Omid Bakhshandeh Babarsad

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Path planning together with the tuning and determination of controller parameters are major concerns in omnidirectional mobile robots. Defining appropriate controller parameters in acceleration and deceleration to reach far and near target points without slippage is one of critical issues since some troubles due to unregulated velocities may greatly affect(More)
Today, research on automatic text summarization challenges on readability factor as one of the most important aspects of summarizers' performance. In this paper, we present Pazesh: a language-independent graph-based approach for increasing the readability of summaries while preserving the most important content. Pazesh accomplishes this task by constructing(More)
This paper presents a novel method for answering complex temporal ordering questions in the context of an event and query-based text summarization. This task is accomplished by precisely mapping the problem of " query-based summarization of temporal ordering questions " in the field of Natural Language Processing to " verifying a finite state model against(More)
proper public and private inference rules in FOCET, we are able to complement raw context data by adding more deduced facts from existing known ones. Using weight and relevancy matrices we are able to scale (up/down) the effect of context in evaluating trust. There are number of future works we could consider to extend our model. Uncertainty is an important(More)
While most imaging devices use the Bayer pattern, virtually all vision methods assume the availability of information for a complete color space. This creates the need for demosaicing step, for which even the fastest naïve interpolation is in some applications a computational burden. In this paper, a complete real-time vision infrastructure is built(More)
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