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The climate system can be regarded as a dynamic nonlinear system. Thus, traditional linear statistical methods fail to model the nonlinearities of such a system. These nonlinearities render it necessary to find alternative statistical techniques. Since artificial neural network models (NNM) represent such a nonlinear statistical method their use in analyzing the climate system has been studied for a couple of years now. Most authors use the standard Backpropagation Network (BPN) for their investigations, although this specific model architecture carries a certain risk of over-/underfitting. Here we use the so called Cauchy Machine (CM) with an implemented Fast Simulated Annealing schedule (FSA) (Szu, 1986) for the purpose of attributing and detecting anthropogenic climate change instead. Under certain conditions the CM-FSA guarantees to find the global minimum of a yet undefined cost function (Geman and Geman, 1986). In addition to potential anthropogenic influences on climate (greenhouse gases (GHG), sulphur dioxide (SO2)) natural influences on near surface air temperature (variations of solar activity, explosive volcanism and the El Nino = Southern Oscillation phenomenon) serve as model inputs. The simulations are carried out on different spatial scales: global and area weighted averages. In addition, a multiple linear regression analysis serves as a linear reference. It is shown that the adaptive nonlinear CM-FSA algorithm captures the dynamics of the climate system to a great extent. However, free parameters of this specific network architecture have to be optimized subjectively. The quality of the simulations obtained by the CM-FSA algorithm exceeds the results of a multiple linear regression model; the simulation quality on the global scale amounts up to 81% explained variance. Furthermore the combined anthropogenic effect corresponds to the observed increase in temperature Jones et al. (1994), updated by Jones (1999a), for the examined period 1856–1998 on all investigated scales. In accordance to recent findings of physical climate models, the CM-FSA succeeds with the detection of anthropogenic induced climate change on a high significance level. Thus, the CMFSA algorithm can be regarded as a suitable nonlinear statistical tool for modeling and diagnosing the climate system.
Observed global and European spatiotemporal related fields of surface air temperature, mean-sea-level pressure and precipitation are analyzed statistically with respect to their response to external forcing factors such as anthropogenic greenhouse gases, anthropogenic sulfate aerosol, solar variations and explosive volcanism, and known internal climate mechanisms such as the El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). As a first step, a principal component analysis (PCA) is applied to the observed spatiotemporal related fields to obtain spatial patterns with linear independent temporal structure. In a second step, the time series of each of the spatial patterns is subject to a stepwise regression analysis in order to separate it into signals of the external forcing factors and internal climate mechanisms as listed above as well as the residuals. Finally a back-transformation leads to the spatiotemporally related patterns of all these signals being intercompared. Two kinds of significance tests are applied to the anthropogenic signals. First, it is tested whether the anthropogenic signal is significant compared with the complete residual variance including natural variability. This test answers the question whether a significant anthropogenic climate change is visible in the observed data. As a second test the anthropogenic signal is tested with respect to the climate noise component only. This test answers the question whether the anthropogenic signal is significant among others in the observed data. Using both tests, regions can be specified where the anthropogenic influence is visible (second test) and regions where the anthropogenic influence has already significantly changed climate (first test).
First results on the production of Xi- and Anti-xi hyperons in Pb+Pb interactions at 40 A GeV are presented. The Anti-xi/Xi- ratio at midrapidity is studied as a function of collision centrality. The ratio shows no significant centrality dependence within statistical errors; it ranges from 0.07 to 0.15. The Anti-xi/Xi- ratio for central Pb+Pb collisions increases strongly with the collision energy.
Deutsche Fassung: Expertise als soziale Institution: Die Internalisierung Dritter in den Vertrag. In: Gert Brüggemeier (Hg.) Liber Amicorum Eike Schmidt. Müller, Heidelberg, 2005, 303-334.
Coreference-Based Summarization and Question Answering: a Case for High Precision Anaphor Resolution
(2003)
Approaches to Text Summarization and Question Answering are known to benefit from the availability of coreference information. Based on an analysis of its contributions, a more detailed look at coreference processing for these applications will be proposed: it should be considered as a task of anaphor resolution rather than coreference resolution. It will be further argued that high precision approaches to anaphor resolution optimally match the specific requirements. Three such approaches will be described and empirically evaluated, and the implications for Text Summarization and Question Answering will be discussed.
This paper is focused on the coordination of order and production policy between buyers and suppliers in supply chains. When a buyer and a supplier of an item work independently, the buyer will place orders based on his economic order quantity (EOQ). However, the buyer s EOQ may not lead to an optimal policy for the supplier. It can be shown that a cooperative batching policy can reduce total cost significantly. Should the buyer have the more powerful position to enforce his EOQ on the supplier, then no incentive exists for him to deviate from his EOQ in order to choose a cooperative batching policy. To provide an incentive to order in quantities suitable to the supplier, the supplier could offer a side payment. One critical assumption made throughout in the literature dealing with incentive schemes to influence buyer s ordering policy is that the supplier has complete information regarding buyer s cost structure. However, this assumption is far from realistic. As a consequence, the buyer has no incentive to report truthfully on his cost structure. Moreover there is an incentive to overstate the total relevant cost in order to obtain as high a side payment as possible. This paper provides a bargaining model with asymmetric information about the buyer s cost structure assuming that the buyer has the bargaining power to enforce his EOQ on the supplier in case of a break-down in negotiations. An algorithm for the determination of an optimal set of contracts which are specifically designed for different cost structures of the buyer, assumed by the supplier, will be presented. This algorithm was implemented in a software application, that supports the supplier in determining the optimal set of contracts.
We present a novel practical algorithm that given a lattice basis b1, ..., bn finds in O(n exp 2 *(k/6) exp (k/4)) average time a shorter vector than b1 provided that b1 is (k/6) exp (n/(2k)) times longer than the length of the shortest, nonzero lattice vector. We assume that the given basis b1, ..., bn has an orthogonal basis that is typical for worst case lattice bases. The new reduction method samples short lattice vectors in high dimensional sublattices, it advances in sporadic big jumps. It decreases the approximation factor achievable in a given time by known methods to less than its fourth-th root. We further speed up the new method by the simple and the general birthday method. n2
We enhance the security of Schnorr blind signatures against the novel one-more-forgery of Schnorr [Sc01] andWagner [W02] which is possible even if the discrete logarithm is hard to compute. We show two limitations of this attack. Firstly, replacing the group G by the s-fold direct product G exp(×s) increases the work of the attack, for a given number of signer interactions, to the s-power while increasing the work of the blind signature protocol merely by a factor s. Secondly, we bound the number of additional signatures per signer interaction that can be forged effectively. That fraction of the additional forged signatures can be made arbitrarily small.
Presentation at the Università di Pisa, Pisa, Itlay 3 July 2002, the conference on Irreversible Quantum Dynamics', the Abdus Salam ICTP, Trieste, Italy, 29 July - 2 August 2002, and the University of Natal, Pietermaritzburg, South Africa, 14 May 2003. Version of 24 April 2003: examples added; 16 December 2002: revised; 12 Sptember 2002. See the corresponding papers "Zeno Dynamics of von Neumann Algebras", "Zeno Dynamics in Quantum Statistical Mechanics" and "Mathematics of the Quantum Zeno Effect"