Search results for "Benchmark"

Elaboración de modelos 3D de diferentes morfologías y escalas utilizando técnicas Structure-from-Motion y fotografías terrestres

2016

En este trabajo se evalúan los métodos de foto-reconstrucción automatizada basados en el uso conjunto de las técnicas Structure from Motion (SfM) y Multi-View Stereo (MVS) para medir, monitorizar y cuantificar la dinámica de tres formas geomorfológicas: i) el glaciar rocoso del Corral del Veleta (Granada, España), ii) un paisaje de cárcavas de tipo calanchi (Sicilia, Italia) y ii) cinco pequeñas cabeceras de cárcava (Cáceres, España). Se incluyen en este trabajo los resultados sobre la precisión, utilidad y aplicabilidad de estas técnicas. Para la cuantificación de la precisión se utilizan el error cuadrático medio (RMSE) de los puntos de control que se emplean en la georreferenciación y la…

A critical review of life cycle assessment benchmarking methodologies for construction materials

2022

As it stands, the construction sector accounts for a significant proportion of global emissions. The majority of these emissions can be associated with material production. As a result, the importance of quantifying these environmental impacts is continually increasing. However, there is a current lack of guidance and methodologies regarding how to benchmark the impacts of construction products, and thus achieve more transparent environmental reporting and decision-making. Therefore, the aim of this study was to review engineering life-cycle assessment (LCA) literature and applicable standards to identify the key methodological variables required and the key steps for a sector-wide methodol…

Video-Based Depression Detection Using Local Curvelet Binary Patterns in Pairwise Orthogonal Planes

2016

International audience; Depression is an increasingly prevalent mood disorder. This is the reason why the field of computer-based depression assessment has been gaining the attention of the research community during the past couple of years. The present work proposes two algorithms for depression detection, one Frame-based and the second Video-based, both employing Curvelet transform and Local Binary Patterns. The main advantage of these methods is that they have significantly lower computational requirements, as the extracted features are of very low dimensionality. This is achieved by modifying the previously proposed algorithm which considers Three-Orthogonal-Planes, to only Pairwise-Ort…

The shortest-path problem with resource constraints with -loop elimination and its application to the capacitated arc-routing problem

2014

Abstract In many branch-and-price algorithms, the column generation subproblem consists of computing feasible constrained paths. In the capacitated arc-routing problem (CARP), elementarity constraints concerning the edges to be serviced and additional constraints resulting from the branch-and-bound process together impose two types of loop-elimination constraints. To fulfill the former constraints, it is common practice to rely on a relaxation where loops are allowed. In a k-loop elimination approach all loops of length k and smaller are forbidden. Following Bode and Irnich (2012) for solving the CARP, branching on followers and non-followers is the only known approach to guarantee integer …

Particle Swarm Optimization as a New Measure of Machine Translation Efficiency

2018

The present work proposes a new approach to measuring efficiency of evolutionary algorithm-based Machine Translation. We implement some attributes of evolutionary algorithms performing cosine similarity objective function of a Particle Swarm Optimization (PSO) algorithm then, we evaluate an English text set for translation precision into the Spanish text as a simulated benchmark, and explore the backward process. Our results show that PSO algorithm can be used for translation of multiple language sentences with one identifier only, in other words the technology presented is language-pair independent. Specifically, we indicate that our cosine similarity objective function improves the veloci…

2014

Large data sets classification is widely used in many industrial applications. It is a challenging task to classify large data sets efficiently, accurately, and robustly, as large data sets always contain numerous instances with high dimensional feature space. In order to deal with this problem, in this paper we present an online Logdet divergence based metric learning (LDML) model by making use of the powerfulness of metric learning. We firstly generate a Mahalanobis matrix via learning the training data with LDML model. Meanwhile, we propose a compressed representation for high dimensional Mahalanobis matrix to reduce the computation complexity in each iteration. The final Mahalanobis mat…

A simple analytical method for heterogeneity corrections in low dose rate prostate brachytherapy

2015

In low energy brachytherapy, the presence of tissue heterogeneities contributes significantly to the discrepancies observed between treatment plan and delivered dose. In this work, we present a simplified analytical dose calculation algorithm for heterogeneous tissue. We compare it with Monte Carlo computations and assess its suitability for integration in clinical treatment planning systems. The algorithm, named as RayStretch, is based on the classic equivalent path length method and TG-43 reference data. Analytical and Monte Carlo dose calculations using Penelope2008 are compared for a benchmark case: a prostate patient with calcifications. The results show a remarkable agreement between …

Deep Learning Estimation of 10-2 and 24-2 Visual Field Metrics Based on Thickness Maps from Macula OCT.

2021

Purpose To develop deep learning (DL) systems estimating visual function from macula-centered spectral-domain (SD) OCT images. Design Evaluation of a diagnostic technology. Participants A total of 2408 10-2 visual field (VF) SD OCT pairs and 2999 24-2 VF SD OCT pairs collected from 645 healthy and glaucoma subjects (1222 eyes). Methods Deep learning models were trained on thickness maps from Spectralis macula SD OCT to estimate 10-2 and 24-2 VF mean deviation (MD) and pattern standard deviation (PSD). Individual and combined DL models were trained using thickness data from 6 layers (retinal nerve fiber layer [RNFL], ganglion cell layer [GCL], inner plexiform layer [IPL], ganglion cell-IPL […

Harmonized benchmark labels of the hippocampus on magnetic resonance: The EADC-ADNI project

2015

Abstract Background A globally harmonized protocol (HarP) for manual hippocampal segmentation based on magnetic resonance has been recently developed by a task force from European Alzheimer's Disease Consortium (EADC) and Alzheimer's Disease Neuroimaging Initiative (ADNI). Our aim was to produce benchmark labels based on the HarP for manual segmentation. Methods Five experts of manual hippocampal segmentation underwent specific training on the HarP and segmented 40 right and left hippocampi from 10 ADNI subjects on both 1.5 T and 3 T scans. An independent expert visually checked segmentations for compliance with the HarP. Descriptive measures of agreement between tracers were intraclass cor…

A Model‐Based Workflow to Benchmark the Clinical Cholestasis Risk of Drugs

2021

We present a generic workflow combining physiology-based computational modeling and in vitro data to assess the clinical cholestatic risk of different drugs systematically. Changes in expression levels of genes involved in the enterohepatic circulation of bile acids were obtained from an in vitro assay mimicking 14 days of repeated drug administration for 10 marketed drugs. These changes in gene expression over time were contextualized in a physiology-based bile acid model of glycochenodeoxycholic acid. The simulated drug-induced response in bile acid concentrations was then scaled with the applied drug doses to calculate the cholestatic potential for each compound. A ranking of the cholest…