Search results for "Clusterin"

Fuzzy modeling of solar irradiance on inclined surfaces

2003

A model of solar irradiance on arbitrarily oriented inclined surfaces is proposed, based on fuzzy logic procedures. The behavior of the proposed model is similar to that of other models of increased performance such as the models of Perez or Gueymard, though it requires only a very limited number of classes and adjustable parameters. The use of fuzzy clustering optimizes the number and definition of the sky categories. The model considers overlapping clusters and allows an improved description of the sky situations close to the transition zone between contiguous categories.

Gravitational weighted fuzzy c-means with application on multispectral image segmentation

2014

This paper presents a novel clustering approach based on the classic Fuzzy c-means algorithm. The approach is inspired from the concept of interaction between objects in physics. Each data point is regarded as a particle. A specific weight is associated with each data particle depending on its interaction with other particles. This interaction is induced by attraction forces between pairs of particles and the escape velocity from other particles. Classification experiments using two data sets from UCI repository demonstrate the outperformance of the proposed approach over other clustering algorithms. In addition, results demonstrate the effectiveness of the proposed scheme for segmentation …

Semi-automated and interactive segmentation of contrast-enhancing masses on breast DCE-MRI using spatial fuzzy clustering

2022

Abstract Multiparametric Magnetic Resonance Imaging (MRI) is the most sensitive imaging modality for breast cancer detection and is increasingly playing a key role in lesion characterization. In this context, accurate and reliable quantification of the shape and extent of breast cancer is crucial in clinical research environments. Since conventional lesion delineation procedures are still mostly manual, automated segmentation approaches can improve this time-consuming and operator-dependent task by annotating the regions of interest in a reproducible manner. In this work, a semi-automated and interactive approach based on the spatial Fuzzy C-Means (sFCM) algorithm is proposed, used to segme…

Accurate detection and characterization of corner points using circular statistics and fuzzy clustering

1998

Accurate detection and characterization of corner points in grey level images is considered as a pattern recognition problem. The method considers circular statistic tests to detect 2D features. A fuzzy clustering algorithm is applied to the edge orientations near the prospective corners to detect and classify them. The method is based on formulating hypotheses about the distribution of these orientations around an edge, corner or other 2-D feature. The method may provide accurate estimates of the direction of the edges that converge in a corner, along with their confidence intervals. Experimental results show the method to be robust enough against noise and contrast changes. Fuzzy membersh…

A Novel Clustering Algorithm based on a Non-parametric "Anti-Bayesian" Paradigm

2015

The problem of clustering, or unsupervised classification, has been solved by a myriad of techniques, all of which depend, either directly or implicitly, on the Bayesian principle of optimal classification. To be more specific, within a Bayesian paradigm, if one is to compare the testing sample with only a single point in the feature space from each class, the optimal Bayesian strategy would be to achieve this based on the distance from the corresponding means or central points in the respective distributions. When this principle is applied in clustering, one would assign an unassigned sample into the cluster whose mean is the closest, and this can be done in either a bottom-up or a top-dow…

Weighted Fuzzy Clustering for Online Detection of Application DDoS Attacks in Encrypted Network Traffic

2016

Distributed denial-of-service (DDoS) attacks are one of the most serious threats to today’s high-speed networks. These attacks can quickly incapacitate a targeted business, costing victims millions of dollars in lost revenue and productivity. In this paper, we present a novel method which allows us to timely detect application-layer DDoS attacks that utilize encrypted protocols by applying an anomaly-based approach to statistics extracted from network packets. The method involves construction of a model of normal user behavior with the help of weighted fuzzy clustering. The construction algorithm is self-adaptive and allows one to update the model every time when a new portion of network tr…

Comparison of Internal Clustering Validation Indices for Prototype-Based Clustering

2017

Clustering is an unsupervised machine learning and pattern recognition method. In general, in addition to revealing hidden groups of similar observations and clusters, their number needs to be determined. Internal clustering validation indices estimate this number without any external information. The purpose of this article is to evaluate, empirically, characteristics of a representative set of internal clustering validation indices with many datasets. The prototype-based clustering framework includes multiple, classical and robust, statistical estimates of cluster location so that the overall setting of the paper is novel. General observations on the quality of validation indices and on t…

Clustering techniques for personal photo album management

2009

In this work we propose a novel approach for the automatic representation of pictures achieving at more effective organization of personal photo albums. Images are analyzed and described in multiple representation spaces, namely, faces, background and time of capture. Faces are automatically detected, rectified and represented projecting the face itself in a common low-dimensional eigenspace. Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter bank. Faces, time and background information of each image in the collection is automatically organized using a mean-shift clustering technique. Given the particular domain of personal photo libraries, wh…

2013

Clusterin, also known as apolipoprotein J, is expressed from a variety of tissues and implicated in pathological disorders such as neurodegenerative diseases, ischemia and cancer. In contrast to secretory clusterin (sCLU), which acts as an extracellular chaperone, the synthesis, subcellular localization and function(s) of intracellular CLU isoforms is currently a matter of intense discussion. By investigating human CLU mRNAs we here unravel mechanisms leading to the synthesis of distinct CLU protein isoforms and analyze their subcellular localization and their impact on apoptosis and on NF-κB-activity. Quantitative PCR-analyses revealed the expression of four different stress-inducible CLU …

GIS-data related route optimization, hierarchical clustering, location optimization, and kernel density methods are useful for promoting distributed …

2019

Currently, geographic information system (GIS) models are popular for studying location-allocation-related questions concerning bioenergy plants. The aim of this study was to develop a model to investigate optimal locations for two different types of bioenergy plants, for farm and centralized biogas plants, and for wood terminals in rural areas based on minimizing transportation distances. The optimal locations of biogas plants were determined using location optimization tools in R software, and the optimal locations of wood terminals were determined using kernel density tools in ArcGIS. The present case study showed that the utilized GIS tools are useful for bioenergy-related decision-maki…