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Deep Learning in Healthcare. 2. Cryptography and Security. 3. IoT and Wireless Sensor Networks. 4. Energy and Environment using AI &ML. 5. Artificial Intelligence Applications. 6. Physics and Engineering using Deep Learning & IOT. 7. Emerging Technologies using Deep Learning & IOT. 8. Data Science and Optimization. 9. Social Impact and Applications using AI &ML. 330 $aThis book explores the critical challenges and emerging trends in Information, Communication, and Computing Technology (ICCT). It provides a comprehensive overview of the key issues facing these rapidly evolving fields, from data security and privacy to advancements in artificial intelligence, communication networks, and quantum computing. 606 $aComputer science 606 $aArtificial intelligence 615 0$aComputer science. 615 0$aArtificial intelligence. 676 $a004 701 $aKannadhasan$b S$01741488 701 $aKannan$b A. Rajiv$01776473 701 $aSivakumar$b P$01776474 701 $aVennila$b V$01776475 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910909268503321 996 $aChallenges in Information, Communication and Computing Technology$94294252 997 $aUNINA LEADER 06204nam 2201201z- 450 001 9910557314603321 005 20220111 035 $a(CKB)5400000000042709 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/77117 035 $a(oapen)doab77117 035 $a(oapen)77117 035 $a(EXLCZ)995400000000042709 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNumerical Simulation in Biomechanics and Biomedical Engineering 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 online resource (300 p.) 311 08$a3-0365-2211-5 311 08$a3-0365-2212-3 330 $aIn the first contribution, Morbiducci and co-workers discuss the theoretical and methodological bases supporting the Lagrangian- and Euler-based methods, highlighting their application to cardiovascular flows. The second contribution, by the Ansoﾌ］ and van Lenthe groups, proposes an automated virtual bench test for evaluating the stability of custom shoulder implants without the necessity of mechanical testing. Urdeitx and Doweidar, in the third paper, also adopt the finite element method for developing a computational model aim to study cardiac cell behavior under mechano-electric stimulation. In the fourth contribution, Ayensa-Jimeﾌ］ez et al. develop a methodology to approximate the multidimensional probability density function of the parametric analysis obtained developing a mathematical model of the cancer evolution. The fifth paper is oriented to the topological data analysis; the group of Cueto and Chinesta designs a predictive model capable of estimating the state of drivers using the data collected from motion sensors. In the sixth contribution, the Ohayon and Finet group uses wall shear stress-derived descriptors to study the role of recirculation in the arterial restenosis due to different malapposed and overlapping stent conditions. In the seventh contribution, the research group of Antoﾌ］ demonstrates that the simulation time can be reduced for cardiovascular numerical analysis considering an adequate geometry-reduction strategy applicable to truncated patient specific artery. In the eighth paper, Grasa and Calvo present a numerical model based on the finite element method for simulating extraocular muscle dynamics. The ninth paper, authored by Kahla et al., presents a mathematical mechano-pharmaco-biological model for bone remodeling. Martiﾌ］ez, Penﾌヂ, and co-workers propose in the tenth paper a methodology to calibrate the dissection properties of aorta layer, with the aim of providing useful information for reliable numerical tools. In the eleventh contribution, Martiﾌ］ez-Bocanegra et al. present the structural behavior of a foot model using a detailed finite element model. The twelfth contribution is centered on the methodology to perform a finite, element-based, numerical model of a hydroxyapatite 3D printed bone scaffold. In the thirteenth paper, Talygin and Gorodkov present analytical expressions describing swirling jets for cardiovascular applications. In the fourteenth contribution, Schenkel and Halliday propose a novel non-Newtonian particle transport model for red blood cells. Finally, Zurita et al. propose a parametric numerical tool for analyzing a silicone customized 3D printable trachea-bronchial prosthesis. 606 $aTechnology: general issues$2bicssc 610 $a3D model 610 $a3D printing 610 $a3D scaffold 610 $aadditive manufacturing 610 $aaortic dissection 610 $abiomechanics 610 $ablood flow modelling 610 $abone disorders 610 $abone physiology 610 $abone tissue engineering 610 $acardiac cell 610 $acardiac muscle tissue 610 $acardiomyocyte 610 $acell dynamics 610 $acohesive zone model 610 $acomputational cost analysis 610 $acomputational fluid dynamics 610 $acopulas 610 $acustomized prosthesis 610 $adelamination tests 610 $adesign of experiments 610 $adivergence 610 $aelectrical stimulation 610 $aexplicit FEM 610 $afinite element analysis 610 $afinite element method 610 $afinite element modelling 610 $afixed points 610 $afoot and ankle model 610 $afoot finite element method 610 $aglioblastoma multiforme 610 $ahaemorheology 610 $ahemodynamics 610 $ahepatic artery 610 $aimplant design 610 $aimplicit FEM 610 $ain-silico 610 $aliver cancer 610 $amachine learning 610 $amalapposition 610 $amanifolds 610 $amathematical model 610 $amathematical modelling 610 $amicromotion 610 $aMorse theory 610 $aNavier-Stokes equations 610 $anumerical fluid mechanics 610 $aoverlap 610 $aparametric model 610 $aparticle transport 610 $apatient specific 610 $apersonalized medicine 610 $aplantar pressure 610 $aporcine aorta 610 $apotential swirling flow 610 $aradioembolization 610 $areverse shoulder arthroplasty 610 $aseparated mesh 610 $ashared nodes 610 $ashoulder implant stability 610 $askeletal muscle 610 $asmart driving 610 $astenosis 610 $astent 610 $athrombosis 610 $atime series 610 $atopological data analysis 610 $atornado-like jets 610 $atracheobronchial stent 610 $aunsteady swirling flow 610 $avascular mechanics 615 7$aTechnology: general issues 700 $aMalveﾌ$b Mauro$4edt 702 $aMalveﾌ$b Mauro$4oth 906 $aBOOK 912 $a9910557314603321 996 $aNumerical Simulation in Biomechanics and Biomedical Engineering$93021089 997 $aUNINA