The LNCS Journal on Data Semantics is devoted to the presentation of notable work that, in one way or another, addresses research and development on issues related to data semantics. Based on the highly visible publication platform Lecture Notes in Computer Science, this new journal is widely disseminated and available worldwide. The scope of the journal ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge. The journal addresses researchers and advanced practitioners working on the semantic web, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, conceptual database modeling, ontologies, and artificial intelligence.
Based on more than 40 interviews with Jobs conducted over two years--as well as interviews with more than 100 family members, friends, adversaries, competitors, and colleagues--Isaacson has written a riveting story of the roller-coaster life and searingly intense personality of a creative entrepreneur whose passion for perfection and ferocious drive revolutionized six industries: personal computers, animated movies, music, phones, tablet computing, and digital publishing.
Why do some innovation projects succeed where others fail? The book reveals the business implications of Jobs Theory and explains how to put Jobs Theory into practice using Outcome-Driven Innovation.
We hear it from politicians, the media, and just about everyone else: "We need more good jobs!" And yet nobody is telling us how to create good jobs. After successfully starting and growing a multibillion-dollar company in Silicon Valley, Martin Babinec returned to his home in Upstate New York where he then realized there were a number of forces at play in Silicon Valley-forces he hadn't appreciated-that had helped him succeed as an entrepreneur. Since then, he's been on a journey to understand the importance of community dynamics in the creation of new businesses. He's found a growing divergence between magnet cities-brimming with talent and new businesses-and talent exporting cities-where bright young minds leave in search of better opportunities. More Good Jobs is the playbook for turning your community into a magnet city, helping local entrepreneurs to start and grow companies and, in doing so, creating more good jobs for everyone in our communities.
This new edition of the well established text Scheduling - Theory, Algorithms, and Systems provides an up-to-date coverage of important theoretical models in the scheduling literature as well as significant scheduling problems that occur in the real world. It again includes supplementary material in the form of slide-shows from industry and movies that show implementations of scheduling systems. The main structure of the book as per previous edition consists of three parts. The first part focuses on deterministic scheduling and the related combinatorial problems. The second part covers probabilistic scheduling models; in this part it is assumed that processing times and other problem data are random and not known in advance. The third part deals with scheduling in practice; it covers heuristics that are popular with practitioners and discusses system design and implementation issues. All three parts of this new edition have been revamped and streamlined. The references have been made completely up-to-date. Theoreticians and practitioners alike will find this book of interest. Graduate students in operations management, operations research, industrial engineering, and computer science will find the book an accessible and invaluable resource. Scheduling - Theory, Algorithms, and Systems will serve as an essential reference for professionals working on scheduling problems in manufacturing, services, and other environments. Reviews of third edition: This well-established text covers both the theory and practice of scheduling. The book begins with motivating examples and the penultimate chapter discusses some commercial scheduling systems and examples of their implementations." (Mathematical Reviews, 2009)
This textbook provides a rigorous introduction to online algorithms for graduate and senior undergraduate students. In-depth coverage of most of the important topics is presented with special emphasis on elegant analysis. A wide range of solved examples and practice exercises are included, allowing hands-on exposure to the basic concepts.
