Bounded Integration

In this comparative study of the religion-state relationship in Turkey and Israel in the modern era, Bounded Integration reveals the influence this dynamic interaction has had on democratic performance in both countries. In societies where a dominant religion serves as an important component of individual and collective identity, the imposition of secular policies from above may not facilitate democratization but may rather impede the embedding of democracy in society. Moreover, the inclusion or exclusion of religion following statehood may facilitate a certain type of path-dependent political culture, one with long-term political consequences. Aviad Rubin's refreshing analytical approach comparing and contrasting the region's only two longstanding democratic entities and the dynamics of religion and the state in two different religions, Islam and Judaism, facilitates generalizable lessons for emergent political regimes in the post–Arab Spring Middle East.

Active Calculus - single variable is a free, open-source calculus text that is designed to support an active learning approach in the standard first two semesters of calculus, including approximately 200 activities and 500 exercises. In the HTML version, more than 250 of the exercises are available as interactive WeBWorK exercises; students will love that the online version even looks great on a smart phone. Each section of Active Calculus has at least 4 in-class activities to engage students in active learning. Normally, each section has a brief introduction together with a preview activity, followed by a mix of exposition and several more activities. Each section concludes with a short summary and exercises; the non-WeBWorK exercises are typically involved and challenging. More information on the goals and structure of the text can be found in the preface.

This book constitutes the refereed proceedings of the Third International Conference on Unconventional Models of Computation, UMC 2002, held in Kobe, Japan in October 2002.The 18 revised full papers presented together with eight invited full papers were carefully reviewed and selected from 36 submissions. All major areas of unconventinal computing models are covered, especially quantum computing, DNA computing, membrane computing, cellular computing, and possibilities to break Turing's barrier. The authors address theoretical aspects, practical implementations, as well as philosophical reflections.

Designed to offer applied mathematicians, physicists, chemists, engineers, geophysicists, and other scientists an elementary level explanation of integral equations of the first kind. It maintains a casual, conversational approach. The book emphasizes understanding, while deliberately avoiding special methods of highly limited application. Special features: all problems illustrate important topics covered in the text; the subject is explained using a fairly non-rigorous approach to introduce any mathematics not commonly understood by the intended audience; designed for self-study, but can also be used as a text.

This book constitutes the joint refereed proceedings of the three confederated conferences, CoopIS 2003, DOA 2003, and ODBASE 2003, held in Catania, Sicily, Italy, in November 2003. The 95 revised full papers presented were carefully reviewed and selected from a total of 360 submissions. The papers are organized in topical sections on information integration and mediation, Web services, agent systems, cooperation and evolution, peer-to-peer systems, cooperative systems, trust management, workflow systems, information dissemination systems, data management, the Semantic Web, data mining and classification, ontology management, temporal and spatial data, data semantics and metadata, real-time systems, ubiquitous systems, adaptability and mobility, systems engineering, software engineering, and transactions.

In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Markov chain Monte Carlo models; bootstrapping methods; ensemble Kalman filters; and interacting particle filters. Mean Field Simulation for Monte Carlo Integration presents the first comprehensive and modern mathematical treatment of mean field particle simulation models and interdisciplinary research topics, including interacting jumps and McKean-Vlasov processes, sequential Monte Carlo methodologies, genetic particle algorithms, genealogical tree-based algorithms, and quantum and diffusion Monte Carlo methods. Along with covering refined convergence analysis on nonlinear Markov chain models, the author discusses applications related to parameter estimation in hidden Markov chain models, stochastic optimization, nonlinear filtering and multiple target tracking, stochastic optimization, calibration and uncertainty propagations in numerical codes, rare event simulation, financial mathematics, and free energy and quasi-invariant measures arising in computational physics and population biology. This book shows how mean field particle simulation has revolutionized the field of Monte Carlo integration and stochastic algorithms. It will help theoretical probability researchers, applied statisticians, biologists, statistical physicists, and computer scientists work better across their own disciplinary boundaries.

This volume contains many examples and applied methods explaining the basic architecture of the mobile terminals. It includes sufficient introductory material to enabling even non-expert readers to understand the topics and to make a step towards system integration of complex future applications.

Everyone is familiar with the speed-accuracy trade-off (SAT). To make good choices, we need to balance the conflicting demands of fast and accurate decision making. After all, hasty decisions often lead to poor choices, but accurate decisions may be useless if they take too long. This notion is intuitive because it reflects a fundamental aspect of cognition: not only do we deliberate over the evidence for decisions, but we can control that deliberative process. This control raises many questions for the study of choice behaviour and executive function. For example, how do we figure out the appropriate balance between speed and accuracy on a given task? How do we impose that balance on our decisions, and what is its neural basis? Researchers have addressed these and related questions for decades, using a variety of methods and offering answers at different levels of abstraction. Given this diverse methodology, our aim is to provide a unified view of the SAT. Extensive analysis of choice behaviour suggests that we make decisions by accumulating evidence until some criterion is reached. Thus, adjusting the criterion controls how long we accumulate evidence and therefore the speed and accuracy of decisions. This simple framework provides the platform for our unified view. In the pages that follow, leading experts in decision neuroscience consider the history of SAT research, strategies for determining the optimal balance between speed and accuracy, conditions under which this seemingly ubiquitous phenomenon breaks down, and the neural mechanisms that may implement the computations of our unifying framework.