcome. The greatest improvement was seen in patients aged ${\leq}55$ years. The effect of CPAP treatment was weaker in older patients (>55 years) and in patients with CHD. In CHF patients, CPAP treatment was associated with an increased risk of mortality, AMI, or CVI. Conclusions: The effectiveness of CPAP is modest in younger patients. Long-term effectiveness is limited in older patients and in patients with heart disease (CHD or CHF).

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.179-188
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• 2022

Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.225-230
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• 1998

The purpose of this study is to contribute the development of an El Nino prediction model. The objectives of the study are to (1) extract sea surface height data from the TOPEI/Poseidon altimeter, and (2) compare the relations among the sea surface height, sea surface temperature and wind field. NOAA AVHRR Multi-channel data is used for sea surface temperature and wind data is derived from ERS 1, 2 AMI wind scatterometer. The results showed that sea surface height has increased significantly during the El Nino season. The sea surface height is positively related to sea surface temperature and negatively related to zonal wind.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.2
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• pp.85-91
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• 2015

With the increasing popularity of Smart Grid infrastructure, it is much easier to collect energy usage data using AMI (Advanced Measuring Instrument) from residential housing, buildings and factories. Several researches have been done to improve an energy efficiency by analyzing the collected energy usage data. However, it is not easy to store and analyze the energy data using a traditional relational database management system since the data size grows exponentially with an increasing popularity of Smart grid infrastructure. In this paper, we are proposing a Hadoop based Big data system to store and analyze energy usage data. Based on our limited experiments, Hadoop based energy data analysis is three times faster than that of a relational database management system based approach with the current system.