12,601 research outputs found

    An agent-based framework for petroleum information services from distributed heterogeneous data resources

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    For making good decisions in the area of petroleum production, it is becoming a big problem how to timely gather sufficient and correct information, which may be stored in databases, data files, or on the World Wide Web. In this paper, Gaia methodology and Open Agent Architecture were employed to contribute a framework to solve above problem. The framework consists of three levels, namely, role mode, agent type, and agent instance. The model with five roles is analyzed. Four agent types are designed Six agent instances are developed for constructing the system of petroleum information services. The experimental results show that all agents in the system can work cooperatively to organize and retrieve relevant petroleum information. The successful implementation of the framework shows that agent-based technology can significantly facilitate the construction of complex systems in distributed heterogeneous data resource environment.<br /

    A Platform to Integrate well-log Information Application on heterogeneous Environments

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    Distributed data mining in grid computing environments

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    The official published version of this article can be found at the link below.The computing-intensive data mining for inherently Internet-wide distributed data, referred to as Distributed Data Mining (DDM), calls for the support of a powerful Grid with an effective scheduling framework. DDM often shares the computing paradigm of local processing and global synthesizing. It involves every phase of Data Mining (DM) processes, which makes the workflow of DDM very complex and can be modelled only by a Directed Acyclic Graph (DAG) with multiple data entries. Motivated by the need for a practical solution of the Grid scheduling problem for the DDM workflow, this paper proposes a novel two-phase scheduling framework, including External Scheduling and Internal Scheduling, on a two-level Grid architecture (InterGrid, IntraGrid). Currently a DM IntraGrid, named DMGCE (Data Mining Grid Computing Environment), has been developed with a dynamic scheduling framework for competitive DAGs in a heterogeneous computing environment. This system is implemented in an established Multi-Agent System (MAS) environment, in which the reuse of existing DM algorithms is achieved by encapsulating them into agents. Practical classification problems from oil well logging analysis are used to measure the system performance. The detailed experiment procedure and result analysis are also discussed in this paper

    An agent-based intelligent system for information gathering from world wide web environment

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    To use the vast amount of information efficiently and effectively from Web sites is very important for making informed decisions. There are, however, still many problems that need to be overcome in the information gathering research arena to enable the delivery of relevant information required by users. In this paper, an information gathering system is develop by means of multiple agents to solve those problems. We employed some ideas of Gaia\u27s methodology and an open agent architecture to analyze and design the system. The system consists of a query preprocessing agent, information retrieval agent, information filtering agent, and information management agent. The filtering agent is trained with categorized documents and can provide users with the necessary information. The experimental results show that all agents in the system can work cooperatively to retrieve relevant information from the World Wide Web environment. <br /

    Towards Loosely-Coupled Programming on Petascale Systems

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    We have extended the Falkon lightweight task execution framework to make loosely coupled programming on petascale systems a practical and useful programming model. This work studies and measures the performance factors involved in applying this approach to enable the use of petascale systems by a broader user community, and with greater ease. Our work enables the execution of highly parallel computations composed of loosely coupled serial jobs with no modifications to the respective applications. This approach allows a new-and potentially far larger-class of applications to leverage petascale systems, such as the IBM Blue Gene/P supercomputer. We present the challenges of I/O performance encountered in making this model practical, and show results using both microbenchmarks and real applications from two domains: economic energy modeling and molecular dynamics. Our benchmarks show that we can scale up to 160K processor-cores with high efficiency, and can achieve sustained execution rates of thousands of tasks per second.Comment: IEEE/ACM International Conference for High Performance Computing, Networking, Storage and Analysis (SuperComputing/SC) 200

    Economy-wide and distributional impacts of an oil price shock on the south African economy

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    As crude oil prices reach new highs, there is renewed concern about how external shocks will affect growth and poverty in developing countries. This paper describes a macro-micro framework for examining the structural and distributional consequences of a significant external shock-an increase in the world price of oil-on the South African economy. The authors merge results from a highly disaggregative computable general equilibrium model and a micro-simulation analysis of earnings and occupational choice based on socio-demographic characteristics of the household. The model provides changes in employment, wages, and prices that are used in the micro-simulation. The analysis finds that a 125 percent increase in the price of crude oil and refined petroleum reduces employment and GDP by approximately 2 percent, and reduces household consumption by approximately 7 percent. The oil price shock tends to increase the disparity between rich and poor. The adverse impact of the oil price shock is felt by the poorer segment of the formal labor market in the form of declining wages and increased unemployment. Unemployment hits mostly low and medium-skilled workers in the services sector. High-skilled households, on average, gain from the oil price shock. Their income rises and their spending basket is less skewed toward food and other goods that are most affected by changes in oil prices.Economic Theory&Research,,Labor Policies,Markets and Market Access,Access to Finance
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