含铬制革废弃物处理的研究现状和研究思路

含铬制革废弃物经过适当处理可以回收其中的能量、重金属铬和胶原蛋白,但目前不合理的处置造成了环境污染及资源浪费。本文简述了含铬制革废弃物的来源和处置现状,综合国内外最新的含铬制革废弃物处理的文献,系统总结了含铬制革废弃物处理方式的相关研究,将处置方式分为直接处理和间接处理两大类分别进行阐述,详细介绍了吸附剂、热解、焚烧这3种直接处理方式及氧化法、酸水解法、碱水解法、酶水解法这4种间接处理方式,分析了每种处置方式的原理、存在的优缺点和应用前景,简述了各种处置方式的主要作用以及优缺点对比。最后提出了含铬制革废弃物处置的研究思路,特别是开展含铬制革废弃物热解和焚烧过程中燃烧和污染物排放机理研究。     

Multi-view Laplacian twin support vector machines

Twin support vector machines are a recently proposed learning method for pattern classification. They learn two hyperplanes rather than one as in usual support vector machines and often bring performance improvements. Semi-supervised learning has attracted great attention in machine learning in the last decade. Laplacian support vector machines and Laplacian twin support vector machines have been proposed in the semi-supervised learning framework. In this paper, inspired by the recent success of multi-view learning we propose multi-view Laplacian twin support vector machines, whose dual optimization problems are quadratic programming problems. We further extend them to kernel multi-view Laplacian twin support vector machines. Experimental results demonstrate that our proposed methods are effective.     

Multi-view k-proximal plane clustering

Multi-view clustering is an active direction in machine learning and pattern recognition which aims at exploring the consensus and complementary information among multiple views. In the last few years, a number of methods based on multi-view learning have been widely investigated and achieved promising performance. Generally, classical multi-view clustering methods such as multi-view kernel k-means clustering are point-based methods. The performance of point-based methods will be fairly good when the data points are distributed around the center point. The plane-based clustering methods can handle data points that are clustered along a straight line and have never been investigated in multi-view learning. In this paper, we propose a novel multi-view k-proximal plane clustering method, which initializes cluster labels by multi-view spectralclustering and updates whole multi-view cluster hyperplanes and labels alternately until some stopping conditions are satisfied. Extensive experimental results on several benchmark datasets show that the proposed model outperforms other state-of-the-art multi-view algorithms.

     

Multi-view Opinion Mining with Deep Learning

Neural Processing Letters - With the explosive growth of social media on the Internet, people are expressing an increasing number of opinions. As for objectives like business decision making and...     

水布垭混凝土面板堆石坝安全性分析

水布垭混凝土面板堆石坝,坝高233m。在尚无200m级以上面板坝设计先例的情况下,为了论证水布垭混凝土面板堆石坝的安全稳定,对影响大坝安全因素及设计方案进行了分析。