Soluble dendrimers europium(III) β-diketonate complex for organic memory devices

We report the synthesis of a soluble dendrimers europium(III) complex, tris(dibenzoylmethanato)(1,3,5-tris[2-(2′-pyridyl)benzimidazoly]methylbenzene)-europium(III), and its application in organic electrical bistable memory device. Excellent stability that ensured more than 10⁶ write-read-erase-reread cycles has been performed in ambient conditions without current-induced degradation. High-density, low-cost memory, good film-firming property, fascinating thermal and morphological stability allow the application of the dendrimers europium(III) complex as an active medium in non-volatile memory devices.     

Hierarchical image segmentation based on similarity of NDVI time series

Although a variety of hierarchical image segmentation procedures for remote sensing imagery have been published, none of them specifically integrates remote sensing time series in spatial or hierarchical segmentation concepts. However, this integration is important for the analysis of ecosystems which are hierarchical in nature, with different ecological processes occurring at different spatial and temporal scales. Therefore, the objective of this paper is to introduce a multi-temporal hierarchical image segmentation (MTHIS) methodology to generate a hierarchical set of segments based on spatial similarity of remote sensing time series. MTHIS employs the similarity of the fast Fourier transform (FFT) components of multi-seasonal time series to group pixels with similar temporal behavior into hierarchical segments at different scales. Use of the FFT allows the distinction between noise and vegetation related signals and increases the computational efficiency. The MTHIS methodology is demonstrated on the area of South Africa in an MTHIS protocol for Normalized Difference Vegetation Index (NDVI) time series. Firstly, the FFT components that express the major spatio-temporal variation in the NDVI time series, the average and annual term, are selected and the segmentation is performed based on these components. Secondly, the results are visualized by means of a boundary stability image that confirms the accuracy of the algorithm to spatially group pixels at different scale levels. Finally, the segmentation optimum is determined based on discrepancy measures which illustrate the correspondence of the applied MTHIS output with landcover-landuse maps describing the actual vegetation. In future research, MTHIS can be used to analyze the spatial and hierarchical structure of any type of remote sensing time series and their relation to ecosystem processes.     

CNC存储器的体系结构

介绍了CNC使用的存储器类型，硬件体系结构，存储的软件和数据类型及CNC存储器的发展趋势。     

Dynamic neural network modeling for nonlinear, nonstationary machine tool thermally induced error

This paper presents a new modeling methodology for nonstationary machine tool thermal errors. The method uses the dynamic neural network model to track nonlinear time-varying machine tool errors under various thermal conditions. To accommodate the nonstationary nature of the thermo-elastic process, an Integrated Recurrent Neural Network (IRNN) is introduced to identify the nonstationarity of the thermo-elastic process with a deterministic linear trend. Experiments on spindle thermal deformation are conducted to evaluate the model performance in terms of model estimation accuracy and robustness. The comparison indicates that the IRNN performs better than other modeling methods, such as, multi-variable regression analysis (MRA), multi-layer feedforward neural network (MFN), and recurrent neural network (RNN), in terms of model robustness under a variety of working conditions.     

Accuracy evaluation of machine tools by modeling spherical deviation based on double ball-bar measurements

In this study, the accuracy of a machine tool was evaluated by modeling the spherical deviation based on double ball-bar measurements under unloaded conditions. Circular measurement paths on the XY-, YZ-, and ZX-planes were planned, and three linear axis drives were commanded to follow the paths describing a nominal sphere. The spherical deviation, defined as the maximum radial range of deviations around a least-squares sphere, is affected by the accuracies of the three linear axes together. Therefore, the spherical deviation represents the accuracy of machine tools by quantifying the effect of the accuracies of three linear axes, whereas the circular deviation only quantifies the accuracies of two linear axes among the three linear axes. In this experimental study, spherical deviations of vertical/horizontal machine tools were measured and analyzed under various nominal lengths of a double ball-bar for various feed rates. The measurement uncertainty of the measured spherical deviation was investigated to determine the confidence interval.     

ANALYSIS AND IMPROVEMENT OF RECURRENT CORRELATION NEURAL NETWORKS

This paper analyzes the relationship between capacity and dynamics in recurrent correlation neural network, and points out that in some conditions the recurrent correlation neural network has high memory capacity. Then this paper presents several methods for improving the performance.     

双作用液压缸在冲压机中的新应用

通过对传统冲床与双作用液压缸冲床的机构及工作过程的分析,得到在近似相同的工作时间内,新型机床的功耗降低了25%.因此,通过改进传统冲压机床的操作控制系统,实现机-电-液-体化,提高工作效率,节约能源.     

Machine intelligence arbitration for geometrical form errors and geometrical adaptive control strategy

Evaluation of form errors is specified by the ISO in terms of the minimum-zone concept. A method is proposed for numerically determining the form errors based on the minimum-zone evaluation, and a general criterion is given for arbitrating the form errors. A general procedure for “machine-intelligent” arbitration is developed for geometrical form errors. A geometrical adaptive control strategy is presented on the basis of machine-intelligent arbitration. The use of the control strategy provides a convenient structure for the control system and produces an optimal control procedure for the cutting and grinding processes.     

Cationic starches as gas hydrate kinetic inhibitors

This work investigated the kinetic inhibiting effect of a number of cationic starches in hydrate formation experiments with methane and methane/ethane and methane/propane gas mixtures. The starches were found to exhibit a very weak inhibiting effect except for tapioca starch which increased the induction time (delay of onset of crystallization) by an order of magnitude. The addition of polyethylene oxide (PEO) was found to further enhance the performance of tapioca starch as well as some of the other starches. Finally, the presence of tapioca starch and PEO was found to suppress the memory effect. The results were interpreted based on a mechanism proposed by Zeng et al. [2006a. Effect of antifreeze protein on nucleation, growth and memory of gas hydrates. A.I.Ch.E. Journal 52(9), 3304-3309; 2006b. Effect of antifreeze proteins on the nucleation, growth and the memory during tetrahydrofuran clathrate hydrate formation. Journal of the American Chemical Society 128, 2844-2850] whereby the starches interfere with nucleation through interactions with heterogeneous nucleation sites.