In productivity analysis, the performance of production units is measured through the distance of the individual decision making units (DMU) to the technology which is defined as the frontier of the production set. Most of the existing methods, Farrell-Debreu and Shephard radial measures (input or output oriented) and hyperbolic distance functions, rely on multiplicative measures of the distanc...

Shape based classification of breast tumor and its corresponding analysis of micro and macrolabulated variations are important for future diagnostic purpose. There are two types of breast tumor named as benign and malignant. Benign type tumors having well defined regular shaped structure where the malignant type tumors having quite opposite nature like ill defined and irregular nature. The main...

We used a previously validated automated machine learning algorithm based on adaptive boosting to segment the hippocampi in baseline and 12-month follow-up 3D T1-weighted brain MRIs of 150 cognitively normal elderly (NC), 245 mild cognitive impairment (MCI) and 97 Dementia of the Alzheimer's type (DAT) ADNI subjects. Using the radial distance mapping technique, we examined the hippocampal corre...

BACKGROUND Anatomically, it is difficult to give a systematic description of the superficial branch of the radial nerve (SBRN). Our aim was to describe the exact relationship of the SBRN to fixed bony points of radial styloid and Lister's tubercle, and to the cephalic vein. We also compared our data with other international studies. METHODS The study was a descriptive anatomical study. Twenty...

Rodents move their whiskers to locate objects in space. Here we used psychophysical methods to show that head-fixed mice can localize objects along the axis of a single whisker, the radial dimension, with one-millimeter precision. High-speed videography allowed us to estimate the forces and bending moments at the base of the whisker, which underlie radial distance measurement. Mice judged radia...

Very few studies involve how to construct the efficient RBFs by means of problem features. Recently the present author presented general solution RBF (GS-RBF) methodology to create operator-dependent RBFs successfully [1]. On the other hand, the normal radial basis function (RBF) is defined via Euclidean space distance function or the geodesic distance [2]. This purpose of this note is to redef...

Radial Basis Function (RBF) networks typically use a distance function designed for numeric attributes, such as Euclidean or city-block distance. This paper presents a heterogeneous distance function which is appropriate for applications with symbolic attributes, numeric attributes, or both. Empirical results on 30 data sets indicate that the heterogeneous distance metric yields significantly i...