Presence Of Non-ideal Conditions Research Articles

Utilisation of Clamshell Waste for Removing Mercury From Water: Fixed Bed Adsorption and Modelling Studies

The present communication investigated the sustainable utilization of the clamshell waste powder (CSP) for eliminating mercury through fixed bed adsorption. This CSP is freshly prepared and packed in a stable multi-port column. Their breakthrough performance in the column is evaluated by varying its bed depth (5, 10, 15, 20 and 25 min) and flow rate (8, 10 and 12 mL/min). The CSP column’s design parameters and kinetic behavior are estimated from its breakthrough curve and validated using column models. The results revealed that slow saturation of the CSP bed and maximum adsorption capacity (2.8 mg/g) occurred at lower column depth (5 cm) and elevated influent flow rates (12 mL/min). Moreover, the mass transfer zone exhibited fluctuations with elevated column depth, indicating the presence of non-ideal conditions. The YN model showed superior fitness for mercury removal using CSP. The dynamic studies showed that CSP is a cost-effective, eco-friendly, biocompatible and sustainable adsorbent that can be successfully employed for treating industrial effluent.

Optimal synchronization in pulse-coupled oscillator networks using reinforcement learning.

Spontaneous synchronization is ubiquitous in natural and man-made systems. It underlies emergent behaviors such as neuronal response modulation and is fundamental to the coordination of robot swarms and autonomous vehicle fleets. Due to its simplicity and physical interpretability, pulse-coupled oscillators has emerged as one of the standard models for synchronization. However, existing analytical results for this model assume ideal conditions, including homogeneous oscillator frequencies and negligible coupling delays, as well as strict requirements on the initial phase distribution and the network topology. Using reinforcement learning, we obtain an optimal pulse-interaction mechanism (encoded in phase response function) that optimizes the probability of synchronization even in the presence of nonideal conditions. For small oscillator heterogeneities and propagation delays, we propose a heuristic formula for highly effective phase response functions that can be applied to general networks and unrestricted initial phase distributions. This allows us to bypass the need to relearn the phase response function for every new network.

A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies

A simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals. The algorithm to define the dynamic threshold is a modification of a convex combination found in literature. This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise. The present work shows preliminary results over a database built with some political speech. The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared. Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works.