The increasingly larger scale of available data and the more restrictive concerns on their privacy are some of the challenging aspects of data mining today. In this paper, Entropy-based Consensus on Cluster Centers (EC3) is introduced for clustering in distributed systems with a consideration for confidentiality of data; i.e. it is the negotiations among local cluster centers that are used in t...

The clustering algorithm hybridization scheme has become of research interest in data partitioning applications in recent years. The present paper proposes a Hybrid Fuzzy clustering algorithm (combination of Fuzzy C-means with extension and Subtractive clustering algorithm) for data classifications applications. The fuzzy c-means (FCM) and subtractive clustering (SC) algorithm has been widely d...

dendritic cells (dcs) induce pathogen-specific t cell responses. we comprehensively studied the effects of addition of maturation stimulus, fibroblasts (fibroblast conditioned medium), pha activated t cells (t cell conditioned medium), and mixture of fibroblast & pha activated t cells (fcm-tccm) conditioned media on maturation of dcs. monocytes were cultured with gm-csf and il-4 for five da...

Information granules have been considered as the fundamental constructs of Granular Computing. As a useful unsupervised learning technique, Fuzzy C-Means (FCM) is one most frequently used methods to construct information granules. The FCM-based granulation–degranulation mechanism plays pivotal role in In this paper, enhance quality degranulation (reconstruction) process, we augment by introduci...

Fuzzy C-Means (FCM) is a common data analysis method, but the clustering effect of this algorithm easily affected by initial centers. Currently, scholars often use multiple population genetic (MPGA) to optimize centers, MPGA has insufficient global search ability and lacks self-adaptability, prone premature convergence, poor Therefore, paper proposes an adaptive FCM DMGA-FCM based on derivative...

A 3D rib cage model helps to study anatomical structures in some medical applications such as biomechanical and surgical operations. Its quality directly depends on rib cage segmentation if it is reconstructed from image data. This paper presents an optional segmentation method based on K-means clustering. It uses a hierarchical concept to control the clustering, and it organizes clustered regi...

Dendritic cells (DCs) induce pathogen-specific T cell responses. We comprehensively studied the effects of addition of maturation stimulus, fibroblasts (fibroblast conditioned medium), PHA activated T cells (T cell conditioned medium), and mixture of fibroblast & PHA activated T cells (FCM-TCCM) conditioned media on maturation of DCs. Monocytes were cultured with GM-CSF and IL-4 for five days. ...

Synthetic aperture side-scan sonar (SAS) provides an imaging modality for detecting objects on the sea floor. It is also an excellent tool for shallow water characterization where immobile, submerged threats would not be detected by conventional forward-looking sonar range-doppler techniques. SAS images provide an image of an object and its shadow, both of which can be used in the classificatio...

In the aim of providing sophisticated applications and getting benefits from the advantageous properties of agents, designing agent-based and multi-agent systems has become an important issue that received further consideration from many application domains. Towards the same goal, this work gathered three different research fields; image segmentation, fuzzy clustering and multi-agent systems (M...