Design of Distributed Authentication Mechanism for Equipment Support Information Network

Considering the secure authentication problem for equipment support information network,a clustering method based on the business information flow is proposed. Based on the proposed method,a cluster-based distributed authentication mechanism and an optimal design method for distributed certificate authority( CA)are designed. Compared with some conventional clustering methods for network,the proposed clustering method considers the business information flow of the network and the task of the network nodes,which can decrease the communication spending between the clusters and improve the network efficiency effectively. The identity authentication protocols between the nodes in the same cluster and in different clusters are designed. From the perspective of the security of network and the availability of distributed authentication service,the definition of the secure service success rate of distributed CA is given and it is taken as the aim of the optimal design for distributed CA. The efficiency of providing the distributed certificate service successfully by the distributed CA is taken as the constraint condition of the optimal design for distributed CA. The determination method for the optimal value of the threshold is investigated. The proposed method can provide references for the optimal design for distributed CA.

Neural Network Based on GA-BP Algorithm and its Application in the Protein Secondary Structure Prediction

The advantages and disadvantages of genetic algorithm and BP algorithm are introduced. A neural network based on GA-BP algorithm is proposed and applied in the prediction of protein secondary structure, which combines the advantages of BP and GA. The prediction and training on the neural network are made respectively based on 4 structure classifications of protein so as to get higher rate of predication---the highest prediction rate 75.65%,the average prediction rate 65.04%.

Research on the Essential Network Equipment Risk Assessment Methodology based on Vulnerability Scanning Technology

In this paper, we conduct research on the essential network equipment risk assessment method based on vulnerability scanning technology. A growing number of hackers wanton invasion of the computer, through the network to steal important information, or destroy the network, the paralyzed which caused huge losses to the state and society. Find a known vulnerability rather than to find the unknown vulnerabilities much easier, which means that most of the attacker＇ s use is common vulnerabilities. Therefore, we adopt the advantages of the technique to finalize the methodology for the essential network equipment risk assessment which will be meaningful.

Analysis of cumulative handoff delay for graded secondary users in cognitive radio networks

According to the fact that the secondary users＇ delay requirements for data transmission are not unitary in cognitive radio networks, the secondary users are divided into two classes, denoted by SU1 and SU2, respectively. It is assumed that SU1 has a higher priority to occupy the primary users＇ unutilized channels than SU2. A preemptive resume priority M/G/1 queuing network is used to model the multiple spectrum handoffs processing. By using a state transition probability matrix and a cost matrix, the average cumulative delays of SU1 and SU2 are calculated, respectively. Numerical results show that the more the primary user＇s traffic load, the more rapidly the SU2＇s cumulative handoff delay grows. Compared with the networks where secondary users are unitary, the lower the SUI＇s arrival rate, the more obviously both SUI＇s and SU2＇s handoff delays decrease. The admission access regions limited by the maximum tolerable delay can also facilitate the design of admission control rules for graded secondary users.

Equipment Maintenance Mode Based on Network Environment

Aimed at the actuality of Peoplep's Liberation Army(PLA) army equipment maintenance, this paper develops equipment maintenance mode based on network,and focuses on the design of maintenance decision-making system. Analyzing maintenance weight is applied to making decision of repair level.The purpose of the research is introducing basic concept and setting up an equipment maintenance mode using military network.Maintenance mode based on network can reduce the costs,enhance the maintenance efficiency, and save the human resource and finance.

Effects of Network Closure on Cooperative Innovation: Evidence from Dongying's Petroleum Equipment Industry in China

There are two opposing viewpoints on which kind of network configuration provides a more competitive advantage, namely,network closure or structural holes, with the latter occupying the dominant position in the literature. Using social network analysis and negative binomial regression methods, we graph the co-patent network of Dongying's petroleum equipment industry in China and explore its impact on enterprise innovation. The analysis is based on 17 face-to-face interviews, 31 enterprise questionnaires, and 354 co-patent records from the China State Intellectual Property Office identifying cooperative innovation for the years 1988–2013. We find that this network is closed, controlled by state-owned enterprises, and its closure has positive effects on enterprise innovation performance. This may be related to China's unique industrial development history, state system and policies, regional culture and circumstances, and enterprise characteristics. Therefore, for some industries in specific regions, the advantages usually attributed to structural holes and open innovation may not necessarily apply.

SHARING AND PLANNING OF DISTRIBUTED EQUIPMENT FOR NETWORKED MANUFACTURING

Efficient utilization of the equipment distributed in different enterprises and optimal allocation of these resources is an important concern for networked manufacturing. The third party based equipment sharing approach is put forward to optimize the utilization of distributed equipment for networked manufacturing; Taking advantage of the shared equipment offered by equipment providers by means of lease agreement, the third party carries out production by establishing networked virtual factory. Operational mechanism of the third party based equipment sharing is discussed, and characteristics of this approach in achieving resource allocation are analyzed. Shared equipment planning is formulated as an optimization problem with the objective of maximizing profits for equipment coordinator, a mathematical model for shared equipment planning is developed. Finally a case study is discussed to show the effectiveness of the planning model.

Using Neural Networks to Predict Secondary Structure for Protein Folding

Protein Secondary Structure Prediction (PSSP) is considered as one of the major challenging tasks in bioinformatics, so many solutions have been proposed to solve that problem via trying to achieve more accurate prediction results. The goal of this paper is to develop and implement an intelligent based system to predict secondary structure of a protein from its primary amino acid sequence by using five models of Neural Network (NN). These models are Feed Forward Neural Network (FNN), Learning Vector Quantization (LVQ), Probabilistic Neural Network (PNN), Convolutional Neural Network (CNN), and CNN Fine Tuning for PSSP. To evaluate our approaches two datasets have been used. The first one contains 114 protein samples, and the second one contains 1845 protein samples.

An evaluation method of contribution rate based on fuzzy Bayesian networks for equipment system-of-systems architecture

The contribution rate of equipment system-of-systems architecture(ESoSA)is an important index to evaluate the equipment update,development,and architecture optimization.Since the traditional ESoSA contribution rate evaluation method does not make full use of the fuzzy information and uncertain information in the equipment system-of-systems(ESoS),and the Bayesian network is an effective tool to solve the uncertain information,a new ESoSA contribution rate evaluation method based on the fuzzy Bayesian network(FBN)is proposed.Firstly,based on the operation loop theory,an ESoSA is constructed considering three aspects:reconnaissance equipment,decision equipment,and strike equipment.Next,the fuzzy set theory is introduced to construct the FBN of ESoSA to deal with fuzzy information and uncertain information.Furthermore,the fuzzy importance index of the root node of the FBN is used to calculate the contribution rate of the ESoSA,and the ESoSA contribution rate evaluation model based on the root node fuzzy importance is established.Finally,the feasibility and rationality of this method are validated via an empirical case study of aviation ESoSA.Compared with traditional methods,the evaluation method based on FBN takes various failure states of equipment into consideration,is free of acquiring accurate probability of traditional equipment failure,and models the uncertainty of the relationship between equipment.The proposed method not only supplements and improves the ESoSA contribution rate assessment method,but also broadens the application scope of the Bayesian network.

Dynamic Characteristics Analysis on MHTGR Plant’s Secondary Side Fluid Flow Network

Multipe NSSS (Nuclear Steam Supply System) modules use the common feeding-water system to drive the common turbine power generation set. The SSFFN (secondary side fluid flow network) of MHTGR plant has features i.e. strong-coupling and nonlinearity. A wide range of power switching operation will cause unsteady flow, which may destroy the working elements and will be a threat for normal operation. To overcome those problems, a differential-algebraic model and PI controllers are designed for the SSFFN. In MATLAB\SIMULINK environment, a simulation platform is established and used to make a simulation of SSFFN of a MHTGR plant with two NSSS modules, which uses feedwater valves to control the mass flow rate in each module instead of feedwater pump. Results reflect good robustness of controllers.

Value analysis of district heating system with gas-fired peak load boiler in secondary network

In district heating(DH) system with gas-fired peak load regulating boiler in the secondary network,by prolonging run time of base load plants under rated condition,the mean energy efficiency could be increased. The fuels of the system,including coal and gas,would cause different environmental impacts. Meanwhile,the reliability of the heating networks would be changed because the peak load regulating boiler could work as a standby heat source. A model for assessment of heating system was established by value analysis to optimize this kind of system. Energy consumption,greenhouse gas emission,pollution emission and system reliability were selected as functional assessment indexes in the model. Weights of each function were determined by analytical hierarchy process (AHP) and experts consultation. Life cycle cost was used as the cost in the model. A real case as an example was discussed to obtain the optimal base load ratio. The result shows that the optimal base load ratio of the case is 0.77.

Applying Neural Network withGenetic Algorithm and FuzzySelection Models to Select Equipmentsfor Fully-Mechanized Coal Mining

According to the typical engineering samples, a neural net work model with genetic algorithm to optimize weight values is put forward to forecast the productivities and efficiencies of mining faces. By this model we can obtain the possible achievements of available equipment combinations under certain geological situations of fully-mechanized coal mining faces. Then theory of fuzzy selection is applied to evaluate the performance of each equipment combination. By detailed empirical analysis, this model integrates the functions of forecasting mining faces' achievements and selecting optimal equipment combination and is helpful to the decision of equipment combination for fully-mechanized coal mining.

Automatic infrared image recognition method for substation equipment based on a deep self-attention network and multi-factor similarity calculation

Infrared image recognition plays an important role in the inspection of power equipment.Existing technologies dedicated to this purpose often require manually selected features,which are not transferable and interpretable,and have limited training data.To address these limitations,this paper proposes an automatic infrared image recognition framework,which includes an object recognition module based on a deep self-attention network and a temperature distribution identification module based on a multi-factor similarity calculation.First,the features of an input image are extracted and embedded using a multi-head attention encoding-decoding mechanism.Thereafter,the embedded features are used to predict the equipment component category and location.In the located area,preliminary segmentation is performed.Finally,similar areas are gradually merged,and the temperature distribution of the equipment is obtained to identify a fault.Our experiments indicate that the proposed method demonstrates significantly improved accuracy compared with other related methods and,hence,provides a good reference for the automation of power equipment inspection.

New “Intellectual Networks” (Smart Grid) for Detecting Electrical Equipment Faults, Defects and Weaknesses

The most important elements of “intellectual networks” (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which described in this paper, were proposed to use together with rapid digital protection against short-circuit regimes in transformer windings. This paper presents an application’s experience of LVI-testing, some results of the use of Frequency Response Analysis (FRA) to check the condition of transformer windings and infra-red control results of electrical equipment. The LVI method and short-circuit inductive reactance measurements are sensitive for detecting such faults as radial, axial winding deformations, a twisting of low-voltage or regulating winding, a losing of winding’s pressing and others.

Education Equipment Configuration and Funding Situation Analysis of Underdeveloped Areas of Information Technology in Rural Primary and Secondary School

In order to understand IT teaching conditions and living environment in the less developed areas of rural primary and secondary school, the paper uses questionnaire survey equipment to investigate education of some rural underdeveloped areas of information technology in primary and secondary school in Jiangxi. And it has analyzed 2011-2013 investment and construction of the status quo in education funding for information technology equipment. The results show： Less Developed Areas in primary and secondary school education information and technology education equipment cannot meet the needs of the development of education with lack of funding support, poor school environment and information technology teaching conditions. And this phenomenon has been analyzed, and effective measures are to improve primary and secondary school education in underdeveloped areas of information technology conditions and educational level.

Measurement methods on the complexity of network

Based on the size of network and the number of paths in the network,we proposed a model of topology complexity of a network to measure the topology complexity of the network. Based on the analyses of the effects of the number of the equipment,the types of equipment and the processing time of the node on the complexity of the network with the equipment-constrained,a complexity model of equipment-constrained network was constructed to measure the integrated complexity of the equipment-constrained network. The algorithms for the two models were also developed. An automatic generator of the random single label network was developed to test the models. The results show that the models can correctly evaluate the topology complexity and the integrated complexity of the networks.

Research on Construction Scheme of Cloud Platform for Core Network Equipment of Railway 5G Private Network

This paper studies and analyzes the rigorous requirements of railway 5G private network core network(5GC)equipment based on network function virtualization(NFV)technology in terms of reliability,security,latency and other aspects of communication cloud,compares cloud platform schemes with different decoupling modes,and proposes that railway 5GC should be implemented by software and hardware integration scheme or software and hardware two-layer decoupling scheme.At the same time,the redundancy and disaster recovery schemes and measures that can be taken by 5GC based on cloud platform are proposed.Finally,taking the products of ZTE Corporation as an example,the implementation architecture of railway 5GC cloud platform in 1+1 redundancy mode is given.It serves as a reference for the engineering construction of 5G-R core network.

Earthquake disaster chain model based on complex networks for urban engineering systems

According to news reports on severe earthquakes since 2008,a total of 51 cases with magnitudes of 6.0 or above were analyzed,and 14 frequently occurring secondary disasters were identified.A disaster chain model was developed using principles from complex network theory.The vulnerability and risk level of each edge in this model were calculated,and high-risk edges and disaster chains were identified.The analysis reveals that the edge“floods→building collapses”has the highest vulnerability.Implementing measures to mitigate this edge is crucial for delaying the spread of secondary disasters.The highest risk is associated with the edge“building collapses→casualties,”and increased risks are also identified for chains such as“earthquake→building collapses→casualties,”“earthquake→landslides and debris flows→dammed lakes,”and“dammed lakes→floods→building collapses.”Following an earthquake,the prompt implementation of measures is crucial to effectively disrupt these chains and minimize the damage from secondary disasters.