In the theory of generalized metric spaces, the notion of knetworks has played an important role. Every locally separable metric space or CW-complex, more generally, every space dominated by locally separable metric spaces has a star-countable k-network. Every LaSnev space, as well as, every space dominated by LaSnev spaces has a a-compact-finite knetwork. We recall that every space has a compa...

Five classifiers including the K-means, Fuzzy c-means, K-nearest neighbour, Multi-Layer Perceptron Neural Network and Probabilistic Neural Network classifiers are compared for application to colour grade classification and detection of bruising of Granny Smith apples. A number of suitable discriminate features are determined heuristically for the categorisation of four classes including: high g...

Logistic network design is one of the most important strategic decisions in supply chain management that has recently attracted the attention of many researchers. Transportation network design is then one of the most important fields of logistic network. This study is concerned with designing a multi-stage and multi-product logistic network. At first, a mixed integer nonlinear programming model...

In a network with capacity h for multicast, information Xh = (X1, X2, · · · , Xh) can be transmitted from a source node to sink nodes without error by a linear network code. Furthermore, secret information S r = (S 1, S 2, · · · , S r) can be transmitted securely against wiretappers by k-secure network coding for k ≤ h−r. In this case, no information of the secret leaks out even if an adversary...

handwritten digit recognition can be categorized as a classification problem. probabilistic neural network (pnn) is one of the most effective and useful classifiers, which works based on bayesian rule. in this paper, in order to recognize persian (farsi) handwritten digit recognition, a combination of intelligent clustering method and pnn has been utilized. hoda database, which includes 80000 p...

Over the last two decades, robust optimization has emerged as a computationally attractive approach to formulate and solve single-stage decision problems affected by uncertainty. More recently, robust optimization has been successfully applied to multi-stage problems with continuous recourse. This paper takes a step towards extending the robust optimization methodology to problems with integer ...

We study two-stage robust optimization problems with mixed discrete-continuous decisions in both stages. Despite their broad range of applications, these problems pose two fundamental challenges: (i) they constitute infinite-dimensional problems that require a finite-dimensional approximation, and (ii) the presence of discrete recourse decisions typically prohibits dualitybased solution schemes...

The paper presents: (1) a graph-based theoretical background to refactoring a correct heterogeneous meta-program into its k-stage representation; (2) the refactoring method; (3) refactoring experiments with tasks taken from different domains, including real world tasks, such as meta-programs to teach Computer Science (CS) topics using educational robots. Refactoring meta-programs by staging ena...

The sequential algorithm for target detection in impulse environment by K-stage processing in polar Hough (PH) space is investigated. This algorithm permits the search radar to minimize the time of target detection, because the sequential detector used minimizes the number of the necessary radar antenna scans, while the conventional detector uses a fix scan number. The aim of our study is to mi...