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This paper presents an assessment method to measure the lean transformation (LT) stage of an LT enterprise. Although there are many assessment tools to measure the various aspects of lean practices in enterprises, there is none to measure the stage of LT using the enterprise transformation characteristics from enterprise level. In this paper, the characteristic metrics and characteristic model of LT cycle were extracted from the basic capacity, process power and transformation results. Then, an assessment approach based on fuzzy nearness degree and TOPSIS is proposed to determine the stage of LT. Finally, an example is shown to highlight the procedure of the proposed method. This paper shows that the proposed model is very well suited as an assessment tool for enterprises in the manufacturing industry and other industries to evaluate the LT stage. [ABSTRACT FROM AUTHOR]

The shear strength of topsoil indicates the resistance of surface land to external erosive forces and represents a key variable for inferring the extent and rate of soil erosion. However, the influence of land use on topsoil shear strength is poorly understood. This study aims to examine topsoil shear strength under different land uses in the purple-soiled region of the Three Gorges Reservoir area in China and explore the related factors that control the observed variability. Direct shear tests were performed to determine the shear strength of topsoil in terms of internal friction angle (φ) and cohesion (c) under 5 typical land use systems. The results showed that the topsoil shear stress increases with increasing shear displacement from 0 to 6 mm; thereafter, it remains relatively stable over a further increase of shear displacement from 6 to 10 mm. The shear stress–shear displacement curves display a hardening strain trend. Land use exerts a strong effect on the shear strength through differentiation of soil physicochemical properties. In general, topsoil from orchard land has the highest mean values for clay fraction, φ, and c and the lowest mean values for sand fraction and water content. The topsoil in abandoned land shows the highest mean values for bulk density and silt content. The bulk density and the clay and silt content are the main direct factors controlling the difference in shear strength of the purple topsoil. Organic matter content, total porosity, and sand content represent important indirect factors that contribute to the variability in c and φ values of the studied soils.

The shear strength of topsoil indicates the resistance of surface land to external erosive forces and represents a key variable for inferring the extent and rate of soil erosion. However, the influence of land use on topsoil shear strength is poorly understood. This study aims to examine topsoil shear strength under different land uses in the purple-soiled region of the Three Gorges Reservoir area in China and explore the related factors that control the observed variability. Direct shear tests were performed to determine the shear strength of topsoil in terms of internal friction angle (φ) and cohesion (c) under 5 typical land use systems. The results showed that the topsoil shear stress increases with increasing shear displacement from 0 to 6 mm; thereafter, it remains relatively stable over a further increase of shear displacement from 6 to 10 mm. The shear stress–shear displacement curves display a hardening strain trend. Land use exerts a strong effect on the shear strength through differentiation of soil physicochemical properties. In general, topsoil from orchard land has the highest mean values for clay fraction, φ, and c and the lowest mean values for sand fraction and water content. The topsoil in abandoned land shows the highest mean values for bulk density and silt content. The bulk density and the clay and silt content are the main direct factors controlling the difference in shear strength of the purple topsoil. Organic matter content, total porosity, and sand content represent important indirect factors that contribute to the variability in c and φ values of the studied soils. [ABSTRACT FROM AUTHOR]

Background subtraction has been widely used in the detection of a moving object from a still scene. Due to the uncertainty in the classification of the pixels in the foreground and background, we propose a novel fuzzy approach for background subtraction using fuzzy histograms based on fuzzy c-means clustering and the fuzzy nearness degree, called FCFN. In this method, the temporal characteristics of the pixels are described by a fuzzy histogram using the fuzzy c-means algorithm. The segmentation threshold is adaptively calculated according to the distribution of the fuzzy nearness degree of the individual pixel. Fuzzy adaptive background maintenance is adopted in the background update framework. The performance of the FCFN is evaluated against several state-of-the-art methods in the complex dynamic scenes. The experimental results demonstrate that the proposed method doubles the improvements in performance than the classic fuzzy background modeling methods and outperforms most state-of-the-art methods.

As a measure of information shared between two fuzzy pattern vectors, the fuzzy information proximity measure (FIPM) plays an important part in fuzzy pattern recognition, fuzzy clustering analysis and fuzzy approximate reasoning. In this paper, two novel FIPMs are set up. Firstly, an axiom theory about the FIPM is given, and different expressions of the FIPM are discussed. A new FIPM is then proposed based on the axiom theory of the FIPM and the concept of fuzzy subsethood function. Two concepts based on the idea of Shannon information entropy, fuzzy joint entropy (FJE) and fuzzy conditional entropy (FCE), are proposed and the basic properties of FJE and FCE are given and proved. Finally, classical similarity measures such as dissimilarity measure (DM) and similarity measure (SM) are studied, and two new measures, fuzzy absolute information measure (FAIM) and fuzzy relative information measure (FRIM), are set up, which can be used as measures of the proximity between fuzzy sets A and B. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a multidimensional fault characteristic parameter model for rotating parts for the purpose of mechanical fault diagnosis technology. Specifically, a fuzzy-grey optimising prediction method is presented to foretell short-term faults. The method is able to set up a prediction model with as few as four data and also can effectively handle the non-linearity of prediction data. The optimising factor is determined to make the prediction data closest to the original data. Taking a rolling bearing of an oil-line pump as an example to forecast its fault characteristic parameters and comparing with GM(1,1), the experiment results show that ideal effects of precision examination have been obtained, and the method proves feasible and practical. [Copyright &y& Elsevier]