• Korean Journal of Remote Sensing
• /
• v.38 no.2
• /
• pp.179-188
• /
• 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 TCI and VCI require historical reference values for the LST and NDVI for each date and location.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GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.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
• /
• 1998.09a
• /
• pp.225-230
• /
• 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
• /
• v.64 no.2
• /
• pp.85-91
• /
• 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.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.10 no.1
• /
• pp.39-46
• /
• 2015

The paper studied possibility of improvement of efficient of data processing in the line coder when Hangul syllables in Unicode system is used for the source code. The scrambling in the line coder is to solve the problem happened due to the source code. The study is based on the HDB-3 scrambling method in ITU-T standards that is applied to AMI line coder. The referred data of Hangul syllables and its use frequency which are required to analysis was used the data extracted from the source data of the National Korean Language Institute. According to the analysis, the average 24% scrambling was generated in source code of Hangul syllables in Unicode system. When the referred Hangul syllables was applied to Unicode system, the average 27% scrambling was producted. Total 8,924ea Hangul syllables in 11,172ea Hangul syllables in Unicode system were not scrambled. Therefore the referred Hangul syllables 1,540ea were accepted in the unscrambled code areas. As a result, the existing Unicode Hangul syllable codes can't prevent the scrambling, but it is possible to completely remove the 27% scrambling with new source coding system. And then, it can be improved the data processing efficient upto minimum 27% in line coder by software in presentation layer instead of physical layer.

• International journal of advanced smart convergence
• /
• v.8 no.2
• /
• pp.218-226
• /
• 2019

The use of Information and Communication Technologies (ICT) is the key to operate a change from the traditional manual reading of water meters and sensors to an automated system where high frequency data is remotely collected and analyzed in real time, one of the main components of a Smart Water Grid. The recent boom of ICT offers a wide range of both wired and wireless technologies to achieve this objective. We review and present in this article the most widely recognized technologies and protocols along with their respective advantages, drawbacks and applicability range which can be Home Area Network (HAN), Building Area Network (BAN) or Local/Neighborhood Area Network (LAN/NAN). We also present our findings and we give recommendations on the application of ICT in Smart Water Grids and future work needed.

• KEPCO Journal on Electric Power and Energy
• /
• v.6 no.4
• /
• pp.399-404
• /
• 2020

There are many attempts to apply AI technology to diagnose facilities or improve the work efficiency of the power industry. The emergence of new machine learning technologies, such as deep learning, is accelerating the digital transformation of the power sector. The problem is that traditional power systems face security risks when adopting state-of-the-art AI systems. This adoption has convergence characteristics and reveals new cybersecurity threats and vulnerabilities to the power system. This paper deals with the security measures and implementations of the power system using machine learning. Through building a commercial facility operations forecasting system using machine learning technology utilizing power big data, this paper identifies and addresses security vulnerabilities that must compensated to protect customer information and power system safety. Furthermore, it provides security guidelines by generalizing security measures to be considered when applying AI.

• Health Policy and Management
• /
• v.30 no.3
• /
• pp.418-429
• /
• 2020

Background: This study aims to analyze the cost and the length of stay (LOS) of acute myocardial infarction (AMI) patients with coronary artery stenting according to the characteristics of individuals and institutions. Methods: The data was collected from Korean National Health Insurance Service's customized database in 2010 and 2015. Chi-square test, t-test, analysis of variance, and multilevel analysis were performed. Results: The intraclass correlation coefficients for cost were 7.02% in 2010, 5.61% in 2015 and for LOS were 3.17%, 1.40%, respectively. The average costs were 9,067,000 won in 2010 and 9,889,000 won in 2015 (p<0.0001). However, the cost in 2015 was lower than the cost applying increased fee. The costs increased in aged 50-59 years, 60-69 years, and aged ≥70 years versus in aged under 49 years. The cost was higher in Charlson comorbidity index (CCI) 3 to 4 and ≥5 than in CCI 0. The costs were lower in male, medical aid recipients, metropolises, and local hospitals in other regions in 2010. LOS decreased from 8.1 days in 2010 to 7.4 days in 2015. It decreased in male, high income group, and the group of admission via emergency room. However, it increased in higher ages and medical aid recipients, and it also increased when CCI rose. The Internal Herfindahl Index was related to LOS in 2010. Conclusion: The variation of hospital level was small compared to the patient level. Therefore, it is important to implement applicable policies at the patient level in order to reduce cost and LOS of AMI patients.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.10
• /
• pp.145-154
• /
• 2012

Recently, the cardiovascular disease has increased by causes such as westernization dietary life, smoking, and obesity. In particular, the acute myocardial infarction (AMI) occupies 50% death rate in cardiovascular disease. Following this trend, the AMI has been carried out a research for discovery of risk factors based on national data. However, there is a lack of diagnosis minor suitable for Korean. The objective of this paper is to develop a classifier for short-term relapse mortality prediction of cardiovascular disease patient based on prognosis data which is supported by KAMIR(Korea Acute Myocardial Infarction). Through this study, we came to a conclusion that ANN is the most suitable method for predicting the short-term relapse mortality of patients who have ST-segment elevation myocardial infarction. Also, data set obtained by logistic regression analysis performed highly efficient performance than existing data set. So, it is expect to contribute to prognosis estimation through proper classification of high-risk patients.

• KEPCO Journal on Electric Power and Energy
• /
• v.2 no.1
• /
• pp.61-69
• /
• 2016

Understanding load patterns and customer classification is a basic step in analyzing the behavior of electricity consumers. To achieve that, there have been many researches about clustering customers' daily load data. Nowadays, the deployment of advanced metering infrastructure (AMI) and big-data technologies make it easier to study customers' load data. In this paper, we study load clustering from the view point of yearly and daily load pattern. We compare four clustering methods; K-means clustering, hierarchical clustering (average & Ward's method) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise). We also discuss the relationship between clustering results and Korean Standard Industrial Classification that is one of possible labels for customers' load data. We find that hierarchical clustering with Ward's method is suitable for clustering load data and KSIC can be well characterized by daily load pattern, but not quite well by yearly load pattern.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.4
• /
• pp.1493-1515
• /
• 2015

A smart meter is one of the core components in Advanced Metering Infrastructure (AMI) that is responsible for providing effective control and monitor of electrical energy consumptions. The multifunction tasks that a smart meter carries out such as facilitating two-way communication between utility providers and consumers, managing metering data, delivering anomalies reports, analyzing fault and power quality, simply show that there are huge amount of data exchange in smart metering networks (SMNs). These data are prone to security threats due to high dependability of SMNs on Internet-based communication, which is highly insecure. Therefore, there is a need to identify all possible security threats over this network and propose suitable countermeasures for securing the communication between smart meters and utility provider office. This paper studies the architecture of the smart grid communication networks, focuses on smart metering networks and discusses how such networks can be vulnerable to security attacks. This paper also presents current mechanisms that have been used to secure the smart metering networks from specific type of attacks in SMNs. Moreover, we highlight several open issues related to the security and privacy of SMNs which we anticipate could serve as baseline for future research directions.