Articles — Project / Lab Report

Relatório lab 7,8,9

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.

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En la actualidad, el estudio y análisis de los sistemas de control automático representan un campo de aplicación bastante extendido, esto debido a las imperantes necesidades por mejorar los procesos productivos, optimizar los recursos e incluso para predecir comportamientos, desde entornos educativos, investigativos o industriales, hasta entornos económicos, sociales y demás. En efecto, esto ha impulsado a los desarrolladores a buscar herramientas o alternativas que permitan aumentar las capacidades de cómputo al momento de desarrollar un sistema de control automático. Ahora bien, la instrumentación industrial desde hace muchos años viene comandada por los Autómatas Programables (PLC), dispositivos útiles e ideales para ejecutar las tareas de control de una planta, independientemente de la escala. El presente documento presenta el diseño e implementación de un controlador PID en una planta didáctica conformada con equipos industriales, haciendo uso de OPC y algunos conceptos de la teoría de control. Mediante la herramienta computacional MATLAB se realiza la identificación de la planta obteniendo su función de transferencia, y haciendo uso de algunas herramientas disponibles en este software, se determinan los parámetros de sintonía de un controlador tipo PID, para posteriormente sintonizar la estrategia de control implementada en un autómata programable de gama alta.

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.

After the fixture was sealed within the bell jar, the Margherita 2 underwent bakeout and a test seal on a one-inch tile. Following this small success, a larger project of sealing a larger tile during cesiation launched in the final week of the author's summer in the LAPPD Lab. Central to the ability to control these processes is the ability to monitor temperatures, pressures, and RGA plots as well as adjust heating inputs accurately and timely. This report documents the heating procedures, basic sealing cycle, and plotting past events or in real-time with the Margherita 2 infrastructure.

Trabajo realizado en la catedra fenomenos 3

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.

Thermal wave phenomenon is observed is thin metallic rod by application of periodic heating. In this way, it is demonstrated that there is no wave nature in these improperly called thermal waves by showing that they do not transport energy and its propagation properties can be used to determine the thermal diffusivity of the material.