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We confirm this by running simulations with the standard TDDM formulation and show that the simplified formulation approximates well the full model under steady-state conditions.
The preceding two case studies highlight the value of leveraging ICT to allow for many different learning opportunities to be created in a short period of time by running simulations with varying inputs.
By simulating authentic learning opportunities, this research aims to demonstrate the value of using ICT to create a tool to allow for many different learning opportunities to be experienced in a short period of time by running simulations with varying inputs.
We also explore the effects of the magnitude of fixed maturation parameters on inheritance of growth, and vice versa, by running simulations with M1– M18 set at 300 or 500 mm and X1– X12 set at 0.3 or 0.7.
We assessed the sensitivity of the results to this assumed mixing pattern by running simulations with a well-mixed population (no difference between within-group and between-group mixing) and a population with highly assortative mixing (between-group mixing rate that was 25% of the within-group mixing rate) (Web Figures 4 and 5).
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In order to find the maximum throughput gain possible by using channel borrowing, we ran simulations with Matlab's linear program solver: one set with a single channel (no borrowing) to simulate standard 802.11, and a second set with two channels and relay nodes to simulate BCR.
To model this, we run simulations with different fractions of mesenchyme covered by mesothelium.
We also ran simulations with ancestral ranges of double these sizes (because the simulations start by dividing the ancestral range in two).
Most of the NFC simulators today work by running the simulation with a user-defined set of facility build orders and preferences.
The time scale in the model was calibrated by running a simulation with only uninfected cells and determining the doubling time.
ExOR simply selects the set of forwarders by running a simulation with the full set of candidates and select those nodes that forward at least 10% of the packets.
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by running searches with
by conducting simulations with
by performing simulations with
by running tasks with
by benchmarking simulations with
by running reactions with
by running services with
by running ads with
by repeating simulations with
by fitting simulations with
by comparing simulations with
by running trains with
by running samples with
by running analyses with
by running tools with
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