Search results for "Hierarchical"

Adapting hierarchical bidirectional inter prediction on a GPU-based platform for 2D and 3D H.264 video coding

2013

The H.264/AVC video coding standard introduces some improved tools in order to increase compression efficiency. Moreover, the multi-view extension of H.264/AVC, called H.264/MVC, adopts many of them. Among the new features, variable block-size motion estimation is one which contributes to high coding efficiency. Furthermore, it defines a different prediction structure that includes hierarchical bidirectional pictures, outperforming traditional Group of Pictures patterns in both scenarios: single-view and multi-view. However, these video coding techniques have high computational complexity. Several techniques have been proposed in the literature over the last few years which are aimed at acc…

Incorporating Uncertainties into Traffic Simulators

2007

Applications and Limitations of Robust Bayesian Bounds and Type II MLE

1994

Three applications of robust Bayesian analysis and three examples of its limitations are given. The applications that are reviewed are the development of an automatic Ockham’s Razor, outlier detection, and analysis of weighted distributions. Limitations of robust Bayesian bounds are highlighted through examples that include analysis of a paranormal experiment and a hierarchical model. This last example shows a disturbing difference between actual hierarchical Bayesian analysis and robust Bayesian bounds, a difference which also arises if, instead, a Type II MLE or empirical Bayes analysis is performed.

Sectors on sectors (SonS): A new hierarchical clustering visualization tool

2011

Clustering techniques have been widely applied to extract information from high-dimensional data structures in the last few years. Graphs are especially relevant for clustering, but many graphs associated with hierarchical clustering do not give any information about the values of the centroids' attributes and the relationships among them. In this paper, we propose a new visualization approach for hierarchical cluster analysis in which the above-mentioned information is available. The method is based on pie charts. The pie charts are divided into several pie segments or sectors corresponding to each cluster. The radius of each pie segment is proportional to the number of patterns included i…

The problem of interoperability: A common data format for quantum chemistry codes

2007

A common format for quantum chemistry (QC), enhancing code interoperability and communication between different programs, has been designed and implemented. An XML-based format, QC-ML, is presented for representing quantities such as geometry, basis set, and so on, while an HDF5-based format is presented for the storage of large binary data files. Some preliminary applications that use the format have been implemented and are also described. This activity was carried out within the COST in Chemistry D23 project “MetaChem,” in the Working Group “A meta-laboratory for code integration in ab initio methods.” © 2007 Wiley Periodicals, Inc. Int J Quantum Chem, 2007

A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data …

2013

Abstract Background Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summarized as a three step process: (1) choice of a distance function; (2) choice of a clustering algorithm; (3) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Results A procedure is proposed for the assessment of the discriminative ability of a distance functi…

Automated Uncertainty Quantification Through Information Fusion in Manufacturing Processes

2017

International audience; Evaluation of key performance indicators (KPIs) such as energy consumption is essential for decision-making during the design and operation of smart manufacturing systems. The measurements of KPIs are strongly affected by several uncertainty sources such as input material uncertainty, the inherent variability in the manufacturing process, model uncertainty, and the uncertainty in the sensor measurements of operational data. A comprehensive understanding of the uncertainty sources and their effect on the KPIs is required to make the manufacturing processes more efficient. Towards this objective, this paper proposed an automated methodology to generate a hierarchical B…

Fast Implementation of Double-coupled Nonnegative Canonical Polyadic Decomposition

2019

Real-world data exhibiting high order/dimensionality and various couplings are linked to each other since they share some common characteristics. Coupled tensor decomposition has become a popular technique for group analysis in recent years, especially for simultaneous analysis of multi-block tensor data with common information. To address the multiblock tensor data, we propose a fast double-coupled nonnegative Canonical Polyadic Decomposition (FDC-NCPD) algorithm in this study, based on the linked CP tensor decomposition (LCPTD) model and fast Hierarchical Alternating Least Squares (Fast-HALS) algorithm. The proposed FDCNCPD algorithm enables simultaneous extraction of common components, i…

A Hierarchical Model for Analysing Consumption Patterns in Italy Before and During the Great Recession

2016

The paper aims to explore how the Great Recession of the twenty-first century has impacted on the consumption behaviour of Italian households. Following a hierarchical approach, the study investigates differences in consumption behaviour at both household and regional levels. Using micro data on Italian Household Expenditure for the years 2002, 2006, 2010 and 2012, multilevel and two-step regression models have been estimated. The analysis has been performed for four different consumption categories: food, housing, work-related and leisure. The analysis reveals that the economic crisis led to increasing income elasticity for each category of consumption, especially for food, the most essent…

On utilizing an enhanced object partitioning scheme to optimize self-organizing lists-on-lists

2020

With the advent of “Big Data” as a field, in and of itself, there are at least three fundamentally new questions that have emerged, namely the Artificially Intelligence (AI)-based algorithms required, the hardware to process the data, and the methods to store and access the data efficiently. This paper (The work of the second author was partially supported by NSERC, the Natural Sciences and Engineering Council of Canada. We are very grateful for the feedback from the anonymous Referees of the original submission. Their input significantly improved the quality of this final version.) presents some novel schemes for the last of the three areas. There have been thousands of papers written rega…