"Bill Tweed has that rare combination of deep historical knowledge and even deeper passion for the national parks. I can't think of a better trail guide." Dayton Duncan, author of the National Parks: America's Best Idea --

In this case study of the politics of transition in Eastern Europe, Rudolf Martin Rizman provides a careful, detailed sociological explanation and narrative on the emergence of independent statehood and democracy in Slovenia. In his focus on the transition from an authoritarian to a democratic regime, Rizman analyzes social processes and political issues in the context of the Third Wave of democratization, identifying "zones of certainty and uncertainty." Challenging many generally accepted ideas about small states and their transitions to democracy, this book places Slovenia's pattern of democratization in the wider regional context of eastern and central European post-communist transitions.

Europe’s Uncertain Path is an introduction to Europe’s turbulent history from 1814 to 1914. It presents a clear narrative of the major political events, set against the backdrop of social, economic, and cultural change. An introduction to Europe’s turbulent history from 1814 to 1914 Provides students with a solid grounding in the main political events and social changes of the period Explains the causes and outcomes of major events: the effect of the emergence of mass politics; the evolution of political ideologies; and the link between foreign and domestic policy Offers balanced coverage of Eastern, Western, and Central Europe Illustrations, maps, and figures enhance student understanding

In this provocative walking meditation, writer and former park ranger William Tweed takes us to California’s spectacular High Sierra to discover a new vision for our national parks as they approach their 100th anniversary. Tweed, who worked among the Sierra Nevada’s big peaks and big trees for more than thirty years, has now hiked more than 200 miles along California’s John Muir Trail in a personal search for answers: How do we address the climate change we are seeing even now—in melting glaciers in Glacier National Park, changing rainy seasons on Mt Rainer, and more fire in the West’s iconic parks. Should we intervene where we can to preserve biodiversity? Should the parks merely become ecosystem museums that exhibit famous landscapes and species? Asking how we can make these magnificent parks relevant for the next generation, Tweed, through his journey, ultimately shows why we must do just that.

This first book focuses on uncertain graph and network optimization. It covers three different main contents: uncertain graph, uncertain programming and uncertain network optimization. It also presents applications of uncertain network optimization in a lot of real problems such as transportation problems, dispatching medical supplies problems and location problems. The book is suitable for researchers, engineers, teachers and students in the field of mathematics, information science, computer science, decision science, management science and engineering, artificial intelligence, industrial engineering, economics and operations research.

Because he chose to take part in the revolution on Melida/Daan, Obi-Wan Kenobi is no longer a Jedi. But as the revolution continues and he can no longer tell his friends from his enemies, he grows to regret his choice.

This book explores international human resource management (IHRM) practices in the contexts of high uncertainties. It encompasses situations of financial crisis, political and civil uncertainty, environmental collapse and recession. Research on unstable and unpredictable contexts on business and HRM remain relatively scarce and scattered across disciplines. This volume brings together recent thinking from a range of different perspectives and methodologies. MNEs are often distinguished by the supposedly superior ability to implement highly tactical, more robust talent management practices, including work-based, HRM-led and international systems, in line with the rest of their worldwide operations; however, they often fall short. The chapters in this book explore the how, why, and when. At a theoretical level, this collection brings together developments and extensions of a range of salient theories. They explore common methodological challenges and ways forward for future researchers on HRM in high contextual uncertainty. The chapters in this book were originally published as a special issue of The International Journal of Human Resource Management.

Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and rapidly increasing amounts of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task. Ranking queries (also known as top-k queries) are often natural and useful in analyzing uncertain data. Ranking Queries on Uncertain Data discusses the motivations/applications, challenging problems, the fundamental principles, and the evaluation algorithms of ranking queries on uncertain data. Theoretical and algorithmic results of ranking queries on uncertain data are presented in the last section of this book. Ranking Queries on Uncertain Data is the first book to systematically discuss the problem of ranking queries on uncertain data.

Today’s cyber defenses are largely static allowing adversaries to pre-plan their attacks. In response to this situation, researchers have started to investigate various methods that make networked information systems less homogeneous and less predictable by engineering systems that have homogeneous functionalities but randomized manifestations. The 10 papers included in this State-of-the Art Survey present recent advances made by a large team of researchers working on the same US Department of Defense Multidisciplinary University Research Initiative (MURI) project during 2013-2019. This project has developed a new class of technologies called Adaptive Cyber Defense (ACD) by building on two active but heretofore separate research areas: Adaptation Techniques (AT) and Adversarial Reasoning (AR). AT methods introduce diversity and uncertainty into networks, applications, and hosts. AR combines machine learning, behavioral science, operations research, control theory, and game theory to address the goal of computing effective strategies in dynamic, adversarial environments.