Search results for "Fuzzy cluster"
showing 10 items of 32 documents
Fuzzy quantification of common and rare species in ecological communities (FuzzyQ)
2021
International audience; Most species in ecological communities are rare, whereas only a few are common. This distributional paradox has intrigued ecologists for decades but the interpretation of species abundance distributions remains elusive.We present Fuzzy Quantification of Common and Rare Species in Ecological Communities (FuzzyQ) as an R package. FuzzyQ shifts the focus from the prevailing species-categorization approach to develop a quantitative framework that seeks to place each species along a rarity-commonness gradient. Given a community surveyed over a number of sites, quadrats, or any other convenient sampling unit, FuzzyQ uses a fuzzy clustering algorithm that estimates a probab…
Longitudinal Study on Sustained Attention to Response Task (SART): Clustering Approach for Mobility and Cognitive Decline
2022
The Sustained Attention to Response Task (SART) is a computer-based go/no-go task to measure neurocognitive function in older adults. However, simplified average features of this complex dataset lead to loss of primary information and fail to express associations between test performance and clinically meaningful outcomes. Here, we combine a novel method to visualise individual trial (raw) information obtained from the SART test in a large population-based study of ageing in Ireland and an automatic clustering technique. We employed a thresholding method, based on the individual trial number of mistakes, to identify poorer SART performances and a fuzzy clusters algorithm to partition the da…
A Comparative Study on Fuzzy-Clustering-Based Lip Region Segmentation Methods
2011
As the first step of many lip-reading or visual speaker authentication systems, lip region segmentation is of vital importance. And fuzzy clustering based methods have been widely used in lip segmentation. In this paper, four fuzzy clustering based lip segmentation methods have been elaborated with their underlying rationale. Experiments have been carried out evaluate their performance comparatively. From the experimental results, SFCM has the best efficiency and FCMST has the best segmentation accuracy.
Sequential Lip Region Segmentation Using Fuzzy Clustering with Spatial and Temporal Information
2012
For many visual speech recognition and visual speaker authentication systems, lip region extraction is of vital important. In order to segment the lip region accurately and robustly from a lip sequence, a new fuzzy-clustering based algorithm is proposed. In the proposed method, a new dissimilarity measure is introduced to take all the color, spatial and temporal information into consideration. An iterative optimization method is employed to derive the optimal lip region membership map and the final segmentation result. From the experimental results, it is observed that the proposed algorithm can provide superior results compared with other traditional methods.
SMART: Unique splitting-while-merging framework for gene clustering
2014
© 2014 Fa et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Successful clustering algorithms are highly dependent on parameter settings. The clustering performance degrades significantly unless parameters are properly set, and yet, it is difficult to set these parameters a priori. To address this issue, in this paper, we propose a unique splitting-while-merging clustering framework, named "splitting merging awareness tactics" (SMART), which does not require any a priori knowledge of either the number …
Data Analysis and Bioinformatics
2007
Data analysis methods and techniques are revisited in the case of biological data sets. Particular emphasis is given to clustering and mining issues. Clustering is still a subject of active research in several fields such as statistics, pattern recognition, and machine learning. Data mining adds to clustering the complications of very large data-sets with many attributes of different types. And this is a typical situation in biology. Some cases studies are also described.
Distance Functions, Clustering Algorithms and Microarray Data Analysis
2010
Distance functions are a fundamental ingredient of classification and clustering procedures, and this holds true also in the particular case of microarray data. In the general data mining and classification literature, functions such as Euclidean distance or Pearson correlation have gained their status of de facto standards thanks to a considerable amount of experimental validation. For microarray data, the issue of which distance function works best has been investigated, but no final conclusion has been reached. The aim of this extended abstract is to shed further light on that issue. Indeed, we present an experimental study, involving several distances, assessing (a) their intrinsic sepa…
Structural clustering of millions of molecular graphs
2014
We propose an algorithm for clustering very large molecular graph databases according to scaffolds (i.e., large structural overlaps) that are common between cluster members. Our approach first partitions the original dataset into several smaller datasets using a greedy clustering approach named APreClus based on dynamic seed clustering. APreClus is an online and instance incremental clustering algorithm delaying the final cluster assignment of an instance until one of the so-called pending clusters the instance belongs to has reached significant size and is converted to a fixed cluster. Once a cluster is fixed, APreClus recalculates the cluster centers, which are used as representatives for…
Compaction of Open-Graded HMAs Evaluated by a Fuzzy Clustering Technique
2015
The aim of this paper is the proposal of an expeditious procedure to be used during the execution of an asphalt layer for improving the compaction task. This procedure, based on a fuzzy clustering technique, starts from the knowledge of some information recorded by ordinary measuring instruments and provides an aid to the decision-maker on the number of roller passes needed to achieve a specific density at a certain temperature. This result can be deduced with great rapidity during the paving operations on site without waiting for the time spent in the core extraction and in the subsequent laboratory analysis. In this way it is possible to identify more precisely which aspects of the execut…
Plastic or not plastic? That’s the problem: analysing the Italian students purchasing behavior of mineral water bottles made with eco-friendly packag…
2022
Abstract European Strategy for Plastics in a Circular Economy draws new shapes of economy in order to protect the environment and reduce marine pollution, GHGs and countries’ dependence on imported fossil fuels. The core of EU Strategy is also to try to transform the way plastic products are designed, produced, used and recycled in the EU. Italy is the first country in Europe and the second in the world for consumption of bottled water, with remarkable environmental impacts, from production to distribution. Starting from social science theory, this work aims to investigate consumers' behavior and the related factors that influence their behavior pertaining to the purchase of. mineral water …