“…The talented group of writers, musicians, and artists contributing to the book include: Jed Alger Judd Apatow Marian Bantjes Ken Carbone Tim Carvell Deanne Cheuk Wayne Coyne Russell Davies Arem Duplessis Dave Eggers Karen Fowler Ze Frank Jona Frank Jill Greenberg Stanley Hainsworth Peter Hannan Debbie Millman Rick Morris Seth Morris Christoph Niemann David Norland Patton Oswalt Martha Rich Stefan Sagmeister Meredith Scardino J.J. Sedelmaier Dave Stewart Lara Tomlin Jakob Trollbäck Rick Valicenti Esther Pearl Watson Lynda Weinman Jan Wilker Doyald Young Tarsem If you answer even half of the questions in this book, it will change your life…”

“…Contains contributions from Sophia Adams, Michael J. Allen, Sam Bithell, Cameron Clegg, Geoffrey Dannell, Lorne Elliott, Elizabeth Foulds, Freddie Foulds, Christopher Green, Darren Grocke, Derek Hamilton, Colin Haselgrove, Yvonne Inall, Tina Jakob, Mandy Jay, Sally Kellett, Robert Kenyon, Mark Landon, Edward McSloy, Janet Montgomery, J.A. …”

“…John Resig is an acknowledged JavaScript authority and the creator of the jQuery library. Bear Bibeault is a web developer and author of the first edition, as well as coauthor of Ajax in Practice, Prototype and Scriptaculous in Action, and jQuery in Action from Manning. …”

“…Ses passionnantes histoires" J. A. [4e de couverture]…”

“…Están inspiradas en las obras de los fabulistas clásicos Esopo y Fedro, del francés Jean de La Fontaine y del inglés J. Gay. Tienen propósito didáctico. Su estilo es sencillo. …”

Tabla de Contenidos: “….) -- I) RESPONSABILIDAD DE LOS ORGANISMOS DE AUTORREGULACIÓN Y DEMANDA DE LAS (...) -- J) LA RESPONSABILIDAD DISCIPLINARIA PRIVADA Y EL TÍTULO DE IMPUTACIÓN -- 3. …”
Enlace del recurso

Tabla de Contenidos: “….) -- 2.7.2 LISTAS NEGRAS -- 2.7.3 LISTAS BLANCAS -- 2.7.4 EXPRESIONES REGULARES -- 2.7.5 FILTROS -- 2.8 GUÍA OWASP DE DESARROLLO SEGURO -- 2.9 EJERCICIOS -- 2.10 RESUMEN -- 2.11 BIBLIOGRAFÍA -- 2.12 AUTOEVALUACIÓN UNIDAD 2 -- 2.13 LECTURAS RECOMENDADAS -- 2.14 GLOSARIO DE TÉRMINOS -- 3 PROGRAMACIÓN SEGURA EN SERVICIOS WEB -- INTRODUCCIÓN -- OBJETIVOS DE LA UNIDAD DIDÁCTICA -- 3.1 CARACTERÍSTICAS DE LOS SERVICIOS WEB -- 3.2 ARQUITECTURAS ORIENTADAS A SERVICIOS -- 3.3 ARQUITECTURA DE LOS SERVICIOS WEB -- 3.4 TECNOLOGÍAS -- 3.4.1 XML -- 3.4.2 SOAP -- 3.4.3 WSDL -- 3.4.4 AJAX -- 3.4.5 SERVICIOS REST -- 3.4.6 TECNOLOGÍAS DE SEGUNDA GENERACIÓN -- 3.5 TECNOLOGÍAS J2EE PARA SERVICIOS WEB -- 3.5.1 JAXP -- 3.5.2 JAXM -- 3.5.3 JAX-RPC / JAX-WS -- 3.5.4 JAXR -- 3.5.5 JAXB -- 3.5.6 OTRAS LIBRERÍAS -- 3.6 IMPLEMENTACIÓN DE LOS SERVICIOS WEB (...) -- 3.6.1 TIPOS DE DATOS -- 3.6.2 ANOTACIONES -- 3.7 SERVICIOS WEB AVANZADOS -- 3.7.1 OPTIMIZACIÓN DE MENSAJES -- 3.7.2 SERVICIOS WEB SEGUROS -- 3.7.3 CONFIDENCIALIDAD E INTEGRIDAD -- 3.7.4 AUTENTICACIÓN EN SERVICIOS WEB -- 3.8 FRAMEWORKS JAVA PARA SERVICIOS WEB (...) -- 3.8.1 AXIS 2 -- 3.8.2 CXF -- 3.8.3 JAX-WS -- 3.9 SEGURIDAD EN API REST CON JAVA JAX-RS -- 3.9.1 AUTENTICACIÓN EN JAX-RS -- 3.9.2 AUTORIZACIÓN EN JAX-RS…”

Tabla de Contenidos: “…Un modelo de Universidad tradicional, centralista y j -- 5. El ministerio de Joaquín Ruiz-Giménez Cortés -- 6. …”
Lectura limitada a 1 usuario concurrente.

Tabla de Contenidos: “…Nota informativa -- a) Mareas -- b) Mareas atmosféricas -- c) Mareas terrestres -- d) Mareas biológicas -- e) Variación de la ionización atmosférica -- f) Variación en el magnetismo terrestre -- g) Desviación del viento solar -- h) Freno del movimiento de rotación -- i) Movimientos de precesión y nutación -- j) Alteraciones en la conducta humana -- 1.5 Relación Sol-Tierra-Luna -- 2. …”

Tabla de Contenidos: “…CANTERA SAN FRANCISCO IX. EXPTE. D.P.M.: 9511 J 88.- -- 5.2.22. CANTERA SAN FRANCISCO X. EXPTE. -- 5.2.23. …”

Tabla de Contenidos: “…BUFFET -- PRESENTACIÓN -- MENÚ PARA BUFFET FROID -- MENÚ PARA BUFFET FROID ET CHAUD -- I. CENA -- J. VINO DE HONOR -- II. SECUENCIA DE SERVICIO Y PREPARACIÓN (...) -- 1. …”

Tabla de Contenidos: “…Intro -- Portadilla -- Christopher Maurer, «Prólogo: Lorca de viva voz» -- Rafael Inglada y Víctor Fernández, «El poeta al que no le gustaban las entrevistas» -- Declaraciones y entrevistas completas -- Primera parte. 1922-1933 -- Federico García Lorca, Homenaje a Granada -- Febronio Ortega, La España nueva: Federico García Lorca -- Rafael Moragas, Durante un ensayo, en el Goya, de «Mariana Pineda» -- Francisco Ayala, Un drama de García Lorca: «Mariana Pineda» -- Federico García Lorca, Autocrítica de «Mariana Pineda» -- Juan González Olmedilla, García Lorca, el público, la crítica y «Mariana Pineda» -- Ernesto Giménez Caballero, Itinerarios jóvenes de España: Federico García Lorca -- Germán Arciniegas, Federico García Lorca -- Miguel Pérez Ferrero, Voces de desembarque: veinte minutos de paseo con Federico García Lorca -- J. L., Antes del estreno: hablando con Federico García Lorca -- César González-Ruano, Bajo la sonrisa de «La zapatera prodigiosa» -- Rodolfo Gil Benumeya, Estampa de García Lorca -- Juan de Alfarache, Federico García Lorca, o la simpatía -- V. …”

Tabla de Contenidos: “…Harras, and Mostafa Ammar / /7.1 Introduction 159 / /7.2 Design Space with Examples 161 / /7.2.1 Mont-Blanc 162 / /7.2.2 Computing while Charging 163 / /7.2.3 FemtoCloud 164 / /7.2.4 Serendipity 166 / /7.3 FemtoCloud Performance Evaluation 168 / /7.3.1 Experimental Setup 168 / /7.3.2 FemtoCloud Simulation Results 169 / /7.3.3 FemtoCloud Prototype Evaluation 173 / /7.4 Serendipity Performance Evaluation 175 / /7.4.1 Experimental Setup 175 / /7.4.2 Serendipity's Performance Benefits 176 / /7.4.3 Impact of Network Environment 179 / /7.4.4 The Impact of the Job Properties 182 / /7.5 Challenges 186 / /References 186 / /III APPLICATIONS OF FOG 189 / /8 The Role of Fog Computing in the Future of the Automobile 191 /Flavio Bonomi, Stefan Poledna, and Wilfried Steiner / /8.1 Introduction 191 / /8.2 Current Automobile Electronic Architectures 193 / /8.3 Future Challenges of Automotive E/E Architectures and Solution Strategies 195 / /8.4 Future Automobiles as Fog Nodes on Wheels 200 / /8.5 Deterministic FOG Nodes on Wheels Through Real-Time Computing and Time-Triggered Technologies /203 / /8.5.1 Deterministic Fog Node Addressing the Scalability Challenge through Virtualization 203 / /8.5.2 Deterministic Fog Node Addressing the Connectivity and Security Challenges 204 / /8.5.3 Emerging Use Case of Deterministic Fog Nodes in Automotive Applications - Vehicle-Wide /Virtualization 206 / /8.6 Conclusion 209 / /References 209 / /9 Geographic Addressing for Field Networks 211 /Robert J. Hall / /9.1 Introduction 211 / /9.1.1 Field Networking 211 / /9.1.2 Challenges of Field Networking 212 / /9.2 Geographic Addressing 214 / /9.3 SAGP: Wireless GA in the Field 215 / /9.3.1 SAGP Processing 216 / /9.3.2 SAGP Retransmission Heuristics 217 / /9.3.3 Example of SAGP Packet Propagation 218 / /9.3.4 Followcast: Efficient SAGP Streaming 219 / /9.3.5 Meeting the Challenges 220 / /9.4 Georouting: Extending GA to the Cloud 221 / /9.5 SGAF: A Multi-Tiered Architecture for Large-Scale GA 222 / /9.5.1 Bridging Between Tiers 223 / /9.5.2 Hybrid Security Architecture 225 / /9.6 The AT&T Labs Geocast System 225 / /9.7 Two GA Applications 226 / /9.7.1 PSCommander 226 / /9.7.2 Geocast Games 230 / /9.8 Conclusions 232 / /References 232 / /10 Distributed Online Learning and Stream Processing for a Smarter Planet 234 /Deepak S.…”

Tabla de Contenidos: “…5.3.1.a Testing a Hypothesis About a Coefficient -- 5.3.1.b The F Statistic -- 5.3.2 Tests Based on the Fit of the Regression -- 5.3.2.a The Restricted Least Squares Estimator -- 5.3.2.b The Loss of Fit from Restricted Least Squares -- 5.3.2.c Testing the Significance of the Regression -- 5.3.2.d Solving Out the Restrictions and a Caution about R2 -- 5.3.3 Lagrange Multiplier Tests -- 5.4 Large-Sample Tests and Robust Inference -- 5.5 Testing Nonlinear Restrictions -- 5.6 Choosing Between Nonnested Models -- 5.6.1 Testing Nonnested Hypotheses -- 5.6.2 An Encompassing Model -- 5.6.3 Comprehensive Approach-The J Test -- 5.7 A Specification Test -- 5.8 Model Building-A General to Simple Strategy -- 5.8.1 Model Selection Criteria -- 5.8.2 Model Selection -- 5.8.3 Classical Model Selection -- 5.8.4 Bayesian Model Averaging -- 5.9 Summary and Conclusions -- CHAPTER 6 Functional Form, Difference in Differences, and Structural Change -- 6.1 Introduction -- 6.2 Using Binary Variables -- 6.2.1 Binary Variables in Regression -- 6.2.2 Several Categories -- 6.2.3 Modeling Individual Heterogeneity -- 6.2.4 Sets of Categories -- 6.2.5 Threshold Effects and Categorical Variables -- 6.2.6 Transition Tables -- 6.3 Difference in Differences Regression -- 6.3.1 Treatment Effects -- 6.3.2 Examining the Effects of Discrete Policy Changes -- 6.4 Using Regression Kinks and Discontinuities to Analyze Social Policy -- 6.4.1 Regression Kinked Design -- 6.4.2 Regression Discontinuity Design -- 6.5 Nonlinearity in the Variables -- 6.5.1 Functional Forms -- 6.5.2 Interaction Effects -- 6.5.3 Identifying Nonlinearity -- 6.5.4 Intrinsically Linear Models -- 6.6 Structural Break and Parameter Variation -- 6.6.1 Different Parameter Vectors -- 6.6.2 Robust Tests of Structural Break with Unequal Variances -- 6.6.3 Pooling Regressions -- 6.7 Summary And Conclusions…”

Tabla de Contenidos: “…Commerce extérieur, par groupe de produits -- Tableau J. Monnaie et crédit -- Tableau K. Secteur public -- Tableau L. …”

Tabla de Contenidos: “…Balance des paiements -- Tableau J. Secteurs monétaire et bancaire -- Tableau K. …”

Tabla de Contenidos:

Tabla de Contenidos: “…Commerce extérieur par groupe de produits -- Tableau J. Balance des paiements sur la base des règlements -- Tableau K. …”

Tabla de Contenidos: “…_Int_yrbDRWGx -- _Int_mvWxOBgk -- _Int_e1ynDwng -- _Int_E5WPbRvd -- _Int_ik07RnQT -- _Int_uixqLP4p -- _Int_MQCIDSbu -- _Int_vW101Fs3 -- _Int_MECdmoIg -- _Int_il1DBMWc -- _Int_im4ch9Qs -- _Int_KjAnUAkS -- _Int_RQnK0GqL -- _Int_MqK5ubgh -- _Int_pcKZkOxh -- _Int_nVxBbOCf -- _Int_OhycVcV5 -- _Int_MdzmHSAR -- _Int_WMRKuNSs -- _Int_CbYOG8Xf -- _Int_rMoP6Y4c -- _Int_ryKbdLPF -- _Int_q4kK1Ige -- _Int_uNRm8pdn -- _Int_qQYLWHFL -- _Int_g6u1uoJ1 -- OLE_LINK6 -- _Int_plBgvcrr -- _Int_EBC0KAuq -- _Int_UwUd5a5S -- _Int_OURbvCOX -- _Int_SGc11RZW -- _Int_0luoJlVa -- _Int_ytaf4YEa -- _Int_DyeYW99t -- _Int_X7oA6gKG -- _Int_91RIYQKN -- _Int_1sbY7MpC -- _Int_SUH43hNk -- _Int_dk4CsUJz -- _Int_zOmEaDJc -- OLE_LINK14 -- OLE_LINK16 -- OLE_LINK17 -- _Int_iOPc4I79 -- _Int_vObvpBwX -- _Int_Sh0PvUCQ -- _Int_FkbdxX9t -- _Int_xqObit9S -- OLE_LINK19 -- _Hlk149855058 -- _Int_W5E01Lay -- _Int_9YpkIXGW -- _Int_k3fsPxvI -- _Int_D56ZjsqT -- _Int_Q5LrUWR3 -- _Int_bkaDCfSC -- _Int_2yOM05By -- _Int_rNsi5wbp -- _Int_KyRSlOuT -- _Int_P00FIjSH -- _Int_CencMsfh -- _Int_3lslfkJe -- _Int_7oSSbBgT -- OLE_LINK22 -- _Int_0M403O60 -- _Int_GmK1TWt6 -- _Int_6DkODWnF -- _Int_1A9bfKrt -- _Int_SkAVqdcG -- OLE_LINK9 -- _Hlk151532699 -- OLE_LINK10 -- OLE_LINK5 -- OLE_LINK11 -- _Hlk151709071 -- OLE_LINK8 -- _Hlk154054230 -- OLE_LINK12 -- OLE_LINK13 -- OLE_LINK15 -- OLE_LINK17 -- __codelineno-0-1 -- OLE_LINK18 -- _Hlk154408967 -- OLE_LINK1 -- OLE_LINK2 -- OLE_LINK3 -- OLE_LINK4 -- OLE_LINK5 -- OLE_LINK7 -- _Hlk162119449 -- OLE_LINK10 -- OLE_LINK12 -- OLE_LINK11 -- OLE_LINK1 -- OLE_LINK4 -- OLE_LINK7 -- _Hlk162119449 -- OLE_LINK10 -- OLE_LINK12 -- OLE_LINK11 -- _Hlk162122907 -- OLE_LINK9 -- OLE_LINK1 -- OLE_LINK18 -- OLE_LINK19 -- OLE_LINK21 -- OLE_LINK22 -- OLE_LINK23 -- OLE_LINK24 -- OLE_LINK20 -- OLE_LINK29 -- _Hlk167132856 -- OLE_LINK25 -- _Hlk167133000 -- _Hlk167133017 -- OLE_LINK26 -- OLE_LINK27…”

Tabla de Contenidos: “…1.15.5 Superconductors -- 1.15.6 3D printing -- 1.15.7 Autonomous vehicle -- 1.16 Conclusion -- References -- Chapter 2: Advances of deep learning and related applications -- 2.1 Introduction -- 2.2 Deep learning techniques -- 2.3 Multilayer perceptron -- 2.4 Convolutional neural network -- 2.5 Recurrent neural network -- 2.6 Long-term short-term memory -- 2.7 GRU -- 2.8 Autoencoders -- 2.9 Attention mechanism -- 2.10 Deep generative models -- 2.11 Restricted Boltzmann machine -- 2.12 Deep belief network -- 2.13 Modern deep learning platforms -- 2.13.1 PyTorch -- 2.13.2 TensorFlow -- 2.13.3 Keras -- 2.13.4 Caffe (Convolutional architecture for fast feature embedding) and Caffe2 -- 2.13.5 Deeplearning4j -- 2.13.6 Theano -- 2.13.7 Microsoft cognitive toolkit (CNTK) -- 2.14 Challenges of deep learning -- 2.15 Applications of deep learning -- 2.16 Conclusion -- References -- Chapter 3: Machine learning for big data and neural networks -- 3.1 Introduction -- 3.2 Machine learning and fundamentals -- 3.2.1 Supervised learning -- 3.2.2 Decision trees -- 3.2.3 Linear regression -- 3.2.4 Naive Bayes -- 3.2.5 Logistic regression -- 3.3 Unsupervised learning -- 3.3.1 K-Means algorithm -- 3.3.2 Principal component analysis -- 3.4 Reinforcement learning -- 3.5 Machine learning in large-scale data -- 3.6 Data analysis in big data -- 3.7 Predictive modelling -- 3.7.1 Understanding customer behavior and preferences -- 3.7.2 The role of supply chain and performance management in organizational success -- 3.7.3 Management of quality and enhancement -- 3.7.4 Risk mitigation and detection of fraud -- 3.8 Neural networks -- 3.8.1 Artificial neural network -- 3.8.2 RNN -- 3.8.3 CNN -- 3.8.4 Deep learning using convolutional neural networks to find building defects -- 3.9 Data generation and manipulation -- 3.9.1 Generative Adversarial Networks…”