Tree trunk instance segmentation is crucial for under-canopy unmanned aerial vehicles(UAVs)to autonomously extract standing tree stem attributes.Using cameras as sensors makes these UAVs compact and lightweight,facili...Tree trunk instance segmentation is crucial for under-canopy unmanned aerial vehicles(UAVs)to autonomously extract standing tree stem attributes.Using cameras as sensors makes these UAVs compact and lightweight,facilitating safe and flexible navigation in dense forests.However,their limited onboard computational power makes real-time,image-based tree trunk segmentation challenging,emphasizing the urgent need for lightweight and efficient segmentation models.In this study,we present RT-Trunk,a model specifically designed for real-time tree trunk instance segmentation in complex forest environments.To ensure real-time performance,we selected SparseInst as the base framework.We incorporated ConvNeXt-T as the backbone to enhance feature extraction for tree trunks,thereby improving segmentation accuracy.We further integrate the lightweight convolutional block attention module(CBAM),enabling the model to focus on tree trunk features while suppressing irrelevant information,which leads to additional gains in segmentation accuracy.To enable RT-Trunk to operate effectively under diverse complex forest environments,we constructed a comprehensive dataset for training and testing by combining self-collected data with multiple public datasets covering different locations,seasons,weather conditions,tree species,and levels of forest clutter.Com-pared with the other tree trunk segmentation methods,the RT-Trunk method achieved an average precision of 91.4%and the fastest inference speed of 32.9 frames per second.Overall,the proposed RT-Trunk provides superior trunk segmentation performance that balances speed and accu-racy,making it a promising solution for supporting under-canopy UAVs in the autonomous extraction of standing tree stem attributes.The code for this work is available at https://github.com/NEFU CVRG/RT Trunk.展开更多
In this work, the potential of natural and pretreated palm tree trunk (PTT) as agents for adsorption of an organic dye, 2,6-dichlorophenolindophenol (2,6-DCPIP) from aqueous solutions was probed. Natural and acetic ac...In this work, the potential of natural and pretreated palm tree trunk (PTT) as agents for adsorption of an organic dye, 2,6-dichlorophenolindophenol (2,6-DCPIP) from aqueous solutions was probed. Natural and acetic acid treated PTT were characterized by Fourier transform infrared (FT-IR) spectroscopy and by the point of zero charge (pzc). The biosorption of 2,6-DCPIP was investigated in batch mode using natural and treated PTT. This study was achieved by highlighting several parameters such as the contact time, biosorbents dosage, the initial concentration of 2,6-DCPIP, the pH of the solution, the ionic strength and the interfering ions. The results showed that 2,6-DCPIP was successfully adsorbed from aqueous solutions by natural and treated PTT. The equilibrium was attained after 40 minutes for treated PTT and 20 minutes for natural PTT. The maximum capacity of adsorption was obtained at pH = 2. The adsorption isotherms were investigated and it was found that the experimental data were best described by the Dubinin-Radushkevich isotherm for the natural PTT (R2 = 0.979) and by the Temkin isotherm for the treated PTT (R2 = 0.976). The maximum adsorption capacities determined by Langmuir isotherm were found as 108.932 and 157.233 μmol·g–1 for natural and treated PTT, respectively. The adsorption kinetics was analyzed and was best described by the pseudo-second order model (R2 ≥ 0.998). The diffusion mechanism was studied and the result showed that external mass transfer is the main rate controlling step. The desorption of 2,6-DCPIP is favorable in alkaline medium.展开更多
In this work we determine the physical and mechanical properties of local composites reinforced with papaya trunk fibers (FTP) on one hand and particles of the hulls of the kernels of the garlic (PCNFA) in the other h...In this work we determine the physical and mechanical properties of local composites reinforced with papaya trunk fibers (FTP) on one hand and particles of the hulls of the kernels of the garlic (PCNFA) in the other hand. The samples are produced according to BSI 2782 standards;by combining fibers and untreated to polyester matrix following the contact molding method. We notice that the long fibers of papaya trunks improve the tensile/compression characteristics of composites by 45.44% compared to pure polyester;while the short fibers improve the flexural strength of composites by 62.30% compared to pure polyester. Furthermore, adding fibers decreases the density of the final composite material and the rate of water absorption increases with the size of the fibers. As regards composite materials with particle reinforcement from the cores of the winged fruits, the particle size (fine ≤ 800 μm and large ≤ 1.6 mm) has no influence on the Young’s modulus and on the rate of water absorption. On the other hand, fine particles improve the flexural strength of composite materials by 53.08% compared to pure polyester;fine particles increase the density by 19% compared to the density of pure polyester.展开更多
To determine the age of oil-tea camellia trees, regression equations including Logistic, Mitscherlich, Gompertz, Korf, and Richards were used to calculate accumulative growth rate using basal trunk disc and investigat...To determine the age of oil-tea camellia trees, regression equations including Logistic, Mitscherlich, Gompertz, Korf, and Richards were used to calculate accumulative growth rate using basal trunk disc and investigate the relations between the age of oil-tea camellia trees and their growth rate of secondary trunk. The Gompertz equation Y=71.296 1exp （-3.874 4exp （-0.006 4t）） was the most optimal equation to simulate the accumulative growth rate of basal trunk disc. This equation could be used to estimate the age of oil-tea camellia trees that grow under similar environmental conditions. The Korf equation Y=576.900 1exp （-4.153 0x -0.314 2 ） was the best equation to describe the relation between the age and growth rate of different secondary trunks. With the adjustment coefficient and average growth of different secondary trunk discs, it is possible to predict the age of ancient oil-tea camellia trees that grow under similar environmental conditions. In addition, taking three or more discs from the same diameter group and calculating their average growth rate could lead to more accurate results. For trees that grow in different areas, environmental conditions should be carefully considered when using the above two equations to predict the age of ancient oil-tea camellia trees.展开更多
基金supported in part by the National Natural Science Foundation of China(No.31470714 and 61701105).
文摘Tree trunk instance segmentation is crucial for under-canopy unmanned aerial vehicles(UAVs)to autonomously extract standing tree stem attributes.Using cameras as sensors makes these UAVs compact and lightweight,facilitating safe and flexible navigation in dense forests.However,their limited onboard computational power makes real-time,image-based tree trunk segmentation challenging,emphasizing the urgent need for lightweight and efficient segmentation models.In this study,we present RT-Trunk,a model specifically designed for real-time tree trunk instance segmentation in complex forest environments.To ensure real-time performance,we selected SparseInst as the base framework.We incorporated ConvNeXt-T as the backbone to enhance feature extraction for tree trunks,thereby improving segmentation accuracy.We further integrate the lightweight convolutional block attention module(CBAM),enabling the model to focus on tree trunk features while suppressing irrelevant information,which leads to additional gains in segmentation accuracy.To enable RT-Trunk to operate effectively under diverse complex forest environments,we constructed a comprehensive dataset for training and testing by combining self-collected data with multiple public datasets covering different locations,seasons,weather conditions,tree species,and levels of forest clutter.Com-pared with the other tree trunk segmentation methods,the RT-Trunk method achieved an average precision of 91.4%and the fastest inference speed of 32.9 frames per second.Overall,the proposed RT-Trunk provides superior trunk segmentation performance that balances speed and accu-racy,making it a promising solution for supporting under-canopy UAVs in the autonomous extraction of standing tree stem attributes.The code for this work is available at https://github.com/NEFU CVRG/RT Trunk.
文摘In this work, the potential of natural and pretreated palm tree trunk (PTT) as agents for adsorption of an organic dye, 2,6-dichlorophenolindophenol (2,6-DCPIP) from aqueous solutions was probed. Natural and acetic acid treated PTT were characterized by Fourier transform infrared (FT-IR) spectroscopy and by the point of zero charge (pzc). The biosorption of 2,6-DCPIP was investigated in batch mode using natural and treated PTT. This study was achieved by highlighting several parameters such as the contact time, biosorbents dosage, the initial concentration of 2,6-DCPIP, the pH of the solution, the ionic strength and the interfering ions. The results showed that 2,6-DCPIP was successfully adsorbed from aqueous solutions by natural and treated PTT. The equilibrium was attained after 40 minutes for treated PTT and 20 minutes for natural PTT. The maximum capacity of adsorption was obtained at pH = 2. The adsorption isotherms were investigated and it was found that the experimental data were best described by the Dubinin-Radushkevich isotherm for the natural PTT (R2 = 0.979) and by the Temkin isotherm for the treated PTT (R2 = 0.976). The maximum adsorption capacities determined by Langmuir isotherm were found as 108.932 and 157.233 μmol·g–1 for natural and treated PTT, respectively. The adsorption kinetics was analyzed and was best described by the pseudo-second order model (R2 ≥ 0.998). The diffusion mechanism was studied and the result showed that external mass transfer is the main rate controlling step. The desorption of 2,6-DCPIP is favorable in alkaline medium.
文摘In this work we determine the physical and mechanical properties of local composites reinforced with papaya trunk fibers (FTP) on one hand and particles of the hulls of the kernels of the garlic (PCNFA) in the other hand. The samples are produced according to BSI 2782 standards;by combining fibers and untreated to polyester matrix following the contact molding method. We notice that the long fibers of papaya trunks improve the tensile/compression characteristics of composites by 45.44% compared to pure polyester;while the short fibers improve the flexural strength of composites by 62.30% compared to pure polyester. Furthermore, adding fibers decreases the density of the final composite material and the rate of water absorption increases with the size of the fibers. As regards composite materials with particle reinforcement from the cores of the winged fruits, the particle size (fine ≤ 800 μm and large ≤ 1.6 mm) has no influence on the Young’s modulus and on the rate of water absorption. On the other hand, fine particles improve the flexural strength of composite materials by 53.08% compared to pure polyester;fine particles increase the density by 19% compared to the density of pure polyester.
基金Supported by Hunan Forestry Science and Technology Project(XLK201707)
文摘To determine the age of oil-tea camellia trees, regression equations including Logistic, Mitscherlich, Gompertz, Korf, and Richards were used to calculate accumulative growth rate using basal trunk disc and investigate the relations between the age of oil-tea camellia trees and their growth rate of secondary trunk. The Gompertz equation Y=71.296 1exp （-3.874 4exp （-0.006 4t）） was the most optimal equation to simulate the accumulative growth rate of basal trunk disc. This equation could be used to estimate the age of oil-tea camellia trees that grow under similar environmental conditions. The Korf equation Y=576.900 1exp （-4.153 0x -0.314 2 ） was the best equation to describe the relation between the age and growth rate of different secondary trunks. With the adjustment coefficient and average growth of different secondary trunk discs, it is possible to predict the age of ancient oil-tea camellia trees that grow under similar environmental conditions. In addition, taking three or more discs from the same diameter group and calculating their average growth rate could lead to more accurate results. For trees that grow in different areas, environmental conditions should be carefully considered when using the above two equations to predict the age of ancient oil-tea camellia trees.
