EHNG50／50／32型汽轮机主蒸汽滤过网修复改进

通过对汽轮机主蒸汽滤过网破坏原因的分析，提出改进及修复方法，并取得较好效果。

Improving the precision of the keyword-matching pornographic text filtering method using a hybrid model

With the flooding of pornographic information on the Internet, how to keep people away from that offensive information is becoming one of the most important research areas in network information security. Some applications which can block or filter such information are used. Approaches in those systems can be roughly classified into two kinds: metadata based and content based. With the development of distributed technologies, content based filtering technologies will play a more and more important role in filtering systems. Keyword matching is a content based method used widely in harmful text filtering. Experiments to evaluate the recall and precision of the method showed that the precision of the method is not satisfactory, though the recall of the method is rather high. According to the results, a new pornographic text filtering model based on reconfirming is put forward. Experiments showed that the model is practical, has less loss of recall than the single keyword matching method, and has higher precision.

SAFE:a Scalable Filter-Based Packet Filtering Scheme

Recently, attacks have become Denial-of-Service （DOS） the mainstream threat to the internet service availability. The filter-based packet filtering is a key technology to defend against such attacks. Relying on the filtering location, the proposed schemes can be grouped into Victim-end Filtering and Source-end Filtering. The first scheme uses a single filtering router to block the attack flows near the victim, but does not take the factor that the filters are scarce resource into account, which causes the huge loss of legitimate flows; considering each router could contribute a few filters, the other extreme scheme pushes the filtering location back into each attack source so as to obtain ample filters, but this may incur the severe network transmission delay due to the abused filtering routers. Therefore, in this paper, we propose a scalable filter-based packet filtering scheme to balance the number of filtering routers and the available filters. Through emulating DoS scenarios based on the synthetic and real-world Intemet topologies and further implementing the various filter-based packet filtering schemes on them, the results show that our scheme just uses fewer filtering routers to cut off all attack flows while minimizing the loss of legitimate flows.

A Router Based Packet Filtering Scheme for Defending Against DoS Attacks

The filter-based reactive packet filtering is a key technology in attack traffic filtering for defending against the Denial-of- Service （DOS） attacks. Two kinds of relevant schemes have been proposed as victim- end filtering and source-end filtering. The first scheme prevents attack traffic from reaching the victim, but causes the huge loss of legitimate flows due to the scarce filters （termed as collateral damages）; the other extreme scheme can obtain the sufficient filters, but severely degrades the network transmission performance due to the abused filtering routers. In this paper, we propose a router based packet filtering scheme, which provides relatively more filters while reducing the quantity of filtering touters. We implement this scheme on the emulated DoS scenarios based on the synthetic and real-world Internet topologies. Our evaluation results show that compared to the previous work, our scheme just uses 20% of its filtering routers, but only increasing less than 15 percent of its collateral damage.

A neighbor information based false data filtering scheme in wireless sensor networks

In sensor networks,the adversaries can inject false data reports from compromised nodes.Previous approaches to filter false reports,e.g.,SEF,only verify the correctness of the message authentication code (MACs) carried in each data report on intermediate nodes,thus cannot filter out fake reports that are forged in a collaborative manner by a group of compromised nodes,even if these compromised nodes distribute in different geographical areas.Furthermore,if the adversary obtains keys from enough (e.g.,more than t in SEF) distinct key partitions,it then can successfully forge a data report without being detected en-route.A neighbor information based false report filtering scheme (NFFS) in wireless sensor networks was presented.In NFFS,each node distributes its neighbor information to some other nodes after deployment.When a report is generated for an observed event,it must carry the IDs and the MACs from t detecting nodes.Each forwarding node checks not only the correctness of the MACs carried in the report,but also the legitimacy of the relative position of these detecting nodes.Analysis and simulation results demonstrate that NFFS can resist collaborative false data injection attacks efficiently,and thus can tolerate much more compromised nodes than existing schemes.

Experimental investigation of oil particles filtration on carbon nanotubes composite filter

Due to the lipophilicity of carbon nanotubes (CNTs),the carbon nanotubes composite filter for removing oil particles in cooking fumes is synthesized. The composite filter was fabricated by the chemical vapor deposition (CVD) method. The filtration characteristics of the resultant filter and the influence of the parameters were investigated. The results show that the filtration efficiency of the CNT filter during the saturation period is 99.92%, which satisfies the high efficiency particulate air (HEPA) standard. Pressure drop increases linearly before saturation and the pressure drop at the saturation stage is only two times that of the initial stage, which is far less than that of conventional glass fiber filters. The efficiency increases by enhancing filtration velocity. Pressure drops in the composite filter at the equilibrium stage are equal under different aerosol concentrations. The increase in concentration can improve the efficiency of composite filters. Therefore, the CNT filter is suitable for decreasing oil particle pollution due to its lower increase ratio of pressure drop and higher efficiency.

Horror Video Recognition Based on Fuzzy Comprehensive Evolution

Technique for horror video recognition is important for its application in web content filtering and surveillance, especially for preventing children from being threaten. In this paper, a novel horror video recognition algorithm based on fuzzy comprehensive evolution model is proposed. Three low-level video features are extracted as typical features, and they are video key-light, video colour energy and video rhythm. Analytic Hierarchy Process （AHP） is adopted to estimate the weights of extracted features in fuzzy evolution model. Horror evaluation （membership function） is on shot scale and it is constructed based on the knowledge that videos which share the same affective have similar low-level features. K-Means algorithm is implemented to help finding the most representative feature vectors. The experimental results demonstrate that the proposed approach has good performance in recognition precision, recall rate and F1 measure.

Accelerating Packet Classification with Counting Bloom Filters for Virtual Open Flow Switching

The growing trend of network virtualization results in a widespread adoption of virtual switches in virtualized environments. However, virtual switching is confronted with great performance challenges regarding packet classification especially in Open Flow-based software defined networks. This paper first takes an insight into packet classification in virtual Open Flow switching, and points out that its performance bottleneck is dominated by flow table traversals of multiple failed mask probing for each arrived packet. Then we are motivated to propose an efficient packet classification algorithm based on counting bloom filters. In particular, counting bloom filters are applied to predict the failures of flow table lookups with great possibilities, and bypass flow table traversals for failed mask probing. Finally, our proposed packet classification algorithm is evaluated with real network traffic traces by experiments. The experimental results indicate that our proposed algorithm outperforms the classical one in Open v Switch in terms of average search length, and contributes to promote virtual Open Flow switching performance.

Research on multi-document summarization based on latent semantic indexing

A multi-document summarization method based on Latent Semantic Indexing (LSI) is proposed. The method combines several reports on the same issue into a matrix of terms and sentences, and uses a Singular Value Decomposition (SVD) to reduce the dimension of the matrix and extract features, and then the sentence similarity is computed. The sentences are clustered according to similarity of sentences. The centroid sentences are selected from each class. Finally, the selected sentences are ordered to generate the summarization. The evaluation and results are presented, which prove that the proposed methods are efficient.

Optimum Design of Passive Shunt Filters for Power Distribution Networks

Static, passive, filters present an economic and simple solution to the harmonic distortion at the distribution level and at the same time supply the required reactive power for voltage support and/or power factor correction. Applying these filters to a distribution network, if not properly designed, may have an adverse effect on the network. This paper presents analysis of the effects of using passive harmonic filters in a power distribution networks. The driving point impedance at the node where the filter installed, as a measure of how harmonic currents would produce harmonic voltages, is determined as function of the filter parameters. Hence, effects of filter parameters on the system impedance, parallel resonant frequency and impedance at resonance are illustrated. The effects of using more than one filter are also examined. A method for the optimal design of a passive filter considering the component limits, harmonic distortion limits and parameter tolerances is also presented. The proposed optimization model has proved its effectiveness through application to measurements at a real distribution feeder.

Design of Congestion Control Strategy Based on Pipeline Flux Leak Monitoring Networks

Flow against pipeline leakage and the pipe network sudden burst pipe to pipeline leakage flow for the application objects,network congestion avoidance strategy is designed in pipeline leak monitoring.Based on the property of Markov chain for network data,a new estimator with particle filter is proposed for congestion control in this paper.The proposed scheme can predict the traffic patterns by the decision-making model.To compare with previous scheme based on fuzzy neural network,the proposed scheme can adaptively adjust the network rate in real-time and reduce the cell loss rate,so that it can avoid the traffic congestion.Simulation results show that network congestion avoidance strategy with particle filter can improve the bandwidth utilization,Transmission Control Protocol (TCP) friendliness and reduce the packet drop rate in Pipeline Flux Leak Monitoring networks.

The optimized design of duct net disposal for filter-rods based on topology structure

The filter-rods were supplied through compressed air conveyed to cigarette-maker by transmitter in my factory. Usually, each maker has two feed-pipes, it adopts fixed and one-to-one fashion, with the flexible manufacturing system extending, and it＇s original fashion unable to satisfy the needs of a wide range of cigarette brands already, so it cry for a viable and reliable substitute. This paper creatively bring forward the optimized fashion of duct net about filter-rods based on topology structure, it adopts Freud＇s algorithm and improved-separated algorithm in order to achieve the optimized route, it has a apparent effect to improve the transport stability and reduce the transport time of filter- rods.

Experimental Investigation of a Cryogenic Filter for Separating Solid Carbon Dioxide Particles from Liquid Nitrogen

This paper presents an investigation of a new method of purifying cryogenic liquid using sintered metallic wire-mesh filter, which has the advantages of high purifying efficiency and preferred strength at absolutely low temperature. Experiments are conducted to purify solid CO2 particles from liquid nitrogen. Temperature and pressure in the upstream and downstream of the filter, and the flow rate of carbon dioxide （CO2） gas and liquid nitrogen are measured, with the gas content of filtrate analyzed using a CO2 concentration detector. It is illustrated that after filtration, the purity of liquid nitrogen （volume fraction） is higher than 99.99%, which means that the volume fraction of CO2 is less than 0.01%. Effects of operation parameters on the performance of the filter, such as pressure drop Ap and filtration efficiency E are analyzed quantitatively. The present conclusions will provide a guideline to the optimumal design and operation of sintered metallic wire-mesh filter in cryogenic application.

Coupling Agent Based Simulation with Dynamic Networks Analysis to Study the Emergence of Mutual Knowledge as a Percolation Phenomenon

The emergence of mutual knowledge is a major cognitive mechanism for the robustness of complex socio-technical systems. It has been extensively studied from an ethnomethodological point of view and empirically reproduced by multi-agent simulations. Whilst such simulations have been used to design real work settings the underlying theoretical grounding for the process is vague. The aim of this paper is to investigate whether the emergence of mutual knowledge(MK) in a group of colocated individuals can be explained as a percolation phenomenon. The followed methodology consists in coupling agent-based simulation with dynamic networks analysis to study information propagation phenomena: After using an agent-based simulation the authors generated and then analyzed its traces as networks where agents met and exchanged knowledge. Deep analysis of the resulting networks clearly shows that the emergence of MK is comparable to a percolation process. The authors specifically focus on how changes at the microscopic level in the proposed agent based simulator affect percolation and robustness. These results therefore provide theoretical basis for the analysis of social organizations.

Improved Scheme of Internet Congestion Control under Moving Average Filter

An important task of Internet congestion control is inhibiting sporadic data flow to maintain a suitable window size or route queue length. Such a requirement is just consistent with the basic idea and function of a moving average filter. In this paper one prior Internet congestion control model, named transmission control protocol (TCP)/random early detection (RED) stroboscopic model, is studied, and then one new scheme is proposed to enlarge its stable domain, where a simple moving average filter is introduced to inhibit sporadic data flow as possible. In the novel scheme the bifurcation phenomenon is postponed without any extra controller. The effectiveness of the new scheme is verified by theoretical analyses and numerical simulations.

Convergence analysis of distributed Kalman filtering for relative sensing networks

We study the distributed Kalman filtering problem in relative sensing networks with rigorous analysis.The relative sensing network is modeled by an undirected graph while nodes in this network are running homogeneous dynamical models. The sufficient and necessary condition for the observability of the whole system is given with detailed proof. By local information and measurement communication, we design a novel distributed suboptimal estimator based on the Kalman filtering technique for comparison with a centralized optimal estimator. We present sufficient conditions for its convergence with respect to the topology of the network and the numerical solutions of n linear matrix inequality（LMI） equations combining system parameters. Finally, we perform several numerical simulations to verify the effectiveness of the given algorithms.