LEADER 03465nam 22004693 450 001 9910838217603321 005 20230629222249.0 010 $a84-11-22011-7 035 $a(MiAaPQ)EBC29195687 035 $a(Au-PeEL)EBL29195687 035 $a(CKB)21547508500041 035 $a(NjHacI)9921547508500041 035 $a(EXLCZ)9921547508500041 100 $a20220422d2021 uy 0 101 0 $aspa 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aInvestigación en el ámbito Escolar 205 $a1st ed. 210 1$aMadrid :$cDykinson, S.L.,$d2021. 210 4$d©2021. 215 $a1 online resource (680 pages) 311 08$aPrint version: Simón Márquez, María del Mar Investigación en el ámbito Escolar: Variables Psicológicas y Educativas Madrid : Dykinson, S.L.,c2021 327 $aFront Matter -- Table of Contents -- CAPI?TULO 1 GEOGRAFI?A Y REDES SOCIALES: EXPERIENCIAS DE INNOVACIO?N DOCENTE CON NUEVAS TECNOLOGI?AS PARA LA ENSEN?ANZA ONLINE -- CAPI?TULO 2 IMPLICACIO?N DEL ALUMNADO, AUTONOMI?A EN EL APRENDIZAJE Y TIPO DE EVALUACIO?N EN CLASE DE LENGUA ESPAN?OLA: UN ESTUDIO COMPARADO EN CONTEXTOS DE APRENDIZAJE VIRTUALES UNIVERSITARIOS -- CAPI?TULO 3 APLICACIO?N DE LAS NUEVAS TECNOLOGI?AS Y TE?CNICAS DE INTELIGENCIA ARTIFICIAL PARA LA TUTORIZACIO?N Y PREVENCIO?N DEL FRACASO EN ALUMNOS UNIVERSITARIOS -- CAPI?TULO 4 EDUCACIO?N MUSICAL EN LA FORMACIO?N DE MAESTROS/AS: CO?MO BAILA TU CEREBRO -- CAPI?TULO 5 INTELIGENCIA EMOCIONAL FAMILIAR Y CAPACIDAD DE REGULACIO?N EN ADOLESCENTES EN TIEMPOS DE COVID-19 -- CAPI?TULO 6 VIAJAR EN EL TIEMPO MEDIANTE REALIDAD VIRTUAL: UNA EXPERIENCIA INMERSIVA PARA LA ENSEN?ANZA DE GEOGRAFI?A E HISTORIA -- CAPI?TULO 7 COMPARATIVA DEL EMPLEO DE LOS CUENTOS INFANTILES ENTRE FUTUROS MAESTROS Y MAESTROS EN ACTIVO -- CAPI?TULO 60 TECNOESTRE?S EN EL CONTEXTO EDUCATIVO: UNA REVISIO?N SISTEMA?TICA -- CAPI?TULO 61 ESTRATEGIAS EDUCATIVAS EN EL A?MBITO ESCOLAR PARA FAVORECER LA IGUALDAD DE GE?NERO Y UNA CIUDADANI?A GLOBAL -- Back Matter. 330 $aNos encontramos en un momento de grandes y ra?pidos cambios, lo que dentro del a?mbito educativo se traduce en la necesidad de adaptacio?n a los avances tecnolo?gicos y de afrontar los diferentes retos educativos. En la actualidad, la tarea docente exige mucho ma?s esfuerzo y dedicacio?n que en an?os anteriores. Pues las aulas son ma?s diversas, la administracio?n se ha vuelto ma?s demandante y las familias del alumnado tambie?n reclaman atencio?n. Las distintas investigaciones coinciden en que la innovacio?n es la u?nica vi?a efectiva para dar respuesta a estas exigencias educativas, sin embargo, existen centros que son referentes en cuestiones de innovacio?n y, por otra parte, un nu?mero muy elevado continu?a aferrado a las metodologi?as dida?cticas tradicionales. 606 $aEducational psychology 606 $aSchool environment 615 0$aEducational psychology. 615 0$aSchool environment. 676 $a370.15 700 $aSimo?n Ma?rquez$b Mari?a del Mar.$01530368 701 $aBarragán Martín$b Ana Belén$01730021 701 $aMartos Martínez$b África$01730022 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910838217603321 996 $aInvestigación en el ámbito Escolar$94140399 997 $aUNINA LEADER 04111nam 22005895 450 001 9910416084103321 005 20200825094902.0 010 $a981-15-6044-7 024 7 $a10.1007/978-981-15-6044-6 035 $a(CKB)4100000011401175 035 $a(MiAaPQ)EBC6318838 035 $a(DE-He213)978-981-15-6044-6 035 $a(PPN)250212994 035 $a(EXLCZ)994100000011401175 100 $a20200825d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aFog Data Analytics for IoT Applications$b[electronic resource] $eNext Generation Process Model with State of the Art Technologies /$fedited by Sudeep Tanwar 205 $a1st ed. 2020. 210 1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2020. 215 $a1 online resource (501 pages) 225 1 $aStudies in Big Data,$x2197-6503 ;$v76 311 $a981-15-6043-9 327 $aIntroduction -- Introduction to Fog data analytics for IoT applications -- Fog Data Analytics: Systematic Computational Classification and Procedural Paradigm -- Fog Computing: Building a Road to IoT with Fog Analytics -- Data Collection in Fog Data Analytics -- Mobile FOG Architecture Assisted Continuous Acquisition of Fetal ECG Data for Efficient Prediction -- Proposed Framework for Fog Computing to Improve Quality-of-Service in IoT applications -- Fog Data Based Statistical Analysis to Check Effects of Yajna and Mantra Science: Next Generation Health Practices -- Process Model for Fog Data Analytics for IoT Applications -- Medical Analytics Based on Artificial Neural Networks Using Cognitive Internet of Things. 330 $aThis book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. The exponential increase in sensors and smart gadgets (collectively referred as smart devices or Internet of things (IoT) devices) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud. Current research and development efforts generally focus on big data analytics and overlook the difficulty of facilitating fog data analytics (FDA). This book presents a model that addresses various research challenges, such as accessibility, scalability, fog nodes communication, nodal collaboration, heterogeneity, reliability, and quality of service (QoS) requirements, and includes case studies demonstrating its implementation. Focusing on FDA in IoT and requirements related to Industry 4.0, it also covers all aspects required to manage the complexity of FDA for IoT applications and also develops a comprehensive taxonomy. 410 0$aStudies in Big Data,$x2197-6503 ;$v76 606 $aComputational intelligence 606 $aBig data 606 $aApplication software 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120 606 $aBig Data/Analytics$3https://scigraph.springernature.com/ontologies/product-market-codes/522070 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 615 0$aComputational intelligence. 615 0$aBig data. 615 0$aApplication software. 615 14$aComputational Intelligence. 615 24$aBig Data. 615 24$aBig Data/Analytics. 615 24$aInformation Systems Applications (incl. 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