Predicting visual similarity between colour palettes

This work is concerned with the prediction of visual colour difference between pairs of palettes. In this study, the palettes contained five colours arranged in a horizontal row. A total of 95 pairs of palettes were rated for visual difference by 20 participants. The colour difference between the palettes was predicted using two algorithms, each based on one of six colour-difference formulae. The best performance (r² = 0.86 and STRESS = 16.9) was obtained using the minimum colour-difference algorithm (MICDM) using the CIEDE2000 equation with a lightness weighing of 2. There was some evidence that the order (or arrangement) of the colours in the palettes was a factor affecting the visual colour differences although the MICDM algorithm does not take order into account. Application of this algorithm is intended for digital design workflows where colour palettes are generated automatically using machine learning and for comparing palettes obtained from psychophysical studies to explore, for example, the effect of culture, age, or gender on colour associations.     

Surface structural and solar absorptance features of nitrate-based copper-cobalt oxides composite coatings: Experimental studies and molecular dynamic simulation

The copper and cobalt oxides composites coatings on aluminum substrates have been successfully synthesized via sol-gel method using nitrate-based sol precursors. The composites were characterized by X-ray Diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Field Emission Scanning Electron Microscopy (FESEM), Atomic Force Microscopy (AFM), and UV–Vis–NIR spectrophotometry. The sol-gel reactions were discussed and Molecular Dynamics (MD) simulation was integrated into the study to predict molecules assembly properties. The XRD analyses revealed that the CuO and the Co₃O₄ composites were formed after the annealing process with the average difference of the calculated lattice parameters compared to ICDDs was 1.17%. The surface electronic structure was mainly consisted of tetrahedral Cu(I), octahedral Cu(II), tetrahedral Co(II), octahedral Co(III) as well as surface, sub-surface and lattice oxygen O^?. The XRD, XPS and MD simulation results showed that there was minimal (or possibly non-existing) indication of copper-cobalt mixed phase oxides formations. FESEM and AFM surveys revealed that the coating had a porous surface composed of interlinked nanoparticles in the range of ~?10 to ~?40?nm. UV–Vis–NIR reflectance spectra showed that the sol precursors concentration and the dip-drying cycle significantly influenced the absorptance value with optimum absorptance (α) of 88.7% exhibited by coating synthesized using sol concentration of 0.1?M and 10 dip-drying cycles. High absorptance value and simplicity in the synthesis process render the coatings to be very promising candidates for solar selective absorber (SSA) applications.     

基于注意力机制与文本信息的用户关系抽取

随着社交媒体的发展,用户之间的关系网络对于社交媒体的分析有很大的帮助。因此,该文主要研究用户好友关系检测。以往的关于用户好友关系抽取的研究主要基于社交媒体上的结构化信息,比如其他好友关系,用户的不同属性等。但是,很多时候用户本身并没有大量的好友信息存在,同时也不一定有很多确定的属性。因此,我们希望基于用户发表的文本信息来对用户关系进行预测。不同于以往的潜在好友推荐算法,该文提出了一种基于注意力机制以及长短时记忆网络(long short-term memory,LSTM)的好友关系预测模型,将好友之间的评论分开处理,通过分析用户之间的评论来判断是否具备一定的好友关系。该模型将好友双方信息拼接后的结果作为输入,并将注意力机制应用于LSTM的输出。实验表明,用户之间的评论对于好友关系预测确实有较大的实际意义,该文提出的模型较之于多个基准系统的效果,取得了明显的提升。在不加入任何其它非文本特征的情况下,实验结果的准确率达到了77%。     

Multi-objective layout optimization for an orbital propellant depot

Structural and Multidisciplinary Optimization - The overall layout optimization design of an orbital propellant depot involves the optimization of shape, size, and positions of propellant tanks in...     

Image Super-Resolution Based on Generative Adversarial Networks: A Brief Review

Single image super resolution (SISR) is an important research content in the field of computer vision and image processing. With the rapid development of deep neural networks, different image super-resolution models have emerged. Compared to some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods using traditional convolutional neural networks, SISR based on generative adversarial networks (GAN) has achieved the most advanced visual performance. In this review, we first explore the challenges faced by SISR and introduce some common datasets and evaluation metrics. Then, we review the improved network structures and loss functions of GAN-based perceptual SISR. Subsequently, the advantages and disadvantages of different networks are analyzed by multiple comparative experiments. Finally, we summarize the paper and look forward to the future development trends of GAN-based perceptual SISR.     

Corrosion behavior of Cu–Sn bronze alloys in simulated archeological soil media

The corrosion behavior of synthetic Cu–Sn bronze alloys with six different Sn contents was examined through an electrochemical test and a synthetic test in a simulated corrosive medium. The mechanism of corrosion and the morphology of the corroded surfaces were characterized through field emission scanning electron microscopy equipped with energy-dispersive spectroscopy. At the corrosion potential, the corrosion behavior appears to be determined by the charge transfer step and the diffusion process. It was found that the bronze-IV (Cu–26.8Sn) specimen exhibited the best corrosion resistance, as evidenced by a low corrosion current density and a high impedance. This improvement resulted from an increase in the content of the Cu–Sn solid solution in the alloy, which was conducive to forming a relatively more protective passive film on the surface of the bronze alloy. This finding would be valuable in the anticorrosion protection of archeological artefacts after their excavation.     

Facile construction of composition-tuned ruthenium-nickel nanoparticles on g-C3N4 for enhanced hydrolysis of ammonia borane without base additives

Developing high-efficiency and low-cost catalysts for hydrogen evolution from hydrolysis of ammonia borane (AB) is significant and critical for the exploitation and utilization of hydrogen energy. Herein, the in-situ fabrication of well-dispersed and small bimetallic RuNi alloy nanoparticles (NPs) with tuned compositions and concomitant hydrolysis of AB are successfully achieved by using graphitic carbon nitride (g-C₃N₄) as a NP support without additional stabilizing ligands. The optimized Ru₁Ni_7.5/g-C₃N₄ catalyst exhibits an excellent catalytic activity with a high turnover frequency of 901 min^?1 and an activation energy of 28.46 kJ mol^?1 without any base additives, overtaking the activities of many previously reported catalysts for AB hydrolysis. The kinetic studies indicate that the AB hydrolysis over Ru₁Ni_7.5/g-C₃N₄ is first-order and zero-order reactions with respect to the catalyst and AB concentrations, respectively. Ru₁Ni_7.5/g-C₃N₄ has a good recyclability with 46% of the initial catalytic activity retained even after five runs. The high performance of Ru₁Ni_7.5/g-C₃N₄ should be assigned to the small-sized alloy NPs with abundant accessible active sites and the synergistic effect between the composition-tuned Ru–Ni bimetals. This work highlights a potentially powerful and simple strategy for preparing highly active bimetallic alloy catalysts for AB hydrolysis to generate hydrogen.     

溪洛渡水电站导流洞布置设计

溪洛渡水电站施工期采用左、右岸各布置3条导流洞的施工导流方案,无论是导流洞规模、单洞泄流量还是导流洞断面尺寸均居国内已建和在建导流洞的前列,特别是6条大断面尺寸的导流洞布置规模,在世界上位居首位。本文简要介绍了溪洛渡导流洞布置设计情况。     

博斯腾湖东泵站电气主接线及主设备选型设计

博斯腾湖泵站分东、西泵站二期建设,本文介绍了博斯腾湖东泵站工程电气一次设计中的接入系统设计、电气主接线、设备选择。     

针对不同地质目标的叠前时间偏移成像解释评价

随着计算机硬件和地震勘探成像技术的发展，叠前时间偏移正逐步替代常规的NMO加DMO加叠后时间偏移成为地震数据成像处理方法的主流。但对于不同的地质目标，叠前时间偏移的成像效果是否优于常规NMO加DMO加叠后时间偏移的成像效果呢？为此，从地震数据成像处理方法、处理流程和处理参数等方面进行了讨论，并基于某地区三维数据常规处理结果和叠前时间偏移处理结果，针对不同地质目标进行了剖析与评价。认为：叠前时间偏移成像的垂向分辨率较常规处理明显降低，但对于空间波阻抗变化明显的河流和断层，叠前时间偏移成像的空间分辨率要高于常规处理；对于小于1／4波长的叠置薄储层，叠前时间偏移成像的垂向和空间分辨率低于常规处理结果。