Autorentext

Dr. Cyrus F. Nourani has a national and international reputation in computer science, artificial intelligence, mathematics, virtual haptic computation, information technology, predictive analytics, economics game models, decision trees, and management sciences. He has many years of experience in the design and implementation of computing systems. Dr. Nourani's academic experience includes faculty positions at the University of Michigan-Ann Arbor, the University of Pennsylvania, the University of Southern California, UCLA, MIT, and the University of California, Santa Barbara. He was a Visiting Professor at Edith Cowan University, Perth, Australia, and a Lecturer of Management Science and IT at the University of Auckland, New Zealand. His more recent years' engagements are research professor at SFU Burnaby, British Columbia, Canada, and TU Berlin, Germany.

Dr. Nourani commenced his university degrees at MIT where he became interested in algebraic semantics. That was pursued with a category theorist at the University of California. Dr. Nourani's dissertation on computing models and categories proved to have novel mathematical foundations developments that were published from his postdoctoral times on at AMS, ASL, and European Mathematics circles. He has taught AI to the Los Angeles aerospace industry and has authored many R&D and commercial ventures. He has written and co-authored several books. He has over 400 publications in management sciences, pure mathematics, and computer science and has written on additional topics, such as AI, EC, decision trees, predictive economics game modeling. In 1987, he founded Ventures for computing R&D. He began independent consulting with clients such as System Development Corporation (SDC), the US Air Force Space Division, and GE Aerospace. Dr. Nourani has designed and developed AI robot planning and reasoning systems at Northrop Research and Technology Center, Palos Verdes, California. He also has comparable AI, software, and computing foundations and R&D experience at GTE Research Labs .He has written over 15 invention disclosures on the above areas.

Zusammenfassung

Ecosystems and Technology: Idea Generation and Content Model Processing, ****presents important new innovations in the area of management and computing. Innovation is the generation and application of new ideas and skills to produce new products, processes, and services that improve economic and social prosperity. This includes management and design policy decisions and encompasses innovation research, analysis, and best practice in enterprises, public and private sector service organizations, government, regional societies and economies.

The book, the first volume in the Innovation Management and Computing book series, looks at technology that improves efficiency and idea generation, including systems for business, medical/health, education, and more.

The book provides detailed examples to provide readers with current issues, including

• Venture planning for innovations
• New technologies supporting innovations systems
• Competitive business modeling
• Context-driven innovation modeling
• The generation of ideas faster
• The measurement of relevant data
• Virtual interfaces
• Business intelligence and content processing
• Predictive modeling
• Haptic expression and emotion recognition innovations, with applications to neurocognitive medical science This book provides a wealth of information that will be useful for IT and business professionals, educators, and students in many fields.

Inhalt

Technology Selection for Software Startups. Innovation Ecosystems and Technology. Self-Organizing Coordination and Control Approaches: The Impact of Social Norms on Self-Regulated Innovation Activities in Self-Managing Teams. Digital Opportunities for First-Year University Students' Motivational Enhancement. Building a Successful Innovation Platform for Affordable Medical Technology in Low Resource Settings. Soft-Factors Enabling Innovation. IoT and M.E.S.: Are You Ready for the Next Industrial Revolution?. A Structured Process to Generate Ideas in Med Tech. Logic-Based Medicine versus Evidence-Based Medicine for Modeling Qualified-Self Health Kits. Virtual Mobile Interfaces, Business Intelligence, and Analytics Content Processing. A Haptic Computing basis for Facial or Visual Emotion Expression Recognition.