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This paper proposes a method to cluster documents of variable length. The main idea is to apply (a) automatic identification of 1, 2, and 3 grams (To reduce the dependency on huge background vocabulary support or learning or complex probabilistic approach), (b) order them by some measure of relevance, which is developed with the help of Tf-Idf and Term-Weighting approach, and finally (c) use them...
Stream ciphers are widely used for information security. The keystream produced by a cipher must be unpredictable. Attacks on stream ciphers typically exploit some underlying patterns existing in the keystream. The objective of this paper is to develop such an attack with the help of machine learning algorithms. The Linear Feedback Shift Register (LFSR) has been solved for several test cases using...
Semisupervised clustering algorithms partition a given data set using limited supervision from the user. The success of these algorithms depends on the type of supervision and also on the kind of dissimilarity measure used while creating partitions of the space. This paper proposes a clustering algorithm that uses supervision in terms of relative comparisons, viz., x is closer to y than to z. The...
This paper proposes a neural network (NN) based control scheme for coordinated multiple robot manipulators carrying a common object. Firstly, an integrated dynamic model of the manipulators and the object is derived in terms of object position and orientation as states of the derived model. Based on this model a controller is proposed that achieves the stability in the sense of Lyapunov for the trajectory...
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