An Agent-based Classification Model

The major function of this model is to access the UCI Wisconsin Breast Cancer data-set[1] and classify the data items into two categories, which are normal and anomalous. This kind of classification can be referred as anomaly detection, which discriminates anomalous behaviour from normal behaviour in computer systems. One popular solution for anomaly detection is Artificial Immune Systems (AIS). AIS are adaptive systems inspired by theoretical immunology and observed immune functions, principles and models which are applied to problem solving. The Dendritic Cell Algorithm (DCA)[2] is an AIS algorithm that is developed specifically for anomaly detection. It has been successfully applied to intrusion detection in computer security. It is believed that agent-based modelling is an ideal approach for implementing AIS, as intelligent agents could be the perfect representations of immune entities in AIS. This model evaluates the feasibility of re-implementing the DCA in an agent-based simulation environment called AnyLogic, where the immune entities in the DCA are represented by intelligent agents. If this model can be successfully implemented, it makes it possible to implement more complicated and adaptive AIS models in the agent-based simulation environment.

Uma API criptográfica para aplicações embarcadas

This document presents GEmSysC, an unified cryptographic API for embedded systems. Software layers implementing this API can be built over existing libraries, allowing embedded software to access cryptographic functions in a consistent way that does not depend on the underlying library. The API complies to good practices for API design and good practices for embedded software development and took its inspiration from other cryptographic libraries and standards. The main inspiration for creating GEmSysC was the CMSIS-RTOS standard, which defines an unified API for embedded software in an implementation-independent way, but targets operating systems instead of cryptographic functions. GEmSysC is made of a generic core and attachable modules, one for each cryptographic algorithm. This document contains the specification of the core of GEmSysC and three of its modules: AES, RSA and SHA-256. GEmSysC was built targeting embedded systems, but this does not restrict its use only in such systems – after all, embedded systems are just very limited computing devices. As a proof of concept, two implementations of GEmSysC were made. One of them was built over wolfSSL, which is an open source library for embedded systems. The other was built over OpenSSL, which is open source and a de facto standard. Unlike wolfSSL, OpenSSL does not specifically target embedded systems. The implementation built over wolfSSL was evaluated in a Cortex- M3 processor with no operating system while the implementation built over OpenSSL was evaluated on a personal computer with Windows 10 operating system. This document displays test results showing GEmSysC to be simpler than other libraries in some aspects. These results have shown that both implementations incur in little overhead in computation time compared to the cryptographic libraries themselves. The overhead of the implementation has been measured for each cryptographic algorithm and is between around 0% and 0.17% for the implementation over wolfSSL and between 0.03% and 1.40% for the one over OpenSSL. This document also presents the memory costs for each implementation.

Analizar y comparar el lenguaje de alto nivel SystemC frente a los de HDL. aplicación al diseño de sistemas de computo

La complejidad de los sistemas actuales de computación ha obligado a los diseñadores de herramientas CAD/CAE a acondicionar lenguajes de alto nivel, tipo C++, para la descripción y automatización de estructuras algorítmicas a sus correspondientes diseños a nivel físico. Los proyectos a realizar se encuadran dentro de una línea de trabajo consistente en estudiar la programación, funcionamiento de los lenguajes SystemC y SystemVerilog, sus herramientas asociadas y analizar cómo se adecuan a las restricciones temporales y físicas de los componentes (librerías, IP's, macro-celdas, etc) para su directa implementación. En una primera fase, y para este TFG, se estudiarán los componentes que conforman el framework elegido que es SystemC y su inclusión en herramientas de diseño arquitectural. Este conocimiento nos ayudará a entender el funcionamiento y capacidad de dicha herramienta y proceder a su correcto manejo. Analizaremos y estudiaremos unos de los lenguajes de alto nivel de los que hace uso dicha herramienta. Una vez entendido el contexto de aplicación, sus restricciones y sus elementos, diseñaremos una estructura hardware. Una vez que se tenga el diseño, se procederá a su implementación haciendo uso, si es necesario, de simuladores. El proyecto finalizará con una definición de un conjunto de pruebas con el fin de verificar y validar la usabilidad y viabilidad de nuestra estructura hardware propuesta.

A framework for abstraction and virtualization of sensors in mobile context-aware computing

110 p.

User Interface Abstraction for enabling TV set based Inclusive Access to the Information Society

199 p.

A Visual Analytics Approach to Comparing Cohorts of Event Sequences

Sequences of timestamped events are currently being generated across nearly every domain of data analytics, from e-commerce web logging to electronic health records used by doctors and medical researchers. Every day, this data type is reviewed by humans who apply statistical tests, hoping to learn everything they can about how these processes work, why they break, and how they can be improved upon. To further uncover how these processes work the way they do, researchers often compare two groups, or cohorts, of event sequences to find the differences and similarities between outcomes and processes. With temporal event sequence data, this task is complex because of the variety of ways single events and sequences of events can differ between the two cohorts of records: the structure of the event sequences (e.g., event order, co-occurring events, or frequencies of events), the attributes about the events and records (e.g., gender of a patient), or metrics about the timestamps themselves (e.g., duration of an event). Running statistical tests to cover all these cases and determining which results are significant becomes cumbersome. Current visual analytics tools for comparing groups of event sequences emphasize a purely statistical or purely visual approach for comparison. Visual analytics tools leverage humans' ability to easily see patterns and anomalies that they were not expecting, but is limited by uncertainty in findings. Statistical tools emphasize finding significant differences in the data, but often requires researchers have a concrete question and doesn't facilitate more general exploration of the data. Combining visual analytics tools with statistical methods leverages the benefits of both approaches for quicker and easier insight discovery. Integrating statistics into a visualization tool presents many challenges on the frontend (e.g., displaying the results of many different metrics concisely) and in the backend (e.g., scalability challenges with running various metrics on multi-dimensional data at once). I begin by exploring the problem of comparing cohorts of event sequences and understanding the questions that analysts commonly ask in this task. From there, I demonstrate that combining automated statistics with an interactive user interface amplifies the benefits of both types of tools, thereby enabling analysts to conduct quicker and easier data exploration, hypothesis generation, and insight discovery. The direct contributions of this dissertation are: (1) a taxonomy of metrics for comparing cohorts of temporal event sequences, (2) a statistical framework for exploratory data analysis with a method I refer to as high-volume hypothesis testing (HVHT), (3) a family of visualizations and guidelines for interaction techniques that are useful for understanding and parsing the results, and (4) a user study, five long-term case studies, and five short-term case studies which demonstrate the utility and impact of these methods in various domains: four in the medical domain, one in web log analysis, two in education, and one each in social networks, sports analytics, and security. My dissertation contributes an understanding of how cohorts of temporal event sequences are commonly compared and the difficulties associated with applying and parsing the results of these metrics. It also contributes a set of visualizations, algorithms, and design guidelines for balancing automated statistics with user-driven analysis to guide users to significant, distinguishing features between cohorts. This work opens avenues for future research in comparing two or more groups of temporal event sequences, opening traditional machine learning and data mining techniques to user interaction, and extending the principles found in this dissertation to data types beyond temporal event sequences.

Interfaces for Intelligent Environments

Presentaciones de la asignatura Interfaces para Entornos Inteligentes del Máster en Tecnologías de la Informática/Machine Learning and Data Mining.

Algorithmique et complexité des systèmes à compteurs

Réalisé en cotutelle avec l'École normale supérieure de Cachan – Université Paris-Saclay

Del videojuego a la realidad : sistema interactivo para la seguridad vial

El vertiginoso crecimiento de los centros urbanos, las tecnologías emergentes y la demanda de nuevos servicios por parte de la población plantea encaminar esfuerzos hacia el desarrollo de las ciudades inteligentes. Éste concepto ha tomado fuerza entre los sectores político, económico, social, académico, ambiental y civil; de forma paralela, se han generado iniciativas que conducen hacia la integración de la infraestructura, la tecnología y los servicios para los ciudadanos. En éste contexto, una de las problemáticas con mayor impacto en la sociedad es la seguridad vial. Es necesario contar con mecanismos que disminuyan la accidentalidad, mejoren la atención a incidentes, optimicen la movilidad urbana y planeación municipal, ayuden a reducir el consumo de combustible y la emisión de gases de efecto de invernadero, así como ofrecer información dinámica y efectiva a los viajeros. En este artículo se describen dos (2) enfoques que contribuyen de manera eficiente dicho problema: los videojuegos como juegos serios y los sistemas de transporte inteligente. Ambos enfoques están encaminados a evitar colisiones y su diseño e implementación requieren componentes altamente tecnológicos (e.g. sistemas telemáticos e informáticos, inteligencia artificial, procesamiento de imágenes y modelado 3D).

Auditoría de sistemas al cumplimiento de los requerimientos 7, 8, 9 de la norma PCIDSS aplicada a Coral Hipermercado, Racar plaza con corte a Junio de 2015

Coral Hipermercado GO es una empresa dedicada a la comercialización de diversos productos de consumo masivo. Debido a la demanda que mantienen y el nivel de transacciones que realizan en ventas diariamente,

Falcon herramientas de software para el procesamiento aerofotogramétrico

En el área de Aerofotogrametría Digital, el software comercial prevalente para postproceso presenta limitaciones debido a dos factores: (i) las legislaciones de cada país o región requieren diferentes convenciones, y (ii) las necesidades de las empresas son tan cambiantes que no justifican la compra de software de alto rendimiento, que puede quedar sin utilizar debido a un viraje del mercado -- El presente proyecto se ha desarrollado para atender necesidades de procesamiento automático de planos (partición, detección y corrección de errores, etc.), así como módulos de importación – exportación paquete a paquete, trazado de rutas e interacción con GPS -- Este artículo informa de los dos últimos aspectos -- Debido a necesidades de los clientes, los archivos entregados deben llevar un formato comercial (DWG, DXF), pero el procesamiento de los archivos debe ser hecho en paquetes y formatos diversos (DGN) -- Por lo tanto, fue necesario diseñar e implementar un formato acompañante que permitió llevar la información que se pierde al usar filtros comerciales (DGN a DXF/DWG) -- Asimismo se crearon módulos de importación y exportación redundantes, que hicieron efectivos dichos atributos -- En el aspecto de generación de rutas de vuelo, se reportan en este artículo la aplicación de algoritmos tradicionales de barrido (peinado) de áreas 2D, a los cuales se agregaron restricciones geométricas (puntos fijos, offsets, orden de los barridos de acuerdo a coordenadas del sitio de partida, etc.) -- Debido a los altos costos de equipos equivalentes, se decidió desarrollar software para traducción de rutas entre formatos GPS y formatos geográficos locales al país -- Ello permite la eliminación de fuentes de error y además facilita la carga del plan de vuelo, a costos mucho menores a los del hardware / software comercial

Semantics, knowledge and grids on big data

Semantics, knowledge and Grids represent three spaces where people interact, understand, learn and create. Grids represent the advanced cyber-infrastructures and evolution. Big data influence the evolution of semantics, knowledge and Grids. Exploring semantics, knowledge and Grids on big data helps accelerate the shift of scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies.

Impact of single parameter changes on Ceph cloud storage performance

In a general purpose cloud system efficiencies are yet to be had from supporting diverse applications and their requirements within a storage system used for a private cloud. Supporting such diverse requirements poses a significant challenge in a storage system that supports fine grained configuration on a variety of parameters. This paper uses the Ceph distributed file system, and in particular its global parameters, to show how a single changed parameter can effect the performance for a range of access patterns when tested with an OpenStack cloud system.

Improving user-insurance communication on accident reports

This paper presents an easy to use methodology and system for insurance companies targeting at managing traffic accidents reports process. The main objective is to facilitate and accelerate the process of creating and finalizing the necessary accident reports in cases without mortal victims involved. The diverse entities participating in the process from the moment an accident occurs until the related final actions needed are included. Nowadays, this market is limited to the consulting platforms offered by the insurance companies. Copyright 2014 ACM.

Criação de uma ontologia e respectiva povoação a partir do processamento de relatórios médicos

A evolução tecnológica tem provocado uma evolução na medicina, através de sistemas computacionais voltados para o armazenamento, captura e disponibilização de informações médicas. Os relatórios médicos são, na maior parte das vezes, guardados num texto livre não estruturado e escritos com vocabulário proprietário, podendo ocasionar falhas de interpretação. Através das linguagens da Web Semântica, é possível utilizar antologias como modo de estruturar e padronizar a informação dos relatórios médicos, adicionando¬ lhe anotações semânticas. A informação contida nos relatórios pode desta forma ser publicada na Web, permitindo às máquinas o processamento automático da informação. No entanto, o processo de criação de antologias é bastante complexo, pois existe o problema de criar uma ontologia que não cubra todo o domínio pretendido. Este trabalho incide na criação de uma ontologia e respectiva povoação, através de técnicas de PLN e Aprendizagem Automática que permitem extrair a informação dos relatórios médicos. Foi desenvolvida uma aplicação, que permite ao utilizador converter relatórios do formato digital para o formato OWL. ABSTRACT: Technological evolution has caused a medicine evolution through computer systems which allow storage, gathering and availability of medical information. Medical reports are, most of the times, stored in a non-structured free text and written in a personal way so that misunderstandings may occur. Through Semantic Web languages, it’s possible to use ontology as a way to structure and standardize medical reports information by adding semantic notes. The information in those reports can, by these means, be displayed on the web, allowing machines automatic information processing. However, the process of creating ontology is very complex, as there is a risk creating of an ontology that not covering the whole desired domain. This work is about creation of an ontology and its population through NLP and Machine Learning techniques to extract information from medical reports. An application was developed which allows the user to convert reports from digital for¬ mat to OWL format.