After Victory Ikenberry, G. John
2019, 2019-01-22, Letnik:
161
eBook
The end of the Cold War was a big bang reminiscent of earlier moments after major wars, such as the end of the Napoleonic Wars in 1815 and the end of the world wars in 1919 and 1945. But what do ...states that win wars do with their newfound power, and how do they use it to build order? In After Victory , John Ikenberry examines postwar settlements in modern history, arguing that powerful countries do seek to build stable and cooperative relations, but the type of order that emerges hinges on their ability to make commitments and restrain power. He explains that only with the spread of democracy in the twentieth century and the innovative use of international institutions—both linked to the emergence of the United States as a world power—has order been created that goes beyond balance of power politics to exhibit constitutional characteristics. Blending comparative politics with international relations, and history with theory, After Victory will be of interest to anyone concerned with the organization of world order, the role of institutions in world politics, and the lessons of past postwar settlements for today.
After victory Ikenberry, G. John
2008., 20090701, 2009, 2000, 2009-07-01, Letnik:
117
eBook
The end of the Cold War was a "big bang" reminiscent of earlier moments after major wars, such as the end of the Napoleonic Wars in 1815 and the end of the World Wars in 1919 and 1945. Here John ...Ikenberry asks the question, what do states that win wars do with their newfound power and how do they use it to build order? In examining the postwar settlements in modern history, he argues that powerful countries do seek to build stable and cooperative relations, but the type of order that emerges hinges on their ability to make commitments and restrain power.
Convolutions of independent random variables often arise in a natural way in many applied areas. In this paper, we study various stochastic orderings of convolutions of heterogeneous gamma random ...variables in terms of the majorization order
p
-larger order, reciprocal majorization order of parameter vectors and the likelihood ratio order dispersive order, hazard rate order, star order, right spread order, mean residual life order between convolutions of two heterogeneous gamma sets of variables wherein they have both differing scale parameters and differing shape parameters. The results established in this paper strengthen and generalize those known in the literature.
A systematic method for approximating the complex‐order Laplacian operator by realizable integer‐order transfer functions is presented in this work. The realization is performed by a simple structure ...where only one active element is used. Thanks to the employment of complex‐order impedances, both integrators and differentiators can be readily implemented by the same core simply by interchanging the associated impedance locations. The validity of the presented concept is verified through simulation and experimental results, using the OrCAD PSpice suite and a Field Programmable Analog array device.
A systematic method for approximating the complex‐order Laplacian operator by realizable integer‐order transfer functions is presented in this work. Both integrators and differentiators can be readily implemented by the same core. Discrete component and FPAA‐based implementations are provided for confirming the validity of the presented concept.
With the increasing penetration of electronic loads and distributed energy resources, conventional load models cannot capture their dynamics. Therefore, a new comprehensive composite load model is ...developed by Western Electricity Coordinating Council (WECC). However, this model is a complex high-order non-linear system with multi-time-scale property, which poses challenges on power system studies with heavy computational burden. In order to reduce the model complexity, the authors firstly develop a large-signal order reduction (LSOR) method using singular perturbation theory. In this method, the fast dynamics are integrated into the slow ones to preserve transient characteristics of the former. Then, accuracy assessment conditions are proposed and embedded into the LSOR to improve and guarantee the accuracy of reduced-order model. Finally, the reduced-order WECC composite load model is derived by using the proposed algorithm. Simulation results show that the reduced-order large-signal model significantly alleviates the computational burden while maintaining similar dynamic responses as the original composite load model.
This study compares two different series systems under various scenarios for which the components are assumed to be heterogeneous and follow Gompertz-G distributions. In the first scheme, the ...components of the systems are supposed to be independently distributed. In the second, we compared two series systems in the case that the independent components also experience random shocks. In the last scenario, we considered a case where the components of the systems have dependent structure sharing Archimedean copula. However, in all scenarios, the comparisons are performed based on the concepts of usual stochastic, the hazard rate, and the likelihood ratio orders through the majorization of the Gompertz-G parameters.
Today, there is a great tendency toward using fractional calculus to solve engineering problems. The control is one of the fields in which fractional calculus has attracted a lot of attention. On the ...one hand, fractional order dynamic models simulate characteristics of real dynamic systems better than integer order models. On the other hand, Fractional Order (FO) controllers outperform Integer Order (IO) controllers in many cases. FO-controllers have been studied in both time an frequency domain. The latter one is the fundamental tool for industry to design FO-controllers. The scope of this paper is to review research which has been carried out on FO-controllers in the frequency domain. In this review paper, the concept of fractional calculus and their applications in the control problems are introduced. In addition, basic definitions of the fractional order differentiation and integration are presented. Then, four common types of FO-controllers are briefly presented and after that their representative tuning methods are introduced. Furthermore, some useful continuous and discrete approximation methods of FO-controllers and their digital and analogue implementation methods are elaborated. Then, some Matlab toolboxes which facilitate utilizing FO calculus in the control field are presented. Finally, advantages and disadvantages of using FO calculus in the control area are discussed. To wrap up, this paper helps beginners to get started rapidly and learn how to select, tune, approximate, discretize, and implement FO-controllers in the frequency domain.
Solving nonlinear equations in Banach spaces (real or complex nonlinear equations, nonlinear systems, and nonlinear matrix equations, among others), is a non-trivial task that involves many areas of ...science and technology. Usually the solution is not directly affordable and require an approach using iterative algorithms. This Special Issue focuses mainly on the design, analysis of convergence, and stability of new schemes for solving nonlinear problems and their application to practical problems. Included papers study the following topics: Methods for finding simple or multiple roots either with or without derivatives, iterative methods for approximating different generalized inverses, real or complex dynamics associated to the rational functions resulting from the application of an iterative method on a polynomial. Additionally, the analysis of the convergence has been carried out by means of different sufficient conditions assuring the local, semilocal, or global convergence. This Special issue has allowed us to present the latest research results in the area of iterative processes for solving nonlinear equations as well as systems and matrix equations. In addition to the theoretical papers, several manuscripts on signal processing, nonlinear integral equations, or partial differential equations, reveal the connection between iterative methods and other branches of science and engineering.
Ordering relations such as total orders, partial orders and preorders play important roles in a host of applications such as automated decision making, image processing, and pattern recognition. A ...total order that extends a given partial order is called an admissible order and a preorder that arises by mapping elements of a non-empty set into a poset is called an h-order or reduced order. In practice, one often considers a discrete setting, i.e., admissible orders and h-orders on the class of non-empty, closed subintervals of a finite set Ln={0,1,...,n}. We denote the latter using the symbol In⁎. Admissible orders and h-orders on In⁎ can be generated by the function that maps each interval x=x_,x‾∈In⁎ to the convex combination Kα(x)=(1−α)x_+αx‾ of its left and right endpoints. In this paper, we determine a set consisting of a finite number of relevant α's in 0,1 that generate different h-orders on In⁎. For every n∈N, this set allows us to construct the families of all h-orders and admissible orders on In⁎ that are determined by some convex combination. We also provide formulas for the cardinalities of these families in terms of Euler's totient function.
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