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Author: Gregory J. Battersby Publisher: Wolters Kluwer ISBN: 0735598967 Category : Law Languages : en Pages : 2760
Book Description
Drafting Internet Agreements, Second Edition is the most comprehensive single volume collection of annotated forms for the internet. The book also offers valuable insights for business executives who want to know how internet transactions are structured and how to negotiate the best deals. This easy-to-use reference with accompanying CD-ROM offers instant access to more than 40 sample agreements for every area of internet practice including: Internet advertising Internet consulting Electronic commerce Internet joint ventures Internet licensing Technology development Website agreements And more Each form has been developed by the authors or other experienced internet law practitioners and has been used in actual transactions. Organized by type of transaction, each chapter includes a full agreement that illustrates the entire transaction as a seamless whole, as well as a variety of agreements for closely related issues. For each form, the authors provide a brief overview, an analysis of the different kinds of forms that relate to the topic, and a description of the form's applicability and use. Coverage includes: Developing the content portion of the website Seeking intellectual property protection of website content Resolving domain name disputes Seeking to recover a domain name to which you have rights Linking a website to other sites Raising capital to develop and operate a site Marketing the Internet site Selling advertising on the internet site And more. A andquot;Practice Tipsandquot; section before each form identifies the andquot;hot spotsandquot; that are likely to arise during the transaction, and offers guidance on resolving these hotly negotiated provisions quickly. Detailed checklists assist in drafting the final agreement. Drafting Internet Agreements, Second Edition also includes a free companion CD-ROM containing over 40 forms presented in the guide, making it easy to incorporate the forms into a word processing program.
Author: Constantin Stefanou Publisher: Routledge ISBN: 1317148266 Category : Law Languages : en Pages : 352
Book Description
Drafting Legislation sets out to prove Sir William Dale's doctrine that the rules for drafting good quality legislation are the same in common and civil systems of law. Legislative solutions can therefore serve the drafter, the judge and the practitioner of any jurisdiction. The book discusses the general issue of quality in legislation from the legislative process to the actual drafting interpretation and enforcement. It also analyzes topics related to quality in legislation such as clarity, precision and disambiguity, plain language and gender-neutral language and assesses whether Sir William's view of universality in the definition and elements of quality in legislation is right or not. The volume is of critical interest to students and scholars of European law and the philosophy and theory of law.
Author: Alessandro Somma Publisher: Kluwer Law International B.V. ISBN: 9041131418 Category : Law Languages : en Pages : 250
Book Description
This collection of essays reflects both the diversity of the group's work and the common thread that runs through it. The core claim here is that the DCFR, despite the Commission's characterization of its proposals as purely technical, cannot escape politics. The intent is to critically identify and evaluate the model of social justice underlying the DCFR.
Author: National Research Council Publisher: National Academies Press ISBN: 0309147026 Category : Science Languages : en Pages : 193
Book Description
For much of the past 60 years, the U.S. research community dominated the discovery of new crystalline materials and the growth of large single crystals, placing the country at the forefront of fundamental advances in condensed-matter sciences and fueling the development of many of the new technologies at the core of U.S. economic growth. The opportunities offered by future developments in this field remain as promising as the achievements of the past. However, the past 20 years have seen a substantial deterioration in the United States' capability to pursue those opportunities at a time when several European and Asian countries have significantly increased investments in developing their own capacities in these areas. This book seeks both to set out the challenges and opportunities facing those who discover new crystalline materials and grow large crystals and to chart a way for the United States to reinvigorate its efforts and thereby return to a position of leadership in this field.
Author: William L. William L. Hamilton Publisher: Springer Nature ISBN: 3031015886 Category : Computers Languages : en Pages : 141
Book Description
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.