Security Analysis of Separation Kernels Specifications and a Framework for the Verification of Concurrent Implementations

Due to the new trend of integrating safe and secure functionalities into one separation kernel, security analysis of ARINC 653 as well as a formal specification with security proofs are thus significant for the development and certification of Separation Kernels (SKs). In this talk we present a specification development and security analysis method for ARINC SKs based on refinement. We present a security model for event-based non-Interference and a stepwise refinement framework that will allow us to check security on sequential SKs specifications. Moreover to be able to reason on SKs implementations running on top of multi-core architectures it is essential to deal with the interference of the environment between SKs instances running on different cores. Concurrent program reasoning techniques such as rely-guarantee can be leveraged to reason on multi-core SKs implementations. However the source code of the programs to be verified often involves language features such as exceptions and procedures which are not supported by the existing mechanizations of those concurrent reasoning techniques. CSimpl, is a rich specification language with concurrency-oriented language features and verification techniques that will allow reasoning on multi-core SKs implementations.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A new self-organizing neural gas model based on Bregman divergences

In this paper, a new self-organizing neural gas model that we call Growing Hierarchical Bregman Neural Gas (GHBNG) has been proposed. Our proposal is based on the Growing Hierarchical Neural Gas (GHNG) in which Bregman divergences are incorporated in order to compute the winning neuron. This model has been applied to anomaly detection in video sequences together with a Faster R-CNN as an object detector module. Experimental results not only confirm the effectiveness of the GHBNG for the detection of anomalous object in video sequences but also its selforganization capabilities.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Vehicle Type Detection by Convolutional Neural Networks

In this work a new vehicle type detection procedure for traffic surveillance videos is proposed. A Convolutional Neural Network is integrated into a vehicle tracking system in order to accomplish this task. Solutions for vehicle overlapping, differing vehicle sizes and poor spatial resolution are presented. The system is tested on well known benchmarks, and multiclass recognition performance results are reported. Our proposal is shown to attain good results over a wide range of difficult situations.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments

Among current foreground detection algorithms for video sequences, methods based on self-organizing maps are obtaining a greater relevance. In this work we propose a probabilistic self-organising map based model, which uses a uniform distribution to represent the foreground. A suitable set of characteristic pixel features is chosen to train the probabilistic model. Our approach has been compared to some competing methods on a test set of benchmark videos, with favorable results.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Excellence and Quality in Andalusia University Library System

From 1996 onwards, then, the Quality Assessment National Plan and the adoption of its agenda by regional authorities and Universities alike has resulted in a growing acceptance by the Spanish academic community of the challenges and opportunities offered by evaluation and quality assurance activities. Academic librarians have been committed to this culture of quality from the very beginnings and in most cases have being leading the way in their own institutions. General tools like the Evaluation Guide referred to above developed to be applied in administration and services alike were of little use for libraries, so academic libraries have been the first units to develop their own evaluation guides at local and regional levels. University System in Andalusia (Spain) is formed by 10 Universities financed by regional government. The Quality Unit of Andalusia Universities convened in 2000 an Assessment University Libraries Pilot Plan to do a global analysis of the Library System. This Pilot Plan has had three steps: - During 2000-2002, a technical committee to draft a new evaluation guide for academic libraries. Based on the EFQM, because of its growing influence in the evaluation of the public sector and not-for-profit organizations across Europe. During the course of our work we were delighted to see that we concurred basically with the approach taken by LISIM. The Guide is divided into 5 parts, as follows: Analysis and Description of 9 criteria adapted to library scenario, 35 Tables for data collection, a set of 30 quality and performance Indicators, a Excellence-rating matrix, an objective tool, to determine the level of excellence achieved by the library on a scale from 0 to 10, and General guidelines for the Assessment Committees of University Departments (the basic unit of research assessment undertaken by the University) and of degree courses (the basic unit of assessment of teaching personnel). - In 2002-2004, a coordination committee drove the assessment process of 9 libraries and tested materials and evaluation methodology. The Pilot Plan has finalised with External Evaluation for 5 External Committee formed by librarians, faculties and EFQM methodology specialist. The aim of this paper is explain different parts and strong points of this process and how EFQM is suitable for all kind of librarie

Análisis de filtración en presas con cimientos yesíferos

El emplazamiento de presas en España es cada vez más restringido y las características geológicas y geotécnicas del cimiento no siempre tan favorables como se desearía. En el caso de cimientos yesíferos, es necesario proyectar una sección tipo de presa que limite, dentro de valores aceptables, el proceso de disolución del cimiento. El objetivo es modelizar el proceso de disolución del cimiento debido a la filtración, determinando el correspondiente cambio de permeabilidad de éste y el consiguiente aumento de los caudales de filtración. Para ello se ha desarrollado un programa en Visual Basic (denominado DISOLUCION2D) que realiza un cálculo iterativo en el tiempo, a partir de los resultados del programa comercial SEEP2D, de cálculo de redes de filtración mediante elementos finitos. Se han realizado ensayos, para comprobar la validez de las formulaciones. Se han calculado modelos presa-cimiento con distintos diseños de presa y características del cimiento (porcentaje de material soluble, profundidad y espesor de la capa yesífera, permeabilidades iniciales, ...) para concluir qué factores son determinantes

Road pollution estimation using static cameras and neural networks

Este artículo presenta una metodología para estimar la contaminación en carreteras mediante el análisis de secuencias de video de tráfico. El objetivo es aprovechar la gran red de cámaras IP existente en el sistema de carreteras de cualquier estado o país para estimar la contaminación en cada área. Esta propuesta utiliza redes neuronales de aprendizaje profundo para la detección de objetos, y un modelo de estimación de contaminación basado en la frecuencia de vehículos y su velocidad. Los experimentos muestran prometedores resultados que sugieren que el sistema se puede usar en solitario o combinado con los sistemas existentes para medir la contaminación en carreteras.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Blood Cell Classification Using the Hough Transform and Convolutional Neural Networks

https://doi.org/10.1007/978-3-319-77712-2_62The detection of red blood cells in blood samples can be crucial for the disease detection in its early stages. The use of image processing techniques can accelerate and improve the effectiveness and efficiency of this detection. In this work, the use of the Circle Hough transform for cell detection and artificial neural networks for their identification as a red blood cell is proposed. Specifically, the application of neural networks (MLP) as a standard classification technique with (MLP) is compared with new proposals related to deep learning such as convolutional neural networks (CNNs). The different experiments carried out reveal the high classification ratio and show promising results after the application of the CNNs.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech