Abstract In the present paper we examine a projectively flat spacetime solution of F ( R )-gravity theory. It is seen that once deploy projective flatness in geometry spacetime, matter field has constant energy density and isotropic pressure. We then make condition weaker discuss effects harmonic theory show this case reduces to generalised Robertson-Walker with shear, vorticity, acceleration f...

Standard analysis methods for genome wide association studies (GWAS) are not robust to complex disease models, such as interactions between variables with small main effects. These types of effects likely contribute to the heritability of complex human traits. Machine learning methods that are capable of identifying interactions, such as Random Forests (RF), are an alternative analysis approach...

The present paper deals with metallic K?hler manifolds. Firstly, we define a tensor H which can be written in terms of the (0,4)-Riemannian curvature and fundamental 2-form manifold study its properties some hybrid tensors. Secondly, weobtain conditions under Hermitian is conformal to manifold. Thirdly, prove that recurrency implies also obtain Riemannian form conformally recurrent non-zero sca...

This paper details the developments to date of an unmanned air vehicle (UAV) based on a standard size 60 model helicopter. The design goal is to have the helicopter achieve stable hover with the aid of an INS and stereo vision. The focus of this paper is on the development of an artificial neural network (ANN) that makes use of only the INS data to generate hover commands, which are used to dir...

Results are presented of a simulation which mimics an evolutionary learning process for small networks. Special features of these networks include a high recurrency, a transition function which decreases for large input activities, and the absence of tunable weights attached to the lines the line is either there (weight 1) or absent (weight 0). It is remarkable that already these simple systems...

We present a novel approach to unsupervised temporal sequence processing in the form of an unsupervised, recurrent neural network based on a selforganizing map (SOM). A standard SOM clusters each input vector irrespective of context, whereas the recurrent SOM presented here clusters each input based on an input vector and a context vector. The latter acts as a recurrent conduit feeding back a 2...