Rigorous development of safety-critical systems

Nowadays, computer-based systems tend to become more complex and control increasingly critical functions affecting different areas of human activities. Failures of such systems might result in loss of human lives as well as significant damage to the environment. Therefore, their safety needs to be ensured. However, the development of safety-critical systems is not a trivial exercise. Hence, to preclude design faults and guarantee the desired behaviour, different industrial standards prescribe the use of rigorous techniques for development and verification of such systems. The more critical the system is, the more rigorous approach should be undertaken. To ensure safety of a critical computer-based system, satisfaction of the safety requirements imposed on this system should be demonstrated. This task involves a number of activities. In particular, a set of the safety requirements is usually derived by conducting various safety analysis techniques. Strong assurance that the system satisfies the safety requirements can be provided by formal methods, i.e., mathematically-based techniques. At the same time, the evidence that the system under consideration meets the imposed safety requirements might be demonstrated by constructing safety cases. However, the overall safety assurance process of critical computerbased systems remains insufficiently defined due to the following reasons. Firstly, there are semantic differences between safety requirements and formal models. Informally represented safety requirements should be translated into the underlying formal language to enable further veri cation. Secondly, the development of formal models of complex systems can be labour-intensive and time consuming. Thirdly, there are only a few well-defined methods for integration of formal verification results into safety cases. This thesis proposes an integrated approach to the rigorous development and verification of safety-critical systems that (1) facilitates elicitation of safety requirements and their incorporation into formal models, (2) simplifies formal modelling and verification by proposing specification and refinement patterns, and (3) assists in the construction of safety cases from the artefacts generated by formal reasoning. Our chosen formal framework is Event-B. It allows us to tackle the complexity of safety-critical systems as well as to structure safety requirements by applying abstraction and stepwise refinement. The Rodin platform, a tool supporting Event-B, assists in automatic model transformations and proof-based verification of the desired system properties. The proposed approach has been validated by several case studies from different application domains.

Typing of Pseudomonas aeruginosa from hospitalized patients: a comparison of susceptibility and biochemical profiles with genotype

Typing techniques are essential for understanding hospital epidemiology, permitting the elucidation of the source of infection and routes of bacterial transmission. Although DNA-based techniques are the "gold standard" for the epidemiological study of Pseudomonas aeruginosa, antibiotic profiles and biochemical results are used because they are easy to perform and to interpret and relatively inexpensive. Antibiotypes (susceptibility profiles) and biotypes (biochemical profiles) were compared to genotypes established by DNA restriction enzyme analysis in 81 clinical isolates of P. aeruginosa from three hospitals in Porto Alegre, Brazil. The epidemiological relationship among patients was also evaluated. Susceptibility and restriction profiles were discrepant in more than 50% of the cases, and many antibiotypes were observed among isolates from the same genotype. Furthermore, susceptibility profiles did not allow the distinction of isolates from unrelated genotypes. Since a large number of isolates (63%) yielded the same biochemical results, only 10 biotypes were detected, showing that this typing method has a low discriminatory power. On the other hand, DNA restriction enzyme typing allowed us to establish 71 distinct types. Epidemiological data about the relation among P. aeruginosa isolates were not conclusive. The results of the present study indicate that the only method that can establish a clonal relation is DNA restriction enzyme typing, whereas the other methods may cause misleading interpretations and are inadequate to guide proper infection control measures.

Mineraalien rikastusprosessin vesijalanjälki

Mineraalien rikastamiseen käytetään useita fysikaalisia ja kemiallisia menetelmiä. Prosessi sisältää malmin hienonnuksen, rikastuksen ja lopuksi vedenpoistamisen rikastelietteestä. Malmin rikastamiseen käytetään muun muassa vaahdotusta, liuotusta, magneettista rikastusta ja tiheyseroihin perustuvia rikastusmenetelmiä. Rikastuslietteestä voidaan poistaa vettä sakeuttamalla ja suodattamalla. Rikastusprosessin ympäristövaikutuksia voidaan arvioida laskemalla tuotteen vesijalanjälki, joka kertoo valmistamiseen kulutetun veden määrän. Tässä kirjallisuustyössä esiteltiin mineraalien käsittelymenetelmiä sekä prosessijätevesien puhdistusmenetelmiä. Kirjallisuuslähteiden pohjalta selvitettiin Pyhäsalmen kaivoksella valmistetun kuparianodin vesijalanjälki sekä esitettiin menetelmiä, joilla prosessiin tarvittavan raakaveden kulutusta voitaisiin vähentää. Pyhäsalmella kuparirikasteesta valmistetun kuparianodin vesijalanjälki on 240 litraa H2O ekvivalenttia tuotettua tonnia kohden. Pyhäsalmen prosessin raakaveden kulutusta voidaan vähentää lisäämällä sisäistä vedenkierrätystä. Kalsiumsulfaatin saostuminen putkiin ja pumppuihin on ilmentynyt ongelmaksi vedenkierrätyksen lisäämisessä. Kalsiumsulfaattia voidaan erottaa vedestä membraaneihin, ioninvaihtoon ja sähkökemiaan perustuvilla tekniikoilla. Vaihtoehdossa, jossa johdetaan kaikista kolmesta vaahdotuksesta saatavat rikastuslietteen ja rikastushiekan sakeutuksien ylitteet sekä suodatuksien suodosvedet samaan vedenkäsittelyyn voidaan kattaa arviolta noin 65 % koko veden tarpeesta. Raakavettä säästetään vuodessa 3,4 Mm^3 ja samalla rikastushiekka-altaiden tarvittava koko pienenee, joka vähentää ympäristöriskejä.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

L’Assistance Ventriculaire définitive : un groupe de cOdéveloppement profeSsionnel en Soutien aux sOins INfirmierS pour développer des compétences éthiques- Projet A-VOS-SOINS

Rapport de stage présenté à la Faculté des sciences infirmières en vue de l'obtention du grade de Maître ès sciences (M.Sc.) en sciences infirmières option expertise-conseil en soins infirmiers

L'assimilation rock de la musique romantique par le groupe Muse

La version intégrale de ce mémoire est disponible uniquement pour consultation individuelle à la Bibliothèque de musique de l’Université de Montréal (www.bib.umontreal.ca/MU).

Dérivation de diagrammes de séquence UML compactes à partir de traces d’exécution en se basant des heuristiques.

Nous proposons une approche d’extraction des diagrammes de séquence à partir de programmes orientés objets en combinant l’analyse statique et dynamique. Notre objectif est d’extraire des diagrammes compacts mais contenant le plus d’informations possible pour faciliter la compréhension du comportement d’un programme. Pour cette finalité, nous avons défini un ensemble d’heuristiques pour filtrer les événements d’exécution les moins importants et extraire les structures de contrôles comme les boucles et la récursivité. Nous groupons aussi les objets en nous basant sur leurs types respectifs. Pour tenir compte des variations d’un même scénario, notre approche utilise plusieurs traces d’exécution et les aligne pour couvrir le plus possible le comportement du programme. Notre approche a été évaluée sur un système de simulation d’ATM. L’étude de cas montre que notre approche produit des diagrammes de séquence concis et informatifs.

Molecular Approaches For Characterization And Determination Of Pathogenicity Of Vibrios With Special Reference To Vibrio Harveyi From Penaeus Monodon Larval Production Systems

The present study focuses on vibrios especially Vibrio harveyi isolated from shrimp (P. monodon) larval production systems from both east and west coasts during times of mortality. A comprehensive approach has been made to work out their systematics through numerical taxonomy and group them based on RAPD profiling and to segregate the virulent from non- virulent isolates based on the presence of virulent genes as well as their phenotypic expression. The information gathered has helped to develop a simple scheme of identification based on phenotypic characters and segregate the virulent from non virulent strains of V. harveyi.

Interacting software-agents to support a kind of expert supervision systems

Expert supervision systems are software applications specially designed to automate process monitoring. The goal is to reduce the dependency on human operators to assure the correct operation of a process including faulty situations. Construction of this kind of application involves an important task of design and development in order to represent and to manipulate process data and behaviour at different degrees of abstraction for interfacing with data acquisition systems connected to the process. This is an open problem that becomes more complex with the number of variables, parameters and relations to account for the complexity of the process. Multiple specialised modules tuned to solve simpler tasks that operate under a co-ordination provide a solution. A modular architecture based on concepts of software agents, taking advantage of the integration of diverse knowledge-based techniques, is proposed for this purpose. The components (software agents, communication mechanisms and perception/action mechanisms) are based on ICa (Intelligent Control architecture), software middleware supporting the build-up of applications with software agent features

Time misalignments in fault detection and diagnosis

El desalineamiento temporal es la incorrespondencia de dos señales debido a una distorsión en el eje temporal. La Detección y Diagnóstico de Fallas (Fault Detection and Diagnosis-FDD) permite la detección, el diagnóstico y la corrección de fallos en un proceso. La metodología usada en FDD está dividida en dos categorías: técnicas basadas en modelos y no basadas en modelos. Esta tesis doctoral trata sobre el estudio del efecto del desalineamiento temporal en FDD. Nuestra atención se enfoca en el análisis y el diseño de sistemas FDD en caso de problemas de comunicación de datos, como retardos y pérdidas. Se proponen dos técnicas para reducir estos problemas: una basada en programación dinámica y la otra en optimización. Los métodos propuestos han sido validados sobre diferentes sistemas dinámicos: control de posición de un motor de corriente continua, una planta de laboratorio y un problema de sistemas eléctricos conocido como hueco de tensión.

En la prehistòria dels hisendats. De senyors útils a propietaris (vegueria de Girona, 1486-1730)

A la vegueria de Girona, entre 1486 i 1730, es produeix el procés de formació històrica d'un grup social que sorgit de la pagesia s'anirà diferenciant progressivament d'aquesta: els senyors útils i propietaris de masos. Aquest grup social basa el seu poder econòmic i polític en l'acumulació de masos: font de rendes i font de l'estatus social assolit dins la parròquia i la universitat on fixa la seva residència. El seu pes social el manifesta a través dels seus espais de sociabilitat (especialment la parròquia, veritable espai de representació), però també manifesta la seva posició de preeminència, fet que pot abocar als conflictes amb el conjunt de la comunitat. Un conflicte que es planteja en termes de diferenciació dels uns i d'igualtat dels altres. És l'enfrontament entre dues visions de la societat: l'individualisme enfront el comunitarisme.

Imagem por Ressonância Magnética : uma ferramenta poderosa para a Engenharia de Tecidos. Uma revisão atualizada

A Engenharia de Tecidos (ET) é uma área de investigação crescente que se direciona à criação de substitutos biológicos funcionais para vários tecidos do corpo humano. Requer condições específicas favoráveis para a regeneração de tecidos, e o resultado do tecido engenheirado deve ser avaliado objetivamente. A Imagem por Ressonância Magnética (IRM) é uma das técnicas mais promissoras para este efeito. Esta revisão discute as publicações mais recentes acerca das várias técnicas baseadas na IRM disponíveis para a avaliação de tecidos engenheirados e as presentes aplicações da IRM na ET.

Pose and Structure Recovery using Active Models

A new formulation of a pose refinement technique using ``active'' models is described. An error term derived from the detection of image derivatives close to an initial object hypothesis is linearised and solved by least squares. The method is particularly well suited to problems involving external geometrical constraints (such as the ground-plane constraint). We show that the method is able to recover both the pose of a rigid model, and the structure of a deformable model. We report an initial assessment of the performance and cost of pose and structure recovery using the active model in comparison with our previously reported ``passive'' model-based techniques in the context of traffic surveillance. The new method is more stable, and requires fewer iterations, especially when the number of free parameters increases, but shows somewhat poorer convergence.

Review of computer vision in intelligent environment design

This paper discusses and compares the use of vision based and non-vision based technologies in developing intelligent environments. By reviewing the related projects that use vision based techniques in intelligent environment design, the achieved functions, technical issues and drawbacks of those projects are discussed and summarized, and the potential solutions for future improvement are proposed, which leads to the prospective direction of my PhD research.

Modelling seasonally varying data: A case study for sudden infant death syndrome (SIDS)

Many time series are measured monthly, either as averages or totals, and such data often exhibit seasonal variability-the values of the series are consistently larger for some months of the year than for others. A typical series of this type is the number of deaths each month attributed to SIDS (Sudden Infant Death Syndrome). Seasonality can be modelled in a number of ways. This paper describes and discusses various methods for modelling seasonality in SIDS data, though much of the discussion is relevant to other seasonally varying data. There are two main approaches, either fitting a circular probability distribution to the data, or using regression-based techniques to model the mean seasonal behaviour. Both are discussed in this paper.