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Dynamics of Caputo fractional-order SIRV model:The effects of imperfect vaccination on disease transmission

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International Journal of Biomathematics 2024年第4期17卷 267-285页

作者： Auwal Abdullahi mohd Hafiz mohd Department of Mathematics and Computer Science Federal University Kashere Nigeria School of Mathematical Sciences Universiti Sains Malaysia 11800 USMPulau PinangMalaysia

Though vaccination protects individuals against many infectious diseases,such protection does not always last forever since a few vaccinated individuals could lose their lifelong immunity and eventually become *** study,therefore,determines the effects of imperfect vaccination and memory index on the spread of diseases through the Caputo fractional-order SIRV(Susceptible-Infected-Recovered-Vaccinated)epidemic *** properties of the new model including the conditions for the existence of a unique solution determined through the fixed-point theory and the conditions for the existence of a positive solution of the model obtained via the Mittag-Leffler function along with the Laplace transformation-are thoroughly ***,our simulation results report that an increase in the imperfect vaccination force increases the population of infected *** the memory effect,the higher“memory”the epidemic system has of past states(which corresponds to decreasing values of fractionalorder parameter),the greater the peaks and magnitudes of infection shaping the epidemiological system dynamics.

关键词： Vaccination model fractional-order model Caputo fractional-order derivative Mittag-Leffer function fixed-point theory

Exploring Nutritional Compositions,Volatile Compounds,Health Benefits,Emerging Processing Technologies,and Potential Food Products of Glutinous Rice:A Review

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Rice science 2024年第3期31卷 251-268页

作者： Maimunah mohd ALI Norhashila HASHIM Department of Food Sciences Faculty of Science and TechnologyUniversiti Kebangsaan MalaysiaBangi 43600SelangorMalaysia Department of Biological and Agricultural Engineering Faculty of EngineeringUniversiti Putra MalaysiaSerdang 43400SelangorMalaysia SMART Farming Technology Research Centre Faculty of EngineeringUniversiti Putra MalaysiaUPM Serdang 43400SelangorMalaysia Innovation Center for Confectionary Technology(MANIS) Faculty of Science and TechnologyUniversiti Kebangsaan MalaysiaUKM Bangi 43600Selangor Darul EhsanMalaysia

Glutinous rice(Oryza sativa ***)stands out as one of the most popular rice varieties globally,amidst thousands of rice *** increasing popularity is attributed to its rich nutritional compositions and health *** review aims to summarize the nutritional compositions,volatile compounds,and health benefits of glutinous ***,in-depth studies are necessary to explore the utilization of glutinous rice in enhancing processing technologies and developing new food *** rice has been shown to possess numerous health benefits,including antioxidant activity,bioactive compounds,anti-cancer properties,anti-inflammatory effects,anti-diabetic potential,and cholesterol-lowering *** its nutritional compositions,the major volatile compounds identified in glutinous rice could serve as a functional food for human *** processing technologies related to glutinous rice are elaborated to improve the latest developments for incorporating them into various food products.

关键词： glutinous rice health benefit volatile compound nutritional composition processing technology

Experiment and performance analysis of serpentine-shaped cantilever beam for pipeline vibration-based piezoelectric energy harvester prototype development

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Clean Energy 2024年第4期8卷 111-134页

作者： Wan Nabila mohd Fairuz Illani mohd Nawi Mohamad Radzi Ahmad Ramani Kannan Department of Electrical&Electronics Engineering Universiti Teknologi PETRONASBandar Seri Iskandar31750 TronohPerak Darul RidzuanMalaysia

Pipelines produce vibrations during fluid or gas *** vibrations are less likely to cause structural failure as they exist with a small magnitude and can be harvested into useful *** paper presents a study on the piezoelectric energy-harvesting method converting mechanical energy from pipeline vibration into electrical *** performance of the serpentine-shaped piezoelectric cantilever beam was observed to check whether the design can produce the highest output voltage within the allowable vibration region of the pipeline from 10 to 300 Hz through finite element analysis using COMSOL Multiphysics software(Supplementary Material).In addition,this study investigates the energy-harvesting potential of the proposed design under real pipeline vibration conditions through a lab vibration *** harvested energy output is evaluated based on various vibration frequencies and amplitudes,which gives an idea of the device and its performance under different operating *** experiment result shows that the energy harvester produced an open-circuit voltage of 10.28-15.45 V with 1 g of vibration *** results of this research will contribute to the development of efficient piezoelectric energy harvesters adapted for pipeline environments.

关键词： piezoelectric energy harvester unimorph piezoelectric cantilever beam pipeline vibration energy harvesting COMSOL finite element modelling

Hybrid firefly algorithm-neural network for battery remaining useful life estimation

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Clean Energy 2024年第5期8卷 157-166页

作者： Zuriani Mustaffa mohd Herwan Sulaiman Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)26600 Pekan PahangMalaysia Faculty of Electrical&Electronics Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)26600 Pekan PahangMalaysia

Accurately estimating the remaining useful life(RUL)of batteries is crucial for optimizing maintenance,preventing failures,and enhancing reliability,thereby saving costs and *** study introduces a hybrid approach for estimating the RUL of a battery based on the firefly algorithm–neural network(FA–NN)model,in which the FA is employed as an optimizer to fine-tune the network weights and hidden layer biases in the *** performance of the FA–NN is comprehensively compared against two hybrid models,namely the harmony search algorithm(HSA)–NN and cultural algorithm(CA)–NN,as well as a single model,namely the autoregressive integrated moving average(ARIMA).The comparative analysis is based mean absolute error(MAE)and root mean squared error(RMSE).Findings reveal that the FA–NN outperforms the HSA–NN,CA–NN,and ARIMA in both employed metrics,demonstrating su-perior predictive capabilities for estimating the RUL of a ***,the FA–NN achieved a MAE of 2.5371 and a RMSE of 2.9488 compared with the HSA–NN with a MAE of 22.0583 and RMSE of 34.5154,the CA–NN with a MAE of 9.1189 and RMSE of 22.4646,and the ARIMA with a MAE of 494.6275 and RMSE of ***,the FA–NN exhibits significantly smaller maximum errors at 34.3737 compared with the HSA–NN at 490.3125,the CA–NN at 827.0163,and the ARIMA at 1.16e+03,further emphasizing its robust performance in minimizing prediction *** study offers important insights into battery health management,showing that the proposed method is a promising solution for precise RUL predictions.

关键词： battery remaining useful life firefly algorithm neural networks optimization

Optimizing Average Electric Power During the Charging of Lithium-Ion Batteries Through the Taguchi Method

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Transactions of Tianjin University 2024年第2期30卷 152-166页

作者： mohd H.S.Alrashdan Department of Electrical Engineering Al-Hussein Bin Talal UniversityMaan 71110Jordan

In recent times, lithium-ion batteries have been widely used owing to their high energy density, extended cycle lifespan, and minimal self-discharge rate. The design of high-speed rechargeable lithium-ion batteries faces a significant challenge owing to the need to increase average electric power during charging. This challenge results from the direct influence of the power level on the rate of chemical reactions occurring in the battery electrodes. In this study, the Taguchi optimization method was used to enhance the average electric power during the charging process of lithium-ion batteries. The Taguchi technique is a statistical strategy that facilitates the systematic and efficient evaluation of numerous experimental variables. The proposed method involved varying seven input factors, including positive electrode thickness, positive electrode material, positive electrode active material volume fraction, negative electrode active material volume fraction, separator thickness, positive current collector thickness, and negative current collector thickness. Three levels were assigned to each control factor to identify the optimal conditions and maximize the average electric power during charging. Moreover, a variance assessment analysis was conducted to validate the results obtained from the Taguchi analysis. The results revealed that the Taguchi method was an eff ective approach for optimizing the average electric power during the charging of lithium-ion batteries. This indicates that the positive electrode material, followed by the separator thickness and the negative electrode active material volume fraction, was key factors significantly infl uencing the average electric power during the charging of lithium-ion batteries response. The identification of optimal conditions resulted in the improved performance of lithium-ion batteries, extending their potential in various applications. Particularly, lithium-ion batteries with average electric power of 16 W and 17

关键词： Lithium-ion batteries Average electric power during charging Taguchi method COMSOL Multiphysics software C rate L27 orthogonal array

State of charge estimation for electric vehicles using random forest

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Green Energy and Intelligent Transportation 2024年第5期3卷 42-51页

作者： mohd Herwan Sulaiman Zuriani Mustaffa Faculty of Electrical&Electronics Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)26600 Pekan PahangMalaysia Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)26600 Pekan PahangMalaysia

This paper introduces an innovative approach to addressing a critical challenge in the electric vehicle(EV)industry—the accurate estimation of the state of charge(SOC)of EV batteries under real-world operating *** electric mobility landscape is rapidly evolving,demanding more precise SOC estimation methods to improve range prediction accuracy and battery *** study applies a Random Forest(RF)machine learning algorithm to improve SOC ***,SOC estimation has posed a formidable challenge,particularly in capturing the complex dependencies between various parameters and SOC values during dynamic driving *** methods,including the Extreme Learning Machine(ELM),have exhibited limitations in providing the accuracy and robustness required for practical EV *** contrast,this research introduces the RF model,for SOC estimation approach that excels in real-world *** leveraging decision trees and ensemble learning,the RF model forms resilient relationships between input parameters,such as voltage,current,ambient temperature,and battery temperatures,and SOC *** unique approach empowers the model to deliver precise and consistent SOC estimates across diverse driving *** comparative analyses showcase the superiority of the RF over *** RF model not only outperforms in accuracy but also demonstrates exceptional robustness and reliability,addressing the pressing needs of the EV *** results of this study not only underscore the potential of RF in advancing electric mobility but also suggest a promising integration of the SOC estimation approach into the battery management system of BMW *** integration holds the key to more efficient and dependable electric vehicle operations,marking a significant milestone in the ongoing evolution of EV ***,the RF model demonstrates a lower Root Mean Squared Error(RMSE)of 5.902,8%compared to 6.312,7%for ELM,and a

关键词： Electric vehicles Extreme learning machine Machine learning Random Forest State of charge of battery

Forecasting solar power generation using evolutionary mating algorithm-deep neural networks

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Energy and AI 2024年第2期16卷 346-362页

This paper proposes an integration of recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) in optimizing the weights and biases of deep neural networks (DNN) for forecasting the solar power generation. The study employs a Feed Forward Neural Network (FFNN) to forecast AC power output using real solar power plant measurements spanning a 34-day period, recorded at 15-minute intervals. The intricate nonlinear relationship between solar irradiation, ambient temperature, and module temperature is captured for accurate prediction. Additionally, the paper conducts a comprehensive comparison with established algorithms, including Differential Evolution (DE-DNN), Barnacles Mating Optimizer (BMO-DNN), Particle Swarm Optimization (PSO-DNN), Harmony Search Algorithm (HSA-DNN), DNN with Adaptive Moment Estimation optimizer (ADAM) and Nonlinear AutoRegressive with eXogenous inputs (NARX). The experimental results distinctly highlight the exceptional performance of EMA-DNN by attaining the lowest Root Mean Squared Error (RMSE) during testing. This contribution not only advances solar power forecasting methodologies but also underscores the potential of merging metaheuristic algorithms with contemporary neural networks for improved accuracy and reliability.

关键词： Deep learning neural networks Evolutionary mating algorithm Feed forward neural networks Metaheuristic Optimizers Solar PV

Metabolomics for quality assessment of poultry meat and eggs

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Food Quality and Safety 2024年第1期8卷 27-40页

作者： M.S.Yogeswari Jinap Selamat Nuzul Noorahya Jambari Alf Khatib mohd Hishammfariz mohd Amin Suganya Murugesu Laboratory of Food Safety and Food Integrity Institute of Tropical Agriculture and Food SecurityUniversiti Putra MalaysiaSerdangSelangor Darul EhsanMalaysia Department of Food Science Faculty of Food Science and TechnologyUniversiti Putra MalaysiaSerdangSelangor Darul EhsanMalaysia Department of Pharmaceutical Chemistry Kulliyyah of PharmacyInternational Islamic University MalaysiaKuantanPahang Darul MakmurMalaysia Faculty of Pharmacy Airlangga UniversitySurabayaIndonesia Department of Veterinary Service Malaysia Federal Government Administration CentrePutrajayaMalaysia

The poultry industry is experiencing rapid growth *** accelerated growth has led to multiple food fraud incidents across the food supply chain,which consequently created a demand for precise determination of quality poultry *** increase in demand for precise poultry production quality has necessitated advanced *** has emerged as a viable solution by offering detailed differentiation of biochemical indicators throughout the poultry supply ***,this study provides a means to address risk factors affecting the poultry industry without compromising animal welfare,which is a critical *** review focuses on important issues related to poultry product quality *** adulteration has escalated in recent years as it is driven by the increasing focus on consuming high-quality and nutritious ***,there is no specifc guideline for such determinations,especially when appearance,texture,and taste can be manipulated by substituting for food *** can pave the way for a deeper understanding of existing and novel biochemical indicators responsible for determining the quality of poultry meat and *** approach holds the potential to enhance the overall quality of poultry meat and egg products while also preventing food fraud.

关键词： Poultry metabolomics welfare application authentication.

Can the Bass innovation diffusion model describe adsorption breakthrough curves of pharmaceutical contaminants?

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Green Chemical Engineering 2024年第2期5卷 145-149页

作者： Khim Hoong Chu mohd Ali Hashim Department of Chemical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur50603Malaysia

*** Fixed bed adsorption is a widely used separation process in the chemical industry for the processing of liquids and *** performance of fixed bed adsorption systems is often evaluated by analyzing the breakthrough curves,which represent the variation of the solute concentration in the effluent stream as a function of time or bed volume.

关键词： adsorption breakthrough curves