LEADER 04562oam 22012374 450 001 9910788697403321 005 20230828230225.0 010 $a1-4623-1649-2 010 $a1-4527-9553-3 010 $a1-283-51849-X 010 $a1-4519-0980-2 010 $a9786613830944 035 $a(CKB)3360000000444018 035 $a(EBL)3014550 035 $a(SSID)ssj0000940807 035 $a(PQKBManifestationID)11600657 035 $a(PQKBTitleCode)TC0000940807 035 $a(PQKBWorkID)10955707 035 $a(PQKB)11208309 035 $a(OCoLC)694141260 035 $a(MiAaPQ)EBC3014550 035 $a(IMF)WPIEE2006267 035 $a(EXLCZ)993360000000444018 100 $a20020129d2006 uf 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aFinancial Integration in Asia : $eEstimating the Risk-Sharing Gains for Australia and Other Nations /$fBenoît Mercereau 210 1$aWashington, D.C. :$cInternational Monetary Fund,$d2006. 215 $a1 online resource (22 p.) 225 1 $aIMF Working Papers 300 $a"December 2006." 311 $a1-4518-6527-9 320 $aIncludes bibliographical references. 327 $a""Contents""; ""I. INTRODUCTION""; ""II. FINANCIAL INTEGRATION REDUCES RISK""; ""III. ESTIMATION METHODOLOGY AND DATA""; ""IV. RESULTS""; ""V. CONCLUSION""; ""Appendix. Data Sources and Construction""; ""References"" 330 3 $aHolding foreign assets reduces the volatility of a country's income by allowing countries to share risk. Yet, financial integration is limited in Asia. This paper estimates how much Australia and other countries in the Asia-Pacific region would gain from greater financial integration. The results suggest that these welfare gains are large, which argues in favor of a progressive capital account liberalization across the region. 410 0$aIMF Working Papers; Working Paper ;$vNo. 2006/267 606 $aFinance$zAsia 606 $aMonetary policy$zAsia 606 $aExports and Imports$2imf 606 $aFinance: General$2imf 606 $aInvestments: Stocks$2imf 606 $aMacroeconomics$2imf 606 $aGeneral Financial Markets: General (includes Measurement and Data)$2imf 606 $aInternational Investment$2imf 606 $aLong-term Capital Movements$2imf 606 $aPension Funds$2imf 606 $aNon-bank Financial Institutions$2imf 606 $aFinancial Instruments$2imf 606 $aInstitutional Investors$2imf 606 $aMacroeconomics: Consumption$2imf 606 $aSaving$2imf 606 $aWealth$2imf 606 $aCurrent Account Adjustment$2imf 606 $aShort-term Capital Movements$2imf 606 $aFinance$2imf 606 $aInternational economics$2imf 606 $aInvestment & securities$2imf 606 $aFinancial integration$2imf 606 $aForeign assets$2imf 606 $aStocks$2imf 606 $aConsumption$2imf 606 $aCapital account$2imf 606 $aInternational finance$2imf 606 $aInvestments, Foreign$2imf 606 $aEconomics$2imf 606 $aBalance of payments$2imf 607 $aHong Kong Special Administrative Region, People's Republic of China$2imf 615 0$aFinance 615 0$aMonetary policy 615 7$aExports and Imports 615 7$aFinance: General 615 7$aInvestments: Stocks 615 7$aMacroeconomics 615 7$aGeneral Financial Markets: General (includes Measurement and Data) 615 7$aInternational Investment 615 7$aLong-term Capital Movements 615 7$aPension Funds 615 7$aNon-bank Financial Institutions 615 7$aFinancial Instruments 615 7$aInstitutional Investors 615 7$aMacroeconomics: Consumption 615 7$aSaving 615 7$aWealth 615 7$aCurrent Account Adjustment 615 7$aShort-term Capital Movements 615 7$aFinance 615 7$aInternational economics 615 7$aInvestment & securities 615 7$aFinancial integration 615 7$aForeign assets 615 7$aStocks 615 7$aConsumption 615 7$aCapital account 615 7$aInternational finance 615 7$aInvestments, Foreign 615 7$aEconomics 615 7$aBalance of payments 700 $aMercereau$b Benoît$01558707 801 0$bDcWaIMF 906 $aBOOK 912 $a9910788697403321 996 $aFinancial Integration in Asia$93823301 997 $aUNINA LEADER 01258nam 2200433 450 001 9910814357703321 005 20230809225406.0 010 $a80-246-2808-2 035 $a(CKB)3790000000543020 035 $a(MiAaPQ)EBC5205471 035 $a(Au-PeEL)EBL5205471 035 $a(CaPaEBR)ebr11492885 035 $a(OCoLC)1019659993 035 $a(EXLCZ)993790000000543020 100 $a20180201h20172017 uy 0 101 0 $acze 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aJak odskodnit holocaust? /$fJan Kuklik 210 1$a[Place of publication not identified] :$cCharles University in Prague, Karolinum Press,$d2017. 210 4$d©2017 215 $a1 online resource (756 pages) $cillustrations 311 $a80-246-2798-1 320 $aIncludes bibliographical references. 606 $aJewish property$zEurope 606 $aRestitution$zCzech Republic 615 0$aJewish property 615 0$aRestitution 676 $a940.5318144 700 $aKukli?k$b Jan$01627204 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910814357703321 996 $aJak odskodnit holocaust$93963657 997 $aUNINA LEADER 04192nam 22007215 450 001 9910574060903321 005 20251113191841.0 010 $a981-19-2746-4 024 7 $a10.1007/978-981-19-2746-1 035 $a(MiAaPQ)EBC7001367 035 $a(Au-PeEL)EBL7001367 035 $a(CKB)22898392200041 035 $a(PPN)269148302 035 $a(OCoLC)1322837872 035 $a(DE-He213)978-981-19-2746-1 035 $a(EXLCZ)9922898392200041 100 $a20220527d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDeep Learning in Solar Astronomy /$fby Long Xu, Yihua Yan, Xin Huang 205 $a1st ed. 2022. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022. 215 $a1 online resource (103 pages) 225 1 $aSpringerBriefs in Computer Science,$x2191-5776 311 08$aPrint version: Xu, Long Deep Learning in Solar Astronomy Singapore : Springer,c2022 9789811927454 320 $aIncludes bibliographical references and index. 327 $aChapter 1: Introduction -- Chapter 2: Classical deep learning models -- Chapter 3: Deep learning in solar image classification tasks -- Chapter 4: Deep learning in solar object detection tasks -- Chapter 5: Deep learning in solar image generation tasks -- Chapter 6: Deep learning in solar forecasting tasks. 330 $aThe volume of data being collected in solar astronomy has exponentially increased over the past decade and we will be entering the age of petabyte solar data. Deep learning has been an invaluable tool exploited to efficiently extract key information from the massive solar observation data, to solve the tasks of data archiving/classification, object detection and recognition. Astronomical study starts with imaging from recorded raw data, followed by image processing, such as image reconstruction, inpainting and generation, to enhance imaging quality. We study deep learning for solar image processing. First, image deconvolution is investigated for synthesis aperture imaging. Second, image inpainting is explored to repair over-saturated solar image due to light intensity beyond threshold of optical lens. Third, image translation among UV/EUV observation of the chromosphere/corona, Ha observation of the chromosphere and magnetogram of the photosphere is realized by using GAN, exhibiting powerful image domain transfer ability among multiple wavebands and different observation devices. It can compensate the lack of observation time or waveband. In addition, time series model, e.g., LSTM, is exploited to forecast solar burst and solar activity indices. This book presents a comprehensive overview of the deep learning applications in solar astronomy. It is suitable for the students and young researchers who are major in astronomy and computer science, especially interdisciplinary research of them. 410 0$aSpringerBriefs in Computer Science,$x2191-5776 606 $aAstronomy 606 $aAstronomy$vObservations 606 $aMachine learning 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aAstronomy, Cosmology and Space Sciences 606 $aAstronomy, Observations and Techniques 606 $aMachine Learning 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aComputer Vision 615 0$aAstronomy. 615 0$aAstronomy 615 0$aMachine learning. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 14$aAstronomy, Cosmology and Space Sciences. 615 24$aAstronomy, Observations and Techniques. 615 24$aMachine Learning. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aComputer Vision. 676 $a523.70285631 700 $aXu$b Long$0720841 702 $aYan$b Yihua 702 $aHuang$b Xin 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910574060903321 996 $aDeep Learning in Solar Astronomy$92860233 997 $aUNINA