Articles — Essay

In this paper we will study an algorithm designed by Madgwick which is commonly used to determine the orientation of a quadcopter. The algorithm uses a group of accelerometers, gyroscopes and magnetometers integrated in what is called an IMU as input. Some differences have been found between the results obtained by the original paper and the implementation done by the author. Therefore, a thorough study has been made, finding a miscalculation in the equations. The results show a relative average error in the orientation of 1,44 ppm.

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Software is designed to simplify the lives of its users. The rapid growth of social media and the technology industry has foreseen a plethora of different types of software used as a service, with the aim of engaging its users and creating a form of revenue. With an abundance of software applications from which to choose from, this paper looks into the types of communication between the user and the application itself, and how automation and disruptive notification are intertwined to form a successful application.

a report for PMB

Senior high school student interested in math, hope to make math friends. lzakaria54@gmail.com

We describe computer experiments suggesting that there is an infinite family L of Riemann zeta cycles Λ of each size L = 1, 2, 3, ....

A proof of the product integral using derivatives and and the limit of a difference quotient to certify its identity as an integral of the natural logarithm.

Código ASCII

This project focuses on a modification of a greedy transition based dependency parser. Typically a Part-Of-Speech (POS) tagger models a probability distribution over all the possible tags for each word in the given sentence and chooses one as its best guess. This is then pass on to the parser which uses this information to build a parse tree. The current state of the art for POS tagging is about 97% word accuracy, which seems high but results in a around 56% sentence accuracy. Small errors at the POS tagging phase can lead to large errors down the NLP pipeline and transition based parsers are particularity sensitive to these types of mistakes. A maximum entropy Markov model was trained as a POS multi-tagger passing more than its 1-best guess to the parser which was thought could make a better decision when committing to a parse for the sentence. This has been shown to give improved accuracy in other parsing approaches. We shown there is a correlation between tagging ambiguity and parsers accuracy and in fact the higher the average tags per word the higher the accuracy.