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It has been observed that the high-level abstraction obtained with ORSM has better generalization performance on unseen data as compared to other topic modeling schemes.
However, Wi-Fi requires very less energy to transfer the data as compared to cellular networks.
This technique requires less training data as compared to other techniques available in the literature.
The cooperative techniques create more delay and overhead while detecting malicious data as compared to local-based detection in VANETs.
Hence, fewer chunks are utilized to transmit data as compared to the number of chunks utilized for a higher AF.
The enabled-beacon MAC provides only dedicated slots to emergency and non-emergency data as compared to IEEE 802.15.4 MAC.
Also DCT requires relatively less number of coefficients to represent the signal/image data as compared to DFT.
Significant improvement in the match with experimental data, as compared to the constant property grain model, has been achieved.
This is caused by the granted time slot to lower modulated SSs that can only carry smaller amount of data as compared to high modulated SSs.
The simulation results revealed that proposed method can remove 93% of redundancy in the data as compared to non-cooperative methods.
Also using LRM, it was observed that ANN 4 and ANN 3 models give better fitness to predict data as compared to deterministic model.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com