Modelagem e simulação de redes em chip sem fio.

O paradigma das redes em chip (NoCs) surgiu a fim de permitir alto grau de integração entre vários núcleos de sistemas em chip (SoCs), cuja comunicação é tradicionalmente baseada em barramentos. As NoCs são definidas como uma estrutura de switches e canais ponto a ponto que interconectam núcleos de propriedades intelectuais (IPs) de um SoC, provendo uma plataforma de comunicação entre os mesmos. As redes em chip sem fio (WiNoCs) são uma abordagem evolucionária do conceito de rede em chip (NoC), a qual possibilita a adoção dos mecanismos de roteamento das NoCs com o uso de tecnologias sem fio, propondo a otimização dos fluxos de tráfego, a redução de conectores e a atuação em conjunto com as NoCs tradicionais, reduzindo a carga nos barramentos. O uso do roteamento dinâmico dentro das redes em chip sem fio permite o desligamento seletivo de partes do hardware, o que reduz a energia consumida. Contudo, a escolha de onde empregar um link sem fio em uma NoC é uma tarefa complexa, dado que os nós são pontes de tráfego os quais não podem ser desligados sem potencialmente quebrar uma rota preestabelecida. Além de fornecer uma visão sobre as arquiteturas de NoCs e do estado da arte do paradigma emergente de WiNoC, este trabalho também propõe um método de avaliação baseado no já consolidado simulador ns-2, cujo objetivo é testar cenários híbridos de NoC e WiNoC. A partir desta abordagem é possível avaliar diferentes parâmetros das WiNoCs associados a aspectos de roteamento, aplicação e número de nós envolvidos em redes hierárquicas. Por meio da análise de tais simulações também é possível investigar qual estratégia de roteamento é mais recomendada para um determinado cenário de utilização, o que é relevante ao se escolher a disposição espacial dos nós em uma NoC. Os experimentos realizados são o estudo da dinâmica de funcionamento dos protocolos ad hoc de roteamento sem fio em uma topologia hierárquica de WiNoC, seguido da análise de tamanho da rede e dos padrões de tráfego na WiNoC.

Análise numérico-experimental de blindagens balísticas

O desenvolvimento técnico e científico em torno das blindagens tem procurado contrariar o constante aperfeiçoamento dos projéteis e do seu poder de penetração. Para cumprir este objetivo, é necessário recorrer a soluções inovadoras tanto em termos dos materiais utilizados no fabrico, como ao nível do formato da própria blindagem. Com este trabalho pretende-se dar os primeiros passos na produção e teste de materiais em situação de tiro real, bem como na modelação e simulação dos mesmos com o objetivo de adquirir capacidades, técnicas e procedimentos para trabalhos futuros. O trabalho teve início com a realização da pesquisa bibliográfica sobre vários aspetos desde o fabrico até à avaliação do desempenho de blindagens balísticas. O trabalho teórico desta tese incidiu na modelação por elementos finitos dos elementos balísticos (proteções e projétil) tendo como objetivo a simulação numérica da sua interação em condições de impacto. O trabalho experimental foi realizado no campo de tiro da Escola das Armas onde foram testados os alvos com os materiais compósitos produzidos e com placas de alumínio, com diferentes combinações. A análise de resultados permitiu comparar e avaliar as diferenças entre as estimativas teóricas e as suas limitações com as observações experimentais do tiro real.

Physiologically based synthetic models of hepatic disposition

Current Physiologically based pharmacokinetic (PBPK) models are inductive. We present an additional, different approach that is based on the synthetic rather than the inductive approach to modeling and simulation. It relies on object-oriented programming A model of the referent system in its experimental context is synthesized by assembling objects that represent components such as molecules, cells, aspects of tissue architecture, catheters, etc. The single pass perfused rat liver has been well described in evaluating hepatic drug pharmacokinetics (PK) and is the system on which we focus. In silico experiments begin with administration of objects representing actual compounds. Data are collected in a manner analogous to that in the referent PK experiments. The synthetic modeling method allows for recognition and representation of discrete event and discrete time processes, as well as heterogeneity in organization, function, and spatial effects. An application is developed for sucrose and antipyrine, administered separately and together PBPK modeling has made extensive progress in characterizing abstracted PK properties but this has also been its limitation. Now, other important questions and possible extensions emerge. How are these PK properties and the observed behaviors generated? The inherent heuristic limitations of traditional models have hindered getting meaningful, detailed answers to such questions. Synthetic models of the type described here are specifically intended to help answer such questions. Analogous to wet-lab experimental models, they retain their applicability even when broken apart into sub-components. Having and applying this new class of models along with traditional PK modeling methods is expected to increase the productivity of pharmaceutical research at all levels that make use of modeling and simulation.

An Autonomic Framework for Mobile Cloud Computing

This thesis presents the formal definition of a novel Mobile Cloud Computing (MCC) extension of the Networked Autonomic Machine (NAM) framework, a general-purpose conceptual tool which describes large-scale distributed autonomic systems. The introduction of autonomic policies in the MCC paradigm has proved to be an effective technique to increase the robustness and flexibility of MCC systems. In particular, autonomic policies based on continuous resource and connectivity monitoring help automate context-aware decisions for computation offloading. We have also provided NAM with a formalization in terms of a transformational operational semantics in order to fill the gap between its existing Java implementation NAM4J and its conceptual definition. Moreover, we have extended NAM4J by adding several components with the purpose of managing large scale autonomic distributed environments. In particular, the middleware allows for the implementation of peer-to-peer (P2P) networks of NAM nodes. Moreover, NAM mobility actions have been implemented to enable the migration of code, execution state and data. Within NAM4J, we have designed and developed a component, denoted as context bus, which is particularly useful in collaborative applications in that, if replicated on each peer, it instantiates a virtual shared channel allowing nodes to notify and get notified about context events. Regarding the autonomic policies management, we have provided NAM4J with a rule engine, whose purpose is to allow a system to autonomously determine when offloading is convenient. We have also provided NAM4J with trust and reputation management mechanisms to make the middleware suitable for applications in which such aspects are of great interest. To this purpose, we have designed and implemented a distributed framework, denoted as DARTSense, where no central server is required, as reputation values are stored and updated by participants in a subjective fashion. We have also investigated the literature regarding MCC systems. The analysis pointed out that all MCC models focus on mobile devices, and consider the Cloud as a system with unlimited resources. To contribute in filling this gap, we defined a modeling and simulation framework for the design and analysis of MCC systems, encompassing both their sides. We have also implemented a modular and reusable simulator of the model. We have applied the NAM principles to two different application scenarios. First, we have defined a hybrid P2P/cloud approach where components and protocols are autonomically configured according to specific target goals, such as cost-effectiveness, reliability and availability. Merging P2P and cloud paradigms brings together the advantages of both: high availability, provided by the Cloud presence, and low cost, by exploiting inexpensive peers resources. As an example, we have shown how the proposed approach can be used to design NAM-based collaborative storage systems based on an autonomic policy to decide how to distribute data chunks among peers and Cloud, according to cost minimization and data availability goals. As a second application, we have defined an autonomic architecture for decentralized urban participatory sensing (UPS) which bridges sensor networks and mobile systems to improve effectiveness and efficiency. The developed application allows users to retrieve and publish different types of sensed information by using the features provided by NAM4J's context bus. Trust and reputation is managed through the application of DARTSense mechanisms. Also, the application includes an autonomic policy that detects areas characterized by few contributors, and tries to recruit new providers by migrating code necessary to sensing, through NAM mobility actions.

Optimizing rate algorithms in wireless networks

Since wireless network optimisations can be typically designed and evaluated independently of one another under the assumption that they can be applied jointly or independently. In this paper, we have analysis some rate algorithms in wireless networks. Since wireless networks have different standards in IEEE with peculiar features, data rate is one of those important parameters that wireless networks depend on for performances. The optimisation of this network is dependent on the behaviour of a particular rate algorithm in a network scenario. We have considered some first and second generation's rate algorithm, and it is all about selecting an appropriate data rate that any available wireless network can utilise for transmission in order to achieve a good performance. We have designed and analysis a wireless network and results obtained for some rate algorithms, like ONOE and AARF.

Pattern competition in volumetricaly heated fluids

Finite element simulations have been performed along side Galerkin-type calculations that examined the development of volumetrically heated flow patterns in a horizontal layer controlled by the Prandtl number, Pr, and the Grashof number, Gr. The fluid was bounded by an isothermal plane above an adiabatic plane. In the simulations performed here, a number of convective polygonal planforms occurred, as Gr increased above the critical Grashof number, Grc at Pr = 7, while roll structures were observed for Pr < 1 at 2Grc.

Quality Estimation of e-Learning Systems

Existing approaches to quality estimation of e-learning systems are analyzed. The “layered” approach for quality estimation of e-learning systems enhanced with learning process modeling and simulation is presented. The method of quality estimation using learning process modeling and quality criteria are suggested. The learning process model based on extended colored stochastic Petri net is described. The method has been implemented in the automated system of quality estimation of e-learning systems named “QuAdS”. Results of approbation of the developed method and quality criteria are shown. We argue that using learning process modeling for quality estimation simplifies identifying lacks of an e-learning system for an expert.

The construction and optimization of an ion mobility spectrometer for the analysis of explosives and drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs.^ In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug.^ Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). ^ The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.^

The Construction and Optimization on an Ion Mobility Spectrometer for the Analysis of Explosives and Drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs. In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug. Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.

Modelagem do consumo de energia de redes de sensores sem fio usando SystemC-AMS e stateflow

This work aims at modeling power consumption at the nodes of a Wireless Sensor Network (WSN). For doing so, a finite state machine was implemented by means of SystemC-AMS and Stateflow modeling and simulation tools. In order to achieve this goal, communication data in a WSN were collected. Based on the collected data, a simulation environment for power consumption characterization, which aimed at describing the network operation, was developed. Other than performing power consumption simulation, this environment also takes into account a discharging model as to analyze the battery charge level at any given moment. Such analysis result in a graph illustrating the battery voltage variations as well as its state of charge (SOC). Finally, a case study of the WSN power consumption aims to analyze the acquisition mode and network data communication. With this analysis, it is possible make adjustments in node-sensors to reduce the total power consumption of the network.

A Proposed Framework for Simulation Based Learning of Inheritance

Different types of serious games have been used in elucidating computer science areas such as computer games, mobile games, Lego-based games, virtual worlds and webbased games. Different evaluation techniques have been conducted like questionnaires, interviews, discussions and tests. Simulation have been widely used in computer science as a motivational and interactive learning tool. This paper aims to evaluate the possibility of successful implementation of simulation in computer programming modules. A framework is proposed to measure the impact of serious games on enhancing students understanding of key computer science concepts. Experiments will be held on the EEECS of Queen’s University Belfast students to test the framework and attain results.

Valoração do efluente da indústria processadora de pescado por incorporação de nutrientes em aphanothece microscopica nägeli

Nesta tese procurou-se demonstrar a valoração do efluente do processamento de pescado por incorporação dos nutrientes em Aphanothece microscopica Nägeli a diferentes temperaturas. Para tanto o trabalho é composto de cinco artigos que objetivaram avaliar sob o ponto de vista do tratamento do efluente pela cianobactéria Aphanothece e a separação e avaliação da biomassa gerada. O primeiro artigo intitula-se “Influência da temperatura na remoção de nutrientes do efluente da indústria de pescado por Aphanothece microscopica Nägeli”, e teve por objetivo avaliar a influência da temperatura (10, 20 e 30ºC) em um sistema de tratamento pela cianobactéria Aphanothece na remoção de matéria orgânica, nitrogênio e fósforo do efluente oriundo do processamento de pescado. A análise dos resultados mostrou que a temperatura influenciou significativamente na remoção de DQO, NTK, N-NH4 + e P-PO4 -3 . Para os experimentos a 20 e 30ºC todos os limites estabelecidos para os parâmetros avaliados foram atingidos. O segundo artigo intitulado “Efeito de coagulantes no efluente da indústria da pesca visando à separação de biomassa quando tratado por cianobactéria” avaliou o efeito da concentração e pH de dois tipos de coagulantes, cloreto férrico (FeCl3) e sulfato de alumínio (Al2(SO4)3), na separação da biomassa da cianobactéria Aphanothece microscopica Nägeli cultivada em efluente da indústria da pesca, assim como a remoção de matéria orgânica e nutrientes do efluente. Os resultados indicaram que o coagulante FeCl3 foi mais eficaz na remoção de todos os parâmetros testados. No que concerne à separação da biomassa, com um número de seis lavagens foi removido cerca de 97,6% da concentração de FeCl3 adicionado inicialmente. O terceiro artigo com o título “Caracterização da biomassa de Aphanothece microscopica Nägeli gerada no efluente da indústria da pesca em diferentes temperaturas de cultivo” avaliou a composição química da biomassa da cianobactéria Aphanothece microscopica Nägeli quando desenvolvida em meio de cultivo padrão BG11 e no efluente do processamento de pescado. O quarto artigo teve como título “Influência do meio de cultivo e temperatura em compostos nitrogenados na cianobactéria Aphanothece microscopica Nägeli” objetivou avaliar o teor de compostos nitrogenados presentes na biomassa da cianobactéria Aphanothece microscopica Nägeli quando cultivada em meio padrão e no efluente da indústria da pesca nas diferentes fases de crescimento. Para o estudo da composição química e nitrogenados no efluente foram realizados experimentos nas temperaturas de 10, 20 e 30ºC. As concentrações de proteína, cinzas e pigmentos aumentaram com o aumento da temperatura. Por outro lado, foi observada uma redução do teor de lipídios e carboidratos com o aumento da temperatura. O íon amônio juntamente com os ácidos nucléicos representa uma importante fração do nitrogênio não protéico presente na biomassa da cianobactéria Aphanothece. Ficou demonstrada a influência do meio de cultivo na concentração de nitrogênio, bem como a determinação de proteína pelo método de Kjeldahl superestima a concentração protéica em cianobactérias. O quinto artigo intitulado “Produção de proteína unicelular a partir do efluente do processamento do pescado: modelagem preditiva e simulação” avaliou a produção de proteína unicelular através do cultivo da cianobactéria Aphanothece microscopica Nägeli no efluente da indústria da pesca. Os dados cinéticos de crescimento celular foram ajustados a quatro modelos matemáticos (Logístico, Gompertz, Gompertz Modificado e Baranyi). Os resultados demonstraram que o modelo Logístico foi considerado o mais adequado para descrever a formação de biomassa. A análise preditiva mostrou a possibilidade da obtenção de 1,66, 18,96 e 57,36 kg.m-3.d-1 de biomassa por volume do reator em 1000 h de processo contínuo, para as temperaturas de 10, 20 e 30ºC, respectivamente.

Definition of Model-based diagnosis problems with Altarica

International audience

An algorithm for the inclusion of RC compact models of packages into board level thermal simulation tools

International audience

Using Intelligent Agents to Understand Management Practices and Retail Productivity

Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents could offer potential for fostering sustainable organizational capabilities in the future. The project is still at an early stage. So far we have conducted a case study in a UK department store to collect data and capture impressions about operations and actors within departments. Furthermore, based on our case study we have built and tested our first version of a retail branch simulator which we will present in this paper.