The world is increasingly turbulent and complex, awash with disruptions, tipping points and knock-on effects exemplified by the implosion of financial markets and economies around the globe. This book is for business and organizational leaders who want and need to think through how best to deal with increasing turbulence, and with the complexity and uncertainty that come with it. The authors explain in clear language how future orientation and, specifically, modern scenario techniques help to address these conditions. They draw on examples from a wide variety of international settings and circumstances including large corporations, inter-governmental organizations, small firms and municipalities. Readers will be inspired to try out scenario approaches themselves to better address the turbulence that affects them and others with whom they work, live and do business. This second edition extends the use of scenarios planning and methods to tackle the risk and uncertainty of financial markets and the potentially massive impacts on businesses of all kinds, providing powerful tools to give far thinking executives an advantage in these turbulent times.

Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.

The world is increasingly turbulent and complex, awash with disruptions, tipping points and knock-on effects exemplified by the implosion of financial markets and economies around the globe. This book is for business and organizational leaders who want and need to think through how best to deal with increasing turbulence, and with the complexity and uncertainty that come with it. The authors explain in clear language how future orientation and, specifically, modern scenario techniques help to address these conditions. They draw on examples from a wide variety of international settings and circumstances including large corporations, inter-governmental organizations, small firms and municipalities. Readers will be inspired to try out scenario approaches themselves to better address the turbulence that affects them and others with whom they work, live and do business. This second edition extends the use of scenarios planning and methods to tackle the risk and uncertainty of financial markets and the potentially massive impacts on businesses of all kinds, providing powerful tools to give far thinking executives an advantage in these turbulent times.

This book is dedicated to study the inverse problem of ordinary differential equations, that is it focuses in finding all ordinary differential equations that satisfy a given set of properties. The Nambu bracket is the central tool in developing this approach. The authors start characterizing the ordinary differential equations in R^N which have a given set of partial integrals or first integrals. The results obtained are applied first to planar polynomial differential systems with a given set of such integrals, second to solve the 16th Hilbert problem restricted to generic algebraic limit cycles, third for solving the inverse problem for constrained Lagrangian and Hamiltonian mechanical systems, fourth for studying the integrability of a constrained rigid body. Finally the authors conclude with an analysis on nonholonomic mechanics, a generalization of the Hamiltonian principle, and the statement an solution of the inverse problem in vakonomic mechanics.

This book is dedicated to study the inverse problem of ordinary differential equations, that is it focuses in finding all ordinary differential equations that satisfy a given set of properties. The Nambu bracket is the central tool in developing this approach. The authors start characterizing the ordinary differential equations in R^N which have a given set of partial integrals or first integrals. The results obtained are applied first to planar polynomial differential systems with a given set of such integrals, second to solve the 16th Hilbert problem restricted to generic algebraic limit cycles, third for solving the inverse problem for constrained Lagrangian and Hamiltonian mechanical systems, fourth for studying the integrability of a constrained rigid body. Finally the authors conclude with an analysis on nonholonomic mechanics, a generalization of the Hamiltonian principle, and the statement an solution of the inverse problem in vakonomic mechanics.

Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.

During the 1980s and 1990s, Richard Normann and his colleagues developed an original approach to strategy, based on seeing value as inherently co-produced in systems. Their 'Value Creating Systems' approach was a strong contrast to the idea of 'competitive advantage' that defined strategy at the time. The approach focuses on the design of the 'offerings' that define relationships among co-producers, and which connect actors in fields which transcend traditional industry borders. In the contemporary networked world, where consumers become co-producers, the ideas Normann and his colleagues developed towards strategy are uniquely effective in explaining and guiding practice.Strategy for a Networked World revisits and further develops these ideas. It is co-authored by two long-standing colleagues of Normann, Rafael Ramirez and Ulf Mannervik, who have successfully applied these ideas to their own consultancy practice. This book provides the theoretical basis for strategies of value co-creation, an accessible methodology and practical guidance, case studies of Facebook and the World Economic Forum, and examples of successful collaborations with organisations such as EDF, Scania, Essity and Shell.Designed to advise strategists and business developers working in uncertain, complex and turbulent contexts, it is suitable both for practitioners and for academics, combining theory and the means to turn it into practice. It will also serve as a valuable contribution to MBA classes and towards the development of more effective business strategies.