Rank determination issue is one of the most significant issues in non-negative matrix factorization (NMF) research. However, rank determination problem has not received so much emphasis as sparseness regularization pr...Rank determination issue is one of the most significant issues in non-negative matrix factorization (NMF) research. However, rank determination problem has not received so much emphasis as sparseness regularization problem. Usually, the rank of base matrix needs to be assumed. In this paper, we propose an unsupervised multi-level non-negative matrix factorization model to extract the hidden data structure and seek the rank of base matrix. From machine learning point of view, the learning result depends on its prior knowledge. In our unsupervised multi-level model, we construct a three-level data structure for non-negative matrix factorization algorithm. Such a construction could apply more prior knowledge to the algorithm and obtain a better approximation of real data structure. The final bases selection is achieved through L2-norm optimization. We implement our experiment via binary datasets. The results demonstrate that our approach is able to retrieve the hidden structure of data, thus determine the correct rank of base matrix.展开更多
AIM： To explore a feasible method on the establishment of an animal model of conjunctivochalasis （CCH）. METHODS： Twelve clean-grade New Zealand white rabbits were divided into four groups （n=3/group）： the contr...AIM： To explore a feasible method on the establishment of an animal model of conjunctivochalasis （CCH）. METHODS： Twelve clean-grade New Zealand white rabbits were divided into four groups （n=3/group）： the control group （one received no interventions, and the others underwent subconjunctival injection of sterile water）, the matrix metalloproteinases （MMPs） group （administered subconjunctival injection of MMP-3）, the aging group （administered subcutaneous injection of D-galactose）, the tumor necrosis factor-α （TNF-α） solution group （administered eye drops of TNF-α）. Anterior segment photography, conjunctival tissue light microscopy and transmission electron microscopy （TEM） were performed after 12wk. RESULTS： Among all groups, the MMPs group had the following changes： the looser connection between the inferior bulbar conjunctiva and sclera; the more disordered collagen fibers （Trichrome staining） and the broken elastic fibers （Aldehyde-fuchsin staining）; the focal necrosis of fibroblasts （TEM）. CONCLUSION： Administration of MMPs may be a feasible method for the establishment of an animal model of CCH.展开更多
The germinal matrix being an accumulation of immature blood vessels in the premature infant brain is known to be the main cause of the intracranial hemorrhage. To investigate the injuring mechanism to the blood vessel...The germinal matrix being an accumulation of immature blood vessels in the premature infant brain is known to be the main cause of the intracranial hemorrhage. To investigate the injuring mechanism to the blood vessels of the germinal matrix, a modeling scenario that consists of three basic steps is proposed. First, the cerebral blood flow that depends on autoregulation, CO2 reactivity, and variations of intracranial pressure is modeled. Second, the chaotic blood vessel network of the germinal matrix is generated, and blood pressures in the vessels of this network are computed dependent on the outcome of the first step. In the third step, the pressures computed on the second step are used in finite element simulations of separate blood vessels of the germinal matrix to detect critical values for vessels impairment.展开更多
随着互联网和面向服务技术的发展,一种新型的Web应用——Mashup服务,开始在互联网上流行并快速增长.如何在众多Mashup服务中找到高质量的服务,已经成为一个大家关注的热点问题.寻找功能相似的服务并进行聚类,能有效提升服务发现的精度...随着互联网和面向服务技术的发展,一种新型的Web应用——Mashup服务,开始在互联网上流行并快速增长.如何在众多Mashup服务中找到高质量的服务,已经成为一个大家关注的热点问题.寻找功能相似的服务并进行聚类,能有效提升服务发现的精度与效率.目前国内外主流方法为挖掘Mashup服务中隐含的功能信息,进一步采用特定聚类算法如K-means等进行聚类.然而Mashup服务文档通常为短文本,基于传统的挖掘算法如LDA无法有效处理短文本,导致聚类效果并不理想.针对这一问题,提出一种基于非负矩阵分解的TWE-NMF(nonnegative matrix factorization combining tags and word embedding)模型对Mashup服务进行主题建模.所提方法首先对Mashup服务规范化处理,其次采用一种基于改进的Gibbs采样的狄利克雷过程混合模型,自动估算主题的数量,随后将词嵌入和服务标签等信息与非负矩阵分解相结合,求解Mashup服务主题特征,并通过谱聚类算法将服务聚类.最后,对所提方法的性能进行了综合评价,实验结果表明,与现有的服务聚类方法相比,所提方法在准确率、召回率、F-measure、纯度和熵等评价指标方面都有显著提高.展开更多
文摘Rank determination issue is one of the most significant issues in non-negative matrix factorization (NMF) research. However, rank determination problem has not received so much emphasis as sparseness regularization problem. Usually, the rank of base matrix needs to be assumed. In this paper, we propose an unsupervised multi-level non-negative matrix factorization model to extract the hidden data structure and seek the rank of base matrix. From machine learning point of view, the learning result depends on its prior knowledge. In our unsupervised multi-level model, we construct a three-level data structure for non-negative matrix factorization algorithm. Such a construction could apply more prior knowledge to the algorithm and obtain a better approximation of real data structure. The final bases selection is achieved through L2-norm optimization. We implement our experiment via binary datasets. The results demonstrate that our approach is able to retrieve the hidden structure of data, thus determine the correct rank of base matrix.
基金Supported by the Key Medical Discipline Project of Shanghai Municipal Health Bureau-Ophthalmology(No.ZK2015A20)the Health System Independent Innovation Science Foundation of Shanghai Putuo District(No.2015PTKW001)Plateau Science,Integrated Traditional Chinese and Western Medicine,Shanghai University of Traditional Chinese Medicine
文摘AIM： To explore a feasible method on the establishment of an animal model of conjunctivochalasis （CCH）. METHODS： Twelve clean-grade New Zealand white rabbits were divided into four groups （n=3/group）： the control group （one received no interventions, and the others underwent subconjunctival injection of sterile water）, the matrix metalloproteinases （MMPs） group （administered subconjunctival injection of MMP-3）, the aging group （administered subcutaneous injection of D-galactose）, the tumor necrosis factor-α （TNF-α） solution group （administered eye drops of TNF-α）. Anterior segment photography, conjunctival tissue light microscopy and transmission electron microscopy （TEM） were performed after 12wk. RESULTS： Among all groups, the MMPs group had the following changes： the looser connection between the inferior bulbar conjunctiva and sclera; the more disordered collagen fibers （Trichrome staining） and the broken elastic fibers （Aldehyde-fuchsin staining）; the focal necrosis of fibroblasts （TEM）. CONCLUSION： Administration of MMPs may be a feasible method for the establishment of an animal model of CCH.
文摘The germinal matrix being an accumulation of immature blood vessels in the premature infant brain is known to be the main cause of the intracranial hemorrhage. To investigate the injuring mechanism to the blood vessels of the germinal matrix, a modeling scenario that consists of three basic steps is proposed. First, the cerebral blood flow that depends on autoregulation, CO2 reactivity, and variations of intracranial pressure is modeled. Second, the chaotic blood vessel network of the germinal matrix is generated, and blood pressures in the vessels of this network are computed dependent on the outcome of the first step. In the third step, the pressures computed on the second step are used in finite element simulations of separate blood vessels of the germinal matrix to detect critical values for vessels impairment.
文摘随着互联网和面向服务技术的发展,一种新型的Web应用——Mashup服务,开始在互联网上流行并快速增长.如何在众多Mashup服务中找到高质量的服务,已经成为一个大家关注的热点问题.寻找功能相似的服务并进行聚类,能有效提升服务发现的精度与效率.目前国内外主流方法为挖掘Mashup服务中隐含的功能信息,进一步采用特定聚类算法如K-means等进行聚类.然而Mashup服务文档通常为短文本,基于传统的挖掘算法如LDA无法有效处理短文本,导致聚类效果并不理想.针对这一问题,提出一种基于非负矩阵分解的TWE-NMF(nonnegative matrix factorization combining tags and word embedding)模型对Mashup服务进行主题建模.所提方法首先对Mashup服务规范化处理,其次采用一种基于改进的Gibbs采样的狄利克雷过程混合模型,自动估算主题的数量,随后将词嵌入和服务标签等信息与非负矩阵分解相结合,求解Mashup服务主题特征,并通过谱聚类算法将服务聚类.最后,对所提方法的性能进行了综合评价,实验结果表明,与现有的服务聚类方法相比,所提方法在准确率、召回率、F-measure、纯度和熵等评价指标方面都有显著提高.
