The security of powerful systems and large networks is often addressed through complex defenses. While these types of defenses offer increased security, they are resource intensive and therefore impractical to implement on many new classes of networked systems, such as mobile phones and small, embedded network infrastructure devices. To provide security for these systems, new defenses must be created that provide highly efficient security. The Moving Target IPv6 Defense (MT6D) is a network layer moving target defense that dynamically changes Internet Protocol version 6 (IPv6) addresses mid-session while still maintaining continuous communication. MT6D was originally written in Python language, but this implementation suffers from severe performance limitations. By translating MT6D from Python to C and taking advantage of operating system specific application programming interfaces (APIs) and optimizations, MT6D can become a viable defense for resource constrained systems. The Python version of MT6D is analyzed initially to determine what functions might be performance bottlenecks that could be performed more efficiently using C. Based on this analysis, specific parts of the Python version are identified for improvement in the C version by either using functionality of the Linux kernel and network stack or by reworking the code in a more efficient way. After this analysis, the information gathered about the Python version is used to write the C version, using methods specific to a moving target defense to capture, analyze, modify, and tunnel packets. Finally, tests are designed and run to compare the performance of the Python and C versions. / Master of Science

L'essor du Python comme language scientifique et la popularité grandissante du calcul GPGPU constitue un environnement fertile pour le développement de PyTissueOptics, un simulateur de propagation de la lumière dans les tissus, qui est un module entièrement programmé en Python, qui se concentre sur la mise en œuvre simple et compréhensible des mécanismes de propagation de la lumière, afin de catalyser la démocratisation de cette technique. Dans ce mémoire, nous explorons la théorie derrière le modèle de Monte Carlo, visitons les aspects techniques de la réalisation du projet, expliquons les différentes possibilités d'utilisation et comparons avec des modules connus, tel que MCML et MCX. / The rise of Python as a scientific language and the growing popularity of GPGPU computing creates a fertile environment for the development of PyTissueOptics, a light propagation simulator in tissues, which is a module entirely programmed in Python. It focuses on the simple and comprehensible implementation of light propagation mechanisms, aiming to catalyze the democratization of this technique. In this thesis, we explore the theory behind the Monte Carlo model, examine the technical aspects of the project's realization, explain the various usage possibilities, and compare it with known modules, such as MCML and MCX.

Šiame darbe tiriamos trimatės Blender aplinkos panaudojamumo garsinių signalų modeliavimui galimybės. Darbe aprašyta programos vartotojo sąsaja, vidinė architektūra, ištirtos vidinio programavimo galimybės ir pateikti tyrimų rezultatai. Naudojant Python programavimo kalbą buvo sukurta garsinių signalų analizės ir vizualizavimo programa SigBlender, veikianti Blender aplinkoje. Programa naudoja beveik periodinių garso signalų periodų išskyrimo algoritmą, kuris buvo sukurtas ir realizuotas darbo metu. Naudojant tekstinį redaktorių Notepad++ sukurta nauja programavimo aplinka, integruojanti Python ir Blender programas. Darbe pateikiami trimačiai garso signalų ir jų amplitudinių charakteristikų grafikai, demonstruojantys trimatės grafikos privalumus garsinių signalų vizualizavime. / This work studies feasibility of a three-dimensional environment, called Blender, for sound signal modeling. It describes user interface and architecture of the environment and analyses capabilities of internal programming. During the work a program for a sound signal analysis and visualization was developed. It was written using Python programming language and was called SigBlender. For extraction of periods of almost periodical sound signals SigBlender uses an algorithm which was developed and implemented during this work. By using the text editor Notepad++ a new programming environment was created and used for coding. Charts of sound signals and their spectral characteristics presented throughout this work illustrate the benefits of visualizing sound signals in a three-dimensional space.

SQLite filer används av ett flertal olika program för att spara viktig information.Information som kan vara viktig för forensiska utredningar, behovet att kunnaåterskapa SQLite filer är då ett växande bekymmer. Problemet med att återskapa SQLitefiler är att, till skillnad från andra filer så har SQLite filer inget definerat slut eller någonmarkör som visar var filen slutar. Detta arbete presenterar en ny metod att bestämmaslutet på SQLite filer och jämför denna metod mot den metod som används idag tillmesta del för att återskapa SQLite filer. För att jämföra dessa metoder utvecklades tvåprogram stpextr och blkextr. Blkextr är den metod som utvecklades under detta arbete.Stpextr visade sig vara snabbare och använda mindre arbetsminne än blkextr. Men ivissa sammanhang så kommer information gå förlorad när stpextr körs till skillnad från blkextr.

In recent years, the use of machine learning has increased significantly. Its uses range from making the everyday life easier with voice-guided smart devices to image recognition, or predicting the stock market. Predicting economic values has long been possible by using methods other than machine learning, such as statistical algorithms. These algorithms and machine learning models use time series, which is a set of data points observed constantly over a given time interval, in order to predict data points beyond the original time series. But which of these methods gives the best results? The overall purpose of this project is to predict Sweden’s aid curve using the machine learning model Support Vector Regression and the classic statistical algorithm autoregressive integrated moving average which is abbreviated ARIMA. The time series used in the prediction are annual summaries of Sweden’s total aid to the world from openaid.se since 1998 and up to 2019. SVR and ARIMA are implemented in python with the help of the Scikit- and Statsmodels libraries. The results from SVR and ARIMA are measured in comparison with the original value and their predicted values, while the accuracy is measured in Root Square Mean Error and presented in the results chapter. The result shows that SVR with the RBF-kernel is the algorithm that provides the best results for the data series. All predictions beyond the times series are then visually presented on a openaid prototype page using D3.js / Under det senaste åren har användningen av maskininlärning ökat markant. Dess användningsområden varierar mellan allt från att göra vardagen lättare med röststyrda smarta enheter till bildigenkänning eller att förutspå börsvärden. Att förutspå ekonomiska värden har länge varit möjligt med hjälp av andra metoder än maskininlärning, såsom exempel statistiska algoritmer. Dessa algoritmer och maskininlärningsmodeller använder tidsserier, vilket är en samling datapunkter observerade konstant över en given tidsintervall, för att kunna förutspå datapunkter bortom den originella tidsserien. Men vilken av dessa metoder ger bäst resultat? Projektets övergripande syfte är att förutse sveriges biståndskurva med hjälp av maskininlärningsmodellen Support Vector Regression och den klassiska statistiska algoritmen autoregressive integrated moving average som förkortas ARIMA. Tidsserien som används vid förutsägelsen är årliga summeringar av biståndet från openaid.se sedan år 1998 och fram till 2019. SVR och ARIMA implementeras i python med hjälp av Scikit-learn och Statsmodelsbiblioteken. Resultatet från SVR och ARIMA mäts i jämförelse mellan det originala värdet och deras förutspådda värden medan noggrannheten mäts i root square mean error och presenteras under resultatkapitlet. Resultatet visar att SVR med RBF kärnan är den algoritm som ger det bästa testresultatet för dataserien. Alla förutsägelser bortom tidsserien presenteras därefter visuellt på en openaid prototypsida med hjälp av D3.js.

Esta tese propõe um modelo computacional para análise de conformidade de áreas e superfícies de proteção de aeródromos aos critérios de projeto geométrico previstos no Anexo 14 da ICAO (International Civil Aviation Organization). Não foram encontrados na literatura softwares open source com esta finalidade. Os critérios da ICAO impõem áreas e superfícies imaginárias de proteção que se originam na vizinhança de cada uma das pistas de pouso e/ou de decolagem. Dessas exigências normativas decorre um complexo conjunto de áreas em solo e superfícies no espaço aéreo, as quais ordenam a presença de objetos fixos e móveis dentro e fora dos limites do sítio aeroportuário. Os dados de entrada do modelo proposto compreendem: informações sobre a topografia e sobre os limites internos e externos do sítio; a posição de objetos fixos e móveis; a categoria da aeronave; o procedimento de aproximação empregado; e informações sobre a configuração do sistema de pistas. O modelo computacional proposto integra conceitos de CAD (Computer Aided Design) e de GIS (Geographic Information System) para a geração automática de geometrias georreferenciadas, de acordo com um MDE (Modelo Digital de Elevação), internamente representado por uma malha TIN (Triangulated Irregular Network). Além da geração virtual das geometrias, o modelo permite a detecção automática de eventuais interferências nas áreas e superfícies de proteção pelos objetos fixos e móveis. O modelo apresenta os resultados das análises por meio de janelas gráficas e permite a exportação dos arquivos KML para um globo virtual, como o Google Earth. Os arquivos KML representam as áreas e superfícies de proteção e os objetos fixos e móveis, destacando os obstáculos detectados. A modelagem proposta foi implementada em linguagem Python, testada e validada para instâncias fictícias e para um caso real, relacionado ao Aeroporto de Viracopos em Campinas, no Brasil (SBKP). Buscas sistemáticas na literatura científica nacional e internacional indicam que a modelagem aqui proposta é inédita, contribuindo para preencher a lacuna identificada na revisão bibliográfica realizada. / This thesis proposes a computational model for analysis of conformity of aerodrome protection areas and surfaces according to ICAO (International Civil Aviation Organization) Annex 14 geometric design criteria. No open source software with this purpose could be found in the literature. ICAO criteria impose imaginary protection areas and surfaces that start at the vicinity of each runway, leading to a complex set of geometries on the ground and in the airspace. Fixed and movable objects, both inside and outside the aerodrome property limits, are controlled by means of this set of imaginary surfaces. Input data for the herein proposed model comprises: aerodrome site topography and internal and external boundaries; fixed and movable objects position; aircraft category; approach procedures; and runway system configuration data. The model integrates CAD (Computer Aided Design) and GIS (Geographic Information System) technologies in order to automatically generate georeferenced geometries, that take into account a DEM (Digital Elevation Model), internally represented by a TIN (Triangulated Irregular Network) approach. In addition to geometry generation, the proposed model also performs obstacle assessment regarding the suppositional geometric interferences between protection areas and surfaces and the fixed and movable objects. The model results are outputted by means of screen plots, execution console (detected geometric interferences) and KML (Keyhole Markup Language) files, to be exported to virtual globes, like Google Earth. The KML files represent the geometries of protection areas and surfaces as well as fixed and movable objects, highlighting detected obstacles. The model was implemented in Python language and tested for validation, employing both fictitious and a real instance, related to the Viracopos International Airport (SBKP), in Campinas, Brazil. The undergone bibliographic search, considering national and international literature, indicates that this research introduces an unprecedented model, filling in a gap in the literature.

In recent years, the use of magnetic resonance technology has grown with advances in hardware, delivering accessible and small-size equipment and devices that open a range of new applications. Innovation in this field requires versatility and flexibility of both hardware and software. Despite the technological advances in the magnetic resonance hardware, the software still the most notable problem currently. This stagnation, delays progress that could reduce production costs and deliver faster development. Researchers in this field are unsatisfied with currently available options. In this panorama, we seek the enhancement of our specific framework for programming magnetic resonance systems, employing concepts from the areas of computing, engineering, and physics. This setup allows the software to merge different perceptions, causing it to be flexible and robust. We converged to Python and object-oriented programming to offer the Python Magnetic Resonance framework - PyMR. The PyMR includes graphical interfaces from templates that can be filled with data, requiring no programming. Our framework comprises other programming tools such as our plugin for the Spyder IDE, which creates the perfect environment to create systems and the pulse sequences. Also, a user-friendly magnetic resonance simulator MR SPRINT, derived from the PyMR structure, addresses educational use, exposing the whole experiment construction, setup, and visualization. Including, PyMR has been contributing to new challenging magnetic resonance systems, introducing modern concepts to change the actual scenario the researchers are facing when developing new magnetic resonance systems. / Nos últimos anos, o uso da tecnologia de ressonância magnética cresceu com os avanços em hardware, fornecendo equipamentos e dispositivos acessíveis e de pequeno porte que abrem uma série de novas aplicações. Inovações neste campo requerem versatilidade e flexibilidade de hardware e software. Apesar dos avanços tecnológicos no hardware de ressonância magnética, o software ainda é um dos maiores problemas atualmente. Essa estagnação atrasa o progresso que poderia reduzir os custos de produção e proporcionar um desenvolvimento mais rápido. Além disso, pesquisadores neste campo estão insatisfeitos com as opções atualmente disponíveis. Com este panorama, buscamos o aprimoramento de nosso framework para programação de sistemas de ressonância magnética, empregando conceitos das áreas de computação, engenharia e física. Essa configuração permite que o software mescle visões de diferentes meios, fazendo com que a estrutura seja flexível e robusta. Nós convergimos, então, para a linguagem Python e programação orientada a objetos para oferecer o framework Python Magnetic Resonance - PyMR. O PyMR inclui interfaces gráficas a partir de modelos que podem ser preenchidos com dados, sem a necessidade de programação. Nossa estrutura compreende outras ferramentas de programação, como o nosso plugin para o Spyder IDE, que cria o ambiente perfeito para criar novos sistemas e sequências de pulsos. Além disso, um simulador de ressonância magnética de fácil utilização, MR SPRINT, derivado da estrutura PyMR, aborda o uso educacional, expondo toda a construção, configuração e visualização do experimento. O PyMR vem contribuindo para novos e desafiadores sistemas de ressonância magnética, introduzindo conceitos modernos para mudar o cenário atual que os pesquisadores estão enfrentando.

Submitted by Verena Pereira (verenagoncalves@uefs.br) on 2018-11-14T23:32:15Z No. of bitstreams: 1 Disserta??o - Dados Astron?micos_Uma proposta de implementa??o para banco de dados - VERSAO DIGITAL.pdf: 12472772 bytes, checksum: 7819133722c393f66647cb47f14700c6 (MD5) / Made available in DSpace on 2018-11-14T23:32:15Z (GMT). No. of bitstreams: 1 Disserta??o - Dados Astron?micos_Uma proposta de implementa??o para banco de dados - VERSAO DIGITAL.pdf: 12472772 bytes, checksum: 7819133722c393f66647cb47f14700c6 (MD5) Previous issue date: 2018-06-21 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / With the advent of computing, the way of doing science has changed circumstantially, revolutionizing scientific research. In astronomy, telescopes now equipped with increasingly modern sensors, produce data quantities never seen before, making it impossible to exhaust all the capacity to extract knowledge from the data produced, thus presenting conditions of reuse by their peers or other purposes. The value of this data to Science lies in its unexplored potential. In this sense, this work shares the philosophy of Virtual Observatories, regarding the reuse of old data. Therefore, this dissertation is about the implementation of procedures and computational techniques that allow to organize and search for images from telescopes. Images that were found were of the exclusive period. With this, studies were developed on data structure, computational tools, algorithms and programming languages that could contribute to the development and resolution of the research problem under analysis / Com advento da Computa??o, a forma de fazer Ci?ncia mudou circunstancialmente, revolucionando a pesquisa cient?fica. Na Astronomia, os telesc?pios agora equipados com sensorescada vez mais modernos, produzem quantidades de dados nunca vista antes, tornando imposs?vel exaurir toda ? capacidade de extra??o de conhecimento dos dados produzidos, apresentando assim, condi??es de reutiliza??o pelos seus pares ou outras finalidades. O valor desses dados para a Ci?ncia est? no seu potencial n?o explorado. Nesse sentido, esse trabalho compartilha da filosofia dos Observat?rios Virtuais,no que tange ? reutiliza??o de dados antigos. Para tanto, essa disserta??o versa sobre a implementa??o de procedimentos e t?cnicas computacionais que permitem organizar e buscar imagens oriundas de telesc?pios. Imagens que se encontram foram do per?odo de exclusividade. Com isso, foram desenvolvidos estudos sobre estrutura de dados, ferramentas computacionais, algoritmos e linguagens de programa??o que pudessem contribuir com o desenvolvimento e resolu??o do problema de pesquisa em an?lise

Os Sistemas de Distribuição são responsáveis pelo fornecimento da energia elétrica aos consumidores residenciais, industriais e comerciais com padrões de qualidade regulamentados pela Agência Nacional de Energia Elétrica (ANEEL). Assim, as concessionárias monitoram seu sistema para verificar o perfil de tensão na rede elétrica e as perdas técnicas do sistema. Este último critério de desempenho é extremamente relevante, pois representa o desperdício em energia e diminuição na capacidade de receita da empresa. Portanto, há interesse em fornecer a energia elétrica dentro das especificações regidas pela ANEEL e com as menores perdas elétricas possível. Contudo, técnicas como reconfiguração de linhas, recondutoramento, alocação de capacitores e geradores distribuídos são aplicadas. Em especial, a alocação de capacitores é uma técnica que visa identificar a quantidade, localização e tipo dos bancos de capacitores (BCs) que serão alocados no sistema com o intuito de minimizar as perdas, levando em consideração custos de implantação e operação. Para tal, métodos computacionais são utilizados para definir a melhor configuração dos BCs. As metaheurítiscas têm sido aplicadas na solução deste problema, cuja função objetivo é a minimização das perdas técnicas do sistema de distribuição. Desta forma, este trabalho tem o objetivo de propor uma abordagem de solução utilizando a metaheurística Entropia Cruzada implementada no software Python para redução das perdas de sistemas elétricos modelados no OpenDSS. A abordagem se mostrou uma importante ferramenta de análise de sistemas de distribuição, proporcionando resultados extremamente satisfatórios. / The distribution systems are responsible for providing electricity to residential, industrial and commercial consumers under quality standards regulated by the National Electric Energy Agency (ANEEL). Thus, utilities monitor the system to check the voltage profile in the grid and system technical losses. The latter quantity is an extremely important performance criterion, as it represents energy losses and decrease in revenue capacity of the company. Therefore, there is interest in providing electricity within specification stated by ANEEL with the lowest possible electrical losses. Techniques such as topology reconfiguration, reconductoring, allocation of capacitors and distributed generators are usually proposed in technical studies. Particularly, the allocation of capacitors is a technique that aims to identify the amount, location and type of capacitor banks (CBs), which are allocated in the system in order to minimize the losses, taking into consideration the implementation and operation costs. For this purpose, computational methods are used to determine the best configuration of CBs. Metaheuristics have been applied for the solution of this problem, with the objective to minimize the technical losses of distribution systems. This document shows the development of a solution method using the Cross Entropy metaheuristic implemented in Python programming language to reduce the losses of electrical systems modeled in OpenDSS program. The developed approach resulted in an important analysis tool for distribution systems, providing extremely satisfactory results.

Les travaux de recherche de cette thèse concernent principalement l‘aide à la navigation individualisée dans un hypermédia épistémique. Nous disposons d‘un certain nombre de ressources qui peut se formaliser à l‘aide d‘un graphe acyclique orienté (DAG) : le graphe des épistèmes. Après avoir cerné les environnements de ressources et de parcours, les modalités de visualisation et de navigation, de traçage, d‘adaptation et de fouille de données, nous avons présenté une approche consistant à corréler les activités de conception ou d‘édition à celles dédiées à l‘utilisation et la navigation dans les ressources. Cette approche a pour objectif de fournir des mécanismes d‘individualisation de la navigation dans un environnement qui se veut évolutif. Nous avons alors construit des prototypes appropriés pour mettre à l‘épreuve le graphe des épistèmes. L‘un de ces prototypes a été intégré à une plateforme existante. Cet hypermédia épistémique baptisé HiPPY propose des ressources et des parcours portant sur l‘apprentissage du langage Python. Il s‘appuie sur un graphe des épistèmes, une navigation dynamique et un bilan de connaissances personnalisé. Ce prototype a fait l‘objet d‘une expérimentation qui nous a donné la possibilité d‘évaluer les principes introduits et d‘analyser certains usages. / This research work mainly concerns means of assistance in individualized navigation through an epistemic hypermedia. We have a number of resources that can be formalized by a directed acyclic graph (DAG) called the graph of epistemes. After identifying resources and pathways environments, methods of visualization and navigation, tracking, adaptation and data mining, we presented an approach correlating activities of design or editing with those dedicated to resources‘ use and navigation. This provides ways of navigation‘s individualization in an environment which aims to be evolutive. Then, we built prototypes to test the graph of epistemes. One of these prototypes was integrated into an existing platform. This epistemic hypermedia called HiPPY provides resources and pathways on Python language. It is based on a graph of epistemes, a dynamic navigation and a personalized knowledge diagnosis. This prototype, which was experimented, gave us the opportunity to evaluate the introduced principles and analyze certain uses.