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Senthil Kumar Arumugasamy

Showing results (1-10 of 9) with videos related to

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Environmental Monitoring and Assessment|January 7, 2022
Stability of biochar derived from banana peel through pyrolysis as alternative source of nutrient in soil: feedforward neural network modelling studyHong Kai Bong, Anurita Selvarajoo, Senthil Kumar Arumugasamy
Enzyme and Microbial Technology|January 15, 2019
Optimization and modelling of enzymatic polymerization of ε-caprolactone to polycaprolactone using Candida Antartica Lipase B with response surface methodology and artificial neural networkHarshini Pakalapati, Mohammad Asad Tariq, Senthil Kumar Arumugasamy
Environmental Science and Ecotechnology|September 26, 2022
Data augmentation and machine learning techniques for control strategy development in bio-polymerization processSizhou Wei, Zhiyuan Chen, Senthil Kumar Arumugasamy, et al.
Biopolymers|November 30, 2018
Parametric optimization of polycaprolactone synthesis catalysed by Candida antarctica lipase B using response surface methodologyHarshini Pakalapati, Senthil Kumar Arumugasamy, Jegalakshimi Jewaratnam, et al.
Environmental Monitoring and Assessment|September 10, 2021
Modelling of adsorption of anionic azo dye using Strychnos potatorum Linn seeds (SPS) from aqueous solution with artificial neural network (ANN)Wei Wen Wee, Mei Yuen Siau, Senthil Kumar Arumugasamy, et al.
Environmental Monitoring and Assessment|June 20, 2020
Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) adsorption from aqueous solution using biochar derived from rambutan (Nephelium lappaceum) peelYong Jie Wong, Senthil Kumar Arumugasamy, Chang Han Chung, et al.
Journal of Bioscience and Bioengineering|May 28, 2018
Development of polyhydroxyalkanoates production from waste feedstocks and applicationsHarshini Pakalapati, Chih-Kai Chang, Pau Loke Show, et al.
Polymers|April 11, 2019
Statistical Design of Experimental and Bootstrap Neural Network Modelling Approach for Thermoseparating Aqueous Two-Phase Extraction of PolyhydroxyalkanoatesYoong Kit Leong, Chih-Kai Chang, Senthil Kumar Arumugasamy, et al.
Environmental Science and Pollution Research International|February 20, 2024
Machine learning methods for the modelling and optimisation of biogas production from anaerobic digestion: a reviewJordan Yao Xing Ling, Yi Jing Chan, Jia Win Chen, et al.
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Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Environmental Monitoring and Assessment|January 7, 2022
Stability of biochar derived from banana peel through pyrolysis as alternative source of nutrient in soil: feedforward neural network modelling studyHong Kai Bong, Anurita Selvarajoo, Senthil Kumar Arumugasamy
Enzyme and Microbial Technology|January 15, 2019
Optimization and modelling of enzymatic polymerization of ε-caprolactone to polycaprolactone using Candida Antartica Lipase B with response surface methodology and artificial neural networkHarshini Pakalapati, Mohammad Asad Tariq, Senthil Kumar Arumugasamy
Environmental Science and Ecotechnology|September 26, 2022
Data augmentation and machine learning techniques for control strategy development in bio-polymerization processSizhou Wei, Zhiyuan Chen, Senthil Kumar Arumugasamy, et al.
Biopolymers|November 30, 2018
Parametric optimization of polycaprolactone synthesis catalysed by Candida antarctica lipase B using response surface methodologyHarshini Pakalapati, Senthil Kumar Arumugasamy, Jegalakshimi Jewaratnam, et al.
Environmental Monitoring and Assessment|September 10, 2021
Modelling of adsorption of anionic azo dye using Strychnos potatorum Linn seeds (SPS) from aqueous solution with artificial neural network (ANN)Wei Wen Wee, Mei Yuen Siau, Senthil Kumar Arumugasamy, et al.
Environmental Monitoring and Assessment|June 20, 2020
Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) adsorption from aqueous solution using biochar derived from rambutan (Nephelium lappaceum) peelYong Jie Wong, Senthil Kumar Arumugasamy, Chang Han Chung, et al.
Journal of Bioscience and Bioengineering|May 28, 2018
Development of polyhydroxyalkanoates production from waste feedstocks and applicationsHarshini Pakalapati, Chih-Kai Chang, Pau Loke Show, et al.
Polymers|April 11, 2019
Statistical Design of Experimental and Bootstrap Neural Network Modelling Approach for Thermoseparating Aqueous Two-Phase Extraction of PolyhydroxyalkanoatesYoong Kit Leong, Chih-Kai Chang, Senthil Kumar Arumugasamy, et al.
Environmental Science and Pollution Research International|February 20, 2024
Machine learning methods for the modelling and optimisation of biogas production from anaerobic digestion: a reviewJordan Yao Xing Ling, Yi Jing Chan, Jia Win Chen, et al.
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