Articles — Project / Lab Report

An bachelor experimental physics project at Niels Bohr Insititue (The template for this report can be found here.)

In the last few years the resolution of NLP tasks with architectures composed of neural models has taken vogue. There are many advantages to using these approaches especially because there is no need to do features engineering. In this paper, we make a survey of a Deep Learning architecture that propose a resolutive approach to some classical tasks of the NLP. The Deep Learning architecture is based on a cutting-edge model that exploits both word-level and character-level representations through the combination of bidirectional LSTM, CNN and CRF. This architecture has provided cutting-edge performance in several sequential labeling activities for the English language. The architecture that will be treated uses the same approach for the Italian language. The same guideline is extended to perform a multi-task learning involving PoS labeling and sentiment analysis. The results show that the system performs well and achieves good results in all activities. In some cases it exceeds the best systems previously developed for Italian.

Interaction Design. The purpose of the mini-project is to apply the methodology and theory presented in the lectures to a concrete design problem.

The kernel is a computer program that has complete control over the operating system. It handles the input/output requests and translates them into data-processing instructions for the CPU. It handles not only the memory, but also peripherals. The kernel controls the tasks that are managed in the running system, some of these are running processes, hardware management and handling interrupts, in the kernel space. On the other hand, the user performs in the user space. This separation helps to prevent data interfering that can cause instability and slowness, or worse, malfunctioning application programs that can crash the entire operating system. The process scheduler decides which is the next task to run. In the following project we analyzed the behavior of the scheduler changing the default value of the runtime scheduling, this value is 950000µs for the scheduler real time running variable. According to this, 5% of the CPU time is reserved for processes that are not running under a realtime or deadline scheduling policy. On this project, this value specifies how much of the period time could be used by real-time and deadline scheduled processes on the system.

El inductivismo saca conclusiones generales de algo particular. Este ha sido el método científico más común utilizado y sobre éste surgieron nuevos paradigmas para hacer ciencia. Se analizarán las características y limitantes de este método.

Relatório de estágio desenvolvido para a obtenção do título de Bacharel em Ciência da Computação no Instituto de Computação na Universidade Federal de Mato Grosso.

En ingenieria un canal es una construccion cuyo destino es el transporte de fluidos en donde se busca realizar una descripcion del comportamiento hidraulico de los canales, en este trabajo se busca determinar ciertos parametros de un canal para observar el comportamiento del agua en este y calcular parametros por medio del flujo crítico en donde se deben plantear una serie de ecuaciones en función de su tirante crítico (Yc).

Laboratorio 3

We study Logarithmically Spiral Trajectories and, in particular, we look for a solution to minimize the transit time of a Spacecraft propelled by a Solar Sail, while simultaneously minimizing the area of the Solar Sail, which would allow us to carry more payload on board. We start by analyzing the forces that act on the Spacecraft taking into account that its propellant is a Solar Sail; we use the studied forces to deduce the motion equations. We then solve this motion equation with a Runge-Kutta 4 method and transform the problem of minimizing time and area to a Non-linear Optimization problem. When solving the NLP we also try to minimize the relative final speed of th spacecraft with the destination planet in order to guarantee the possibility of a safe landing on its surface. The model improves when an angle parameter α (describing the angle formed by the Solar Sail with the colliding photons) is defined as a piecewise constant function and optimized whose values are optimized in every interval to minimize transit time and Area. Using the developed model to optimize the trajectory to be followed for sending from Earth to Mars a 2000kg-spacecraft propelled by a Solar Sail, subject to the condition that at trajectory start Mars and Earth were at their closest approach, and the Arrival Relative Velocity is less than 9km/s, give us a minimal transit time of 500days and a minimal area for the Solar Sail of 183158m2, meaning that the maximal payload would be 718kg. Compared with different number of partitions of α, the optimum stays stable. This gives a solid optimal trajectory and a great result for the numerical method used. Actually, waiting until the best moment to throw the Spacecraft, id est, Mars is at 1.14 radians respectively to Earth initial position, the minimal sail area 145950 m2 and, therefore, ables to transport until 978 kg of payload with the same transit time. In addition and to conclude we tried the model to optimize the inverse trajectory.