We use the BFKL equation to calculate the rate of deep inelastic scattering events containing two forward jets (adjacent to the proton remnants) at HERA. We compare the production of two forward jets with that of only one forward jet (the “Mueller” process). We obtain a stable prediction for this two to one jet ratio, which may serve as a measure of the BFKL vertex function.

Assuming that daily spot exchange rates follow a martingale process. we derive the implied time series process for the vector of 30-day forward rate forecast errors from using weekly data. The conditional second moment matrix of this vector is modeled as a multivariate generalized ARCH process. The estimated model is used to test the hypothesis that the risk premium is a linear function of the ...

This paper considers the modelling of collateralized debt obligations (CDOs). We propose a top-down model via forward rates generalizing Filipović, Overbeck and Schmidt (2009) to the case where the forward rates are driven by a finite dimensional Lévy process. The contribution of this work is twofold: we provide conditions for absence of arbitrage in this generalized framework. Furthermore, we ...

Let the underlying process Y be a semimartingale taking values in an interval I. Let φ : I → R be a difference of convex functions, and let X := φ(Y ). A typical application takes Y to be a positive price process and φ(y) = log y for y ∈ I = (0,∞). Then [the floating leg of] a forward-starting weighted variance swap or generalized variance swap on φ(Y ) (shortened to “on Y ” if the φ is underst...

In this study, efficient methods for optimal sensor placement (OSP) based on a new geometrical viewpoint for damage detection in structures is presented. The purpose is to minimize the effects of noise on the damage detection process. In the geometrical viewpoint, a sensor location is equivalent to projecting the elliptical noise on to a face of response space which is corresponding to the sens...

Basic definitions concerning the multi-layer feed-forward neural networks are given. The back-propagation training algorithm is explained. Partial derivatives of the objective function with respect to the weight and threshold coefficients are derived. These derivatives are valuable for an adaptation process of the considered neural network. Training and generalisation of multi-layer feed-forwar...

Bead-on-plate welding of zircaloy-4 (a reactive material) plates was conducted using electron beam according to central composite design of experiments. Its predictive models were developed in the form of knowledge-based systems in both forward and reverse directions using neural networks. Input parameters considered for this welding of reactive metals were accelerating voltage, beam current an...

Developing artificial neural network (ANN), a model to make a correct prediction of required force and torque in ring rolling process is developed for the first time. Moreover, an optimal state of process for specific range of input parameters is obtained using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. Radii of main roll and mandrel, rotational speed of main roll, pr...

We propose a general framework for broadcasting in ad hoc networks through self-pruning. The approach is based on selecting a small subset of hosts (also called nodes) to form a forward node set to carry out a broadcast process. Each node, upon receiving a broadcast packet, determines whether to forward the packet based on two neighborhood coverage conditions proposed in this paper. These cover...

In this paper, a novel MIMO Neural NARX model is used for simultaneously modeling and identifying both joints of the 2-axes PAM robot arm’s inverse and forward dynamic model. The highly nonlinear cross effect of both links of the 2-axes PAM robot arm are thoroughly modeled through an Inverse and Forward Neural MIMO NARX Model-based identification process using experimental input-output training...