LEADER 05629nam 2200745Ia 450 001 9910784522303321 005 20230721030549.0 010 $a1-281-91866-0 010 $a9786611918668 010 $a981-270-894-4 035 $a(CKB)1000000000399349 035 $a(EBL)1681434 035 $a(OCoLC)879025347 035 $a(SSID)ssj0000375234 035 $a(PQKBManifestationID)11288987 035 $a(PQKBTitleCode)TC0000375234 035 $a(PQKBWorkID)10447933 035 $a(PQKB)10522517 035 $a(MiAaPQ)EBC1681434 035 $a(WSP)00006494v9 035 $a(Au-PeEL)EBL1681434 035 $a(CaPaEBR)ebr10255530 035 $a(CaONFJC)MIL191866 035 $a(EXLCZ)991000000000399349 100 $a20061018d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aAdvances in geosciences$hVolume 9$iSolid earth (SE), ocean science (OS) and atmospheric science (AS)$b[electronic resource] /$feditor-in-chief, Wing-Huen Ip ; volume editor-in-chief, Yun-Tai Chen 210 $aHackensack, N.J. $cWorld Scientific$dc2007 215 $a1 online resource (245 p.) 225 1 $aAdvances in Geosciences ;$vv.9 300 $aDescription based upon print version of record. 311 $a981-270-988-6 320 $aIncludes bibliographical references. 327 $aCONTENTS; SOLID EARTH (SE); Tracking the High-Frequency Energy Radiation Sources of the 2004 Sumatra-Andaman MW 9.0 Earthquake Using the Short-Period Seismic Data: Preliminary Result H.-L. Du, L.-S. Xu, Y.-T. Chen, C.-L. Li and K. Stammler; 1. Introduction; 2. Data; 3. Method; 4. Correction for the Slowness Vectors Using Aftershocks; 5. Tracking the Energy Sources; 6. Discussion and Conclusions; Acknowledgments; References; Rupture Process of the 2005 Southern Asian (Pakistan) MW 7.6 Earthquake from Long-Period Waveform Data Y. Zhang, Y.-T. Chen and L.-S. Xu; 1. Introduction 327 $a2. Data and Processing3. Spatio-temporal and Rupture Process; 4. Discussion and Conclusions; Acknowledgments; References; Seismic Characteristics of Strong Deep Focal Earthquakes and Associated Phenomena in Northeastern Asia J. Wang, X.-S. He and Y.-Q. Li; 1. Introduction; 2. Seismic Data; 3. Spatial-Temporal Characteristics of Deep Focal Earthquakes; 3.1. Wavelet analysis on temporal-frequency characteristics; 3.2. Relative active and quiet periods of deep focal earthquakes; 3.3. Spatial distribution of strong deep focal earthquakes; 4. Characteristics of Strong Shallow Earthquakes and Tests 327 $a4.1. Spatial-temporal distribution of strong shallow earthquakes4.2. Test of seismic characteristics; 4.3. Seismic characteristics of Northeastern China; 4.4. Mechanism of the relationship between strong shallow earthquakes and great deep focal earthquakes; 5. Discussion and Conclusions; Acknowledgments; References; Moho Depths in the Indian Ocean Based on the Inversion of Satellite Gravity Data D. N. Arabelos, G. Mantzios and D. Tsoulis; 1. Introduction; 2. Data; 2.1. Gravity anomalies; 2.2. Digital terrain model; 2.3. CRUST 2.0; 2.4. Altimetry 327 $a3. Inversion of the Gravity Anomalies Using LSC4. Assessment of the Estimated Moho Depths in the Indian Ocean; 4.1. Based on the comparison with CRUST 2.0; 4.2. Based on isostatic reductions on JASON 1 altimeter data using Airy or the computed model; 5. Conclusions; References; Post Earthquake Debris Management - an Overview R. Sarkar; 1. Introduction; 2. Post Earthquake Debris Separation; 2.1. Vegetative debris; 2.2. Non-vegetative debris; 3. Post Earthquake Debris Management Plan; 4. Selection of Post Earthquake Debris Collection and Storage Sites 327 $a5. Types of Earthquake Debris Disposal Sites6. Transportation of Post Earthquake Debris; 8. Post Earthquake Debris Management Related to Various Phases after the Disaster; 9. Basic Rules for the Post Earthquake Debris Management; 10. Post Earthquake Debris Management Related to Night Soil, Garbage Collection, and Collapsed Structures; 11. Emergency Management Perspectives for Post Earthquake Debris Clearance; 12. Conclusion; References; OCEAN SCIENCE (OS) 327 $aBuried and Surface Polymetallic Nodule Distribution in the Eastern Clarion-Clipperton Zone: Main Distinctions and Similarities R. Kotlinski and V. Stoyanova 330 $a Advances in Geosciences is the result of a concerted effort in bringing the latest results and planning activities related to earth and space science in Asia and the international arena. The volume editors are all leading scientists in their research fields covering six sections: Hydrological Science (HS), Planetary Science (PS), Solar Terrestrial (ST), Solid Earth (SE), Ocean Science (OS) and Atmospheric Science (AS). The main purpose is to highlight the scientific issues essential to the study of earthquakes, tsunamis, atmospheric dust storms, climate change, drought, flood, typhoons 410 0$aAdvances in Geosciences 606 $aEarth sciences 606 $aPlanetary meteorology 606 $aPlanetology 606 $aSpace environment 606 $aSpace sciences 615 0$aEarth sciences. 615 0$aPlanetary meteorology. 615 0$aPlanetology. 615 0$aSpace environment. 615 0$aSpace sciences. 676 $a550 701 $aIp$b W.-H$0855808 701 $aChen$b Yuntai$01545370 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910784522303321 996 $aAdvances in geosciences$93800274 997 $aUNINA LEADER 04011nam 22005775 450 001 9910366619303321 005 20251116220341.0 010 $a3-662-59717-9 024 7 $a10.1007/978-3-662-59717-0 035 $a(CKB)4100000009522832 035 $a(DE-He213)978-3-662-59717-0 035 $a(MiAaPQ)EBC5945761 035 $a(PPN)258863692 035 $a(EXLCZ)994100000009522832 100 $a20191014d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial intelligence - When do machines take over? /$fby Klaus Mainzer 205 $a1st ed. 2020. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2020. 215 $a1 online resource (XI, 279 p. 57 illus., 10 illus. in color.) 225 1 $aTechnik im Fokus,$x2194-0770 311 08$a3-662-59716-0 320 $aIncludes bibliographical references. 327 $aIntroduction: What is AI? -- A brief history of AI -- Logical thinking becomes automatic -- Systems become experts -- Computers learn to speak -- Algorithms simulate evolution -- Neural networks simulate brains -- Robots become social -- Automobiles become autonomous -- Factories become intelligent -- From natural to artificial to super intelligence?. 330 $aEverybody knows them. Smartphones that talk to us, wristwatches that record our health data, workflows that organize themselves automatically, cars, airplanes and drones that control themselves, traffic and energy systems with autonomous logistics or robots that explore distant planets are technical examples of a networked world of intelligent systems. Machine learning is dramatically changing our civilization. We rely more and more on efficient algorithms, because otherwise we will not be able to cope with the complexity of our civilizing infrastructure. But how secure are AI algorithms? This challenge is taken up here: Complex neural networks are fed and trained with huge amounts of data (big data). The number of necessary parameters explodes exponentially. Nobody knows exactly what is going on in these "black boxes". In machine learning we need more explainability and accountability of causes and effects in order to be able to decide ethical and legal questions of responsibility (e.g. in autonomous driving or medicine). Besides causal learning, we also analyze procedures of tests and verification to get certified AI-programs. Since its inception, AI research has been associated with great visions of the future of mankind. It is already a key technology that will decide the global competition of social systems. "Artificial Intelligence and Responsibility" is another central supplement to this book: How should we secure our individual liberty rights in the AI world? This book is a plea for technology design: AI must prove itself as a service in society. 410 0$aTechnik im Fokus,$x2194-0770 606 $aTechnology 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aPopular Science in Technology$3https://scigraph.springernature.com/ontologies/product-market-codes/Q36000 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 615 0$aTechnology. 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 14$aPopular Science in Technology. 615 24$aComputational Intelligence. 615 24$aArtificial Intelligence. 676 $a600 700 $aMainzer$b Klaus$4aut$4http://id.loc.gov/vocabulary/relators/aut$045836 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910366619303321 996 $aArtificial intelligence - When do machines take over$91990778 997 $aUNINA