In Radial Basis Neural Networks (RBNN), the activation of each neuron depends on the Euclidean distance between a pattern and the neuron center. Such a symmetrical activation assumes that all attributes are equally relevant, which might not be true. Non-symmetrical distances like Mahalanobis can be used. However, this distance is computed directly from the data covariance matrix and therefore t...

We present radial velocity and new interferometric measurements of the double star Atlas, which permit, with the addition of published interferometric data, to precisely derive the orbital parameters of the binary system and the masses of the components. The derived semi-major axis, compared with its measured angular size, allows to determine a distance to Atlas of 132± 4 pc in a purely geometr...

BACKGROUND There is no consensus in the literature as to which point of the radial artery (RA) is the safest to attempt vascular access. The purpose of this study was to measure the diameter, tortuosity and branching patterns of the distal RA. MATERIALS AND METHODS 140 cadaveric RAs (66 male, 74 female) were dissected and measured. The external diameter of the RA was measured at 2 cm incremen...

We consider distance-based similarity measures for real-valued vectors of interest in kernel-based machine learning algorithms. In particular, a truncated Euclidean similarity measure and a self-normalized similarity measure related to the Canberra distance. It is proved that they are positive semi-definite (p.s.d.), thus facilitating their use in kernel-based methods, like the Support Vector M...

BACKGROUND To describe the radial artery and its variants in origin, branching pattern, mode of termination, and measurements of its length and external diameter. MATERIAL AND METHODS One hundred upper limbs of 30 men and 20 women adult cadavers were used in this study. The cadavers were obtained from the Anatomy Department, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia...