Underwater image super-resolution using multi-stage information distillation networks

Recently, single image super-resolution (SISR) has been widely applied in the fields of underwater robot vision and obtained remarkable performance. However, most current methods generally suffered from the problem of a heavy burden on computational resources with large model sizes, which limited their real-world underwater robotic applications. In this paper, we introduce and tackle the super resolution (SR) problem for underwater robot vision and provide an efficient solution for near real-time applications. We present a novel lightweight multi-stage information distillation network, named MSIDN, for better balancing performance against applicability, which aggregates the local distilled features from different stages for more powerful feature representation. Moreover, a novel recursive residual feature distillation (RRFD) module is constructed to progressively extract useful features with a modest number of parameters in each stage. We also propose a channel interaction & distillation (CI&D) module that employs channel split operation on the preceding features to produce two-part features and utilizes the inter channel-wise interaction information between them to generate the distilled features, which can effectively extract the useful information of current stage without extra parameters. Besides, we present USR-2K dataset, a collection of over 1.6K samples for large-scale underwater image SR training, and a testset with an additional 400 samples for benchmark evaluation. Extensive experiments on several standard benchmark datasets show that the proposed MSIDN can provide state-of-the-art or even better performance in both quantitative and qualitative measurements.     

Turbulent boundary layer control with a spanwise array of DBD plasma actuators

The turbulent boundary layer control on NACA 0012 airfoil with Mach number ranging from 0.3 to 0.5 by a spanwise array of dielectric barrier discharge(DBD)plasma actuators by hot-film sensor technology is investigated.Due to temperature change mainly caused through heat produced along with plasma will lead to measurement error of shear stress measured by hot-film sensor,the correction method that takes account of the change measured by another sensor is used and works well.In order to achieve the value of shear stress change,we combine computational fluid dynamics computation with experiment to calibrate the hot-film sensor.To test the stability of the hot-film sensor,seven repeated measurements of shear stress at Ma = 0.3 are conducted and show that confidence interval of hot-film sensor measurement is from-0.18 to 0.18 Pa and the root mean square is 0.11 Pa giving a relative error 0.5％over all Mach numbers in this experiment.The research on the turbulent boundary layer control with DBD plasma actuators demonstrates that the control makes shear stress increase by about 6％over the three Mach numbers,which is thought to be reliable through comparing it with the relative error 0.5％,and the value is hardly affected by burst frequency and excitation voltage.     

Hydrogen sulfide gas detection by Au-decorated ZnO nanotube: a computational study and comparison to experimental observations

Based on the experimental reports, Au-decoration on the ZnO nanostructures dramatically increases the electronic sensitivity to H₂S gas. In the current study, we computationally scrutinized the mechanism of Au-decoration on a ZnO nanotube (ZON) and the influence on its sensing behavior toward H₂S gas. The intrinsic ZON weakly interacted with the H₂S gas with an adsorption energy of ?11.2 kcal/mol. The interaction showed no effect on the HOMO–LUMO gap and conductivity of ZON. The predicted response of intrinsic ZON toward H₂S gas is 6.3, which increases to 78.1 by the Au-decoration at 298 K. The corresponding experimental values are about 5.0 and 80.0, indicating excellent agreement with our findings. We showed that the Au atom catalyzes the reaction 3O₂?+?2H₂S?→?2SO₂?+?2H₂O. Our calculated energy barrier (at 298 K) is about 12.3 kcal/mol for this reaction. The gap and electrical conductance Au-ZON largely changed by this reaction are attributed to the electron donation and back-donation processes. The obtained recovery time is about 1.35 ms for desorption of generated gases from the surface of the Au-ZON sensor.     

基于光刀图像的机器人示教纠偏方法

为了解决机器人辅助在线检测系统示教过程中效率低、人为干预多的问题,针对孔类特征,提出一种通过处理光刀图像获取机器人位姿纠正参数的方法。在该方法中,纠偏过程按照将图像光刀线调整为水平方向、将被测特征调整至图像中央、根据不同特征调整最优扫描方向3个步骤进行。根据光刀图像可以求出测量坐标系与被测特征的位姿关系,并得到该位姿与理想测量位姿的偏差。经过坐标变换即可得到在机器人基坐标系下的调整参数。另外,可利用电脑控制机器人运动,从而实现了纠偏过程的自动化。实验结果表明,该方法可将初始的示教位姿修正为理想位姿,且比传统方式效率更高。     

Sub-band coding of hexagonal images

According to the circle-packing theorem, the packing efficiency of a hexagonal lattice is higher than an equivalent square tessellation. Consequently, in several contexts, hexagonally sampled images compared to their Cartesian counterparts are better at preserving information content. In this paper, novel mapping techniques alongside the wavelet compression scheme are presented for hexagonal images. Specifically, we introduce two tree-based coding schemes, referred to as SBHex (spirally-mapped branch-coding for hexagonal images) and BBHex (breadth-first block-coding for hexagonal images). Both of these coding schemes respect the geometry of the hexagonal lattice and yield better compression results. Our empirical results show that the proposed algorithms for hexagonal images produce better reconstruction quality at low bits per pixel representations compared to the tree-based coding counterparts for the Cartesian grid.     

Potential influence of microorganisms on the corrosion of carbon steel in the French high- and intermediate-level long-lived radioactive waste disposal context

In the context of the high-level radioactive waste disposal CIGEO, the corrosion rate due to microbially influenced corrosion (MIC) has to be evaluated. In France, it is envisaged to dispose of high- and intermediate-level long-lived radioactive waste at a depth of 500 m in a deep geological disposal, drilled in the Callovo-Oxfordian claystone (Cox) formation. To do so, a carbon steel casing will be inserted inside disposal cells, which are horizontal tunnels drilled in the Cox. A specific cement grout will be injected between the carbon steel casing and the claystone. A study was conducted to evaluate the possibility of MIC on carbon steel in the foreseeable high radioactive waste disposal. The corrosiveness of various environments was investigated at 50°C and 80°C with or without microorganisms enriched from samples of Andra's underground research laboratory. The monitoring of corrosion during the experiments was ensured using gravimetric method and real-time corrosion monitoring using sensors based on the measurements of the electrical resistance. The corrosion data were completed with microbiological analyses including cultural and molecular characterizations.     

基于PMU的电力系统监控体系结构优化设计

文中提出了一种利用有限数量的相量测量单元(PMU)和相量数据集中器(PDC)设计最优监控结构的方法。通过在大量的设定值场景下,使电力系统可观测性曲线的期望值最大化,同时使通信基础设施成本最小化,最终确定PMU和PDC的最佳位置。提出了一种非线性动态扩展卡尔曼滤波(EFK)状态观测器。这种状态观测器可以将暂态行为转换为由代数微分方程描述的广域电力系统,而无需非线性反演技术。最后以IEEE-5电力系统为例,说明了该方法的有效性。     

基于改进残差特征蒸馏的轻量级超分辨率网络

基于深度学习的图像超分辨率算法通常采用递归的方式或参数共享的策略来减少网络参数，这将增加网络的深度，使得运行网络花费大量的时间，从而很难将模型部署到现实生活中。为了解决上述问题，本文设计一种轻量级超分辨率网络，对中间特征的关联性及重要性进行学习，且在重建部分结合高分辨率图像的特征信息。首先，引入层间注意力模块，通过考虑层与层之间的相关性，自适应地分配重要层次特征的权重。其次，使用增强重建模块提取高分辨率图像中更精细的特征信息，以此得到更加清晰的重建图片。通过大量的对比实验表明，本文设计的网络与其他轻量级模型相比，有更小的网络参数量，并且在重建精度和视觉效果上都有一定的提升。     

Effect of heat treatment on structural,morphological, dielectric and magnetic properties of Mg–Zn ferrite nanoparticles

Green combustion was used to prepare a ferrite composition of Mg_0.4Zn_0.6Fe₂O₄ using a blend of fresh lemon juice as a natural fuel-reductant. Effect of heat treatment on phase, morphological, dielectric, and humidity sensor properties is discussed. The formation of a cubic spinel ferrite has been established by XRD-diffraction and vibrational spectroscopic studies. The experimental lattice parameter ranges from 8.3721 to 8.3631 Å. The broadening of octahedral band (υ₂) in the vibrational spectra is an identification for the existence of ferrite nanoparticles in various sizes. The typical crystallite size ranges from 10.2 to 36.9 nm. Using micrographs obtained from field-effect scanning electron microscopy (FESEM), researchers observed a spherical-shaped microstructure with agglomerated nanoparticles. Dielectric investigations have shown that the current ferrite composition has typical dielectric dispersion. The highest reported value for saturation magnetization (M_s) in the present study is 33 emu/g. Magnetic behaviour is primarily influenced by magnetocrystalline anisotropy, cation distribution, and crystallite size. The existence of void spaces in the sintered samples, as well as their porous nature, rendered them suitable for humidity sensor applications. Sintered samples have good sensing capability at 900 °C. The current findings are integrated in terms of cation distribution and magnetocrystalline anisotropy, assuming fine size effects of ferrite nanoparticles.