In order to reveal the mechanics of composite regeneration by coupling cerium-based additive and microwave for a diesel particulate filter, a composite regeneration model by coupling cerium-based additive and microwav...In order to reveal the mechanics of composite regeneration by coupling cerium-based additive and microwave for a diesel particulate filter, a composite regeneration model by coupling cerium-based additive and microwave for a diesel particulate filter was established based on field synergy theory. Performance evaluation on field synergy and composite regeneration of the diesel particulate filter was conducted by using the vortex crushing combustion and field synergy mathematical models. The results show that the peak temperature of the particulate filter body reaches 1180-1190 K when the regeneration time is 175 s, and there are optimal coordination degree between the velocity vector and temperature gradient of the filter body and the maximum ratio0.56-0.60 of the best burning regeneration region is obtained. Accordingly, the largest regeneration combustion rate inside the particulate filter body and the highest regeneration efficiency at the moment are achieved.展开更多
In this paper, we present Real-Time Flow Filter (RTFF) -a system that adopts a middle ground between coarse-grained volume anomaly detection and deep packet inspection. RTFF was designed with the goal of scaling to hi...In this paper, we present Real-Time Flow Filter (RTFF) -a system that adopts a middle ground between coarse-grained volume anomaly detection and deep packet inspection. RTFF was designed with the goal of scaling to high volume data feeds that are common in large Tier-1 ISP networks and providing rich, timely information on observed attacks. It is a software solution that is designed to run on off-the-shelf hardware platforms and incorporates a scalable data processing architecture along with lightweight analysis algorithms that make it suitable for deployment in large networks. RTFF also makes use of state of the art machine learning algorithms to construct attack models that can be used to detect as well as predict attacks.展开更多
基金Projects(51176045,51276056)supported by the National Natural Science Foundation of ChinaProject(531105050037)supported by the Changjiang Scholars and Innovative Research Team in University,ChinaProjects(201208430262,201306130031)supported by the National Studying Abroad Foundation Project of China
文摘In order to reveal the mechanics of composite regeneration by coupling cerium-based additive and microwave for a diesel particulate filter, a composite regeneration model by coupling cerium-based additive and microwave for a diesel particulate filter was established based on field synergy theory. Performance evaluation on field synergy and composite regeneration of the diesel particulate filter was conducted by using the vortex crushing combustion and field synergy mathematical models. The results show that the peak temperature of the particulate filter body reaches 1180-1190 K when the regeneration time is 175 s, and there are optimal coordination degree between the velocity vector and temperature gradient of the filter body and the maximum ratio0.56-0.60 of the best burning regeneration region is obtained. Accordingly, the largest regeneration combustion rate inside the particulate filter body and the highest regeneration efficiency at the moment are achieved.
文摘In this paper, we present Real-Time Flow Filter (RTFF) -a system that adopts a middle ground between coarse-grained volume anomaly detection and deep packet inspection. RTFF was designed with the goal of scaling to high volume data feeds that are common in large Tier-1 ISP networks and providing rich, timely information on observed attacks. It is a software solution that is designed to run on off-the-shelf hardware platforms and incorporates a scalable data processing architecture along with lightweight analysis algorithms that make it suitable for deployment in large networks. RTFF also makes use of state of the art machine learning algorithms to construct attack models that can be used to detect as well as predict attacks.
