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This handbook is the first to provide comprehensive coverage of original state-of-the-science research, analysis, and design of integrated, human-technology systems.
Although cognitive engineering has gained widespread acceptance as one of the most promising approaches to addressing and preventing difficulties with human-machine coordination and collaboration, it still meets with considerable skepticism and resistance in some of the industries that could benefit from its insights and recommendations. The challe
This volume provides an exceptional perspective on the nature, evolution, contributions and future of the field of Cognitive Systems Engineering (CSE). It is a resource to support both the teaching and practice of CSE. It accomplishes this through its organization into two complementary approaches to the topic. The first is an historical perspective: In the retrospections of leaders of the field, what have been the seminal achievements of cognitive human factors? What are the "lessons learned" that became foundational to CSE, and how did that foundation evolve into a broader systems view of cognitive work? The second perspective is both pedagogical and future-looking: What are the major conceptual issues that have to be addressed by CSE and how can a new generation of researchers be prepared to further advance CSE? Topics include studies of expertise, cognitive work analysis, cognitive task analysis, human performance, system design, cognitive modeling, decision making, human-computer interaction, trust in automation, teamwork and ecological interface design. A thematic focus will be on systems-level analysis, and such notions as resilience engineering and systems-level measurement. The book features broad coverage of many of the domains to which CSE is being applied, among them industrial process control, health care, decision aiding and aviation human factors. The book’s contributions are provided by an extraordinary group of leaders and pathfinders in applied psychology, cognitive science, systems analysis and system design. In combination these chapters present invaluable insights, experiences and continuing uncertainties on the subject of the field of CSE, and in doing so honor the career and achievements of Professor David D. Woods of Ohio State University.
Nothing has been more prolific over the past century than human/machine interaction. Automobiles, telephones, computers, manufacturing machines, robots, office equipment, machines large and small; all affect the very essence of our daily lives. However, this interaction has not always been efficient or easy and has at times turned fairly hazardous.
The cognitive approach to the IoT provides connectivity to everyone and everything since IoT connected devices are known to increase rapidly. When the IoT is integrated with cognitive technology, performance is improved, and smart intelligence is obtained. Discussed in this book are different types of datasets with structured content based on cognitive systems. The IoT gathers the information from the real time datasets through the internet, where the IoT network connects with multiple devices. This book mainly concentrates on providing the best solutions to existing real-time issues in the cognitive domain. Healthcare-based, cloud-based and smart transportation-based applications in the cognitive domain are addressed. The data integrity and security aspects of the cognitive computing main are also thoroughly discussed along with validated results.
A woman is operated on while she's awake... A plane runs out of gas while circling an airport for 30 minutes... A passenger liner is mistaken for an enemy fighter and shot down... A company invests in a new system that will cost them money... What do these failure have in common? How can we prevent them from happening again?
What we profoundly witness these days is a growing number of human-centric systems and a genuine interest in a comprehensive understanding of their underlying paradigms and the development of solid and efficient design practices. We are indeed in the midst of the next information revolution, which very likely brings us into a completely new world of ubiquitous and invisible computing, Ambient Intelligent (AMI), and wearable hardware. This requires a totally new way of thinking in which cognitive aspects of design, cognitive system engineering and distributed approach play a pivotal role. This book fully addresses these timely needs by filling a gap between the two well-established disciplines of cognitive sciences and cognitive systems engineering. As we put succinctly in the preface, with the psychological perspective of human cognition in mind, “the book explores the computational models of reasoning, learning, planning and multi-agent coordination and control of the human moods”. This is an excellent, up to the point description of the book. The treatise is focused on the underlying fundamentals, spans across a vast territory embracing logic perspectives of human cognition, distributed models, parallel computing, expert systems, and intelligent robotics.
Powerful information technologies and the complex support systems they engender are evolving faster than people’s ability to adjust to them. In the workplace, this leads to troublesome task performance, added stress on users, increased organizational inefficiency, and, in some cases, a heightened risk of wide-scale .disaster. In the marketplace, it makes for consumer dissatisfaction. Clearly, traditional human-computer interaction (HCI) and system design (SD) solutions to this dilemma have proven woefully inadequate. What is needed is a fresh multidisciplinary approach offering a broader, more dynamic framework for assessing needs and designing usable, efficient systems. Taking modeling concepts from engineering, psychology, cognitive science, information science, and computer science, cognitive systems engineering (CSE) provides such a framework. This book is the first comprehensive guide to the emerging new field of CSE. Providing equal parts theory and practice, it is based on the authors’ many years of experience with work systems in a wide range of work domains, including process control, manufacturing, hospitals, and libraries. Throughout, the emphasis is on powerful analytical techniques that enhance the systems designer’s ability to see the "big picture," and to design for all crucial aspects of human-work interaction. Applicable to highly structured technical systems such as process plants, as well as less structured user-driven systems like libraries, these analytical techniques form the basis for the evaluation and design guidelines that make up the bulk of this book. And since the proof is in the pudding, the authors provide a chapter-length case history in which they demonstrate the success of their approach when applied to a full-scale software design project. The project, a retrieval system for public libraries, is described in detail, from field studies to concept validation experiments, and, of course, the empirical evaluation of the system while in use by the library users and personnel. Computer-based information systems are rapidly becoming a fundamental part of the human landscape. How that landscape evolves over the next decade or so, whether it becomes a hostile one or one that generously supports the needs of future generations, is in the hands of all those involved with the study and design of information systems.
Using robust software, this book focuses on learning assistants for evidence-based reasoning that learn complex problem solving from humans.
"This is a book for artists, but it is also for curators, art school faculty, landscape architects, gallerists, archivists, post-disciplinary multi-hyphenates, museum program staff, and anyone who wants to know about the ways art and congnitive science come together to engage an audience."--Cover