In real-time hybrid simulation（RTHS）, it is difficult if not impossible to completely erase the error in restoring force due to actuator response delay using existing displacement-based compensation methods. This pa...In real-time hybrid simulation（RTHS）, it is difficult if not impossible to completely erase the error in restoring force due to actuator response delay using existing displacement-based compensation methods. This paper proposes a new force correction method based on online discrete tangent stiffness estimation（online DTSE） to provide accurate online estimation of the instantaneous stiffness of the physical substructure. Following the discrete curve parameter recognition theory, the online DTSE method estimates the instantaneous stiffness mainly through adaptively building a fuzzy segment with the latest measurements, constructing several strict bounding lines of the segment and calculating the slope of the strict bounding lines, which significantly improves the calculation efficiency and accuracy for the instantaneous stiffness estimation. The results of both computational simulation and real-time hybrid simulation show that：（1） the online DTSE method has high calculation efficiency, of which the relatively short computation time will not interrupt RTHS; and（2） the online DTSE method provides better estimation for the instantaneous stiffness, compared with other existing estimation methods. Due to the quick and accurate estimation of instantaneous stiffness, the online DTSE method therefore provides a promising technique to correct restoring forces in RTHS.展开更多
Current public-opinion propagation research usually focused on closed network topologies without considering the fluctuation of the number of network users or the impact of social factors on propagation. Thus, it rema...Current public-opinion propagation research usually focused on closed network topologies without considering the fluctuation of the number of network users or the impact of social factors on propagation. Thus, it remains difficult to accurately describe the public-opinion propagation rules of social networks. In order to study the rules of public opinion spread on dynamic social networks, by analyzing the activity of social-network users and the regulatory role of relevant departments in the spread of public opinion, concepts of additional user and offline rates are introduced, and the direct immune-susceptible, contacted, infected, and refractory (DI-SCIR) public-opinion propagation model based on real-time online users is established. The interventional force of relevant departments, credibility of real information, and time of intervention are considered, and a public-opinion propagation control strategy based on direct immunity is proposed. The equilibrium point and the basic reproduction number of the model are theoretically analyzed to obtain boundary conditions for public-opinion propagation. Simulation results show that the new model can accurately reflect the propagation rules of public opinion. When the basic reproduction number is less than 1, public opinion will eventually disappear in the network. Social factors can significantly influence the time and scope of public opinion spread on social networks. By controlling social factors, relevant departments can analyze the rules of public opinion spread on social networks to suppress the propagate of negative public opinion and provide a powerful tool to ensure security and stability of society.展开更多
Failures are very common during the online real-time monitoring of large quantities of complex liquids in industrial processes, and can result in excessive resource consumption and pollution. In this study, we introdu...Failures are very common during the online real-time monitoring of large quantities of complex liquids in industrial processes, and can result in excessive resource consumption and pollution. In this study, we introduce a monitoring method capable of non-contact original-state online real-time monitoring for strongly coated, high-salinity, and multi-component liquids. The principle of the method is to establish the relationship among the concentration of the target substance in the liquid （C）, the color space coor- dinates of the target substance at different concentrations （L＊, a＊, b＊）, and the maximum absorption wave- length （λmax）; subsequently, the optimum wavelength λT of the liquid is determined by a high-precision scanning-type monitoring system that is used to detect the instantaneous concentration of the target substance in the flowing liquid. Unlike traditional monitoring methods and existing online monitoring methods, the proposed method does not require any pretreatment of the samples （i.e., filtration, dilution, oxidation/reduction, addition of chromogenic agent, constant volume, etc.）, and it is capable of original- state online real-time monitoring. This method is employed at a large electrolytic manganese plant to monitor the Fe3. concentration in the colloidal process of the plant＇s aging liquid （where the concentra- tions of Fe3＋, Mn2＋, and （NH4）2SO4 are 0.5-18 mg.L 1, 35-39 g.L 1, and 90-110 g.L 1, respectively）. The relative error of this monitoring method compared with an off-line laboratory monitoring is less than 2%.展开更多
AIM: To determine whether online diffusion of the "Ten Warning Signs of Primary Immunodeficiency Diseases(PID)'' adheres to accepted scientific standards.METHODS: We analyzed how reproducible is online di...AIM: To determine whether online diffusion of the "Ten Warning Signs of Primary Immunodeficiency Diseases(PID)'' adheres to accepted scientific standards.METHODS: We analyzed how reproducible is online diffusion of a unique instrument, the "Ten Warning Signs of PID", created by the Jeffrey Modell Foundation(JMF),by Google-assisted searches among highly visited sites from professional, academic and scientific organizations;governmental agencies; and patient support/advocacy organizations. We examined the diffusion, consistency of use and adequate referencing of this instrument.Where applicable, variant versions of the instrument were examined for changes in factual content that would have practical impact on physicians or on patients and their families.RESULTS: Among the first 100 sites identified by Google search, 85 faithfully reproduced the JMF model, and correctly referenced to its source. By contrast, the other15 also referenced the JMF source but presented one or more changes in content relative to their purported model and therefore represent uncontrolled variants, of unknown origin. Discrepancies identified in the latter included changes in factual content of the original JMF list(C), as well as removal(R) and introduction(I) of novel signs(Table 2), all made without reference to any scientific publications that might account for the drastic changes in factual content. Factual changes include changes inthe number of infectious episodes considered necessary to raise suspicion of PID, as well as the inclusion of various medical conditions not mentioned in the original.Together, these changes will affect the way physicians use the instrument to consult or to inform patients,and the way patients and families think about the need for specialist consultation in view of a possible PID diagnosis.CONCLUSION: The retrieved adaptations and variants,which significantly depart from the original instrument,raise concerns about standards for scientific information provided online to physicians, patients and families.展开更多
The probabilistic real-time automaton （PRTA） is a representation of dynamic processes arising in the sciences and industry. Currently, the induction of automata is divided into two steps： the creation of the prefix...The probabilistic real-time automaton （PRTA） is a representation of dynamic processes arising in the sciences and industry. Currently, the induction of automata is divided into two steps： the creation of the prefix tree acceptor （PTA） and the merge procedure based on clustering of the states. These two steps can be very time intensive when a PRTA is to be induced for massive or even unbounded datasets. The latter one can be efficiently processed, as there exist scalable online clustering algorithms. However, the creation of the PTA still can be very time consuming. To overcome this problem, we propose a genuine online PRTA induction approach that incorporates new instances by first collapsing them and then using a maximum frequent pattern based clustering. The approach is tested against a predefined synthetic automaton and real world datasets, for which the approach is scalable and stable. Moreover, we present a broad evaluation on a real world disease group dataset that shows the applicability of such a model to the analysis of medical processes.展开更多
基金Priority Academic Program Development of Jiangsu Higher Education Institutions under Grant No.1105007002National Natural Science Foundation of China under Grant No.51378107 and No.51678147
文摘In real-time hybrid simulation（RTHS）, it is difficult if not impossible to completely erase the error in restoring force due to actuator response delay using existing displacement-based compensation methods. This paper proposes a new force correction method based on online discrete tangent stiffness estimation（online DTSE） to provide accurate online estimation of the instantaneous stiffness of the physical substructure. Following the discrete curve parameter recognition theory, the online DTSE method estimates the instantaneous stiffness mainly through adaptively building a fuzzy segment with the latest measurements, constructing several strict bounding lines of the segment and calculating the slope of the strict bounding lines, which significantly improves the calculation efficiency and accuracy for the instantaneous stiffness estimation. The results of both computational simulation and real-time hybrid simulation show that：（1） the online DTSE method has high calculation efficiency, of which the relatively short computation time will not interrupt RTHS; and（2） the online DTSE method provides better estimation for the instantaneous stiffness, compared with other existing estimation methods. Due to the quick and accurate estimation of instantaneous stiffness, the online DTSE method therefore provides a promising technique to correct restoring forces in RTHS.
基金Project supported by the National Natural Science Foundation of China (Grant No. 61471080)the Equipment Development Department Research Foundation of China (Grant No. 61400010303)+2 种基金the Natural Science Research Project of Liaoning Education Department of China (Grant Nos. JDL2019019 and JDL2020002)the Surface Project for Natural Science Foundation in Guangdong Province of China (Grant No. 2019A1515011164)the Science and Technology Plan Project in Zhanjiang, China (Grant No. 2018A06001)。
文摘Current public-opinion propagation research usually focused on closed network topologies without considering the fluctuation of the number of network users or the impact of social factors on propagation. Thus, it remains difficult to accurately describe the public-opinion propagation rules of social networks. In order to study the rules of public opinion spread on dynamic social networks, by analyzing the activity of social-network users and the regulatory role of relevant departments in the spread of public opinion, concepts of additional user and offline rates are introduced, and the direct immune-susceptible, contacted, infected, and refractory (DI-SCIR) public-opinion propagation model based on real-time online users is established. The interventional force of relevant departments, credibility of real information, and time of intervention are considered, and a public-opinion propagation control strategy based on direct immunity is proposed. The equilibrium point and the basic reproduction number of the model are theoretically analyzed to obtain boundary conditions for public-opinion propagation. Simulation results show that the new model can accurately reflect the propagation rules of public opinion. When the basic reproduction number is less than 1, public opinion will eventually disappear in the network. Social factors can significantly influence the time and scope of public opinion spread on social networks. By controlling social factors, relevant departments can analyze the rules of public opinion spread on social networks to suppress the propagate of negative public opinion and provide a powerful tool to ensure security and stability of society.
文摘Failures are very common during the online real-time monitoring of large quantities of complex liquids in industrial processes, and can result in excessive resource consumption and pollution. In this study, we introduce a monitoring method capable of non-contact original-state online real-time monitoring for strongly coated, high-salinity, and multi-component liquids. The principle of the method is to establish the relationship among the concentration of the target substance in the liquid （C）, the color space coor- dinates of the target substance at different concentrations （L＊, a＊, b＊）, and the maximum absorption wave- length （λmax）; subsequently, the optimum wavelength λT of the liquid is determined by a high-precision scanning-type monitoring system that is used to detect the instantaneous concentration of the target substance in the flowing liquid. Unlike traditional monitoring methods and existing online monitoring methods, the proposed method does not require any pretreatment of the samples （i.e., filtration, dilution, oxidation/reduction, addition of chromogenic agent, constant volume, etc.）, and it is capable of original- state online real-time monitoring. This method is employed at a large electrolytic manganese plant to monitor the Fe3. concentration in the colloidal process of the plant＇s aging liquid （where the concentra- tions of Fe3＋, Mn2＋, and （NH4）2SO4 are 0.5-18 mg.L 1, 35-39 g.L 1, and 90-110 g.L 1, respectively）. The relative error of this monitoring method compared with an off-line laboratory monitoring is less than 2%.
文摘AIM: To determine whether online diffusion of the "Ten Warning Signs of Primary Immunodeficiency Diseases(PID)'' adheres to accepted scientific standards.METHODS: We analyzed how reproducible is online diffusion of a unique instrument, the "Ten Warning Signs of PID", created by the Jeffrey Modell Foundation(JMF),by Google-assisted searches among highly visited sites from professional, academic and scientific organizations;governmental agencies; and patient support/advocacy organizations. We examined the diffusion, consistency of use and adequate referencing of this instrument.Where applicable, variant versions of the instrument were examined for changes in factual content that would have practical impact on physicians or on patients and their families.RESULTS: Among the first 100 sites identified by Google search, 85 faithfully reproduced the JMF model, and correctly referenced to its source. By contrast, the other15 also referenced the JMF source but presented one or more changes in content relative to their purported model and therefore represent uncontrolled variants, of unknown origin. Discrepancies identified in the latter included changes in factual content of the original JMF list(C), as well as removal(R) and introduction(I) of novel signs(Table 2), all made without reference to any scientific publications that might account for the drastic changes in factual content. Factual changes include changes inthe number of infectious episodes considered necessary to raise suspicion of PID, as well as the inclusion of various medical conditions not mentioned in the original.Together, these changes will affect the way physicians use the instrument to consult or to inform patients,and the way patients and families think about the need for specialist consultation in view of a possible PID diagnosis.CONCLUSION: The retrieved adaptations and variants,which significantly depart from the original instrument,raise concerns about standards for scientific information provided online to physicians, patients and families.
文摘The probabilistic real-time automaton （PRTA） is a representation of dynamic processes arising in the sciences and industry. Currently, the induction of automata is divided into two steps： the creation of the prefix tree acceptor （PTA） and the merge procedure based on clustering of the states. These two steps can be very time intensive when a PRTA is to be induced for massive or even unbounded datasets. The latter one can be efficiently processed, as there exist scalable online clustering algorithms. However, the creation of the PTA still can be very time consuming. To overcome this problem, we propose a genuine online PRTA induction approach that incorporates new instances by first collapsing them and then using a maximum frequent pattern based clustering. The approach is tested against a predefined synthetic automaton and real world datasets, for which the approach is scalable and stable. Moreover, we present a broad evaluation on a real world disease group dataset that shows the applicability of such a model to the analysis of medical processes.
