동해 돌연고파의 발생 메커니즘과 기계학습 예측모델

학위논문 (박사)-- 서울대학교 대학원 공과대학 건설환경공학부, 2017. 8. 서경덕.Exceptional high waves have occurred repeatedly in the East Sea of Korea. These disastrous waves claimed the losses of life more than 50 people during the ten years between 2005 and 2015 in the east coast of Korea. Several researchers have examined the generation mechanism and characteristics of sudden high waves. However, the definition of the high waves is still vague and insufficient to explain the characteristics of sudden high waves. Also, occurrence of sudden high waves is only roughly forecasted in the daily weather forecast. In this study sudden high waves were defined using a new intensity parameter and the generation mechanism of the sudden high waves was investigated. Next, significant wave height and period were forecasted in the East Sea of Korea using machine-learning. Finally, sudden high waves were forecasted using the intensity parameter proposed and the forecasted significant waves in the East Sea of Korea. In this study, the index of sudden high waves was suggested as and it was calculated using wave data measured in Gangneung and Wangdolcho in 2005–2012. The criteria of sudden high waves was set 80 m^3/hr, which corresponds to the top 20% of cumulative percentage of . Next, to find the generation mechanism of sudden high waves, the evolution of spatial patterns of wind velocity and sea level pressures was presented during the sudden high wave events by CSEOF analysis and regression analysis. The wave data in Gangneung and Wangdolcho were used and the meteorological data were reanalysis data of National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). There are two peaks in the modes of all CSLV considered the physical process of sudden high waves. The patterns were categorized two groups. The first pattern was that the first peak was generated by low pressure moving to the north east part of the East Sea and easterly wind blowing for 1 day, whereas the second peak was caused by strong wind. The second pattern was that the first peak was affected by the wind speed in the east coast and the second peak was influenced by wind in the offshore area. To forecast significant waves in multiple locations simultaneously, an EOFWNN model was developed by combining the EOF analysis and wavelet analysis with the neural network. The wave data used in this research were measured at eight wave observation stations in the East Sea and the meteorological data were the NCEP/NCAR reanalysis data. The results of the EOFWNN model for significant wave height were compared with those of a wavelet and neural network hybrid (WNN) model in Gangneung, Sakata and Aomori for several lead times. The EOFWNN model is better than the WNN model in that the former shows higher accuracy for longer lead times regardless of the wavelet decomposition level. Significant wave period series were also forecasted using the EOFWNN model. The results of significant wave period also show quite high accuracy. Also, the proposed model was employed to the numerical wave modeling data in the entire area of the East Sea. The results also show relatively high accuracy for one and three hour lead times. Using the proposed intensity parameter of sudden high waves and the forecasted significant waves by the EOFWNN model, sudden high wave was detected and forecasted. From the forecasted wave data at 24 hour lead time, was calculated in Gangneung and Sakata. Although there is a slight deviation between the results of observed and forecasted wave data, sudden high wave was detected clearly.CHAPTER 1 INTRODUCTION 1 1.1 Background 1 1.2 Research objectives 6 CHAPTER 2 THEORETICAL STUDY 8 2.1 Analysis methods of mechanism of sudden high waves 8 2.1.1 CSEOF analysis 9 2.1.2 Regreggion analysis 11 2.2 Wave forecast methods 13 2.2.1 EOF analysis 14 2.2.2 Wavelet analysis 16 2.2.3 Artificial Neural Network 19 2.2.4 EOF-Wavelet-ANN (EOFWNN) model 23 CHAPTER 3 CHARACTERISTICS OF SUDDEN HIGH WAVES 27 3.1 Data for anlaysis of characteristics of sudden high waves 27 3.1.1 Wave data 27 3.1.2 Meteorological data 27 3.2 Definition of sudden high waves 30 3.3 Mechanism of sudden high waves 43 CHAPTER 4 FORECASTING OF SUDDEN HIGH WAVES 62 4.1 Data for forecasting of sudden high waves 62 4.1.1 Observed wave data 62 4.1.2 Numerical wave modeling data 64 4.1.3 Meteorological data for forecasting 66 4.2 Forecasting of significant wave height and period using the observed data 67 4.3 Forecasting of significant wave height and peak period using the numerical modeling data 92 4.4 Detecting and forecasting of sudden high waves 103 CHAPTER 5 CONCLUSIONS 111 5.1 Summary and conclusions 111 5.2 Future study 114 REFERENCES 117 APPENDIX 121 국문초록 137Docto

최근 60년 동안 한반도에 영향을 미친 태풍의 강도 및 지속기간의 경향 분석

학위논문 (석사)-- 서울대학교 대학원 : 건설환경공학부, 2011.2. 서경덕.Maste

인체자원의 지속적인 활용을 위한 불멸화 세포주 연구

Graduate Program in Science for Aging/박사Epstein-Barr virus (EBV)-transformed lymphoblastoid cell lines (LCLs) promise to address the challenge posed by the limited availability of primary cells needed as a source of genomic DNA for genetic studies. However, the genetic stability of LCLs following prolonged culture has never been rigorously investigated. The impact of genomic aberration on the biological experiments such as gene expression and miRNA expression level has not been explored. Purposes of current study are to investigate whether genetic instability of LCLs might cause the accumulation of genetic modifications following their long-term subculture and to examine a correlation between genomic aberration and expression level in genes and miRNAs. To accomplish our goals, we isolated genomic DNA from human peripheral blood mononuclear cells and LCLs collected from 20 individuals and genotyped the DNA samples using the Affymetrix Gene Chip Human mapping 500K array set and Illumina HumanExome BeadChip array. Genotype concordance measurements between two sources of DNA from the same individual indicated that genotypic discordance is negligible in early-passage LCLs (50 passages). Analysis of concordance on a chromosome-by chromosome basis identified genomic regions with a high frequency of genotypic errors resulting from the loss of heterozygosity observed in late-passage LCLs. Discovered genomic aberrations were of 90 regions of copy number variations (CNVs) observed in late-passage LCLs. In addition, integrated analysis revealed genomic aberration changed expression levels in genes and miRNAs.Our findings suggest that, although LCLs harvested during early stages of propagation are a reliable source of genomic DNA for genetic studies, investigations that involve genotyping of the entire genome should not use DNA from late-passage LCLs.ope