One-stage production of carbohydrate-enriched microalgae biomass in wastewater is a promising option to obtain biofuels. Understanding the interaction water quality parameters such as nutrients, carbon, internal carbohydrates, and microbial composition culture crucial for efficient operation viable large-scale cultivation. Bioprocess models are an essential tool studying simultaneous effect complex factors on carbohydrate accumulation, optimizing process, reducing operational costs. In this...

Abstract Eutrophication is one of the most relevant concerns due to risk water supply and food security. Nitrogen phosphorus chemical species concentrations determined magnitude eutrophication. These analyses are even more in basins with intensive agriculture agrochemical discharges. However, analyzing these nutrients labor intensive, as sampling intercalibration laboratory requires considerable financial human resources. Currently, artificial intelligence allows modeling phenomena variables...

This article presents a dynamic modeling and control strategy for non-ideal buck DC–DC (direct current) converter using PID neural controller. Unlike conventional approaches that rely on fixed-gain (Proportional Integral Derivative) controllers, the proposed method dynamically updates controller’s gain constants to enhance robustness against parametric variations caused by tolerances, wear, or other practical discrepancies. To ensure network’s weight convergence, Lyapunov-based algorithm is...

This study presents a comprehensive dataset designed for the visual detection of crop diseases, comprising 43,267 images 12 species across 15 disease classes. The was developed over 14 months dedicated human effort. To evaluate its effectiveness, several plant and classification algorithms were tested. models generated by these deployed on mobile devices specialized hardware, enabling practical applications ranging from drones to Android smartphones, with on-device capabilities. results...

This research introduces a fractional high-order sliding mode control (FHOSMC) method that utilises an inverse integral order, 0<β<1, as the high order on FHOSMC reaching law, exhibiting novel contribution in related field of study. The application proposed approach into bioreactor system via diffeomorphism operations demonstrates notable improvement management dynamics versus classic controllers. numerical findings highlight improved precision tracking reference signals and enhanced...

Abstract In this article, the theory of fractional control and state estimation applied to biological science is studied, particularly in hybrid wastewater treatment. For nonlinear systems with stable known states, an interconnected robust design high gain proposed generate a insensitive nutritional perturbations originated by advanced oxidation process microalgae culture. An online study for mineralization glyphosate its feedback cultivation where through designed light dynamics manipulated...

High confidence in disparity map estimation is critical several application fields. A novel framework that employs customized local binary patterns and Jaccard distance for stereo matching along consistency checks presented. The proposal contributes with a method allows greater its estimates, without dependence on supervised learning, capable of generating dense low-cost filtering. proposed has been implemented CPU GPU parallel processing capability. First, Local are obtained during the...

The deterioration of current environmental water sources has led to the need find ways monitor quality conditions. In this paper, we propose use Streeter–Phelps contaminant distribution models and state estimation techniques (observer) be able estimate variables that are very difficult measure in rivers with online sensors, such as Biochemical Oxygen Demand (BOD). We design a novel Fractional Order High Gain Observer (FOHO) consider Lyapunov convergence functions demonstrate stability, it is...

Abstract This article addresses the problem of controlling growth microalgae originating in Mexican rivers, especially state Sinaloa, Culiacan River. For this purpose, a robust, high-gain nonlinear observer is proposed to estimate unknown disturbance cultivation mixotrophic with presence organic nutrients. Once perturbation function related change ambient light estimated, an output feedback control for photobioreactor proposed, which through Lyapunov’s convergence functions, final boundary...

Los metamateriales mecánicos son materiales diseñados artificialmente con la finalidad de presentar un mejor desempeño gracias a los cambios en estructura que conforma y no su composición química. En algunos casos este tipo estructuras están basadas naturaleza, por ejemplo, el interior huesos, panales abejas. Actualmente, avances tecnológicos tanto software hardware ha facilitado diseño fabricación estos materiales. La determinación las propiedades es realizada medio simulación computadora,...

En la presente investigación se evaluaron recuperación de nutrientes y remoción materia orgánica del agua residual agrícola (ARA) mediante un proceso oxidación avanzada (POA). Para ello, configuró sistema UV/H2O2 30 W/m2 optimizado en cuanto a dosis reactivo oxidante tiempo irradiación UV. Los niveles evaluados fueron 48.9, 65.3 84.6 mM peróxido hidrógeno (H2O2) 60, 90 120 min, respectivamente. Así, través algoritmo metodología superficie respuesta (MSR) conjunto con el función deseabilidad,...

This paper proposes a fractional-order sliding mode controller (FOSMC) for the robust control of nonlinear process subjected to unknown parametric disturbances. The aims ensure optimal growth in photobioreactors native microalgae involved eutrophication Sinaloa rivers Mexico. design is based on Caputo fractional integral-order derivative and convergence properties surface. For systems, proposed FOSMC guarantees surface even presence model compared an Internal Model Control (IMC) through...

A novel approach for dense disparity map (DM) estimation is designed. The proposed frameworks include together processing of stereo pairs using the following blocks: CIEL*a*b* color space conversion, matching via multilevel scheme, employing Normalized Cross-Correlation or Structural Similarity Index Measure, segmentation by k-means on a*b* plane, and adaptive post-filtering. Bad Matching Pixels Measure criteria are applied in order to compare performance against state-of-the-art techniques....

In this paper, an approach is described to develop deep learning models that recognize plant diseases of commercial interest through the classification leaf images. A Raspberry Pi 4 microcomputer was used for hardware implementation. Some employed from a subset artificial intelligence, called Deep Learning, were pest detection by fine-tuning Transfer Learning obtain high accuracy rates based on PlantVillage dataset containing thirty-eight different classes, including diseased and healthy...

Different hardware implementations of designed automatic 2D to 3D video color conversion employing sequence are presented. The analyzed framework includes together processing neighboring frames using the following blocks: CIELa*b* space conversion, wavelet transform, edge detection HF sub-bands (HF, LH and HH), segmentation via <i>k-means </i>on a*b* plane, up-sampling, disparity map (DM) estimation, adaptive postfiltering, finally, anaglyph scene generation. During detection, Donoho...

The paper presents the design and hardware implementation of novel framework for image resolution enhancement employing wavelet domain. principal idea consists using edge preservation procedure mutual interpolation between input low-resolution (LR) HF sub-band images performed via Discrete Wavelet Transform (DWT). LR is used in sparse representation resolutionenhancement process, a 1-D set angle directions; following, computations new samples are found, estimating missing samples. Finally,...