A three-way catalyst comprised novel oxygen storage components for emission control in natural gas powered engines was prepared. The addition of novel oxygen storage components to the Pd/γ-Al2O3 catalysts resulted ...A three-way catalyst comprised novel oxygen storage components for emission control in natural gas powered engines was prepared. The addition of novel oxygen storage components to the Pd/γ-Al2O3 catalysts resulted in improved activities of the fresh and aged catalyst by lowering the light-off temperature for methane in natural gas engines exhaust.展开更多
We prove C1.α-partial regularity of weak solutions of nonlinear elliptic systems under the main assumption that Aia and Bi satisfy the controllable growth condition or the natural growth condition.
Oxygen transfer presents a serious challenge in the application of liquid lead as a nuclear coolant in advanced reactors. To mitigate corrosion by liquid lead in contact with steel, carefully controlling the oxygen co...Oxygen transfer presents a serious challenge in the application of liquid lead as a nuclear coolant in advanced reactors. To mitigate corrosion by liquid lead in contact with steel, carefully controlling the oxygen concentration has been used as an effective way. Oxygen needs to mix in liquid lead uniformly and quickly. To enhance oxygen transport in liquid lead, nanoparticles are added to the liquid metal. In the current study, a lattice Boltzmann method is applied to investigate natural convection of copper/lead and aluminum oxide/lead in two-dimensional simplified container. Two thermal boundary cases are evaluated in order to check the effect of different natural convection flow patterns on oxygen transport. Some useful information are obtained such as improvement in natural convection and reduction in oxygen equilibrium time.展开更多
The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access...The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.展开更多
There are multiple ways to control a robotic system. Most of them require the users to have prior knowledge about robots or get trained before using them. Natural language based control attracts increasing attention d...There are multiple ways to control a robotic system. Most of them require the users to have prior knowledge about robots or get trained before using them. Natural language based control attracts increasing attention due to its versatility and less requirements for users. Since natural language instructions from users cannot be understood by the robots directly, the linguistic input has to be processed into a formal representation which captures the task specification and removes the ambiguity inherent in natural language. For most of existing natural language controlled robotic system, they assume the given language instructions are already in correct orders. However, it is very likely for untrained users to give commands in a mixed order based on their direct observation and intuitive thinking. Simply following the order of the commands can lead to failures of tasks. To provide a remedy for the problem, we propose a novel framework named dependency relation matrix （DRM） to model and organize the semantic information extracted from language input, in order to figure out an executable sequence of subtasks for later execution. In addition, the proposed approach projects abstract language input and detailed sensory information into the same space, and uses the difference between the goal specification and temporal status of the task under implementation to monitor the progress of task execution. In this paper, we describe the DRM framework in detail, and illustrate the utility of this approach with experiment results.展开更多
The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access...The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.展开更多
基金the National Natural Science Foundation of China(No:20273043)the Ministry of Education of China for providing financial support for this project
文摘A three-way catalyst comprised novel oxygen storage components for emission control in natural gas powered engines was prepared. The addition of novel oxygen storage components to the Pd/γ-Al2O3 catalysts resulted in improved activities of the fresh and aged catalyst by lowering the light-off temperature for methane in natural gas engines exhaust.
文摘We prove C1.α-partial regularity of weak solutions of nonlinear elliptic systems under the main assumption that Aia and Bi satisfy the controllable growth condition or the natural growth condition.
基金the financial support from the office of Vice-President for Research at University of Nevada-Las Vegas
文摘Oxygen transfer presents a serious challenge in the application of liquid lead as a nuclear coolant in advanced reactors. To mitigate corrosion by liquid lead in contact with steel, carefully controlling the oxygen concentration has been used as an effective way. Oxygen needs to mix in liquid lead uniformly and quickly. To enhance oxygen transport in liquid lead, nanoparticles are added to the liquid metal. In the current study, a lattice Boltzmann method is applied to investigate natural convection of copper/lead and aluminum oxide/lead in two-dimensional simplified container. Two thermal boundary cases are evaluated in order to check the effect of different natural convection flow patterns on oxygen transport. Some useful information are obtained such as improvement in natural convection and reduction in oxygen equilibrium time.
文摘The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.
文摘There are multiple ways to control a robotic system. Most of them require the users to have prior knowledge about robots or get trained before using them. Natural language based control attracts increasing attention due to its versatility and less requirements for users. Since natural language instructions from users cannot be understood by the robots directly, the linguistic input has to be processed into a formal representation which captures the task specification and removes the ambiguity inherent in natural language. For most of existing natural language controlled robotic system, they assume the given language instructions are already in correct orders. However, it is very likely for untrained users to give commands in a mixed order based on their direct observation and intuitive thinking. Simply following the order of the commands can lead to failures of tasks. To provide a remedy for the problem, we propose a novel framework named dependency relation matrix （DRM） to model and organize the semantic information extracted from language input, in order to figure out an executable sequence of subtasks for later execution. In addition, the proposed approach projects abstract language input and detailed sensory information into the same space, and uses the difference between the goal specification and temporal status of the task under implementation to monitor the progress of task execution. In this paper, we describe the DRM framework in detail, and illustrate the utility of this approach with experiment results.
基金supported by Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘The National Institute of Standards and Technology(NIST)has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy(NLACP)to a machine-readable form.To study the automation process,we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations.Therefore,this paper focuses on the questions of:how can we automatically infer the hierarchical structure of an ABAC model given NLACPs;and,how can we extract and define the set of authorization attributes based on the resulting structure.To address these questions,we propose an approach built upon recent advancements in natural language processing and machine learning techniques.For such a solution,the lack of appropriate data often poses a bottleneck.Therefore,we decouple the primary contributions of this work into:(1)developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts,and(2)generating a set of realistic synthetic natural language access control policies(NLACPs)to evaluate the proposed framework.Our experimental results are promising as we achieved-in average-an F1-score of 0.96 when extracting attributes values of subjects,and 0.91 when extracting the values of objects’attributes from natural language access control policies.
