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More Mathematics into Medicine!
More Mathematics into Medicine!

... which allowed for an essential speed-up in time and accuracy of the measurement process. This led to completely new scanning geometries and thus to new challenges in mathematics. The originally introduced parallel geometry, where one path was measured at a time instance, was replaced by fan-beam geo ...
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UNIVERSITY OF GREENWICH MAW Mike Sharp, HOD the

Technical Problem Solving 2015 regional v2 key
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A simple mathematical model for Batesian mimicry

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Why a computer is known as data processor

Investigation and Numerical Resolution of Some
Investigation and Numerical Resolution of Some

... In mathematical modeling of many natural phenomena and processes can be described by the initial-boundary value problems posed for parabolic differential and integrodifferential models. Most of these problems are nonlinear and multi-dimensional. These moments significantly complicate investigation o ...
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Evolutionary decision games in complex biological interactions at

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广东海洋大学教师论文被 SCI-Expanded 收录情况统计
广东海洋大学教师论文被 SCI-Expanded 收录情况统计

... Publisher: Institute of Electrical and Electronics Engineers Inc. Abstract: With the development of Internet, we put forward high requests for information retrieval. First, efficiency; second, personalizing. In this paper a model and an algorithm are proposed which are according to the user's retrie ...
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Summary and purpose of document

what can we learn about fundamental physics?
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Investigating shape representation in human visual cortex

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Kirkpatrick_Boulder2016--mxGREML

... vector y is a single draw from a multivariatenormal distribution having (in general) dense covariance matrix, V. 2. The parameters of V are of primary interest. 3. Random effects are normally distributed. 4. GLS regression (using V-1) is adequate model for phenotypic mean. ...
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retreat - people.csail.mit.edu

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PPT - 서울대 Biointelligence lab

...  To perform stimulus decoding using the model-based likelihood function.  One can obtain the most likely stimulus to have generated the response y by maximizing the posterior for x, which gives the maximum a posteriori estimate of the stimulus  With mean-squared error, this estimator is given by ...
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Computer simulation



A computer simulation is a simulation, run on a single computer, or a network of computers, to reproduce behavior of a system. The simulation uses an abstract model (a computer model, or a computational model) to simulate the system. Computer simulations have become a useful part of mathematical modeling of many natural systems in physics (computational physics), astrophysics, climatology, chemistry and biology, human systems in economics, psychology, social science, and engineering. Simulation of a system is represented as the running of the system's model. It can be used to explore and gain new insights into new technology and to estimate the performance of systems too complex for analytical solutions.Computer simulations vary from computer programs that run a few minutes to network-based groups of computers running for hours to ongoing simulations that run for days. The scale of events being simulated by computer simulations has far exceeded anything possible (or perhaps even imaginable) using traditional paper-and-pencil mathematical modeling. Over 10 years ago, a desert-battle simulation of one force invading another involved the modeling of 66,239 tanks, trucks and other vehicles on simulated terrain around Kuwait, using multiple supercomputers in the DoD High Performance Computer Modernization ProgramOther examples include a 1-billion-atom model of material deformation; a 2.64-million-atom model of the complex maker of protein in all organisms, a ribosome, in 2005;a complete simulation of the life cycle of Mycoplasma genitalium in 2012; and the Blue Brain project at EPFL (Switzerland), begun in May 2005 to create the first computer simulation of the entire human brain, right down to the molecular level.Because of the computational cost of simulation, computer experiments are used to perform inference such as uncertainty quantification.
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