Tackling the questions that systems designers care about, this book brings queueing theory decisively back to computer science. The book is written with computer scientists and engineers in mind and ...is full of examples from computer systems, as well as manufacturing and operations research. Fun and readable, the book is highly approachable, even for undergraduates, while still being thoroughly rigorous and also covering a much wider span of topics than many queueing books. Readers benefit from a lively mix of motivation and intuition, with illustrations, examples and more than 300 exercises – all while acquiring the skills needed to model, analyze and design large-scale systems with good performance and low cost. The exercises are an important feature, teaching research-level counterintuitive lessons in the design of computer systems. The goal is to train readers not only to customize existing analyses but also to invent their own.
The development of modern civilization leads to us having to solve new problems which did not exist before. The contemporary world faces a great challenge of aging societies, where the increasing ...number of citizens requires constant medical attention. To ensure safety and wellbeing of elderly people, patients in hospitals and disabled persons, advanced technologies can be implemented. These include both sophisticated data acquisition systems and data processing algorithms, aiming at the constant and discreet monitoring of persons whilst raising alarm if immediate attention is required. Computer Systems for Healthcare and Medicine presents a novel look at the introduced problems, including proposed solutions in the form of automated data acquisition and processing systems, which were tested in various environments. Characteristic features include a wide range of sensors used to monitor the situation of the person, and accurate decision making algorithms, often based on the computational intelligence domain. Technical topics discussed in the book include application for the healthcare of the following:
Infrared sensors
MEMS
Ultra wideband radars
Deep learning
Decision trees
Artificial neural networks
Gabor filters
Decision support systems
Fault Tolerant Systems Israel Koren, C. Mani Krishna
2007, 2010, 2010-07-19T00:00:00, 2010-07-19, c2007
eBook
There are many applications in which the reliability of the overall system must be far higher than the reliability of its individual components. In such cases, designers devise mechanisms and ...architectures that allow the system to either completely mask the effects of a component failure or recover from it so quickly that the application is not seriously affected. This is the work of fault-tolerant designers and their work is increasingly important and complex not only because of the increasing number of “mission critical” applications, but also because the diminishing reliability of hardware means that even systems for non-critical applications will need to be designed with fault-tolerance in mind. Reflecting the real-world challenges faced by designers of these systems, this book addresses fault tolerance design with a systems approach to both hardware and software. No other text on the market takes this approach, nor offers the comprehensive and up-to-date treatment the authors provide. Students, designers and architects of high performance processors will value this comprehensive overview of the field.
Cyber-Physical Systems Houbing Song, Danda B Rawat, Sabina Jeschke, Christian Brecher / Houbing Song, Danda B. Rawat, Sabina Jeschke, Christian Brecher
2016, 2016-09-11
eBook
Cyber-Physical Systems: Foundations, Principles and Applications explores the core system science perspective needed to design and build complex cyber- physical systems. Using Systems Science's ...underlying theories, such as probability theory, decision theory, game theory, organizational sociology, behavioral economics, and cognitive psychology, the book addresses foundational issues central across CPS applications, including System Design -- How to design CPS to be safe, secure, and resilient in rapidly evolving environments, System Verification -- How to develop effective metrics and methods to verify and certify large and complex CPS, Real-time Control and Adaptation -- How to achieve real-time dynamic control and behavior adaptation in a diverse environments, such as clouds and in network-challenged spaces, Manufacturing -- How to harness communication, computation, and control for developing new products, reducing product concepts to realizable designs, and producing integrated software-hardware systems at a pace far exceeding today's timeline. The book is part of the Intelligent Data-Centric Systems: Sensor- Collected Intelligence series edited by Fatos Xhafa, Technical University of Catalonia. Indexing: The books of this series are submitted to EI-Compendex and SCOPUS * Includes in-depth coverage of the latest models and theories that unify perspectives, expressing the interacting dynamics of the computational and physical components of a system in a dynamic environment * Focuses on new design, analysis, and verification tools that embody the scientific principles of CPS and incorporate measurement, dynamics, and control * Covers applications in numerous sectors, including agriculture, energy, transportation, building design and automation, healthcare, and manufacturing
The advent of the internet, the exponential growth in computing power and the rapid developments in artificial intelligence have given rise to numerous ethical questions in relation to cybersecurity ...across various domains, not least by virtue of the dual-use character of cybertechnology—it can be used to provide great benefits to humankind, but also to do great harm. The domains in question intersect and include business (e.g., data security, data ownership and privacy), public communication (e.g., disinformation and computational propaganda), health (e.g., privacy, ransomware attacks), law enforcement (e.g., data security, predictive policing), and interstate conflict (e.g., cyberwar, autonomous weapons). This work undertakes analyses of the key ethical concepts in play, such as privacy, freedom of communication, security, and the right to self-defence. This work also develops sets of ethical guidelines to give direction to the regulation of cyberspace in these various domains. It does so from a liberal democratic perspective that seeks to protect individual rights while ensuring the collective good of cybersecurity. A central informing idea is that of institutionally embedded collective moral responsibilities that function as “webs of prevention” against cyberattacks. Cybersecurity is, in the end, a collective moral responsibility of both individual citizens and organizations, but a collective responsibility the discharging of which requires new regulation and the redesign of institutional roles, as well as technical countermeasures to cyberattacks, such as passwords, encryption, firewalls, patching, and the like. It also involves at times, we suggest, offensive as well as defensive measures.
Convolutional Neural Networks (CNNs) have emerged as a fundamental technology for machine learning. High performance and extreme energy efficiency are critical for deployments of CNNs, especially in ...mobile platforms such as autonomous vehicles, cameras, and electronic personal assistants. This paper introduces the Sparse CNN (SCNN) accelerator architecture, which improves performance and energy efficiency by exploiting the zero-valued weights that stem from network pruning during training and zero-valued activations that arise from the common ReLU operator. Specifically, SCNN employs a novel dataflow that enables maintaining the sparse weights and activations in a compressed encoding, which eliminates unnecessary data transfers and reduces storage requirements. Furthermore, the SCNN dataflow facilitates efficient delivery of those weights and activations to a multiplier array, where they are extensively reused; product accumulation is performed in a novel accumulator array. On contemporary neural networks, SCNN can improve both performance and energy by a factor of 2.7× and 2.3×, respectively, over a comparably provisioned dense CNN accelerator.
Do you spend a lot of time during the design process wondering what users really need? Do you hate those endless meetings where you argue how the interface should work? Have you ever developed ...something that later had to be completely redesigned? Paper Prototyping can help. Written by a usability engineer with a long and successful paper prototyping history, this book is a practical, how-to guide that will prepare you to create and test paper prototypes of all kinds of user interfaces. You'll see how to simulate various kinds of interface elements and interactions. You'll learn about the practical aspects of paper prototyping, such as deciding when the technique is appropriate, scheduling the activities, and handling the skepticism of others in your organization. Numerous case studies and images throughout the book show you real world examples of paper prototyping at work. Learn how to use this powerful technique to develop products that are more useful, intuitive, efficient, and pleasing: * Save time and money - solve key problems before implementation begins * Get user feedback early - use it to focus the development process * Communicate better - involve development team members from a variety of disciplines * Be more creative - experiment with many ideas before committing to one*Enables designers to solve design problems before implementation begins *Five case studies provide real world examples of paper prototyping at work *Delves into the specifics of what types of projects paper prototyping is and isn't good for.
Memristor-based synaptic network has been widely investigated and applied to neuromorphic computing systems for the fast computation and low design cost. As memristors continue to mature and achieve ...higher density, bit failures within crossbar arrays can become a critical issue. These can degrade the computation accuracy significantly. In this work, we propose a defect rescuing design to restore the computation accuracy. In our proposed design, significant weights in a specified network are first identified and retraining and remapping algorithms are described. For a two layer neural network with 92.64% classification accuracy on MNIST digit recognition, our evaluation based on real device testing shows that our design can recover almost its full performance when 20% random defects are present.
PDF
