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For this class of systems, we define a discrete Hamiltonian dynamics that exactly satisfies a discrete energy balance.
Finally, to support the development of dependable systems, we define for each system creation activity, a checklist that specifies the key issues that need to be addressed with respect to each dependability process.
To connect these equations with Dirac systems, we define the linear isomorphism by (3.4).
By considering the multicell system as a superposition of single-cell systems we define the average virtual BER of one single-cell system.
By treating the multicell system as a superposition of single cell systems we define the average virtual bit error rate (BER) of one single-cell system, allowing us to compute the power allocation in a distributed manner at each BS.
In order to estimate the movement phases based on these two characteristics that apply to different MRT systems, we define those two indicators of acceleration as M-Acc and V-Acc.
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Both theories, situated learning and CoP, can be seen as extensions of two factors of the activity systems we defined in this study: community and roles.
Due to the diversity of underlying principles, assumptions, and scoring systems, we defined the prediction agreement, i.e. the number of methods that agree on a certain miRNA target prediction, as a measure of confidence in the target prediction.
By introducing dwell time for the topology-varying system, we define the solutions for the closed-loop system equations.
For this system we define chain length n as the number of large (A type) particles in the aggregates, and the respective number of chains, Nn, is normalized as Xn = Nn/NA.
By using the control system, we define the house energy policy and improve the energy behavior with regard to a selected energy criterion, self-consumption.
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