“精灵圈”是海岸带盐沼植被生态系统中的一种“空间自组织”结构,对盐沼湿地的生产力、稳定性和恢复力有重要影响。无人机影像是实现“精灵圈”空间位置高精度识别及解译其时空演化趋势与规律的重要数据源,但“精灵圈”像素与背景像素...“精灵圈”是海岸带盐沼植被生态系统中的一种“空间自组织”结构,对盐沼湿地的生产力、稳定性和恢复力有重要影响。无人机影像是实现“精灵圈”空间位置高精度识别及解译其时空演化趋势与规律的重要数据源,但“精灵圈”像素与背景像素在色彩信息和外形特征上差异较小,如何从二维影像中智能精准地识别“精灵圈”像素并对识别的单个像素形成个体“精灵圈”是目前的技术难点。本文提出了一种结合分割万物模型(Segment Anything Model,SAM)视觉分割模型与随机森林机器学习的无人机影像“精灵圈”分割及分类方法,实现了单个“精灵圈”的识别和提取。首先,通过构建索伦森-骰子系数(S?rensen-Dice coefficient,Dice)和交并比(Intersection over Union,IOU)评价指标,从SAM中筛选预训练模型并对其参数进行优化,实现全自动影像分割,得到无属性信息的分割掩码/分割类;然后,利用红、绿、蓝(RGB)三通道信息及空间二维坐标将分割掩码与原图像进行信息匹配,构造分割掩码的特征指标,并根据袋外数据(Out of Bag,OOB)误差减小及特征分布规律对特征进行分析和筛选;最后,利用筛选的特征对随机森林模型进行训练,实现“精灵圈”植被、普通植被和光滩的自动识别与分类。实验结果表明:本文方法“精灵圈”平均正确提取率96.1%,平均错误提取率为9.5%,为精准刻画“精灵圈”时空格局及海岸带无人机遥感图像处理提供了方法和技术支撑。展开更多
X-ray Computed Tomography(XCT)enables non-destructive acquisition of the internal structure of materials,and image segmentation plays a crucial role in analyzing material XCT images.This paper proposes an image segmen...X-ray Computed Tomography(XCT)enables non-destructive acquisition of the internal structure of materials,and image segmentation plays a crucial role in analyzing material XCT images.This paper proposes an image segmentation method based on the Segment Anything model(SAM).We constructed a dataset of carbide in nickel-based single crystal superalloys XCT images and preprocessed the images using median filtering,histogram equalization,and gamma correction.Subsequently,SAM was fine-tuned to adapt to the task of material XCT image segmentation,resulting in Material-SAM.We compared the performance of threshold segmentation,SAM,U-Net model,and Material-SAM.Our method achieved 88.45%Class Pixel Accuracy(CPA)and 88.77%Dice Similarity Coefficient(DSC)on the test set,outperforming SAM by 5.25%and 8.81%,respectively,and achieving the highest evaluation.Material-SAM demonstrated lower input requirements compared to SAM,as it only required three reference points for completing the segmentation task,which is one-fifth of the requirement of SAM.Material-SAM exhibited promising results,highlighting its potential as a novel method for material XCT image segmentation.展开更多
Three model polyurethane hard segments based on dimethylol butanoic acid (DMBA) and 1,6-hexane diisocyanate (HDI), toluene diisocyanate (TDI) and 4,4'-diphenylmethane diisocyanate (MDI) were prepared by the soluti...Three model polyurethane hard segments based on dimethylol butanoic acid (DMBA) and 1,6-hexane diisocyanate (HDI), toluene diisocyanate (TDI) and 4,4'-diphenylmethane diisocyanate (MDI) were prepared by the solution method. Fourier Infrared (FTIR) spectroscopy was employed to study the H-bonds in these model polyurethanes. The model polyurethane hard segment prepared from HDI and 1,4-butanodiol (BDO) was used for comparison. It was found that the incorporation of the pendent carboxyl through DMBA into the model hard segments weakens the original NH…O = C H-bond but gives more H-bond patterns based on the two H-bond donors, urethane NH and carboxylic OH. The carboxylic dimer is one of the main H-bond types and is stronger than another main H-bond type NH…O=C. In addition, the H-bond in aromatic model hard segments is stronger than that of aliphatic hard segments. The appearance of the free C=O and the fact that almost all N—H is H-bonded suggest that there possibly exist either the third H-bond acceptor or the H-bond formed by one acceptor with two donors.展开更多
Estimating individual tree volume is one of the essential building blocks in forest growth and yield models. Ecologically based taper equations provide accurate vol- ume predictions and allow classification by mer- ch...Estimating individual tree volume is one of the essential building blocks in forest growth and yield models. Ecologically based taper equations provide accurate vol- ume predictions and allow classification by mer- chantable sizes, assisting in sustainable forest management. In the present study, ecoregion-based compatible volume systems for brutian pine and black pine in the three ecoregions of southern Turkey were developed. Several well-known taper functions were evaluated. A second- order continuous-time autoregressive error structure was used to correct the inherent autocorrelation in the hierar- chical data, allowing the model to be applied to irregularly spaced and unbalanced data. The compatible segmented model of Fang et al. (For Sci 46:1-12, 2000) best described the experimental data. It is therefore recommended for estimating diameter at a specific height, height to a specific diameter, merchantable volume, and total volume for the three ecoregions and two species analyzed. The nonlinearextra sum of squares method indicated differences in ecoregion and tree-specific taper functions. A different taper function should therefore be used for each pine spe- cies and ecoregion in southern Turkey. Using ecoregion- specific taper equations allows making more robust esti- mations and, therefore, will enhance the accuracy of diameter at different heights and volume predictions.展开更多
Taper equations are an important tool in estimating stem volumes at a multi-product level for sustainable forest management.Nine taper equations are tested from three categories to estimate diameter at specified point...Taper equations are an important tool in estimating stem volumes at a multi-product level for sustainable forest management.Nine taper equations are tested from three categories to estimate diameter at specified point on the stem,height at specified diameter,volumes of any desired portion of the stem,and whole tree volume of Taurus fir in Taurus Mountains of Turkey.To account for autocorrelation and multicollinearity present among multiple stem data observations collected from the same tree.proper statistical approaches were used in model fitting.Comparisons are made to determine which equation provides the best overall fit to all data based on four goodness-of-fit statistics,Coefficient of determination(R2);Root mean square error(RMSE),Akaike’s Information Criterion(AIC),and Bayesian information criterion(BIC).Results indicated that all taper equations tested could be used to accurately estimate section diameter at given height and stem volume.Clark et al.’s taper equation provided better results than the others for Taurus fir when an additional stem diameter observation at 5.30 m was available.Segmented and variable-form taper models consistently provided better results than the simple taper models except for Max and Burkhart’s model.Fang et al.’s and Kozak’s taper models showed equally good performance to describe stem taper and to predict tree stem volume.Therefore,these taper equations are able to be used to estimate diameter and volume for Taurus fir trees,if an upper stem diameter measurement was not available.展开更多
We developed a simple polynomial taper equation for poplars growing on former farmland in Sweden and also evaluated the performance of some well-known taper equations. In Sweden there is an increasing interest in the ...We developed a simple polynomial taper equation for poplars growing on former farmland in Sweden and also evaluated the performance of some well-known taper equations. In Sweden there is an increasing interest in the use of poplar. Effective management of poplar plantations for high yield production would be facilitated by taper equations providing better predictions of stem volume than currently available equations. In the study a polynomial stem taper equation with five parameters was established for individual poplar trees growing on former farmland. The outputs of the polynomial taper equation were compared with five published equations. Data for fitting the equations were collected from 69 poplar trees growing at 37 stands in central and southern Sweden (lat. 55–60° N). The mean age of the stands was 21 years (range 14–43), the mean density 984 stems·ha?1 (198–3,493), and the mean diameter at breast height (outside bark) 25 cm (range 12–40). To verify the tested equations, performance of accuracy and precision diameter predictions at seven points along the stem was closely analyzed. Statistics used for evaluation of the equations indicated that the variable exponent taper equation presented by Kozak (1988) performed best and can be recommended. The stem taper equation by Kozak (1988) recommended in the study is likely to be beneficial for optimising the efficiency and profitability of poplar plantation management. The constructed polynomial equation and the segmented equation presented by Max & Burkhart (1976) were second and third ranked. Due to the statistical complexity of Kozak’s equation, the constructed polynomial equation is alternatively recommended when a simple model is requested and larger bias is accepted.展开更多
Based on the spherical earth dislocation theory and a fault slip model of the Tohoku-Oki M_(W)9.0 earthquake,the co-seismic Coulomb failure stress changes(ΔCFS)on the northern Tanlu fault zone at depths of 0–40 km a...Based on the spherical earth dislocation theory and a fault slip model of the Tohoku-Oki M_(W)9.0 earthquake,the co-seismic Coulomb failure stress changes(ΔCFS)on the northern Tanlu fault zone at depths of 0–40 km are calculated.By comparing two sets of results from the spherical earth dislocation theory and the semi-infinite space one,the effect of earth curvature on the calculation results is analyzed quantitatively.First,we systematically summarize previous researches related to the northern Tanlu fault zone,divide the fault zone as detailed as possible,give the geometric parameters of each segment,and establish a segmented structural model of the northern Tanlu fault zone.Second,we calculate the Coulomb stress changes on the northern Tanlu fault zone by using the spherical earth dislocation theory.The result shows the Coulomb stress changes are no more than 0.003 MPa,which proves the great earthquake did not significantly change the stress state of the fault zone.Finally,we quantitatively analyze the disparities between the results of semi-infinite space dislocation theory and the spherical earth one.The average disparity between them is about 7.7%on the northern Tanlu fault zone and is 16.8%on the Fangzheng graben,the maximum disparity on this graben reaches up to 25.5%.It indicates that the effect of earth curvature can not be ignored.So it’s necessary to use the spherical earth dislocation theory instead of the semi-infinite space one to study the Coulomb stress change in the far field.展开更多
The desire to benefit from economy of scale is one of the major driving forces behind the continuous growth in ship sizes. However, models of new large ships need to be thoroughly investigated to determine the carrier...The desire to benefit from economy of scale is one of the major driving forces behind the continuous growth in ship sizes. However, models of new large ships need to be thoroughly investigated to determine the carrier's response in waves. In this work, experimental and numerical assessments of the motion and load response of a 550,000 DWT ore carrier are performed using prototype ships with softer stiffness, and towing tank tests are conducted using a segmented model with two schemes of softer stiffness. Numerical analyses are performed employing both rigid body and linear hydroelasticity theories using an in-house program and a comparison is then made between experimental and numerical results to establish the influence of stiffness on the ore carrier's springing response. Results show that softer stiffness models can be used when studying the springing response of ships in waves.展开更多
Micromechanics aims mainly at establishing the quantitative relation between the macroscopic mechanical behavior and the microstructure of heterogeneous materials.
The use of non-destructive testing(NDT) equipment, such as the falling weight deflectometer(FWD), provides important estimates of road health and helps to optimize road management regimes. However, periodic road testi...The use of non-destructive testing(NDT) equipment, such as the falling weight deflectometer(FWD), provides important estimates of road health and helps to optimize road management regimes. However, periodic road testing and post-processing of the collected data are cumbersome and require much expertise, a considerable amount of time, money, and other resources. This study attempts to develop a reliable prediction method for estimating the deflection basin area of different asphalt pavements using road temperature, load time, and load pressure as main characteristics. The data are obtained from 19 kinds of asphalt pavements on a 2.038-km-long full-scale fleld accelerated pavement testing track named RIOHTrack(Research Institute of Highway Track) in Tongzhou, Beijing. In addition, a chaotic particle swarm algorithm(CPSO) and a segmented regression strategy are proposed in this paper to optimize the XGBoost model. The experiment results of the proposed method are compared with those of classical machine learning algorithms and achieve an average of mean square error and mean absolute error respectively by 5.80 and 1.59.The experiments demonstrate the superiority of the XGBoost algorithm over classical machine learning methods in dealing with nonlinear problems in road engineering. Signiflcantly, the method can reduce the frequency of deflection tests without affecting its estimation accuracy, which is a promising alternative way to facilitate the rapid assessment of pavement conditions.展开更多
Renewable energy production has been surging around the world in recent years.To mitigate the increasing uncertainty and intermittency of the renewable generation,proactive demand response algorithms and programs are ...Renewable energy production has been surging around the world in recent years.To mitigate the increasing uncertainty and intermittency of the renewable generation,proactive demand response algorithms and programs are proposed and developed to further improve the utilization of load flexibility and increase the efficiency of power system operation.One of the biggest challenges to efficient control and operation of demand response resources is how to forecast the baseline electricity consumption and estimate the load impact from demand response resources accurately.In this paper,we propose a mixed effect segmented regression model and a new robust estimate for forecasting the baseline electricity consumption in Southern California,USA,by combining the ideas of random effect regression model,segmented regression model,and the least trimmed squares estimate.Since the log-likelihood of the considered model is not differentiable at breakpoints,we propose a new backfitting algorithm to estimate the unknown parameters.The estimation performance of the new estimation procedure has been demonstrated with both simulation studies and the real data application for the electric load baseline forecasting in Southern California.展开更多
AIM:To develop a deep learning-based model for automatic retinal vascular segmentation,analyzing and comparing parameters under diverse glucose metabolic status(normal,prediabetes,diabetes)and to assess the potential ...AIM:To develop a deep learning-based model for automatic retinal vascular segmentation,analyzing and comparing parameters under diverse glucose metabolic status(normal,prediabetes,diabetes)and to assess the potential of artificial intelligence(AI)in image segmentation and retinal vascular parameters for predicting prediabetes and diabetes.METHODS:Retinal fundus photos from 200 normal individuals,200 prediabetic patients,and 200 diabetic patients(600 eyes in total)were used.The U-Net network served as the foundational architecture for retinal arteryvein segmentation.An automatic segmentation and evaluation system for retinal vascular parameters was trained,encompassing 26 parameters.RESULTS:Significant differences were found in retinal vascular parameters across normal,prediabetes,and diabetes groups,including artery diameter(P=0.008),fractal dimension(P=0.000),vein curvature(P=0.003),C-zone artery branching vessel count(P=0.049),C-zone vein branching vessel count(P=0.041),artery branching angle(P=0.005),vein branching angle(P=0.001),artery angle asymmetry degree(P=0.003),vessel length density(P=0.000),and vessel area density(P=0.000),totaling 10 parameters.CONCLUSION:The deep learning-based model facilitates retinal vascular parameter identification and quantification,revealing significant differences.These parameters exhibit potential as biomarkers for prediabetes and diabetes.展开更多
Periodic orbits are crucial in facilitating the understanding of the dynamical behavior of elongated asteroids.As a specific type of periodic orbit,resonant orbits can enrich the orbit design method of deep-space expl...Periodic orbits are crucial in facilitating the understanding of the dynamical behavior of elongated asteroids.As a specific type of periodic orbit,resonant orbits can enrich the orbit design method of deep-space exploration missions.Herein,a dipole segment model for investigating the orbital dynamics of elongated asteroids is briefly introduced.A new numerical algorithm named the modified path searching method for identifying spin-orbit resonant orbits is proposed.Using the modified path searching and pseudo-arclength continuation methods,four spin-orbit resonant families for asteroid 2063 Bacchus are obtained.The distribution of eigenvalues and stability curves for the four resonant families are presented.In particular,some critical points corresponding to period-doubling and tangent bifurcations appear in the stability curves.展开更多
Recently,Meta AI Research approaches a general,promptable segment anything model(SAM)pre-trained on an unprecedentedly large segmentation dataset(SA-1B).Without a doubt,the emergence of SAM will yield significant bene...Recently,Meta AI Research approaches a general,promptable segment anything model(SAM)pre-trained on an unprecedentedly large segmentation dataset(SA-1B).Without a doubt,the emergence of SAM will yield significant benefits for a wide array of practical image segmentation applications.In this study,we conduct a series of intriguing investigations into the performance of SAM across various applications,particularly in the fields of natural images,agriculture,manufacturing,remote sensing and healthcare.We analyze and discuss the benefits and limitations of SAM,while also presenting an outlook on its future development in segmentation tasks.By doing so,we aim to give a comprehensive understanding of SAM's practical applications.This work is expected to provide insights that facilitate future research activities toward generic segmentation.Source code is publicly available at https://github.com/LiuTingWed/SAM-Not-Perfect.展开更多
The precooler is a distinctive component of precooled air-breathing engines but constitutes a challenge to conventional thermal design methods.The latter are based upon assumptions that often reveal to be limited for ...The precooler is a distinctive component of precooled air-breathing engines but constitutes a challenge to conventional thermal design methods.The latter are based upon assumptions that often reveal to be limited for precooler design.In this paper,a refined design method considering the variations of fluid thermophysical properties,flow area and thermal parameters distortion,was proposed to remediate their limitations.Firstly,the precooler was discretized into a fixed number of sub-microtubes based on a new discretization criterion.Next,in-house one-dimensional(1D)and two-dimensional(2D)segmented models were established for rapid thermal design and precooler rating with non-uniform airflow,respectively.The heat transfer experimental studies of supercritical hydrocarbon fuel were performed to verify the Jackson correlation for precooler design and the in-house models were validated against the reported data from open literature.On this basis,the proposed method was employed for the design analysis of hydrocarbon fuel precoolers for precooled-Turbine Based Combined Cycle(TBCC)engines.The results show that the local performance of precoolers is intrinsically impacted by the aforementioned three variations.In the case study,the local heat transfer performance is drastically affected by coolant flow transition.While the circumferential temperature distortion of airflow is weakened by heat transfer.With consideration of additional parameter variations,this novel method improves design accuracy and shortens the design time.展开更多
Hedge funds have recently become popular because of their low correlation with traditional investments and their ability to generate positive returns with a relatively low volatility.However,a close look at those high...Hedge funds have recently become popular because of their low correlation with traditional investments and their ability to generate positive returns with a relatively low volatility.However,a close look at those high-performing hedge funds raises the questions on whether their performance is truly superior and whether the high management fees are justified.Incurring no alpha costs,passive hedge fund replication strategies raise the question on whether they can similarly perform by improving efficiency at reduced costs.Therefore,this study investigates two different model approaches for the equity long/short strategy,where weighted segmented linear regression models are employed and combined with two-state Markov switching models.The main finding proves a short put option structure,i.e.,short equity market volatility,with the put structure present in all market states.We obtain an evidence that the hedge fund managers decrease their short-volatility profile during turbulent markets.展开更多
文摘“精灵圈”是海岸带盐沼植被生态系统中的一种“空间自组织”结构,对盐沼湿地的生产力、稳定性和恢复力有重要影响。无人机影像是实现“精灵圈”空间位置高精度识别及解译其时空演化趋势与规律的重要数据源,但“精灵圈”像素与背景像素在色彩信息和外形特征上差异较小,如何从二维影像中智能精准地识别“精灵圈”像素并对识别的单个像素形成个体“精灵圈”是目前的技术难点。本文提出了一种结合分割万物模型(Segment Anything Model,SAM)视觉分割模型与随机森林机器学习的无人机影像“精灵圈”分割及分类方法,实现了单个“精灵圈”的识别和提取。首先,通过构建索伦森-骰子系数(S?rensen-Dice coefficient,Dice)和交并比(Intersection over Union,IOU)评价指标,从SAM中筛选预训练模型并对其参数进行优化,实现全自动影像分割,得到无属性信息的分割掩码/分割类;然后,利用红、绿、蓝(RGB)三通道信息及空间二维坐标将分割掩码与原图像进行信息匹配,构造分割掩码的特征指标,并根据袋外数据(Out of Bag,OOB)误差减小及特征分布规律对特征进行分析和筛选;最后,利用筛选的特征对随机森林模型进行训练,实现“精灵圈”植被、普通植被和光滩的自动识别与分类。实验结果表明:本文方法“精灵圈”平均正确提取率96.1%,平均错误提取率为9.5%,为精准刻画“精灵圈”时空格局及海岸带无人机遥感图像处理提供了方法和技术支撑。
基金This work was supported by the National Natural Science Foundation of China(Grant Number 52073030)National Natural Science Foundation of China-Guangxi Joint Fund(U20A20276).
文摘X-ray Computed Tomography(XCT)enables non-destructive acquisition of the internal structure of materials,and image segmentation plays a crucial role in analyzing material XCT images.This paper proposes an image segmentation method based on the Segment Anything model(SAM).We constructed a dataset of carbide in nickel-based single crystal superalloys XCT images and preprocessed the images using median filtering,histogram equalization,and gamma correction.Subsequently,SAM was fine-tuned to adapt to the task of material XCT image segmentation,resulting in Material-SAM.We compared the performance of threshold segmentation,SAM,U-Net model,and Material-SAM.Our method achieved 88.45%Class Pixel Accuracy(CPA)and 88.77%Dice Similarity Coefficient(DSC)on the test set,outperforming SAM by 5.25%and 8.81%,respectively,and achieving the highest evaluation.Material-SAM demonstrated lower input requirements compared to SAM,as it only required three reference points for completing the segmentation task,which is one-fifth of the requirement of SAM.Material-SAM exhibited promising results,highlighting its potential as a novel method for material XCT image segmentation.
基金This work was supported by the Natural Science Foundation of Henan Province (004030600)
文摘Three model polyurethane hard segments based on dimethylol butanoic acid (DMBA) and 1,6-hexane diisocyanate (HDI), toluene diisocyanate (TDI) and 4,4'-diphenylmethane diisocyanate (MDI) were prepared by the solution method. Fourier Infrared (FTIR) spectroscopy was employed to study the H-bonds in these model polyurethanes. The model polyurethane hard segment prepared from HDI and 1,4-butanodiol (BDO) was used for comparison. It was found that the incorporation of the pendent carboxyl through DMBA into the model hard segments weakens the original NH…O = C H-bond but gives more H-bond patterns based on the two H-bond donors, urethane NH and carboxylic OH. The carboxylic dimer is one of the main H-bond types and is stronger than another main H-bond type NH…O=C. In addition, the H-bond in aromatic model hard segments is stronger than that of aliphatic hard segments. The appearance of the free C=O and the fact that almost all N—H is H-bonded suggest that there possibly exist either the third H-bond acceptor or the H-bond formed by one acceptor with two donors.
基金financially supported by the Scientific and Technological Research Council of Turkey(Project No:109 O 714)
文摘Estimating individual tree volume is one of the essential building blocks in forest growth and yield models. Ecologically based taper equations provide accurate vol- ume predictions and allow classification by mer- chantable sizes, assisting in sustainable forest management. In the present study, ecoregion-based compatible volume systems for brutian pine and black pine in the three ecoregions of southern Turkey were developed. Several well-known taper functions were evaluated. A second- order continuous-time autoregressive error structure was used to correct the inherent autocorrelation in the hierar- chical data, allowing the model to be applied to irregularly spaced and unbalanced data. The compatible segmented model of Fang et al. (For Sci 46:1-12, 2000) best described the experimental data. It is therefore recommended for estimating diameter at a specific height, height to a specific diameter, merchantable volume, and total volume for the three ecoregions and two species analyzed. The nonlinearextra sum of squares method indicated differences in ecoregion and tree-specific taper functions. A different taper function should therefore be used for each pine spe- cies and ecoregion in southern Turkey. Using ecoregion- specific taper equations allows making more robust esti- mations and, therefore, will enhance the accuracy of diameter at different heights and volume predictions.
基金the part of Ph D dissertation and funded by the Suleyman Demirel University-Teaching Staff Training Program (Project number: OYP05250-DR-14)。
文摘Taper equations are an important tool in estimating stem volumes at a multi-product level for sustainable forest management.Nine taper equations are tested from three categories to estimate diameter at specified point on the stem,height at specified diameter,volumes of any desired portion of the stem,and whole tree volume of Taurus fir in Taurus Mountains of Turkey.To account for autocorrelation and multicollinearity present among multiple stem data observations collected from the same tree.proper statistical approaches were used in model fitting.Comparisons are made to determine which equation provides the best overall fit to all data based on four goodness-of-fit statistics,Coefficient of determination(R2);Root mean square error(RMSE),Akaike’s Information Criterion(AIC),and Bayesian information criterion(BIC).Results indicated that all taper equations tested could be used to accurately estimate section diameter at given height and stem volume.Clark et al.’s taper equation provided better results than the others for Taurus fir when an additional stem diameter observation at 5.30 m was available.Segmented and variable-form taper models consistently provided better results than the simple taper models except for Max and Burkhart’s model.Fang et al.’s and Kozak’s taper models showed equally good performance to describe stem taper and to predict tree stem volume.Therefore,these taper equations are able to be used to estimate diameter and volume for Taurus fir trees,if an upper stem diameter measurement was not available.
基金financially supported by Skogssll-skapet foundation
文摘We developed a simple polynomial taper equation for poplars growing on former farmland in Sweden and also evaluated the performance of some well-known taper equations. In Sweden there is an increasing interest in the use of poplar. Effective management of poplar plantations for high yield production would be facilitated by taper equations providing better predictions of stem volume than currently available equations. In the study a polynomial stem taper equation with five parameters was established for individual poplar trees growing on former farmland. The outputs of the polynomial taper equation were compared with five published equations. Data for fitting the equations were collected from 69 poplar trees growing at 37 stands in central and southern Sweden (lat. 55–60° N). The mean age of the stands was 21 years (range 14–43), the mean density 984 stems·ha?1 (198–3,493), and the mean diameter at breast height (outside bark) 25 cm (range 12–40). To verify the tested equations, performance of accuracy and precision diameter predictions at seven points along the stem was closely analyzed. Statistics used for evaluation of the equations indicated that the variable exponent taper equation presented by Kozak (1988) performed best and can be recommended. The stem taper equation by Kozak (1988) recommended in the study is likely to be beneficial for optimising the efficiency and profitability of poplar plantation management. The constructed polynomial equation and the segmented equation presented by Max & Burkhart (1976) were second and third ranked. Due to the statistical complexity of Kozak’s equation, the constructed polynomial equation is alternatively recommended when a simple model is requested and larger bias is accepted.
基金This study was supported financially by the National Key R&D Program of China(No.2018YFC1503704)the National Natural Science Foundation of China(No.41874003)。
文摘Based on the spherical earth dislocation theory and a fault slip model of the Tohoku-Oki M_(W)9.0 earthquake,the co-seismic Coulomb failure stress changes(ΔCFS)on the northern Tanlu fault zone at depths of 0–40 km are calculated.By comparing two sets of results from the spherical earth dislocation theory and the semi-infinite space one,the effect of earth curvature on the calculation results is analyzed quantitatively.First,we systematically summarize previous researches related to the northern Tanlu fault zone,divide the fault zone as detailed as possible,give the geometric parameters of each segment,and establish a segmented structural model of the northern Tanlu fault zone.Second,we calculate the Coulomb stress changes on the northern Tanlu fault zone by using the spherical earth dislocation theory.The result shows the Coulomb stress changes are no more than 0.003 MPa,which proves the great earthquake did not significantly change the stress state of the fault zone.Finally,we quantitatively analyze the disparities between the results of semi-infinite space dislocation theory and the spherical earth one.The average disparity between them is about 7.7%on the northern Tanlu fault zone and is 16.8%on the Fangzheng graben,the maximum disparity on this graben reaches up to 25.5%.It indicates that the effect of earth curvature can not be ignored.So it’s necessary to use the spherical earth dislocation theory instead of the semi-infinite space one to study the Coulomb stress change in the far field.
基金Supported by the National Natural Science Foundation of China (Grant No. 51079034), and the National Basic Research Program of China (Grant No. 2011CB013703)
文摘The desire to benefit from economy of scale is one of the major driving forces behind the continuous growth in ship sizes. However, models of new large ships need to be thoroughly investigated to determine the carrier's response in waves. In this work, experimental and numerical assessments of the motion and load response of a 550,000 DWT ore carrier are performed using prototype ships with softer stiffness, and towing tank tests are conducted using a segmented model with two schemes of softer stiffness. Numerical analyses are performed employing both rigid body and linear hydroelasticity theories using an in-house program and a comparison is then made between experimental and numerical results to establish the influence of stiffness on the ore carrier's springing response. Results show that softer stiffness models can be used when studying the springing response of ships in waves.
文摘Micromechanics aims mainly at establishing the quantitative relation between the macroscopic mechanical behavior and the microstructure of heterogeneous materials.
基金supported by the National Key Research and Development Program of China (Grant No. 2020YFA0714300)the National Natural Science Foundation of China (Grant Nos. 61833005 and 62003084)the Natural Science Foundation of Jiangsu Province of China (Grant No.BK20200355)。
文摘The use of non-destructive testing(NDT) equipment, such as the falling weight deflectometer(FWD), provides important estimates of road health and helps to optimize road management regimes. However, periodic road testing and post-processing of the collected data are cumbersome and require much expertise, a considerable amount of time, money, and other resources. This study attempts to develop a reliable prediction method for estimating the deflection basin area of different asphalt pavements using road temperature, load time, and load pressure as main characteristics. The data are obtained from 19 kinds of asphalt pavements on a 2.038-km-long full-scale fleld accelerated pavement testing track named RIOHTrack(Research Institute of Highway Track) in Tongzhou, Beijing. In addition, a chaotic particle swarm algorithm(CPSO) and a segmented regression strategy are proposed in this paper to optimize the XGBoost model. The experiment results of the proposed method are compared with those of classical machine learning algorithms and achieve an average of mean square error and mean absolute error respectively by 5.80 and 1.59.The experiments demonstrate the superiority of the XGBoost algorithm over classical machine learning methods in dealing with nonlinear problems in road engineering. Signiflcantly, the method can reduce the frequency of deflection tests without affecting its estimation accuracy, which is a promising alternative way to facilitate the rapid assessment of pavement conditions.
基金The research of W.Yao was supported by National Science Foundation(No.DMS-1461677)Department of Energy(No.DE-EE0007328)+1 种基金The research of N.Yu was supported by National Science Foundation(No.1637258)Department of Energy(No.DE-EE0007328).
文摘Renewable energy production has been surging around the world in recent years.To mitigate the increasing uncertainty and intermittency of the renewable generation,proactive demand response algorithms and programs are proposed and developed to further improve the utilization of load flexibility and increase the efficiency of power system operation.One of the biggest challenges to efficient control and operation of demand response resources is how to forecast the baseline electricity consumption and estimate the load impact from demand response resources accurately.In this paper,we propose a mixed effect segmented regression model and a new robust estimate for forecasting the baseline electricity consumption in Southern California,USA,by combining the ideas of random effect regression model,segmented regression model,and the least trimmed squares estimate.Since the log-likelihood of the considered model is not differentiable at breakpoints,we propose a new backfitting algorithm to estimate the unknown parameters.The estimation performance of the new estimation procedure has been demonstrated with both simulation studies and the real data application for the electric load baseline forecasting in Southern California.
基金Supported by Shenzhen Science and Technology Program(No.JCYJ20220530153604010).
文摘AIM:To develop a deep learning-based model for automatic retinal vascular segmentation,analyzing and comparing parameters under diverse glucose metabolic status(normal,prediabetes,diabetes)and to assess the potential of artificial intelligence(AI)in image segmentation and retinal vascular parameters for predicting prediabetes and diabetes.METHODS:Retinal fundus photos from 200 normal individuals,200 prediabetic patients,and 200 diabetic patients(600 eyes in total)were used.The U-Net network served as the foundational architecture for retinal arteryvein segmentation.An automatic segmentation and evaluation system for retinal vascular parameters was trained,encompassing 26 parameters.RESULTS:Significant differences were found in retinal vascular parameters across normal,prediabetes,and diabetes groups,including artery diameter(P=0.008),fractal dimension(P=0.000),vein curvature(P=0.003),C-zone artery branching vessel count(P=0.049),C-zone vein branching vessel count(P=0.041),artery branching angle(P=0.005),vein branching angle(P=0.001),artery angle asymmetry degree(P=0.003),vessel length density(P=0.000),and vessel area density(P=0.000),totaling 10 parameters.CONCLUSION:The deep learning-based model facilitates retinal vascular parameter identification and quantification,revealing significant differences.These parameters exhibit potential as biomarkers for prediabetes and diabetes.
基金supported partially by the National Natural Science Foundation of China(Grant Nos.11772009 and 12172013)the Beijing Municipal Natural Science Foundation(Grant No.1192002).
文摘Periodic orbits are crucial in facilitating the understanding of the dynamical behavior of elongated asteroids.As a specific type of periodic orbit,resonant orbits can enrich the orbit design method of deep-space exploration missions.Herein,a dipole segment model for investigating the orbital dynamics of elongated asteroids is briefly introduced.A new numerical algorithm named the modified path searching method for identifying spin-orbit resonant orbits is proposed.Using the modified path searching and pseudo-arclength continuation methods,four spin-orbit resonant families for asteroid 2063 Bacchus are obtained.The distribution of eigenvalues and stability curves for the four resonant families are presented.In particular,some critical points corresponding to period-doubling and tangent bifurcations appear in the stability curves.
基金supported by the Mitacs,CFI-JELF and NSERC Discovery grants.
文摘Recently,Meta AI Research approaches a general,promptable segment anything model(SAM)pre-trained on an unprecedentedly large segmentation dataset(SA-1B).Without a doubt,the emergence of SAM will yield significant benefits for a wide array of practical image segmentation applications.In this study,we conduct a series of intriguing investigations into the performance of SAM across various applications,particularly in the fields of natural images,agriculture,manufacturing,remote sensing and healthcare.We analyze and discuss the benefits and limitations of SAM,while also presenting an outlook on its future development in segmentation tasks.By doing so,we aim to give a comprehensive understanding of SAM's practical applications.This work is expected to provide insights that facilitate future research activities toward generic segmentation.Source code is publicly available at https://github.com/LiuTingWed/SAM-Not-Perfect.
基金co-supported by the Specialized Research Foundation of Civil Aircraft,China(MJ-2016-D-35)the Advanced Jet Propulsion Creativity Center,AEAC,China(HKCX2019-01-004)。
文摘The precooler is a distinctive component of precooled air-breathing engines but constitutes a challenge to conventional thermal design methods.The latter are based upon assumptions that often reveal to be limited for precooler design.In this paper,a refined design method considering the variations of fluid thermophysical properties,flow area and thermal parameters distortion,was proposed to remediate their limitations.Firstly,the precooler was discretized into a fixed number of sub-microtubes based on a new discretization criterion.Next,in-house one-dimensional(1D)and two-dimensional(2D)segmented models were established for rapid thermal design and precooler rating with non-uniform airflow,respectively.The heat transfer experimental studies of supercritical hydrocarbon fuel were performed to verify the Jackson correlation for precooler design and the in-house models were validated against the reported data from open literature.On this basis,the proposed method was employed for the design analysis of hydrocarbon fuel precoolers for precooled-Turbine Based Combined Cycle(TBCC)engines.The results show that the local performance of precoolers is intrinsically impacted by the aforementioned three variations.In the case study,the local heat transfer performance is drastically affected by coolant flow transition.While the circumferential temperature distortion of airflow is weakened by heat transfer.With consideration of additional parameter variations,this novel method improves design accuracy and shortens the design time.
文摘Hedge funds have recently become popular because of their low correlation with traditional investments and their ability to generate positive returns with a relatively low volatility.However,a close look at those high-performing hedge funds raises the questions on whether their performance is truly superior and whether the high management fees are justified.Incurring no alpha costs,passive hedge fund replication strategies raise the question on whether they can similarly perform by improving efficiency at reduced costs.Therefore,this study investigates two different model approaches for the equity long/short strategy,where weighted segmented linear regression models are employed and combined with two-state Markov switching models.The main finding proves a short put option structure,i.e.,short equity market volatility,with the put structure present in all market states.We obtain an evidence that the hedge fund managers decrease their short-volatility profile during turbulent markets.