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Determining the price of a rail ticket from data of Spanish railways
Investigación Aplicada a la Ingenieria
informe de practica pendulo fisico
En este informe se presenta detalladamente el desarrollo de la primera practica de laboratorio, en la cual encontramos la ley de ohm y sus aplicaciones en los circuitos en paralelo y en serie, teniendo en cuenta las normas de laboratorio para así lograr la correcta finalización de dicha guía.
DSA Project Report
Mobile ad-hoc network (MANET) is a collection of mobile terminals forming an infrastructure less and quick deployable network, which can communicate to each other via multiple hops or single hop. Such ad-hoc networks have always been important for various applications like defence applications especially for countries like India having boundaries and regions with large geographical diversity. Mobility attribute is a notable one in MANETs, as this leads to frequent topology changes which are the primary cause of route failure. A route is an ordered set of links, hence for predicting future availability of any particular route, it is important to estimate the availability of its currently available constituent links. This paper explores various link availability prediction model and proposes a least square polynomial regression-based statistical approach to predict the availability of link. Proposed approach assumes that movement of nodes are based on column mobility model i.e each node in the network is linearly moving with constant speed. Each node in the network periodically broadcasts hello packets to its neighbours to inform it’s availability in the network. Neighbour node receives hello packet and uses its signal strength to estimate distance between sender and receiver of hello packet. A monotonically decreasing signal strength of hello packets at receiver node indicates that nodes are moving away from each other and link between them may break in future so it starts link residual time prediction algorithm to predict the time when the distance between them will exceed the pre-defined threshold value. The proposed algorithm is simulated using NS 2.35. The performance of the algorithm has been analyzed for identified parameters. The results are also been compared by simulating other existing link prediction approaches based on interpolation.
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.
Projeto lab CE2
With the detectors currently off, LIGO has detected and gathered an abundance of data from the second observing run (O2). Some of which, captures the most recent triggers that are potential candidates for future gravitational waves, are analyzed more thoroughly. My responsibility as a student researcher is to perform independent checks on four of the most recent Compact Binary Coalescence (CBC) triggers. In order to do so, I compare the \(h(t)\) Omega scans of these events to the Gravity Spy classes. Omega scans are a detector characterization tool to help measure the Signal-to-Noise-Ratio (SNR) of transient noises during detections. This helps scientists distinguish the difference between a gravitational wave signal, which looks like a `chirp' versus a glitch in the data. Gravity Spy is a citizen science program that helps LIGO in classifying glitches to improve machine learning for gravitational wave signals. For each event I determine if it looks like one of the known categories of solved or unsolved glitches seen in the Advanced LIGO detectors? My results are then recorded in the O2 event detection checklist. Omega scans are a `burst-type' search pipeline that detect glitches efficiently. The Omega scan is labeled using time measured in seconds on the x-axis, frequency measured in Hz on the y-axis and the signal measured is normalized to demonstrate how `loud' the noise is.