Gallery — Project / Lab Report

Pacotes fundamentais

A dual energy radiography method using basis decomposition was developed, the process to do it is shown and it is compared against an alternate more direct method of analyzing the data using the logarithm of the original data, concluding that this second method does work but it is not better than basis decomposition.

Quantum Dots are semiconductor nanocrystals whose diameter is in the range of 2-10 nm, corre- sponding to 10 to 50 atoms in diameter and a total of 100 to 100,000 atoms within the quantum dot volume. Many types of quantum dot emit light of specific frequencies if electricity or light is applied to them, and these frequencies can be precisely tuned by changing the dots’ size, shape and material, giving rise to many applica- tions. Because of their high tunable properties, quantum dots are of wide interest. It finds its applications in nanotechnology, medical imaging, transistors, solar cells, LED’s, diode lasers, quantum computing, etc. With this project, we intend to further understand and study the properties of quantum dots by using atomic force microscopy.

Se pretende describir el decaimiento de una partícula α encontrando los niveles de energía Eα correspondientes a los estados ligados de la partícula producto de la desintegración. Los niveles de energía y los estados ligados se encuentran mediante dos métodos de aproximación: WKB y diferencias finitas. Posteriormente se halla el tiempo de vida medio τ, se comparan los resultados con los de la literatura y se decide el mejor método de solución acorde con la literatura.

A report created with the Project Report template at howtotex.com.

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.

Trabalho de Cálculo 4 - CEFET/MG

Template for the the final project of the course.

The purpose of this report is to explain how – by leveraging on the capabilities of the amazon web services – it is possible to manage and process a set of data that is too large and complex for traditional data processing techniques and technologies. The report discusses the implementation of a set of services – from the retrieval of external data to its transformation, through the storage on non relational databases and finally the parallel computation on an external cluster – meant for the management of discographic information in order to easily join different data in an agile manner and subsequently perform additional processing based on the joined output.