基于非下采样Shearlet变换与模糊对比度的合成孔径雷达图像增强

针对合成孔径雷达（SAR）图像在成像和传输过程中引入噪声和干扰从而导致图像清晰度下降、细节丢失等问题,提出了一种非下采样Shearlet变换（NSST）与模糊对比度的SAR图像增强算法。首先,原始图像经NSST分解成一个低频分量和若干个高频分量;然后对低频分量进行线性增强以提高整体对比度,对高频分量采用阈值法进行增强以去除图像中的噪声;接着对处理后的两部分分量进行NSST反变换得到重构图像;最后采用模糊对比度算法对重构图像进行增强,提高图像细节信息和层次感,得到增强后的图像。对40幅图像的实验结果表明,与直方图均衡化、多尺度Retinex增强算法、基于Shearlet变换和多尺度Retinex的遥感图像增强算法、基于剪切波域改进Gamma校正的医学图像增强算法相比,该算法的图像峰值信噪比至少提升了22.9%,均方根误差至少降低了36.2%,能明显提升图像的清晰度,使图像的纹理信息更加清晰。     

Impact of mechanical stress on barium titanate-based positive temperature coefficient resistive material

The sensitivity toward mechanical stress of barium titanate-based positive temperature coefficient resistor material was investigated by determining the resistance change with application of uniaxial stress from room temperature to 200 °C, which is well above the Curie temperature T_C. Using the Landau–Ginsburg–Devonshire theory the resistance increases in the paraelectric state, the negligible impact of stress close to T_C and the observed increase in T_C with increasing stress could be rationalized. For the ferroelectric state, the stress-related resistance increase was attributed to ferroelasticity, a change in bulk permittivity and interfacial stress inducing a piezoelectric potential. The obtained results are also discussed with respect to recent endeavors to tune properties of potential barriers in piezoelectric semiconductors by mechanical stress.     

Comparison of direct electrocaloric characterization methods exemplified by 0.92 Pb(Mg1/3Nb2/3)O3‐0.08 PbTiO3 multilayer ceramics

Electrocaloric device structures have been developed as multilayer ceramics (MLCs) based on fundamental research carried out on PMN‐8PT bulk ceramics. Two different MLC structures were prepared with nine layers each and layer thicknesses of 86 μm and 39 μm. The influence of the device design on its properties has been characterized by microstructural, dielectric, ferroelectric, and direct electrocaloric measurement. For direct characterization two different methods, ie temperature reading (thermistor and thermocouple) and heat flow measurement (differential scanning calorimetry), were used. A comparison of results revealed a highly satisfactory agreement between the different methods. This study confirms that MLCs are promising candidates for implementation into energy‐efficient electrocaloric cooling systems providing large refrigerant volume and high electrocaloric effect. Due to their micron‐sized active layers, they allow for the application of high electric fields under low operation voltages. We measured a maximum electrocaloric temperature change of ΔT=2.67 K under application/withdrawal of an electric field of ΔE=16 kV mm^?1, which corresponds to operation voltages below 1.5 kV.     

Predicting piezometric water level in dams via artificial neural networks

The safety control of dams is based on measurements of parameters of interest such as seepage flows, seepage water clarity, piezometric levels, water levels, pressures, deformations or movements, temperature variations, loading conditions, etc. Interpretation of these large sets of available data is very important for dam health monitoring and it is based on mathematical models. Modelling seepage through geological formations located near the dam site or dam bodies is a challenging task in dam engineering. The objective of this study is to develop a feedforward neural network (FNN) model to predict the piezometric water level in dams. An improved resilient propagation algorithm has been used to train the FNN. The measured data have been compared with the results of FNN models and multiple linear regression (MLR) models that have been widely used in analysis of the structural dam behaviour. The FNN and MLR models have been developed and tested using experimental data collected during 9 years. The results of this study show that FNN models can be a powerful and important tool which can be used to assess dams.     

Soundness verification for conceptual workflow nets with data: Early detection of errors with the most precision possible

A conceptual workflow model specifies the control flow of a workflow together with abstract data information. This model is later on refined by adding specific data information, resulting in an executable workflow which is then run on an information system. It is desirable that correctness properties of the conceptual workflow are transferable to its refinements. In this paper, we present classical workflow nets extended with data operations as a conceptual workflow model. For these nets, we develop a novel technique to verify soundness. An executable workflow is sound if from every reachable state it is always possible to terminate properly. Our technique allows us to analyze a conceptual workflow and to conclude whether there exists at least one sound refinement of it, and whether any refinement of a conceptual workflow model is sound. The positive answer to the first question in combination with the negative answer to the second question means that sound and unsound refinements for the conceptual workflow in question are possible.     

Relating the structural strength of concrete sewer pipes and material properties retrieved from core samples

Drill core samples are taken in practice for an analysis of the material characteristics of concrete pipes in order to improve the quality of the decision-making on rehabilitation actions. Earlier research has demonstrated that core sampling is associated with a significant uncertainty. In this paper, the results of core samples are compared with the results of full-scale pipe cracking lab experiments. It is shown that the concrete of deteriorated sewer pipes shows a significant variability in material characteristics. Further it is shown that the formation of ettringite due to biochemical sulphuric corrosion is not necessarily limited to the crown of the pipe and also degradation of pipe material, measured by the carbonation depth, is occurring at the inside and outside of the pipe. It is concluded that tensile splitting strength and the carbonation depth are the two material property parameters of core sampling with a sufficiently high correlation (R² > .90) with the structural strength of the pipe. The thickness of the remaining ‘healthy’ concrete material is the optimal parameter, as this requires the smallest sampling size.     

Microscopic Models and Network Transformations for Automated Railway Traffic Planning

This article tackles the real‐world planning problem of railway operations. Improving the timetable planning process will result in more reliable product plans and a higher quality of service for passengers and freight operators. We focus on the microscopic models for computing accurate track blocking times for guaranteeing feasibility and stability of railway timetables. A conflict detection and resolution model manages feasibility by identifying conflicts and computing minimum headway times that provide conflict‐free services. The timetable compression method is used for computing capacity consumption and verifying the stability according to the UIC Capacity Code 406. Furthermore, the microscopic models have been incorporated in a multilevel timetabling framework for completely automated generation of timetables. The approach is demonstrated in a real‐world case study from the Dutch railway network. Practitioners can use these microscopic timetabling models as an important component in the timetabling process to improve the general quality of timetables.     

Creating Oxidase–Peroxidase Fusion Enzymes as a Toolbox for Cascade Reactions

A set of bifunctional oxidase–peroxidases has been prepared by fusing four distinct oxidases to a peroxidase. Although such fusion enzymes have not been observed in nature, they could be expressed and purified in good yields. Characterization revealed that the artificial enzymes retained the capability to bind the two required cofactors and were catalytically active as oxidase and peroxidase. Peroxidase fusions of alditol oxidase and chitooligosaccharide oxidase could be used for the selective detection of xylitol and cellobiose with a detection limit in the low-micromolar range. The peroxidase fusions of eugenol oxidase and 5-hydroxymethylfurfural oxidase could be used for dioxygen-driven, one-pot, two-step cascade reactions to convert vanillyl alcohol into divanillin and eugenol into lignin oligomers. The designed oxidase–peroxidase fusions represent attractive biocatalysts that allow efficient biocatalytic cascade oxidations that only require molecular oxygen as an oxidant.