the large amount of computation necessary for obtaining time optimal solution for moving a manipulator on specified path has made it impossible to introduce an on line time optimal control algorithm. most of this computational burden is due to calculation of switching points. in this paper a learning algorithm is proposed for finding the switching points. the method, which can be used for both ...

The dimensions of neuronal dendrites, axons, and synaptic terminals are reproducibly specified for each neuron type, yet it remains unknown how these structures acquire their precise dimensions of length and diameter. Similarly, it remains unknown how active zone number and synaptic strength are specified relative the precise dimensions of presynaptic boutons. In this paper, we demonstrate that...

Higher levels of integration have led to a generation of integrated circuits for which power dissipation and reliability are major design concerns. In CMOS circuits, both of these problems are directly related to the extent of circuit switching activity. The average number of transitions per second at a circuit node is a measure of switching activity thit has been called the transition density....

Business process management (BPM) has emerged as a dominant technology in current enterprise systems and business solutions. However, the technology continues to face challenges in coping with dynamic business environments where requirements and goals are constantly changing. In this paper, we present a modelling framework for business processes that is conducive to dynamic change and the need ...

In this paper back-propagation artificial neural network (BPANN) is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the...

In this paper back-propagation artificial neural network (BPANN) with Levenberg–Marquardt algorithm is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent ...

Recent literature on semiparametric copula models focused on the situation when the marginals are specified nonparametrically and the copula function is given a parametric form. For example, this setup is used in Chen, Fan and Tsyrennikov (2006) [Efficient Estimation of Semiparametric Multivariate Copula Models, JASA] who focus on the efficient estimation of copula parameters. We consider a rev...

Formally-specified computations are defined by logical statements (a.k.a. claims) interpreted in a computable model. Semantic Games (SGs) of claims provide novel answers to crowdsourcing challenges yet with several limitations. We provide a comprehensive analysis of the limitations of SGs when used for crowdsourcing and propose a new concept, called the Contradiction-Agreement Game (CAG), which...

We study the Partial Nearest Neighbor Problem that consists in preprocessing n points D from d-dimensional metric space such that the following query can be answered efficiently: Given a query vector Q ∈ R and an axes-aligned query subspace represented by S ∈ {0, 1}, report a point P ∈ D with dS(Q,P ) ≤ dS(Q,P ′) for all P ′ ∈ D, where dS(Q,P ) is the distance between Q and P in the subspace S....

Significant research efforts have been devoted in recent years to the development of displacement-based seismic design methodologies, recognizing the shortcomings of traditional, code-specified force-based design procedures. Recent advances in direct displacement-based seismic design of columns rely on the estimates of yield curvature for the determination of seismic design forces to satisfy th...