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Parallel corpora are essential for training statistical machine translation models. Since parallel sentence-aligned corpora are usually noisy due to inexact automatic methods when generated from parallel or comparable documents, we need to clean parallel corpora. In this paper, new features are introduced to assess the correctness of a sentence pair. Also, the impact of new features in combination...
Although RED has been widely used with TCP, however it has several known drawbacks [1]. The BLUE algorithm that benefits from a different structure has tried to compensate some of them in a successful way [2]. A quick review on active queue management algorithms from the very beginning indicates that most of them tried to improve classic algorithms. Some of them use network traffic history to achieve...
Statistical properties of natural signals is an important factor in forming neuronal selectivities of brain sensory system. One such property is the redundancy in visual and auditory inputs to the brain. In this paper, we introduce the concept of class specific redundancies in natural images and propose that the selectivity of neurons in extrastriate visual areas is developed to reveal these redundancies...
Mobile robot global path planning in a static environment is an important problem. This paper proposes a method of global path planning based on genetic algorithm to reach an optimum path for mobile robot with obstacle avoidance. In this method for decreasing the complexity, the two-dimensional coding for the path via-points was converted to one-dimensional coding and the fitness of both of the collision...
PSO is an evolutionary algorithm that is inspired from collective behavior of animals such as fish schooling or bird flocking. One of the drawbacks of this model is premature convergence and trapping in local optima. In this paper we propose a solution to this problem in discrete version of PSO that uses Learning Automata and introduce a cellular learning automata (CLA) based discrete PSO. Experimental...
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