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.     

Evaluation of direct light processing for the fabrication of bioactive ceramic scaffolds: Effect of pore/strut size on manufacturability and mechanical performance

Bioactive ceramic scaffolds for bone regeneration consisting of a three-dimensional mesh of interpenetrating struts with square section were fabricated via Digital Light Processing (DLP). The ability of the technique to manufacture 3D porous structures from β-tricalcium phosphate (β-TCP) powders with different dimensions of struts and pores was evaluated, identifying the possibilities and limitations of the manufacturing process. Small pore sizes were found to seriously complicate the elimination of excess slurry from the scaffold’s innermost pores. The effect of the strut/pore size on the mechanical performance of the scaffolds under compressive stresses was also evaluated, but no significant influence was found. Under compressive stresses, the structures resulted weaker when tested perpendicularly to the printing plane due to interlayer shear failure. Interlayer superficial grooves are proposed as potential failure-controlling defects, which could also explain the lack of a Weibull size effect on the mechanical strength of the fabricated DLP scaffolds.     

Fabrication and properties of 3D printed zirconia scaffold coated with calcium silicate/hydroxyapatite

The scaffold of bone repair needs a variety of material combinations to meet its intended performance; a typical single material such as zirconia has excellent mechanical properties, while hydroxyapatite and calcium silicate are bioactive materials with different degradation rates. In this paper, porous zirconia scaffolds were fabricated using 3D printing technology. The surface of the scaffold was coated by dipping with different contents of calcium silicate and hydroxyapatite to improve the biological activity and mechanical properties. Mechanical tests show that the coating material can effectively fill the pores of the porous scaffold, increasing its compressive strength by an average of 55%. The simulated body fluid (SBF) test showed that the higher calcium silicate in the coating increased the degradation rate. Cell experiments showed that the coated scaffolds exhibited good cytocompatibility and were beneficial to the proliferation and differentiation of cells. In conclusion, coated scaffolds have potential applications in the field of bone repair.     

Determinants of the intention to use non-medical insertable digital devices: The case of Chile and Colombia

In the past, thinking of carrying electronic devices inside our bodies was only posed by non-real scenarios. The emergence of insertable devices has changed this. Since this technology is still in its initial development stages, few studies have investigated factors that influence its acceptance. This paper analyzes the predictors of the intention to use non-medical insertable devices in two Latin American contexts. We used partial least squares structural equation modeling to examine whether six constructs predicted intention to use insertable devices. A questionnaire was administered to undergraduate students located in Colombia and Chile (n = 672). We also examined whether these predictors influenced intention differently for both of them. Four common constructs significantly and positively influenced both Chilean and Colombian respondents to use insertable devices (hedonic motivation, habit, performance expectancy, and social influence). Also, the habit has a complementary mediating effect on the relationship between social influence and behavioral intention. By contrast, effort expectations were a positive and significant predictor, but only among Chilean respondents. Findings suggest that when technologies are emerging, well-known predictors of intention (e.g., performance and effort expectations) are less influential than predictors related to self-efficacy (e.g., habit and hedonic motivation). The use of insertable devices has a significant impact on society. Thus, a better understanding of what motivates their use has implications for both academia and industry.     

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。     

Secure image encryption scheme using 4D-Hyperchaotic systems based reconfigurable pseudo-random number generator and S-Box

This paper introduces the design of a hardware efficient reconfigurable pseudorandom number generator (PRNG) using two different feedback controllers based four-dimensional (4D) hyperchaotic systems i.e. Hyperchaotic-1 and -2 to provide confidentiality for digital images. The parameter's value of these two hyperchaotic systems is set to be a specific value to get the benefits i.e. all the multiplications (except a few multiplications) are performed using hardwired shifting operations rather than the binary multiplications, which doesn't utilize any hardware resource. The ordinary differential equations (ODEs) of these two systems have been exploited to build a generic architecture that fits in a single architecture. The proposed architecture provides an opportunity to switch between two different 4D hyperchaotic systems depending on the required behavior. To ensure the security strength, that can be also used in the encryption process in which encrypt the input data up to two times successively, each time using a different PRNG configuration. The proposed reconfigurable PRNG has been designed using Verilog HDL, synthesized on the Xilinx tool using the Virtex-5 (XC5VLX50T) and Zynq (XC7Z045) FPGA, its analysis has been done using Matlab tool. It has been found that the proposed architecture of PRNG has the best hardware performance and good statistical properties as it passes all fifteen NIST statistical benchmark tests while it can operate at 79.101-MHz or 1898.424-Mbps and utilize only 0.036 %, 0.23 %, and 1.77 % from the Zynq (XC7Z045) FPGA's slice registers, slice LUTs, and DSP blocks respectively. Utilizing these PRNGs, we design two 16 × 16 substitution boxes (S-boxes). The proposed S-boxes fulfill the following criteria: Bijective, Balanced, Non-linearity, Dynamic Distance, Strict Avalanche Criterion (SAC) and BIC non-linearity criterion. To demonstrate these PRNGs and S-boxes, a new three different scheme of image encryption algorithms have been developed: a) Encryption using S-box-1, b) Encryption using S-box-2 and, c) Two times encryption using S-box-1 and S-box-2. To demonstrate that the proposed cryptosystem is highly secure, we perform the security analysis (in terms of the correlation coefficient, key space, NPCR, UACI, information entropy and image encryption quantitatively in terms of (MSE, PSNR and SSIM)).     

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.     

Microstructural,mechanical properties and strengthening mechanism of DLP produced β-tricalcium phosphate scaffolds by incorporation of MgO/ZnO/58S bioglass

The inherent brittleness of bioceramics restricts their applications in load-bearing implant, although they possess good biocompatibility and bioactivity. ZnO, MgO and 58S bioglass (BG) were incorporated as additives to further improve the mechanical properties and biocompatibility of β-TCP and ZnO/MgO/BG-β-TCP composite scaffolds were manufactured via digital light processing (DLP). The composite with the best comprehensive performance was selected for degradation behavior and biocompatibility evaluation. The effects of different proportions of ZnO/MgO/BG on mechanical strength were analyzed and ZnO0·5/MgO1/BG2-β-TCP (ZMBT) samples exhibited superior mechanical strength. The improvement by 272% and 99% respectively was achieved in fracture toughness and compressive strength with the optimal recipe. The enhancement effect is realized through phase transition, alterative sliding actions and transgranular fracture to effectively prevent the load transfer combining the functions of bioglass and metal oxide. ZMBT scaffolds exhibited a more desirable pH environment and an enhanced ability of apatite-mineralization formation, meanwhile Si⁴⁺, Mg²⁺ and Zn²⁺ were gradually released from scaffolds. Furthermore, in vitro evaluation indicated that ZMBT scaffolds presented not only excellent cell attachment, proliferation, alkaline phosphatase (ALP) activity, but they up-regulated osteogenic gene (ALP, OCN, Runx2). These results suggest that the addition of ZnO/MgO/BG to DLP-printed β-TCP scaffolds offer a smart strategy to fabricate porous scaffolds with conspicuously better biological and physicochemical properties including compressive strength, bioactivity, osteogenesis and osteogenesis-related gene expression. Metal-oxide and BG synergistically enhanced the mechanical and biological properties which make the ZMBT scaffolds a strong candidate for bone repair applications.     

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。