7 research outputs found
Assessing and augmenting SCADA cyber security: a survey of techniques
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
Submarine glacial landforms have been identified and mapped in order to reconstruct ice sheet
dynamics and to describe postglacial sedimentary processes of coastal SĂžre SunnmĂžre in
southwestern Norway which lies between 62 and 62.5â°N. 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 SĂžre SunnmĂžre 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. SĂžre SunnmĂžreâs 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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A letter from Edward D. Ossim to Oscar Del Rio regarding his inquiry for employment.
A letter from Edward D. Ossim to Oscar Del Rio regarding his inquiry for employment
Python Functional Programming: Study of List Comprehensions and Lambda Functions Performance and Change-Proneness Risk
RĂSUMĂ: Python est un langage de programmation populaire et sa popularitĂ© gagne du terrain dans de nombreux secteurs informatiques diffĂ©rents tels que lâapprentissage automatique, lâanalyse de donnĂ©es, etc. De nos jours, câest le langage de programmation standard dâapprentissage automatique. La popularitĂ© de Python sâexplique en partie par sa syntaxe proche de lâanglais, son niveau dâabstraction et les structures de donnĂ©es disponibles facilitant la tĂąche pour implĂ©menter rapidement des idĂ©es abstraites au moyen dâun vaste Ă©cosystĂšme de modules et de bibliothĂšques. Les fonctionnalitĂ©s Python permettent de mettre en Ćuvre 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 quâil sâagisse dâun langage interprĂ©tĂ©, les performances sont acceptables dans la plupart des cas oĂč le temps nâest pas la contrainte la plus stricte. Python est un langage multi-paradigme et lâune de ses fonctionnalitĂ©s populaires, utilisĂ©e par de nombreux programmeurs, est la programmation fonctionnelle. Ce dernier, mĂȘme sâil 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, câest- 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. LâexpĂ©rience a Ă©tĂ© reproduite 30 fois, les rĂ©sultats collectĂ©s et analysĂ©s statistiquement Ă lâaide de la mĂ©thode du Cliff delta. Les rĂ©sultats montrent quâil est prĂ©fĂ©rable dâutiliser la comprĂ©hension de liste plutĂŽt que les boucles for lorsquâil sâagit dâexĂ©cuter un code avec un grand nombre dâitĂ©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. Pythonâs 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
Submarine glacial landforms have been identified and mapped in order to reconstruct ice sheet
dynamics and to describe postglacial sedimentary processes of coastal SĂžre SunnmĂžre in
southwestern Norway which lies between 62 and 62.5â°N. 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 SĂžre SunnmĂžre 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. SĂžre SunnmĂžreâs 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