Excitações elementares em super-redes quasiperiódicas com simetria espelho

In this thesis, we investigated the magnonic and photonic structures that exhibit the so-called deterministic disorder. Speci cally, we studied the effects of the quasiperiodicity, associated with an internal structural symmetry, called mirror symmetry, on the spectra of photonics and magnonics multilayer. The quasiperiodicity is introduced when stacked layers following the so-called substitutional sequences. The three sequences used here were the Fibonacci sequence, Thue-Morse and double-period, all with mirror symmetry. Aiming to study the propagation of light waves in multilayer photonic, and spin waves propagation in multilayer magnonic, we use a theoretical model based on transfer matrix treatment. For the propagation of light waves, we present numerical results that show that the quasiperiodicity associated with a mirror symmetry greatly increases the intensity of transmission and the transmission spectra exhibit a pro le self-similar. The return map plotted for this system show that the presence of internal symmetry does not alter the pattern of Fibonacci maps when compared with the case without symmetry. But when comparing the maps of Thue-Morse and double-time sequences with their case without the symmetry mirror, is evident the change in the pro le of the maps. For magnetic multilayers, we work with two di erent systems, multilayer composed of a metamagnetic material and a non-magnetic material, and multilayers composed of two cubic Heisenberg ferromagnets. In the rst case, our calculations are carried out in the magnetostatic regime and calculate the dispersion relation of spin waves for the metamgnetic material considered FeBr2. We show the e ect of mirror symmetry in the spectra of spin waves, and made the analysis of the location of bulk bands and the scaling laws between the full width of the bands allowed and the number of layers of unit cell. Finally, we calculate the transmission spectra of spin waves in quasiperiodic multilayers consisting of Heisenberg ferromagnets. The transmission spectra exhibit self-similar patterns, with regions of scaling well-de ned in frequency and the return maps indicates only dependence of the particular sequence used in the construction of the multilayer

ArchWiSeN: uma estratégia baseada em modelos para desenvolvimento de aplicações para redes de sensores e atuadores sem fio

Wireless Sensor and Actuator Networks (WSAN) are a key component in Ubiquitous Computing Systems and have many applications in different knowledge domains. Programming for such networks is very hard and requires developers to know the available sensor platforms specificities, increasing the learning curve for developing WSAN applications. In this work, an MDA (Model-Driven Architecture) approach for WSAN applications development called ArchWiSeN is proposed. The goal of such approach is to facilitate the development task by providing: (i) A WSAN domain-specific language, (ii) a methodology for WSAN application development; and (iii) an MDA infrastructure composed of several software artifacts (PIM, PSMs and transformations). ArchWiSeN allows the direct contribution of domain experts in the WSAN application development without the need of specialized knowledge on WSAN platforms and, at the same time, allows network experts to manage the application requirements without the need for specific knowledge of the application domain. Furthermore, this approach also aims to enable developers to express and validate functional and non-functional requirements of the application, incorporate services offered by WSAN middleware platforms and promote reuse of the developed software artifacts. In this sense, this Thesis proposes an approach that includes all WSAN development stages for current and emerging scenarios through the proposed MDA infrastructure. An evaluation of the proposal was performed by: (i) a proof of concept encompassing three different scenarios performed with the usage of the MDA infrastructure to describe the WSAN development process using the application engineering process, (ii) a controlled experiment to assess the use of the proposed approach compared to traditional method of WSAN application development, (iii) the analysis of ArchWiSeN support of middleware services to ensure that WSAN applications using such services can achieve their requirements ; and (iv) systematic analysis of ArchWiSeN in terms of desired characteristics for MDA tool when compared with other existing MDA tools for WSAN.

Distribuição de derivados de petróleo por redes de polidutos: uma abordagem através de algoritmos evolucionários híbridos para um problema triobjetivo

An important problem faced by the oil industry is to distribute multiple oil products through pipelines. Distribution is done in a network composed of refineries (source nodes), storage parks (intermediate nodes), and terminals (demand nodes) interconnected by a set of pipelines transporting oil and derivatives between adjacent areas. Constraints related to storage limits, delivery time, sources availability, sending and receiving limits, among others, must be satisfied. Some researchers deal with this problem under a discrete viewpoint in which the flow in the network is seen as batches sending. Usually, there is no separation device between batches of different products and the losses due to interfaces may be significant. Minimizing delivery time is a typical objective adopted by engineers when scheduling products sending in pipeline networks. However, costs incurred due to losses in interfaces cannot be disregarded. The cost also depends on pumping expenses, which are mostly due to the electricity cost. Since industrial electricity tariff varies over the day, pumping at different time periods have different cost. This work presents an experimental investigation of computational methods designed to deal with the problem of distributing oil derivatives in networks considering three minimization objectives simultaneously: delivery time, losses due to interfaces and electricity cost. The problem is NP-hard and is addressed with hybrid evolutionary algorithms. Hybridizations are mainly focused on Transgenetic Algorithms and classical multi-objective evolutionary algorithm architectures such as MOEA/D, NSGA2 and SPEA2. Three architectures named MOTA/D, NSTA and SPETA are applied to the problem. An experimental study compares the algorithms on thirty test cases. To analyse the results obtained with the algorithms Pareto-compliant quality indicators are used and the significance of the results evaluated with non-parametric statistical tests.

iSalud: uma arquitetura para publicação e distribuição de sistemas de informação para o SUS

The Brazil Telehealth Networks Program was established by the Ministry of Health in 2007. Its main objective is to support professionals in Primary Health Care (PHC) by offering educational qualification, resulting in more favorable conditions to fixate the professional in remote areas. The formulation and management of telehealth services are performed by scientific and technical centers that are operated by public institutions of higher education and responsible for providing tools and services in the context of the regions where they are. However, one of the problems generated by this decentralization is the development of various tools with different types of language, architecture and without any regulation and integration of information with the Ministry of Health. Aiming to solve the above problem, we propose the specification, implementation and validation of an architectural model in the development and distribution of the Unified Health System software tools. This proposed architecture enables tools developed in telehealth center to be shared among the other centers, thereby preventing the unnecessary use of resources.

Controle de mobilidade infraestruturado e orientado à qualidade para maximização de admissões em sistemas WiNeMO: uma abordagem definida por software

The spread of wireless networks and growing proliferation of mobile devices require the development of mobility control mechanisms to support the different demands of traffic in different network conditions. A major obstacle to developing this kind of technology is the complexity involved in handling all the information about the large number of Moving Objects (MO), as well as the entire signaling overhead required to manage these procedures in the network. Despite several initiatives have been proposed by the scientific community to address this issue they have not proved to be effective since they depend on the particular request of the MO that is responsible for triggering the mobility process. Moreover, they are often only guided by wireless medium statistics, such as Received Signal Strength Indicator (RSSI) of the candidate Point of Attachment (PoA). Thus, this work seeks to develop, evaluate and validate a sophisticated communication infrastructure for Wireless Networking for Moving Objects (WiNeMO) systems by making use of the flexibility provided by the Software-Defined Networking (SDN) paradigm, where network functions are easily and efficiently deployed by integrating OpenFlow and IEEE 802.21 standards. For purposes of benchmarking, the analysis was conducted in the control and data planes aspects, which demonstrate that the proposal significantly outperforms typical IPbased SDN and QoS-enabled capabilities, by allowing the network to handle the multimedia traffic with optimal Quality of Service (QoS) transport and acceptable Quality of Experience (QoE) over time.

Teleconsultoria Off-line: uma arquitetura distribuída e compartilhada para sistemas heterogêneos

The Telehealth Brazil Networks Program, created in 2007 with the aim of strengthening primary care and the unified health system (SUS - Sistema Único de Saúde), uses information and communication technologies for distance learning activities related to health. The use of technology enables the interaction between health professionals and / or their patients, furthering the ability of Family Health Teams (FHT). The program is grounded in law, which determines a number of technologies, protocols and processes which guide the work of Telehealth nucleus in the provision of services to the population. Among these services is teleconsulting, which is registered consultation and held between workers, professionals and managers of healthcare through bidirectional telecommunication instruments, in order to answer questions about clinical procedures, health actions and questions on the dossier of work. With the expansion of the program in 2011, was possible to detect problems and challenges that cover virtually all nucleus at different scales for each region. Among these problems can list the heterogeneity of platforms, especially teleconsulting, and low internet coverage in the municipalities, mainly in the interior cities of Brazil. From this perspective, the aim of this paper is to propose a distributed architecture, using mobile computing to enable the sending of teleconsultation. This architecture works offline, so that when internet connection data will be synchronized with the server. This data will travel on compressed to reduce the need for high transmission rates. Any Telehealth Nucleus can use this architecture, through an external service, which will be coupled through a communication interface.

Implementação de uma matriz de neurônios dinamicamente reconfigurável para descrição de topologias de redes neurais artificiais multilayer perceptrons

The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.

Implementação de uma matriz de neurônios dinamicamente reconfigurável para descrição de topologias de redes neurais artificiais multilayer perceptrons

The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.

Estratégias distribuídas para a coexistência de redes de banda larga sem fio em bandas não-licensiadas

The increasing demand for Internet data traffic in wireless broadband access networks requires both the development of efficient, novel wireless broadband access technologies and the allocation of new spectrum bands for that purpose. The introduction of a great number of small cells in cellular networks allied to the complimentary adoption of Wireless Local Area Network (WLAN) technologies in unlicensed spectrum is one of the most promising concepts to attend this demand. One alternative is the aggregation of Industrial, Science and Medical (ISM) unlicensed spectrum to licensed bands, using wireless networks defined by Institute of Electrical and Electronics Engineers (IEEE) and Third Generation Partnership Project (3GPP). While IEEE 802.11 (Wi-Fi) networks are aggregated to Long Term Evolution (LTE) small cells via LTE / WLAN Aggregation (LWA), in proposals like Unlicensed LTE (LTE-U) and LWA the LTE air interface itself is used for transmission on the unlicensed band. Wi-Fi technology is widespread and operates in the same 5 GHz ISM spectrum bands as the LTE proposals, which may bring performance decrease due to the coexistence of both technologies in the same spectrum bands. Besides, there is the need to improve Wi-Fi operation to support scenarios with a large number of neighbor Overlapping Basic Subscriber Set (OBSS) networks, with a large number of Wi-Fi nodes (i.e. dense deployments). It is long known that the overall Wi-Fi performance falls sharply with the increase of Wi-Fi nodes sharing the channel, therefore there is the need for introducing mechanisms to increase its spectral efficiency. This work is dedicated to the study of coexistence between different wireless broadband access systems operating in the same unlicensed spectrum bands, and how to solve the coexistence problems via distributed coordination mechanisms. The problem of coexistence between different networks (i.e. LTE and Wi-Fi) and the problem of coexistence between different networks of the same technology (i.e. multiple Wi-Fi OBSSs) is analyzed both qualitatively and quantitatively via system-level simulations, and the main issues to be faced are identified from these results. From that, distributed coordination mechanisms are proposed and evaluated via system-level simulations, both for the inter-technology coexistence problem and intra-technology coexistence problem. Results indicate that the proposed solutions provide significant gains when compare to the situation without distributed coordination.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model