This essay takes the three models from Allison and Zelikow book Essence of decision and applies them on the Swedish defense system. After the cold war the Swedish defense system had to undergo changes to be a more modern defense and be able to defend Sweden against threats. To also be able to cooperate with other countries in peacekeeping operations the Swedish defense had to be reorganized. The solution was to change direction from a defense system that was organized for invasion to instead be a movable defense ready for any challenge in Sweden or abroad. This reorganization will be analyzed according to the three different models.

<p>This essay takes the three models from Allison and Zelikow book Essence of decision and applies them on the Swedish defense system. After the cold war the Swedish defense system had to undergo changes to be a more modern defense and be able to defend Sweden against threats. To also be able to cooperate with other countries in peacekeeping operations the Swedish defense had to be reorganized. The solution was to change direction from a defense system that was organized for invasion to instead be a movable defense ready for any challenge in Sweden or abroad. This reorganization will be analyzed according to the three different models.</p>

There has recently been a resurgence in interest in techniques for effective programming of multi-core computers. Most programmers find general-purpose concurrent programming to be extremely difficult. This difficulty severely limits the number of applications that currently benefit from multi-core computers. There already exist many concurrent solutions for the class of regular applications, which include various algorithms for linear algebra. For the class of irregular applications, which operate on dynamic and pointer- and graph-based structures, efficient concurrent solutions have so far remained elusive. Dataflow analysis applications, which are often found in compilers and program analysis tools, have received particularly little attention with regard to execution on multi-core machines. Operating on the theory that the Actor model, which structures computations as systems of asynchronously-communicating entities, is a more appropriate method for representing irregular algorithms than the shared-memory model, this work presents a concurrent Actor-based formulation of the IFDS, or Interprocedural Finite Distributive Subset, dataflow analysis algorithm. The implementation of this algorithm is done using the Scala language and its Actors library. This algorithm achieves significant speedup on multi-core machines without using any optimistic execution. This work contributes to Actor research by showing how the Actor model can be practically applied to a dataflow analysis problem. This work contributes to static analysis research by showing how a dataflow analysis algorithm can effectively make use of multi-core machines, allowing the possibility of faster and more precise analyses.

Devido ao contínuo crescimento dos dados científicos nos últimos anos, a análise intensiva de dados nessas quantidades massivas de dados é muito importante para extrair informações valiosas. Por outro lado, o formato de dados científicos GRIB (GRIdded Binary) é amplamente utilizado na comunidade meteorológica para armazenar histórico de dados e previsões meteorológicas. No entanto, as ferramentas atuais disponíveis e métodos para processar arquivos neste formato não realizam o processamento em um ambiente distribuído. Essa situação limita as capacidades de análise dos cientistas que precisam realizar uma avaliação sobre grandes conjuntos de dados com o objetivo de obter informação no menor tempo possível fazendo uso de todos os recursos disponíveis. Neste contexto, este trabalho apresenta uma alternativa ao processamento de dados no formato GRIB usando o padrão Manager-Worker implementado com o modelo de atores fornecido pelo Akka toolkit. Realizamos também uma comparação da nossa proposta com outros mecanismos, como o round-robin, random, balanceamento de carga adaptativo, bem como com um dos principais frameworks para o processamento de grandes quantidades de dados tal como o Apache Spark. A metodologia utilizada considera vários fatores para avaliar o processamento dos arquivos GRIB. Os experimentos foram conduzidos em um cluster na plataforma Microsoft Azure. Os resultados mostram que nossa proposta escala bem à medida que o número de nós aumenta. Assim, nossa proposta atingiu um melhor desempenho em relação aos outros mecanismos utilizados para a comparação, particularmente quando foram utilizadas oito máquinas virtuais para executar as tarefas. Nosso trabalho com o uso de metadados alcançou um ganho de 53.88%, 62.42%, 62.97%, 61.92%, 62.44% e 59.36% em relação aos mecanismos round-robin, random, balanceamento de carga adaptativo que usou métricas CPU, JVM Heap e um combinado de métricas, e o Apache Spark, respectivamente, em um cenário onde um critério de busca é aplicado para selecionar 2 dos 27 parâmetros totais encontrados no conjunto de dados utilizado nos experimentos. / Because of the continuous and overwhelming growth of scientific data in the last few years, data-intensive analysis on this vast amount of scientific data is very important to extract valuable scientific information. The GRIB (GRIdded Binary) scientific data format is widely used within the meteorological community and is used to store historical meteorological data and weather forecast simulation results. However, current libraries to process the GRIB files do not perform the computation in a distributed environment. This situation limits the analytical capabilities of scientists who need to perform analysis on large data sets in order to obtain information in the shortest time possible using of all available resources. In this context, this work presents an alternative to data processing in the GRIB format using the well-know Manager-Worker pattern, which was implemented with the Actor model provided by the Akka toolkit. We also compare our proposal with other mechanisms, such as the round-robin, random and an adaptive load balancing, as well as with one of the main frameworks currently existing for big data processing, Apache Spark. The methodology used considers several factors to evaluate the processing of the GRIB files. The experiments were conducted on a cluster in Microsoft Azure platform. The results show that our proposal scales well as the number of worker nodes increases. Our work reached a better performance in relation to the other mechanisms used for the comparison particularly when eight worker virtual machines were used. Thus, our proposal upon using metadata achieved a gain of 53.88%, 62.42%, 62.97%, 61.92%, 62.44% and 59.36% in relation to the mechanisms: round-robin, random, an adaptive load balancing that used CPU, JVM Heap and mix metrics, and the Apache Spark respectively, in a scenario where a search criteria is applied to select 2 of 27 total parameters found in the dataset used in the experiments.

Devido ao contínuo crescimento dos dados científicos nos últimos anos, a análise intensiva de dados nessas quantidades massivas de dados é muito importante para extrair informações valiosas. Por outro lado, o formato de dados científicos GRIB (GRIdded Binary) é amplamente utilizado na comunidade meteorológica para armazenar histórico de dados e previsões meteorológicas. No entanto, as ferramentas atuais disponíveis e métodos para processar arquivos neste formato não realizam o processamento em um ambiente distribuído. Essa situação limita as capacidades de análise dos cientistas que precisam realizar uma avaliação sobre grandes conjuntos de dados com o objetivo de obter informação no menor tempo possível fazendo uso de todos os recursos disponíveis. Neste contexto, este trabalho apresenta uma alternativa ao processamento de dados no formato GRIB usando o padrão Manager-Worker implementado com o modelo de atores fornecido pelo Akka toolkit. Realizamos também uma comparação da nossa proposta com outros mecanismos, como o round-robin, random, balanceamento de carga adaptativo, bem como com um dos principais frameworks para o processamento de grandes quantidades de dados tal como o Apache Spark. A metodologia utilizada considera vários fatores para avaliar o processamento dos arquivos GRIB. Os experimentos foram conduzidos em um cluster na plataforma Microsoft Azure. Os resultados mostram que nossa proposta escala bem à medida que o número de nós aumenta. Assim, nossa proposta atingiu um melhor desempenho em relação aos outros mecanismos utilizados para a comparação, particularmente quando foram utilizadas oito máquinas virtuais para executar as tarefas. Nosso trabalho com o uso de metadados alcançou um ganho de 53.88%, 62.42%, 62.97%, 61.92%, 62.44% e 59.36% em relação aos mecanismos round-robin, random, balanceamento de carga adaptativo que usou métricas CPU, JVM Heap e um combinado de métricas, e o Apache Spark, respectivamente, em um cenário onde um critério de busca é aplicado para selecionar 2 dos 27 parâmetros totais encontrados no conjunto de dados utilizado nos experimentos. / Because of the continuous and overwhelming growth of scientific data in the last few years, data-intensive analysis on this vast amount of scientific data is very important to extract valuable scientific information. The GRIB (GRIdded Binary) scientific data format is widely used within the meteorological community and is used to store historical meteorological data and weather forecast simulation results. However, current libraries to process the GRIB files do not perform the computation in a distributed environment. This situation limits the analytical capabilities of scientists who need to perform analysis on large data sets in order to obtain information in the shortest time possible using of all available resources. In this context, this work presents an alternative to data processing in the GRIB format using the well-know Manager-Worker pattern, which was implemented with the Actor model provided by the Akka toolkit. We also compare our proposal with other mechanisms, such as the round-robin, random and an adaptive load balancing, as well as with one of the main frameworks currently existing for big data processing, Apache Spark. The methodology used considers several factors to evaluate the processing of the GRIB files. The experiments were conducted on a cluster in Microsoft Azure platform. The results show that our proposal scales well as the number of worker nodes increases. Our work reached a better performance in relation to the other mechanisms used for the comparison particularly when eight worker virtual machines were used. Thus, our proposal upon using metadata achieved a gain of 53.88%, 62.42%, 62.97%, 61.92%, 62.44% and 59.36% in relation to the mechanisms: round-robin, random, an adaptive load balancing that used CPU, JVM Heap and mix metrics, and the Apache Spark respectively, in a scenario where a search criteria is applied to select 2 of 27 total parameters found in the dataset used in the experiments.

Expansion of computer networks and availability of internet connection enables our society to grow faster then ever before. However, at the same time it opens up a new opportunuties for a cybercrime activities. That's why there is an increasing need of security administrators and law enforcing agencies for existence of a tools to analyze the captured data flows. This master thesis deals with ways of analysis of captured network traffic in a distributed environment, which would allow scaling of available analysis power and therefore adapt to ever increasing volumes of data transmitted over the computer networks.

Existem várias linguagens e plataformas que permitem a programação baseada no modelo de atores, uma solução elegante para a programação concorrente proposta há algumas décadas. Segundo esse modelo, implementa-se o programa na forma de uma série de agentes que são executados em paralelo e se comunicam entre si somente por meio da troca de mensagens, sem a necessidade de memória compartilhada ou estruturas tradicionais de sincronização como semáforos e mutexes. Uma das áreas nas quais esse modelo seria particularmente adequado é a programação de aplicações web, isto é, aplicações cujas lógicas de negócios e de dados residem num servidor e que são acessadas pelo usuário por intermédio de um navegador. Porém, existem muitos obstáculos ao desenvolvimento de aplicações desse tipo, entre eles a falta de linguagens e ferramentas que permitam integrar tanto o servidor quanto o cliente (navegador) no modelo de atores, as dificuldades de conversões de dados que se fazem necessárias quando o servidor e o cliente são desenvolvidos em linguagens diferentes, e a necessidade de contornar as dificuldades inerentes aos detalhes do protocolo de comunicação (HTTP). O PAWEB é uma proposta de uma plataforma para o desenvolvimento e execução de aplicações web que fornece a infraestrutura necessária para que tanto o lado cliente quanto o lado servidor do aplicativo hospedado possam ser escritos numa mesma linguagem (Python), e possam criar e gerenciar atores que trocam mensagens entre si,tanto local quanto remotamente, de maneira transparente e sem a necessidade de implementar conversões de dados ou outros detalhes de baixo nível. / There are several programming languages and platforms that allow the development of systems based on the actor model, an elegant solution for concurrent programming proposed a few decades ago. According to this model, the program is implemented in the form of several agents that run concurrently and only communicate amongst themselves through the exchange of messages, without the need for shared memory or traditional synchronization structures such as semaphores and mutexes. One of the areas where this model would be particularly appropriate would be the development of web applications, that is, applications whose business and database logic reside on the server and are accessed by the user by means of a web browser. However, there are several obstacles to the development of this type of application, amongst them the lack of languages and tools that allow for the integration of both the server and the client (browser) into the actor model, data conversion difficulties arising from using different programming languages on the server and the client, and the need to circumvent the inherent difficulties posed by the details of the communications protocol (HTTP). PAWEB is a proposal for an application development and execution platform that supplies the infrastructure needed so that both the server and client sides of the hosted application can be written in the same language (Python) and so that they may create and manage actors that exchange messages with one another, both locally and remotely, in a transparent manner and without the need to implement data conversions or other low-level mechanisms.

O modelo de programação baseado em atores é frequentemente utilizado para o desenvolvimento de grandes aplicações e sistemas. Podemos citar como exemplo o serviço de bate-papo do Facebook ou ainda o WhatsApp. Estes sistemas dão suporte a milhares de usuários conectados simultaneamente levando em conta estritas restrições de desempenho e interatividade. Tais sistemas normalmente são amparados por infraestruturas de hardware com processadores de múltiplos núcleos. Normalmente, máquinas deste porte são baseadas em uma estrutura de memória compartilhada hierarquicamente (NUMA - Non-Uniform Memory Access). Nossa análise dos atuais ambientes de execução para atores e a pesquisa na literatura mostram que poucos estudos sobre a adequação deste ambientes a essas plataformas hierárquicas foram conduzidos. Estes ambientes de execução normalmente assumem que o espaço de memória é uniforme o que pode causar sérios problemas de desempenho. Nesta tese nós estudamos os desafios enfrentados por um ambiente de execução para atores quando da sua execução nestas plataformas. Estudamos particularmente os problemas de gerenciamento de memória, de escalonamento e de balanceamento de carga. Neste documento nós também analisamos e caracterizamos as aplicações baseadas no modelo de atores. Tal análise nos permitiu evidenciar o fato de que a execução de benchmarks e aplicações criam estruturas de comunicação peculiares entre os atores. Tais peculiaridades podem, então, ser utilizadas pelos ambientes de execução para otimizar o seu desempenho. A avaliação dos grafos de comunicação e a implementação da prova de conceito foram feitas utilizando um ambiente de execução real, a máquina virtual da linguagem Erlang. A linguagem Erlang utiliza o modelo de atores para concorrência com uma sintaxe clara e consistente. As modificações que nós efetuamos nesta máquina virtual permitiram uma melhora significativa no desempenho de certas aplicações através de uma melhor afinidade de comunicação entre os atores. O escalonamento e o balanceamento de carga também foram melhorados graças à utilização do conhecimento sobre o comportamento da aplicação e sobre a plataforma de hardware. / The actor model is present in several mission-critical systems, such as those supporting WhatsApp and Facebook Chat. These systems serve thousands of clients simultaneously, therefore demanding substantial computing resources usually provided by multi-processor and multi-core platforms. Non-Uniform Memory Access (NUMA) architectures account for an important share of these platforms. Yet, research on the suitability of the current actor runtime environments for these machines is very limited. Current runtime environments, in general, assume a flat memory space, thus not performing as well as they could. In this thesis we study the challenges hierarchical shared memory multi-core platforms present to actor runtime environments. In particular, we investigate aspects related to memory management, scheduling, and load-balancing. In this document, we analyze and characterize actor based applications to, in light of the above, propose improvements to actor runtime environments. This analysis highlighted the existence of peculiar communication structures. We argue that the comprehension of these structures and the knowledge about the underlying hardware architecture can be used in tandem to improve application performance. As a proof of concept, we implemented our proposal using a real actor runtime environment, the Erlang Virtual Machine (VM). Concurrency in Erlang is based on the actor model and the language has a consistent syntax for actor handling. Our modifications to the Erlang VM significantly improved the performance of some applications thanks to better informed decisions on scheduling and on load-balancing.

This Bachelor thesis focuses on examining the Ghanaian state's policies regarding inward Foreign Direct Investments and furthermore the policy implementation to attract and receive FDI, the question asked is What policy choices have been implemented by Ghana to attract Chinese FDI? This thesis employs a single case study design with a qualitative approach as it seeks to draw upon Liberal IPE and RAM to understand the policy choices in attracting FDI, more specifically how Ghana has shaped their policies. When conducting the analysis, the thesis assembles documents, both primary and secondary data to be able to answer the research question. The documents used for gathering data is from Ghana's government as well as governmental organisations, governmental policies and official statistics to peer reviewed articles and organisational data. This enables the thesis to find empirical evidence to support the aims of the conducted research. Moreover, secondary data will be used to situate, contextualize and present the findings. The main problem seen is how the policy behaviour of governments is conducted to receive FDI in this trudge. The solution to the problem is presented to be the policy decision taken to open markets and welcoming Foreign Direct Investment, through reforms aimed at both domestic companies and market as well as to the global markets and actors.

<p>University of Växjö, School of Social Sciences</p><p>Course: PO 5363, Political Science, G3</p><p>Title: the Role of the USA’s and Great Britain in the Coup d'Etat, Iran 1953</p><p>Author: Ashkan Panahirad</p><p>Supervisor: Lennart Bergfeldt</p><p>The purpose of this study is to examine Great Britain’s and US’ motives and action alternatives in regards to the Coup d'état against the iranian regime under Mossadegh in 1953.</p><p>The method used is motive analysis (investigates the actors motives). The theories used are Rational actors model and Governmental politics. Rational actor model allows states to choose among a set of alternatives displayed in a particular situation in order to achieve their goals. Governmental politics explains what happens in states as a result of bargaining games between important actors in the government.</p><p>Analysis from the rational actor model shows that the motives behind the Coup d'état were oil, economical reasons, Iran and communism. Coup d'état was the most rational action for them to achieve their goals. Governmental politics reveal the shifting of policies from one administration to another. While Clement Attlee’s government and Harry Truman’s administration where more moderate, Winston Churchill’s and Eisenhower’s where more eager to replace Mossadegh, which finally lead to a Coup d'état</p>