Background: The Emei Shan Liocichla(Liocichla omeiensis) is a globally vulnerable babbler, endemic to southwestern China. We investigated its nest predators, nest-site selection and nest success at the Laojunshan Nati...Background: The Emei Shan Liocichla(Liocichla omeiensis) is a globally vulnerable babbler, endemic to southwestern China. We investigated its nest predators, nest-site selection and nest success at the Laojunshan National Nature Reserve in Sichuan, China in order to identify the precise nesting-habitat requirements of the species, and to test whether the nest-site-selection cues, preferred by the Emei Shan Liocichla, are positively associated with nest success.Methods: We used infrared cameras to determine nest predators. We compared the microhabitat attributes between nest and random sites, as well as successful and failed nests. We used Binary Logistic Regression to determine the most important variables affecting nest-site selection of the Emei Shan Liocichla. We used the nest survival analysis in Program MARK to estimate daily nest survival rates(DSR). Nest success was calculated using the Mayfield method.Results: In total 56 nests were found. The DSR for all nests that contained at least one egg was 0.9564 ± 0.0091(95 % CI 0.9346–0.9711)(n = 40), while the total nest success was 27.5 %. We identified four categories of predators in 10 nest predation events, i.e. squirrels(n = 5), snakes(n = 3), raptors(n = 1) and wasps(n = 1). We found that:(1) nest predation was the primary reason for nest failure of the Emei Shan Liocichla,(2) tree cover, bamboo cover, liana abundance and distance to forest edge or gap were the most important variables affecting nest-site selection of this species, and(3) the nest-site-selection variables we measured appeared not to be positively associated with nest success.Conclusions: Our findings suggest that the Emei Shan Liocichla tended to select nest sites near forest edges or gaps with good concealment and that nest-site selection by this species was nonrandom but not necessarily adaptive. Reducing forest-edge development and protecting bamboo stands should be effective for conservation of this species.展开更多
Changing landscapes and land-use practices are altering habitat for Florida wild turkeys (Meleagris gallopavo osceola). However, an understanding of habitat determinants of nest success is lacking for this unique turk...Changing landscapes and land-use practices are altering habitat for Florida wild turkeys (Meleagris gallopavo osceola). However, an understanding of habitat determinants of nest success is lacking for this unique turkey subspecies, potentially limiting conservation success. We examined female wild turkey nest site selection and nest success at microhabitat and patch levels using logistic regression in an Information-Theoretical framework in Florida, 2008-2010. We captured and radio-equipped adult female turkeys, and followed birds to nests. Nests were monitored to document success, and habitat was measured at multiple levels at nest and random sites. Females selected nest sites in dense vegetation (i.e., increased saw palmetto cover [Serenoa repens] and higher palm stem densities) that may have provided lateral and vertical cover for concealment at the microhabitat level (i.e., area within 7 m of the nest), while selecting for a more open habitat (i.e., decreasing hardwood and conifer stem densities) at the patch level (i.e., area within 28 m of the nest). Similarly, successful nests were in more dense vegetation at the nest site (i.e., increased saw palmetto cover) in an otherwise more open habitat (i.e., lower basal area) than unsuccessful nests. Habitat management that creates patches of dense shrub vegetation such as saw palmetto within an open landscape may be best for Florida wild turkey nesting habitat and success.展开更多
Successful China pro- curement is the result of a comprehensive set of complex and high-ly-specialized processes. Dis- tilling this down to a ＂magical recipe＂ for success is no simple task, and there are no shortcut...Successful China pro- curement is the result of a comprehensive set of complex and high-ly-specialized processes. Dis- tilling this down to a ＂magical recipe＂ for success is no simple task, and there are no shortcuts. However, as a useful reference, two fundamental ingredients for procurement success are： the selection of the right suppliers： and the effective management of chosen suppliers to optimize their performance.展开更多
A groundbreaking method is introduced to leverage machine learn-ing algorithms to revolutionize the prediction of success rates for science fiction films.In the captivating world of the film industry,extensive researc...A groundbreaking method is introduced to leverage machine learn-ing algorithms to revolutionize the prediction of success rates for science fiction films.In the captivating world of the film industry,extensive research and accurate forecasting are vital to anticipating a movie’s triumph prior to its debut.Our study aims to harness the power of available data to estimate a film’s early success rate.With the vast resources offered by the internet,we can access a plethora of movie-related information,including actors,directors,critic reviews,user reviews,ratings,writers,budgets,genres,Facebook likes,YouTube views for movie trailers,and Twitter followers.The first few weeks of a film’s release are crucial in determining its fate,and online reviews and film evaluations profoundly impact its opening-week earnings.Hence,our research employs advanced supervised machine learning techniques to predict a film’s triumph.The Internet Movie Database(IMDb)is a comprehensive data repository for nearly all movies.A robust predictive classification approach is developed by employing various machine learning algorithms,such as fine,medium,coarse,cosine,cubic,and weighted KNN.To determine the best model,the performance of each feature was evaluated based on composite metrics.Moreover,the significant influences of social media platforms were recognized including Twitter,Instagram,and Facebook on shaping individuals’opinions.A hybrid success rating prediction model is obtained by integrating the proposed prediction models with sentiment analysis from available platforms.The findings of this study demonstrate that the chosen algorithms offer more precise estimations,faster execution times,and higher accuracy rates when compared to previous research.By integrating the features of existing prediction models and social media sentiment analysis models,our proposed approach provides a remarkably accurate prediction of a movie’s success.This breakthrough can help movie producers and marketers anticipate a film’s triumph before its release,allowing them to tailor their promotional activities accordingly.Furthermore,the adopted research lays the foundation for developing even more accurate prediction models,considering the ever-increasing significance of social media platforms in shaping individ-uals’opinions.In conclusion,this study showcases the immense potential of machine learning algorithms in predicting the success rate of science fiction films,opening new avenues for the film industry.展开更多
With the rapid development of the information technology （IT） and the more competitive environment of the corporations, IT is not only important for the enterprises tactically but also strategically, We extend the c...With the rapid development of the information technology （IT） and the more competitive environment of the corporations, IT is not only important for the enterprises tactically but also strategically, We extend the concept of the critical success factors （CSF） and Nolan＇s stages theory to identify the IT issues and measure their CSF of the manufacturers in China. We put forward the IT selection matrix based on Nolan＇s stages theory to analyze the IT application in manufacturers in Beijing based on our survey. We analyze the development of IT, IT selection strategy and the CSF influencing the IT growth of manufacturers in China.展开更多
采用全谱建立多元校正模型时,通常计算量大,模型不够稳健,而且模型的预测精度往往也不能达到最优。文章介绍一种新的波长选择方法:采用连续投影算法(successive projections algorithm),并将其集成偏最小二乘(partial least squares)多...采用全谱建立多元校正模型时,通常计算量大,模型不够稳健,而且模型的预测精度往往也不能达到最优。文章介绍一种新的波长选择方法:采用连续投影算法(successive projections algorithm),并将其集成偏最小二乘(partial least squares)多变量校正技术构成SPA-PLS方法,用于谷物小麦近红外光谱波长优化选择及其与水分含量的定量分析。结果表明:在经SPA算法后,光谱波数可削减97.72%,后继的定量校正模型结构得到显著简化,模型的稳健性也大大增强;同时,被选取的波长物理意义明确,模型的解释能力增强,而模型的预测性能也与GA-PLS方法相当。展开更多
酸度是评价砂糖橘品质的重要指标之一,为了消除光谱变量间的共线性影响、减少建模变量以提高校正速度,该文应用连续投影算法(SPA)对砂糖橘总酸近红外光谱无损检测模型进行优化。利用连接点修正方法修正近红外光谱,结合学生化残差图和模...酸度是评价砂糖橘品质的重要指标之一,为了消除光谱变量间的共线性影响、减少建模变量以提高校正速度,该文应用连续投影算法(SPA)对砂糖橘总酸近红外光谱无损检测模型进行优化。利用连接点修正方法修正近红外光谱,结合学生化残差图和模型回归图剔除异常样本,利用SPXY(sample set partitioning based on joint x-y distances)方法划分样本集,最后利用SPA进行变量选择,比较SPA选择的变量建模和全光谱变量PLS模型的预测效果,并分析橘皮对总酸模型的预测精度的影响程度。结果表明,只用了全部2001个变量中的9个变量,整果测定酸度情况下的SPA-MLR模型和SPA-PLS模型的预测精度与全部变量PLS模型的预测精度相当,预测相关系数Rp分别为0.829470,0.837095和0.857299。去皮留果肉测定酸度情况下则优选了13个变量,其SPA-MLR模型和SPA-PLS模型的Rp分别为0.819430、0.825277,均比全光谱变量PLS模型的Rp(0.780146)高,SPA算法提高了去皮留果肉测定酸度情况下的模型预测精度。展开更多
基金supported by the National Natural Science Foundation of China(No.31272330)the Scientific Research Innovation Team Projects of Leshan Normal University
文摘Background: The Emei Shan Liocichla(Liocichla omeiensis) is a globally vulnerable babbler, endemic to southwestern China. We investigated its nest predators, nest-site selection and nest success at the Laojunshan National Nature Reserve in Sichuan, China in order to identify the precise nesting-habitat requirements of the species, and to test whether the nest-site-selection cues, preferred by the Emei Shan Liocichla, are positively associated with nest success.Methods: We used infrared cameras to determine nest predators. We compared the microhabitat attributes between nest and random sites, as well as successful and failed nests. We used Binary Logistic Regression to determine the most important variables affecting nest-site selection of the Emei Shan Liocichla. We used the nest survival analysis in Program MARK to estimate daily nest survival rates(DSR). Nest success was calculated using the Mayfield method.Results: In total 56 nests were found. The DSR for all nests that contained at least one egg was 0.9564 ± 0.0091(95 % CI 0.9346–0.9711)(n = 40), while the total nest success was 27.5 %. We identified four categories of predators in 10 nest predation events, i.e. squirrels(n = 5), snakes(n = 3), raptors(n = 1) and wasps(n = 1). We found that:(1) nest predation was the primary reason for nest failure of the Emei Shan Liocichla,(2) tree cover, bamboo cover, liana abundance and distance to forest edge or gap were the most important variables affecting nest-site selection of this species, and(3) the nest-site-selection variables we measured appeared not to be positively associated with nest success.Conclusions: Our findings suggest that the Emei Shan Liocichla tended to select nest sites near forest edges or gaps with good concealment and that nest-site selection by this species was nonrandom but not necessarily adaptive. Reducing forest-edge development and protecting bamboo stands should be effective for conservation of this species.
文摘Changing landscapes and land-use practices are altering habitat for Florida wild turkeys (Meleagris gallopavo osceola). However, an understanding of habitat determinants of nest success is lacking for this unique turkey subspecies, potentially limiting conservation success. We examined female wild turkey nest site selection and nest success at microhabitat and patch levels using logistic regression in an Information-Theoretical framework in Florida, 2008-2010. We captured and radio-equipped adult female turkeys, and followed birds to nests. Nests were monitored to document success, and habitat was measured at multiple levels at nest and random sites. Females selected nest sites in dense vegetation (i.e., increased saw palmetto cover [Serenoa repens] and higher palm stem densities) that may have provided lateral and vertical cover for concealment at the microhabitat level (i.e., area within 7 m of the nest), while selecting for a more open habitat (i.e., decreasing hardwood and conifer stem densities) at the patch level (i.e., area within 28 m of the nest). Similarly, successful nests were in more dense vegetation at the nest site (i.e., increased saw palmetto cover) in an otherwise more open habitat (i.e., lower basal area) than unsuccessful nests. Habitat management that creates patches of dense shrub vegetation such as saw palmetto within an open landscape may be best for Florida wild turkey nesting habitat and success.
文摘Successful China pro- curement is the result of a comprehensive set of complex and high-ly-specialized processes. Dis- tilling this down to a ＂magical recipe＂ for success is no simple task, and there are no shortcuts. However, as a useful reference, two fundamental ingredients for procurement success are： the selection of the right suppliers： and the effective management of chosen suppliers to optimize their performance.
文摘A groundbreaking method is introduced to leverage machine learn-ing algorithms to revolutionize the prediction of success rates for science fiction films.In the captivating world of the film industry,extensive research and accurate forecasting are vital to anticipating a movie’s triumph prior to its debut.Our study aims to harness the power of available data to estimate a film’s early success rate.With the vast resources offered by the internet,we can access a plethora of movie-related information,including actors,directors,critic reviews,user reviews,ratings,writers,budgets,genres,Facebook likes,YouTube views for movie trailers,and Twitter followers.The first few weeks of a film’s release are crucial in determining its fate,and online reviews and film evaluations profoundly impact its opening-week earnings.Hence,our research employs advanced supervised machine learning techniques to predict a film’s triumph.The Internet Movie Database(IMDb)is a comprehensive data repository for nearly all movies.A robust predictive classification approach is developed by employing various machine learning algorithms,such as fine,medium,coarse,cosine,cubic,and weighted KNN.To determine the best model,the performance of each feature was evaluated based on composite metrics.Moreover,the significant influences of social media platforms were recognized including Twitter,Instagram,and Facebook on shaping individuals’opinions.A hybrid success rating prediction model is obtained by integrating the proposed prediction models with sentiment analysis from available platforms.The findings of this study demonstrate that the chosen algorithms offer more precise estimations,faster execution times,and higher accuracy rates when compared to previous research.By integrating the features of existing prediction models and social media sentiment analysis models,our proposed approach provides a remarkably accurate prediction of a movie’s success.This breakthrough can help movie producers and marketers anticipate a film’s triumph before its release,allowing them to tailor their promotional activities accordingly.Furthermore,the adopted research lays the foundation for developing even more accurate prediction models,considering the ever-increasing significance of social media platforms in shaping individ-uals’opinions.In conclusion,this study showcases the immense potential of machine learning algorithms in predicting the success rate of science fiction films,opening new avenues for the film industry.
文摘With the rapid development of the information technology （IT） and the more competitive environment of the corporations, IT is not only important for the enterprises tactically but also strategically, We extend the concept of the critical success factors （CSF） and Nolan＇s stages theory to identify the IT issues and measure their CSF of the manufacturers in China. We put forward the IT selection matrix based on Nolan＇s stages theory to analyze the IT application in manufacturers in Beijing based on our survey. We analyze the development of IT, IT selection strategy and the CSF influencing the IT growth of manufacturers in China.
文摘采用全谱建立多元校正模型时,通常计算量大,模型不够稳健,而且模型的预测精度往往也不能达到最优。文章介绍一种新的波长选择方法:采用连续投影算法(successive projections algorithm),并将其集成偏最小二乘(partial least squares)多变量校正技术构成SPA-PLS方法,用于谷物小麦近红外光谱波长优化选择及其与水分含量的定量分析。结果表明:在经SPA算法后,光谱波数可削减97.72%,后继的定量校正模型结构得到显著简化,模型的稳健性也大大增强;同时,被选取的波长物理意义明确,模型的解释能力增强,而模型的预测性能也与GA-PLS方法相当。
文摘酸度是评价砂糖橘品质的重要指标之一,为了消除光谱变量间的共线性影响、减少建模变量以提高校正速度,该文应用连续投影算法(SPA)对砂糖橘总酸近红外光谱无损检测模型进行优化。利用连接点修正方法修正近红外光谱,结合学生化残差图和模型回归图剔除异常样本,利用SPXY(sample set partitioning based on joint x-y distances)方法划分样本集,最后利用SPA进行变量选择,比较SPA选择的变量建模和全光谱变量PLS模型的预测效果,并分析橘皮对总酸模型的预测精度的影响程度。结果表明,只用了全部2001个变量中的9个变量,整果测定酸度情况下的SPA-MLR模型和SPA-PLS模型的预测精度与全部变量PLS模型的预测精度相当,预测相关系数Rp分别为0.829470,0.837095和0.857299。去皮留果肉测定酸度情况下则优选了13个变量,其SPA-MLR模型和SPA-PLS模型的Rp分别为0.819430、0.825277,均比全光谱变量PLS模型的Rp(0.780146)高,SPA算法提高了去皮留果肉测定酸度情况下的模型预测精度。
