针对现有数学表达式检索系统中待检索表达式与目标文档之间的语义关联问题,在使用序列化特征提取方法解析La Te X表达式的基础上,提出一种基于Ontology的数学表达式检索方法。运用Ontology建立数学表达式及其概念之间的联系并构建数学...针对现有数学表达式检索系统中待检索表达式与目标文档之间的语义关联问题,在使用序列化特征提取方法解析La Te X表达式的基础上,提出一种基于Ontology的数学表达式检索方法。运用Ontology建立数学表达式及其概念之间的联系并构建数学表达式语义本体库,以达到输入关键词、概念、短语和数学名词可检索数学表达式语义相关文献的目的。实验结果表明,基于Ontology的数学表达式检索方法运用本体概念扩展查询结果集,使得查全率、查准率和扩展率均有一定程度提高。展开更多
Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from i...Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from images, and the description of spatial features on maps.However, little achievements have been made for it by far.In this paper, spatial similarity relation was put forward with the introduction of automated map generalization in the construction of multi-scale map databases;then the definition of spatial similarity relations was presented based on set theory, the concept of spatial similarity degree was given, and the characteristics of spatial similarity were discussed in detail, in-cluding reflexivity, symmetry, non-transitivity, self-similarity in multi-scale spaces, and scale-dependence.Finally a classification system for spatial similarity relations in multi-scale map spaces was addressed.This research may be useful to automated map generalization, spatial similarity retrieval and spatial reasoning.展开更多
It is more difficult to retrieve land surface temperature(LST) from passive microwave remote sensing data than from thermal remote sensing data, because the emissivities in the passive microwave band can change more e...It is more difficult to retrieve land surface temperature(LST) from passive microwave remote sensing data than from thermal remote sensing data, because the emissivities in the passive microwave band can change more easily than those in the thermal infrared band. Thus, it is very difficult to build a stable relationship. Passive microwave band emissivities are greatly influenced by the soil moisture, which varies with time. This makes it difficult to develop a general physical algorithm. This paper proposes a method to utilize multiple-satellite, sensors and resolution coupled with a deep dynamic learning neural network to retrieve the land surface temperature from images acquired by the Advanced Microwave Scanning Radiometer 2(AMSR2), a sensor that is similar to the Advanced Microwave Scanning Radiometer Earth Observing System(AMSR-E). The AMSR-E and MODIS sensors are located aboard the Aqua satellite. The MODIS LST product is used as the ground truth data to overcome the difficulties in obtaining large scale land surface temperature data. The mean and standard deviation of the retrieval error are approximately 1.4° and 1.9° when five frequencies(ten channels, 10.7, 18.7, 23.8, 36.5, 89 V/H GHz) are used. This method can effectively eliminate the influences of the soil moisture, roughness, atmosphere and various other factors. An analysis of the application of this method to the retrieval of land surface temperature from AMSR2 data indicates that the method is feasible. The accuracy is approximately 1.8° through a comparison between the retrieval results with ground measurement data from meteorological stations.展开更多
AIM:To compare non-liquid and clear-liquid diets,and to assess whether the latter is the optimal treatment for mild acute pancreatitis.METHODS:The Cochrane Library,PUBMED,EMBASE,EBM review databases,Science Citation I...AIM:To compare non-liquid and clear-liquid diets,and to assess whether the latter is the optimal treatment for mild acute pancreatitis.METHODS:The Cochrane Library,PUBMED,EMBASE,EBM review databases,Science Citation Index Expanded,and several Chinese databases were searched up to March 2011.Randomized controlled trials(RCTs) that compared non-liquid with clear-liquid diets in patients with mild acute pancreatitis were included.A meta-analysis was performed using available evidence from RCTs.RESULTS:Three RCTs of adequate quality involving a total of 362 participants were included in the final analysis.Compared to liquid diet,non-liquid diet significantly decreased the length of hospitalization [mean difference(MD):1.18,95% CI:0.82-1.55;P﹤0.00001] and total length of hospitalization(MD:1.31,95% CI:0.45-2.17;P = 0.003).The subgroup analysis showed solid diet was more favorable than clear liquid diet in the length of hospitalization,with a pooled MD being-1.05(95% CI:-1.43 to-0.66;P﹤0.00001).However,compared with clear liquid diet,both soft and solid diets did not show any significant differences for recurrence of pain after re-feeding,either alone [relative risk(RR):0.95;95% CI:0.51-1.87;P = 0.88] and(RR:1.22;95% CI:0.69-2.16;P = 0.49),respectively,or analyzed together as non-liquid diet(RR:0.80;95% CI:0.47-1.36;P = 0.41).CONCLUSION:The non-liquid soft or solid diet did not increase pain recurrence after re-feeding,compared with the clear-liquid diet.The non-liquid diet reduced hospitalization.展开更多
Reflectance measurements of both the visible and infrared bands of passive remote sensing sensors are widely used to retrieve aerosol optical depth(AOD) information. This is performed commonly for data obtained over b...Reflectance measurements of both the visible and infrared bands of passive remote sensing sensors are widely used to retrieve aerosol optical depth(AOD) information. This is performed commonly for data obtained over both ocean and land, and these measurements allow for the off line development of a lookup table using radiative transfer models. Owing to molecular and aerosol effects, the reflected light received by the sensor is usually highly polarized. The linear polarization effect may be up to 100%, and the polarization factor of a sensor optical system will change the total intensity as well as the polarization status of the signal reaching the detector. The detector response will be different when the incident light polarization status changes, even if the total intensity remains constant. However, if the polarization calibration is neglected, it will cause obvious errors in the aerosol data retrieval. This is especially true for aerosol optical depth retrieval over an ocean. This measurement relies directly on the reflectance output of the sensor. Cases involving land surfaces are not discussed herein because the inhomogeneous properties conceal the error due to polarization. Taking the 550 and 860 nm bands as examples, the difference between the real top-of-atmosphere(TOA) reflectance and the reflectance reaching the detector is calculated using three different sensor polarization standards according to the Sea-viewing Wide Field-of-view Sensor(Sea Wi FS) and Moderate Resolution Imaging Spectroradiometer(MODIS) standards. The differences in AOD retrieval are also demonstrated using the lookup table developed previously from a vector radiative transfer code. The results reveal that under a normal situation in which the AOD is 0.15, the maximum AOD retrieval error could reach 0.04 in 550 nm but only 0.02 in 860 nm for the dust aerosol model. For the soot aerosol model, the maximum AOD retrieval error is 0.1 in 550 nm and 0.12 in 860 nm, indicating that the lack of polarization calibration will lead to large errors in aerosol retrieval over an ocean.展开更多
文摘针对现有数学表达式检索系统中待检索表达式与目标文档之间的语义关联问题,在使用序列化特征提取方法解析La Te X表达式的基础上,提出一种基于Ontology的数学表达式检索方法。运用Ontology建立数学表达式及其概念之间的联系并构建数学表达式语义本体库,以达到输入关键词、概念、短语和数学名词可检索数学表达式语义相关文献的目的。实验结果表明,基于Ontology的数学表达式检索方法运用本体概念扩展查询结果集,使得查全率、查准率和扩展率均有一定程度提高。
文摘Similarity relation is one of the spatial relations in the community of geographic information science and cartography.It is widely used in the retrieval of spatial databases, the recognition of spatial objects from images, and the description of spatial features on maps.However, little achievements have been made for it by far.In this paper, spatial similarity relation was put forward with the introduction of automated map generalization in the construction of multi-scale map databases;then the definition of spatial similarity relations was presented based on set theory, the concept of spatial similarity degree was given, and the characteristics of spatial similarity were discussed in detail, in-cluding reflexivity, symmetry, non-transitivity, self-similarity in multi-scale spaces, and scale-dependence.Finally a classification system for spatial similarity relations in multi-scale map spaces was addressed.This research may be useful to automated map generalization, spatial similarity retrieval and spatial reasoning.
基金Under the auspices of National Natural Science Foundation of China(No.41571427)National Key Project of China(No.2016YFC0500203)Open Fund of State Key Laboratory of Remote Sensing Science(No.OFSLRSS 201515)
文摘It is more difficult to retrieve land surface temperature(LST) from passive microwave remote sensing data than from thermal remote sensing data, because the emissivities in the passive microwave band can change more easily than those in the thermal infrared band. Thus, it is very difficult to build a stable relationship. Passive microwave band emissivities are greatly influenced by the soil moisture, which varies with time. This makes it difficult to develop a general physical algorithm. This paper proposes a method to utilize multiple-satellite, sensors and resolution coupled with a deep dynamic learning neural network to retrieve the land surface temperature from images acquired by the Advanced Microwave Scanning Radiometer 2(AMSR2), a sensor that is similar to the Advanced Microwave Scanning Radiometer Earth Observing System(AMSR-E). The AMSR-E and MODIS sensors are located aboard the Aqua satellite. The MODIS LST product is used as the ground truth data to overcome the difficulties in obtaining large scale land surface temperature data. The mean and standard deviation of the retrieval error are approximately 1.4° and 1.9° when five frequencies(ten channels, 10.7, 18.7, 23.8, 36.5, 89 V/H GHz) are used. This method can effectively eliminate the influences of the soil moisture, roughness, atmosphere and various other factors. An analysis of the application of this method to the retrieval of land surface temperature from AMSR2 data indicates that the method is feasible. The accuracy is approximately 1.8° through a comparison between the retrieval results with ground measurement data from meteorological stations.
文摘AIM:To compare non-liquid and clear-liquid diets,and to assess whether the latter is the optimal treatment for mild acute pancreatitis.METHODS:The Cochrane Library,PUBMED,EMBASE,EBM review databases,Science Citation Index Expanded,and several Chinese databases were searched up to March 2011.Randomized controlled trials(RCTs) that compared non-liquid with clear-liquid diets in patients with mild acute pancreatitis were included.A meta-analysis was performed using available evidence from RCTs.RESULTS:Three RCTs of adequate quality involving a total of 362 participants were included in the final analysis.Compared to liquid diet,non-liquid diet significantly decreased the length of hospitalization [mean difference(MD):1.18,95% CI:0.82-1.55;P﹤0.00001] and total length of hospitalization(MD:1.31,95% CI:0.45-2.17;P = 0.003).The subgroup analysis showed solid diet was more favorable than clear liquid diet in the length of hospitalization,with a pooled MD being-1.05(95% CI:-1.43 to-0.66;P﹤0.00001).However,compared with clear liquid diet,both soft and solid diets did not show any significant differences for recurrence of pain after re-feeding,either alone [relative risk(RR):0.95;95% CI:0.51-1.87;P = 0.88] and(RR:1.22;95% CI:0.69-2.16;P = 0.49),respectively,or analyzed together as non-liquid diet(RR:0.80;95% CI:0.47-1.36;P = 0.41).CONCLUSION:The non-liquid soft or solid diet did not increase pain recurrence after re-feeding,compared with the clear-liquid diet.The non-liquid diet reduced hospitalization.
基金supported by the Risk Reduction Programs of the Ministry of Civil Affairs of the People’s Republic of China(Grant No.TC088641)
文摘Reflectance measurements of both the visible and infrared bands of passive remote sensing sensors are widely used to retrieve aerosol optical depth(AOD) information. This is performed commonly for data obtained over both ocean and land, and these measurements allow for the off line development of a lookup table using radiative transfer models. Owing to molecular and aerosol effects, the reflected light received by the sensor is usually highly polarized. The linear polarization effect may be up to 100%, and the polarization factor of a sensor optical system will change the total intensity as well as the polarization status of the signal reaching the detector. The detector response will be different when the incident light polarization status changes, even if the total intensity remains constant. However, if the polarization calibration is neglected, it will cause obvious errors in the aerosol data retrieval. This is especially true for aerosol optical depth retrieval over an ocean. This measurement relies directly on the reflectance output of the sensor. Cases involving land surfaces are not discussed herein because the inhomogeneous properties conceal the error due to polarization. Taking the 550 and 860 nm bands as examples, the difference between the real top-of-atmosphere(TOA) reflectance and the reflectance reaching the detector is calculated using three different sensor polarization standards according to the Sea-viewing Wide Field-of-view Sensor(Sea Wi FS) and Moderate Resolution Imaging Spectroradiometer(MODIS) standards. The differences in AOD retrieval are also demonstrated using the lookup table developed previously from a vector radiative transfer code. The results reveal that under a normal situation in which the AOD is 0.15, the maximum AOD retrieval error could reach 0.04 in 550 nm but only 0.02 in 860 nm for the dust aerosol model. For the soot aerosol model, the maximum AOD retrieval error is 0.1 in 550 nm and 0.12 in 860 nm, indicating that the lack of polarization calibration will lead to large errors in aerosol retrieval over an ocean.
