DICLADelay-Intensive Carry-Lookahead Adder
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A DICLA firstly is a CA in which a learning automaton is assigned to every cell.
The current value of n for a particular node determined by n = f(n) according to its current energy level and its neighbors using the principle of DICLA. Maximum and minimum thresholds of parameter n are also used to avoid the incomprehensible value.
* The dynamic mechanism is imported from LA to adjust the parameter n, and DICLA is used to characterize the mobility of nodes in the opportunistic networks.
However, diversification of energy consumption of nodes and their current neighbors are considered using the DICLA [18] method.
We use the DICLA model to illustrate dynamic topology of opportunistic networks.
The SD has the formal assignment of acting in accordance with the GLP principles, and must prioritize the scientific standard of the studies related to the quality/efficacy of the experimental design, evaluation and significance of the generated data (for more details on the DE responsibilities, see the section II of the NIT DICLA 035) (9).