Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the lim...Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the limited energy resources of SNs.Current energy efficiency strategies,such as clustering,multi-hop routing,and data aggregation,face challenges,including uneven energy depletion,high computational demands,and suboptimal cluster head(CH)selection.To address these limitations,this paper proposes a hybrid methodology that optimizes energy consumption(EC)while maintaining network performance.The proposed approach integrates the Low Energy Adaptive Clustering Hierarchy with Deterministic(LEACH-D)protocol using an Artificial Neural Network(ANN)and Bayesian Regularization Algorithm(BRA).LEACH-D improves upon conventional LEACH by ensuring more uniform energy usage across SNs,mitigating inefficiencies from random CH selection.The ANN further enhances CH selection and routing processes,effectively reducing data transmission overhead and idle listening.Simulation results reveal that the LEACH-D-ANN model significantly reduces EC and extends the network’s lifespan compared to existing protocols.This framework offers a promising solution to the energy efficiency challenges in WSNs,paving the way for more sustainable and reliable network deployments.展开更多
In order to improve the leaching resistance of active ingredient-copper in ammoniacal copper quat-type D （ACQ-D） treated Chinese fir （Cunninghamia lanceolata Hook.）, microwave post-treatments were carried out. The...In order to improve the leaching resistance of active ingredient-copper in ammoniacal copper quat-type D （ACQ-D） treated Chinese fir （Cunninghamia lanceolata Hook.）, microwave post-treatments were carried out. The percentages of leached copper from ACQ-D treated Chinese fir with different microwave post-treatments were obtained after leaching tests by analyzing the copper retention in treated wood. The fixation mechanism of copper in the treated wood was determined with the help of SEM and FTIR spectra, while the valence conversion of copper after microwave post-treatments was studied by UV spectroscopy. Our experimental results show that the percentage of leached copper was reduced significantly after microwave post-treatment over time. This development was reinforced by allowing even more time for the treatment as well as with an increase in the power of microwave post-treatment. The leaching resistance of copper in wrapped samples was better than that in unwrapped samples, which is attributed to the combined effects of temperature and moisture content. Compared with air-dried samples, the valence conversion in the samples with microwave post-treatments changed slightly, which demonstrates that microwave post-treatments cannot impair the natural decay resistance of ACQ-D treated wood. SEM and FTIR spectra showed the presence of crystal particles formed by chemical reactions between copper and wood ingredients in wood cell walls and wood pits. Only a small amount of copper reacted with cellulose, while lignin and hemicellulose were the major bonding sites for copper in wood. Given the experimental results of mechanical properties, microwave post-treatments had a slight effect on the compression strength parallel to the grain and on the erystallinity of ACQ-D treated Chinese fir.展开更多
文摘Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the limited energy resources of SNs.Current energy efficiency strategies,such as clustering,multi-hop routing,and data aggregation,face challenges,including uneven energy depletion,high computational demands,and suboptimal cluster head(CH)selection.To address these limitations,this paper proposes a hybrid methodology that optimizes energy consumption(EC)while maintaining network performance.The proposed approach integrates the Low Energy Adaptive Clustering Hierarchy with Deterministic(LEACH-D)protocol using an Artificial Neural Network(ANN)and Bayesian Regularization Algorithm(BRA).LEACH-D improves upon conventional LEACH by ensuring more uniform energy usage across SNs,mitigating inefficiencies from random CH selection.The ANN further enhances CH selection and routing processes,effectively reducing data transmission overhead and idle listening.Simulation results reveal that the LEACH-D-ANN model significantly reduces EC and extends the network’s lifespan compared to existing protocols.This framework offers a promising solution to the energy efficiency challenges in WSNs,paving the way for more sustainable and reliable network deployments.
基金the FANEDD of China (No. 200352)the Fok Ying Tong Education Foundation (No. 101028) for financial support
文摘In order to improve the leaching resistance of active ingredient-copper in ammoniacal copper quat-type D （ACQ-D） treated Chinese fir （Cunninghamia lanceolata Hook.）, microwave post-treatments were carried out. The percentages of leached copper from ACQ-D treated Chinese fir with different microwave post-treatments were obtained after leaching tests by analyzing the copper retention in treated wood. The fixation mechanism of copper in the treated wood was determined with the help of SEM and FTIR spectra, while the valence conversion of copper after microwave post-treatments was studied by UV spectroscopy. Our experimental results show that the percentage of leached copper was reduced significantly after microwave post-treatment over time. This development was reinforced by allowing even more time for the treatment as well as with an increase in the power of microwave post-treatment. The leaching resistance of copper in wrapped samples was better than that in unwrapped samples, which is attributed to the combined effects of temperature and moisture content. Compared with air-dried samples, the valence conversion in the samples with microwave post-treatments changed slightly, which demonstrates that microwave post-treatments cannot impair the natural decay resistance of ACQ-D treated wood. SEM and FTIR spectra showed the presence of crystal particles formed by chemical reactions between copper and wood ingredients in wood cell walls and wood pits. Only a small amount of copper reacted with cellulose, while lignin and hemicellulose were the major bonding sites for copper in wood. Given the experimental results of mechanical properties, microwave post-treatments had a slight effect on the compression strength parallel to the grain and on the erystallinity of ACQ-D treated Chinese fir.
