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Machine Learning for Computer Scientists and Data Analysts
This textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution networks. Most importantly, this book helps readers to understand the concepts of ML algorithms and enables them to develop the skills necessary to choose an apt ML algorithm for a problem they wish to solve. In addition, this book includes numerous case studies, ranging from simple time-series forecasting to object recognition and recommender systems using massive databases. Lastly, this book also provides practical implementation examples and assignments for the readers to practice and improve their programming capabilities for the ML applications.
In vivo Models for Drug Discovery
This one-stop reference is the first to present the complete picture -- covering all relevant organisms, from single cells to mammals, as well as all major disease areas, including neurological disorders, cancer and infectious diseases. Addressing the needs of the pharmaceutical industry, this unique handbook adopts a broad perspective on the use of animals in the early part of the drug development process, including regulatory rules and limitations, as well as numerous examples from real-life drug development projects. After a general introduction to the topic, the expert contributors from research-driven pharmaceutical companies discuss the basic considerations of using animal models, incl...
VLSI-SoC: Design and Engineering of Electronics Systems Based on New Computing Paradigms
This book contains extended and revised versions of the best papers presented at the 26th IFIP WG 10.5/IEEE International Conference on Very Large Scale Integration, VLSI-SoC 2018, held in Verona, Italy, in October 2018. The 13 full papers included in this volume were carefully reviewed and selected from the 27 papers (out of 106 submissions) presented at the conference. The papers discuss the latest academic and industrial results and developments as well as future trends in the field of System-on-Chip (SoC) design, considering the challenges of nano-scale, state-of-the-art and emerging manufacturing technologies. In particular they address cutting-edge research fields like heterogeneous, neuromorphic and brain-inspired, biologically-inspired, approximate computing systems.
Silicon Valley Cybersecurity Conference
This book constitutes selected and revised papers from the Second Silicon Valley Cybersecurity Conference, held in San Jose, USA, in December 2021. Due to the COVID-19 pandemic the conference was held in a virtual format. The 9 full papers and one shoprt paper presented in this volume were thoroughly reviewed and selected from 15 submissions. They present most recent research on dependability, reliability, and security to address cyber-attacks, vulnerabilities, faults, and errors in networks and systems. Chapters 1, 4, 5, 6, and 8-10 are published open access under a CC BY license (Creative Commons Attribution 4.0 International License).
On-Chip Communication Architectures
Over the past decade, system-on-chip (SoC) designs have evolved to address the ever increasing complexity of applications, fueled by the era of digital convergence. Improvements in process technology have effectively shrunk board-level components so they can be integrated on a single chip. New on-chip communication architectures have been designed to support all inter-component communication in a SoC design. These communication architecture fabrics have a critical impact on the power consumption, performance, cost and design cycle time of modern SoC designs. As application complexity strains the communication backbone of SoC designs, academic and industrial R&D efforts and dollars are increa...
Advances in Computer Systems Architecture
The refereed proceedings of the 12th Asia-Pacific Computer Systems Architecture Conference are presented in this volume. Twenty-six full papers are presented together with two keynote and eight invited lectures. Collectively, they represent some of the most important developments in computer systems architecture. The papers emphasize hardware and software techniques for state-of-the-art, multi-core and multi-threaded architectures.
Concepts of Machine Learning
Since AI has dominated data innovation for more than 20 years, it has played a significant but frequently unnoticed role in our lives. Shrewd information examination will probably turn out to be considerably more common as a prerequisite for mechanical progression because of the steadily growing amounts of information that are becoming available. The main objectives of this chapter are to organise the zoo of issues and to provide the reader with a comprehensive overview of the numerous applications that have machine learning challenges at their core. The language where various AI issues should be figured out to become agreeable to arrangement, measurements and likelihood hypothesis will next...
Circadian Rhythms for Future Resilient Electronic Systems
This book describes methods to address wearout/aging degradations in electronic chips and systems, caused by several physical mechanisms at the device level. The authors introduce a novel technique called accelerated active self-healing, which fixes wearout issues by enabling accelerated recovery. Coverage includes recovery theory, experimental results, implementations and applications, across multiple nodes ranging from planar, FD-SOI to FinFET, based on both foundry provided models and predictive models. Presents novel techniques, tested with experiments on real hardware; Discusses circuit and system level wearout recovery implementations, many of these designs are portable and friendly to the standard design flow; Provides circuit-architecture-system infrastructures that enable the accelerated self-healing for future resilient systems; Discusses wearout issues at both transistor and interconnect level, providing solutions that apply to both; Includes coverage of resilient aspects of emerging applications such as IoT.
Embedded Computer Systems: Architectures, Modeling, and Simulation
This book constitutes the refereed proceedings of the 6th International Workshop on Systems, Architectures, Modeling, and Simulation, SAMOS 2006, held in Samos, Greece on July 2006. The 47 revised full papers presented together with 2 keynote talks were thoroughly reviewed and selected from 130 submissions. The papers are organized in topical sections on system design and modeling, wireless sensor networks, processor design, dependable computing, architectures and implementations, and embedded sensor systems.
Big Data Analytics in Fog-Enabled IoT Networks
The integration of fog computing with the resource-limited Internet of Things (IoT) network formulates the concept of the fog-enabled IoT system. Due to a large number of IoT devices, the IoT is a main source of Big Data. A large volume of sensing data is generated by IoT systems such as smart cities and smart-grid applications. A fundamental research issue is how to provide a fast and efficient data analytics solution for fog-enabled IoT systems. Big Data Analytics in Fog-Enabled IoT Networks: Towards a Privacy and Security Perspective focuses on Big Data analytics in a fog-enabled-IoT system and provides a comprehensive collection of chapters that touch on different issues related to healthcare systems, cyber-threat detection, malware detection, and the security and privacy of IoT Big Data and IoT networks. This book also emphasizes and facilitates a greater understanding of various security and privacy approaches using advanced artificial intelligence and Big Data technologies such as machine and deep learning, federated learning, blockchain, and edge computing, as well as the countermeasures to overcome the vulnerabilities of the fog-enabled IoT system.
