Search results for "cluster [track data analysis]"
showing 10 items of 1171 documents
Instability of cuboctahedral copper clusters.
1992
Equilibrium structures of copper clusters up to 10 000 atoms are studied using molecular-dynamics and effective-medium theory. Icosahedral closed-shell clusters are most stable up to \ensuremath{\sim}2500 atoms and the Wulff polyhedra are favored for larger clusters. Cuboctahedral closed-shell clusters up to \ensuremath{\sim}2000 atoms are unstable. They undergo a nondiffusive transition to an icosahedral structure at low temperatures and melt directly above the fcc-cluster-melting temperature. The melting temperature decreases with decreasing cluster size but not as deeply as has been reported for pure metals.
Efficient distributed average consensus in wireless sensor networks
2020
International audience; Computing the distributed average consensus in Wireless Sensor Networks (WSNs) is investigated in this article. This problem, which is both natural and important, plays a significant role in various application fields such as mobile agents and fleet vehicle coordination, network synchronization, distributed voting and decision, load balancing of divisible loads in distributed computing network systems, and so on. By and large, the average consensus' objective is to have all nodes in the network converged to the average value of the initial nodes' measurements based only on local nodes' information states. In this paper, we introduce a fully distributed algorithm to a…
Construction of Disjoint Virtual Backbones for Wireless Sensor Networks
2020
A wireless sensor network is a wireless network of sensors aimed at monitoring physical events. It has ingratiated itself into almost all areas of human endeavors. Data dissemination in these networks is quite challenging and is generally accomplished by flooding. But flooding introduces broadcast storm problem due from implosion and overlap. To overcome this, topology management can prescribe a virtual backbone network to which routing is confined. In this paper we propose an algorithm that constructs multiple disjoint virtual backbone networks, using only nodes' locations. The disjointedness makes routing more robust and the network exploitation energy efficient. Simulations show our algo…
Mitochondrial DNA Regionalism and Historical Demography in the Extant Populations of Chirocephalus kerkyrensis (Branchiopoda: Anostraca)
2012
BackgroundMediterranean temporary water bodies are important reservoirs of biodiversity and host a unique assemblage of diapausing aquatic invertebrates. These environments are currently vanishing because of increasing human pressure. Chirocephalus kerkyrensis is a fairy shrimp typical of temporary water bodies in Mediterranean plain forests and has undergone a substantial decline in number of populations in recent years due to habitat loss. We assessed patterns of genetic connectivity and phylogeographic history in the seven extant populations of the species from Albania, Corfu Is. (Greece), Southern and Central Italy.Methodology/principal findingsWe analyzed sequence variation at two mito…
Clustering-Assisted 3D Beamforming for Throughput Maximization in mmWave Networks
2021
Beamforming schemes have been widely used to improve network throughput in 5G mmWave networks. However, 3D beamforming schemes have hereto not been investigated in this context. In this work, a cluster-assisted 3D beamforming scheme is proposed to optimize the downtilt angle for network coverage and throughput maximization. User Equipment (UEs) are clustered based on inter-user and the inter-cluster distances. The interference is accounted from the adjacent clusters and thus frequency resources can be assigned to the non-adjacent clusters. Optimal downtilt angles are obtained for every cluster to maximize the throughput while considering the interference from adjacent clusters. 3D beam patt…
Contribution of HVSR measures for seismic microzonation studies
2018
The HVSR method applied to seismic noise can be a very useful technique to map the site effects of the territory, to identify the thickness of the soft covering and so the depth of the seismic bedrock. The case of the urban area of Oliveri is presented. Because of its high seismic hazard this area has been subject of first level seismic microzonation. The town lies on a large coastal plain made of mixed fluvial/marine sediments, overlapping a deformed substrate. In order to identify points on the area probably suffering of relevant site effects and to define a preliminary Vs subsurface model, 23 HVSR measurements were performed. A clustering technique of continuous signals has been used to …
Cluster-based active learning for compact image classification
2010
In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer…
Sparse Manifold Clustering and Embedding to discriminate gene expression profiles of glioblastoma and meningioma tumors.
2013
Sparse Manifold Clustering and Embedding (SMCE) algorithm has been recently proposed for simultaneous clustering and dimensionality reduction of data on nonlinear manifolds using sparse representation techniques. In this work, SMCE algorithm is applied to the differential discrimination of Glioblastoma and Meningioma Tumors by means of their Gene Expression Profiles. Our purpose was to evaluate the robustness of this nonlinear manifold to classify gene expression profiles, characterized by the high-dimensionality of their representations and the low discrimination power of most of the genes. For this objective, we used SMCE to reduce the dimensionality of a preprocessed dataset of 35 single…
A Coclustering Approach for Mining Large Protein-Protein Interaction Networks
2012
Several approaches have been presented in the literature to cluster Protein-Protein Interaction (PPI) networks. They can be grouped in two main categories: those allowing a protein to participate in different clusters and those generating only nonoverlapping clusters. In both cases, a challenging task is to find a suitable compromise between the biological relevance of the results and a comprehensive coverage of the analyzed networks. Indeed, methods returning high accurate results are often able to cover only small parts of the input PPI network, especially when low-characterized networks are considered. We present a coclustering-based technique able to generate both overlapping and nonove…
Evaluation of training in guideline-oriented biopsychosocial management of low back pain in occupational health services:Protocol of a cluster random…
2021
Background To prevent low back pain (LBP) from developing into a prolonged disabling condition, clinical guidelines advocate early stage assessment, risk‐screening, and tailored interventions. Occupational health services recommend guideline‐oriented biopsychosocial screening and individualized assessment and management. However, it is not known whether training a limited number of health care professionals improves the management process. The primary objective of this study is to investigate whether training in the biopsychosocial practice model is effective in reducing disability. Furthermore, we aim to evaluate health‐economic impacts of the training intervention in comparison to usual m…