基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction,segmentation, classification and detection approaches

With the development of Computer-aided Diagnosis (CAD) and image scanning techniques, Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis. Therefore, WSI analysis has become the key to modern digital histopathology. Since 2004, WSI has been used widely in CAD. Since machine vision methods are usually based on semi-automatic or fully automatic computer algorithms, they are highly efficient and labor-saving. The combination of WSI and CAD technologies for segmentation, classification, and detection helps histopathologists to obtain more stable and quantitative results with minimum labor costs and improved diagnosis objectivity. This paper reviews the methods of WSI analysis based on machine learning. Firstly, the development status of WSI and CAD methods are introduced. Secondly, we discuss publicly available WSI datasets and evaluation metrics for segmentation, classification, and detection tasks. Then, the latest development of machine learning techniques in WSI segmentation, classification, and detection are reviewed. Finally, the existing methods are studied, and the application prospects of the methods in this field are forecasted.

     

Aqueous-based,high-density nanoporous carbon xerogels with high specific surface area for supercapacitors

Journal of Porous Materials - Electrode materials with high density for assembling supercapacitors with high volumetric capacitance are urgently needed. Herein, nanoporous carbon xerogels (NPCXs)...     

Homogeneous reinforcement as a strategy for the efficient preparation of high-strength,insulating and high heat-resistant PBO composite paper

Journal of Materials Science - Poly(p-phenylene benzobisoxazole) (PBO) fibre-based specialty paper has become a promising candidate for high-performance insulating materials due to the remarkable...     

Germination improves the functional properties of soybean and enhances soymilk quality

The effects of soybean variety and germination time on structural changes, antinutritional factor content, antioxidant activity of germinated soybean, and on the functional properties of soymilk were comprehensively investigated. The results showed that the antioxidant activity increased with increasing germination time. The content of antinutritional factors decreased with increasing germination time. Soybean varieties with the lowest tannin and trypsin inhibitor content were DN690 and HJ1. Lipoxygenase activity and phytic acid content showed no significant differences among soybean varieties. The content of α-helices and β-turns in soybean protein decreased with increasing germination time, while the content of β-sheets was increased. Soybean protein was progressively broken down into smaller molecular peptides during the germination process. The digestion and content of soluble protein in soymilk increased with germination. In summary, we show that germination is an effective, cheap, and green method that improves the functional properties of soybean and soymilk.