Predicting future actions is a key in visual understanding, surveillance, and human behavior analysis. Current methods for video-based prediction are primarily using single-view data, while the real world multiple cameras produced videos readily available, which may potentially benefit action tasks. However, it bring up new challenge: subjects more likely to be occluded by objects when captured...

This work presents a detailed thermo-economic analysis of unit water costs from dual-purpose cogeneration plants. The power levelized cost was first calculated for stand-alone steam, nuclear, and combined-cycle energy needed to operate the desalination systems connected plants evaluated based on two different approaches: power- heat-allocated methods. Numerical models heat mass balances plants’...

An important amount of work exists on the topic of optimal operation and control of batch distillation though it is still based on the assumption of an accurate process model being available. While this assumption is valid from a theoretical point of view, there will always remain the challenge of practical applications. Reinforcement Learning (RL) has been recognised already as a particularly ...

Increasing global demand for fresh water is driving research and development of advanced desalination technologies. As a result, a detailed model of multiple e ect distillation (MED) is developed that is exible, simple to implement, and suitable for use in optimization of water and power cogeneration systems. The MED system is modeled in a modular method in which each of the subcomponents is mo...

Background: Thymus daenensis is on e of the endemic aromatic species in Iran that its essential oil is used in food and pharmaceutical industries. Objective: In this study, the effects of plant growth stages and distillation methods on essential oil content and thymol percentage of this species were evaluated. Methods: The aerial parts of Th. daenensis were collected in three stages of plan...

Abstract: This paper presents a contribution in multivariable predictive control. A new approach of multi-model based control is presented. The controller used is the quasilinear multivariable generalized predictive control (QMGPC). A metric based in 2-norm is presented in order to build a global model using local models. Simulation results in a distillation column, with a comparative analysis,...

Online knowledge distillation conducts transfer among all student models to alleviate the reliance on pre-trained models. However, existing online methods rely heavily prediction distributions and neglect further exploration of representational knowledge. In this paper, we propose a novel Multi-scale Feature Extraction Fusion method (MFEF) for distillation, which comprises three key components:...

The essential oils are frequently used in food processing industry, perfumery, cosmetics and pharmaceuticals. Most of the oils obtained by steam distillation and water distillation. It is necessary to specify the best conditions of essential oils production to get much more major compound(s) and higher yield oil. So, fennel oil was selected in this study. The objective of this work was to ident...

Multi-exit architectures, in which a sequence of intermediate classifiers are introduced at different depths the feature layers, perform adaptive computation by early exiting ``easy" samples to speed up inference. In this paper, novel Harmonized Dense Knowledge Distillation (HDKD) training method for multi-exit architecture is designed encourage each exit flexibly learn from all its later exits...

Solvents with an improved price/performance ratio allow for processes with less operating and/or capital expenditure. Therefore, from an industrial perspective, it is worth reviewing the R&D progress in designing new competitive solvents on a regular basis. This paper aims at discussing the potential of new solvent systems applicable as absorbents or entrainers for boosting the performance of a...