This book examines the origins and dynamical characteristics of atmospheric inertia-gravity waves in the Antarctic mesosphere. Gravity waves are relatively small-scale atmospheric waves with a restoring force of buoyancy that can transport momentum upward from the troposphere to the middle atmosphere. In previous studies, the dynamical characteristics of mesospheric gravity waves have not been fully examined using numerical simulations, since performing a numerical simulation with a high resolution and a high model-top requires considerable computational power. However, recent advances in computational capabilities have allowed us to perform numerical simulations using atmospheric general circulation models, which cover the troposphere to the mesosphere with a sufficiently fine horizontal resolution to resolve small-scale gravity waves. The book first describes the simulation of mesospheric gravity waves using a high-resolution non-hydrostatic atmospheric model with a high model top. The accuracy of the numerical results was confirmed by the first Mesosphere-Stratosphere-Troposphere/Incoherent Scattering (MST/IS) radar observation in the Antarctic. It also depicts the origins and propagation processes of mesospheric gravity waves on the basis of the results of the high-resolution numerical model. The behaviors of mesospheric gravity waves can be clearly explained using both fundamental and cutting-edge theories of fluid dynamics

As the healthcare industry continues to expand, it must utilize technology to ensure efficiencies are maintained. Healthcare needs to move in a direction where computational methods and algorithms can relieve the routine work of medical doctors, leaving them more time to carry out more important and skilled tasks such as surgery. Computational Methods and Algorithms for Medicine and Optimized Clinical Practice discusses some of the most interesting aspects of theoretical and applied research covering complementary facets of computational methods and algorithms to achieve greater efficiency and support medical personnel. Featuring research on topics such as healthcare reform, artificial intelligence, and disease detection, this book will particularly appeal to medical professionals and practitioners, hospitals, administrators, students, researchers, and academicians.

Even though many data analytics tools have been developed in the past years, their usage in the field of cyber twin warrants new approaches that consider various aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real-time analysis, sampling, dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection. Further study is required to fully understand the opportunities, benefits, and difficulties of data analytics and the internet of things in today's modern world. New Approaches to Data Analytics and Internet of Things Through Digital Twin considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. Covering key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

This book explores the main elements of e-Democracy, the term normally used to describe the implementation of democratic government processes by electronic means. It provides insights into the main technological and human issues regarding governance, government, participation, inclusion, empowerment, procurement and, last but not least, ethical and privacy issues. Its main aim is to bridge the gap between technological solutions, their successful implementation, and the fruitful utilization of the main set of e-Services totally or partially delivered by governments or non-government organizations. Today, various parameters actively influence e-Services' success or failure: cultural aspects, organisational issues, bureaucracy and workflows, infrastructure and technology in general, user habits, literacy, capacity or merely interaction design. This includes having a significant population of citizens who are willing and able to adopt and use online services; as well as developing the managerial and technical capability to implement applications that meet citizens' needs. This book helps readers understand the mutual dependencies involved; further, a selection of success stories and failures, duly commented on, enables readers to identify the right approach to innovation in governmental e-Services. With its balanced humanistic and technological approach, the book mainly targets public authorities, decision-makers, stakeholders, solution developers, and graduate students.

The unification of symbolist and connectionist models is a major trend in AI. The key is to keep the symbolic semantics unchanged. Unfortunately, present embedding approaches cannot. The approach in this book makes the unification possible. It is indeed a new and promising approach in AI. -Bo Zhang, Director of AI Institute, Tsinghua It is indeed wonderful to see the reviving of the important theme Nural Symbolic Model. Given the popularity and prevalence of deep learning, symbolic processing is often neglected or downplayed. This book confronts this old issue head on, with a historical look, incorporating recent advances and new perspectives, thus leading to promising new methods and approaches. -Ron Sun (RPI), on Governing Board of Cognitive Science Society Both for language and humor, approaches like those described in this book are the way to snickerdoodle wombats. -Christian F. Hempelmann (Texas A&M-Commerce) on Executive Board of International Society for Humor Studies

This book is a compilation of advanced research and applications on robotic item picking and warehouse automation for e-commerce applications. The works in this book are based on results that came out of the Amazon Robotics Challenge from 2015-2017, which focused on fully automated item picking in a warehouse setting, a topic that has been assumed too complicated to solve or has been reduced to a more tractable form of bin picking or single-item table top picking. The book's contributions reveal some of the top solutions presented from the 50 participant teams. Each solution works to address the time-constraint, accuracy, complexity, and other difficulties that come with warehouse item picking. The book covers topics such as grasping and gripper design, vision and other forms of sensing, actuation and robot design, motion planning, optimization, machine learning and artificial intelligence, software engineering, and system integration, among others. Through this book, the authors describe how robot systems are built from the ground up to do a specific task, in this case, item picking in a warehouse setting. The compiled works come from the best robotics research institutions and companies globally.

As global communities are attempting to transform into more efficient and technologically-advanced metropolises, artificial intelligence (AI) has taken a firm grasp on various professional fields. Technology used in these industries is transforming by introducing intelligent techniques including machine learning, cognitive computing, and computer vision. This has raised significant attention among researchers and practitioners on the specific impact that these smart technologies have and what challenges remain. Applications of Artificial Intelligence for Smart Technology is a pivotal reference source that provides vital research on the implementation of advanced technological techniques in professional industries through the use of AI. While highlighting topics such as pattern recognition, computational imaging, and machine learning, this publication explores challenges that various fields currently face when applying these technologies and examines the future uses of AI. This book is ideally designed for researchers, developers, managers, academicians, analysts, students, and practitioners seeking current research on the involvement of AI in professional practices.

Addresses different scenarios when finding complex relationships in spatiotemporal data by modeling them as graphs, giving readers a comprehensive synopsis on two successful partition-based algorithms designed by the authors.

Drawn to Life is a two-volume collection of the legendary lectures of long-time Disney animator Walt Stanchfield. For over 20 years, Walt mentored a new generation of animators at the Walt Disney Studios and influenced such talented artists such as Tim Burton, Brad Bird, Glen Keane, and Andreas Deja. His writing and drawings have become must-have lessons for fine artists, film professionals, animators, and students looking for inspiration and essential training in drawing and the art of animation. Written by Walt Stanchfield (1919–2000), who began work for the Walt Disney Studios in the 1950s. His work can be seen in films such as Sleeping Beauty, The Jungle Book, 101 Dalmatians, and Peter Pan. Edited by Disney Legend and Oscar®-nominated producer Don Hahn, whose credits include the classic Beauty and the Beast, The Lion King, and Hunchback of Notre Dame.

Electronic participation is an emerging and growing research area that makes use of internet solutions to enhance citizens' participation in government processes in order to provide a fair and efficient society. This book examines recommender-system technologies and voting advice applications as tools to enable electronic citizen participation during election campaigns. Further, making use of fuzzy classification, it provides an evaluation framework for eParticipation. A dynamic voting advice application developed for the 2017 Ecuador national election serves as a real-world case study to introduce readers to the practical implementation and evaluation issues. The book concludes with a comprehensive analysis of the 2017 election project based on altmetrics, Google Analytics and statistics from the case study.

Smart Homes (SH) offer a promising approach to assisted living for the ageing population. Yet the main obstacle to the rapid development and deployment of Smart Home (SH) solutions essentially arises from the nature of the SH field, which is multidisciplinary and involves diverse applications and various stakeholders. Accordingly, an alternative to a one-size-fits-all approach is needed in order to advance the state of the art towards an open SH infrastructure. This book makes a valuable and critical contribution to smart assisted living research through the development of new effective, integrated, and interoperable SH solutions. It focuses on four underlying aspects: (1) Sensing and Monitoring Technologies; (2) Context Interference and Behaviour Analysis; (3) Personalisation and Adaptive Interaction, and (4) Open Smart Home and Service Infrastructures, demonstrating how fundamental theories, models and algorithms can be exploited to solve real-world problems. This comprehensive and timely book offers a unique and essential reference guide for policymakers, funding bodies, researchers, technology developers and managers, end users, carers, clinicians, healthcare service providers, educators and students, helping them adopt and implement smart assisted living systems.

This book contains selected papers presented at the 15th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School on Privacy and Identity Management, held in Maribor, Slovenia, in September 2020.*The 13 full papers included in this volume were carefully reviewed and selected from 21 submissions. Also included is a summary paper of a tutorial. As in previous years, one of the goals of the IFIP Summer School was to encourage the publication of thorough research papers by students and emerging scholars. The papers combine interdisciplinary approaches to bring together a host of perspectives, such as technical, legal, regulatory, socio-economic, social or societal, political, ethical, anthropological, philosophical, or psychological perspectives. *The summer school was held virtually.

The past few years have seen a major change in computing systems, as growing data volumes and stalling processor speeds require more and more applications to scale out to clusters. Today, a myriad data sources, from the Internet to business operations to scientific instruments, produce large and valuable data streams. However, the processing capabilities of single machines have not kept up with the size of data. As a result, organizations increasingly need to scale out their computations over clusters. At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too. This book, a revised version of the 2014 ACM Dissertation Award winning dissertation, proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Whereas early cluster computing systems, like MapReduce, handled batch processing, our architecture also enables streaming and interactive queries, while keeping MapReduce's scalability and fault tolerance. And whereas most deployed systems only support simple one-pass computations (e.g., SQL queries), ours also extends to the multi-pass algorithms required for complex analytics like machine learning. Finally, unlike the specialized systems proposed for some of these workloads, our architecture allows these computations to be combined, enabling rich new applications that intermix, for example, streaming and batch processing. We achieve these results through a simple extension to MapReduce that adds primitives for data sharing, called Resilient Distributed Datasets (RDDs). We show that this is enough to capture a wide range of workloads. We implement RDDs in the open source Spark system, which we evaluate using synthetic and real workloads. Spark matches or exceeds the performance of specialized systems in many domains, while offering stronger fault tolerance properties and allowing these workloads to be combined. Finally, we examine the generality of RDDs from both a theoretical modeling perspective and a systems perspective. This version of the dissertation makes corrections throughout the text and adds a new section on the evolution of Apache Spark in industry since 2014. In addition, editing, formatting, and links for the references have been added.

This book presents best selected research papers presented at the International Conference on Recent Trends in Communication and Intelligent Systems (ICRTCIS 2020), organized by Arya College of Engineering and IT, Jaipur, on 20-21 November 2020. It discusses the latest technologies in communication and intelligent systems, covering various areas of communication engineering, such as signal processing, VLSI design, embedded systems, wireless communications, and electronics and communications in general. Featuring work by leading researchers and technocrats, the book serves as a valuable reference resource for young researchers and academics as well as practitioners in industry.

This book offers a comprehensive overview of the challenges in hydrological modeling. Hydrology, on both a local and global scale, has undergone dramatic changes, largely due to variations in climate, population growth and the associated land-use and land-cover changes. Written by experts in the field, the book provides decision-makers with a better understanding of the science, impacts, and consequences of these climate and land-use changes on hydrology. Further, offering insights into how the changing behavior of hydrological processes, related uncertainties and their evolution affect the modeling process, it is of interest for all researchers and practitioners using hydrological modeling.

The concept of virtual worlds is strongly related to the current innovations of new media communication. As such, it is increasingly imperative to understand the criteria for creating virtual worlds as well as the evolution in system architecture, information visualization and human interaction. Meta-plasticity in Virtual Worlds: Aesthetics and Semantics Concepts provides in-depth coverage of the state-of-the-art among the best international research experiences of virtual world concept creations from a wide range of media culture fields, at the edge of artistic and scientific inquiry and emerging technologies. Written for professionals, researchers, artists and designers, this text is a perfect companion for those who want to improve their understanding of the strategic role of virtual worlds within the development of digital communication.

This book provides a survey on research, development, and trends in innovative computing in communications engineering and computer science. It features selected and expanded papers from the EAI International Conference on Computer Science and Engineering 2018 (COMPSE 2018), with contributions by top global researchers and practitioners in the field. The content is of relevance to computer science graduates, researchers and academicians in computer science and engineering. The authors discuss new technologies in computer science and engineering that have reduced the dimension of data coverage worldwide, reducing the gaps and coverage of domains globally. They discuss how these advances have also contributed to strength in prediction, analysis, and decision in the areas such as Technology, Management, Social Computing, Green Computing, and Telecom. Contributions show how nurturing the research in technology and computing is essential to finding the right pattern in the ocean of data. Focuses on research areas of innovative computing and its application in engineering and technology; Includes contributions from researchers in computing and engineering from around the world; Features selected and expanded papers from EAI International Conference on Computer Science and Engineering 2018 (COMPSE 2018).

The book is logically divided into 5 main categories with each category representing a major skill set required by most security professionals:
1. Coding The ability to program and script is quickly becoming a mainstream requirement for just about everyone in the security industry. This section covers the basics in coding complemented with a slue of programming tips and tricks in C/C++, Java, Perl and NASL.
2. Sockets The technology that allows programs and scripts to communicate over a network is sockets. Even though the theory remains the same communication over TCP and UDP, sockets are implemented differently in nearly ever language.
3. Shellcode Shellcode, commonly defined as bytecode converted from Assembly, is utilized to execute commands on remote systems via direct memory access.
4. Porting Due to the differences between operating platforms and language implementations on those platforms, it is a common practice to modify an original body of code to work on a different platforms. This technique is known as porting and is incredible useful in the real world environments since it allows you to not recreate the wheel.
5. Coding Tools The culmination of the previous four sections, coding tools brings all of the techniques that you have learned to the forefront. With the background technologies and techniques you will now be able to code quick utilities that will not only make you more productive, they will arm you with an extremely valuable skill that will remain with you as long as you make the proper time and effort dedications.
*Contains never before seen chapters on writing and automating exploits on windows systems with all-new exploits.
*Perform zero-day exploit forensics by reverse engineering malicious code.
*Provides working code and scripts in all of the most common programming languages for readers to use TODAY to defend their networks."

Going Virtual: Distributed Communities in Practice contributes to the understanding of how more subtle kinds of knowledge can be managed in a distributed international environment. It describes academic work in the field of Knowledge Management, with a specific focus on the management of knowledge which cannot be managed by the normal capture-codify-store approach and hopes to answer the question, "what is the nature of the more 'subtle' kind of knowledge and how can it be managed in the distributed environment?"

This book summarizes years of research in the field of fuzzy relational programming, with a special emphasis on geometric models. It discusses the state-of-the-art in fuzzy relational geometric problems, together with key open issues that must be resolved to achieve a more efficient application of this method. Though chiefly based on research conducted by the authors, who were the first to introduce fuzzy geometric problems, it also covers important findings obtained in the field of linear and non-linear programming. Thanks to its balance of basic and advanced concepts, and its wealth of practical examples, the book offers a valuable guide for both newcomers and experienced researcher in the fields of soft computing and mathematical optimization.

This book features a collection of high-quality research papers presented at the International Conference on Intelligent and Cloud Computing (ICICC 2019), held at Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India, on December 20, 2019. Including contributions on system and network design that can support existing and future applications and services, it covers topics such as cloud computing system and network design, optimization for cloud computing, networking, and applications, green cloud system design, cloud storage design and networking, storage security, cloud system models, big data storage, intra-cloud computing, mobile cloud system design, real-time resource reporting and monitoring for cloud management, machine learning, data mining for cloud computing, data-driven methodology and architecture, and networking for machine learning systems.

This book presents a unified mathematical treatment of diverse problems in the general domain of robotics and associated fields using Clifford or geometric alge- bra. By addressing a wide spectrum of problems in a common language, it offers both fresh insights and new solutions that are useful to scientists and engineers working in areas related with robotics. It introduces non-specialists to Clifford and geometric algebra, and provides ex- amples to help readers learn how to compute using geometric entities and geomet- ric formulations. It also includes an in-depth study of applications of Lie group theory, Lie algebra, spinors and versors and the algebra of incidence using the universal geometric algebra generated by reciprocal null cones. Featuring a detailed study of kinematics, differential kinematics and dynamics using geometric algebra, the book also develops Euler Lagrange and Hamiltoni- ans equations for dynamics using conformal geometric algebra, and the recursive Newton-Euler using screw theory in the motor algebra framework. Further, it comprehensively explores robot modeling and nonlinear controllers, and discusses several applications in computer vision, graphics, neurocomputing, quantum com- puting, robotics and control engineering using the geometric algebra framework. The book also includes over 200 exercises and tips for the development of future computer software packages for extensive calculations in geometric algebra, and a entire section focusing on how to write the subroutines in C++, Matlab and Maple to carry out efficient geometric computations in the geometric algebra framework. Lastly, it shows how program code can be optimized for real-time computations. An essential resource for applied physicists, computer scientists, AI researchers, roboticists and mechanical and electrical engineers, the book clarifies and demon- strates the importance of geometric computing for building autonomous systems to advance cognitive systems research.

This book highlights new advances in biometrics using deep learning toward deeper and wider background, deeming it "Deep Biometrics". The book aims to highlight recent developments in biometrics using semi-supervised and unsupervised methods such as Deep Neural Networks, Deep Stacked Autoencoder, Convolutional Neural Networks, Generative Adversary Networks, and so on. The contributors demonstrate the power of deep learning techniques in the emerging new areas such as privacy and security issues, cancellable biometrics, soft biometrics, smart cities, big biometric data, biometric banking, medical biometrics, healthcare biometrics, and biometric genetics, etc. The goal of this volume is to summarize the recent advances in using Deep Learning in the area of biometric security and privacy toward deeper and wider applications. Highlights the impact of deep learning over the field of biometrics in a wide area; Exploits the deeper and wider background of biometrics, such as privacy versus security, biometric big data, biometric genetics, and biometric diagnosis, etc.; Introduces new biometric applications such as biometric banking, internet of things, cloud computing, and medical biometrics.