7 research outputs found

    Assessing and augmenting SCADA cyber security: a survey of techniques

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    SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

    Ice-sheet Dynamics and Postglacial Sedimentary Processes of Coastal SĂžre SunnmĂžre, Southwest Norway

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    Submarine glacial landforms have been identified and mapped in order to reconstruct ice sheet dynamics and to describe postglacial sedimentary processes of coastal Sþre Sunnmþre in southwestern Norway which lies between 62 and 62.5⁰N. Landform identification has been accomplished through analysis of high-resolution multibeam echosounder (MBES) bathymetric data, backscatter data, LiDAR data, video recordings, and seismic data using ArcGIS (geographical information system). The submarine landscape architecture of coastal Sþre Sunnmþre has been largely shaped by glacialinterglacial cycles. The majority of present-day glacial landforms and deposits are a result of growth and decay cycles of the Fennoscandian Ice Sheet during the late Weichselian glaciation of the Pleistocene. A simplified model describing ice sheet dynamics from maximum glacial conditions until final deglaciation is proposed based on evidence including glacial lineations, glacial troughs, morainal banks, and De Geer moraines. Sþre Sunnmþre’s dissected and discontinuous distribution of high elevation alpine environments has resulted in a unique glacial dynamics narrative which differs from other localities of southwestern Norway. Sedimentary processes active during final deglaciation up until the present have continued to rework glacially deposited sediment and alter glacial landforms. Fluvial systems and terrestrial mass wasting events continue to supply sediment to marine environments. The occurrence of slope failures, potentially triggered by postglacial isostatic rebound, is indicated by evidence such as submarine rock avalanche deposits and slide scars

    The Practical Guide to Latino Marketing

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    Python Functional Programming: Study of List Comprehensions and Lambda Functions Performance and Change-Proneness Risk

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    RÉSUMÉ: Python est un langage de programmation populaire et sa popularitĂ© gagne du terrain dans de nombreux secteurs informatiques diffĂ©rents tels que l’apprentissage automatique, l’analyse de donnĂ©es, etc. De nos jours, c’est le langage de programmation standard d’apprentissage automatique. La popularitĂ© de Python s’explique en partie par sa syntaxe proche de l’anglais, son niveau d’abstraction et les structures de donnĂ©es disponibles facilitant la tĂąche pour implĂ©menter rapidement des idĂ©es abstraites au moyen d’un vaste Ă©cosystĂšme de modules et de bibliothĂšques. Les fonctionnalitĂ©s Python permettent de mettre en Ɠuvre des idĂ©es plus efficacement et plus rapidement, souvent en utilisant moins de lignes de code [1] par rapport aux autres langages. De plus, bien qu’il s’agisse d’un langage interprĂ©tĂ©, les performances sont acceptables dans la plupart des cas oĂč le temps n’est pas la contrainte la plus stricte. Python est un langage multi-paradigme et l’une de ses fonctionnalitĂ©s populaires, utilisĂ©e par de nombreux programmeurs, est la programmation fonctionnelle. Ce dernier, mĂȘme s’il peut avoir quelques effets indĂ©sirables, offre plusieurs avantages aux programmeurs comme une meilleure parallĂ©lisation et mĂȘme parfois une meilleure comprĂ©hensibilitĂ© [2]. Ce projet se concentre sur deux constructions de programmation fonctionnelle en Python qui sont la comprĂ©hension de liste et les fonctions lambda. Il y a plusieurs objectifs. Pre- miĂšrement et avant tout, dĂ©veloppez un petit ensemble de rĂšgles pour transformer les com- prĂ©hensions de liste (programmation fonctionnelle) en constructions Ă©quivalentes basĂ©es sur des boucles for et vice-versa. Ces rĂšgles doivent ĂȘtre suffisamment gĂ©nĂ©rales pour garantir que la plupart des comprĂ©hensions de liste sont correctement transformĂ©es. Une fois les rĂšgles dĂ©veloppĂ©es, un deuxiĂšme objectif est de comparer et de contraster les performances, c’est- Ă -dire de vĂ©rifier si la comprĂ©hension des listes est effectivement plus rapide. Pour vĂ©rifier les performances, plusieurs Ă©tapes ont Ă©tĂ© effectuĂ©es. La comparaison entre la comprĂ©hension de liste et les boucles for a Ă©tĂ© effectuĂ©e en exĂ©cutant des fragments de code Ă©quivalents de 10 000 et 100 000 itĂ©rations. L’expĂ©rience a Ă©tĂ© reproduite 30 fois, les rĂ©sultats collectĂ©s et analysĂ©s statistiquement Ă  l’aide de la mĂ©thode du Cliff delta. Les rĂ©sultats montrent qu’il est prĂ©fĂ©rable d’utiliser la comprĂ©hension de liste plutĂŽt que les boucles for lorsqu’il s’agit d’exĂ©cuter un code avec un grand nombre d’itĂ©rations. ABSTRACT: Python is a popular programming language and its popularity is gaining traction in many different IT sectors such as machine learning, data analytics etc.. Nowadays it is the factor of the standard machine learning programming language. Python’s popularity is partially ex- plained by its syntax close to English, its level of abstraction and its available data structures easing the task of quickly implementing abstract ideas through a vast ecosystem of modules and libraries. Python features allow ideas implementation more efficiently and quickly, often, using fewer lines of code [1] compared to other languages. Furthermore, despite being an interpreted language, performances are acceptable in most cases where time is not the most stringent constraint. Python is a multi-paradigm language and one of its popular features, used by a lot of programmers, is functional programming. The latter, even if it may have some undesirable effects, offers several advantages to programmers, advantages such as better parallelization and even sometimes better comprehensibility [2]. This project focuses on two Python functional programming constructs: list comprehension and lambda functions. There are multiple objectives. First and foremost develop a small set of rules to transform list comprehensions (functional programming) into the equivalent for loop-based constructs and vice-versa. These rules should be general enough to ensure most list comprehensions are correctly transformed. Once rules are developed, a second objective is to compare and contrast performances i.e., verify if indeed list comprehensions run faster. To verify performance, several steps have been carried out. The comparison between list comprehension and for loops has been performed running 10 000 and 100 000 iterations equivalent code fragments. The experiment has been replicated 30 times, and the results were collected and statistically analyzed using the Cliff delta effect size. The results show that it is better to use list comprehension over for loops when it comes to running a code with a great number of iterations

    Ice-sheet Dynamics and Postglacial Sedimentary Processes of Coastal SĂžre SunnmĂžre, Southwest Norway

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    Submarine glacial landforms have been identified and mapped in order to reconstruct ice sheet dynamics and to describe postglacial sedimentary processes of coastal Sþre Sunnmþre in southwestern Norway which lies between 62 and 62.5⁰N. Landform identification has been accomplished through analysis of high-resolution multibeam echosounder (MBES) bathymetric data, backscatter data, LiDAR data, video recordings, and seismic data using ArcGIS (geographical information system). The submarine landscape architecture of coastal Sþre Sunnmþre has been largely shaped by glacialinterglacial cycles. The majority of present-day glacial landforms and deposits are a result of growth and decay cycles of the Fennoscandian Ice Sheet during the late Weichselian glaciation of the Pleistocene. A simplified model describing ice sheet dynamics from maximum glacial conditions until final deglaciation is proposed based on evidence including glacial lineations, glacial troughs, morainal banks, and De Geer moraines. Sþre Sunnmþre’s dissected and discontinuous distribution of high elevation alpine environments has resulted in a unique glacial dynamics narrative which differs from other localities of southwestern Norway. Sedimentary processes active during final deglaciation up until the present have continued to rework glacially deposited sediment and alter glacial landforms. Fluvial systems and terrestrial mass wasting events continue to supply sediment to marine environments. The occurrence of slope failures, potentially triggered by postglacial isostatic rebound, is indicated by evidence such as submarine rock avalanche deposits and slide scars
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