Analysis and Key Parameter Optimization Design of Leningrader Seal Performance

In order to improve the performance and service life of the Leningrader seal of the Stirling engine piston rod,interference,pre-load and friction coefficient were taken as influencing factors,and the curved surface response method was adopted to reduce the contact stress of sealing surface and von Mises stress of the sealing sleeve as the response index,with the optimization goal of reducing wear and extending life.The above three key parameters are analyzed and optimized,the influence of each parameter on the sealing performance and service life is obtained,and the best combination scheme of the three is determined.The results show that the interaction between pre-tightening force and interference fit has the greatest impact on contact stress.The interaction between interference fit and friction coeffi-cient has the most significant effect on von Mises stress.The optimized parameters can reduce the maximum contact stress and maximum von Mises stress of the sealing sleeve by 26.3%and 20.6%,respectively,under a media pressure of 5-9 MPa.Test bench verification shows that the leakage of the optimized sealing device in 12 h is reduced by 0.44 cc·min^(-1)(1 cc=1 cm^(3)).The wear rate of the sealing sleeve is 1.08%before optimization and 0.45%after optimization,indicating that the optimized parameters in this paper are effective.

Synthesis and Raman Performance Enhancement of Multilayer AuAg Heterostructures with Magnetic Resonance

Significant amplification of surface enhanced Raman scattering(SERS)signals can be achieved mainly by the electric field enhancement in metal core-shell nanostructures,and the enhanced magnetic field is rarely studied.In this study,we prepared multi-gap Au/AgAu core-shell hybrid nanostructures by using gold nanocup as the core.The overgrowth processes to grow one,two,and three layers of AgAu hybrid nanoshells can produce Au/AgAu^(1),Au/AgAu^(2),and Au/AgAu^(3) heteronanostructures.The strong plasmon coupling between the core and shell leads to significant electromagnetic field enhancement.Under the synergistic effect of electromagnetic plasmon resonance and plasmon coupling,Au/AgAu core-shell hybrid nanostructures exhibit excellent SERS signals.We also investigate the effect of the interstitial position of the rhodamine B(RhB)molecule on Raman enhancement in Au/AgAu~3 heteronanostructures.This study can provide new ideas for the synthesis of multi-gap Raman signal amplifiers based on magnetic plasmon coupling.

Optimal Control Virtual Inertia of Optical Storage Microgrid Based on Improved Sailfish Algorithm

The optical storage microgrid system composed of power electronic converters is a small inertia system.Load switching and power supply intermittent will affect the stability of the direct current(DC)bus voltage.Aiming at this problem,a virtual inertia optimal control strategy applied to optical storage microgrid is proposed.Firstly,a small signal model of the system is established to theoretically analyze the influence of virtual inertia and damping coefficient on DC bus voltage and to obtain the constraint range of virtual inertia and damping coefficient;Secondly,aiming at the defect that the Sailfish optimization algorithm is easy to premature maturity,a Sailfish optimization algorithm based on the leak-proof net and the cross-mutation propagation mechanism is proposed;Finally,the virtual inertia and damping coefficient of the system are optimized by the improved Sailfish algorithm to obtain the best control parameters.The simulation results in Matlab/Simulink show that the virtual inertia control optimized by the improved Sailfish algorithm improves the system inertia as well as the dynamic response and robustness of the DC bus voltage.

Application of Improved Compact Particle Swarm Optimization to Large Ontology Alignment Task

Ontology occupies an important position in artificial intelligence,computer linguistics and knowledge management.However,when different ontologies are constructed to represent the same information in a domain,the so-called heterogeneity problem arises.In order to address this problem,a key task is to discover the semantic relationship of entities between given two ontologies,called ontology alignment.Recently,the meta-heuristic algorithms have already been regarded as an effective approach for solving ontology alignment problem.However,firstly,as the ontologies become increasingly large,meta-heuristic algorithms may be easier to find local optimal alignment in large search spaces.Secondly,many existing approaches exploit the population-based meta-heuristic algorithms so that the massive calculation is required.In this paper,an improved compact particle swarm algorithm by using a local search strategy is proposed,called LSCPSOA,to improve the performance of finding more correct correspondences.In LSCPSOA,two update strategies with local search capability are employed to avoid falling into a local optimal alignment.The proposed algorithm has been evaluated on several large ontology data sets and compared with existing ontology alignment methods.The experimental results show that the proposed algorithm can find more correct correspondences and improves the time performance compared with other meta-heuristic algorithms.

Influence of CNN Structure Parameters on Blind Equalization of Shortwave Channels

Aiming at the severe inter-symbol interference and high bit error rate in short-wave fast time-varying channels,this paper designs a short-wave channel blind equalizer based on Convolution Neural Network(CNN),and analyzes the influence of parameters in CNN structure on channel equalization,such as the number of convolution layers,the depth of convolution layer and the size of the convolution kernel layer.By simulating two typical short-wave time-varying channel,Rayleigh flat fading and frequency selective fading channels,we have the following results:1)Compared with the Recurrent Neural Network(RNN)structure equalizer,the CNN has higher accuracy during the training process,the convergence speed is faster,and the stability after convergence is higher.2)Under the condition of simulation,the CNN-based short-wave channel blind equalizer designed in this paper can effectively extract input signal when using 2×3×3 convolution kernel size and 2-layer convolutional layer.The characteristics of the classification layer improve the equalization performance while reducing the complexity of CNN structure.3)For the short-wave channel,the error rate of Convolution Neural Network Equalizer(CNNE)is lower than that of Recurrent Neural Network Equalizer(RNNE)under the same SNR.

C^(1) Smoothness of Steiner Symmetrizations

In this paper,we study the smoothness of the Steiner symmetrization process and generalize the Steiner symmetrization of functions in Sobolev space to the Steiner symmetrization of convex body.We prove that for a C^(1)convex body,its Steiner symmetral is still a C^(1)convex body.

The Walsh Transform of a Class of Boolean Functions

The Walsh transform is an important tool to investigate cryptographic properties of Boolean functions.This paper is devoted to study the Walsh transform of a class of Boolean functions defined as g(x)=f(x)Tr^(n)_(1)(x)+h(x)Tr^(n)_(1)(δx),by making use of the known conclusions of Walsh transform and the properties of trace function,and the conclusion is obtained by generalizing an existing result.

Systematic Synthesis for Multiple-Feedback Filter Using OTAs and CCCIIs

In order to obtain the multiple-feedback filter with simpler structure and electronic control,this paper first derives nodal admittance matrix(NAM)equation of the multiple-feedback filter.Furthermore,in accordance with the pathological models of the operational transconductance amplifier(OTA)and second generation current-controlled conveyor(CCCII),the multiplefeedback filter based on OTAs and CCCIIs are respectively synthesized by the NAM expansion method.The filter employing three OTAs has eight equivalent realizations and the filter employing three CCCIIs has 16 equivalent realizations.24 different forms of the current-mode filters are synthesized in all.fo and Q of the synthesized filters can be tuned by tuning bias currents of the active elements.The hand analysis and computer analysis are included to support the method to be utilized.

A Novel Routing Strategy to Provide Source Location Privacy in Wireless Sensor Networks

In order to secure the source location privacy when information is sent back to the base station in wireless sensor network, we propose a novel routing strategy which routes the packets to the base station through three stages： directional random routing, h-hop routing in the annular region and the shortest path routing. These stages provide two fold protections to prevent the source location from being tracked down by the adversary. The analysis and simulation results show that proposed scheme, besides providing longer safety period, can significantly reduce energy consumption compared with two baseline schemes.

A Novel Chinese Polar Knowledge Repository Based on Polar Data-Sharing Ontology

In order to archive and utilize the information from Chinese polar expeditions to the greatest extent, we design a novel knowledge repository, in which an automatic query model based on neural networks is proposed and a data call trigger is established to keep data consistent between polar data-sharing platforms. And in this repository, anybody can make contributions to the repository by creating or updating entries with version control and an authority control mechanism. In this paper, the data sources,data processes and network structure of this repository are described, and the keywords extraction and decision support operation are detailed. The analysis of this design＇s feasibility and applicability indicates that this knowledge repository is open, sole and authoritative for Chinese polar expeditions.

Word-Order Switch and Its Representation in Corpus

Word-order reformation is very uselul m mtormatlon orocessing, and it is worthy to annotate in corpus. In this paper, we unalyze the syntactic functions afforded by word-order switch in Mandarin Chinese, and present a feasible annotation approach based on the word order information. The experiment results show that there is a very significant difference for the frequency information of word distribution after annotation. Therefore, it is helpful for obtaining the accurate frequency information. Meanwhile, word-order switch information can also offer meaningful pragmatic information to improve the quality of machine translation.

Towards Fast and Efficient Algorithm for Learning Bayesian Network

Learning Bayesian network structure is one of the most exciting challenges in machine learning. Discovering a correct skeleton of a directed acyclic graph（DAG） is the foundation for dependency analysis algorithms for this problem. Considering the unreliability of high order condition independence（CI） tests, and to improve the efficiency of a dependency analysis algorithm, the key steps are to use few numbers of CI tests and reduce the sizes of conditioning sets as much as possible. Based on these reasons and inspired by the algorithm PC, we present an algorithm, named fast and efficient PC（FEPC）, for learning the adjacent neighbourhood of every variable. FEPC implements the CI tests by three kinds of orders, which reduces the high order CI tests significantly. Compared with current algorithm proposals, the experiment results show that FEPC has better accuracy with fewer numbers of condition independence tests and smaller size of conditioning sets. The highest reduction percentage of CI test is 83.3% by EFPC compared with PC algorithm.

Software Defect Prediction Using Fuzzy Integral Fusion Based on GA-FM

The fuzzy measure and fuzzy integral are applied to the classification of software defects in this paper. The fuzzy measure of software attributes and attributes＇ sets are treated by genetic algorithm, and then software attributes are fused by the Choquet fuzzy integral algorithm. Finally, the class labels of soft- ware modules can be output. Experimental results have shown that there are interactions between characteristic attributes of software modules, and also proved that the fuzzy integral fusing method using Fuzzy Measure based on Genetic Algorithm （GA-FM） can significantly improve the accuracy for software defect prediction.

An Operator on Ascent Sequences

We solve two problems about ascent sequences： how to get the ascent sequence of the reflection of A with respect to its antidiagonal for a matrix A ∈ Intn and its ascent sequences, and how to determine the ascent sequence of A＋B for kxk matrices A ∈ Int, and B ∈ Intm. We give the other definition of ascent se- quence and get M-sequence. For the first question, we define M-sequence of A and rewrite the ascent sequences as another form We build the bijection between M-sequences and ascent sequences and prove that our bijection is well-defined. For the second ques- tion, we define an operation on M-sequences. On the basis of the operation and the bijections, we get the ascent sequences of the sum of two matrices.

A Simple Implementation of Distributed Vertical Search and Information Integration Technology

The paper proposes the research on the distributed vertical search and information integration technology based on Web mining, which aims at satisfying the requirements of the spe- cific fields＇ applications. Nowadays, mining, analyzing, and inte- grating Web＇s content have become an important trend for daily use. The technique includes the Map/Reduce model, the depth search, and the basic principles of information integration. The focus of the paper is how to implement the distributed vertical search engine based on Map/Reduce technology and the informa- tion integration system. System optimization mechanism and the system test are also proposed.

Jackknifed Liu Estimator in Linear Regression Models

In this paper, we introduce a generalized Liu estimator and jackknifed Liu estimator in a linear regression model with correlated or heteroscedastic errors. Therefore, we extend the Liu estimator. Under the mean square error（MSE）, the jackknifed estimator is superior to the Liu estimator and the jackknifed ridge estimator. We also give a method to select the biasing parameter for d. Furthermore, a numerical example is given to illustvate these theoretical results.

Progress on Soldering Failure Analysis During the Period of Enlistment in Micro-Nanoelectronic Packaging

With development of miniaturization,high integration,multifunction and high efficiency of electronic packaging technology,a higher requirement for soldering material and its enlistment property is needed.It is easily subjected to reliability failure for electronic products or components packaged with micro/nanoelectronic packaging technology.In this paper,research process and some typical failure mechanisms on interconnect solder point reliability are discussed,including electro-migration （EM）,thermal migration （TM）,K-cavity,corrosion,electrochemical migration （ECM） and whisker growth,etc.It provides the basic data for the new generation of micro/nano-packaging technique to improve the fine-pitch jointing reliability.

A Novel Intrusion Detection Method Based on Improved SVM by Combining PCA and PSO

The paper presents an improved support vector machine （SVM） by combining principal component analysis （PCA） and particle swarm optimization （PSO）. Then, the improved SVM is applied to the intrusion detection system （IDS） to improve the detection rate. First, PCA is used to reduce the dimension of feature vectors. Second, we use the PSO algorithm to optimize the punishment factor C and kernel parameters oin SVM. The experimental results indicate that the intrusion detection rate （97.752 8%） of improved SVM by combining PCA and PSO is higher than those （95.635 5%） of PSO-SVM and those （90.476 2%） of standard SVM with KDD Cup 1999 data set.

Texture Preserving Denoising Method Combining Total Variation and Wavelet Shrinkage

In this paper,we propose a new image denoising method that combines total variation（TV） method and wavelet shrinkage. In our method,a noisy image is decomposed into subbands of LL,LH,HL,and HH in wavelet domain. LL subband contains the low frequency coefficients along with less noise,which can be easily eliminated using TV-based method. More edges and other detailed information like textures are contained in the other three subbands,and we propose a shrinkage method based on the local variance to extract them from high frequency noise. Experimental results show that this method retains the edges and textures very well while removing noise.