In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments （data are non-continuous and fragmental ...In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments （data are non-continuous and fragmental in some catchments）, we used non-continuous calibration periods for more independent streamflow data for SIMHYD （simple hydrology） model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization （PSO） method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.展开更多
Anomaly detection has been an active research topic in the field of network intrusion detection for many years. A novel method is presented for anomaly detection based on system calls into the kernels of Unix or Linux...Anomaly detection has been an active research topic in the field of network intrusion detection for many years. A novel method is presented for anomaly detection based on system calls into the kernels of Unix or Linux systems. The method uses the data mining technique to model the normal behavior of a privileged program and uses a variable-length pattern matching algorithm to perform the comparison of the current behavior and historic normal behavior, which is more suitable for this problem than the fixed-length pattern matching algorithm proposed by Forrest et al. At the detection stage, the particularity of the audit data is taken into account, and two alternative schemes could be used to distinguish between normalities and intrusions. The method gives attention to both computational efficiency and detection accuracy and is especially applicable for on-line detection. The performance of the method is evaluated using the typical testing data set, and the results show that it is significantly better than the anomaly detection method based on hidden Markov models proposed by Yan et al. and the method based on fixed-length patterns proposed by Forrest and Hofmeyr. The novel method has been applied to practical hosted-based intrusion detection systems and achieved high detection performance.展开更多
With their widespread utilization, cut-to-length harvesters have become a major source of ‘‘big data’’ for forest management as they constantly capture, and provide a daily flow of, information on log production a...With their widespread utilization, cut-to-length harvesters have become a major source of ‘‘big data’’ for forest management as they constantly capture, and provide a daily flow of, information on log production and assortment over large operational areas. Harvester data afford the calculation of the total log length between the stump and the last cut but not the total height of trees. They also contain the length and end diameters of individual logs but not always the diameter at breast height overbark（DBHOB） of harvested stems largely because of time lapse, operating and processing issues and other system deficiencies. Even when DBHOB is extracted from harvester data, errors and/or bias of the machine measurements due to the variation in the stump height of harvested stems from that specified for the harvester head prior to harvesting and diameter measurement errors may need to be corrected. This study developed（1） a system of equations for estimating DBHOB of trees from diameter overbark（DOB） measured by a harvester head at any height up to 3 m above ground level and（2） an equation to predict the total height of harvested stems in P. radiata plantations from harvester data. To generate the data required for this purpose, cut-to-length simulations of more than 3000 trees with detailed taper measurements were carried out in the computer using the cutting patterns extracted from the harvester data and stump height survey data from clearfall operations. The equation predicted total tree height from DBHOB, total log length and the small end diameter of the top log. Prediction accuracy for total tree height was evaluated both globally over the entire data space and locally within partitioned subspaces through benchmarking statistics. These statistics were better than that of the conventional height-diameter equations for P. radiata found in the literature, even when they incorporated stand age and the average height and diameter of dominant trees in the stand as predictors. So this equation when used with harvester data would outperform the conventional equations in tree height prediction. Tree and stand reconstructions of the harvested forest is the necessary first step to provide the essential link of harvester data to conventional inventory, remote sensing imagery and Li DAR data. The equations developed in this study will provide such a linkage for the most effective combined use of harvester data in predicting the attributes of individual trees, stands and forests, and product recovery for the management and planning of P. radiata plantations in New South Wales, Australia.展开更多
In order to estimate vehicular queue length at signalized intersections accurately and overcome the shortcomings and restrictions of existing studies especially those based on shockwave theory,a new methodology is pre...In order to estimate vehicular queue length at signalized intersections accurately and overcome the shortcomings and restrictions of existing studies especially those based on shockwave theory,a new methodology is presented for estimating vehicular queue length using data from both point detectors and probe vehicles. The methodology applies the shockwave theory to model queue evolution over time and space. Using probe vehicle locations and times as well as point detector measured traffic states,analytical formulations for calculating the maximum and minimum( residual) queue length are developed. The proposed methodology is verified using ground truth data collected from numerical experiments conducted in Shanghai,China. It is found that the methodology has a mean absolute percentage error of 17. 09%,which is reasonably effective in estimating the queue length at traffic signalized intersections. Limitations of the proposed models and algorithms are also discussed in the paper.展开更多
Objective: To measure the hospital operation efficiency, study the correlation between average length of stay and hospital operation efficiency, analyze the importance of shortening average length of stay to the impro...Objective: To measure the hospital operation efficiency, study the correlation between average length of stay and hospital operation efficiency, analyze the importance of shortening average length of stay to the improvement of the hospital operation efficiency and put forward relevant policy suggestion. Methods: Based on China provincial panel data from 2003 to 2012, the hospital operation efficiencies are calculated using Super Efficiency Data Envelopment Analysis model, and the correlation between average length of stay and hospital operation efficiency is tested using Spearman rank correlation coefficient test. Results: From 2003 to 2012, the average of national hospital operation efficiency was increasing slowly and the hospital operations were inefficient in most of the areas. The national hospital operation efficiency is negatively correlated to the average length of stay. Conclusion: Measures should be taken to set average length of stay in a scientific and reasonable way, improve social and economic benefits based on the improvement of efficiency.展开更多
Removal of the length ef fect in otolith shape analysis for stock identification using length scaling is an important issue; however, few studies have attempted to investigate the ef fectiveness or weakness of this me...Removal of the length ef fect in otolith shape analysis for stock identification using length scaling is an important issue; however, few studies have attempted to investigate the ef fectiveness or weakness of this methodology in application. The aim of this study was to evaluate whether commonly used size scaling methods and normalized elliptic Fourier descriptors(NEFDs) could ef fectively remove the size ef fect of fish in stock discrimination. To achieve this goal, length groups from two known geographical stocks of yellow croaker, L arimichthys polyactis, along the Chinese coast(five groups from the Changjiang River estuary of the East China Sea and three groups from the Bohai Sea) were subjected to otolith shape analysis. The results indicated that the variation of otolith shape caused by intra-stock fish length might exceed that due to inter-stock geographical separation, even when otolith shape variables are standardized with length scaling methods. This variation could easily result in misleading stock discrimination through otolith shape analysis. Therefore, conclusions about fish stock structure should be carefully drawn from otolith shape analysis because the observed discrimination may primarily be due to length ef fects, rather than dif ferences among stocks. The application of multiple methods, such as otoliths shape analysis combined with elemental fingering, tagging or genetic analysis, is recommended for sock identification.展开更多
Network congestion, one of the challenging tasks in communication networks, leads to queuing delays, packet loss, or the blocking of new connections. In this study, a data portal is considered as an application-based ...Network congestion, one of the challenging tasks in communication networks, leads to queuing delays, packet loss, or the blocking of new connections. In this study, a data portal is considered as an application-based network, and a cognitive method is proposed to deal with congestion in this kind of network. Unlike previous methods for congestion control, the proposed method is an effective approach for congestion control when the link capacity and information inquiries are unknown or variable. Using sufficient training samples and the current value of the network parameters, available bandwidth is adjusted to distribute the bandwidth among the active flows. The proposed cognitive method was tested under such situations as unexpected variations in link capacity and oscillatory behavior of the bandwidth. Based on simulation results, the proposed method is capable of adjusting the available bandwidth by tuning the queue length, and provides a stable queue in the network.展开更多
Rapid progress in information technology has come to enable us to store all the information in a hospital information system,including management data,patient records,discharge summary and laboratory data.Although the...Rapid progress in information technology has come to enable us to store all the information in a hospital information system,including management data,patient records,discharge summary and laboratory data.Although the reuse of those data has not started,it has been expected that the stored data will contribute to analysis of hospital management.In this paper,the discharge summary of Chiba University Hospital,which has been stored since 1980's were analyzed to characterize the university hospital.The results show several interesting results,which suggests that the reuse of stored data will give a powerful tool to support a long-period management of a university hospital.展开更多
目的:分析口腔颌面部间隙感染(oral and maxillofacial space infection,OMSI)患者住院时间延长的危险因素,建立风险预测模型,为临床干预及管理提供参考。方法:回顾性收集2019年7月—2023年7月在徐州医科大学附属医院收治的265例OMSI患...目的:分析口腔颌面部间隙感染(oral and maxillofacial space infection,OMSI)患者住院时间延长的危险因素,建立风险预测模型,为临床干预及管理提供参考。方法:回顾性收集2019年7月—2023年7月在徐州医科大学附属医院收治的265例OMSI患者。以住院时间的第75百分位数为分界点,分为住院时间延长组和正常组,比较2组患者术前临床资料的差异,通过Lasso回归和多因素logistic回归分析影响患者住院时间延长的相关因素,并基于此建立一种新型OMSI住院时间延长的风险评估模型,结合受试者工作特征曲线、Hosmer-Lemeshow校准曲线和临床决策曲线对模型进行评价。采用SPSS 26.0软件包和R语言4.2.2对数据进行统计学分析。结果:将Lasso回归筛选出回归系数不为零的变量纳入多因素logistic回归,分析结果显示,基础疾病(OR=2.43,95%CI:1.25~4.70)、间隙数目(OR=1.67,95%CI:1.30~2.14)、纤维蛋白原(OR=1.31,95%CI:1.08~1.60)、IL-6(OR=1.01,95%CI:1.00~1.01)是OMSI患者住院时间延长的独立危险因素(P<0.05)。利用上述独立危险因素构建预测模型,预测评分模型的AUC为0.834(95%CI:0.780~0.888),Hosmer-Lemeshow校准曲线检验提示预测模型拟合优度良好(P=0.4555),决策曲线分析表明模型具有较高的临床实用性。结论:本研究构建的口腔颌面部间隙感染患者住院时间延长风险评估模型具有较好的预测效能,有助于早期识别长期住院的高风险患者,及时采取有效干预措施,减轻患者与医疗机构负担。展开更多
基金supported by the National Basic Research Program of China (the 973 Program,Grant No.2010CB951102)the National Supporting Plan Program of China (Grants No.2007BAB28B01 and 2008BAB42B03)the National Natural Science Foundation of China (Grant No. 50709042),and the Regional Water Theme in the Water for a Healthy Country Flagship
文摘In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments （data are non-continuous and fragmental in some catchments）, we used non-continuous calibration periods for more independent streamflow data for SIMHYD （simple hydrology） model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization （PSO） method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.
基金supported by the National Grand Fundamental Research "973" Program of China (2004CB318109)the National High-Technology Research and Development Plan of China (2006AA01Z452)the National Information Security "242"Program of China (2005C39).
文摘Anomaly detection has been an active research topic in the field of network intrusion detection for many years. A novel method is presented for anomaly detection based on system calls into the kernels of Unix or Linux systems. The method uses the data mining technique to model the normal behavior of a privileged program and uses a variable-length pattern matching algorithm to perform the comparison of the current behavior and historic normal behavior, which is more suitable for this problem than the fixed-length pattern matching algorithm proposed by Forrest et al. At the detection stage, the particularity of the audit data is taken into account, and two alternative schemes could be used to distinguish between normalities and intrusions. The method gives attention to both computational efficiency and detection accuracy and is especially applicable for on-line detection. The performance of the method is evaluated using the typical testing data set, and the results show that it is significantly better than the anomaly detection method based on hidden Markov models proposed by Yan et al. and the method based on fixed-length patterns proposed by Forrest and Hofmeyr. The novel method has been applied to practical hosted-based intrusion detection systems and achieved high detection performance.
基金supported by the Forestry Corporation of New South Wales
文摘With their widespread utilization, cut-to-length harvesters have become a major source of ‘‘big data’’ for forest management as they constantly capture, and provide a daily flow of, information on log production and assortment over large operational areas. Harvester data afford the calculation of the total log length between the stump and the last cut but not the total height of trees. They also contain the length and end diameters of individual logs but not always the diameter at breast height overbark（DBHOB） of harvested stems largely because of time lapse, operating and processing issues and other system deficiencies. Even when DBHOB is extracted from harvester data, errors and/or bias of the machine measurements due to the variation in the stump height of harvested stems from that specified for the harvester head prior to harvesting and diameter measurement errors may need to be corrected. This study developed（1） a system of equations for estimating DBHOB of trees from diameter overbark（DOB） measured by a harvester head at any height up to 3 m above ground level and（2） an equation to predict the total height of harvested stems in P. radiata plantations from harvester data. To generate the data required for this purpose, cut-to-length simulations of more than 3000 trees with detailed taper measurements were carried out in the computer using the cutting patterns extracted from the harvester data and stump height survey data from clearfall operations. The equation predicted total tree height from DBHOB, total log length and the small end diameter of the top log. Prediction accuracy for total tree height was evaluated both globally over the entire data space and locally within partitioned subspaces through benchmarking statistics. These statistics were better than that of the conventional height-diameter equations for P. radiata found in the literature, even when they incorporated stand age and the average height and diameter of dominant trees in the stand as predictors. So this equation when used with harvester data would outperform the conventional equations in tree height prediction. Tree and stand reconstructions of the harvested forest is the necessary first step to provide the essential link of harvester data to conventional inventory, remote sensing imagery and Li DAR data. The equations developed in this study will provide such a linkage for the most effective combined use of harvester data in predicting the attributes of individual trees, stands and forests, and product recovery for the management and planning of P. radiata plantations in New South Wales, Australia.
基金Sponsored by the National Natural Science Foundation of China(Grant No.51138003)
文摘In order to estimate vehicular queue length at signalized intersections accurately and overcome the shortcomings and restrictions of existing studies especially those based on shockwave theory,a new methodology is presented for estimating vehicular queue length using data from both point detectors and probe vehicles. The methodology applies the shockwave theory to model queue evolution over time and space. Using probe vehicle locations and times as well as point detector measured traffic states,analytical formulations for calculating the maximum and minimum( residual) queue length are developed. The proposed methodology is verified using ground truth data collected from numerical experiments conducted in Shanghai,China. It is found that the methodology has a mean absolute percentage error of 17. 09%,which is reasonably effective in estimating the queue length at traffic signalized intersections. Limitations of the proposed models and algorithms are also discussed in the paper.
文摘Objective: To measure the hospital operation efficiency, study the correlation between average length of stay and hospital operation efficiency, analyze the importance of shortening average length of stay to the improvement of the hospital operation efficiency and put forward relevant policy suggestion. Methods: Based on China provincial panel data from 2003 to 2012, the hospital operation efficiencies are calculated using Super Efficiency Data Envelopment Analysis model, and the correlation between average length of stay and hospital operation efficiency is tested using Spearman rank correlation coefficient test. Results: From 2003 to 2012, the average of national hospital operation efficiency was increasing slowly and the hospital operations were inefficient in most of the areas. The national hospital operation efficiency is negatively correlated to the average length of stay. Conclusion: Measures should be taken to set average length of stay in a scientific and reasonable way, improve social and economic benefits based on the improvement of efficiency.
基金Supported by the National Basic Research Program of China(973 Program)(No.2015CB453302)the NSFC-Shandong Joint Fund for Marine Science Research Centre(No.U1606404)the Aoshan Science and Technology Innovation Project(No.2015ASKJ02-04)
文摘Removal of the length ef fect in otolith shape analysis for stock identification using length scaling is an important issue; however, few studies have attempted to investigate the ef fectiveness or weakness of this methodology in application. The aim of this study was to evaluate whether commonly used size scaling methods and normalized elliptic Fourier descriptors(NEFDs) could ef fectively remove the size ef fect of fish in stock discrimination. To achieve this goal, length groups from two known geographical stocks of yellow croaker, L arimichthys polyactis, along the Chinese coast(five groups from the Changjiang River estuary of the East China Sea and three groups from the Bohai Sea) were subjected to otolith shape analysis. The results indicated that the variation of otolith shape caused by intra-stock fish length might exceed that due to inter-stock geographical separation, even when otolith shape variables are standardized with length scaling methods. This variation could easily result in misleading stock discrimination through otolith shape analysis. Therefore, conclusions about fish stock structure should be carefully drawn from otolith shape analysis because the observed discrimination may primarily be due to length ef fects, rather than dif ferences among stocks. The application of multiple methods, such as otoliths shape analysis combined with elemental fingering, tagging or genetic analysis, is recommended for sock identification.
文摘Network congestion, one of the challenging tasks in communication networks, leads to queuing delays, packet loss, or the blocking of new connections. In this study, a data portal is considered as an application-based network, and a cognitive method is proposed to deal with congestion in this kind of network. Unlike previous methods for congestion control, the proposed method is an effective approach for congestion control when the link capacity and information inquiries are unknown or variable. Using sufficient training samples and the current value of the network parameters, available bandwidth is adjusted to distribute the bandwidth among the active flows. The proposed cognitive method was tested under such situations as unexpected variations in link capacity and oscillatory behavior of the bandwidth. Based on simulation results, the proposed method is capable of adjusting the available bandwidth by tuning the queue length, and provides a stable queue in the network.
文摘Rapid progress in information technology has come to enable us to store all the information in a hospital information system,including management data,patient records,discharge summary and laboratory data.Although the reuse of those data has not started,it has been expected that the stored data will contribute to analysis of hospital management.In this paper,the discharge summary of Chiba University Hospital,which has been stored since 1980's were analyzed to characterize the university hospital.The results show several interesting results,which suggests that the reuse of stored data will give a powerful tool to support a long-period management of a university hospital.
文摘目的:分析口腔颌面部间隙感染(oral and maxillofacial space infection,OMSI)患者住院时间延长的危险因素,建立风险预测模型,为临床干预及管理提供参考。方法:回顾性收集2019年7月—2023年7月在徐州医科大学附属医院收治的265例OMSI患者。以住院时间的第75百分位数为分界点,分为住院时间延长组和正常组,比较2组患者术前临床资料的差异,通过Lasso回归和多因素logistic回归分析影响患者住院时间延长的相关因素,并基于此建立一种新型OMSI住院时间延长的风险评估模型,结合受试者工作特征曲线、Hosmer-Lemeshow校准曲线和临床决策曲线对模型进行评价。采用SPSS 26.0软件包和R语言4.2.2对数据进行统计学分析。结果:将Lasso回归筛选出回归系数不为零的变量纳入多因素logistic回归,分析结果显示,基础疾病(OR=2.43,95%CI:1.25~4.70)、间隙数目(OR=1.67,95%CI:1.30~2.14)、纤维蛋白原(OR=1.31,95%CI:1.08~1.60)、IL-6(OR=1.01,95%CI:1.00~1.01)是OMSI患者住院时间延长的独立危险因素(P<0.05)。利用上述独立危险因素构建预测模型,预测评分模型的AUC为0.834(95%CI:0.780~0.888),Hosmer-Lemeshow校准曲线检验提示预测模型拟合优度良好(P=0.4555),决策曲线分析表明模型具有较高的临床实用性。结论:本研究构建的口腔颌面部间隙感染患者住院时间延长风险评估模型具有较好的预测效能,有助于早期识别长期住院的高风险患者,及时采取有效干预措施,减轻患者与医疗机构负担。
