Calculo numerico marcia ruggiero pdf

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Márcia Aparecida Gomes Ruggiero (IMECC-UNICAMP). Prof. Dr. Antonio Carlos Moretti Métodos numéricos em minimização com restrições I Elvio Angel. [PDF] V. Ruggiero free ebooks download , Márcia A. Gomes Ruggiero, Vera Lúcia da Rocha Lopes · Cálculo Numérico: Aspectos Teóricos e. O método de Jacobi é um algoritmo para resolver sistemas de equações lineares . Trata-se de .. Efetuando os cálculos com três casas decimais, determine a solução do . (ISIT), July; ↑ Cálculo numérico: aspectos teóricos e Ruggiero, Márcia A. Gomes e Lopes,Vera lúcia da Rocha.

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Cálculo Numérico, Aspectos Teóricos e Computacionais - 2 Edição - Márcia A. Gomes Ruggiero e Vera Lúcia da Rocha Uploaded by Heyder Araujo. Baixar Cálculo Numérico. Aspectos Teóricos e Computacionais Márcia A. Gomes Ruggiero pdf. Baixar Juizados Especiais da Fazenda Pública - Chimenti. [4] RUGGIERO, Márcia A. G., LOPES, Vera Lúcia R., Cálculo Numérico: Aspectos Teóricos e Computacionais, 2 a edição, Makron Books, São Paulo,

Barbara Arndt pdf Download Childhood Studies: They also cannot add new information to their Knowledge Base. Aprende los secretos y trucos utilizados por los mejores ciclistas profesionales y entrenadores, para mejorar tu acondicionamiento, nutricion y fortaleza Mental pdf download Joseph Correa Entrenador y Atleta Profesional Crise Do Socialismo E Movimento Operario pdf download Frederico Celso Das Leben Hannibals. Manuale completo per la prima prova scritta. Related Papers. Table 2 below describes the case tests.

Sensor and Actuator Agents are remote and replicable processes and, thus, it is required that a registry stores and strictly identifies each reference to an agent instance. Once a new Agent is created in the environment it has to be registered to be able to communicate. The Applications Manager joins external client applications that are related to the system. In order to prevent a failure the system has to analyze the behavior of the values of the sensors involved in a certain case.

This analysis is done in the log values that are generated by sensors history values of the environment. DBSitter uses the linear least squares1 [13] method with a grade two polynomial approximation in order to estimate the value of the sensors along time. Once this is done, it is possible to preview the behavior of the sensors. Once the system has them, it is possible to estimate a polynomial parameters and thus predict possible faults. Graph showing table fragmentation values along time.

This is guaranteed by the interaction of intelligent agents and sensor agents, as the role of intelligent agents is to monitor the various parameters as captured by the sensor agents disperse in the database environment. Expressions are built from those parameters, and they characterize the cases to be detected by the system.

The Failure Detector process then matches the current system state with the Similarity Identifier, as a way to assess the possibility of a system fault. Corresponds to the action taken by the actuator agent when a solution for a problem is found in the Case Repository.

Then the failure is corrected, or a message is sent to notify the DBA. Specialized users DBAs can feed the Case Repository, adding new cases manually when required or when they pass through an unknown and not catalogued problem.

Occurs when a DBA queries directly the Case Repository to search for information about a certain failure. This happens when a certain problem has more than one solution, and it comes with a degree of success for each case. The DBA then chooses the most adequate solution. Consists in the improvement of the Cases Repository when a new and unknown problem comes out.

The solution can be an adaptation of previously known solutions catalogued in the repository. For that purpose, we will use Decision Trees [12], which are simple to implement and generate new rule. These can, in turn, be used to implement new cases. In our prototype, only the functionalities of Prevention, Detection and Correction of failures were fully implemented.

The functionality of solution adaptation is partially implemented. Hence, Java was the chosen programming language. This language provides object orientation, useful for modularity and essential for extensibility, as we adopted the proposal of creating a framework for Database solution developers.

The virtual machine provided by Java brings about a multiplatform execution environment. For the case descriptions, we used the framework Jeops [Figueira Filho e Ramalho ], with the aim of employing the logic paradigm integrated to system objects. Through Jeops it is possible to define rules that determine the conditions that trigger events that indicate adverse situations in the database system.

The system reasons about both run time information and history data. The descriptions enable the AAs to act either directly in the system or to provide information for the DBA to take over. Target databases for the implementation of sensors and preliminary tests were Microsoft SqlServer and Oracle. A process call written in Object Pascal was used for the implementation of sensors. These processes are used for monitoring environment states for example, processor or memory states , as for direct database queries for analyzing database states.

The learning functionality, which is one of the differentials of this work, is still in implementation stages. In this example, we will consider that the problem described in Case 1, a table that has reached unacceptable fragmentation levels has just occurred. The process is launched when a Sensor Agent detects that a specific table has reached a critical fragmentation level. This is done through the event of fragmentation monitoring, witch is basically a cyclic SQL query to Oracle Data Dictionary looking for information of the table The Sensor then sends a message to the Environment Change Manager Agent, which in turn interacts with the Reasoning Agent.

The RA then searches Case Repository for a case that best conforms to the problem. When a similar case is found, the RA sends a message to the Coordinator, witch notifies the Actuator Agent of the solution to be automatically done, later sending a message to the DBA, stating that an action was taken to correct the problem. After the action from the Actuator Agent, the table is defragmented, and the Log Agent is triggered to record the action in the History.

This section describes the main results, together with the scenario of the experiments. Table 2 below describes the case tests. Table 3. A tablespace with IM datafile was created.

Then, a table with k extents was created. Tablespace After that, an allocation of 10 extents was Increase the datafile of the Oracle overflow.

Preventing Similar to the above, only that the actuator Increase the datafile of the Tablespace intervened before the amount of extents tablespace with free space near to Oracle overflow generated the error overflow. It is worth remarking that the last case was included in the tests in order to the prevention functionality.

The results obtained were promising, indicating that the solution works as predicted. Both problem resolution and solution performance were considered in this evaluation. The idea was not only to automate known solutions, but also to record novel approaches to problems.

Thus, this paper has presented a tool that combined two well-known AI techniques in a novel approach: We emphasize that among the main differentials of DBSitter relative to the Expert Systems for Database Administration is the fact it can be used in the monitoring of any Database and also as a combination of AI technologies, Case Based Reasoning and Intelligent Agents, making possible the implementation of characteristics of detection, problem prevention, learning and adaptation of solutions.

Furthermore, our prototype was implemented with open-source technologies, which makes it that much easier to be spread and refined by different developers. Another important contribution of this approach is the Case repository open to the DBA , that assists in the propagation of knowledge among DBAS, thus making their daily tasks easies and contributing to the enhancement of the level of service. From our point of view, this is another important advantage of our approach, as discussed earlier in the paper.

The platform was tested with two different databases Sql Server and Oracle 8i. This first evaluation has yielded promising results in both cases, which not only indicates that the approach is an interesting one, but also reinforces the portability of the prototype. The next steps of our research and development include enhancing the implementation of the learning functionality and adaptation of solutions.

It is worth remarking that we have already started this process, laying the necessary architectural foundations. References 1. Aamodt A. Case-Based Reasoning: AI Communications. IOS Press, Vol. Russel, s. Artificial Intelligence: A Modern Approach 2nd Edition.

Prentice Hall; 2nd edition. December, The Source for Java [Java ] Technology —http: Last Access: Figueira Filho, C. Monard, M. C; Sichman, J. S eds. Lecture Notes in Computer Science Springer , pp.

IBM Computer Associates International Hewlett-Packard Company Progress Software Corporation Quest Software Oracle Coorporation: Machine Learning, T. Mitchell, , McGraw-Hill. Makron Books, Related Papers. Il buio nella mente scarica. Angelus Silesius: Atlas global dnhfvua0y4kf. Volume 3. Gomes Ruggiero pdf.

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