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In this document we focus on modifying the Linux Kernel through memory and scheduler parameters. The main objective is to study the performance of a computer during the execution of AIO-Stress Benchmark. It was necessary to run the test several times since three of the parameter mentioned in this project were modified 5 times. After completing the test, the results were displayed on graphs, showing that all the variables have a noticeable influence on the performance of the computer.

Let's take a look into the dynamic history of the Noscuk valley and its people.

Las bases de datos relacionales han sido las herramientas por excelencia para el almacenamiento de la información en los sistemas informáticos. No obstante, las bases de datos NoSQL, como tendencia, han venido ganando espacio especialmente por la escalabilidad y velocidad en sus tiempos de respuestas. PostgreSQL ha incorporado algunas características de tipo NoSQL, como el almacenamiento efímero y el manejo de datos JSON; características que pueden aprovecharse para realizar acciones desde el gestor dándole mayor potencia. El objetivo de este artículo es evaluar, mediante toda la documentación encontrada, el comportamiento de las características NoSQL de PostgreSQL frente a un gestor NoSQL, comparandola con MongoDB, respecto a los tiempos de respuestas y dar a conocer las ventajas de uno con respecto al otro. Palabras Claves: Características NoSQL en PostgreSQL, MongoDB, PostgreSQL

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.

We explore ways of allowing for the offloading of computationally rigorous tasks from devices with slow logical processors onto a network of anonymous peer-processors. Recent advances in secret sharing schemes, decentralized consensus mechanisms, and multiparty computation (MPC) protocols are combined to create a P2P MPC market. Unlike other computational "clouds", ours is able to generically compute any arithmetic circuit, providing a viable platform for processing on the semantic web. Finally, we show that such a system works in a hostile environment, that it scales well, and that it adapts very easily to any future advances in the complexity theoretic cryptography used. Specifically, we show that the feasibility of our system can only improve, and is historically guaranteed to do so.

En los últimos años se ha visto un auge en el uso de los sistemas de bases de datos NoSQL y junto a ello se ha popularizado la idea de aplicaciones de Persistencia Políglota. Esta consiste en que gracias a la gran variedad y cantidad de datos, y los diversos servicios que pueden dar las aplicaciones hoy en día, es probable que un único tipo de sistema de almacenamiento no sea capaz de cubrir de forma eficiente todas las necesidades de la aplicación. En este articulo se dará una idea general de las Aplicaciones de Persistencia Políglota dando información acerca de su funcionamiento, arquitectura y motivación; y ademas se hablara específicamente de como aplicar la Persistencia Políglota con MongoDB y Neo4j. Palabras Clave: NoSQL, Persistencia Políglota, MongoDB, Neo4j, Neo4j Doc Manager

Deep learning is a fast growing field in tech that is often described to have limitless potential. This paper describes its history, why the explosion in popularity, and how it works. An example of classifying images of handwritten digits (MNIST) will be explored using a fully connected network and a convolutional neural network. Next, a brief description of the tools necessary for the reader to implement his or her own network. Finally, a view of the state of the art being developed by companies such as Google, Facebook, and Baidu.

Manufacturing industries are changing rapidly towards more flexibility and autonomy. The RoboCup Logistics League (RCLL) and RoboCup@Work tackle research questions in this domain focusing on automated reasoning and planning, and mobile manipulation respectively. However, future scenarios will require both aspects (and more) and will most likely operate with more heterogeneous systems. In this paper, we propose a cross-over challenge to foster closer cooperation among the two leagues to address these challenges. We outline four integration milestones and propose a specific scenario and task for the first milestone. The effort is driven by stakeholders of both leagues.