EVALUACIÓN DE FIREWALLS BASADOS EN SOFTWARE LIBRE (FIREWALL EVALUATION BASED ON OPEN SOURCE SOFTWARE)

En este trabajo se propone la evaluación de firewalls basado en software libre GNU/LINUX con las características que les permitan integrarse a una cama de pruebas en la cual se estudiaron, evaluaron y analizaron diversos entornos de red y escenarios de ataque. Los firewalls de software libre son una buena alternativa cuando se trata de brindar seguridad en una red, en este trabajo fueron evaluados cuatro distribuciones Linux que han sido especialmente diseñadas para brindar este servicio. Las herramientas de software libre empleadas demostraron ser las adecuadas para las pruebas realizadas a los diferentes firewalls, de este modo se logró obtener resultados que muestran la factibilidad de ClearOS para ser implementado en la cama de pruebas. También se probó su efectividad al mostrar una buena respuesta en la defensa de los ataques, con y sin la inyección del tráfico de fondo generado por la herramienta iperf.In this work we propose the evaluation of firewalls based on free software GNU / LINUX with the characteristics that allow them to be integrated into a test bed in which various network environments and attack scenarios were studied, evaluated and analyzed. Free software firewalls are a good alternative when it comes to providing security in a network, in this work were evaluated four Linux distributions that have been specially designed to provide this service. The free software tools used, proved to be adequate for the tests carried out on the different firewalls, in this way it was possible to obtain results that show the feasibility of ClearOS to be implemented in the test bed. Its effectiveness was also proven by showing a good response in the defense of attacks, with and without the injection of background traffic generated by the iperf tool

A systematic review of non-antibiotic measures for the prevention of urinary tract infections in pregnancy

Background: Urinary tract infections (UTIs) are common in pregnancy and account for the highest proportion of primary care antibiotic prescriptions issued to pregnant women in the UK. It is well known that antibiotic use is associated with increased antimicrobial resistance and therefore measures to minimise antibiotic use for UTI prevention have been studied. The efficacy and safety of these measures in pregnancy have not been addressed and therefore the aim of this study was to systematically review the literature to identify and evaluate potential measures to prevent UTIs in pregnant women. Methods: Ten databases (EMBASE, AMED, BNI, CINAHL, Medline, PubMed, PsycINFO, Cochrane Trials, Scopus and Science Direct) were systematically searched in July 2017 for studies reporting non-antibiotic measures to prevent UTIs in pregnancy. The terms (“urinary tract infection”or UTI or bacteriuria or cystitis) AND (prevention) AND (pregnan*) were used. The quality of the publications was appraised using the Critical Appraisal Skills Programme (CASP) checklists for cohort study, case-control study and randomised controlled trial. The results were synthesised using a textual narrative approach. Results: Search results yielded 3276 publications and after reviewing titles and removing duplicates, 57 full text articles were assessed for eligibility and eight were included in the review. Five different approaches (hygiene measures, cranberry juice, immunisation, ascorbic acid and Canephron® N) have been identified, all of which are reported to be safe in pregnancy. Conclusion: The quality of the evidence varied considerably and only hygiene measures were supported by evidence to be recommended in practice. Future work needs to concentrate on strengthening the evidence base through improved design and reporting of studies with a focus on immunisation, ascorbic acid and Canephron® N

PROCESAMIENTO DE SEÑALES CON FPGA’S

Facultad de Ingeniería Mecánica y Eléctric

Utilización de 100 mg diarios de vitamina C como medida preventiva de infecciones de vías urinarias en el embarazo

Facultad de Medicin

Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks

This paper describes the complete integration of a fuzzy control of multiple evaporator systems with the IEEE 802.15.4 standard, in which we study several important aspects for this kind of system, like a detailed analysis of the end-to-end real-time flows over wireless sensor and actuator networks (WSAN), a real-time kernel with an earliest deadline first (EDF) scheduler, periodic and aperiodic tasking models for the nodes, lightweight and flexible compensation-based control algorithms for WSAN that exhibit packet dropouts, an event-triggered sampling scheme and design methodologies. We address the control problem of the multi-evaporators with the presence of uncertainties, which was tackled through a wireless fuzzy control approach, showing the advantages of this concept where it can easily perform the optimization for a set of multiple evaporators controlled by the same smart controller, which should have an intelligent and flexible architecture based on multi-agent systems (MAS) that allows one to add or remove new evaporators online, without the need for reconfiguring, while maintaining temporal and functional restrictions in the system. We show clearly how we can get a greater scalability, the self-configuration of the network and the least overhead with a non-beacon or unslotted mode of the IEEE 802.15.4 protocol, as well as wireless communications and distributed architectures, which could be extremely helpful in the development process of networked control systems in large spatially-distributed plants, which involve many sensors and actuators. For this purpose, a fuzzy scheme is used to control a set of parallel evaporator air-conditioning systems, with temperature and relative humidity control as a multi-input and multi-output closed loop system; in addition, a general architecture is presented, which implements multiple control loops closed over a communication network, integrating the analysis and validation method for multi-loop control networks designed for multi-evaporator systems

Distributed multi-agent architecture for real-time wireless control networks of multiple plants

This paper describes an interesting model architecture based on the tree topology, as well as its analysisthrough an associated validation method for control networks designed for low-rate wireless sensor andactuator networks (WSAN), consisting of multiple control loops closed over a wireless communicationnetwork, taking advantage of theflexible communications features of IEEE 802.15.4 protocol. The mainproblem to be addressed is the control of multiple or parallel plants, which should have an intelligent andflexible architecture based on multi-agent systems (MAS), that allows to add or remove new plants or nodesonline, without the need of reconfiguring the system, while maintaining temporal and functional restrictionsin the system. Important issues to consider in the research are tackled herein like topology, optimal staticrouting, end-to-end test analysis of the real-timeflows on the WSAN, real-time kernel with Earliest DeadlineFirst (EDF) scheduler, periodic and aperiodictasking models for the nodes, lightweight andflexible com-pensation-based control algorithms for WSAN that exhibit packet dropouts, and an event-triggered samplingscheme. Additionally, as example of an application in a simulation environment is presented, in which isintended to guarantee an optimal parallel fed-batch bioreactor operations model controlled over a WSAN,using a master–slave synchronization system as control strategy, obtaining an accurate end-to-end com-munication analysis of the proposed plant with Wireless Sensor and Actuator Network

Segmentation of the ECG Signal by Means of a Linear Regression Algorithm

The monitoring and processing of electrocardiogram (ECG) beats have been actively studied in recent years: new lines of research have even been developed to analyze ECG signals using mobile devices. Considering these trends, we proposed a simple and low computing cost algorithm to process and analyze an ECG signal. Our approach is based on the use of linear regression to segment the signal, with the goal of detecting the R point of the ECG wave and later, to separate the signal in periods for detecting P, Q, S, and T peaks. After pre-processing of ECG signal to reduce the noise, the algorithm was able to efficiently detect fiducial points, information that is transcendental for diagnosis of heart conditions using machine learning classifiers. When tested on 260 ECG records, the detection approach performed with a Sensitivity of 97.5% for Q-point and 100% for the rest of ECG peaks. Finally, we validated the robustness of our algorithm by developing an ECG sensor to register and transmit the acquired signals to a mobile device in real time