• Journal of Korea Water Resources Association
• /
• v.54 no.9
• /
• pp.705-718
• /
• 2021

Climate change has a significant impact on vegetation growth and terrestrial ecosystems. In this study, the possibility of ecological drought was investigated using satellite remote sensing data. First, the Vegetation Health Index was estimated from the Normalized Difference Vegetation Index and Land Surface Temperature provided by MODIS. Then, a joint probability model was constructed to estimate the possibility of vegetation-related drought in various precipitation/evaporation scenarios in forest areas around 60 major ASOS sites of the Meteorological Administration located throughout Korea. The results of this study show the risk pattern of drought related to forest vegetation under conditions of low atmospheric moisture supply or high atmospheric moisture demand. It also identifies the sensitivity of drought risks associated with forest vegetation under various meterological drought conditions. These findings provide insights for decision makers to assess drought risk and develop drought mitigation strategies related to forest vegetation in a warming era.

• Journal of Ocean Engineering and Technology
• /
• v.33 no.5
• /
• pp.435-446
• /
• 2019

Because offshore structures are affected by various environmental loads, the risk of damage is high. As a result of ever-changing ocean environmental loads, damage to offshore structures is expected to differ from year to year. However, in previous studies, it was assumed that a relatively short period of load acts repeatedly during the design life of a structure. In this study, the residual life of an offshore wind turbine support structure was evaluated in consideration of the timing uncertainty of the ocean environmental load. Sampling points for the wind velocity, wave height, and wave period were generated using a central composites design, and a transfer function was constructed from the numerical analysis results. A simulation was performed using the joint probability model of ocean environmental loads. The stress time history was calculated by entering the load samples generated by the simulation into the transfer function. The damage to the structure was calculated using the rain-flow counting method, Goodman equation, Miner's rule, and S-N curve. The results confirmed that the wind speed generated at a specific time could not represent the wind speed that could occur during the design life of the structure.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.23 no.2
• /
• pp.101-108
• /
• 2019

The seismic safety of nuclear power plants has always been emphasized by the effects of accidents. In general, the seismic safety evaluation of nuclear power plants carries out a seismic probabilistic safety assessment. The current probabilistic safety assessment assumes that damage to the structure, system, and components (SSCs) occurs independently to each other or perfect dependently to each other. In case of earthquake events, the failure event occurs with the correlation due to the correlation between the seismic response of the SSCs and the seismic performance of the SSCs. In this study, the EEMS (External Event Mensuration System) code is developed which can perform the seismic probabilistic safety assessment considering correlation. The developed code is verified by comparing with the multiplier n, which is for calculating the joint probability of failure, which is proposed by Mankamo. It is analyzed the changes in seismic fragility curves and seismic risks with correlation. As a result, it was confirmed that the seismic fragility curves and seismic risk change according to the failure correlation coefficient. This means that it is important to select an appropriate failure correlation coefficient in order to perform a seismic probabilistic safety assessment. And also, it was confirmed that carrying out the seismic probabilistic safety assessment in consideration of the seismic correlation provides more realistic results, rather than providing conservative or non-conservative results comparing with that damage to the SSCs occurs independently.

• The Korean Journal of Applied Statistics
• /
• v.34 no.4
• /
• pp.537-556
• /
• 2021

Properties of statistical process control procedures may not be derived analytically in many cases; however, the application of a Markov chain can solve such problems. This article shows how to derive the properties of the process control procedures using the generated Markov chains when the control statistic satisfies the Markov property. Markov chain approaches that appear in the literature (such as the statistical design and economic design of the control chart as well as the variable sampling rate design) are reviewed along with the introduction of research results for application to a new control procedure and reset chart. The joint application of a Markov chain approach and analytical solutions (when available) can guarantee the correct derivation of the properties. A Markov chain approach is recommended over simulation studies due to its precise derivation of properties and short calculation times.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.1
• /
• pp.697-710
• /
• 2021

This paper attempts to study the impact of Financial Literacy on Youth Entrepreneurial Intent in Pakistan. A closed-ended self-administered structured questionnaire covering financial literacy, computer knowledge, financial attitude, and financial knowledge with Entrepreneurial Intent was collected from young entrepreneurs. The research tried to investigate the education level with computer skill to inspect the effect of financial literateness on young generation Entrepreneurial Intent in the context of Pakistan. The research model was tested using PLS-SEM and authenticating a measurement model through the advanced methodology and their association with Entrepreneurial Intent. Results revealed that financial literacy and its two parts (financial attitude and financial knowledge) have a positive impact on Entrepreneurial Intent. The size of the joint impact of financial literacy and its components on Entrepreneurial Intent was assessed to be adequate. Entrepreneurial Intent is essential for creating new firms to maintain economic development. Furthermore, it is determined in this research that if youth has better financial knowledge and financial attitude, the probability of Entrepreneurial Intent increases. This suggests that if the youth in Pakistan desire to attain a higher limit of Entrepreneurial Intent, they must implement financial literacy models for enhancing and promoting their current Entrepreneurial Intent.

• Nuclear Engineering and Technology
• /
• v.54 no.1
• /
• pp.110-116
• /
• 2022

Human failure event (HFE) dependency analysis is a part of human reliability analysis (HRA). For efficient HFE dependency analysis, a maximum number of minimal cut sets (MCSs) that have HFE combinations are generated from the fault trees for the probabilistic safety assessment (PSA) of nuclear power plants (NPPs). After collecting potential HFE combinations, dependency levels of subsequent HFEs on the preceding HFEs in each MCS are analyzed and assigned as conditional probabilities. Then, HFE recovery is performed to reflect these conditional probabilities in MCSs by modifying MCSs. Inappropriate HFE dependency analysis and HFE recovery might lead to an inaccurate core damage frequency (CDF). Using the above process, HFE recovery is performed on MCSs that are generated with a non-zero truncation limit, where many MCSs that have HFE combinations are truncated. As a result, the resultant CDF might be underestimated. In this paper, a new method is suggested to incorporate HFE recovery into the MCS generation stage. Compared to the current approach with a separate HFE recovery after MCS generation, this new method can (1) reduce the total time and burden for MCS generation and HFE recovery, (2) prevent the truncation of MCSs that have dependent HFEs, and (3) avoid CDF underestimation. This new method is a simple but very effective means of performing MCS generation and HFE recovery simultaneously and improving CDF accuracy. The effectiveness and strength of the new method are clearly demonstrated and discussed with fault trees and HFE combinations that have joint probabilities.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.887-899
• /
• 2022

Drought caused by meteorological factors negatively affects vegetation in terrestrial ecosystems. In this study, the state in which meteorological drought affects vegetation was defined as the ecological drought of vegetation, and the ecological drought condition index of vegetation (EDCI-veg) was proposed to quantitatively monitor the degree of impact. EDCI-veg is derived from a copula-based bi-variate joint probability model between vegetation and meteorological drought information, and can be expressed numerically how affected the current vegetation condition was by the drought when the drought occurred. Comparing past meteorological drought events with their corresponding vegetation condition, the proposed index was examined, and it was confirmed that EDCI-veg could properly monitor the ecological drought of vegetation. In addition, it was possible to spatially identify ecological drought conditions by creating a high-resolution drought map using remote sensing data.

• Journal of Korean Society on Water Environment
• /
• v.39 no.1
• /
• pp.9-19
• /
• 2023

Drought is a natural disaster that can have serious social impacts. Drought's impact ranges from water supply for humans to ecosystems, but the impact of drought on river water quality requires careful investigation. In general, drought occurs meteorologically and is classified as agricultural drought, hydrological drought, and environmental drought. In this study, the BOD environmental drought is defined using the bivariate copula joint probability distribution model between the meteorological drought index and the river BOD, and based on this, the environmental drought condition index (EDCI-BOD) was proposed. The results of examining the proposed index using past precipitation and BOD observation data showed that EDCI-BOD expressed environmental drought well in terms of river BOD water quality. In addition, by classifying the calculated EDCI-BOD into four levels, namely, 'attention', 'caution', 'alert', and 'seriousness', a practical monitoring stage for environmental drought of BOD was constructed. We further estimated the sensitivity of the stream BOD to meteorological drought, and through this, we could identify the stream section in which the stream BOD responded relatively more sensitively to the occurrence of meteorological drought. The results of this study are expected to provide information necessary for river BOD management in the event of meteorological droughts.

• Journal of Broadcast Engineering
• /
• v.13 no.2
• /
• pp.200-213
• /
• 2008

H.264| MPEG-4 AVC is a new video codingstandard defined by JVT (Joint Video Team) which consists of ITU-T and ISO/IEC. Many techniques are adopted fur the compression efficiency: Especially, an intra prediction in an inter frame is one example but it leads to excessive amount of encoding time due to the decision of a candidate mode and a RDcost calculation. For this reason, a fast determination of the best intra prediction mode is the main issue for saving the encoding time. In this paper, by using the result of statistical relation between intra $16{\times}16$ and $4{\times}4$ intra predictions, the number of candidate modes for $4{\times}4$ intra prediction is reduced. Firstly, utilizing motion vector obtained after inter prediction, prediction of a block mode for each macroblock is made. If an intra prediction is needed, the correlation table between $16{\times}16$ and $4{\times}4$ intra predicted modes is created using the probability during each I frame-coding process. Secondly, using this result, the candidate modes for a $4{\times}4$ intra prediction that reaches a predefined specific probability value are only considered in the same GOP For the experiments, JM11.0, the reference software of H.264|MPEG-4 AVC is used and the experimental results show that the encoding time could be reduced by 51.24% in maximum with negligible amounts of PSNR drop and bitrate increase.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.4
• /
• pp.765-773
• /
• 2009

Currently Telematics traffic information services have been various because we can collect real-time traffic information through Intelligent Transport System. In this paper, we proposed and implemented a short-term traffic information prediction model for giving to guarantee the traffic information with high quality in the near future. A Short-term prediction model is for forecasting traffic flows of each segment in the near future. Our prediction model gives an average speed on the each segment from 5 minutes later to 60 minutes later. We designed a Bayesian network for each segment with some casual nodes which makes an impact to the road situation in the future and found out its joint probability density function on the supposition of GMM(Gaussian Mixture Model) using EM(Expectation Maximization) algorithm with training real-time traffic data. To validate the precision of our prediction model we had conducted various experiments with real-time traffic data and computed RMSE(Root Mean Square Error) between a real speed and its prediction speed. As the result, our model gave 4.5, 4.8, 5.2 as an average value of RMSE about 10, 30, 60 minutes later, respectively.