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Machine Learning
The book reviews core concepts of machine learning (ML) while focusing on modern applications. It is aimed at those who want to advance their understanding of ML by providing technical and practical insights. It does not use complicated mathematics to explain how to benefit from ML algorithms. Unlike the existing literature, this work provides the core concepts with emphasis on fresh ideas and real application scenarios. It starts with the basic concepts of ML and extends the concepts to the different deep learning algorithms. The book provides an introduction and main elements of evaluation tools with Python and walks you through the recent applications of ML in self-driving cars, cognitive decision making, communication networks, security, and signal processing. The concept of generative networks is also presented and focuses on GANs as a tool to improve the performance of existing algorithms. In summary, this book provides a comprehensive technological path from fundamental theories to the categorization of existing algorithms, covers state-of-the-art, practical evaluation tools and methods to empower you to use synthetic data to improve the performance of applications.
Nanoelectronic Device Applications Handbook
Nanoelectronic Device Applications Handbook gives a comprehensive snapshot of the state of the art in nanodevices for nanoelectronics applications. Combining breadth and depth, the book includes 68 chapters on topics that range from nano-scaled complementary metal–oxide–semiconductor (CMOS) devices through recent developments in nano capacitors and AlGaAs/GaAs devices. The contributors are world-renowned experts from academia and industry from around the globe. The handbook explores current research into potentially disruptive technologies for a post-CMOS world. These include: Nanoscale advances in current MOSFET/CMOS technology Nano capacitors for applications such as electronics packag...
Electrochemistry of Novel Materials for Energy Storage and Conversion
The papers included in this issue of ECS Transactions were originally presented in the symposium ¿Electrochemistry of Novel Materials for Energy Storage and Conversion¿, held during the 218th meeting of The Electrochemical Society, in Las Vegas, Nevada from October 10 to 15, 2010.
On the Electro-Chemo-Mechanical Coupling in Solid State Batteries and its Impact on Morphological Interface Stability
Solid state batteries with a lithium metal electrode are considered the next generation of high energy battery technology. Unfortunately, lithium metal is prone to harmful protrusion or dendrite growth which causes dangerous cell failure. Within this work the problem of protrusion growth is tackled by deriving a novel electro-chemo-mechanical theory tailored for binary solid state batteries which is then used to discuss the impact of mechanics on interface stability by numerical studies.
Advanced Two-Dimensional Material-Based Heterostructures in Sustainable Energy Storage Devices
Advanced Two-Dimensional Material-Based Heterostructures in Sustainable Energy Storage Devices provides a detailed overview of advances and challenges in the development of 2D materials for use in energy storage devices. It offers deep insight into the synthesis, characterization, and application of different 2D materials and their heterostructures in a variety of energy storage devices, focusing on new phenomena and enhanced electrochemistry. This book: Introduces 2D materials, synthesis methods, and characterization techniques Discusses application in a wide range of batteries and supercapacitors Offers perspectives on future investigations necessary to overcome existing challenges This comprehensive reference is written to guide researchers and engineers working to advance the technology of energy-efficient energy storage devices.
Future Trends of HPC in a Disruptive Scenario
The realization that the use of components off the shelf (COTS) could reduce costs sparked the evolution of the massive parallel computing systems available today. The main problem with such systems is the development of suitable operating systems, algorithms and application software that can utilise the potential processing power of large numbers of processors. As a result, systems comprising millions of processors are still limited in the applications they can efficiently solve. Two alternative paradigms that may offer a solution to this problem are Quantum Computers (QC) and Brain Inspired Computers (BIC). This book presents papers from the 14th edition of the biennial international confe...
Machine Learning, Optimization, and Data Science
This book constitutes the post-conference proceedings of the 4th International Conference on Machine Learning, Optimization, and Data Science, LOD 2018, held in Volterra, Italy, in September 2018.The 46 full papers presented were carefully reviewed and selected from 126 submissions. The papers cover topics in the field of machine learning, artificial intelligence, reinforcement learning, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.
High-Performance Computing and Big Data Analysis
This book constitutes revised and selected papers from the Second International Congress on High-Performance Computing and Big Data Analysis, TopHPC 2019, held in Tehran, Iran, in April 2019. The 37 full papers and 2 short papers presented in this volume were carefully reviewed and selected from a total of 103 submissions. The papers in the volume are organized acording to the following topical headings: deep learning; big data analytics; Internet of Things.- data mining, neural network and genetic algorithms; performance issuesand quantum computing.
Big Data and HPC: Ecosystem and Convergence
Due to the increasing need to solve complex problems, high-performance computing (HPC) is now one of the most fundamental infrastructures for scientific development in all disciplines, and it has progressed massively in recent years as a result. HPC facilitates the processing of big data, but the tremendous research challenges faced in recent years include: the scalability of computing performance for high velocity, high variety and high volume big data; deep learning with massive-scale datasets; big data programming paradigms on multi-core; GPU and hybrid distributed environments; and unstructured data processing with high-performance computing. This book presents 19 selected papers from the TopHPC2017 congress on Advances in High-Performance Computing and Big Data Analytics in the Exascale era, held in Tehran, Iran, in April 2017. The book is divided into 3 sections: State of the Art and Future Scenarios, Big Data Challenges, and HPC Challenges, and will be of interest to all those whose work involves the processing of Big Data and the use of HPC.
Cooperative Localization and Navigation
This book captures the latest results and techniques for cooperative localization and navigation drawn from a broad array of disciplines. It provides the reader with a generic and comprehensive view of modeling, strategies, and state estimation methodologies in that fields. It discusses the most recent research and novel advances in that direction, exploring the design of algorithms and architectures, benefits, and challenging aspects, as well as a potential broad array of disciplines, including wireless communication, indoor localization, robotics, emergency rescue, motion analysis, etc.
