Traditionally, human activity recognition has been achieved mainly by the statistical pattern recognition techniques such as the Nearest Neighbor Rule (NNR), and the state-space methods, e.g. the Hidden Markov Model (HMM). This paper proposes three novel approaches – the use of the Elman Network (EN) and two hybrids of Neural Network (NN) and HMM, i.e. HMM-NN and NN-HMM, to recognize ten simple...

In this paper we have used a Neural Networks approach for the estimation of the Round Trip Time (RTT) in the TCP protocol. We constructed a network operation scenario that approaches the Internet operation. By observing the traffic between different nodes we collected the RTT values during normal network operation. Then we organized these values in such a way so that part of them was used as a ...

The nucleon-nucleon (NN) potential is studied by lattice QCD simulations in the quenched approximation, using the plaquette gauge action and the Wilson quark action on a 32(4) [approximately (4.4 fm)(4)] lattice. A NN potential V(NN)(r) is defined from the equal-time Bethe-Salpeter amplitude with a local interpolating operator for the nucleon. By studying the NN interaction in the (1)S(0) and (...

A unified view of polymer, dumbbell, and oligonucleotide nearest-neighbor (NN) thermodynamics is presented. DNA NN DeltaG degrees 37 parameters from seven laboratories are presented in the same format so that careful comparisons can be made. The seven studies used data from natural polymers, synthetic polymers, oligonucleotide dumbbells, and oligonucleotide duplexes to derive NN parameters; use...

the spline collocation method  is employed to solve a system of linear and nonlinear fredholm and volterra integro-differential equations. the solutions are collocated by cubic b-spline and the integrand is approximated by the newton-cotes formula. we obtain the unique solution for linear and nonlinear system $(nn+3n)times(nn+3n)$ of integro-differential equations. this approximation reduces th...

OBJECTIVE To compare MSLT parameters in two groups of patients with daytime sleepiness, correlated to the occurrence and onset of dreams. METHOD Patients were submitted to the MSLT between January/1999 and June/2002. Sleep onset latency, REM sleep latency and total sleep time were determined. The occurrence of dreams was inquired following each MSLT series. Patients were classified as narcole...

The design and development of the neural network (NN)-based controller performance for the activated sludge process in sequencing batch reactor (SBR) is presented in this paper. Here we give a comparative study of various neural network (NN)-based controllers such as the direct inverse control, internal model control (IMC) and hybrid NN control strategies to maintain the dissolved oxygen (DO) l...

Rotor Flux based Model Reference Adaptive System (RF-MRAS) is the most popularly used conventional speed estimation scheme for sensor-less IM drives. In this scheme, the voltage model equations are used for the reference model. This encounters major drawbacks at low frequencies/speed which leads to the poor performance of RF-MRAS. Replacing the reference model using Neural Network (NN) based fl...

a critical point is a point at which the derivatives of an error function are all zero. It has been shown in the literature that critical points caused by the hierarchical structure of a realvalued neural network (NN) can be local minima or saddle points, although most critical points caused by the hierarchical structure are saddle points in the case of complex-valued neural networks. Several s...

The present work addresses the utilization of Artificial Neural Networks (NN) for the identification and control of systems, in special to control nonlinear dynamic systems or systems with some degree of uncertainty. Because NNs have an inherent ability to approximate functions and to adapt to changes in input and parameters, they can be used to control systems too complex for linear controller...