In this paper we propose a new approach for image classification by simplifying contour of shape and making use of the tangent function as image feature. We firstly extract shapes from a sample image and connecting pixels of its contour. The extracted contour is simplified by our algorithm and converted into tangent function which is regarded as a feature. The tangent function represented a sha...

Recent developments in the econometric estimation of multi-output, multi-input distance functions have provided a promising new solution to the single-output restriction implicit in the standard production function. However, a suspicion that regressor endogeneity may introduce possible simultaneous equations bias has concerned some econometricians. In this paper we show that, under profit maxim...

This paper proposes a Single Input Neuro-fuzzy Logic Controller based on Radial Basis Function Network (SI-NFRBFN) for non-linear systems. To obtain single input from multi inputs a Distance Method is suggested. Using this method all the uncertain inputs are simplified into a single input known as distance. With the help of this variable the control unit matrix introduced in Hybrid Neuro-fuzzy ...

The Hamming distance of a Boolean function to the functions having many linear structures is an important cryptographic parameter. Most notably, the accuracy of the approximation of the combining function by a function of fewer variables is a major issue in most attacks against combination generators. Here, we show that the distance of a function to the functions having a k-dimensional linear s...

This paper presents an analysis of technical efficiency and technology gap ratio (TGR) in greenhouse cucumber in Fars Province, Iran. Cucumber production was chosen for this study for the reason that greenhouse productions in this provincemainly have focused on this product. The data used in this study was obtained from a random sample of 127 greenhouses in Fars Province for 2010 to 2011. Metaf...

Abstract This paper proposes a new method to improve performance of AdaBoost by using a distance weight function to increase the accuracy of its machine learning processes. The proposed distance weight algorithm improves classification in areas where the original binary classifier is weak. This paper derives the new algorithm’s optimal solution, and it demonstrates how classifier accuracy can b...

We study the minimum random bit rate required to simulate a random system (channel), where the simulator operates with a given external input. As measures of simulation accuracy we use both the variational distance and the d distance between joint input-output distributions. We find the asymptotic number of random bits per input sample required for accurate simulation, as a function of the dist...

using the electrostatic capacity of a condenser, the existence of a distance function on a finsler space is discussed. this distance function divides finsler spaces into the two classes, denoted here by i and ii. the topology generated by this distance on the finsler spaces of class ii coincides with its intrinsic topology. this work provides a natural extension of mathematical analysis tools n...