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In this study, we report an easy and quick method on simulating chromosome breaks in cells exposed to heavy charged particles.
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Section 4.2.1 describes the development experiment, while Section 4.2.2 evaluates our proposed method on simulated data.
By testing the method on simulated datasets we can understand its performance features and liabilities.
They show the performance of their method on simulated data and provide a complete analysis on single unit activity recorded on a monkey during a sensory motor task.
We evaluated the method on simulated and in vivo human brain data, comparing the results with the traditional single-tensor and with a probabilistic tractography technique.
This paper presents the first experimental results obtained by applying the proposed method on simulated signals in different environments in order to evaluate its performances and application range.
We compare the performance of our method on simulated data against random pairings, and against a system that is currently in use in tournament chess.
Test sets A and B were used to evaluate the proposed method on simulated reverberant environments, while test set D was used to evaluate the proposed method on real reverberant environments.
We evaluate our method on simulated, offline EMG signals, which are supposed to be generated from a relatively small number of motor units (MU's) with various muscle contraction levels and pathological characteristics.
We tested this method on simulated as well as experimental datasets.
We tested the method on simulated data then treated data from myosin cross-bridges in permeabilized muscle fibers to deduce single myosin lever arm exchanged RLC tagged PA-GFP orientation in rigor.
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