三维石墨烯-碳纳米管/水泥净浆的压敏性能

为了探索三维石墨烯-碳纳米管(G-CNTs)/水泥净浆的压敏性能,采用四电极法研究了荷载作用下GCNTs/水泥净浆的电阻率变化,并分析不同G-CNTs掺量、加载幅度、加载速度以及恒定荷载对电阻率变化的影响。研究表明:随着G-CNTs掺量的增加,电阻率呈先减小后稳定的变化趋势,在G-CNTs掺量由0.2wt%增加至1.6wt%时,电阻率下降51.8%;电阻率与温度呈负相关;G-CNTs掺量高于0.8wt%时可以显著提高水泥净浆的压敏性能,且电阻率变化率与应力应变有明显的对应关系,1.2wt%G-CNTs掺量下试件的应力灵敏系数和应变灵敏系数分别为2.3%/MPa和291;G-CNTs/水泥净浆电阻率变化率幅值随着加载幅度增大而相应增加,其电阻率变化率曲线在不同加载速度以及恒定荷载作用下均与应力-应变曲线一一对应,具有良好的压敏特性。     

Reduction of waste biosolids by RAS-ozonation: Model validation and sensitivity analysis for biosolids reduction and nitrification

Biosolids reduction model by return activated sludge ozonation was validated by simulating nitrification data compiled from our pilot-scale and the literature studies. Then, a global sensitivity analysis (GSA) was performed to identify influential and non-influential parameters for biosolids reduction efficiency, change in specific nitrification activity (SNA), and alteration to expected nitrification stability. In general, the model outputs were sensitive to operational and ozone reaction parameters, but not to biochemical parameters. For operational parameters, mainly temperature and initial solids retention time (SRT) influenced all model outputs. For biosolids reduction, increase in the degradability of the influent COD decreased the reduction efficiency. For SNA, the changes were highly dependent on the influent TKN/COD ratio. Our findings also imply that the stability of the nitrification process in ozonated systems should be enhanced at constant MLVSS for warm temperatures, but could be reduced at temperatures below 12 °C and aerated SRTs below 10 days.     

Modelling of chromatic contrast for retrieval of wallpaper images

Colour remains one of the key factors in presenting an object and, consequently, has been widely applied in retrieval of images based on their visual contents. However, a colour appearance changes with the change of viewing surroundings, the phenomenon that has not been paid attention yet while performing colour‐based image retrieval. To comprehend this effect, in this article, a chromatic contrast model, CAMcc, is developed for the application of retrieval of colour intensive images, cementing the gap that most of existing colour models lack to fill by taking simultaneous colour contrast into account. Subsequently, the model is applied to the retrieval task on a collection of museum wallpapers of colour‐rich images. In comparison with current popular colour models including CIECAM02, HSI and RGB, with respect to both foreground and background colours, CAMcc appears to outperform the others with retrieved results being closer to query images. In addition, CAMcc focuses more on foreground colours, especially by maintaining the balance between both foreground and background colours, while the rest of existing models take on dominant colours that are perceived the most, usually background tones. Significantly, the contribution of the investigation lies in not only the improvement of the accuracy of colour‐based image retrieval but also the development of colour contrast model that warrants an important place in colour and computer vision theory, leading to deciphering the insight of this age‐old topic of chromatic contrast in colour science. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 361–373, 2015     

Sensitivity analysis of Johnson-Cook material parameters on adiabatic shear in different directions

ABSTRACT

This study investigates the effects of strain, strain rates, and forming directions (RD-rolling direction, TD-transverse direction, and ND-normal direction) on adiabatic shear, via dynamic impact compression tests using the Split Hopkinson Pressure Bar (SHPB) apparatus. A modified Johnson-Cook (J-C) constitutive model is proposed, which used to analyse the influence of the constitutive parameters on the sensitivity of adiabatic shear, employing a finite element software. The different sensitivities of adiabatic shear under different directions are explained by combining microscopic analysis and results from mechanical responses. The results show that the sensitivity of adiabatic shear can be related to the time of stress collapse in the following trend: ND?>?TD?>?RD; the sensitivities of these constitutive parameters on adiabatic shear are calculated and compared.     

Y4.67Si3O13-based phosphors: Structure,morphology and upconversion luminescence for optical thermometry

How to improve the sensitivity of the temperature-sensing luminescent materials is one of the most important objects currently. In this work, to obtain high sensitivity and learn the corresponding mechanism, the rare earth (RE) ions doped Y_4.67Si₃O₁₃ (YS) phosphors were developed by solid-state reaction. The phase purity, structure, morphology and luminescence characteristics were evaluated by XRD, TEM, emission spectra, etc. The change of the optical bandgaps between the host and RE-doped phosphors was found, agreeing with the calculation results based on density-functional theory. The temperature-dependence of the upconversion (UC) luminescence revealed that a linear relationship exists between the fluorescence intensity ratio of Ho³⁺ and temperature. The theoretical resolution was evaluated. High absolute (0.083 K⁻¹) and relative (3.53% K⁻¹ at 293 K) sensitivities have been gained in the YS:1%Ho³⁺, 10%Yb³⁺. The effect of the Yb³⁺ doping concentration and pump power on the sensitivities was discussed. The pump-power–dependence of the UC luminescence indicated the main mechanism for high sensitivities in the YS:1%Ho³⁺, 10%Yb³⁺. Moreover, the decay-lifetime based temperature sensing was also evaluated. The above results imply that the present phosphors could be promising candidates for temperature sensors, and the proposed strategies are instructive in exploring other new temperature sensing luminescent materials.     

Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction is a challenging task due to the complicated nature of the retinal vessel structure, which also needs strong skill set and training. In this paper, a supervised technique for blood vessel extraction in retinal images using Modified Adaboost Extreme Learning Machine (MAD-ELM) is proposed. Firstly, the fundus image preprocessing is done for contrast enhancement and in-homogeneity correction. Then, a set of core features is extracted, and the best features are selected using “minimal Redundancy-maximum Relevance (mRmR).” Later, using MAD-ELM method vessels and non vessels are classified. DRIVE and DR-HAGIS datasets are used for the evaluation of the proposed method. The algorithm’s performance is assessed based on accuracy, sensitivity and specificity. The proposed technique attains accuracy of 0.9619 on the DRIVE database and 0.9519 on DR-HAGIS database, which contains pathological images. Our results show that, in addition to healthy retinal images, the proposed method performs well in extracting blood vessels from pathological images and is therefore comparable with state of the art methods.     

Impact sensitivities of energetic materials: Exploring the limitations of a model based only on structural formulas

Using a comprehensive set of drop weight impact test data (h₅₀) newly compiled from literature for 308 materials, a recent approach to predict impact sensitivities of nitro compounds is generalized to most explosive substances of interest. Compared to previous ones, this procedure is more thoroughly validated and exhibits a good predictive value. Furthermore, it yields new insight into the physical mechanisms involved, explaining for instance the unexpected desensitization of some oxygen-deficient triazoles upon nitration.     

Compensation paradox: the influence of monetary rewards on user behaviour

Many e-commerce companies collect users’ personal data for marketing purposes despite privacy concerns. Information-collecting companies often offer a monetary reward to users to alleviate privacy concerns and ease the collection of personal information. This study focused on the negative effects of monetary rewards on both information privacy concerns (IPC) and information disclosure. A survey approach was used to collect data and 370 final responses were analysed using a two-way analysis of variance and a binomial logistic regression model. The results show that monetary rewards increase IPC when an information-collecting company requires sensitive information. Additional results indicate that building trust is a more effective way of collecting personal data. This study identifies how organisations can best execute information-collection activities and contributes additional insights for academia and practitioners.     

Bearing Failure Optimization of Composite Double-Lap Bolted Joints Based on a Three-Step Strategy Marked By Feasible Region Reduction and Model Decoupling

To minimize the mass and increase the bearing failure load of composite doublelap bolted joints, a three-step optimization strategy including feasible region reduction, optimization model decoupling and optimization was presented. In feasible region reduction, the dimensions of the feasible design region were reduced by selecting dominant design variables from numerous multilevel parameters by sensitivity analyses, and the feasible regions of variables were reduced by influence mechanism analyses. In model decoupling, the optimization model with a large number of variables was divided into various sub-models with fewer variables by variance analysis. In the third step, the optimization sub-models were solved one by one using a genetic algorithm, and the modified characteristic curve method was adopted as the failure prediction method. Based on the proposed optimization method, optimization of a double-lap single-bolt joint was performed using the ANSYS^® code. The results show that the bearing failure load increased by 13.5% and that the mass decreased by 8.7% compared with those of the initial design of the joint, which validated the effectiveness of the three-step optimization strategy.     

具有光照鲁棒的图像匹配方法

针对现有的基于局部特征的图像匹配算法对光照变化敏感、匹配正确率低等问题，提出一种具有光照鲁棒性的图像匹配算法。首先使用实时对比保留去色（RTCP）算法灰度化图像，然后利用对比拉伸函数模拟不同光照变换对图像的影响从而提取抗光照变换特征点，最后采用局部强度顺序模式建立特征点描述符，根据待匹配图像局部特征点描述符的欧氏距离判断是否为成对匹配点。在公开数据集上，所提算法与尺度不变特征变换（SIFT）算法、加速鲁棒特征（SURF）算法、"风"（KAZE）算法和ORB算法在匹配速度和匹配正确率上进行了对比实验。实验结果表明：随着图像亮度差异的增加，SIFT算法、SURF算法、"风"（KAZE）算法和ORB算法匹配正确率下降迅速，所提算法下降缓慢并且正确率均高于80%；所提算法特征点检测较慢和描述符维数较高，平均耗时为23.47 s，匹配速度不及另外四种算法，但匹配质量却远超过它们。对实时性要求不高的系统中，所提算法可以克服光照变化对图像匹配造成的影响。