Intellectual Property Rights in a Networked World is a collection of recent essays offering some fresh perspectives on the scope and future of intellectual property rights. The tripartite division of the book is designed to make this interdisciplinary topic more accessible and intelligible to readers of diverse backgrounds. Part I consists of a single essay that provides a broad overview of the main themes in intellectual property scholarship, such as normative intellectual property theory and the legal infrastructure for property protection. The second section of the book presents several essays that are intended to deepen the reader's understanding of intellectual property theory and show how it can help us to grapple with the proper allocation of property rights in cyberspace. And the final section further develops the themes in Part II but in greater detail and with a more practical orientation. For the most part, the essays in this section illustrate the costs and benefits of applying property rights to cyberspace. While intellectual property rights create dynamic incentive effects, they also entail social costs, and they are sometimes in tension with the development of a robust public domain.
This brilliant, innovative book offers an engaging new way for children to discover and learn basic concepts of the alphabet. By running their finger along large, grooved letters, children can explore each shape. Colorful lift-the-flaps on every sturdy page further reinforce easy learning. Each board page features a capital letter that a child can trace with their finger, a flap to lift to find a surprise, and bright illustrations! The bright illustrations include cuddly animals and familiar objects. Also, included are helpful hints on how to extend the fun with guessing games, writing exercises, and more!
This monograph is the continuation and completion of the monograph, "Intelligent Systems: Approximation by Artificial Neural Networks" written by the same author and published 2011 by Springer.
The book you hold in hand presents the complete recent and original work of the author in approximation by neural networks. Chapters are written in a self-contained style and can be read independently. Advanced courses and seminars can be taught out of this brief book. All necessary background and motivations are given per chapter. A related list of references is given also per chapter. The book's results are expected to find applications in many areas of applied mathematics, computer science and engineering. As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also for all science and engineering libraries.
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