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This paper presents an approach to eliminate a representative set of testing cases from a test suite but provide the same coverage as the entire test suite. This approach mainly is based on graph theory and maps the relationship between inputs and outputs of tested system into the bipartite graph. Using the properties of bipartite graph decompose the entire test suite into some small test suites so...
Semi-Supervised Learning (SSL) is a machine learning research area aiming the development of techniques which are able to take advantage from both labeled and unlabeled samples. Additionally, most of the times where SSL techniques can be deployed, only a small portion of samples in the data set is labeled. To deal with such situations in a straightforward fashion, in this paper we introduce a semi-supervised...
Given a graph and an integer L ?? 0, the beacon placement problem (BPP) asks to find a minimum set B of nodes such that for all edges e, at least one of the two endpoints of e can be reached from some node (called an L-beacon) in B using at most L edges. In particular, it reduces to the vertex cover problem if L = 0. This problem arises from link-monitoring in computer networks. Generalizing the works...
Data clustering is an important technique to extract and understand relevant information in large data sets. In this paper, a clustering algorithm based on graph theoretic models and community detection in complex networks is proposed. Two steps are involved in this processing: The first step is to represent input data as a network and the second one is to partition the network into subnetworks producing...
Traditional data clustering techniques present difficulty in determination of clusters of arbitrary forms. On the other hand, graph theoretic methods seek topological orders among input data and, consequently, can solve the above mentioned problem. In this paper, we present an improved graph theoretic model for data clustering. The clustering process of this model is composed of two steps: network...
The minimum vertex ranking spanning tree problem (MVRST) is to find a spanning tree of G whose vertex ranking is minimum. In this paper, we show that MVRST is NP-hard. To prove this, we polynomially reduce the 3-dimensional matching problem to MVRST. Moreover, we present a (⌈Ds/2⌉+1)/(⌊log2(Ds+1)⌋+1)-approximation algorithm for MVRST where Ds is the minimum diameter of spanning trees of G.
In this paper a distributed topology control for stationary and mobile ad hoc networks is described. A topology control algorithm is aimed at maintaining connectivity in a mobile network while minimizing power consumption under the MinMax objective. The algorithm is proactive so that the network connectivity is guaranteed at any time instant. In regard to the topology of the graph induced by the power...
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