Search results for "SCALE"

Flexural Test on a Full-Scale 60-kW Wind Turbine-Tower Telescopic Steel Pipe

2019

A full-scale static test to failure was conducted on 6-m (236.22 in.)-long steel pipes constituting a segment of a telescopic wind tower with a 60-kW wind turbine. The diameter of the circular cross section of the steel pipes was 900 mm (35.43 in.), and the nominal thickness was 10 mm (0.39 in.). The steel grade was 355 MPa (51,488 psi). The tests were conducted in a force-controlled mode in a four-point bending test with a shear-to-span ratio of 2.05. The flexural limit states developed in the form of ovalization of the cross section and of local buckling. The buckling occurred in the plastic range because of the diameter-to-thickness ratio of the section. Although local buckling caused sl…

Robust auto calibration technique for stereo camera

2017

Calibration of the internal and external parameters of a stereo vision camera is a well-known research problem in the computer vision. Usually, to get accurate 3D results the camera should be manually calibrate accurately as well. This paper proposes a robust approach to Auto Calibration stereo camera Without intervention of the user. There are several methods and techniques of calibration that have been proven, in this work we exploiting the geometric constraint, namely, the epipolar geometry. We specifically focuses to use 7 techniques for Features Extraction (SURF, BRISK, FAST, FREAK, MinEigen, MSERF, SIFT), however tries to establish the correspondences between points extracted in stere…

Randomized Hough Transform for Ellipse Detection with Result Clustering

2005

Our research is focused on the development of robust machine vision algorithms for pattern recognition. We want to provide robotic systems the ability to understand more on the external real world. In this paper, we describe a method for detecting ellipses in real world images using the randomized Hough transform with result clustering. A preprocessing phase is used in which real world images are transformed - noise reduction, greyscale transform, edge detection and final binarization - in order to be processed by the actual ellipse detector. The ellipse detector filters out false ellipses that may interfere with the final results. Due to the fact that usually more "virtual" ellipses are de…

Efficient mesoscale hydrodynamics: Multiparticle collision dynamics with massively parallel GPU acceleration

2018

Abstract We present an efficient open-source implementation of the multiparticle collision dynamics (MPCD) algorithm that scales to run on hundreds of graphics processing units (GPUs). We especially focus on optimizations for modern GPU architectures and communication patterns between multiple GPUs. We show that a mixed-precision computing model can improve performance compared to a fully double-precision model while still providing good numerical accuracy. We report weak and strong scaling benchmarks of a reference MPCD solvent and a benchmark of a polymer solution with research-relevant interactions and system size. Our MPCD software enables simulations of mesoscale hydrodynamics at lengt…

Integrative Gene Expression and Metabolic Analysis Tool IgemRNA

2022

ABSTRACTGenome scale metabolic modelling is widely used technique to research metabolism impacts on organism’s properties. Additional omics data integration enables a more precise genotype-phenotype analysis for biotechnology, medicine and life sciences. Transcriptome data amounts rapidly increase each year. Many transcriptome analysis tools with integrated genome scale metabolic modelling are proposed. But these tools have own restrictions, compatibility issues and the necessity of previous experience and advanced user skills. We have analysed and classified published tools, summarized possible transcriptome pre-processing, and analysis methods and implemented them in the new transcriptome…

Methods for Modeling Ecosystem Services: A Review

2015

Abstract Modeling ecosystem services (ES) is an essential tool for the development of strategies that will ensure their future supply, provision and quantification. Given the rapid development in this area of research, a review of the different approaches used to model ES was performed, using an analytical framework based on five criteria for comparing the existing methodological approaches: the types of ES, availability of data sources, spatial scale, types of models used and the possible outcomes of the models. Regulating services were the most commonly modeled, followed by provisioning, cultural, and supporting services. The most frequently used data for modeling were secondary data (alr…

2020

Abstract. Despite the availability of both commercial and open-source software, an ideal tool for digital rock physics analysis for accurate automatic image analysis at ambient computational performance is difficult to pinpoint. More often, image segmentation is driven manually, where the performance remains limited to two phases. Discrepancies due to artefacts cause inaccuracies in image analysis. To overcome these problems, we have developed CobWeb 1.0, which is automated and explicitly tailored for accurate greyscale (multiphase) image segmentation using unsupervised and supervised machine learning techniques. In this study, we demonstrate image segmentation using unsupervised machine le…

Weighted nonlinear correlation for controlled discrimination capability

2002

We recently demonstrated the high discrimination capability as well as the high sensitivity to small intensity variations of the sliced orthogonal nonlinear generalized (SONG) correlation. This nonlinear correlation has a correlation matrix representation. Previous papers considered only the principal diagonal elements of the correlation matrix. We propose using the off-diagonal non-zero elements of the SONG correlation matrix in order to achieve variable discrimination performance and controlled detection adapted to the gray-scale variations. Moreover, we introduce negative coefficients in order to improve the discrimination properties of the SONG correlation. To control the degree of reco…

Machine Learning Methods for Spatial and Temporal Parameter Estimation

2020

Monitoring vegetation with satellite remote sensing is of paramount relevance to understand the status and health of our planet. Accurate and constant monitoring of the biosphere has large societal, economical, and environmental implications, given the increasing demand of biofuels and food by the world population. The current democratization of machine learning, big data, and high processing capabilities allow us to take such endeavor in a decisive manner. This chapter proposes three novel machine learning approaches to exploit spatial, temporal, multi-sensor, and large-scale data characteristics. We show (1) the application of multi-output Gaussian processes for gap-filling time series of…

Market Environment Factors Influence on Development of Bancassurance in Latvia

2021

Banks and insurers as part of financial service industry engage in partnership under the concept of Bancassurance. Several studies are done on this topic, focusing on economies of scale and performance of most Bancassurance common models. The purpose of this study is to identify the key market environment factors that influence the development of Bancassurance for retail banks in Latvia and the level of increase. Aim of this research is to analyse – how market environment factors influence the development of Bancassurance in Latvia. The current paper is focused on the Latvian market where several Bancassurance models are present as we test our propositions by interviewing management represe…