Search results for "pattern"

Evaluation of the bending behaviour of laminated glass beams via electronic speckle pattern interferometry

2017

The paper is devoted to the experimental analysis of the kinematical and mechanical behaviour of laminated glass beam structures. In particular, the utilized laminated glass specimens are composed of two glass layers bonded by a polymer layer constituted by Ethylene-vinyl acetate whose thickness has been nominally considered as constant for all the specimens. The experimental behaviour of the analyzed specimens is deduced by applying Electronic Speckle- Pattern Interferometry technique; actually, among optical methods this technique (handled by phase-stepping technique) is very effective to obtain a full-field displacement map and to numerically achieve the longitudinal strain. In particula…

Bibliometric analysis of publications by South African viticulture and oenology research centres

2012

We analysed the production, impact factor of, and scientific collaboration involved in viticulture and oenology articles associated with South African research centres published in international journals during the period 1990–2009. The articles under scrutiny were obtained from the Science Citation Index database, accessed via the Web of Knowledge platform. The search strategy employed specific viticulture and oenology terms and was restricted to the field ‘topic’. The results showed that 406 articles were published during the review period, with the most number of publications being in the South African Journal of Enology and Viticulture (n = 34), American Journal of Enology and Vit…

Deep learning and process understanding for data-driven Earth system science

2017

Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, rather than amending classical machine learning, we argue that these contextual cues should be used as part of deep learning (an approach that is able to extract spatio-temporal features automatically) to gain further process understanding of Earth system science problems, improving the predictive ability of seasonal forecasting and modelling of long-range spatial connections across multiple timescales, for example. The next step will be a hybri…

Choosing Optimal Seed Nodes in Competitive Contagion.

2019

International audience; In recent years there has been a growing interest in simulating competitive markets to find out the efficient ways to advertise a product or spread an ideology. Along this line, we consider a binary competitive contagion process where two infections, A and B, interact with each other and diffuse simultaneously in a network. We investigate which is the best centrality measure to find out the seed nodes a company should adopt in the presence of rivals so that it can maximize its influence. These nodes can be used as the initial spreaders or advertisers by firms when two firms compete with each other. Each node is assigned a price tag to become an initial advertiser whi…

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…

Radiomics and Prostate MRI: Current Role and Future Applications

2021

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined to prostate cancer staging. Radiomics is the quantitative extraction and analysis of minable data from medical images; it is emerging as a promising tool to detect and categorize prostate lesions. In this paper we review the role of radiomics applied to prostate mpMRI in detection and localization of prostate cancer, prediction of Gleason score and PI-RADS classification, prediction of extracapsular extension and of biochemical recurrence. We also provide a future perspective of artificial intelligence (machine …

Spatial distribution of N-cycling microbial communities showed complex patterns in constructed wetland sediments.

2013

International audience; Constructed wetlands are used for biological treatment of wastewater from agricultural lands carrying pollutants such as nitrates. Nitrogen removal in wetlands occurs from direct assimilation by plants and through microbial nitrification and denitrification. We investigated the spatial distribution of N-cycling microbial communities and genes involved in nitrification and denitrification in constructed wetland sediments receiving irrigation water. We used quantitative real-time PCR (qPCR) to characterize microbial communities. Geostatistical variance analysis was used to relate them with vegetation cover and biogeochemical sediment properties. The spatial distributio…

Pattern Discovery In Biosequences: From Simple To Complex Patterns

2007

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…

Protein Interaction Networks and Disease: Highlights of the 3rd Challenges in Computational Biology Meeting

2017

Cellular functions are managed by a complex network of protein interactions, the malfunction of which may derive in disease phenotypes. In spite of the incompleteness and noise present in our current protein interaction maps, computational biologists are making strenuous efforts to extract knowledge from these intricate networks and, through their integration with other types of biological data, expedite the development of novel and more effective treatments against human disorders. The 3rd Challenges in Computational Biology meeting revolved around the Protein Interaction Networks and Disease subject, bringing expert network biologists to the city of Mainz, Germany to debate the current st…