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Relationship between fatigue life of asphalt concrete and polypropylene/polyester fibers using artificial neural network and genetic algorithm

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Journal of Central South University 2015年第5期22卷 1937-1946页

作者： Morteza Vadood majid safar johari Ali Reza Rahai Textile Engineering Department Amirkabir University of Technology Civil and Environmental Engineering Department Amirkabir University of Technology

While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using polypropylene and polyester fibers was evaluated and two models namely regression and artificial neural network(ANN) were used to predict the fatigue life based on the fibers parameters. As ANN contains many parameters such as the number of hidden layers which directly influence the prediction accuracy, genetic algorithm(GA) was used to solve optimization problem for ANN. Moreover, the trial and error method was used to optimize the GA parameters such as the population size. The comparison of the results obtained from regression and optimized ANN with GA shows that the two-hidden-layer ANN with two and five neurons in the first and second hidden layers, respectively, can predict the fatigue life of fiber-reinforced HMA with high accuracy(correlation coefficient of 0.96).

关键词： hot mix asphalt fatigue property reinforced fiber artificial neural network genetic algorithm

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Nanomaterial-assisted wearable glucose biosensors for noninvasive real-time monitoring:Pioneering point-of-care and beyond

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Nano Materials Science 2024年第3期6卷 263-283页

作者： Moein safarkhani Abdullah Aldhaher Golnaz Heidari Ehsan Nazarzadeh Zare majid Ebrahimi Warkiani Omid Akhavan YunSuk Huh Navid Rabiee NanoBio High-Tech Materials Research Center Department of Biological Sciences and BioengineeringInha UniversityIncheon22212Republic of Korea Department of Chemistry Sharif University of TechnologyTehranIran School of Natural Sciences Massey UniversityPrivate Bag 11222Palmerston North4410New Zealand School of Chemistry Damghan UniversityDamghan36716-45667Iran School of Biomedical Engineering University of Technology SydneySydneyNSW2007Australia Department of Physics Sharif University of TechnologyP.O.Box 11155-9161TehranIran Centre for Molecular Medicine and Innovative Therapeutics Murdoch UniversityPerthWA 6150Australia School of Engineering Macquarie UniversitySydneyNew South Wales2109Australia

This review explores glucose monitoring and management strategies,emphasizing the need for reliable and userfriendly wearable sensors that are the next generation of sensors for continuous glucose *** addition,examines key strategies for designing glucose sensors that are multi-functional,reliable,and cost-effective in a variety of *** unique features of effective diabetes management technology are highlighted,with a focus on using nano/biosensor devices that can quickly and accurately detect glucose levels in the blood,improving patient treatment and control of potential diabetes-related *** potential of next-generation wearable and touch-sensitive nano biomedical sensor engineering designs for providing full control in assessing implantable,continuous glucose monitoring is also *** challenges of standardizing drug or insulin delivery doses,low-cost,real-time detection of increased blood sugar levels in diabetics,and early digital health awareness controls for the adverse effects of injectable medication are identified as unmet ***,the market for biosensors is expected to expand significantly due to the rising need for portable diagnostic equipment and an ever-increasing diabetic *** paper concludes by emphasizing the need for further research and development of glucose biosensors to meet the stringent requirements for sensitivity and specificity imposed by clinical diagnostics while being cost-effective,stable,and durable.

关键词： Glucose sensor Biosensor Wearable devices Noninvasive Real-time monitoring

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