Hierarchically adaptive image block matching under complicated illumination conditions

Image block matching is one of active research fields in image processing, which has been widely used in security monitoring and motion estimation. Due to great disparities in images of the same scene under various illumination, block matching has been a challenging task. To this end, we propose a hierarchical block matching method which is adaptive to the computational complexity and suited to complicated illumination environments. The approach is divided into two parts. First, in order to reduce searching time, the whole algorithm is established in the framework of pyramid structures. Second, the correlation coefficient and structural functions are adopted to evaluate the similarity between two images so as to get better matching results. Simulation results show that, compared with the classical three-step, four-step searching algorithms and OHBM algorithm, this algorithm can reduce the time complexity efficiently. Moreover, since the algorithm makes use of the structure details of images, it is robust to complicated scenes.

One-Step Fabrication of Inverted Pyramid Textured Silicon Wafers via Silver-Assisted Chemical Etching Combing with Synergism of Polyvinylpyrrolidone (PVP)

Inverted pyramid-texturing of silicon surface has been proven to have great application potential in silicon solar cells. In this paper, we utilized Ag-assisted chemical etching (Ag–ACE) technology combing with polyvinylpyrrolidone (PVP) to fabricate an inverted pyramid textured Si surface. We call it Ag@PVP–ACE. The effect of different experimental parameters on etching results was observed. We show that the microstructure of the Si surface exhibited two states as the concentration of NH4HF2 and PVP concentration changed: polishing and inverted pyramid texturing. Meanwhile, we found inverted pyramids easier to form at the high temperature and low H2O2 concentration of the etching system. Consequently, compared to inverted pyramid structures fabricated by nanostructure rebuilding (NSR) technology and Ag@PVP–ACE, we consider that Ag@PVP–ACE technology could become a viable strategy for fabricating inverted pyramid textured Si wafers in Si solar cells production.

Ownership concentration in the Gulf Cooperation Council

PurposeThis article attempts to answer the following questions: Who ultimately owns firms listed in the Gulf Cooperation Council (GCC) countries? Does ownership structure depend on the institutional context? How does ownership affect firm performance? Do institutional factors influence the ownership–performance relationship?Design/methodology/approachWe apply univariate analyses and generalised methods of moments estimations for a sample of 692 GCC listed firms during 2009–2015.FindingsOur results reveal that corporations are mainly controlled by the state or families, the ownership structure is highly concentrated and pyramid structures are common in the region. Ownership is more concentrated in non-financial than financial firms, and ownership concentration and shareholder identity differ by institutional country setting. Finally, ownership concentration does not influence performance, but formal institutions play a moderating role in the relationship.Practical implicationsAs our findings reveal potential type II agency problems due to ownership concentration, policymakers should raise awareness of professional corporate governance practices and tailor them to GCC countries’ institutional contexts.Social implicationsEven with the introduction of new regulations by some GCC states to protect minority investors and promote corporate governance practices, ownership concentration is a rigid structure, and its use by investors to protect their economic endowment and power is culturally embedded.Originality/valueAlthough previous studies have analysed ownership concentration and large shareholders’ identities across countries, this study fills a research gap investigating this phenomenon in-depth in emerging economies.

A Review of Techniques for 3D Reconstruction of Indoor Environments

Indoor environment model reconstruction has emerged as a significant and challenging task in terms of the provision of a semantically rich and geometrically accurate indoor model. Recently, there has been an increasing amount of research related to indoor environment reconstruction. Therefore, this paper reviews the state-of-the-art techniques for the three-dimensional (3D) reconstruction of indoor environments. First, some of the available benchmark datasets for 3D reconstruction of indoor environments are described and discussed. Then, data collection of 3D indoor spaces is briefly summarized. Furthermore, an overview of the geometric, semantic, and topological reconstruction of the indoor environment is presented, where the existing methodologies, advantages, and disadvantages of these three reconstruction types are analyzed and summarized. Finally, future research directions, including technique challenges and trends, are discussed for the purpose of promoting future research interest. It can be concluded that most of the existing indoor environment reconstruction methods are based on the strong Manhattan assumption, which may not be true in a real indoor environment, hence limiting the effectiveness and robustness of existing indoor environment reconstruction methods. Moreover, based on the hierarchical pyramid structures and the learnable parameters of deep-learning architectures, multi-task collaborative schemes to share parameters and to jointly optimize each other using redundant and complementary information from different perspectives show their potential for the 3D reconstruction of indoor environments. Furthermore, indoor–outdoor space seamless integration to achieve a full representation of both interior and exterior buildings is also heavily in demand.

Pyramid Constrained Self-Attention Network for Fast Video Salient Object Detection

Spatiotemporal information is essential for video salient object detection (VSOD) due to the highly attractive object motion for human's attention. Previous VSOD methods usually use Long Short-Term Memory (LSTM) or 3D ConvNet (C3D), which can only encode motion information through step-by-step propagation in the temporal domain. Recently, the non-local mechanism is proposed to capture long-range dependencies directly. However, it is not straightforward to apply the non-local mechanism into VSOD, because i) it fails to capture motion cues and tends to learn motion-independent global contexts; ii) its computation and memory costs are prohibitive for video dense prediction tasks such as VSOD. To address the above problems, we design a Constrained Self-Attention (CSA) operation to capture motion cues, based on the prior that objects always move in a continuous trajectory. We group a set of CSA operations in Pyramid structures (PCSA) to capture objects at various scales and speeds. Extensive experimental results demonstrate that our method outperforms previous state-of-the-art methods in both accuracy and speed (110 FPS on a single Titan Xp) on five challenge datasets. Our code is available at https://github.com/guyuchao/PyramidCSA.

Nano/Microscale Thermal Field Distribution: Conducting Thermal Decomposition of Pyrolytic-Type Polymer by Heated AFM Probes

In relevant investigations and applications of the heated atomic force microscope (AFM) probes, the determination of the actual thermal distribution between the probe and the materials under processing or testing is a core issue. Herein, the polyphthalaldehyde (PPA) film material and AFM imaging of the decomposition structures (pyrolytic region of PPA) were utilized to study the temperature distribution in the nano/microscale air gap between heated tips and materials. Different sizes of pyramid decomposition structures were formed on the surface of PPA film by the heated tip, which was hovering at the initial tip–sample contact with the preset temperature from 190 to 220 °C for a heating duration ranging from 0.3 to 120 s. According to the positions of the 188 °C isothermal surface in the steady-state probe temperature fields, precise 3D boundary conditions were obtained. We also established a simplified calculation model of the 3D steady-state thermal field based on the experimental results, and calculated the temperature distribution of the air gap under any preset tip temperature, which revealed the principle of horizontal (<700 nm) and vertical (<250 nm) heat transport. Based on our calculation, we fabricated the programmable nano-microscale pyramid structures on the PPA film, which may be a potential application in scanning thermal microscopy.

A broadband ultraviolet light source using GaN quantum dots formed on hexagonal truncated pyramid structures

Broadband ultraviolet solid-state light emitter has been demonstrated based on the combined structure of MOCVD grown microstructure and the MBE grown quantum dots, thanks to the strain inhomogeneity of the multi-facet semiconductor microstructure.

Fabrication of Pyramid Structure Substrate Utilized for Epitaxial Growth Free-Standing GaN

Metal–organic chemical vapor deposition (MOCVD)-grown GaN on sapphire substrate was etched by hot phosphoric acids. Pyramid structures were obtained in the N-polar face of the MOCVD–GaN. Details of the formation process and morphology of the structures were discussed. The crystallographic plane index of the pyramid facet was calculated dependent on the symmetry of the wurtzite crystal structure and the tilt angle. The substrates with pyramid structures were utilized in subsequent hydride vapor phase epitaxy (HVPE) growth of GaN. Free-standing crystals were obtained, while HVPE-grown GaN achieved a certain thickness. Raman spectroscopy was employed to obtain the stress conditions of the HVPE–GaN without and with sapphire substrate. The mechanism of the self-separation process was discussed. This facile wet etching method may provide a simple way to acquire free-standing GaN by HVPE growth.