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Simulating the Simulator: Deterministic PRAM Simulation on a Mesh Simulator.
1995The Parallel Random Access Machine, \de{PRAM}, is the dominant theoretical parallel computer model. It consists of a number ofprocessing units, \de{PU}s, which operate synchronously, and which can access a shared memory in constant time. Unfortunately, this high-level model is hardly realizable in hardware using current technology.
Meyer, U., Sibeyn, J.
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Proceedings of the 27th conference on Winter simulation - WSC '95, 1993
This tutorial describes computer languages and other software packages that support discrete-event simulation.
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This tutorial describes computer languages and other software packages that support discrete-event simulation.
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Virtual Technologies in Medicine
The article presents an analysis of the effectiveness of work and defects in the organization of "simulation rooms" at medical institutions in Khabarovsk and the Khabarovsk Territory.
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The article presents an analysis of the effectiveness of work and defects in the organization of "simulation rooms" at medical institutions in Khabarovsk and the Khabarovsk Territory.
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Simulations of Simulations in Evolutionary Robotics
2007In recent years simulation tools for agent-environment interactions have included increasingly complex and physically realistic conditions. These simulations pose challenges for researchers interested in evolutionary robotics because the computational expense of running multiple evaluations can be very high.
Edgar Bermudez Contreras, Anil K. Seth
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1995
We present a simulation for endoscopic procedures. The anatomy of the patient is represented by 3D polyhedral models, computed from tomographic images. The simulation program can be used as a training system, or for prior simulation of complicated individual cases to reduce the error rate and to decide on the feasibility of biopsies.
Bernhard Geiger, Ron Kikinis
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We present a simulation for endoscopic procedures. The anatomy of the patient is represented by 3D polyhedral models, computed from tomographic images. The simulation program can be used as a training system, or for prior simulation of complicated individual cases to reduce the error rate and to decide on the feasibility of biopsies.
Bernhard Geiger, Ron Kikinis
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Fundamenta Informaticae, 2014
Opacity testing is formalized and studied. We specify opacity testers as well as tested systems by (timed) process algebras. We model various testers according to how sophisticated observations of tested system they can make and which kind of conclusions they can obtain. We use this technique to define several realistic security properties.
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Opacity testing is formalized and studied. We specify opacity testers as well as tested systems by (timed) process algebras. We model various testers according to how sophisticated observations of tested system they can make and which kind of conclusions they can obtain. We use this technique to define several realistic security properties.
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Artificial Intelligence, 1986
Qualitative simulation is a key inference process in qualitative causal reasoning. However, the precise meaning of the different proposals and their relation with differential equations is often unclear. In this paper, we present a precise definition of qualitative structure and behavior descriptions as abstractions of differential equations and ...
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Qualitative simulation is a key inference process in qualitative causal reasoning. However, the precise meaning of the different proposals and their relation with differential equations is often unclear. In this paper, we present a precise definition of qualitative structure and behavior descriptions as abstractions of differential equations and ...
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American Journal of Mathematical and Management Sciences, 1988
SYNOPTIC ABSTRACTThe principal shortcoming of simulated annealing (SA) is that it takes too much computer time. We present a few “swindling” ideas for speeding up SA by simulating its action on a problem. The increase in speed is attained at the cost of decreasing generality — the methods all require the use of problem-specific information.
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SYNOPTIC ABSTRACTThe principal shortcoming of simulated annealing (SA) is that it takes too much computer time. We present a few “swindling” ideas for speeding up SA by simulating its action on a problem. The increase in speed is attained at the cost of decreasing generality — the methods all require the use of problem-specific information.
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