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Combining Environmental Factors and Lab VNIR Spectral Data to Predict SOM by Geospatial Techniques 预览
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作者 GUO Long ZHANG Haitao +1 位作者 CHEN Yiyun QIAN Jing 《中国地理科学:英文版》 SCIE CSCD 2019年第2期258-269,共12页
Soil organic matter(SOM) is an important parameter related to soil nutrient and miscellaneous ecosystem services. This paper attempts to improve the performance of traditional partial least square regression(PLSR) mod... Soil organic matter(SOM) is an important parameter related to soil nutrient and miscellaneous ecosystem services. This paper attempts to improve the performance of traditional partial least square regression(PLSR) model by considering the spatial autocorrelation and soil forming factors. Surface soil samples(n = 180) were collected from Honghu City located in the middle of Jianghan Plain, China. The visible and near infrared(VNIR) spectra and six environmental factors(elevation, land use types, roughness, relief amplitude, enhanced vegetation index, and land surface water index) were used as the auxiliary variables to construct the multiple linear regression(MLR), PLSR and geographically weighted regression(GWR) models. Results showed that: 1) the VNIR spectra can increase about 39.62% prediction accuracy than the environmental factors in predicting SOM;2) the comprehensive variables of VNIR spectra and the environmental factors can improve about 5.78% and 44.90% relative to soil spectral models and soil environmental models, respectively;3) the spatial model(GWR) can improve about 3.28% accuracy than MLR and PLSR. Our results suggest that the combination of spectral reflectance and the environmental variables can be used as the suitable auxiliary variables in predicting SOM, and GWR is a promising model for predicting soil properties. 展开更多
关键词 VISIBLE near infrared spectral reflectance environmental factors spatial characteristics partial least SQUARES regression geographically weighted regression
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Unnecessity of lymph node regression evaluation for predicting gastric adenocarcinoma outcome after neoadjuvant chemotherapy 预览
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作者 Yue-Lu Zhu Yong-Kun Sun +3 位作者 Xue-Min Xue Jiang-Ying Yue Lin Yang Li-Yan Xue 《世界胃肠肿瘤学杂志:英文版(电子版)》 CAS 2019年第1期48-58,共11页
BACKGROUND Neoadjuvant chemotherapy has been applied worldwide to improve the survival of patients with gastric adenocarcinoma (GAC). The evaluation of histological regression in primary tumors is valuable for predict... BACKGROUND Neoadjuvant chemotherapy has been applied worldwide to improve the survival of patients with gastric adenocarcinoma (GAC). The evaluation of histological regression in primary tumors is valuable for predicting prognosis. However, the prognostic effect of regression change in lymph nodes (LNs) remains unclear. AIM To confirm whether the evaluation of regression change in LNs could predict the prognosis of GAC patients who received neoadjuvant chemotherapy followed by surgery. METHODS In this study, we evaluated the histological regression of resected LNs from 192 GAC patients (including those with esophagogastric junction adenocarcinoma) treated with neoadjuvant chemotherapy. We classified regression change and residual tumor in LNs into four groups:(A) true negative LNs with no evidence of a preoperative therapy effect,(B) no residual metastasis but the presence of regression change in LNs,(C) residual metastasis with regression change in LNs, and (D) metastasis with minimal or no regression change in LNs. Correlations between regression change and residual tumor groups in LNs and regression change in the primary tumor, as well as correlations between regression change in LNs and clinicopathological characteristics, were analyzed. The prognostic effect of regression change and residual tumor groups in LNs was also analyzed. RESULTS We found that regression change and residual tumor groups in LNs were significantly correlated with regression change in the primary tumor, tumor differentiation, ypT stage, ypN stage, ypTNM stage, lymph-vascular invasion, perineural invasion and R0 resection status. Regression change and residual tumor groups in LNs were statistically significant using univariate Cox proportional hazards analysis, but were not independent predictors. For patients who had no residual tumor in LNs, the 5-year overall survival (OS) rates were 67.5% in Group A and 67.4% in Group B. For the patients who had residual tumors in LNs, the 5-year OS rates were 28.2% in Group C and 39.5% in Group D. T 展开更多
关键词 Gastric cancer NEOADJUVANT CHEMOTHERAPY LYMPH NODES Regression RESIDUAL tumor Regression change
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Comparative Analysis of Fractional Vegetation Cover Estimation Based on Multi-sensor Data in a Semi-arid Sandy Area 预览
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作者 LIU Qiuyu ZHANG Tinglong +3 位作者 LI Yizhe LI Ying BU Chongfeng ZHANG Qingfeng 《中国地理科学:英文版》 SCIE CSCD 2019年第1期166-180,共15页
The estimation of fractional vegetation cover(FVC) is important for identifying and monitoring desertification, especially in arid and semiarid regions. By using regression and pixel dichotomy models, we present the c... The estimation of fractional vegetation cover(FVC) is important for identifying and monitoring desertification, especially in arid and semiarid regions. By using regression and pixel dichotomy models, we present the comparison of Sentinel-2A(S2) multispectral instrument(MSI) and Landsat 8(L8) operational land imager(OLI) data regarding the retrieval of FVC in a semi-arid sandy area(Mu Us Sandland, China, in August 2016). A combination of unmanned aerial vehicle(UAV) high-spatial-resolution images and field plots were used to produce verified data. Based on a normalized difference vegetation index(NDVI) regression model, the results showed that, compared with that of L8, the coefficient of determination(R2) of S2 increased by 26.0%, and the root mean square error(RMSE) and the sum of absolute error(SAE) decreased by 3.0% and 11.4%, respectively. For the ratio vegetation index(RVI) regression model, compared with that of L8, the R2 of S2 increased by 26.0%, and the RMSE and SAE decreased by 8.0% and 20.0%, respectively. When the pixel dichotomy model was used, compared with that of L8, the RMSE of S2 decreased by 21.3%, and the SAE decreased by 26.9%. Overall, S2 performed better than L8 in terms of FVC inversion. Additionally, in this paper, we develop a verified scheme based on UAV data in combination with the object-based classification method. This scheme is feasible and sufficiently robust for building relationships between field data and inversion results from satellite data. Further, the synergy of multi-source sensors(especially UAVs and satellites) is a potential effective way to estimate and evaluate regional ecological environmental parameters(FVC). 展开更多
关键词 fractional vegetation cover (FVC) Sentinel-2A (S2) unmanned AERIAL vehicle (UAV)image PIXEL DICHOTOMY MODEL regression MODEL
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Spatial modelling of deforestation in Romanian Carpathian Mountains using GIS and Logistic Regression
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作者 Gheorghe KUCSICSA Cristina DUMITRIC? 《山地科学学报:英文版》 SCIE CSCD 2019年第5期1005-1022,共18页
Deforestation process represents a wide concern mainly in the mountain environments due to its role in global warming, biodiversity loss, land degradation and natural hazards occurrence. Thus, the present study is foc... Deforestation process represents a wide concern mainly in the mountain environments due to its role in global warming, biodiversity loss, land degradation and natural hazards occurrence. Thus, the present study is focused on the largest afforested landform unit of Romania and, consequently, the most affected area by forest losses: Carpathian Mountains. The main goal of the paper is to examine and analyze the various explanatory variables associated with deforestation process and to model the probability of deforestation using GIS spatial analysis and logistic regression. The forest cover for 1990 and 2012, derived from CORINE Land Cover(CLC) database, were used to quantify historical forest cover change included in the modelling. To explain the biophysical and anthropogenic effects, this study considered several explanatory factors related to local topography, forest cover pattern, accessibility, urban growth and population density. Using ROC(Receiver Operating Characteristic) and 500 controlling sampling points, the statistical and spatial validations were assessed in order to evaluate the performance of the resulted data. The analysis showed that the area experienced a continuous forest cover change, leading to the loss of over 250,000 ha of forested area during the period 1990–2012. The most significant influence of the explanatory factors of deforestation were noticed in case of distance to forest edge(β=–4.215), forest fragmentation(β=2.231), slope declivity(β=–1.901), elevation(β=1.734) and distance to roads(β=–1.713). The statistical and spatial validation indicates a good accuracy of the model with reasonably AUC(0.736) and Kappa(0.739) values. The model’s results suggest an intensification of the deforestation process in the area, designing numerous new clusters with high probability in the Apuseni Mountains, northern and central part of the Eastern Carpathians, western part of the Southern Carpathians and northern part of the Banat Mountains. The study could represent a useful outcome to 展开更多
关键词 DEFORESTATION PROBABILITY Romanian CARPATHIANS LOGISTIC Regression
Monte Carlo sampling for error propagation in linear regression and applications in isochron geochronology
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作者 Yang Li Shuang Zhang +4 位作者 Richard Hobbs Camila Caiado Adam D.Sproson David Selby Alan D.Rooney 《科学通报:英文版》 SCIE EI CSCD 2019年第3期189-197,共9页
Geochronology is essential for understanding Earth’s history. The availability of precise and accurate isotopic data is increasing;hence it is crucial to develop transparent and accessible data reduction techniques a... Geochronology is essential for understanding Earth’s history. The availability of precise and accurate isotopic data is increasing;hence it is crucial to develop transparent and accessible data reduction techniques and tools to transform raw mass spectrometry data into robust chronological data. Here we present a Monte Carlo sampling approach to fully propagate uncertainties from linear regressions for isochron dating. Our new approach makes no prior assumption about the causes of variability in the derived chronological results and propagates uncertainties from both experimental measurements(analytical uncertainties) and underlying assumptions(model uncertainties) into the final age determination.Using synthetic examples, we find that although the estimates of the slope and y-intercept(hence age and initial isotopic ratios) are comparable between the Monte Carlo method and the benchmark‘‘Isoplot' algorithm, uncertainties from the later could be underestimated by up to 60%, which are likely due to an incomplete propagation of model uncertainties. An additional advantage of the new method is its ability to integrate with geological information to yield refined chronological constraints. The new method presented here is specifically designed to fully propagate errors in geochronological applications involves linear regressions such as Rb-Sr, Sm-Nd, Re-Os, Pt-Os, Lu-Hf, U-Pb(with discordant points),Pb-Pb and Ar-Ar. 展开更多
关键词 LINEAR regression ISOCHRON GEOCHRONOLOGY UNCERTAINTY PROPAGATION MONTE Carlo Isoplot
Advanced reliability analysis of slopes in spatially variable soils using multivariate adaptive regression splines 预览
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作者 Leilei Liu Shaohe Zhang +1 位作者 Yung-Ming Cheng Li Liang 《地学前缘:英文版》 CAS CSCD 2019年第2期671-682,共12页
This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the infl... This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the influences of the multiscale spatial variability of soil properties on the probability of failure(P_f) of the slopes. In the proposed approach, the relationship between the factor of safety and the soil strength parameters characterized with spatial variability is approximated by the MARS, with the aid of Karhunen-Loeve expansion. MCS is subsequently performed on the established MARS model to evaluate Pf.Finally, a nominally homogeneous cohesive-frictional slope and a heterogeneous cohesive slope, which are both characterized with different spatial variabilities, are utilized to illustrate the proposed approach.Results showed that the proposed approach can estimate the P_f of the slopes efficiently in spatially variable soils with sufficient accuracy. Moreover, the approach is relatively robust to the influence of different statistics of soil properties, thereby making it an effective and practical tool for addressing slope reliability problems concerning time-consuming deterministic stability models with low levels of P_f.Furthermore, disregarding the multiscale spatial variability of soil properties can overestimate or underestimate the P_f. Although the difference is small in general, the multiscale spatial variability of the soil properties must still be considered in the reliability analysis of heterogeneous slopes, especially for those highly related to cost effective and accurate designs. 展开更多
关键词 SLOPE stability Efficient reliability analysis Spatial VARIABILITY RANDOM field MULTIVARIATE adaptive regression splines Monte Carlo simulation
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上海市社区2型糖尿病视网膜病变患者一年随访调查
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作者 秦飞 施榕 +10 位作者 贾丽丽 江华 冯易 张胜冰 宋道平 蒋玉立 顾文娟 彭云 程慧琴 娄洁琼 龙雯 《中华全科医师杂志》 2019年第6期529-534,共6页
目的探索上海市社区2型糖尿病视网膜病变(DR)患者不同转归结局及其影响因素。方法2015年10月至2016年4月,用目标抽样与整群随机抽样结合的方法,抽取上海市花木、金杨、三林、殷行、四平、大桥6家社区卫生服务中心管理的533例2型糖尿病D... 目的探索上海市社区2型糖尿病视网膜病变(DR)患者不同转归结局及其影响因素。方法2015年10月至2016年4月,用目标抽样与整群随机抽样结合的方法,抽取上海市花木、金杨、三林、殷行、四平、大桥6家社区卫生服务中心管理的533例2型糖尿病DR患者进行随访,收集患者的人口学信息、体格检查、实验室检测及眼底检查结果,进行DR诊断分级,分析患者的DR不同转归结局,采用有序logistic回归模型探索DR的影响因素。结果1年后,478例患者完成随访,女性占58.6%(280/478),男性占41.4%(198/478)。患者年龄(64±7)岁,病程(8.85±4.20)年。35例病情减轻,好转率为7.3%(35/478);29例病情加重,进展率为6.1%(29/478)。有序logistic回归分析发现,年龄(OR=0.197,95%CI:0.056~0.699)、BMI(OR=0.383,95%CI:0.171~0.856)、糖化血红蛋白(HbA1c)(OR=0.287,95%CI:0.102~0.803)、TG(OR=0.541,95%CI:0.295~0.991)、尿微量清蛋白与尿肌酐比值(ACR)(OR=0.218,95%CI:0.066~0.720)是患者DR病情发生不同转归结局的影响因素(均P<0.05)。结论DR患者的转归结局与年龄、BMI、血糖、血脂以及肾脏功能密切相关,降低BMI、控制血糖、血脂以及维持正常肾脏功能对防止DR病情加重以及促进DR病情好转具有重要意义。 展开更多
关键词 糖尿病 2型 糖尿病视网膜病变 随访研究 转归 影响因素
Effects of disparity distribution on visual comfort for multiple objects of stereoscopic images 预览
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作者 苏志斌 Li Dongrui +1 位作者 Zou Fangju Ren Hui 《高技术通讯:英文版》 CAS 2019年第1期42-47,共6页
With the development of stereoscopic technology, more attention is attracted on the stereoscopic three-dimensional (S3D) content and service, and researches on images and videos have emerged in large numbers. This pap... With the development of stereoscopic technology, more attention is attracted on the stereoscopic three-dimensional (S3D) content and service, and researches on images and videos have emerged in large numbers. This paper focuses mainly on visual comfort affected by characteristics of disparity for multiple objects. To find the relationship between disparity distribution and visual comfort perception, several subject evaluation experiments are done. The study contains two spatial distribution types of disparity: 1) only one of the foreground objects has zero disparity;2) one of the foreground objects has positive disparity, while the other one has negative disparity. The experimental results and relative regression analysis provide appropriate relationship between disparity distribution and visual comfort for both conditions, which is significant to meet the applicant field in S3D content acquisition, display adjustment and quality evaluation. 展开更多
关键词 DISPARITY DISTRIBUTION DISPARITY MAGNITUDE STEREOSCOPIC IMAGES visual COMFORT regression analyses
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论格非小说对精英传统的回归与创新 预览
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作者 韩再彬 《红河学院学报》 2019年第1期91-94,共4页
格非作为先锋小说极具代表的实力派作家,早期以先锋小说蜚声文坛,随着现实主义题材《江南三部曲》《望春风》等小说的问世而文囿四方。通览格非的小说历程和小说叙事风格,以《欲望的旗帜》为临界,比较前后期的小说,无论是表达主题、叙... 格非作为先锋小说极具代表的实力派作家,早期以先锋小说蜚声文坛,随着现实主义题材《江南三部曲》《望春风》等小说的问世而文囿四方。通览格非的小说历程和小说叙事风格,以《欲望的旗帜》为临界,比较前后期的小说,无论是表达主题、叙事风格,还是小说语言的构造,都带有明显地转向。格非以精英主义立场写作,并在后期小说创作中有意地向传统古典文学靠拢和回归。然而又不拘囿陈规,凸显出中国古典小说的现代性地表达。因此,对精英传统的回归与创新共同构成了格非小说创作的整体风貌和小说肌理。 展开更多
关键词 格非 精英传统 回归 创新
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Reliability-based design in rock engineering:Application of Bayesian regression methods to rock strength data 预览
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作者 Nezam Bozorgzadeh John P.Harrison 《岩石力学与岩土工程学报:英文版》 CSCD 2019年第3期612-627,共16页
Reliability-based design (RBD) is being adopted by geotechnical design codes worldwide, and it is therefore necessary that rock engineering practice evolves to embrace RBD. This paper examines the Hoek-Brown (H-B) str... Reliability-based design (RBD) is being adopted by geotechnical design codes worldwide, and it is therefore necessary that rock engineering practice evolves to embrace RBD. This paper examines the Hoek-Brown (H-B) strength criterion within the RBD framework, and presents three distinct analyses using a Bayesian approach. Firstly, a compilation of intact compressive strength test data for six rock types is used to examine uncertainty and variability in the estimated H-B parameters m and σc, and corresponding predicted axial strength. The results suggest that within- and between-rock type variabilities are so large that these parameters need to be determined from rock testing campaigns, rather than reference values being used. The second analysis uses an extensive set of compressive and tensile (both direct and indirect) strength data for a granodiorite, together with a new Bayesian regression model, to develop joint probability distributions of m and σc suitable for use in RBD. This analysis also shows how compressive and indirect tensile strength data may be robustly used to fit an H-B criterion. The third analysis uses the granodiorite data to investigate the important matter of developing characteristic strength criteria. Using definitions from Eurocode 7, a formal Bayesian interpretation of characteristic strength is proposed and used to analyse strength data to generate a characteristic criterion. These criteria are presented in terms of characteristic parameters mk and σck, the values of which are shown to depend on the testing regime used to obtain the strength data. The paper confirms that careful use of appropriate Bayesian statistical analysis allows the H-B criterion to be brought within the framework of RBD. It also reveals that testing guidelines such as the International Society for Rock Mechanics and Rock Engineering (ISRM) suggested methods will require modification in order to support RBD. Importantly, the need to fully understand the implications of uncertainty in nonlinear strength criteria i 展开更多
关键词 Reliability-based design(RBD) Hoek-Brown(HeB)criterion BAYESIAN regression Indirect TENSILE STRENGTH Characteristic STRENGTH CRITERION
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单眼一退一缩术式矫正集合不足型间歇性外斜视短期效果分析 预览
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作者 宋金鑫 马卫平 +2 位作者 尹妮 陈丽丽 邢咏新 《国际眼科杂志》 CAS 北大核心 2019年第7期1252-1255,共4页
目的:观察一退一缩术式对集合不足型间歇性外斜视的效果和术后回退程度。方法:对45例集合不足型间歇性外斜视患者由同一术者进行单眼一退一缩术式后,检查术后1d,2wk的斜视度,并进行统计分析。结果:集合不足型间歇性外斜视患者45例进行... 目的:观察一退一缩术式对集合不足型间歇性外斜视的效果和术后回退程度。方法:对45例集合不足型间歇性外斜视患者由同一术者进行单眼一退一缩术式后,检查术后1d,2wk的斜视度,并进行统计分析。结果:集合不足型间歇性外斜视患者45例进行单眼一退一缩术式后,术后1d,视远平均过矫8.27±7.17PD,视近平均过矫2.40±8.86PD,术后2wk视远平均欠矫1.18±6.98PD,视近平均欠矫4.36±7.83PD。术后2wk内,视远平均回退9.45±6.40PD,视近平均回退6.77±7.92PD。视远及视近回退呈正相关。术后2wk视远视近斜视度差异(3.18±5.60PD)较术前(7.65±6.55PD)明显减小,两者呈正相关。结论:集合不足型间歇性外斜视患者适合一退一缩术式,适当加大内直肌手术量可减少术后远近斜视度的差异,且不改变患者内外直肌的张力状态。术后视远视近回退呈同步状态,视远约回退10PD,术后近期过矫10PD可有利于远期正位。 展开更多
关键词 间歇性外斜视 集合不足 术后回退 一退一缩 过矫
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An Innovated Integrated Model Using Singular Spectrum Analysis and Support Vector Regression Optimized by Intelligent Algorithm for Rainfall Forecasting 预览
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作者 Weide Li Juan Zhang 《自主智能(英文)》 2019年第1期46-55,共10页
Rainfall forecasting is becoming more and more significant and precipitation anomalies would lead to droughts and floods disasters.However,because of the complexity and non-stationary of rainfall data,it is difficult ... Rainfall forecasting is becoming more and more significant and precipitation anomalies would lead to droughts and floods disasters.However,because of the complexity and non-stationary of rainfall data,it is difficult to forecast.In this paper,a novel hybrid model to forecast rainfall is developed by incorporating singular spectrum analysis (SSA) and dragonfly algorithm (DA) into support vector regression (SVR) method.Firstly,SSA is used for extracting the trend components of the hydrological data.Then,SVR is utilized to deal with the volatility and irregularity of the precipitation series.Finally,the parameter of SVR is optimized by DA.The proposed SSA-DA-SVR method is used to forecast the monthly precipitation for Songbai,Panshui,Lanma and Jiulongchi stations.To validate the efficiency of the method,four compared models,DA-SVR,SSA-GWO-SVR,SSA-PSO-SVR and SSA-CS-SVR are established.The result shows that the proposed method has the best performance among all five models,and its prediction has high precision and accuracy. 展开更多
关键词 Prediction PRECIPITATION SINGULAR SPECTRUM Analysis Support VECTOR Regression INTELLIGENT Algorithm
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Using random-parameter and fixed-parameter ordered models to explore temporal stability in factors affecting drivers’ injury severity in single-vehicle collisions
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作者 Essam Dabbour Murtaza Haider Eman Diaa 《交通运输工程学报(英文版)》 CSCD 2019年第2期132-146,共15页
Understanding the temporal stability in the factors influencing drivers’ injury severity in single-vehicle collisions would help evaluating the effectiveness of implementing different safety treatments so that resear... Understanding the temporal stability in the factors influencing drivers’ injury severity in single-vehicle collisions would help evaluating the effectiveness of implementing different safety treatments so that researchers could understand whether any safety improvements,observed after applying a certain safety treatment, are attributed to the specific treatment or simply attributed to the temporal instability of the factors being addressed. This study investigates the temporal stability of the factors affecting drivers’ injury severity in singlevehicle collisions involving light-duty vehicles. The study is based on utilizing ordinal regression modeling to analyze the severity of drivers’ injuries in all police-reported lightduty single-vehicle collisions that occurred in North Carolina from January 1, 2007, to December 31, 2013. A separate regression model was estimated for each year so that statistical significance of each risk factor may be compared over the years. The study also estimated random-parameter(mixed) ordered logit models to explore the heterogeneity in data. The most significant factor that was found to increase the severity of drivers’ injuries in light-duty single-vehicle collisions is driving under the influence of alcohol or illicit drugs. Other significant factors, in decreasing order in terms of their significance, include driving on a highway curve, exceeding speed limit, lighting conditions, the age of the driver, and the age of the vehicle. In contrast, there were six factors that were found to be significant in only some years and not in all years. These six temporally unstable factors include the use of seatbelt, driver’s gender, rural highways, undivided highways, the type of the light-duty vehicle, and weather and road surface conditions. These same factors were found by other previous research studies to be significant and stable predictors of drivers’ injury severity in single-vehicle collisions. 展开更多
关键词 Drivers’ injury severity Single-vehicle collisions ORDINAL regression MODELS Mixed logit MODELS Temporal stability
An investigation of influential factors of downgrade truck crashes:A logistic regression approach
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作者 Milhan Moomen Mahdi Rezapour Khaled Ksaibati 《交通运输工程学报(英文版)》 CSCD 2019年第2期185-195,共11页
Truck crash occurrence causes extensive damage to lives and property. Truck crashes on downgrades exacerbate these costs due to the likelihood of a runaway being involved.Highway agencies have continuously sought engi... Truck crash occurrence causes extensive damage to lives and property. Truck crashes on downgrades exacerbate these costs due to the likelihood of a runaway being involved.Highway agencies have continuously sought engineering measures to reduce the incidence of such crashes. However, most past studies on truck crashes have focused on level roadway sections of highways without considering the effects of downgrades. The difference in geometric characteristics of downgrades and the mechanics of truck operations on such sections mean different factors may be at play in contrast to level roadway sections.This paper investigated the factors influencing truck crashes on downgrades;an attempt to fill in some of the research gaps. An empirical analysis of factors affecting truck crashes on two-lane downgrade roadways in Wyoming was carried out using a binary logistic regression technique. After calibrating the model, the effect of each significant variable was determined using theoretical concepts established in previous studies and engineering intuition. Crash factors including driver gender and age, weather, lighting and road conditions, number of crest curves, crash type, number of driveways, day of week and posted speed limit were found to be significant. The results of the study offer new understandings into how the identified factors influence truck crashes on downgrades. 展开更多
关键词 HIGHWAY safety TRUCK crashes Downgrades crashes CRASH FACTORS LOGISTIC regression
Assessment of biomass and net primary productivity of a dry tropical forest using geospatial technology 预览
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作者 Tarun Kumar Thakur S.L.Swamy +1 位作者 Arvind Bijalwan Mammohan J.R.Dobriyal 《林业研究:英文版》 CAS CSCD 2019年第1期157-170,共14页
This study quantifies biomass,aboveground and belowground net productivity,along with additional environmental factors over a 2–3 year period in Barnawapara Sanctuary of Chhattisgarh,India through satellite remotesen... This study quantifies biomass,aboveground and belowground net productivity,along with additional environmental factors over a 2–3 year period in Barnawapara Sanctuary of Chhattisgarh,India through satellite remotesensing and GIS techniques.Ten sampling quadrates 20×20,5×5 and 1×1 m were randomly laid for overstorey(OS),understorey(US)and ground vegetation(GS),respectively.Girth of trees was measured at breast height and collar diameters of shrubs and herbs at 0.1 m height.Biomass was estimated using allometric regression equations and herb biomass by harvesting.Net primary productivity(NPP)was determined by summing biomass increment and litter crop values.Aspect and slope influenced the vegetation types,biomass and NPP in different forests.Standing biomass and NPP varied from 18.6 to 101.5 Mg ha^-1 and 5.3 to 12.7 Mg ha^-1 a^-1,respectively,in different forest types.The highest biomass was found in dense mixed forest,while net production recoded in Teak forests.Both were lowest in degraded mixed forests of different forest types.OS,US and GS contributed 90.4,8.7 and 0.7%,respectively,for the total mean standing biomass in different forests.This study developed spectral models for the estimation of biomass and NPP using Normalized Difference Vegetation Index and other vegetation indices.The study demonstrated the potential of geospatial tools for estimation of biomass and net productivity of dry tropical forest ecosystem. 展开更多
关键词 ALLOMETRIC regression equations Fine root BIOMASS LITTER FALL LAI NDVI SPECTRAL models
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中国东北地区人为活动对森林景观格局及鹿科动物生境的影响
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作者 吴文 李月辉 +2 位作者 胡远满 常禹 熊在平 《地理学报:英文版》 SCIE CSCD 2019年第7期1098-1112,共15页
Species abundance and habitat distribution are two important aspects of species conservation studies and both are affected by similar environmental factors. Forest resource inventory data in 2010 were used to evaluate... Species abundance and habitat distribution are two important aspects of species conservation studies and both are affected by similar environmental factors. Forest resource inventory data in 2010 were used to evaluate the patterns of habitat for target species of Cervidae in six typical forestry bureaus of the Yichun forest area in the Lesser Xing’an Mountains, northeastern China. A habitat suitability index(HSI) model was used based on elevation, slope, aspect, vegetation and age of tree. These five environmental factors were selected by boosted regression tree(BRT) analysis from 14 environmental variables collected during field surveys. Changes in habitat caused by anthropogenic activities mainly involving settlement and road factors were also considered. The results identified 1780.49 km2 of most-suitable and 1770.70 km2 of unsuitable habitat areas under natural conditions, covering 16.38% and 16.29% of the entire study area, respectively. The area of most-suitable habitat had been reduced by 4.86% when human interference was taken into account, whereas the unsuitable habitat area had increased by 11.3%, indicating that anthropogenic disturbance turned some potential habitats into unsuitable ones. Landscape metrics indicated that average patch area declined while patch density and edge density increased. This suggests that as habitat becomes fragmented and its quality becomes degraded by human activities, cervid populations will be threatened with extirpation. The study helped identify the spatial extent of habitat influenced by anthropogenic interference for the local cervid population. As cervid species clearly avoid human activities, more attention should be paid on considering the way and intensity of human activities for habitat management as fully as possible. 展开更多
关键词 CERVIDAE boosted regression tree HABITAT SUITABILITY assessment LANDSCAPE pattern Lesser Xing'an MOUNTAINS
Temporal variability of visibility and its parameterizations in Ningbo,China
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作者 Jingjing Zhang Lei Tong +4 位作者 Chenghui Peng Huiling Zhang Zhongwen Huang Jun He Hang Xiao 《环境科学学报:英文版》 SCIE EI CAS CSCD 2019年第3期372-382,共11页
Simultaneous and continuous measurements of visibility, meteorological parameters and air pollutants were carried out at a suburban site in Ningbo from June 1, 2013 to May 31,2015. The characteristics of visibility an... Simultaneous and continuous measurements of visibility, meteorological parameters and air pollutants were carried out at a suburban site in Ningbo from June 1, 2013 to May 31,2015. The characteristics of visibility and their relationships with air pollutants and meteorological factors were investigated using multiple statistical methods. Daily visibility ranged from 0.6 to 34.1 km, with a mean value of 11.8 km. During the 2-year experiment,43.4% of daily visibility was found to be less than 10.0 km and only 9.2% was greater than 20.0 km. Visibility was lower in winter with a frequency of 53.4% in the range of 0.0–5.0 km.Annual visibility had an obvious diurnal variation, with the lowest and highest visibility being 7.5 km at approximately 06:00 local time and 15.6 km at approximately 14:00 local time, respectively. Multiple correspondence analysis(MCA) indicated that the different ranges of visibility were significantly affected by different levels of pollutants and meteorological conditions. Based on the analyses, visibility was found to be an exponential function of PM2.5 concentrations within a certain range of relative humidity. Thus, nonlinear models combining multiple linear regressions with exponential regression were subsequently developed using the data collected from June 2014 to May 2015, and the data from June 2013 to May 2014 was used to evaluate the performance of the model. It was demonstrated that the derived models can quantitatively describe the relationships between visibility, air quality and meteorological parameters in Ningbo. 展开更多
关键词 VISIBILITY MULTIPLE CORRESPONDENCE analysis(MCA) MULTIPLE NON-LINEAR regression
Effect of the Formulation of Sodium Activation Solutions on the Setting Time of Metakaolin Based Geopolymers 预览
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作者 Lahlou Nouha Ouazzani Touhami Mohamed +1 位作者 Moussa Redouane Hattaf Rabii 《材料科学与工程:中英文B版》 2019年第1期6-12,共7页
Geopolymer materials today represent innovative products,used frequently as a substitute for cementitious traditional materials.They are obtained by the action of an alkaline activation solution(composed of mainly of ... Geopolymer materials today represent innovative products,used frequently as a substitute for cementitious traditional materials.They are obtained by the action of an alkaline activation solution(composed of mainly of silicon dioxide(SiO2)and sodium hydroxide(NaOH)and water)on a powder natural or synthetic aluminosilicates.In this work,we seek to highlight the effect of the percentage of sodium dioxide firstly,on the evolution of the viscosity of the alkali-activated solution and secondly,on the evolution of the viscosity of geopolymeric solution.Another aspect of this work is the determination of the effect of this percentage on the kinetics that characterize the start of the percolation phenomenon(transition from the fresh state to the hardened state).At last result concerns the impact of temperature on this transition.This contribution consolidates the control protocols for the formulation of geopolymers and allows the optimization of the processes of their exploitation. 展开更多
关键词 SODIUM ACTIVATION SOLUTIONS GEOPOLYMER METAKAOLIN setting time rheological behavior polynomial regression
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Multivariable regression model for Fox depth correction factor
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作者 Ravi Kant MITTAL Sanket RAWAT Piyush BANSAL 《结构与土木工程前沿:英文版》 EI CSCD 2019年第1期103-109,共7页
This paper presents a simple and efficient equation for calculating the Fox depth correction factor used in computation of settlement reduction due to foundation embedment.Classical solution of Boussinesq theory was u... This paper presents a simple and efficient equation for calculating the Fox depth correction factor used in computation of settlement reduction due to foundation embedment.Classical solution of Boussinesq theory was used originally to develop the Fox depth correction factor equations which were rather complex in nature.The equations were later simplified in the form of graphs and tables and referred in various international code of practices and standard texts for an unsophisticated and quick analysis.However,these tables and graphs provide the factor only for limited values of the input variables and hence again complicates the process of automation of analysis.Therefore,this paper presents a non-linear regression model for the analysis of effect of embedment developed using "IBM Statistical Package for the Social Sciences" software.Through multiple iterations,the value of coefficient of determination is found to reach 0.987.The equation is straightforward,competent and easy to use for both manual and automated calculation of the Fox depth correction factor for wide range of input values.Using the developed equation,parametric study is also conducted in the later part of the paper to analyse the extent of effect of a particular variable on the Fox depth factor. 展开更多
关键词 SETTLEMENT EMBEDMENT FOX DEPTH correction FACTOR regression MULTIVARIABLE
基于LSTM神经网络模型的交通事故预测 预览
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作者 张志豪 杨文忠 +2 位作者 袁婷婷 李东昊 王雪颖 《计算机工程与应用》 CSCD 北大核心 2019年第14期249-253,259共6页
道路交通事故是道路交通安全水平的具体体现,为使预测数据更科学地为交通管理系统提供决策。提出建立基于LSTM(Long Short-Term Memory)神经网络的交通事故模型,训练交通事故相关的数据,对交通安全水平的指标进行预测。经过与传统回归... 道路交通事故是道路交通安全水平的具体体现,为使预测数据更科学地为交通管理系统提供决策。提出建立基于LSTM(Long Short-Term Memory)神经网络的交通事故模型,训练交通事故相关的数据,对交通安全水平的指标进行预测。经过与传统回归模型和传统神经网络模型进行实验对比,实验显示LSTM拟合效果最佳,另外LSTM模型对同一趋势上的预测效果有明显优势。通过使用LSTM模型捕获数据中存在的时序依赖关系,能够更准确地对交通事故安全水平进行预测,使交通管理部门制定更加科学准确的决策。 展开更多
关键词 交通事故 神经网络 长短期记忆(LSTM) 预测 回归
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