This study constructs a function-private inner-product predicate encryption(FP-IPPE)and achieves standard enhanced function privacy.The enhanced function privacy guarantees that a predicate secret key skf reveals noth...This study constructs a function-private inner-product predicate encryption(FP-IPPE)and achieves standard enhanced function privacy.The enhanced function privacy guarantees that a predicate secret key skf reveals nothing about the predicate f,as long as f is drawn from an evasive distribution with sufficient entropy.The proposed scheme extends the group-based public-key function-private predicate encryption(FP-PE)for“small superset predicates”proposed by Bartusek et al.(Asiacrypt 19),to the setting of inner-product predicates.This is the first construction of public-key FP-PE with enhanced function privacy security beyond the equality predicates,which is previously proposed by Boneh et al.(CRYPTO 13).The proposed construction relies on bilinear groups,and the security is proved in the generic bilinear group model.展开更多
A method to model and analyze the hybrid systems is presented. The time to be considered in the plant is taken as an explicit parameter through the constrained predicated net (CPN). The CPN's basic structure is a ...A method to model and analyze the hybrid systems is presented. The time to be considered in the plant is taken as an explicit parameter through the constrained predicated net (CPN). The CPN's basic structure is a Petri net with predicated transition. All components of the net are expressed by annotation which is defined on rational set Q. The analysis method for the plant is interval temporal logic represented by Petri nets. This paper combines the above two methods to synthesize the hybrid system, gives a simple and clear expression of the expected action of the studied plant.展开更多
Due to the nature of ultra-short-acting opioid remifentanil of high time-varying,complex compartment model and low-accuracy of plasma concentration prediction,the traditional estimation method of population pharmacoki...Due to the nature of ultra-short-acting opioid remifentanil of high time-varying,complex compartment model and low-accuracy of plasma concentration prediction,the traditional estimation method of population pharmacokinetics parameters,nonlinear mixed effects model(NONMEM),has the abuses of tedious work and plenty of man-made jamming factors.The Elman feedback neural network was built.The relationships between the patients’plasma concentration of remifentanil and time,patient’age,gender,lean body mass,height,body surface area,sampling time,total dose,and injection rate through network training were obtained to predict the plasma concentration of remifentanil,and after that,it was compared with the results of NONMEM algorithm.In conclusion,the average error of Elman network is 6.34%,while that of NONMEM is 18.99%.The absolute average error of Elman network is 27.07%,while that of NONMEM is 38.09%.The experimental results indicate that Elman neural network could predict the plasma concentration of remifentanil rapidly and stably,with high accuracy and low error.For the characteristics of simple principle and fast computing speed,this method is suitable to data analysis of short-acting anesthesia drug population pharmacokinetic and pharmacodynamics.展开更多
By analyzing the metallogenic conditions and prospecting marks of F 8 fault belt in Shiujingtun Gold Mine, the geochemical samples were collected along F 8 fault belt and prospecting profile normal to the F 8 fault be...By analyzing the metallogenic conditions and prospecting marks of F 8 fault belt in Shiujingtun Gold Mine, the geochemical samples were collected along F 8 fault belt and prospecting profile normal to the F 8 fault belt. Gold and its indicator elements were tested with X ray fluorescence spectrometry and the content distribution diagram of Au, Ag, Hg and As along the F 8 fault belt was performed. The geochemical primary halo model and the Grey system model of F 8 fault belt are established. With these element distribution features and models, the blind ore bodies in the F 8 fault belt were predicted. Engineering prospect shows that the industrial orebodies have been discovered and the prediction results are dependable.展开更多
The cooling process of tanks relates to various physical actions,parts or components and fluids.A predication method is presented to evaluate the effects of cooling system for tanks.A predication model that includes t...The cooling process of tanks relates to various physical actions,parts or components and fluids.A predication method is presented to evaluate the effects of cooling system for tanks.A predication model that includes the heat production,heat transfer and fluid flow modules is established.The engine combustion and friction between components act as the primary heat sources.The solid components of power transmission train are partitioned into thermal nodes.The heat conductions among the thermal nodes,coolant,lubricant,powerhouse fresh air,combustion gas and exhaust gas are taken into account.The coolant flow,lubricant flow and powerhouse air flow are also considered.The prediction model is resolved by use of a multilayer iterative technique and an arithmetic of local convergence combined with global convergence for coupled modules.A calculation example shows that the model can implement predication of cooling system under different environment temperatures and running conditions quite better.展开更多
基金National Key Research and Development Program of China(2021YFB3101402)National Natural Science Foundation of China(62202294)。
文摘This study constructs a function-private inner-product predicate encryption(FP-IPPE)and achieves standard enhanced function privacy.The enhanced function privacy guarantees that a predicate secret key skf reveals nothing about the predicate f,as long as f is drawn from an evasive distribution with sufficient entropy.The proposed scheme extends the group-based public-key function-private predicate encryption(FP-PE)for“small superset predicates”proposed by Bartusek et al.(Asiacrypt 19),to the setting of inner-product predicates.This is the first construction of public-key FP-PE with enhanced function privacy security beyond the equality predicates,which is previously proposed by Boneh et al.(CRYPTO 13).The proposed construction relies on bilinear groups,and the security is proved in the generic bilinear group model.
文摘A method to model and analyze the hybrid systems is presented. The time to be considered in the plant is taken as an explicit parameter through the constrained predicated net (CPN). The CPN's basic structure is a Petri net with predicated transition. All components of the net are expressed by annotation which is defined on rational set Q. The analysis method for the plant is interval temporal logic represented by Petri nets. This paper combines the above two methods to synthesize the hybrid system, gives a simple and clear expression of the expected action of the studied plant.
文摘目的:探讨多种机器学习模型预测机器人辅助肾部分切除术(robot-assisted partial nephrectomy,RAPN)后肾功能减退的效能,为临床风险分层提供依据。方法:回顾性纳入2019年1月至2023年12月重庆医科大学附属第一医院泌尿外科733例肾细胞癌(renal cell carcinoma,RCC)行RAPN患者的临床数据,整合人口学特征、实验室指标及围手术期参数,构建7种机器学习模型,采用Shapley加性解释(Shapley additive explanations,SHAP)方法解析关键预测因子,并通过受试者工作特征曲线下面积(receiver operating characteristic curve area under the curve,ROC-AUC)评估模型性能。结果:随机森林模型预测效能最优(AUC=0.84)。SHAP分析显示,中性粒细胞/淋巴细胞比值、肿瘤直径、凝血酶原时间国际标准化比值、白细胞计数及术中出血量等因素对术后肾功能减退有明显影响。结论:本研究为临床提供了一种潜在的预测工具,可帮助识别高风险患者并优化术后管理策略。
基金Project(31200748)supported by the National Natural Science Foundation of China
文摘Due to the nature of ultra-short-acting opioid remifentanil of high time-varying,complex compartment model and low-accuracy of plasma concentration prediction,the traditional estimation method of population pharmacokinetics parameters,nonlinear mixed effects model(NONMEM),has the abuses of tedious work and plenty of man-made jamming factors.The Elman feedback neural network was built.The relationships between the patients’plasma concentration of remifentanil and time,patient’age,gender,lean body mass,height,body surface area,sampling time,total dose,and injection rate through network training were obtained to predict the plasma concentration of remifentanil,and after that,it was compared with the results of NONMEM algorithm.In conclusion,the average error of Elman network is 6.34%,while that of NONMEM is 18.99%.The absolute average error of Elman network is 27.07%,while that of NONMEM is 38.09%.The experimental results indicate that Elman neural network could predict the plasma concentration of remifentanil rapidly and stably,with high accuracy and low error.For the characteristics of simple principle and fast computing speed,this method is suitable to data analysis of short-acting anesthesia drug population pharmacokinetic and pharmacodynamics.
基金TheOutstandingYoungScientistsFoundation !(No496 2 5304)andtheKeyProgramofMinistryofScienceandTechnologyofChina !(No95 pre 3
文摘By analyzing the metallogenic conditions and prospecting marks of F 8 fault belt in Shiujingtun Gold Mine, the geochemical samples were collected along F 8 fault belt and prospecting profile normal to the F 8 fault belt. Gold and its indicator elements were tested with X ray fluorescence spectrometry and the content distribution diagram of Au, Ag, Hg and As along the F 8 fault belt was performed. The geochemical primary halo model and the Grey system model of F 8 fault belt are established. With these element distribution features and models, the blind ore bodies in the F 8 fault belt were predicted. Engineering prospect shows that the industrial orebodies have been discovered and the prediction results are dependable.
文摘The cooling process of tanks relates to various physical actions,parts or components and fluids.A predication method is presented to evaluate the effects of cooling system for tanks.A predication model that includes the heat production,heat transfer and fluid flow modules is established.The engine combustion and friction between components act as the primary heat sources.The solid components of power transmission train are partitioned into thermal nodes.The heat conductions among the thermal nodes,coolant,lubricant,powerhouse fresh air,combustion gas and exhaust gas are taken into account.The coolant flow,lubricant flow and powerhouse air flow are also considered.The prediction model is resolved by use of a multilayer iterative technique and an arithmetic of local convergence combined with global convergence for coupled modules.A calculation example shows that the model can implement predication of cooling system under different environment temperatures and running conditions quite better.
