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Approximation and realization of power-law all-pass filters

Non-integer power-law all-pass transfer functions, are approximated by suitable integer-order transfer functions in this work. The derivation of the integer-order transfer functions is based on the analytic expansion of the (non-integer) power-law transfer functions through the utilization of the binomial theorem. The offered benefit is the derivation of stable integer-order transfer functions. This study is supported by experimental results, obtained using a Field Programmable Analog Array device, after the employment of curve fitting based approximation techniques. © 2022 Elsevier GmbH

Artificial Intelligence
Energy and Water
Circuit Theory and Applications

Di- and tri- cyclic aromatic hydrocarbons removal using different prepared materials based Sargassum dentifolium algae, and iron oxide

Polycyclic aromatic hydrocarbons (PAHs) are highly toxic and carcinogenic compounds as they are low water solubility, hardly degradable and may persist in the environment for many years. Therefore, this study was directed to PAHs ‘anthracene and naphthalene’ removal using a combination method between adsorption and degradation using sunlight. Three adsorbent materials, iron oxide (Fe) alone, Sargassum dentifolium (S) alone, and mixture of Iron oxide and Sargassum dentifolium (FeS) were prepared. Afterwards, optimisation process was performed for the three adsorbent forms through some

Artificial Intelligence
Energy and Water
Circuit Theory and Applications
Mechanical Design

Wide Bandwidth Signals for Joint Time-Frequency Characterization of Nonlinear and Time-Varying Circuits

In this work, we generate and use a total of six different wideband signals for joint time-frequency characterization of nonlinear time-invariant [N-shaped differential resistor (NDR)] and linear time-varying (thermistor) circuits. A data acquisition board is used for applying the signals in the form of a voltage excitation and reading the induced current. The input signals have flat power spectra, thus avoiding the need for iterative calibration loops required to obtain signals with low crest factor. Such iterative loops are unavoidable when using random, pseudorandom, or chaotic signals all

Artificial Intelligence
Energy and Water
Circuit Theory and Applications
Software and Communications

Crystal violet removal using algae-based activated carbon and its composites with bimetallic Fe0-Cu

The textile industry is considered a source of pollution because of the discharge of dye wastewater. The dye wastewater effluent has a significant impact on the aquatic environment. According to the World Bank, textile dyeing, and treatment contribute 17 to 20% of the pollution of water. This paper aims to prepare the bimetallic nano zero-valent iron-copper (Fe0-Cu), algae-activated carbon, and their composites (AC-Fe0-Cu), which are employed as adsorbents. In this paper, Synthetic adsorbents are prepared and examined for the adsorption and removal of soluble cationic crystal violet (CV) dye

Artificial Intelligence
Healthcare
Energy and Water
Circuit Theory and Applications
Software and Communications
Mechanical Design
Innovation, Entrepreneurship and Competitiveness

Review on Coral Reef Regeneration Methods through Renewable Powered Electrotherapy

The restoration of coral reef population in coastal regions is currently a growing concern. Many attempts have been made to apply new approaches to limit the deterioration of coral reefs, and to accelerate the growth of new reefs to protect coastal areas and ecosystems using available renewable energy sources. This paper highlights the new approaches and their various advantages and limitations in tidal and wave energy. The paper also suggests improvements to some of those systems using the recent developments in soft robotics, especially the use of biomimetic fish as a feasible support

Artificial Intelligence
Healthcare
Energy and Water
Circuit Theory and Applications
Mechanical Design

Power-Law Negative Group Delay Filters

A study of the behavior of the power-law negative group delay filters, accompanied by a comparison with their integer-order counterparts, is performed in this work. Employing a curve-fitting based approximation technique, the resulting integer-order rational transfer function is versatile in the sense that it has the same form independent of the order and/or the type of the filter. Its implementation is performed by following three alternative approaches, each one offering different advantages. The findings of this work are supported by simulation and experimental results using suitable

Energy and Water

Tikhonov regularization for the deconvolution of capacitance from the voltage–charge response of electrochemical capacitors

The capacitance of capacitive energy storage devices cannot be directly measured, but can be estimated from the applied input and measured output signals expressed in the time or frequency domains. Here the time-domain voltage–charge relationship of non-ideal electrochemical capacitors is treated as an ill-conditioned convolution integral equation where the unknown capacitance kernel function is to be found. This comes from assuming a priori that in the frequency domain the charge is equal to the product of capacitance by voltage, which is in line with the definition of electrical impedance

Artificial Intelligence
Energy and Water
Circuit Theory and Applications
Software and Communications
Mechanical Design

Time-Frequency Design of a Multi-Sine Excitation with Random Phase and Controllable Amplitude for (Bio) Impedance Measurements

Impedance spectroscopy has become a standard electroanalytical technique to study (bio)electrochemical and physiological systems. From an instrumentation point of view, the measurement of impedance can be carried out either in the frequency domain using the classical frequency sweep method or in the time domain using a variety of broadband signals. While time-domain techniques can be implemented with relatively simple hardware and can achieve faster acquisition time, they are still not that popular because of their lower accuracy and modularity. In this work we present a method and an

Artificial Intelligence
Energy and Water
Circuit Theory and Applications
Software and Communications
Mechanical Design

Reduce Computing Complexity of Deep Neural Networks Through Weight Scaling

Large deep neural network (DNN) models are computation and memory intensive, which limits their deployment especially on edge devices. Therefore, pruning, quantization, data sparsity and data reuse have been applied to DNNs to reduce memory and computation complexity at the expense of some accuracy loss. The reduction in the bit-precision results in loss of information, and the aggressive bit-width reduction could result in noticeable accuracy loss. This paper introduces Scaling-Weight-based Convolution (SWC) technique to reduce the DNN model size and the complexity and number of arithmetic

Artificial Intelligence
Energy and Water
Circuit Theory and Applications
Software and Communications

Robust adaptive supervisory fractional order controller for optimal energy management in wind turbine with battery storage

To address the challenges of poor grid stability, intermittency of wind speed, lack of decision-making, and low economic benefits, many countries have set strict grid codes that wind power generators must accomplish. One of the major factors that can increase the efficiency of wind turbines (WTs) is the simultaneous control of the different parts in several operating area. A high performance controller can significantly increase the amount and quality of energy that can be captured from wind. The main problem associated with control design in wind generator is the presence of asymmetric in the

Artificial Intelligence
Energy and Water
Circuit Theory and Applications
Software and Communications
Mechanical Design
Innovation, Entrepreneurship and Competitiveness