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100 results for “Cost models”
Study On Hybrid Model Combining Super Learner And Physics-based Models For SHM In Bridges Using Low-cost BWIM
<p>The main objective of this project is to study and develop hybrid models of BWIM physics-based models incorporates with SHM inspection used by artificial intelligence (AI) techniques to predict structural damage. This study presents a comprehensive assessment of FE simulations leveraging contact method verified by vehicle-bridge interaction(VBI) theory and uses machine learning (ML) techniques to identify and predict structural damages from the structural response automatically. Bridges are a fundamental part of infrastructure management. The main challenge that we face is the aging of these transportation infrastructures without a tool to perform accurate structural assessments in a real-time manner. Unfortunately, this topic is still not completely developed due to the lack of study upon BWIM simulations designed with several different severity damages. The Contact method, a new approach to simulating moving-vehicle motion in BWIM simulation, is to carry out actual structural response verified by the VBI with comprehensive parameter studies. In order to simulation the reality complex condition of the bridge, the FE model is designed by four different classes of damages with three different damage locations applied with two different load conditions (e.g., static load and moving load). The responses collected from FE simulation are used for structural damage prediction leveraging the ML damage prediction model. Among ML methods, the XGBoost with assembly decision tree shows the most reliable results. The results in this project indicate that structural damage prediction can be achieved by using the ML technique and BWIM structural response, which provides high accuracy of damage prediction.</p>
Example of input and output datasets of the cost module implemented in the SHERPA modelling tool
<p><em>Integrated Assessment Model provides a useful framework for evaluating different aspects of air quality policies, spanning from abatement measures to emissions, concentrations, health impacts and costs. These models are then useful to provide a holistic view of the impacts of policies, so that ex-ante one can evaluate how various policies will impact air concentrations, health benefits and implementation costs. Among these Integrated Assessment Models, SHERPA (Screening for High Emission Potentials on Air) has been recently used to evaluate the impact of policies, covering all aspects from measures to health, but without being able to provide the dimension related to abatement measures costs. These three files dataset provide an example of the ability of the new cost module in SHERPA to calculate the cost of emission reductions.</em></p>
SET-NAV: WP5: Invert modelling output for the building sector final energy demand and cost data
<p>This data set contains the Invert modelling results for final energy demand for space heating, cooling and hot water in buildings; hourly data for district heating and electricity (for different technologies) for 3-4 building types; annual data for the other energy carriers.</p> <p>It also contains all annual cost (Annuity of investments, O&M, fuel cost ) of electricity generation and / or heat generation and considered efficiency measures.</p> <p>This data is also available and visualised in our dedicated SET-NAV open data platform: The SET-NAV Scenario Explorer: https://data.ene.iiasa.ac.at/set-nav/#/workspaces</p>
Updated Smoke Exposure Estimate for Indonesian Peatland Fires using a Network of Low-cost PM2.5 sensors and a regional air quality model - Model Simulation Data
<p>WRF-Chem simulated daily mean PM2.5 concentrations for:</p> <p>1) with fires </p> <p>2) without fires</p> <p>simulations. </p>
Updated Smoke Exposure Estimate for Indonesian Peatland Fires using a Network of Low-cost PM2.5 sensors and a regional air quality model - Purple Air data
<p>Daily mean PM2.5 concentrations collected by Purple Air sensors between 2023-08-16 and 2023-12-01. Concentrations have been RH adjusted using the Nilson et al (2022) adjustment. </p>
Data and codes for "The impact, costs, and cost-effectiveness of tuberculosis outbreak investigations in the United States: a model-based analysis"
<p>Data and codes for the manuscript entitled:</p> <p>"<strong>The impact, costs, and cost-effectiveness of tuberculosis outbreak investigations in the United States: a model-based analysis"</strong></p> <p> </p> <p><strong>Please see Readme.txt for details</strong></p>
Simulation results for "COVID-19 vaccination in Sindh Province, Pakistan: a modelling study of health impact and cost-effectiveness"
<p>The high-performance computing results for raw epidemiological simulations and quantiled scenarios associated with https://doi.org/10.1101/2021.02.24.21252338.</p> <p>All results stored as compressed rds files of data.table objects (use-able as data.frame objects) for use with R programming language.</p>
Data Set: Renewable hydrogen fuels versus fossil fuels for trucking, shipping and aviation: A holistic cost model
<p>Data Set: Renewable hydrogen fuels versus fossil fuels for trucking, shipping and aviation: A holistic cost model</p>
Limiting scaring activities reduces economic costs associated with foraging barnacle geese: results from an individual-based model
<ol> <li>With increasing numbers of large grazing birds on agricultural grassland, conflict with farmers is rising. One management approach to alleviate conflict allows foraging on dedicated agricultural land (accommodation areas) and nature reserves, combined with scaring on remaining agricultural land. Here, we examine the cost-effectiveness of these measures by studying the influence on barnacle goose distribution and associated economic damage.</li> <li>We present an individual/agent-based model of barnacle geese (<em>Branta</em> <em>leucopsis</em>) foraging on grasslands in Fryslân, the Netherlands. The model is parameterized using field observations and GPS-tracks and allows simulation of management scenarios, differing in scaring probability and accommodation area size, with different potential management costs. </li> <li>Our model shows that, while yield loss decreases with higher scaring probabilities, costs of damage appraisal increase because geese graze on more fields. With small accommodation areas, achieving high scaring probabilities takes more effort and could result in goose population decline. Total management costs are lowest without scaring activity. </li> <li> <em>Synthesis and applications</em>: Considering costs of active scaring and the need to maintain the barnacle goose population in a favourable conservation status, our model suggests that the most cost-effective scenario is to prevent disturbance of geese. A high scaring probability could be beneficial if applied in small areas, for example around sensitive crops or airfields. Scaring in large areas could result in costs outweighing benefits and a declining barnacle goose population.</li> </ol>
Developing and Testing a Low Cost Opportunistic Glaucoma Screening Model by Non-physician Graders in Vietnam
ClinicalTrials.gov study NCT05151757. IPD Sharing: YES. Countries: 1. Publications: 17.
Data from: Cost-effectiveness of leveraging existing HIV primary health systems and community health workers for hypertension screening and treatment in Africa: An individual-based modelling study
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Long-term research and hierarchical models reveal consistent fitness costs of being the last egg in a clutch
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Data for: Modeling short-term energetic costs of sonar disturbance to cetaceans using high resolution foraging data
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Limiting scaring activities reduces economic costs associated with foraging barnacle geese: results from an individual-based model
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Dataset for Metabolic Cost Calculations of Gait using Musculoskeletal Energy Models, a Comparison Study
<p>This data set contains raw and processed data of gait analysis experiments of level and inclined walking at two speeds for 12 participants. The slopes were uphill and downhill with 8% incline. The raw data contains the output of the force plates and marker data, as well as raw measurements from an K4B2 system. Mat files are processed data: measured metabolic rate, and measured and calculated metabolic cost, as well as kinetic and kinematic data of an averaged gait cycle: joint angles, velocities and moments, ground reaction forces, muscle activation, contractile element length and stimulation, and the duration of the gait cycle.</p>
Data from: A new analytical approach to landscape genetic modeling: least-cost transect analysis and linear mixed models
Landscape genetics aims to assess the effect of the landscape on intraspecific genetic structure. To quantify interdeme landscape structure, landscape genetics mostly uses landscape resistance surfaces and least-cost paths or straight-line transects. However, both approaches have drawbacks. Parameterization of resistance surfaces is a subjective process, and least-cost paths represent a single migration route. A transect-based approach might oversimplify migration patterns by assuming rectilinear migration. To overcome these limitations, we combined these two methods in a new landscape genetic approach: least-cost transect analysis (LCTA). Habitat-matrix resistance surfaces were used to create least-cost paths, which were subsequently buffered to form transects in which the abundance of several landscape elements was quantified. To maintain objectivity, this analysis was repeated so that each landscape element was in turn regarded as migration habitat. The relationship between landscape predictor variables and genetic distances was then assessed following a mixed modeling approach to account for the non-independence of values in distance matrices. Subsequently, predictor variables were selected making use of the R_β^2 statistic. We applied LCTA and the mixed model approach to an empirical genetic dataset on the endangered damselfly, Coenagrion mercuriale. We compared the results to those obtained from traditional least-cost, effective and resistance distance analysis and showed that LCTA not only outperforms existing methods in a statistical way, but also provides more information about the migration ecology of the focal species. Although we believe the statistical approach to be an improvement for the analysis of distance matrices in landscape genetics, more stringent testing is needed.
Data from: Cost of reproduction in the Queensland fruit fly: Y-model vs. lethal protein hypothesis
The trade-off between lifespan and reproduction is commonly explained by differential allocation of limited resources. Recent research has shown that the ratio of protein to carbohydrate (P:C) of a fly's diet mediates the lifespan/reproduction trade-off, with higher P:C diets increasing egg production but decreasing lifespan. To test if this P:C effect is due to changing allocation strategies (Y-model hypothesis) or detrimental effects of protein ingestion on lifespan (lethal protein hypothesis), we measured lifespan and egg production in Queensland fruit flies varying in reproductive status (mated, virgin, and sterilized females, virgin males) that were fed one of 18 diets varying in protein and carbohydrate amounts. The Y-model predicts that for sterilized females and for males, which require little protein for reproduction, there will be no effect of P:C ratio on lifespan; the lethal protein hypothesis predicts that the effect of P:C ratio should be similar in all groups. In support of the lethal protein hypothesis, and counter to the Y model, the P:C ratio of the ingested diets had similar effects for all groups. We conclude that the trade-off between lifespan and reproduction is mediated by the detrimental side-effects of protein ingestion on lifespan.
Supplementary Material for "Cost-Efficient Construction of Performance Models"
<p><strong>Overview</strong></p> <p>The main contribution of the paper is a novel approach to ease the performance modeling process by introducing a pre-processing step that automatically determines performance-irrelevant configuration options and removes them from the remaining modeling process. We show that our identification process can accurately identify performance-irrelevant options using Pace3D, a multi-physics simulation, as case study. </p> <p>As Pace3D is proprietary software to which we are granted access to, we cannot provide an executable. Therefore, it is not possible to repeat measurements of the software. We do, however, provide our collected measurement data, including logs of our conducted experiments and inputs used, as well as performance models created. The measurement data can be used to reproduce the learning of models using DECART. Furthermore, the evaluation data shows the runtime difference between configurations. </p> <p>DECART is available for download here: https://github.com/jmguo/DECART/</p> <p><strong>Structure</strong></p> <p>- training-data: Input configurations and measurement data used for training models.<br>- models: DECART models.<br>- evaluation-data: Input configurations and measurement data for evaluating the models.<br>- questionnaire: Filled questionnare by the Pace3D developer.</p>
Compendium of R code and data for Mycenaean roads in the Peloponnese, Greece: least-cost path modelling using R and Movecost
<p><strong>Abstract</strong></p> <p><em>This study evaluates multiple methodologies and their variants for Least Cost Path (LCP) modelling, applied in combination with different Digital Elevation Models (DEMs), to explore the broader applicability of the Movecost package, using the Mycenaean road networks of the Peloponnese (Greece) as case studies. Using a geographic information system (GIS) and the R programming environment, this paper employs the Movecost package for the R statistical package to simulate ancient routes based on existing road segments. By integrating a variety of functions and parameters, this study evaluates their effectiveness across different DEMs, including both Shuttle Radar Topography Mission DEM (SRTM-DEM) and Copernicus DEM (COP-DEM) at 30 m spatial resolution. The study also examines how varying these parameters can lead to different modelling outcomes, underscoring the necessity of calibrating least-cost analysis to specific regional contexts. The road segments around Nichoria (Messenia), Ayios Ioannis Kazarma (Argolis), and in the Berbati Valley (Argolis), provide a historical canvas against which these methodological innovations are tested with the ultimate aim of exploring the capabilities of the Movecost package and how different combinations of DEM, function, parameter, and path points can effectively model the route through the existing road remains, highlighting the variability and context-specific nature of LCP modelling. The results suggest that the 'Wheeled-vehicle critical cost function' (WCS) was effective in modelling the roads through the extant remains based on start and endpoints suggested by previous research and posited by this paper. These results further suggest that Mycenaean roads likely served as key infrastructure links between major centres and ports or harbours, underscoring their role in facilitating regional trade and communication. However, this outcome represents one of several possible results, as the appropriateness of functions and the parameters tested depend on the specific landscape and archaeological context. This underscores the importance of careful parameter selection, providing insights into the economic and social landscapes of Mycenaean Greece, while also highlighting the potential of integrating spatial data with robust computational tools to enhance our understanding of ancient infrastructure.</em></p>
Data for "Simulating and analysing seabird flyways: an approach combining least-cost path modelling and machine learning"
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