The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.H...The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.However,maintaining consistent forwarding states during these updates is challenging,particularly when rerouting multiple flows simultaneously.Existing approaches pay little attention to multi-flow update,where improper update sequences across data plane nodes may construct deadlock dependencies.Moreover,these methods typically involve excessive control-data plane interactions,incurring significant resource overhead and performance degradation.This paper presents P4LoF,an efficient loop-free update approach that enables the controller to reroute multiple flows through minimal interactions.P4LoF first utilizes a greedy-based algorithm to generate the shortest update dependency chain for the single-flow update.These chains are then dynamically merged into a dependency graph and resolved as a Shortest Common Super-sequence(SCS)problem to produce the update sequence of multi-flow update.To address deadlock dependencies in multi-flow updates,P4LoF builds a deadlock-fix forwarding model that leverages the flexible packet processing capabilities of the programmable data plane.Experimental results show that P4LoF reduces control-data plane interactions by at least 32.6%with modest overhead,while effectively guaranteeing loop-free consistency.展开更多
A fuzzy neural network (FNN) model is developed to predict the 4-CBA concentration of the oxidation unit in purified terephthalic acid process. Several technologies are used to deal with the process data before modeli...A fuzzy neural network (FNN) model is developed to predict the 4-CBA concentration of the oxidation unit in purified terephthalic acid process. Several technologies are used to deal with the process data before modeling.First,a set of preliminary input variables is selected according to prior knowledge and experience. Secondly,a method based on the maximum correlation coefficient is proposed to detect the dead time between the process variables and response variables. Finally, the fuzzy curve method is used to reduce the unimportant input variables.The simulation results based on industrial data show that the relative error range of the FNN model is narrower than that of the American Oil Company (AMOCO) model. Furthermore, the FNN model can predict the trend of the 4-CBA concentration more accurately.展开更多
Soft sensor is attractive in dealing with online product quality measurement by virtue of other easily measured variables. In AMOCO PTA (purified terephthalic acid) production process, the unavailability of real-time ...Soft sensor is attractive in dealing with online product quality measurement by virtue of other easily measured variables. In AMOCO PTA (purified terephthalic acid) production process, the unavailability of real-time measurement of 4-CBA makes it impossible for timely adjustment and thereby influences the product quality and the plant economy benefit. In this paper, a kind of FCMAC (fuzzy cerebellar model articulation controller) method is presented to solve the online measurement problem. Different from the conventional CMAC (cerebellar model articulation controller) networks, which has inferior smoothing ability because of its table look-up based technology. Integrating fuzzy model into CMAC networks, it becomes more accurate in functional mapping without weakening its generalization ability. Numerical example and industrial application results show the method proposed here is satisfactory and feasible.展开更多
Objective:To predict the nephrotoxicity mechanism of Lianqiao-4 through network pharmacology and molecular docking methods.Methods:The main chemical components of Lianqiao(Forsythia suspensa),Bistortae rhizoma,Ophiopo...Objective:To predict the nephrotoxicity mechanism of Lianqiao-4 through network pharmacology and molecular docking methods.Methods:The main chemical components of Lianqiao(Forsythia suspensa),Bistortae rhizoma,Ophiopogonis radix,and Clematidis radix et rhizoma,as well as nephrotoxicity-related targets,were screened through databases such as TCMSP,Swiss Target Prediction,GeneCards,and ETCM.Venny 2.1.0 was used to identify the main components of Lianqiao-4 and nephrotoxicity targets.The STRING platform and David database were utilized to construct a protein-protein interaction(PPI)network diagram,while gene function(GO)enrichment analysis and KEGG pathway analysis were conducted.The“Lianqiao-4 active ingredients-nephrotoxicity targets-signaling pathways”network model was constructed using Cytoscape 3.9.1 software.Results:Network pharmacology and molecular docking analysis revealed that the core active ingredients responsible for the nephrotoxicity mechanism of Mongolian medicine Lianqiao-4 include steroidal saponins such as ophiopogonin A,flavonoids like kaempferol and quercetin,steroidal compounds such asβ-sitosterol and sitosterol,and other key regulatory targets including STAT3,ABCG2,HSP90AA1,MMP9,PTGS2,and EGFR.Major pathways involved include lipid and atherosclerosis,chemical carcinogenesis-DNA adducts,and arachidonic acid metabolism.Conclusion:Mongolian medicine Lianqiao-4 exerts its therapeutic effect on nephrotoxicity through multiple components,targets,and pathways,pending experimental verification.展开更多
Back-propagation neural network was applied to predict and optimize the synthetic technology of 2-chloro-4,6-dinitroresorcinol. A model was established based on back-propagation neural network using the experimental d...Back-propagation neural network was applied to predict and optimize the synthetic technology of 2-chloro-4,6-dinitroresorcinol. A model was established based on back-propagation neural network using the experimental data of homogeneous design as the training sample set and the technological parameters were optimized by it. The optimal technological parameters are as follows： the reaction time is 4h, the reaction temperature is 80℃, the molar ratio of NaOH to 4,6-dinitro-1,2,3-trichlorobenzene is 5.5：1, the molar ratio of methanol to 4,6-dinitro-1,2,3- trichlorobenzene is 11：1, and the molar ratio of water to 4,6-dinitro-1,2,3-trichlorobenzene is 70：1. Under the optimal conditions, three groups of experiments were performed and the average yield of 2-chloro-4,6-dinitroresorcinol is 96.64%, the absolute error of it with the predicted value is -1.07%.展开更多
The first tier of automotive manufacturers has faced to pressures about move,modify,updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor compan...The first tier of automotive manufacturers has faced to pressures about move,modify,updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements,it has to require absolutely lead time to re-wiring of physical interface for production equipment,needs for change existing program and test over again.For prepare this constraints,it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M(Man,Machine,Material, Method)group management which is supports from WSN (Wireless Sensor Network)of the open embedded device called M2M(Machine to Machine)and major functions of middleware including point manager for real-time device communication,real-time data management,Standard API (Application Program Interface)and application template management.To be application system to RMS (Reconfigurable Manufacturing System)for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.展开更多
The first tier of automotive manufacturers has faced to pressures about move, modify, updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor comp...The first tier of automotive manufacturers has faced to pressures about move, modify, updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements, it has to require absolutely lead time to re-wiring of physical interface for production equipment, needs for change existing program and test over again. For prepare this constraints, it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M (Man, Machine, Material, Method) group management which is supports from WSN (Wireless Sensor Network) of the open embedded device called M2M (Machine to Machine) and major functions of middleware including point manager for real-time device communication, real-time data management, Standard API (Application Program Interface) and application template management. To be application system to RMS (Reconfigurable Manufacturing System) for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.展开更多
基金supported by the National Key Research and Development Program of China under Grant 2022YFB2901501in part by the Science and Technology Innovation leading Talents Subsidy Project of Central Plains under Grant 244200510038.
文摘The rapid growth of distributed data-centric applications and AI workloads increases demand for low-latency,high-throughput communication,necessitating frequent and flexible updates to network routing configurations.However,maintaining consistent forwarding states during these updates is challenging,particularly when rerouting multiple flows simultaneously.Existing approaches pay little attention to multi-flow update,where improper update sequences across data plane nodes may construct deadlock dependencies.Moreover,these methods typically involve excessive control-data plane interactions,incurring significant resource overhead and performance degradation.This paper presents P4LoF,an efficient loop-free update approach that enables the controller to reroute multiple flows through minimal interactions.P4LoF first utilizes a greedy-based algorithm to generate the shortest update dependency chain for the single-flow update.These chains are then dynamically merged into a dependency graph and resolved as a Shortest Common Super-sequence(SCS)problem to produce the update sequence of multi-flow update.To address deadlock dependencies in multi-flow updates,P4LoF builds a deadlock-fix forwarding model that leverages the flexible packet processing capabilities of the programmable data plane.Experimental results show that P4LoF reduces control-data plane interactions by at least 32.6%with modest overhead,while effectively guaranteeing loop-free consistency.
基金Supported by the National Outstanding Youth Science Foundation of China (No. 60025308).
文摘A fuzzy neural network (FNN) model is developed to predict the 4-CBA concentration of the oxidation unit in purified terephthalic acid process. Several technologies are used to deal with the process data before modeling.First,a set of preliminary input variables is selected according to prior knowledge and experience. Secondly,a method based on the maximum correlation coefficient is proposed to detect the dead time between the process variables and response variables. Finally, the fuzzy curve method is used to reduce the unimportant input variables.The simulation results based on industrial data show that the relative error range of the FNN model is narrower than that of the American Oil Company (AMOCO) model. Furthermore, the FNN model can predict the trend of the 4-CBA concentration more accurately.
基金Supported by the special Funds for Major State Basic Research Program of China (973 Program) (No. 2002CB312200) the 863 Hi-Tech. Research and Development Program of China (No. 2001AA413130, No.2002AA412110)the Key Technologies R&D Programme of China (No. 2001BA201A04).
文摘Soft sensor is attractive in dealing with online product quality measurement by virtue of other easily measured variables. In AMOCO PTA (purified terephthalic acid) production process, the unavailability of real-time measurement of 4-CBA makes it impossible for timely adjustment and thereby influences the product quality and the plant economy benefit. In this paper, a kind of FCMAC (fuzzy cerebellar model articulation controller) method is presented to solve the online measurement problem. Different from the conventional CMAC (cerebellar model articulation controller) networks, which has inferior smoothing ability because of its table look-up based technology. Integrating fuzzy model into CMAC networks, it becomes more accurate in functional mapping without weakening its generalization ability. Numerical example and industrial application results show the method proposed here is satisfactory and feasible.
文摘Objective:To predict the nephrotoxicity mechanism of Lianqiao-4 through network pharmacology and molecular docking methods.Methods:The main chemical components of Lianqiao(Forsythia suspensa),Bistortae rhizoma,Ophiopogonis radix,and Clematidis radix et rhizoma,as well as nephrotoxicity-related targets,were screened through databases such as TCMSP,Swiss Target Prediction,GeneCards,and ETCM.Venny 2.1.0 was used to identify the main components of Lianqiao-4 and nephrotoxicity targets.The STRING platform and David database were utilized to construct a protein-protein interaction(PPI)network diagram,while gene function(GO)enrichment analysis and KEGG pathway analysis were conducted.The“Lianqiao-4 active ingredients-nephrotoxicity targets-signaling pathways”network model was constructed using Cytoscape 3.9.1 software.Results:Network pharmacology and molecular docking analysis revealed that the core active ingredients responsible for the nephrotoxicity mechanism of Mongolian medicine Lianqiao-4 include steroidal saponins such as ophiopogonin A,flavonoids like kaempferol and quercetin,steroidal compounds such asβ-sitosterol and sitosterol,and other key regulatory targets including STAT3,ABCG2,HSP90AA1,MMP9,PTGS2,and EGFR.Major pathways involved include lipid and atherosclerosis,chemical carcinogenesis-DNA adducts,and arachidonic acid metabolism.Conclusion:Mongolian medicine Lianqiao-4 exerts its therapeutic effect on nephrotoxicity through multiple components,targets,and pathways,pending experimental verification.
文摘Back-propagation neural network was applied to predict and optimize the synthetic technology of 2-chloro-4,6-dinitroresorcinol. A model was established based on back-propagation neural network using the experimental data of homogeneous design as the training sample set and the technological parameters were optimized by it. The optimal technological parameters are as follows： the reaction time is 4h, the reaction temperature is 80℃, the molar ratio of NaOH to 4,6-dinitro-1,2,3-trichlorobenzene is 5.5：1, the molar ratio of methanol to 4,6-dinitro-1,2,3- trichlorobenzene is 11：1, and the molar ratio of water to 4,6-dinitro-1,2,3-trichlorobenzene is 70：1. Under the optimal conditions, three groups of experiments were performed and the average yield of 2-chloro-4,6-dinitroresorcinol is 96.64%, the absolute error of it with the predicted value is -1.07%.
基金supported by the Industry Foundation project from the Ministry of Knowledge Economy in the Korean Government.
文摘The first tier of automotive manufacturers has faced to pressures about move,modify,updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements,it has to require absolutely lead time to re-wiring of physical interface for production equipment,needs for change existing program and test over again.For prepare this constraints,it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M(Man,Machine,Material, Method)group management which is supports from WSN (Wireless Sensor Network)of the open embedded device called M2M(Machine to Machine)and major functions of middleware including point manager for real-time device communication,real-time data management,Standard API (Application Program Interface)and application template management.To be application system to RMS (Reconfigurable Manufacturing System)for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.
文摘The first tier of automotive manufacturers has faced to pressures about move, modify, updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements, it has to require absolutely lead time to re-wiring of physical interface for production equipment, needs for change existing program and test over again. For prepare this constraints, it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M (Man, Machine, Material, Method) group management which is supports from WSN (Wireless Sensor Network) of the open embedded device called M2M (Machine to Machine) and major functions of middleware including point manager for real-time device communication, real-time data management, Standard API (Application Program Interface) and application template management. To be application system to RMS (Reconfigurable Manufacturing System) for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.
