This book constitutes the Proceedings of The Third International Conference on Smart Vehicular Technology, Transportation, Communication and Applications (VTCA 2019), Arad, Romania, held on October 15-18 October 2019 in Arad, Romania. This edition is technically co-sponsored by "Aurel Vlaicu" University of Arad, Romania, Southwest Jiaotong University, Fujian University of Technology, Chang'an University, Shandong University of Science and Technology, Fujian Provincial Key Lab of Big Data Mining and Applications, and National Demonstration Center for Experimental Electronic Information and Electrical Technology Education (Fujian University of Technology), China, Romanian Academy and General Association of Engineers in Romania - Arad Section. The book covers a range of topics including algorithms for optimization, video processing, parking management, IoT, software testing, cryptanalysis, NLP, CNN, wireless sensors network, adaptive security, data protection, green transportation, AI, smart cities, train control, analytic hierarchy process, big data, car following model, etc. The books help to disseminate the knowledge about some active research directions in the field Vehicle Technology and Communication. The book provides useful information to professors, researchers and graduated students in area of Vehicle Technology and Communication.

This book discusses the smooth integration of optical and RF networks in 5G and beyond (5G+) heterogeneous networks (HetNets), covering both planning and operational aspects. The integration of high-frequency air interfaces into 5G+ wireless networks can relieve the congested radio frequency (RF) bands. Visible light communication (VLC) is now emerging as a promising candidate for future generations of HetNets. Heterogeneous RF-optical networks combine the high throughput of visible light and the high reliability of RF. However, when implementing these HetNets in mobile scenarios, several challenges arise from both planning and operational perspectives. Since the mmWave, terahertz, and visible light bands share similar wave propagation characteristics, the concepts presented here can be broadly applied in all such bands. To facilitate the planning of RF-optical HetNets, the authors present an algorithm that specifies the joint optimal densities of the base stations by drawing on stochastic geometry in order to satisfy the users' quality-of-service (QoS) demands with minimum network power consumption. From an operational perspective, the book explores vertical handovers and multi-homing using a cooperative framework. For vertical handovers, it employs a data-driven approach based on deep neural networks to predict abrupt optical outages; and, on the basis of this prediction, proposes a reinforcement learning strategy that ensures minimal network latency during handovers. In terms of multi-homing support, the authors examine the aggregation of the resources from both optical and RF networks, adopting a two-timescale multi-agent reinforcement learning strategy for optimal power allocation. Presenting comprehensive planning and operational strategies, the book allows readers to gain an in-depth grasp of how to integrate future coexisting networks at high-frequency bands in a cooperative manner, yielding reliable and high-speed 5G+ HetNets.

This book highlights papers presented at the Second International Conference on Smart Vehicular Technology, Transportation, Communication and Applications (VTCA 2018), which was held at Mount Emei, Sichuan Province, China from 25 to 28 October 2018. The conference was co-sponsored by Springer, Southwest Jiaotong University, Fujian University of Technology, Chang'an University, Shandong University of Science and Technology, Fujian Provincial Key Lab of Big Data Mining and Applications, and the National Demonstration Center for Experimental Electronic Information and Electrical Technology Education (Fujian University of Technology). The conference was intended as an international forum for researchers and professionals engaged in all areas of smart vehicular technology, vehicular transportation, vehicular communication, and applications.

This book highlights papers presented at the Second International Conference on Smart Vehicular Technology, Transportation, Communication and Applications (VTCA 2018), which was held at Mount Emei, Sichuan Province, China from 25 to 28 October 2018. The conference was co-sponsored by Springer, Southwest Jiaotong University, Fujian University of Technology, Chang'an University, Shandong University of Science and Technology, Fujian Provincial Key Lab of Big Data Mining and Applications, and the National Demonstration Center for Experimental Electronic Information and Electrical Technology Education (Fujian University of Technology). The conference was intended as an international forum for researchers and professionals engaged in all areas of smart vehicular technology, vehicular transportation, vehicular communication, and applications.

This book presents papers from the First International Conference on Smart Vehicular Technology, Transportation, Communication and Applications (VTCA 2017). Held from 6 to 8 November 2017 in Kaohsiung, Taiwan, the conference was co-sponsored by Springer, Fujian University of Technology in China, Fujian Provincial Key Laboratory of Digital Equipment, Fujian Provincial Key Lab of Big Data Mining and Applications, and National Kaohsiung University of Applied Sciences in Taiwan. The book is a valuable resource for researchers and professionals engaged in all areas of smart vehicular technology, vehicular transportation, vehicular communication, and applications.

3D Bioprinting in Tissue and Organ Regeneration covers state-of-the-art advances and applications in bioprinting. Beginning with an introduction that considers techniques, bioinks and construct design, the authors then move onto a detailed review of applications of bioprinting in different biomedical fields (skin, cartilage, bone, vascularized tissue, etc.). This is followed by a chapter overview of intraoperative bioprinting, which is widely considered one of the important future trends in this area. Finally, the authors tackle ethical and regulation concerns regarding the utilization of bioprinting. The book is written by three global experts for an audience of students and professionals with some basic knowledge of bioprinting, but who seek a deeper understanding of the biomedical applications involved in bioprinting.

This book includes selected papers from the fourth International Conference on Smart Vehicular Technology, Transportation, Communication and Applications (VTCA 2021), held in Chengdu City, Sichuan Province, China, during May 22-24, 2021. The conference is technically co-sponsored by Southwest Jiaotong University, Shandong University of Science and Technology, Fujian University of Technology, and Minjiang University. The book includes research works from engineers, researchers, and practitioners interested in the advances and applications in the field of vehicle technology and communication. The book covers four tracks, namely (1) vehicular networking security, (2) vehicular electronics, (3) intelligent transportation systems, and (4) smart vehicular communication networks and telematics.

This book discusses the smooth integration of optical and RF networks in 5G and beyond (5G+) heterogeneous networks (HetNets), covering both planning and operational aspects. The integration of high-frequency air interfaces into 5G+ wireless networks can relieve the congested radio frequency (RF) bands. Visible light communication (VLC) is now emerging as a promising candidate for future generations of HetNets. Heterogeneous RF-optical networks combine the high throughput of visible light and the high reliability of RF. However, when implementing these HetNets in mobile scenarios, several challenges arise from both planning and operational perspectives. Since the mmWave, terahertz, and visible light bands share similar wave propagation characteristics, the concepts presented here can be broadly applied in all such bands. To facilitate the planning of RF-optical HetNets, the authors present an algorithm that specifies the joint optimal densities of the base stations by drawing on stochastic geometry in order to satisfy the users' quality-of-service (QoS) demands with minimum network power consumption. From an operational perspective, the book explores vertical handovers and multi-homing using a cooperative framework. For vertical handovers, it employs a data-driven approach based on deep neural networks to predict abrupt optical outages; and, on the basis of this prediction, proposes a reinforcement learning strategy that ensures minimal network latency during handovers. In terms of multi-homing support, the authors examine the aggregation of the resources from both optical and RF networks, adopting a two-timescale multi-agent reinforcement learning strategy for optimal power allocation. Presenting comprehensive planning and operational strategies, the book allows readers to gain an in-depth grasp of how to integrate future coexisting networks at high-frequency bands in a cooperative manner, yielding reliable and high-speed 5G+ HetNets.

The differential quadrature hierarchical finite element method (DQHFEM) was proposed by Bo Liu. This method incorporated the advantages and the latest research achievements of the hierarchical finite element method (HFEM), the differential quadrature method (DQM) and the isogeometric analysis (IGA). The DQHFEM also overcame many limitations or difficulties of the three methods.This unique compendium systemically introduces the construction of various DQHFEM elements of commonly used geometric shapes like triangle, tetrahedrons, pyramids, etc. Abundant examples are also included such as statics and dynamics, isotropic materials and composites, linear and nonlinear problems, plates as well as shells and solid structures.This useful reference text focuses largely on numerical algorithms, but also introduces some latest advances on high order mesh generation, which often has been regarded as the major bottle neck for the wide application of high order FEM.

Leverage the power of Kubernetes to build an efficient software delivery pipeline. Key Features Learn about DevOps, containers, and Kubernetes all within one handy book A practical guide to container management and orchestration Learn how to monitor, log, and troubleshoot your Kubernetes applications Book DescriptionKubernetes has been widely adopted across public clouds and on-premise data centers. As we're living in an era of microservices, knowing how to use and manage Kubernetes is an essential skill for everyone in the IT industry. This book is a guide to everything you need to know about Kubernetes-from simply deploying a container to administrating Kubernetes clusters wisely. You'll learn about DevOps fundamentals, as well as deploying a monolithic application as microservices and using Kubernetes to orchestrate them. You will then gain an insight into the Kubernetes network, extensions, authentication and authorization. With the DevOps spirit in mind, you'll learn how to allocate resources to your application and prepare to scale them efficiently. Knowing the status and activity of the application and clusters is crucial, so we'll learn about monitoring and logging in Kubernetes. Having an improved ability to observe your services means that you will be able to build a continuous delivery pipeline with confidence. At the end of the book, you'll learn how to run managed Kubernetes services on three top cloud providers: Google Cloud Platform, Amazon Web Services, and Microsoft Azure. What you will learn Learn fundamental and advanced DevOps skills and tools Get a comprehensive understanding of containers Dockerize an application Administrate and manage Kubernetes cluster Extend the cluster functionality with custom resources Understand Kubernetes network and service mesh Implement Kubernetes logging and monitoring Manage Kubernetes services in Amazon Web Services, Google Cloud Platform,and Microsoft Azure Who this book is forThis book is for anyone who wants to learn containerization and clustering in a practical way using Kubernetes. No prerequisite skills are required, however, essential DevOps skill and public/private Cloud knowledge will accelerate the reading speed. If you're advanced, you can get a deeper understanding of all the tools and technique described in the book.

Learn to implement DevOps using Docker & Kubernetes. About This Book * Learning DevOps, container, and Kubernetes within one book. * Leverage Kubernetes as a platform to deploy, scale, and run containers efficiently. * A practical guide towards container management and orchestration Who This Book Is For This book is targeted for anyone, who wants to learn containerization and clustering in a practical way using Kubernetes. No prerequisite skills required, however, essential DevOps skill and public/private Cloud knowledge will accelerate the reading speed. If you're advanced readers, you can also get a deeper understanding of all the tools and technique described in the book. What You Will Learn * Learn fundamental and advanced DevOps skills and tools * Get a comprehensive understanding for container * Learn how to move your application to container world * Learn how to manipulate your application by Kubernetes * Learn how to work with Kubernetes in popular public cloud * Improve time to market with Kubernetes and Continuous Delivery * Learn how to monitor, log, and troubleshoot your application with Kubernetes In Detail Containerization is said to be the best way to implement DevOps. Google developed Kubernetes, which orchestrates containers efficiently and is considered the frontrunner in container orchestration. Kubernetes is an orchestrator that creates and manages your containers on clusters of servers. This book will guide you from simply deploying a container to administrate a Kubernetes cluster, and then you will learn how to do monitoring, logging, and continuous deployment in DevOps. The initial stages of the book will introduce the fundamental DevOps and the concept of containers. It will move on to how to containerize applications and deploy them into. The book will then introduce networks in Kubernetes. We then move on to advanced DevOps skills such as monitoring, logging, and continuous deployment in Kubernetes. It will proceed to introduce permission control for Kubernetes resources via attribute-based access control and role-based access control. The final stage of the book will cover deploying and managing your container clusters on the popular public cloud Amazon Web Services and Google Cloud Platform. At the end of the book, other orchestration frameworks, such as Docker Swarm mode, Amazon ECS, and Apache Mesos will be discussed. Style and approach Readers will be taken through fundamental DevOps skills and Kubernetes concept and administration with detailed examples. It introduces comprehensive DevOps topics, including microservices, automation tools, containers, monitoring, logging, continuous delivery, and popular public cloud environments. At each step readers will learn how to leverage Kubernetes in their everyday lives and transform their original delivery pipeline for fast and efficient delivery.

In this thesis, we revised and proposed several models and then used them to forecast the stock index. The first model is an improved version of the GM (1, 1) model by introducing two parameters. Then we revised the normal hybrid model G-ARMA by merging the ARMA model with the improved GM (1, 1) model. In order to overcome the drawback of directly modeling original stock index, we introduced wavelet methods into the revised G-ARMA model and named this new hybrid model WG-ARMA. Finally, we obtained the last hybrid model WPG-ARMA by replacing the wavelet transform with the wavelet packet decomposition. For hybrid models, we estimated parameters of the hybrid models as the whole instead of estimating parameters for each sub-model separately. To verify prediction performance of the models, we presented case studies for the models based on a leading Canadian stock index. The experimental results gave the rank of predictive ability in terms of the TAE, MPAE and DIR metrics as following: WPG-ARMA model, WG-ARMA model, revised G-ARMA model, improved GM (1, 1) model, and ARIMA model.