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About 10,000 papers for “quantitative evaluation”

Quantitative evaluation.

Min Xu (15203), YouDong Ding (11773099) · Figshare · 2021

<p>The data in this figure is from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0259953#pone.0259953.g003" target="_blank">Fig 3</a>, and the images are in the same order.</p>

Cited by 0Open access

Quantitative evaluation.

Anja Laader (4585654), Karsten Beiderwellen (560822), Oliver Kraff (418618) et al. · Figshare · 2017

<p>(A) Quantitative analysis showing contrast ratios of different parenchymatous organs to the ipsilateral psoas muscle for the T1-weighted sequences. * indicates statistical significance (p value < 0.05).(B) Quantitative analysis showing contrast ratios of different parenchymatous organs to the ipsilateral psoas muscle for TrueFISP and T2-weighted TSE sequence. * indicates statistical significance (p value < 0.05).</p>

Cited by 0Open access

Quantitative Evaluation

Larry Brewster, Behavior A, Larry Brewster · 2014

California has been a leader in prison fine arts programs. Arts-in-Corrections, the granddaddy of them all, enjoyed a highly successful 30 year run until its closure in 2010 as a result of the state's budget crisis. This study evaluates three demonstration projects modeled after AIC, and prison theater programs offered through The Actors ' Gang's Prison Project and Marin Shakespeare. Inmates from San Quentin, Soledad, New Folsom and CRC, Norco state prisons participated in the study. Pre-and Post surveys designed to measure changes in attitudes and behavior were administered at the start and finish of each 12-week arts program. The surveys included attitudinal scales adapted from the "Life Effectiveness Questionnaire " (LEQ) measuring: time management, social competence, achievement motivation, intellectual flexibility, emotional control, active initiative, and self-confidence. In addition to positive correlations between arts education and life effectiveness attitudes, we found a reduction in disciplinary reports and greater participation in academic and vocation programs. This study supports the findings of

Cited by 0

Quantitative evaluation results.

Lei Wu (202933), Xunyan Jiang (22634175), Zhijian Zhao (389825) et al. · Figshare · 2025

<div> Pansharpening usually improves the resolution of low-resolution multispectral (LRMS) images with spatial information from corresponding high-resolution panchromatic (HRPAN) images to produce high-resolution MS (HRMS) images. Traditional pansharpening methods use various domain transformations to make the fused image suffer varying degrees of spatial or spectral distortion because the information in the LRMS and PAN images is heterogeneous and distributed in different domains. The motivation of our proposed work is to develop a balanced and robust pansharpening method named cross-domain correspondence intensity modulation, which is based on Bayesian decision-making for remote sensing image pansharpening. First, the intensity component of the MS image is obtained via the intensity hue saturation (IHS) transform. Second, a fusion rule based on the Bayesian probabilistic model is designed to fuse the intensity component and the corresponding PAN image to obtain an intermediate component. Third, a cross-domain correspondence intensity modulation algorithm is proposed to modulate the intensity information in the intermediate component to produce the desired intensity component. Finally, an inverse IHS transformation is performed to obtain the pansharpened MS image by replacing the original intensity component with the modulated intensity component. The results on different satellite datasets show that the proposed method can effectively enhance the spatial and spectral fidelity of the fused image. </div>

Cited by 0Open access

Insar Quantitative Evaluation

B. Carron · 1997

We will present the INSAR Quantitative Evaluation Study, conducted for ESA/ESRIN. The INSAR consortium coordinated by Matra Cap Systemes gathers 9 European partners to validate interferometry for 5 applications over more than 15 test sites, from Antarctica to northern Norway Islands, The INSAR project aims to evaluate and quantify interferometric SAR approach towards conventional measurements, with ground truth reference data, in the field of the following applications : digital elevation model (DEM) production ; hydrology ; forestry ; earth science (earthquake and volcanoes monitoring) and glaciology (ice monitoring).

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Quantitative vendor evaluation

Tripathy, A. · Indian Institute of Management, Ahmedabad Institutional Repository (Indian Institute of Management, Ahmedabad) · 2010

Achieve (Journal of Bombay Productivity Council), Vol. XVIII, No. 3, (July-September 1991), pp. 10-15

Cited by 0

Quantitative evaluation results.

Lei Wu (202933), Xunyan Jiang (22634175), Zhijian Zhao (389825) et al. · Figshare · 2025

<div> Pansharpening usually improves the resolution of low-resolution multispectral (LRMS) images with spatial information from corresponding high-resolution panchromatic (HRPAN) images to produce high-resolution MS (HRMS) images. Traditional pansharpening methods use various domain transformations to make the fused image suffer varying degrees of spatial or spectral distortion because the information in the LRMS and PAN images is heterogeneous and distributed in different domains. The motivation of our proposed work is to develop a balanced and robust pansharpening method named cross-domain correspondence intensity modulation, which is based on Bayesian decision-making for remote sensing image pansharpening. First, the intensity component of the MS image is obtained via the intensity hue saturation (IHS) transform. Second, a fusion rule based on the Bayesian probabilistic model is designed to fuse the intensity component and the corresponding PAN image to obtain an intermediate component. Third, a cross-domain correspondence intensity modulation algorithm is proposed to modulate the intensity information in the intermediate component to produce the desired intensity component. Finally, an inverse IHS transformation is performed to obtain the pansharpened MS image by replacing the original intensity component with the modulated intensity component. The results on different satellite datasets show that the proposed method can effectively enhance the spatial and spectral fidelity of the fused image. </div>

Cited by 0Open access

Quantitative Nondestructive Evaluation

Dallas G. Smith, John A Schaeffel · 1979

Abstract : This manual has been prepared primarily for the non-NDE specialist. Its aim is to increase understanding of NDE capabilities among those involved in structural design and fracture mechanics calculations, and to provide physical details pertaining to most of the important NDE techniques. Since NDE has been so actively applied in the aerospace industry most of the application examples discussed are related to aerospace structures: however the basic ideas apply to any structure containing fracture critical components. The introduction discusses the relationship of fracture mechanics and quantitative NDE. The present practice of NDE, including military specifications, airplane inspection manuals, and inspector training are discussed next. The 'big five' methods of NDE -- liquid penetrant, magnetic particle, ultrasonic inspection, eddy current, and radiography -- are introduced as well as certain advanced inspection methods -- methods still undergoing development. The state-of-the-art, the sensitivity and reliability, of various methods along with the statistical analysis for determining flaw detection probability and confidence levels is presented. Excerpts from two actual airplane inspection manuals are included in the appendix to illustrate the degree to which instructions to inspectors are detailed and specified.

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Quantitative evaluation metrics.

Qi-long Liu (18056234), Kit-lun Yick (8927807), Yue Sun (197395) et al. · Figshare · 2024

&lt;div&gt;&lt;p&gt;Understanding the dynamic deformation pattern and biomechanical properties of breasts is crucial in various fields, including designing ergonomic bras and customized prostheses, as well as in clinical practice. Previous studies have recorded and analyzed the dynamic behaviors of the breast surface using 4D scanning, which provides a sequence of 3D meshes during movement with high spatial and temporal resolutions. However, these studies are limited by the lack of robust and automated data processing methods which result in limited data coverage or error-prone analysis results. To address this issue, we identify revealing inter-frame dense correspondence as the core challenge towards conducting reliable and consistent analysis of the 4D scanning data. We proposed a fully-automatic approach named Ulta-dense Motion Capture (UdMC) using Thin-plate Spline (TPS) to augment the sparse landmarks recorded via motion capture (MoCap) as initial dense correspondence and then rectified it with a sophisticated post-alignment scheme. Two downstream tasks are demonstrated to validate its applicability: virtual landmark tracking and deformation intensity analysis. For evaluation, a dynamic 4D human breast anthropometric dataset &lt;i&gt;DynaBreastLite&lt;/i&gt; was constructed. The results show that our approach can robustly capture the dynamic deformation characteristics of the breast surfaces, significantly outperforms baselines adapted from previous works in terms of accuracy, consistency, and efficiency. For 10 fps dataset, average error of 0.25 cm on control-landmarks and 0.33 cm on non-control (arbitrary) landmarks were achieved, with 17-70 times faster computation time. Evaluation was also carried out on 60 fps and 120 fps datasets, with consistent and large performance gaining being observed. The proposed method may contribute to advancing research in breast anthropometry, biomechanics, and ergonomics by enabling more accurate tracking of the breast surface deformation patterns and dynamic characteristics.&lt;/p&gt;&lt;/div&gt;

Cited by 0Open access

RINEW-G quantitative evaluation

Jesmin Sultana, Helen O. Pitchik · Open Science Framework · 2022

Pre-analysis plan for a quantitative evaluation if the RINEW-G intervention

Cited by 0Open access