We investigate the extent to which the nuclear transverse response to electron scattering in the quasielastic region, evaluated in the random-phase approximation, can be described by ring approximation calculations. Different effective interactions based on a standard model of the type g81Vp1Vr are employed. For each momentum transfer, we have obtained the value of g08 permitting the ring respo...

The reactions of allylic radicals have the potential to play a critical role in molecular weight growth (MWG) kinetics during hydrocarbon oxidation and/or pyrolysis. Due to their stability (when compared to alkyl radicals), they can accumulate to relatively high concentrations. Thus, even though the rate coefficients for their various reactions are small, the rates of these reactions may be sig...

This paper considers the automatic design of fuzzy rule-based classification systems from labeled data. The classification accuracy and interpretability of generated rules are of major importance in fuzzy classification systems. We propose a weighting function for compatibility grade of patterns that improves the performance of fuzzy classification system without degrading the interpretability ...

An anti-Hebbian local learning algorithm for two-layer optical neural networks is introduced. With this learning rule, the weight update for a certain connection depends only on the input and output of that connection and a global, scalar error signal. Therefore the backpropagation of error signals through the network, as required by the commonly used back error propagation algorithm, is avoide...

In this paper, we describe the system used by the UMIST team as members of the FACILE consortium, to undertake the NE task in MUC-7. The main characteristics of this system employed are as follows: it is rule-based its rule formalism supports context-sensitive partial parsing rules may use pattern-matching-style iteration operators the notation is much more readable than classic pattern-matchin...

We explore neural network learning and parallel human learning on an artificial language task. The task generates rich data on human interaction with syntactic systems, including recursive ones. Studying the network’s properties, we argue for a “Structured Manifold” view of syntactic representation. The “Structured Manifold” lies in the parameter space (weight space) of the network. It exhibits...

In this paper, we investigate the aggregate behavior of populations of learning agents. We compare the outcomes in homogenous populations learning in accordance with imitate the best dynamics and with replicator dynamics to outcomes in populations that mix these two learning rules. New outcomes can emerge. In certain games, a linear combination of the two rules almost always attains an equilibr...

In order to solve the overfitting of sample weights and the low detection rate in training process of the traditional AdaBoost algorithm, an improved AdaBoost algorithm based on Haar-like features and LBP features is proposed. This method improves weight updating rule and weights normalization rule of the traditional AdaBoost algorithm. Then combining this method with the AdaBoost algorithm bas...

Let (G,K) be a Hermitian symmetric pair and let g and k denote the corresponding complexified Lie algebras. Let g = k⊕p+⊕p− be the usual decomposition of g as a k-module. K acts on the symmetric algebra S(p−). We determine the K-structure of all K-stable ideals of the algebra. Our results resemble the Pieri rule for Young diagrams. The result implies a branching rule for a class of finite dimen...