Search results for "Hierarchical Clustering"
showing 10 items of 56 documents
An efficient cluster-based outdoor user positioning using LTE and WLAN signal strengths
2015
In this paper we propose a novel cluster-based RF fingerprinting method for outdoor user-equipment (UE) positioning using both LTE and WLAN signals. It uses a simple cost effective agglomerative hierarchical clustering with Davies-Bouldin criterion to select the optimal cluster number. The positioning method does not require training signature formation prior to UE position estimation phase. It is capable of reducing the search space for clustering operation by using LTE cell-ID searching criteria. This enables the method to estimate UE positioning in short time with less computational expense. To validate the cluster-based positioning real-time field measurements were collected using readi…
Radio frequency fingerprinting for outdoor user equipment localization
2017
The recent advancements in cellular mobile technology and smart phone usage have opened opportunities for researchers and commercial companies to develop ubiquitous low cost localization systems. Radio frequency (RF) fingerprinting is a popular positioning technique which uses radio signal strength (RSS) values from already existing infrastructures to provide satisfactory user positioning accuracy in indoor and densely built outdoor urban areas where Global Navigation Satellite System (GNSS) signal is poor and hard to reach. However a major requirement for the RF fingerprinting to maintain good localization accuracy is the collection and updating of large training database. The Minimization…
A hierarchical cluster analysis to determine whether injured runners exhibit similar kinematic gait patterns
2020
Previous studies have suggested that runners can be subgrouped based on homogeneous gait patterns, however, no previous study has assessed the presence of such subgroups in a population of individuals across a wide variety of injuries. Therefore, the purpose of this study was to assess whether distinct subgroups with homogeneous running patterns can be identified among a large group of injured and healthy runners and whether identified subgroups are associated with specific injury location. Three‐dimensional kinematic data from 291 injured and healthy runners, representing both sexes and a wide range of ages (10‐66 years) was clustered using hierarchical cluster analysis. Cluster analysis r…
An AI Walk from Pharmacokinetics to Marketing
2009
This work is intended for providing a review of reallife practical applications of Artificial Intelligence (AI) methods. We focus on the use of Machine Learning (ML) methods applied to rather real problems than synthetic problems with standard and controlled environment. In particular, we will describe the following problems in next sections: • Optimization of Erythropoietin (EPO) dosages in anaemic patients undergoing Chronic Renal Failure (CRF). • Optimization of a recommender system for citizen web portal users. • Optimization of a marketing campaign. The choice of these problems is due to their relevance and their heterogeneity. This heterogeneity shows the capabilities and versatility …
Iterative Cluster Analysis of Protein Interaction Data
2004
Abstract Motivation: Generation of fast tools of hierarchical clustering to be applied when distances among elements of a set are constrained, causing frequent distance ties, as happens in protein interaction data. Results: We present in this work the program UVCLUSTER, that iteratively explores distance datasets using hierarchical clustering. Once the user selects a group of proteins, UVCLUSTER converts the set of primary distances among them (i.e. the minimum number of steps, or interactions, required to connect two proteins) into secondary distances that measure the strength of the connection between each pair of proteins when the interactions for all the proteins in the group are consid…
Structural analyses in the study of behavior : From rodents to non-human primates
2022
Ajuts: J-BL's research was funded by Natural Sciences and Engineering Research Council of Canada (NSERC, Discovery Grant #: 2015-06034 to J-BL). MC, SA, and GC's research was funded by a grant from the University of Palermo, Italy. The term " structure " indicates a set of components that, in relation to each other, shape an organic complex. Such a complex takes on essential connotations of functionally unitary entity resulting from the mutual relationships of its constituent elements. In a broader sense, we can use the word " structure " to define the set of relationships among the elements of an emergent system that is not determined by the mere algebraic sum of these elements, but by the…
Kullback-Leibler distance as a measure of the information filtered from multivariate data
2007
We show that the Kullback-Leibler distance is a good measure of the statistical uncertainty of correlation matrices estimated by using a finite set of data. For correlation matrices of multivariate Gaussian variables we analytically determine the expected values of the Kullback-Leibler distance of a sample correlation matrix from a reference model and we show that the expected values are known also when the specific model is unknown. We propose to make use of the Kullback-Leibler distance to estimate the information extracted from a correlation matrix by correlation filtering procedures. We also show how to use this distance to measure the stability of filtering procedures with respect to s…
Cruise passengers' trajectories at destination. A Dynamic Time Warping approach.
2015
The present work aims at proposing an analysis of cruise passengers trajectories at the destination through Dynamic Time Warping algorithm. Data collected through GPS devices on cruise passengers’ behavior in the port of Palermo are analyzed in order to show similarities and differences among their spatial trajectories at the destination. A cluster analysis is performed in order to identify cruise passengers’ segments based on trajectories’ similarity. Results are of interest from both a methodological perspective related with the analysis of GPS data, and for the management and planning of cruise tourism destinations.
The Hierarchical Agglomerative Clustering with Gower index: a methodology for automatic design of OLAP cube in ecological data processing context
2015
In Press, Corrected Proof; International audience; The OLAP systems can be an improvement for ecological studies. In fact, ecology studies, follows and analyzes phenomenon across space and time and according to several parameters. OLAP systems can provide to ecologists browsing in a large dataset. One focus of the current research on OLAP system is the automatic design of OLAP cubes and of data warehouse schemas. This kind of works makes accessible OLAP technology to non information technology experts. But to be efficient, the automatic OLAP building must take into account various cases. Moreover the OLAP technology is based on the concept of hierarchy. Thereby the hierarchical clustering m…
SparseHC: A Memory-efficient Online Hierarchical Clustering Algorithm
2014
Computing a hierarchical clustering of objects from a pairwise distance matrix is an important algorithmic kernel in computational science. Since the storage of this matrix requires quadratic space with respect to the number of objects, the design of memory-efficient approaches is of high importance to this research area. In this paper, we address this problem by presenting a memory-efficient online hierarchical clustering algorithm called SparseHC. SparseHC scans a sorted and possibly sparse distance matrix chunk-by-chunk. Meanwhile, a dendrogram is built by merging cluster pairs as and when the distance between them is determined to be the smallest among all remaining cluster pairs. The k…