平移式双模硫化机开模模式的优化

优化平移式双模硫化机的开模模式。将平移式双模硫化机自动开模模式或手动开模模式优化为半自动半手动开模模式,并设置合理的开模暂停高度,可以有效地避免拉伤中心机构、损伤轮胎外观、轮胎过硫的风险。该优化方案在一定程度上减小了操作人员的工作量,缩短了轮胎生产周期,提高了生产效率。

一维非线性链自由能的计算

研究了一维非线性链孤立子的统计性质．引进平移模作为完备基，把系统作为无相互作用的孤立子（反孤立于）一声子组成的“理想气体”，采用巨正则系综计算了低温条件下系统的自由能密度．

On the Hardy-Littlewood Direct Theorem of the Translation Modulus of Continuity in H^P(01)Spaces

In this paper we discuss a Hardy-Littlewood direct theorem of transla- tion modulus of continuity in H_q^p(0<p<1,q>1) spaces.The main result is that for any f(z)∈H_q^p(0<p<1,q>1) and any τE(0,1) we have where z=x+iy,and c_(p,q) is a constant depending on p and q only.

激光工作物质

TN244 2004064075 BiB3O6晶体的喇曼光谱=Raman spectra of bismuth triborate BiB3O6 crystal[刊,中]/滕冰（青岛大学物理系.山东,青岛（266071））,胡小波…∥光电子·激光.—2004,15（6）.—734-738 对BiB3O6晶体（BIBO）的喇曼光谱进行了研究。BIBO的振动模分为外模和内模,外模总数是2A+5B,内模数是11A+10B。运用分子位置群分析的方法分析内模,BIBO的内模归属于[BO3]三角形和[BO4]四面体的振动模,[BO3]和[BO4]共享O原子。外部振动起源于Bi3+、[BO3]基团的平移模与[BO3]基团的天平动。图2表2参9（于晓光）

Limits to foundation displacement of an extra high voltage transmission tower in a mining subsidence area

Given the background of a transmission tower erected on a particular mining subsidence area,we used finite element modeling to analyze the anti-deformation performance of transmission towers under a number of different load conditions,including horizontal foundation displacement,uneven vertical downward displacement,wind loads and icing conditions.The results show that the failure in stability of a single steel angle iron represents the limit of the tower given ground deformation.We calculated the corresponding limits of foundation displacements.The results indicate that compression displacement of the foundation is more dangerous than tension displacement.Under complex foundation displacement conditions,horizontal foundation displacement is a key factor leading to failure in the stability of towers.Under conditions of compression or tension displacement of the foundation,wind load becomes the key factor.Towers do not fail when foundation displacements are smaller than 1% (under tension) or 0.5% (under horizontal compression or single foundation subsidence) of the distance between two supports.

Time Series Models for Short Term Prediction of the Incidence of Japanese Encephalitis in Xianyang City, P R China

Objective To construct a model of Seasonal Autoregressive Integrated Moving Average （SARIMA） for forecasting the epidemic of Japanese encephalitis （JE） in Xianyang, Shaanxi, China, and provide valuable reference information for JE control and prevention. Methods Theoretically epidemiologic study was employed in the research process. Monthly incidence data on JE for the period from Jan 2005 to Sep 2014 were obtained from a passive surveillance system at the Center for Diseases Prevention and Control in Xianyang, Shaanxi province. An optimal SARIMA model was developed for JE incidence from 2005 to 2013 with the Box and Jenkins approach. This SARIMA model could predict JE incidence for the year 2014 and 2015. Results SARIMA （1, 1, 1） （2, 1, 1）12 was considered to be the best model with the lowest Bayesian information criterion, Akaike information criterion, Mean Absolute Error values, the highest R2, and a lower Mean Absolute Percent Error. SARIMA （1, 1, 1） （2, 1, 1）12 was stationary and accurate for predicting JE incidence in Xianyang. The predicted incidence, around 0.3/100 000 from June to August in 2014 with low errors, was higher compared with the actual incidence. Therefore, SARIMA （1, 1, 1） （2, 1, 1）12 appeared to be reliable and accurate and could be applied to incidence prediction. Conclusions The proposed prediction model could provide clues to early identification of the JE incidence that is increased abnormally （≥0.4/100 000）. According to the predicted results in 2014, the JE incidence in Xianyang will decline slightly and reach its peak from June to August.The authors wish to thank the staff from the CDCs from 13 counties of Xianyang, Shaanxi province, China, for their contribution to Japanese encephalitis cases reporting.

Insights into SO_2 and H_2O co-adsorption on Cu(100) surface with calculations of density functional theory

The co-adsorption behaviors of SO2 and H2 O on face-centered cubic Cu（100） ideal surface were studied using the GGA-r PBE method of density functional theory（DFT） with slab models. The optimized structures of single H2 O and SO2 on Cu（100） surface were calculated at the coverage of 0.25 ML（molecular layer） and 0.5 ML. The results show that there was no obvious chemical adsorption of them on Cu（100） surface. The adsorbed structures, adsorption energy and electronic properties including difference charge density, valence charge density, Bader charge analysis and partial density of states（PDOS） of co-adsorbed structures of H2 O and SO2 were investigated to illustrate the interaction between adsorbates and surface. H2 O and SO2 can adsorb on surface of Cu atoms chemically via molecule form at the coverage of 0.25 ML, while H2 O dissociated into OH adsorbed on surface and H bonded with SO2 which keeps away from surface at the coverage of 0.5 ML.

Getting pre-stack time migration travel times from the single square root operator

Improving the focusing capability of pre-stack time migration allows the imaged section to reflect structural characteristics, depth, and interface shape and it is a key step for the preparation of the initial depth migration velocity model. The traditional symmetrical travel time equation is derived based on the assumption of a layered model. It is difficult to achieve the desired effect of focusing in media with strong lateral variation. The nonsymmetrical travel time equation based on Lie algebra and a pseudo-differential operator contains a lateral velocity derivative which can improve the focusing capability even in strongly lateral variable media and also the computation precision of the weight coefficients for relative amplitude preservation. Compared with the symmetrical methods, the nonsymmetrical method is more effective. In this paper, we describe several key steps of nonsymmetric pre-stack travel time calculation and present some test results using synthetic and real data.

A data-driven method to predict future bottlenecks in a remanufacturing system with multi-variant uncertainties

The remanufacturing system is remolding the manufacturing industry by bringing scrapped products back to such a condition that reintegrated performance is just as good as new.The remanufacturing environment is featured by a far deeper level of uncertainty than new manufacturing,such as probabilistic routing files,and highly variable processing time.The stochastic disturbances result in the production bottlenecks,which constrain the productivity of the job shop.The uncertainties in the remanufacturing process cause the bottlenecks to shift when the workshop is processing.Considering this outstanding problem,many researchers try to optimize the production process to mitigate dynamic bottlenecks toward a balanced state.This paper proposes a data-driven method to predict bottlenecks in the remanufacturing system with multi-variant uncertainties.Firstly,discrete event simulation technology is applied to establish a simulation model of the remanufacturing production line and calculate the bottleneck index to identify bottlenecks.Secondly,a data-driven method,auto-regressive moving average(ARMA)model is employed to predict the bottlenecks in the system based on real-time data captured by the Arena software.Finally,the proposed prediction method is verified on real data from the automobile engine remanufacturing production line.

A hybrid model of a subminiature helicopter in horizontal turn

A hybrid model of a subminiature helicopter in horizontal turn is presented. This model is based on a mechanism model and its compensated neural network （NN）. First, the nonlinear dynamics of a sub-miniature helicopter is established. Through the linearization of the nonlinear dynamics on a trim point, the linear time-invariant mechanism model in horizontal turn is obtained. Then a diagonal recursive neural network is used to compensate the model error between the mechanism model and the nonlinear model, thus the hybrid model of a subminiature helicopter in horizontal turn is achieved. Simulation results show that the hybrid model has higher accuracy than the mechanism model and the obtained compensated-NN has good generalization capability.

Research on Modified Shifting Balance Genetic Algorithms

The increasing overlap of core and colony populations during the anaphase of evolution may limit the performance of shifting balance genetic algorithms. To decrease such overlapping,so as to increase the local search capability of the core population,the sub-space method was used to generate uniformly distributed initial colony populations over the decision variable space. The core population was also dynamically divided,making simultaneous searching in several local spaces possible. The algorithm proposed in this paper was compared to the original one by searching for the optimum of a complicated multi-modal function. The results indicate that the solutions obtained by the modified algorithm are better than those of the original algorithm.

Rainfall Forecasting Using Fourier Series

The need for accurate rainfall prediction is readily apparent when considering many benefits in which such information would provide for river control, reservoir operation, forestry interests, flood mitigation, etc.. Due to importance of rainfall in many aspects, studies on rainfall forecast have been conducted since a few decades ago. Although many methods have been introduced, all the researches describe the study as complex because it involves numerous variables and still need to be improved. Nowadays, there are various traditional techniques and mathematical models available, yet, there are no result on which method provide the most reliable estimation. AR （auto-regressive）, ARMA （auto-regressive moving average）, ARIMA （auto-regressive integrated moving average） and ANNs （artificial neural networks） were introduced as a useful and efficient tool for modeling and forecasting. The conventional time series provide reasonable accuracy but suffer from the assumptions of stationary and linearity. The concept of neurons was introduced first which then developed to ANNs with back propagation training algorithm. Although certain ANNs） models are equivalent to time series model, but it is limited to short term forecasting. This Paper presents a mathematical approach for rainfall forecasting for Iran on monthly basic. The model is trained for monthly rainfall forecasting and tested to evaluate the performance of the model. The result Shows reasonably good accuracy for monthly rainfall forecasting.

ARMA Modelling for Whispered Speech

The Autoregressive Moving Average （ARMA） model for whispered speech is proposed. with normal speech, whispered speech has no fundamental frequency because of the glottis being semi-opened and turbulent flow being created, and formant shifting exists in the lower frequency region due to the narrowing of the tract in the false vocal fold regions and weak acoustic coupling with the aubglottal system. Analysis shows that the effect of the subglottal system is to introduce additional pole-zero pairs into the vocal tract transfer function. Theoretically, the method based on an ARMA process is superior to that based on an AR process in the spectral analysis of the whispered speech. Two methods, the least squared modified Yule-Walker likelihood estimate （LSMY） algorithm and the Frequency-Domain Steiglitz-Mcbide （FDSM） algorithm, are applied to the ARMA mfldel for the whispered speech. The performance evaluation shows that the ARMA model is much more appropriate for representing the whispered speech than the AR model, and the FDSM algorithm provides a name acorate estimation of the whispered speech spectral envelope than the LSMY algorithm with higher conputational complexity.

Application of the Moving Averaging Technique in Surplus Production Models

Surplus production models are the simplest analytical methods effective for fish stock assessment and fisheries management. In this paper, eight surplus production estimators(three estimation procedures) were tested on Schaefer and Fox type simulated data in three simulated fisheries(declining, well-managed, and restoring fisheries) at two white noise levels. Monte Carlo simulation was conducted to verify the utility of moving averaging(MA), which was an important technique for reducing the effect of noise in data in these models. The relative estimation error(REE) of maximum sustainable yield(MSY) was used as an indicator for the analysis, and one-way ANOVA was applied to test the significance of the REE calculated at four levels of MA. Simulation results suggested that increasing the value of MA could significantly improve the performance of the surplus production model(low REE) in all cases when the white noise level was low(coefficient of variation(CV) = 0.02). However, when the white noise level increased(CV= 0.25), adding the value of MA could still significantly enhance the performance of most models. Our results indicated that the best model performance occurred frequently when MA was equal to 3; however, some exceptions were observed when MA was higher.

Simulations of Vertical and Horizontal Displacement Fields in the 2008 Wenchuan Earthquake

By using the Yoshimitsu Okada and Steketee fault dislocation model,we calculated the vertical and horizontal displacements along the Yingxiu-Beichuan inverse fault and Guanxian-Anxian inverse fault along which the Wenchuan MS8. 0 earthquake occurred in 2008. Compared to the achievements of field surveying along the surface rupture zone,we found that our computational results are comparable to the real displacement variation trend. Furthermore,the computational results indicated that the surface displacement fields vary with the distance from the fault,and the vertical displacement fields show strong inhomogeneity,in which larger displacement is focused on the ends of the fault. However, in contrast to the vertical displacement,the horizontal displacement shows relative uniformity in space.

Study and application of monitoring plane displacement of a similarity model based on time-series images

In order to compensate for the deficiency of present methods of monitoring plane displacement in similarity model tests,such as inadequate real-time monitoring and more manual intervention,an effective monitoring method was proposed in this study,and the major steps of the monitoring method include:firstly,time-series images of the similarity model in the test were obtained by a camera,and secondly,measuring points marked as artificial targets were automatically tracked and recognized from time-series images.Finally,the real-time plane displacement field was calculated by the fixed magnification between objects and images under the specific conditions.And then the application device of the method was designed and tested.At the same time,a sub-pixel location method and a distortion error model were used to improve the measuring accuracy.The results indicate that this method may record the entire test,especially the detailed non-uniform deformation and sudden deformation.Compared with traditional methods this method has a number of advantages,such as greater measurement accuracy and reliability,less manual intervention,higher automation,strong practical properties,much more measurement information and so on.

Analysis of Heat Transfer of a Flat Plate Oscillating Heat Pipe, for Different Surfaces

Recent and constant demands for greater power densities and smaller sizes of electronic systems have stimulated the growth of new designs of different passive heat transfer methods such as heat pipes. Particularly, OHPs （Oscillating Heat Pipes） are relatively novel devices, capable of removing high heat rates over long and short distances with not much temperature drop. This study concentrates on the design, building and assembling a test rig in order to analyse the flow pattern ofdeionised water through a 5 turns flat plate oscillating heat pipe under different heat inputs, which was made in the school of engineering and materials science of the Queen Mary University of London by two energy M.Sc. students. The filling ratio of the water is 40%. Furthermore an experimental study on the OHP thermal performance is carried out in order to examine the effects of different surface wet conditions： super hydrophilic, hydrophilic and cleaned brass. It is demonstrated the formation of liquid slugs and vapour plugs of the water along the channels. The experimental results showed that the hydrophilic surface tends to be more energy efficient. The heat transfer performance of the super-hydrophilic and hydrophilic is higher than brass by 5-12% and 15-20% respectively.

Annual Earnings Analysis with ARIMA for Future Earnings Prediction

This study investigates annual earnings analysis with ARIMA （Autoregressive Integrated Moving Average） for future earnings prediction. Earnings prediction is very important to be used in various aspect of decision making process, such as： investor, creditor, analyst, academicians, practitioners, etc.. Evidence supports the ARIMA model that it is more accurate. It also has a smaller size of error value.

Lattice Boltzmann Simulation of One Particle Migrating in a Pulsating Flow in Microvessel

A lattice Boltzmann model of two dimensions is used to simulate the movement of a single rigid particle suspended in a pulsating flow in micro vessel The particle is as big as a red blood cell, and the micro vessel is four times as wide as the diameter of the particle. It is found that Segrd-Silberberg effect will not respond to the pulsation of the flow when the Reynolds number is relatively high. However, when the Reynolds number is low enough, Segrd-Silberberg effect disappears. In the steady flow, different initial position leads to different equilibrium positions. In a pulsating flow, different frequencies of pulsation also cause different equilibrium positions. Particularly, when the frequency of pulsation is closed to the human heart rate, Segrd-Silberberg effect presents again. The evolutions of velocity, rotation, and trajectory of the particle are investigated to find the dynamics of such abnormal phenomenon.