In articular cartilage, chondrocytes are surrounded by a narrow region called the pericellular matrix (PCM), which is biochemically, structurally, and mechanically distinct from the bulk extracellular matrix (ECM). Although multiple techniques have been used to measure the mechanical properties of the PCM using isolated chondrons (the PCM with enclosed cells), few studies have measured the biom...

In this paper, we examine the performance of fuzzy clustering algorithms as the major technique in pattern recognition. Both possibilistic and probabilistic approaches are explored. While the Possibilistic C-Means (PCM) has been shown to be advantageous over Fuzzy C-Means (FCM) in noisy environments, it has been reported that the PCM has an undesirable tendency to produce coincident clusters. R...

The fuzzy c-means (FCM) has been a well-known algorithm in machine learning/data mining area as a clustering algorithm. It can also be used for image segmentation, but the algorithm is not robust to noise. The possibilistic c-means (PCM) algorithm was proposed to overcome such a problem. However, the performance of PCM is too sensitive to the initialization of cluster centers, and often deterio...

This paper initially describes the relational counterpart of possibilistic c-means (PCM) algorithm, called relational PCM (or RPCM). RPCM is then improved to better handle arbitrary dissimilarity data. First, a re-scaling of the PCM membership function is proposed in order to obtain zero membership values when the distance to prototype equals the maximum value allowed in bounded dissimilarity m...

The 'kernel method' has attracted great attention with the development of support vector machine (SVM) and has been studied in a general way. In this paper, this 'method' is extended to the well-known fuzzy c-means (FCM) and possibilistic c-means (PCM) algorithms. It is realized by substitution of a kernel-induced distance metric for the original Euclidean distance, and the corresponding algori...

A new methodology for manipulating transient-amorphous states of phase-change memory (PCM) materials is reported as a viable means to boost the speed, yet reduce the power consumption of PC memories, and is applicable to new forms of PCM-based neuromorphic devices. Controlling multiple-pulse interactions with PC materials may provide an opportunity toward developing a new paradigm for ultra-fas...

It is found that sub-pixel classifiers for classification of multi-spectral remote sensing data yield a higher accuracy. With this objective, a study has been carried out, where fuzzy set theory based sub-pixel classifiers have been compared with statistical based sub-pixel classifier for classification of multi-spectral remote sensing data.Although, a number of Fuzzy set theory based classifie...

The analysis and processing of large data are a challenge for researchers. Several approaches have been used to model these complex data, and they are based on some mathematical theories: fuzzy, probabilistic, possibilistic, and evidence theories. In this work, we propose a new unsupervised classification approach that combines the fuzzy and possibilistic theories; our purpose is to overcome th...

A key concept of model-driven software development is the transformation of models into other models or source code. ProtoCom is such a transformation that generates a performance prototype from a Palladio Component Model (PCM) instance by means of a model-to-text transformation. The actual supported platform, on which the PCM instance is mapped, is Java SE. Even though related work suggests th...