Neural architecture search (NAS) targets at finding the optimal of a neural network for problem or family problems. Evaluations architectures are very time-consuming. One possible ways to mitigate this issue is use low-fidelity evaluations, namely training on part dataset, fewer epochs, with channels, etc. In paper, we propose Bayesian multi-fidelity method search: MF-KD. The relies new approac...

Recent studies have recently exploited knowledge distillation (KD) technique to address time-consuming annotation task in semantic segmentation, through which one teacher trained on a single dataset could be leveraged for annotating unlabeled data. However, this context, capacity is restricted, and variety rare different conditions, such as cross-model KD, the KD prohibits student model from di...

Abstract Although the classification method based on deep neural network has achieved excellent results in tasks, it is difficult to apply real-time scenarios because of high memory footprints and prohibitive inference times. Compared unstructured pruning, structured pruning techniques can reduce computation cost model runtime more effectively, but inevitably reduces precision model. Traditiona...

The paper considers the effect of feed plate location on the interactions in a seven plate binary distillation column. The mathematical model of the distillation column is deduced based on the equations of mass and energy balances for each stage, detailed model for both reboiler and condenser, and heat transfer equations. The Dynamic Relative Magnitude Criterion, DRMC is used to assess the inte...

This study aimed to develop a new processing method for the effective use of rice shochu distillation remnants. We examined the inhibitory effects on the growth of human lung carcinoma cells in the medium of rice shochu distillation remnants with various fungi. Interestingly, high inhibitory effects on the growth of human lung carcinoma cells in the medium of rice shochu distillation remnants w...

One of the long-standing challenges in Artificial Intelligence for goal-directed behavior is to build a single agent which can solve multiple tasks. Recent progress in multi-task learning for learning behavior in many goal-directed sequential tasks has been in the form of distillation based learning wherein a single student network learns from multiple task-specific teacher networks by mimickin...

the simulation of distillation columns is an essential step in design, optimization, and rating. in this paper, a new procedure has been proposed for the initial estimation of column profiles based on modified kremser’s group method for simple and/or complex columns. the effect of this initialization algorithm on simulation procedure has been studied through two examples. the results show signi...

The paper considers the effect of feed plate location on the interactions in a seven plate binary distillation column. The mathematical model of the distillation column is deduced based on the equations of mass and energy balances for each stage, detailed model for both reboiler and condenser, and heat transfer equations. The Dynamic Relative Magnitude Criterion, DRMC is used to assess the inte...

Extractive distillation is an alternative for ethanol dehydration processes that has been shown to be more effective than azeotropic distillation and, in close proximity, to be very competitive against the process that uses adsorption with molecular sieves. Glycols have been shown to be the most effective solvents in extractive distillation, mainly ethylene glycol and glycerol. In this work, an...