Análise computacional de imagens de lâminas delgadas na predição dos parâmetros hidráulicos porosidade e condutividade hidráulica do aquífero Barreiras-RN

The understanding of the occurrence and flow of groundwater in the subsurface is of fundamental importance in the exploitation of water, just like knowledge of all associated hydrogeological context. These factors are primarily controlled by geometry of a certain pore system, given the nature of sedimentary aquifers. Thus, the microstructural characterization, as the interconnectivity of the system, it is essential to know the macro properties porosity and permeability of reservoir rock, in which can be done on a statistical characterization by twodimensional analysis. The latter is being held on a computing platform, using image thin sections of reservoir rock, allowing the prediction of the properties effective porosity and hydraulic conductivity. For Barreiras Aquifer to obtain such parameters derived primarily from the interpretation of tests of aquifers, a practice that usually involves a fairly complex logistics in terms of equipment and personnel required in addition to high cost of operation. Thus, the analysis and digital image processing is presented as an alternative tool for the characterization of hydraulic parameters, showing up as a practical and inexpensive method. This methodology is based on a flowchart work involving sampling, preparation of thin sections and their respective images, segmentation and geometric characterization, three-dimensional reconstruction and flow simulation. In this research, computational image analysis of thin sections of rocks has shown that aquifer storage coefficients ranging from 0,035 to 0,12 with an average of 0,076, while its hydrogeological substrate (associated with the top of the carbonate sequence outcropping not region) presents effective porosities of the order of 2%. For the transport regime, it is evidenced that the methodology presents results below of those found in the bibliographic data relating to hydraulic conductivity, mean values of 1,04 x10-6 m/s, with fluctuations between 2,94 x10-6 m/s and 3,61x10-8 m/s, probably due to the larger scale study and the heterogeneity of the medium studied.

Aplicação do método de análise hierárquica na tomada de decisão para adoção de computação em nuvem: um estudo de caso na federação das indústrias do RN

The progresses of the Internet and telecommunications have been changing the concepts of Information Technology IT, especially with regard to outsourcing services, where organizations seek cost-cutting and a better focus on the business. Along with the development of that outsourcing, a new model named Cloud Computing (CC) evolved. It proposes to migrate to the Internet both data processing and information storing. Among the key points of Cloud Computing are included cost-cutting, benefits, risks and the IT paradigms changes. Nonetheless, the adoption of that model brings forth some difficulties to decision-making, by IT managers, mainly with regard to which solutions may go to the cloud, and which service providers are more appropriate to the Organization s reality. The research has as its overall aim to apply the AHP Method (Analytic Hierarchic Process) to decision-making in Cloud Computing. There to, the utilized methodology was the exploratory kind and a study of case applied to a nationwide organization (Federation of Industries of RN). The data collection was performed through two structured questionnaires answered electronically by IT technicians, and the company s Board of Directors. The analysis of the data was carried out in a qualitative and comparative way, and we utilized the software to AHP method called Web-Hipre. The results we obtained found the importance of applying the AHP method in decision-making towards the adoption of Cloud Computing, mainly because on the occasion the research was carried out the studied company already showed interest and necessity in adopting CC, considering the internal problems with infrastructure and availability of information that the company faces nowadays. The organization sought to adopt CC, however, it had doubt regarding the cloud model and which service provider would better meet their real necessities. The application of the AHP, then, worked as a guiding tool to the choice of the best alternative, which points out the Hybrid Cloud as the ideal choice to start off in Cloud Computing. Considering the following aspects: the layer of Infrastructure as a Service IaaS (Processing and Storage) must stay partly on the Public Cloud and partly in the Private Cloud; the layer of Platform as a Service PaaS (Software Developing and Testing) had preference for the Private Cloud, and the layer of Software as a Service - SaaS (Emails/Applications) divided into emails to the Public Cloud and applications to the Private Cloud. The research also identified the important factors to hiring a Cloud Computing provider

Agentes Inteligentes com Foco de Atenção Afetivo em Simulações Baseadas em Agentes

Simulations based on cognitively rich agents can become a very intensive computing task, especially when the simulated environment represents a complex system. This situation becomes worse when time constraints are present. This kind of simulations would benefit from a mechanism that improves the way agents perceive and react to changes in these types of environments. In other worlds, an approach to improve the efficiency (performance and accuracy) in the decision process of autonomous agents in a simulation would be useful. In complex environments, and full of variables, it is possible that not every information available to the agent is necessary for its decision-making process, depending indeed, on the task being performed. Then, the agent would need to filter the coming perceptions in the same as we do with our attentions focus. By using a focus of attention, only the information that really matters to the agent running context are perceived (cognitively processed), which can improve the decision making process. The architecture proposed herein presents a structure for cognitive agents divided into two parts: 1) the main part contains the reasoning / planning process, knowledge and affective state of the agent, and 2) a set of behaviors that are triggered by planning in order to achieve the agent s goals. Each of these behaviors has a runtime dynamically adjustable focus of attention, adjusted according to the variation of the agent s affective state. The focus of each behavior is divided into a qualitative focus, which is responsible for the quality of the perceived data, and a quantitative focus, which is responsible for the quantity of the perceived data. Thus, the behavior will be able to filter the information sent by the agent sensors, and build a list of perceived elements containing only the information necessary to the agent, according to the context of the behavior that is currently running. Based on the human attention focus, the agent is also dotted of a affective state. The agent s affective state is based on theories of human emotion, mood and personality. This model serves as a basis for the mechanism of continuous adjustment of the agent s attention focus, both the qualitative and the quantative focus. With this mechanism, the agent can adjust its focus of attention during the execution of the behavior, in order to become more efficient in the face of environmental changes. The proposed architecture can be used in a very flexibly way. The focus of attention can work in a fixed way (neither the qualitative focus nor the quantitaive focus one changes), as well as using different combinations for the qualitative and quantitative foci variation. The architecture was built on a platform for BDI agents, but its design allows it to be used in any other type of agents, since the implementation is made only in the perception level layer of the agent. In order to evaluate the contribution proposed in this work, an extensive series of experiments were conducted on an agent-based simulation over a fire-growing scenario. In the simulations, the agents using the architecture proposed in this work are compared with similar agents (with the same reasoning model), but able to process all the information sent by the environment. Intuitively, it is expected that the omniscient agent would be more efficient, since they can handle all the possible option before taking a decision. However, the experiments showed that attention-focus based agents can be as efficient as the omniscient ones, with the advantage of being able to solve the same problems in a significantly reduced time. Thus, the experiments indicate the efficiency of the proposed architecture

Contribuição para o estudo do embarque de uma rede neural artificial em field programmable gate array (FPGA)

This study shows the implementation and the embedding of an Artificial Neural Network (ANN) in hardware, or in a programmable device, as a field programmable gate array (FPGA). This work allowed the exploration of different implementations, described in VHDL, of multilayer perceptrons ANN. Due to the parallelism inherent to ANNs, there are disadvantages in software implementations due to the sequential nature of the Von Neumann architectures. As an alternative to this problem, there is a hardware implementation that allows to exploit all the parallelism implicit in this model. Currently, there is an increase in use of FPGAs as a platform to implement neural networks in hardware, exploiting the high processing power, low cost, ease of programming and ability to reconfigure the circuit, allowing the network to adapt to different applications. Given this context, the aim is to develop arrays of neural networks in hardware, a flexible architecture, in which it is possible to add or remove neurons, and mainly, modify the network topology, in order to enable a modular network of fixed-point arithmetic in a FPGA. Five synthesis of VHDL descriptions were produced: two for the neuron with one or two entrances, and three different architectures of ANN. The descriptions of the used architectures became very modular, easily allowing the increase or decrease of the number of neurons. As a result, some complete neural networks were implemented in FPGA, in fixed-point arithmetic, with a high-capacity parallel processing

Uma plataforma de integração de middleware para computação ubíqua

One of the current challenges of Ubiquitous Computing is the development of complex applications, those are more than simple alarms triggered by sensors or simple systems to configure the environment according to user preferences. Those applications are hard to develop since they are composed by services provided by different middleware and it is needed to know the peculiarities of each of them, mainly the communication and context models. This thesis presents OpenCOPI, a platform which integrates various services providers, including context provision middleware. It provides an unified ontology-based context model, as well as an environment that enable easy development of ubiquitous applications via the definition of semantic workflows that contains the abstract description of the application. Those semantic workflows are converted into concrete workflows, called execution plans. An execution plan consists of a workflow instance containing activities that are automated by a set of Web services. OpenCOPI supports the automatic Web service selection and composition, enabling the use of services provided by distinct middleware in an independent and transparent way. Moreover, this platform also supports execution adaptation in case of service failures, user mobility and degradation of services quality. The validation of OpenCOPI is performed through the development of case studies, specifically applications of the oil industry. In addition, this work evaluates the overhead introduced by OpenCOPI and compares it with the provided benefits, and the efficiency of OpenCOPI s selection and adaptation mechanism

Cloud Integrator: uma plataforma para composição de serviços em ambientes de computação em nuvem

With the advance of the Cloud Computing paradigm, a single service offered by a cloud platform may not be enough to meet all the application requirements. To fulfill such requirements, it may be necessary, instead of a single service, a composition of services that aggregates services provided by different cloud platforms. In order to generate aggregated value for the user, this composition of services provided by several Cloud Computing platforms requires a solution in terms of platforms integration, which encompasses the manipulation of a wide number of noninteroperable APIs and protocols from different platform vendors. In this scenario, this work presents Cloud Integrator, a middleware platform for composing services provided by different Cloud Computing platforms. Besides providing an environment that facilitates the development and execution of applications that use such services, Cloud Integrator works as a mediator by providing mechanisms for building applications through composition and selection of semantic Web services that take into account metadata about the services, such as QoS (Quality of Service), prices, etc. Moreover, the proposed middleware platform provides an adaptation mechanism that can be triggered in case of failure or quality degradation of one or more services used by the running application in order to ensure its quality and availability. In this work, through a case study that consists of an application that use services provided by different cloud platforms, Cloud Integrator is evaluated in terms of the efficiency of the performed service composition, selection and adaptation processes, as well as the potential of using this middleware in heterogeneous computational clouds scenarios