BACKGROUND Type 2 diabetes is one of the most common diseases with devastating complications. However, genetic susceptibility of diabetic complications has not been clarified. The vitamin D endocrine system is related with calcification and lipolysis, insulin secretion, and may be associated with many complicated disease including diabetes and cardiovascular disease. Recent studies reported tha...

The treatment of wastewater is a complicated biological reaction process. Reliable effluent prediction critical in the scientific management water plants. This research proposes soft sensor design strategy to address issues above, Multi-Verse Optimizer (MVO)-based random vector functional link network (MVO-RVFL). proposed approach utilized anticipate real-time data obtained from Benchmark Simul...

The purpose of this work is to identify a linear time-invariant dynamic model of wastewater treatment plants with multilevel pseudo random signals as an excitation input. The plants naturally aim to remove suspended substances, organic material and phosphate. An activated sludge process becomes the best technology available to control the discharge of pollutants. For this purpose, state-space m...

Over a decade ago, the concept of a tool that could be used to objectively evaluate the performance of control strategies through simulation using a standard model implementation was introduced for activated sludge wastewater treatment plants. That concept resulted in the development of the Benchmark Simulation Model No 1 (BSM1), the subsequent BSM1_LT and most recently BSM2. Debate about the n...

The implementation of wireless sensor networks (WSNs) for wastewater treatment plant monitoring and control is rare in the literature. Nevertheless, there seem to be some good reasons for considering this application, since WSNs can easily supply several point measurements and keep track on a single variable over a wide area. This report describes a merged simulator, which is a fusion between a...

The objective of this paper is to perform an uncertainty and sensitivity analysis of the predictions of the Benchmark Simulation Model (BSM) No. 1, when comparing four activated sludge control strategies. The Monte Carlo simulation technique is used to evaluate the uncertainty in the BSM1 predictions, considering the ASM1 bio-kinetic parameters and influent fractions as input uncertainties whil...

Abstract To solve the problem of high-energy consumption in activated sludge wastewater treatment, a reinforcement learning-based particle swarm optimization (RLPSO) was proposed to optimize control setting sewage process. This algorithm tries take advantage valid history information guide behavior particles through learning strategy. First, an elite network is constructed by selecting and reco...

In order to ensure the stable operation, improve efficiency, and enhance sustainability of wastewater treatment systems, this paper investigates fault detection problem in process based on an improved kernel extreme learning machine method. Firstly, a (KELM) model optimized by mutation bald eagle search (IMBES) optimizer is proposed generate point predictions effluent quality parameters. Then, ...