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5,573
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5,573 results for “optimality”
Replication package for: Optimal Environmental Targeting in the Amazon Rainforest
<p>The package contains all the code necessary to replicate the figures and tables in Assuncao, J., McMillan, R., Murphy, J., and Souza-Rodrigues, E. (forthcoming). "Optimal Environmental Targeting in the Amazon Rainforest", Review of Economic Studies.</p>
Closed-loop optimization of general conditions for heteroaryl Suzuki coupling
<p>No description provided.</p>
Optimal Sacrificial Domains in Mechanical Polyproteins: S. epidermidis Adhesins Are Tuned for Work Dissipation
<p>Data underlying the figures in the publication: Liu, H. <em>et al</em>. “Optimal Sacrificial Domains in Mechanical Polyproteins: <em>S. epidermidis</em> Adhesins Are Tuned for Work Dissipation” <em>JACS Au</em> <strong>2022</strong> <em>2</em>, 1417-1427, <a href="https://doi.org/10.1021/jacsau.2c00121">https://doi.org/10.1021/jacsau.2c00121</a></p>
PortPy: Planning and Optimization for Radiation Therapy
<p>PortPy (<strong>P</strong>lanning and <strong>O</strong>ptimization for <strong>R</strong>adiation <strong>T</strong>herapy) is a community effort to develop an open source python library to facilitate the development and clinical translation of radiotherapy cancer treatment planning algorithms. PortPy includes:</p> <p>1. Research-ready data and code to promote <em>benchmarking</em>, <em>transparency</em>, <em>reproducibility </em>and <em>community</em>-<em>driven </em>development</p> <p>2. Interface to an open-source optimization package <a href="https://www.cvxpy.org/">CVXPy</a> for easy/quick prototyping and out-of-the-box access to commercial/open-source optimization engines (e.g., Mosek, Gorubi, CPLEX, IPOPT)</p> <p>3. Visualization modules to visualize relevant plan information (e.g, dose volume histograms, dose distribution, fluence map)</p> <p>4. Evaluation modules to quantify plan quality with respect to established clinical metrics (e.g., RTOG metrics, dose conformality, tumor control probability, normal tissue control probability)</p> <p>Data needed for optimization and algorithm development (e.g., a set of beams/beamlets/voxels, dose contribution of each beamlet to each voxel) are provided for a set of pre-specified machine parameters (e.g., beam/colimator/couch angles). We initially provide these data for a set of publicly available dataset from TCIA. We hope to expand our dataset in the future. The data needed for optimization is extracted from the research version of Eclipse<sup>TM</sup> treatment planning system (<a href="https://www.varian.com/">Varian Medical Systems</a>) using its API.</p>
Simulation input files and analysis scripts for "Optimal bond-constraint topology for molecular dynamics simulations of cholesterol"
<p>Simulation input files and analysis scripts for "Optimal bond-constraint topology for molecular dynamics simulations of cholesterol".</p> <p>See ... for details.</p>
Terror Bird NHMW - Optimized OBJ
This 3D model is a repost of [this data](https://sketchfab.com/3d-models/terror-bird-nhmw-geo-201200070001-5847cc0ce8584b26a40056491bc618ca) published by the [Naturhistorisches Museum Wien](https://sketchfab.com/NHMWien), optimized for AR / VR using [rapidcompact.com](https://rapidcompact.com/). 993.6k faces > 30k (97% reduction!). > This model can be found in Hall 9 at the Natural History Museum of Vienna. > > Specimen: Paraphysorins brasiliensis (Alvarenga, 1982) > > Inventory number: NHMW-Geo 2012/0007/0001 > Collection: Natural History Museum Vienna, Geology and Paleontology Department, Vertebrate Collection (curator: Ursula Göhlich) > > Find out more about the NHM Vienna [here](http://www.nhm-wien.ac.at/en). > Scanned and edited by Nikola Brodtmann, Anna Haider, Viola Winkler (NHMW) > > Scanner: Artec Leo. Infrastructure funded by the FFG. Source: Objaverse 1.0 / Sketchfab
Bronze Bowl, Jebel al-Buhai - Optimized
Bronze Bowl, Jebel al-Buhais, Sharjah, UAE. Bronze Age, Umm an Nar. (Córdoba 2016:51, Figure 10). Catalogue No. EXS 48 402 photos. Completely processed (aligned, scaled, modeled, cleaned, simplified, unwrapped, textured, meshed) in Reality Capture. J. Mª Córdoba 2016. Horizontes de la Edad del Bronce (3000-1300 a. C.). Pp. 37-64. In EN LOS CONFINES DE ORIENTE PRÓXIMO: El hallazgo moderno del país de Magán. Museo Arqueológico Nacional Catálogo de la Exposición Temporal Celebrada entre el 18 de abril y el 29 de mayo de 2016. Comisario: J. Mª Córdoba Zoilo. Comisarias adjuntas: C. del Cerro Linares, Mª C. Pérez Díe, E. Pons Mellado. Source: Objaverse 1.0 / Sketchfab
Dataset for publication 'Reconnecting Stochastic Methods with Hydrogeological Applications: Uncertainty Analysis and Risk Assessment for the Design of Optimal Monitoring Networks'
<p>This dataset includes all data and information on how to reproduce the results and the figures of the paper 'Reconnecting Stochastic Methods with Hydrogeological Applications: Uncertainty Analysis and Risk Assessment for the Design of Optimal Monitoring Networks'.</p>
Driving Traffic to Institutional Repositories: How Search Engine Optimization can Increase the Number of Downloads from IR
<p>The success of institutional repositories (IR) is measured in large part by the number of file downloads they sustain. Most traffic to IR is referred by Internet search engines, but referrals are hindered when IR are not properly optimized for search engine harvesting and indexing, leading to low visitation and downloads. This presentation will discuss search engine optimization techniques, especially for Google Scholar, which can be responsible for the majority of referrals that result in IR file downloads. The presentation will also introduce a new web service called RAMP (Repository Analytics & Metrics Portal) that accurately counts file downloads from IR and requires no installation or training.</p>
Supplementary Material for the Paper "Optimizing Workday Planning Based on Time and Productivity Constraints"
<p>This repository contains the (anonymized) supplementary material for our paper. This includes the survey questions we asked, as well as a video and screenshots of DayO.</p> <p><strong>Abstract</strong>: Planning one’s workday was shown to be positively related to increased control of time, work and life satisfaction, and<br> performance. However, planning for an efficient workday is challenging, due to the high complexity of tasks that knowledge<br> workers have to perform and the many constraints that influence their plan. Few planning tools actively support users with the task scheduling process, but they do not take into account these time and productivity constraints. Hence, we have devised an automated task scheduling approach that recommends an optimized workday plan, by considering constraints such as task characteristics (e.g., difficulty, deadline, importance), scheduled appointments, the current stress level and sleep quality from the previous night. A preliminary analysis of the approach, using DayO as a technology probe in situ, showed that participants found the idea<br> very promising, but a real-world application would additionally require further support to reduce the cognitive burden of planning and would let users to adapt their schedules interactively, when constraints change throughout a workday.</p>
Dataset for the paper "Ensemble optimization retrieval algorithm of hydrometeor profiles for the Ice Cloud Imager submillimeter-wave radiometer'
<p>1. "Retrieval_Database" file contains the pre-calculated retrieval database.</p> <p>2. "Algorithm_Input" file contains the input of the ensemble optimization retrieval algorithm.</p> <p>3. "TrueProfiles" file contains the true profiles corresponding to the input brightness temperatures. </p> <p>4. "Algorithm_Output" file contains the output of the ensemble optimization retrieval algorithm.</p>
Quantum Optimization for the Maximum Cut Problem on a Superconducting Quantum Computer
<p>The dataset includes maximum cut problem instances on 3-regular graphs, the cut number returned by the experimental runs of the greedy-enhanced quantum relax-and-round algorithm, and the estimated optimal cut number used for computing the approximation ratio from the paper <em>Benchmarking Quantum Optimization for the Maximum-Cut Problem on a Superconducting Quantum Computer</em> [<a href="https://arxiv.org/abs/2404.17579">https://arxiv.org/abs/2404.17579</a>]</p>
SEM of Recycled Carbon Fibers (T700) with pyro-gasification optimized process
Open the record for dataset details and reuse information.
A mathematical model of COVID-19 with multiple variants of the virus under optimal control in Ghana
Open the record for dataset details and reuse information.
Full optimization of DNP on a 1 T benchtop polarizer with hyperpolarizing solids
<p>The data folder contains the raw NMR and EPR data used in the manuscript to benchmark the DNP performance of different hyperpolarizing solids containing various nitroxide radical loadings compared against the DNP performance of varying nitroxide concentrations (10-100 mM) solvated in a glassy frozen solution. </p> <p>The NMR data is formatted in a pseudo-3d data Bruker format. The EPR data is formated in a text file.</p> <p>The code folder contains the script to process the pseudo-3d data to extract the DNP parameters. The code folder also contains the script to estimate the lineshape of the DNP spectra in the solid effect and cross effect case using the EPR data as input. </p>
MATLAB Implementation for Wind Turbine Prognosis Using Uncertainty Bayesian-Optimized Lightweight Neural Network
<p>These MATLAB codes accompany the paper titled "---," currently submitted to the 11th International Electronic Conference on Sensors and Applications (ECSA-11). The paper presents a novel approach to wind turbine prognosis for maintenance purposes using the Uncertainty Bayesian-Optimized Extreme Learning Machine (UBO-ELM) algorithm.</p> <p>The codes provided here implement the methodology described in the paper, including data preprocessing, model training and evaluation, uncertainty quantification, and visualization of results. These codes are intended for researchers and practitioners in the field of wind energy systems and predictive maintenance.</p> <p>Please note that the paper is currently under review at ECSA-11. Once the paper is approved and the embargo is lifted, these codes will be accessible openly. Users are kindly requested to cite our paper when utilizing these codes for their research.</p>
Electronic Companion - Accelerated Benders Decomposition for Enhanced Co-Optimized T&D System Planning
<p>This release is associated with a paper entitled "Accelerated Benders Decomposition for Enhanced Co-Optimized T&D System Planning".</p> <p>In this document, we include information regarding the physical parameters of the transmission and distribution power systems adopted to present the results shown in the paper. Additionally, data regarding investment and operative costs, as well as the scenarios used to describe the uncertainty of renewable-based generation availability and demand, are provided in this document.</p>
Influence of Nuclear Investment Costs and Baseload Demand on the Optimal Energy Mix
<p>Results from the study on "Influence of Nuclear Investment Costs and Baseload Demand on the Optimal Energy Mix".</p>
Data used for analysis in "Calibrating tropical forest coexistence in ecosystem demography models using multi-objective optimization through population-based parallel surrogate search"
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Data and code for paper: Design Optimization of Geometric-Confined Cardiac Organoids Enabled by Machine Learning Techniques
<p>Collection of the code for the generation of figures, analysis and data for the paper: <strong>Design Optimization of Geometric-Confined Cardiac Organoids Enabled by Machine Learning Techniques.</strong></p> <p>Ensemble learning classifiers, PACMAP & Trimap code in python file. All figures and additional analysis in R code. </p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.