Media convergence

"The book brings together experts from Media and Communication Studies with Postcolonial Studies scholars to illustrate how the two fields may challenge and enrich each other. Its essays introduce readers to selected topics including »Media Convergence«, »Transcultural Subjectivity«, »Hegemony«, »Piracy« and »Media History and Colonialism«. Drawing on examples from film, literature, music, TV and the internet, the contributors investigate the transnational dimensions in today's media, engage with local and global media politics and discuss media outlets as economic agents, thus illustrating mechanisms of power in postcolonial and neo-colonial mediascapes."--Publisher website

Convergence analysis of the Newton algorithm and a pseudo-time marching scheme for diffuse correlation tomography

We propose a self-regularized pseudo-time marching scheme to solve the ill-posed, nonlinear inverse problem associated with diffuse propagation of coherent light in a tissuelike object. In particular, in the context of diffuse correlation tomography (DCT), we consider the recovery of mechanical property distributions from partial and noisy boundary measurements of light intensity autocorrelation. We prove the existence of a minimizer for the Newton algorithm after establishing the existence of weak solutions for the forward equation of light amplitude autocorrelation and its Frechet derivative and adjoint. The asymptotic stability of the solution of the ordinary differential equation obtained through the introduction of the pseudo-time is also analyzed. We show that the asymptotic solution obtained through the pseudo-time marching converges to that optimal solution provided the Hessian of the forward equation is positive definite in the neighborhood of optimal solution. The superior noise tolerance and regularization-insensitive nature of pseudo-dynamic strategy are proved through numerical simulations in the context of both DCT and diffuse optical tomography. (C) 2010 Optical Society of America.

Concise review: Humanized models of tumor immunology in the 21st century: Convergence of cancer research and tissue engineering

Despite positive testing in animal studies, more than 80% of novel drug candidates fail to proof their efficacy when tested in humans. This is primarily due to the use of preclinical models that are not able to recapitulate the physiological or pathological processes in humans. Hence, one of the key challenges in the field of translational medicine is to “make the model organism mouse more human.” To get answers to questions that would be prognostic of outcomes in human medicine, the mouse's genome can be altered in order to create a more permissive host that allows the engraftment of human cell systems. It has been shown in the past that these strategies can improve our understanding of tumor immunology. However, the translational benefits of these platforms have still to be proven. In the 21st century, several research groups and consortia around the world take up the challenge to improve our understanding of how to humanize the animal's genetic code, its cells and, based on tissue engineering principles, its extracellular microenvironment, its tissues, or entire organs with the ultimate goal to foster the translation of new therapeutic strategies from bench to bedside. This article provides an overview of the state of the art of humanized models of tumor immunology and highlights future developments in the field such as the application of tissue engineering and regenerative medicine strategies to further enhance humanized murine model systems.

Effect of boundary condition description on convergence of solution in a boundary-value problem

It is well known that the numerical accuracy of a series solution to a boundary-value problem by the direct method depends on the technique of approximate satisfaction of the boundary conditions and on the stage of truncation of the series. On the other hand, it does not appear to be generally recognized that, when the boundary conditions can be described in alternative equivalent forms, the convergence of the solution is significantly affected by the actual form in which they are stated. The importance of the last aspect is studied for three different techniques of computing the deflections of simply supported regular polygonal plates under uniform pressure. It is also shown that it is sometimes possible to modify the technique of analysis to make the accuracy independent of the description of the boundary conditions.

Convergence correction in colloid scattering

The error introduced in depolarisation measurements due to the convergence of the incident beam has been investigated theoretically as well as experimentally for the case of colloid scattering, where the particles are not small compared to the wavelength of light. Assuming the scattering particles to be anisotropic rods, it is shown that, when the incident unpolarised light is condensed by means of a lens with a circular aperture, the observed depolarisation ratio ϱ u is given by ϱ u = ϱ u0 + 5/3 θ2 where ϱ u0 is the true depolarisation for incident parallel light, and θ the semi-angle of convergence. Appropriate formulae are derived when the incident beam is polarised vertically and horizontally. Experiments performed on six typical colloids support the theoretical conclusions. Other immediate consequences of the theory are also discussed.

Growth and Convergence: The case of China

Growth and Convergence: The Case of China Since the initiation of economic reforms in 1978, China has become one of the world’s fast-growing economies. The rapid growth, however, has not been shared equally across the different regions in China. The prominent feature of substantial differences in incomes and growth rates across the different Chinese regions has attracted the attention of many researchers. This book focuses on issues related to economic growth and convergence across the Chinese regions over the past three decades. The book has eight chapters. Apart from an introduction chapter and a concluding chapter, all the other chapters each deal with some certain aspects of the central issue of regional growth and convergence across China over the past three decades. The whole book is organized as follows. Chapter 1 provides an introduction to the basic issues involved in this book. Chapter 2 tests economic growth and convergence across 31 Chinese provinces during 1981-2005, based on the theoretical framework of the Solow growth model. Chapter 3 investigates the relationship between openness to foreign economic activities, such as foreign trade and foreign direct investment, and the regional economic growth in the case of China during 1981-2005. Chapter 4, based on data of 31 Chinese provinces over the period 1980-2004, presents new evidence on the effects of structural shocks and structural transformation on growth and convergence among the Chinese regions. Chapter 5, by building up an empirical model that takes account of different potential effects of foreign direct investment, focuses on the impacts of foreign direct investment on China’s regional economic performance and growth. Chapter 6 reconsiders the growth and convergence problem of the Chinese regions in an alternative theoretical framework with endogenous saving behavior and capital mobility across regions. Chapter 7, by building up a theoretical model concerning comparative advantage and transaction efficiency, focuses on one of the potential mechanisms through which China achieves its fast economic growth over the past few decades. Chapter 8 concludes the book by summarizing the results from the previous chapters and suggesting directions for further studies.

Convergence feedback and unstable low frequency oscillations in a simple coupled ocean‐atmosphere model

The role of convergence feedback on the stability of a coupled ocean‐atmosphere system is studied using model III of Hirst (1986). It is shown that the unstable coupled mode found by Hirst is greatly modified by the convergence feedback. If the convergence feedback strength exceeds a critical value, several new unstable intraseasonal modes are also introduced. These modes have very weak dependence on the wave number. These results may explain the behaviour of some coupled models and to some extent provide a mechanism for the observed aperiodicity of the El‐Nino and Southern Oscillation (ENSO) events.

Producing interactivity : Does media convergence promote interactivity and audience participation?

This study investigates the process of producing interactivity in a converged media environment. The study asks whether more media convergence equals more interactivity. The research object is approached through semi-structured interviews of prominent decision makers within the Finnish media. The main focus of the study are the three big ones of the traditional media, radio, television and the printing press, and their ability to adapt to the changing environment. The study develops theoretical models for the analysis of interactive features and convergence. Case-studies are formed from the interview data and they are evaluated against the models. As a result the cases arc plotted and compared on a four-fold table. The cases are Radio Rock, NRJ, Biu Brother, Television Chat, Olivia and Sanoma News. It is found out that the theoretical models can accurately forecast the results of the case studies. The models are also able to distinguish different aspects of both interactivity and convergence so that a case, which at a first glance seems not to be very interactive is in the end found out to receive second highest scores on the analysis. The highest scores are received by Big Brother and Sanoma News. Through the theory and the analysis of the research data it is found out that the concepts of interactivity and convergence arc intimately intertwined and very hard in many cases to separate from each other. Hence the answer to the main question of this study is yes, convergence does promote interactivity and audience participation. The main theoretical background for the analysis of interactivity follows the work of Came Fleeter, Spiro Kiousis and Sally McMillan. Heeler's six-dimensional definition of interactivity is used as the basis for operationalizing interactivity. The actor-network theory is used as the main theoretical framework to analyze convergence. The definition and operationalization of the actor-network theory into a model of convergence follows the work of Michel Callon. Bruno Latour and especially John Law and Felix Stalder.

Convergence of Power Control in a Random Channel Environment

In this paper, we study the Foschini Miljanic algorithm, which was originally proposed in a static channel environment. We investigate the algorithm in a random channel environment, study its convergence properties and apply the Gerschgorin theorem to derive sufficient conditions for the convergence of the algorithm. We apply the Foschini and Miljanic algorithm to cellular networks and derive sufficient conditions for the convergence of the algorithm in distribution and validate the results with simulations. In cellular networks, the conditions which ensure convergence in distribution can be easily verified.

Improving the convergence rate of the inverse iteration method

Solution of generalized eigenproblem, K phi = lambda M phi, by the classical inverse iteration method exhibits slow convergence for some eigenproblems. In this paper, a modified inverse iteration algorithm is presented for improving the convergence rate. At every iteration, an optimal linear combination of the latest and the preceding iteration vectors is used as the input vector for the next iteration. The effectiveness of the proposed algorithm is demonstrated for three typical eigenproblems, i.e. eigenproblems with distinct, close and repeated eigenvalues. The algorithm yields 29, 96 and 23% savings in computational time, respectively, for these problems. The algorithm is simple and easy to implement, and this renders the algorithm even more attractive.

From polarization to convergence: need to mend the broken patent system

For more than two hundred years, the world has discussed the issue of whether to continue the process of patenting or whether to do away with it. Developed countries remain polarized for various reasons but nevertheless the pro patent regime continued. The result was a huge volume of patents. The present article explains the implications of excessive volume of patents and conditions under which prior art search fails. This article highlights the importance and necessity of standardization efforts so as to bring about convergence of views on patenting.

On Convergence of Differential Evolution Over a Class of Continuous Functions With Unique Global Optimum

Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms of current interest. Since its inception in the mid 1990s, DE has been finding many successful applications in real-world optimization problems from diverse domains of science and engineering. This paper takes a first significant step toward the convergence analysis of a canonical DE (DE/rand/1/bin) algorithm. It first deduces a time-recursive relationship for the probability density function (PDF) of the trial solutions, taking into consideration the DE-type mutation, crossover, and selection mechanisms. Then, by applying the concepts of Lyapunov stability theorems, it shows that as time approaches infinity, the PDF of the trial solutions concentrates narrowly around the global optimum of the objective function, assuming the shape of a Dirac delta distribution. Asymptotic convergence behavior of the population PDF is established by constructing a Lyapunov functional based on the PDF and showing that it monotonically decreases with time. The analysis is applicable to a class of continuous and real-valued objective functions that possesses a unique global optimum (but may have multiple local optima). Theoretical results have been substantiated with relevant computer simulations.

Convergence problems in a class of model reference adaptive control systems

A class of model reference adaptive control system which make use of an augmented error signal has been introduced by Monopoli. Convergence problems in this attractive class of systems have been investigated in this paper using concepts from hyperstability theory. It is shown that the condition on the linear part of the system has to be stronger than the one given earlier. A boundedness condition on the input to the linear part of the system has been taken into account in the analysis - this condition appears to have been missed in the previous applications of hyperstability theory. Sufficient conditions for the convergence of the adaptive gain to the desired value are also given.

Reducing convergence times of self-propelled swarms via modified nearest neighbor rules

Vicsek et al. proposed a biologically inspired model of self-propelled particles, which is now commonly referred to as the Vicsek model. Recently, attention has been directed at modifying the Vicsek model so as to improve convergence properties. In this paper, we propose two modification of the Vicsek model which leads to significant improvements in convergence times. The modifications involve an additional term in the heading update rule which depends only on the current or the past states of the particle's neighbors. The variation in convergence properties as the parameters of these modified versions are changed are closely investigated. It is found that in both cases, there exists an optimal value of the parameter which reduces convergence times significantly and the system undergoes a phase transition as the value of the parameter is increased beyond this optimal value. (C) 2012 Elsevier B.V. All rights reserved.