Gallery — Two-column

PROYECTO AMAZON

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.

This paper presents a new entropy minimization criterion and corresponding algorithms that are used for both symbol timing and carrier frequency recovery for underwater acoustic receivers. It relies on the entropy estimation of the eye diagram and the constellation diagram of the received signal. During the parameter search, when perfect synchronization is achieved, the entropy will reach a global minimum, indicating the least intersymbol interference or a restored constellation diagram. Unlike other synchronization methods, this unified criterion can be used to build an all-in-one synchronizer with high accuracy. The feasibility of this method is proven using a theoretical analysis and supported by sea trial measurement data.

Gliding is an efficient and versatile way to traverse large distances whilst expending as little energy as possible. Work done in the field of biomimetic robotics has demonstrated further benefits to gliding in increasing trajectory control and reducing landing impact loads. A small-scale micro-glider was built to fit a specific design envelope with the objective of maximizing its glide range. A linear dynamics model was used to design and predict the gliding performance of the robot. Once manufactured, it achieved a glide distance of 1.8m and the performance was accurately captured by the dynamics model.

Accurate prognosis and prediction of a patient's current disease state is critical in an ICU. The use of vast amounts of digital medical information can help in predicting the best course of action for the diagnosis and treatment of patients. The proposed technique investigates the strength of using a combination of latent variable models (latent dirichlet allocation) and structured data to transform the information streams into potentially actionable knowledge. In this project, I use Apache Spark to predict mortality among ICU patients so that it can be used as an acuity surrogate to help physicians identify the patients in need of immediate care.

For an electron moving in a circular path in a magnetic field, if we know the magnetic field strength, accelerating voltage, and radius of the electron's trajectory, then we can make an estimation of the electron's charge to mass ratio. We calculated an average charge to mass ratio of \(2.08 \times 10^{11} \pm 1.81 \times 10^8\) Coulombs per kilogram.

En este documento se encuentra el desarrollo del primer laboratorio de la asignatura Vídeo Digital y Procesamiento de Imágenes el cual trata sobre el análisis de los sensores fotográficos y los metadatos de las imágenes tomadas, Ademas de la creación de algunos scripts en el programa Matlab para lo que se tiene que tener en cuenta la información de geolocalización o GPS de las imágenes. Keywords — GPS, Matlab, Metadatos

Recent work on information extraction has suggested that fast, interactive tools can be highly effective; however, creating a usable system is challenging, and few publically available tools exist. In this paper we present IKE, a new extraction tool that performs fast, interactive bootstrapping to develop high-quality extraction patterns for targeted relations, and provides novel solutions to these usability concerns. In particular, it uses a novel query language that is expressive, easy to understand, and fast to execute - essential requirements for a practical system - and is the first interactive extraction tool to seamlessly integrate symbolic and distributional methods for search. An initial evaluation suggests that relation tables can be populated substantially faster than by manual pattern authoring or using fully automated tools, while retaining accuracy, an important step towards practical knowledge-base construction.

Precision viticulture is a specialization of precision agriculture techniques applied to viticulture. Precision agriculture is the use of information system technologies applied to agricultural production. Some of the applicable technologies are; Wireless Sensor Networks (WSN), Global Positioning Systems (GPS), spectroscopy analysis of Near-Infrared (NIR), Geographic Information Systems (GIS). These systems provide means of observation, evaluation and control of agricultural activities. The farmers demand assistant systems to perform actions for saving time and avoiding risks. There are studies of maps crops and mesh-sampling techniques to predict the harvest volume in a vineyard with a certain varieties of grapes. The prediction is based on a previous study of crops over a period of three to four years. Along these three or four years a large volume of samples is taken to study several parameters. In this application area is where the wireless sensor networks technologies would have high incidence. In this context we intend to analyse, at first place, the specific characteristics of the operational environment of a vineyard. Second, we will analyse the most appropriate architecture for a sensor network in this environment. Application of wireless sensor networks technology can take many forms depending of environment, and implementation objectives. In this paper we discuss about the best procedure for deployment and the optimal topology of a wireless sensor network for viticulture.