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      Amaranthus hybridus waste solid biofuel: comparative and machine learning studies

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          Abstract

          The diminishing supply of fossil fuels, their detrimental environmental effects, and the challenges associated with the disposal of agro-waste necessitated the development of renewable and sustainable alternative energy sources. This study aims at developing bio-briquettes from Amaranthus hybridus waste, with cassava starch as a binder; both are agricultural wastes. Before and following delignification, alkali-treated Amaranthus hybridus (TAHB) and untreated (UAHB) briquettes were evaluated in terms of combustion and physicochemical parameters. FTIR and SEM were utilized to monitor the morphological transformation and bond restructuring of TAHB and UAHB samples. EDXRF was used to assess the Potential Toxic Elements (PTEs) composition and environmental friendliness of both TAHB and UAHB. Furthermore, Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy c-means (FCM) clustering machine learning models were used to optimize the production process and predict the efficiency of bio-briquettes. After delignification, a lower lignin value of 11.47 ± 0.00% in TAHB compared to 12.31 ± 0.01% (UAHB) was recorded. Calorific values of 10.43 ± 0.25 MJ kg −1 (UAHB) and 12.53 ± 0.30 MJ kg −1 (TAHB) were recorded at p < 0.05. EDXRF results showed a difference of 0.016% in Pb concentration in both samples. SEM reveals morphological restructuring, while FTIR reveals a 4 cm −1 difference in the C–O stretch. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) gave values of 0.0249, 2.104, and, 0.0249; (MAE, training) and 0.0223 (MAE, testing) respectively. This shows that the model's predictions match the reality, thereby suggesting a strong agreement between the predicted and experimental data. The finding of this study shows that delignification-disruption improved the solid biofuel's ability to burn cleanly and sustainably.

          Abstract

          The diminishing supply of fossil fuels, their detrimental environmental effects, and the challenges associated with the disposal of agro-waste necessitated the development of renewable and sustainable alternative energy sources.

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          The analysis effect of cluster numbers on fuzzy c-means algorithm for blood vessel segmentation of retinal fundus image

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            ASME 2022 International Mechanical Engineering Congress and Exposition

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                Author and article information

                Journal
                RSC Adv
                RSC Adv
                RA
                RSCACL
                RSC Advances
                The Royal Society of Chemistry
                2046-2069
                10 April 2024
                3 April 2024
                10 April 2024
                : 14
                : 16
                : 11541-11556
                Affiliations
                [a ] Department of Chemistry, Faculty of Natural and Applied Sciences, Lead City University Ibadan Oyo State Nigeria abayomibamisaye@ 123456gmail.com
                [b ] Faculty of Civil Engineering and Environmental Sciences, Białystok University of Technology Wiejska 45E 15-351 Białystok Poland
                [c ] Department of Industrial Chemistry, First Technical University Ibadan Nigeria kwharyourday@ 123456gmail.com
                [d ] Department of Forestry, Fiji National University Koronivia Fiji Island
                [e ] CNRS, LCC (Laboratoire de Chimie de Coordination), UPR8241, Université de Toulouse, UPS, INPT Toulouse Cedex 4 F-31077 France
                [f ] Department of Chemical Sciences, Faculty of Science and Computing, Ahman Pategi University Patigi-Kpada Road Patigi Kwara State Nigeria
                [g ] Department of Manufacturing and Materials Engineering, Kulliyyah of Engineering France
                [h ] Department of Mechanical Engineering Science, University of Johannesburg Johannesburg South Africa
                [i ] Department of Chemistry, College of Physical Science, Federal University of Agriculture Abeokuta Nigeria
                Author information
                https://orcid.org/0000-0003-1466-9058
                https://orcid.org/0000-0002-7502-0132
                Article
                d3ra08378k
                10.1039/d3ra08378k
                11004732
                38601704
                48869b7c-ac77-4ae2-b789-dbfc66523731
                This journal is © The Royal Society of Chemistry
                History
                : 8 December 2023
                : 26 March 2024
                Page count
                Pages: 16
                Categories
                Chemistry
                Custom metadata
                Paginated Article

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