Novel nanometer alumina-silica insulation board with ultra-low thermal conductivity

Advanced nano-porous super thermal insulation materials are widely used in spacecraft, soler-thermal shielding, heat exchangers, photocatalytic carriers due to their low thermal conductivity. In this work, adopting dry preparation technology, nano-Al₂O₃, nano-SiO₂, SiC and glass fibers as raw materials, novel nanometer alumina-silica insulation board (NAIB) were prepared. The preparation process was simple, safe, and reliable. In addition, the NAIB exhibited a high porosity (91.3–92.3%), small pore size (39.83–44.15 nm), low bulk density (0.22–0.26 g/cm³), better volumetric stability, and low thermal conductivity (0.031–0.050 W/(m·K) (200–800 °C)), respectively. The as-prepared NAIB could render them suitable for application as high-temperature thermal insulation materials.     

Effects of particle size distribution and sintering temperature on properties of alumina mold material prepared by stereolithography

Alumina mold materials prepared by stereolithography usually have considerable sintering shrinkage, and their properties related to casting have been rarely studied. In this study, alumina molds materials were prepared by stereolithography, and the effects of particle size distribution and sintering temperature on the properties of the materials were investigated. Results show that the viscosity of the slurries decreases as the fraction of fine powder increases, and the particle size distribution affects the curing behaviors slightly. Sintering shrinkage increases as the fraction of fine powder or the sintering temperature increases. Although lower sintering shrinkage can be achieved by sintering at 1350 °C or 1450 °C, the mold materials sintered at lower temperatures would continue to shrink under the service temperature of 1550 °C, and thus 1550 °C is determined as the optimal sintering temperature. As the fraction of fine powder increases, the creep resistance first increases and then decreases, and specimens prepared with 0.1 fraction of fine powder exhibit the best creep resistance with the droop distance of 4.44 ± 0.45 mm. Specimens prepared with 0.1 fraction of fine powder and sintered at 1550 °C exhibit linear shrinkage of 6.36% along the X/Y direction and 11.39% along the Z direction, and have a flexural strength of 78.15 ± 3.50 MPa and porosity of 30.12 ± 0.08%. The resulting material possesses relatively low sintering shrinkage, proper mechanical strength, porosity and high-temperature properties that meet the requirements for casting purposes.     

Extrinsic parameter's adjustment and potential implications in Plasmodium falciparum malaria diagnosis

Malaria is a major public health concern, affecting over 3.2 billion people in 91 countries. The advent of digital microscopy and Machine learning with the aim of automating Plasmodium falciparum diagnosis extensively depends on the extracted image features. The color of the cells, plasma, and stained artifacts influence the topological, geometrical, and statistical parameters being used to extract image features. During microscopic image acquisition, custom adjustments to the condenser and color temperature controls often have an influence on the extracted statistical features. But, our human visual system sub-consciously adjusts the color and retains the originality in a different lighting environment. Despite the use of appropriate image preprocessing, findings from the literature indicate that statistical feature variations exist, allowing the risk of P. falciparum misinterpretation. In order to eliminate this pervasive variation, the current work focuses on preprocessing the extracted statistical features rather than the prepossessing of the source image. It begins with the augmentation of series images for a microscopic field by inducing illumination variations during the microscopic image acquisition stage. A set of such image series is analyzed using a Nonlinear Regression Model to generalize the relationship between microscopic images acquired with variable ambient brightness and a specific feature. The projection point of the centroid feature onto the brightness parameter is identified in the model and it is denoted as the optimum brightness factor (OBF). Using the model, the feature correction factor (CF) is calculated from the rate of change of feature values over the interval OBF, and the brightness of the test image is processed. The present work has investigated OBF for selected image textural features, namely Contrast, Homogeneity, Entropy, Energy, and Correlation individually from its co-occurrence matrices. For performance analysis, the best state-of-the-art method uses selected texture as a subset feature to evaluate the effectiveness of P. falciparum malaria classification. Then, the impact of proposed feature processing is evaluated on 274 blood smear images with and without Feature Correction (FC). As a result, the “p” value is less than .05, which leads to the result that it is highly significant and the classification accuracy and F-score of P. falciparum malaria are increased.     

Effect of laver powder on textual,rheological properties and water distribution of squid (Dosidicus gigas) surimi gel

In order to ameliorate the gel quality of Dosidicus gigas surimi, the effects of laver powder on gel properties, rheological properties, and water-holding capacity (WHC) were investigated. Results indicated that the addition of laver powder could significantly increase the hardness, chewiness, and breaking force of surimi gels. However, the texture indexes and gel strength began to decline when additional amount exceeded 0.6%. Rheological results demonstrated that the addition of laver powder increased the storage modulus (G′) and viscosity of surimi, prolonged protein denaturation temperature in surimi gels. Moreover, the WHC of surimi gel was improved with the increase of laver powder. Further analyses in low-field nuclear magnetic resonance revealed that laver powder could shorten the transverse relaxation time, enhanced the combination with water, and altered the distribution of different water categories. The proportion of bound water and immobilized water reached its maximum and minimum at 0.6% of laver powder, respectively. Correlation analyses showed that WHC of surimi gel was negatively correlated well with the proportion of loose-bound water, but positively correlated with the strong-bound water and free water. In conclusion, the results supported that 0.6% was the optimal additional amount of laver powder for the squid-based surimi production based on the current ingredients of surimi products.     

基于光流法的固体内部声传播方向测量

目前采用光弹设备测量超声传播方向多为人眼主观观测,其误差较大,难以实现精确的定量测量。将Farneback光流法应用于光弹图像的处理,并根据帧与帧之间的光流图来计算光弹图像中的超声传播方向,可以捕捉图像中的动态声场。在实验中对不同传播方向的超声进行了测量,其绝对偏差度数最大值为2.85°,测量结果较为准确。因此,Farneback光流法可用于光弹图像中声波传播方向的判断,且具有快速、准确和直观等特点。     

基于视觉传达的后继帧视频图像目标跟踪仿真

现阶段所采用的跟踪方法对后继帧视频图像目标跟踪存在跟踪效果不理想、跟踪效率较低等问题。提出基于视觉传达的后继帧视频图像目标跟踪方法。利用图像差分方法获取视频图像运动目标可能出现的区域,并对这个区域视频图像目标进行运动估计,采用形态学方法来降低聚类区域的数量,得到后继帧视频图像目标区域;采用均值漂移法估计后继帧视图像核概率密度,对后继帧视频图像进行分割处理,找出后继帧视频图像目标区域最显著的特征,通过迭代运算找到目标位置,实现目标跟踪。实验结果表明,所提算法具有较好的后继帧视频图像跟踪效果、并且跟踪效率较高,具有一定的应用价值。     

一种基于全变分技术和Lp伪范数的椒盐噪声去除方法

针对传统各向同性全变分（Isotropy total variation，ITV）去噪算法容易导致图像边缘模糊、不易保持图像细节信息等问题，提出一种基于L _p 伪范数和各向同性全变分的图像去噪方法。该方法将L _p 伪范数代替ITV模型中的L ₁范数，利用交替方向乘子算法（Alternating direction method of multipliers, ADMM）将能量泛函拆解成若干个子问题，并将差分算子视为卷积算子；然后引入卷积定理和快速傅里叶变换(Fast Fourier transform, FFT)提高算法运算效率；最后通过Matlab进行仿真实验，运用图像质量的客观和主观评价方法进行评价分析。结果表明，本文方法能够较好地保留图像的边缘特性，有效提升去噪效果。     

改进RetinaFace的自然场景口罩佩戴检测算法

新型冠状病毒可以通过空气中的飞沫、气溶胶等载体进行传播，在公共场所下正确佩戴口罩可以有效地防止病毒的传播。提出了一种自然场景下人脸口罩佩戴检测方法，对RetinaFace算法进行了改进，增加了人脸口罩佩戴检测任务，优化了损失函数。在特征金字塔网络中引入了一种改进的自注意力机制，增强了特征图的表达能力。建立了包含3 000张图片的数据集，并进行手工标注，用于网络训练。实验结果表明该算法可以有效进行口罩佩戴检测，在自然场景视频中也取得了不错的检测效果。     

基于条件信息卷积生成对抗网络的图像识别

传统的图像识别方法需要大量有标签样本进行训练，且模型训练难以达到稳定。针对这些问题，结合条件生成网络和信息最大化生成网络的结构优势建立了条件信息卷积生成网络（C-Info-DCGAN）。模型增加图像的类别信息和潜在信息作为输入数据，然后利用Q网络去更好地发挥类别信息和潜在信息对训练的引导作用，并且利用深度卷积网络来加强对图像特征的提取能力。实验结果表明，该方法能够加快模型训练收敛速度，并有效提高图像识别的准确率。