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In this paper we describe theAgent Distributed Shared Memory Interface (ADSMI), an interface between a generalMAS description and the PDES-MAS platform as an implementation of a DistributedShared Memory (DSM) system for distributed MAS simulations.

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We will highlight the latest capabilities of Plant Simulation and show how it can optimize material flow, resource utilization, throughput and logistics at all levels of the global planning process.

Minsuk Sebastian Ko (Sanhakwon-Ajou University)

Avesani, Third IEEE Conference on Data Mining, 2003.

Rob Patterson has over 24 years of experience in source air emissions and ambient air testing, especially with the EPA and Texas Air Control Board methods of analysis. He is experienced in sampling Method 0010, Modified Method 5 Sampling Train; Method 0030, Volatile Organic Sampling Train; and various EPA and "Site Specific" acid gas and multiple metals sampling trains, including Ontario Hydro and EPA Methods 324 and 30B for Mercury.

Martin, Third International Conference on Data Mining (DMIN-07),66-72.

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Our team performed network and application data captures of the system for a local user in a development environment, then used the OPNET suite of tools and Shunra's WAN emulation appliance to simulate the performance improvement for the remote users.

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The model is built over the cad drawings of the suite, which include the different service areas and their associated fixed resources (rooms, recovery beds, dressing rooms, etc.).

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We want to ensure that generated models have the appropriate hooks and mechanisms for supporting automatic validation and adaptation based on data observed from the real system.

Francisco Ramis (Universidad de Bio-Bio, Chile) and Jose Sepulveda (University of Central Florida)

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The methodology further involves the generation of dynamic behavior, support of cyclic approaches and continuous improvement of the quality of the generated simulation model quality based on current data obtained from the real system.

Greenfield, L. (2005). The Case against Data Warehousing . Retrieved from

This detailed data is required for the performance of simulation.

As a result of this data-driven simulation, companies/organizations are able to reap the benefits of reducing future development time, utilizing the model for other similar systems, achieve quick turn-around, and the ability to perform large scale sensitivity analysis.

Adam MacKenzie, J.O.

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The analysis is performed using data from a large U.S.

This was a great introduction to Programming in R. I feel like I have some basic concepts down and I am looking forward to taking more courses to keep developing my skills in this programming language. I can definitely see the potential for data analysis in my work!

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This allows for effectively exploring different clusters and data values as well as to identify interesting data and trends.

Jim Chilcott, Matthew Mildred and Silvia Hummel (University of Sheffield)