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5,573 results for “optimality”
Systematic review for optimizing sample size in dairy cow methane emission studies: a comprehensive methodological approach
<p>Collection of research data focusing on methane (CH4) emissions from dairy cows across various breeds and conditions. The dataset encompasses a range of studies published from 2012 to 2023, each documented with specific parameters including the study title, authors, country of research, cow breed, lactation status, methods used for CH4 measurement, experimental designs, CH4 yield and its variability, dry matter intake, and diet composition.</p>
Simulation data for the manuscript "Characterizing Optimal Signal Propagation in the Human Brain Network."
<p>See <a href="https://github.com/kuffmode/OI-and-CMs">https://github.com/kuffmode/OI-and-CMs</a></p>
Programs and data used for Extracting latent variables from forecast ensembles and advancements in similarity metric utilizing optimal transport
<p>This is compiled from the program and output data using in Nishizawa (2024).</p> <p> </p> <p>Nishizawa, 2024: Extracting latent variables from forecast ensembles and advancements in similarity metric utilizing optimal transport. submitted to JGR: Machine Learning and Computation.</p>
Xenium Cloud Optimized Geotiff Test
<p>Test dataset for Cloud Optimized Geotiff</p>
Multi-objective particle swarm optimization and training of datasheet-based load dependent lithium-ion voltage models
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Data from: Optimal sampling interval for characterisation of the circadian rhythm of body temperature in homeothermic animals using periodogram and cosinor analysis
<p>Core body temperature (T<sub>c</sub>) is a critical aspect of homeostasis in birds and mammals and is increasingly used as a biomarker of the fitness of an animal to its environment. Periodogram and cosinor analysis can be used to estimate the characteristics of the circadian rhythm of T<sub>c</sub> from data obtained on loggers that have limited memory capacity and battery life. This data set contains five days of core body temperature, measured by loggers implanted into the abdominal cavity, in nine species of birds and mammals.</p>
Machine Learning Guided Optimization of Dynamic Peptide Organocatalysts
<p>Associated data for publication "<strong>Machine Learning Guided Optimization of Dynamic Peptide Organocatalysts". </strong>Full description of the dataset is in the SI of the associated manuscript. </p>
Modeling and optimization via ICNNs: A chiller-pump system application
<p>A data set for the paper "A bilevel fast-convergent optimizer via high-fidelity convex models: Application on optimal operation of all-parallel heterogeneous chiller-pump systems", including modeling data collected from BAS and optimization results</p>
Optimization of lung tissue pre-treatment by bead homogenization for subsequent culturomics
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Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization -- Reproducibility Files
<p>This repository contains the files to reproduce the results from the paper "Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization".</p> <p>Data Collection</p> <p>In this folder, all files used to generate the raw performance data for the set of algorithms are included, as well as the code used to generate the ELA features. For the performance, the packages 'ioh', 'nevergrad', 'modde' and 'modcma' are essential, while 'pflacco' is used for ELA. For all scripts in this folder, the number of parallel threads and the folders for reading function settings (included as 3 csv files in this folder) and storing data should be set before execution. </p> <p>Note that the full performance data exceeds 50GB, so it is not included in this repository. Instead, the results of processing it (using the aocc_extraction script) are included in the 'auc_MABBOB' folder (spread across multiple csv-files, with a version using a different budget factor included as well).</p> <p>The ELA data is included as 'ELA' and 'ELA_BBOB' for the affine combinations and component functions respectively. </p> <p>Data Processing, Analysis and Visualization</p> <p>The remaining reproducibility files can be found in the Reproducibility folder. Within this folder are several notebooks which handle various steps in the pipeline, starting with preprocessing the data collected in the previous steps. This results in some csv-files, which are also included for convenience. Afterwards, the remaining notebooks deal with correlation analysis, instance selection methods, and all included plots from the paper. To match the environment used during our execution of these scripts. a yml-file (to be used with conda or mamba) is available as well. </p>
A combination technique for optimal control problems constrained by random PDEs - numerical tests
<p>This dataset contains the codes used and data analyzed in the manuscript ``A combination technique for optimal control problems under uncertainty".</p> <p> </p>
XYZ files of geometry optimized structures of TTM-TTM by DFT
<p>XYZ files of calculated geometry optimized structures of <strong>TTM-TTM </strong>by DFT methods ((U)B3LYP-D3/def-SVP).</p> <p>For unconstrained (uncon) geometry optimizations the initial structures were extracted from a single crystal structure.</p> <p>For the constrained geometry opimizations (XCH23065 and XCH23116) only the positions of the hydrogen atoms were optimized within the crystal structure.</p>
Optimal forest management schemes and the corresponding forest biomass carbon sink projections in China
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Flexible Automation and Intelligent Manufacturing 2024, Taiwan - Optimization of Thermal Induction Welding Parameters in LPBFM for Enhanced Adhesion Control
<p>Laser powder bed fusion of metals (LPBFM) is an additive manufacturing process in which powdered alloy is selectively fused together to form near net shape parts. A method for qualifying a model to optimize thermal conduction welding parameters to omit lack of fusion defects is proposed. The approach takes into account: material, geometry and previously experimentally derived, robust process parameters.</p> <p><br>It entails carrying out specific experiments to generate data for calibration and validation of the model for fine-tuning of process parameters to compensate for the changing boundary conditions throughout the build. The objective is to achieve defined adhesion criteria for the meltpools of each laser scan vector.</p> <p><br>The method transforms the build job preparation of LPBFM into an optimization problem by determining the required precision and defining requirements for the model approach to be applicable on the shopfloor. The work contributes to a model-based quality assurance of LPBFM technology.</p>
Optimizing Artificial Intelligence (AI) Chatbot Customer Service in Small and Medium Enterprises (SMEs) in E-Marketplace
<p><span>The rise of advanced technologies, such as AI- driven chatbots, enables SMEs in e-marketplaces to provide responsive and efficient customer support, improve engagement, and streamline services. However, customers increasingly express concerns about AI-supported chatbot services, which affects their willingness to engage with these technologies. Consequently, this study aims to examine the factors<span> </span>that<span> </span>influence<span> </span>customers'<span> </span>behavioral<span> </span>intentions<span> </span>to<span> </span>use<span> </span>AI and their intentions for the continued use of AI-supported chatbots. Using a purposive sampling technique, the study collected data from 152 respondents through an online questionnaire. To analyze and predict the findings from the collected data, the study employed PLS-SEM as its statistical approach. The<span> </span>results<span> </span>indicate<span> </span>that<span> </span>information<span> </span>quality, system quality, and service quality significantly influence trust. Furthermore, service quality, perceived ease of use, confirmation of expectations, and perceived usefulness affect user satisfaction. Additionally, confirmation of expectations impacts perceived usefulness, and user satisfaction influences the behavioral intention to use AI chatbots. The findings also reveal that trust, user satisfaction, and perceived usefulness effectively enhance the intention to continue using AI-driven chatbots. However, information quality and system quality do not correlate with user satisfaction, and confirmation of expectations does not relate to<span> </span>user satisfaction. These findings contribute valuable insights to the existing literature on AI- driven chatbot services. Furthermore, stakeholders involved with AI-driven chatbot services for SMEs will gain an understanding<span> </span>of<span> </span>how<span> </span>to<span> </span>enhance<span> </span>user-friendly<span> </span>chatbot<span> </span><span>services.</span></span></p>
Rational design of optimal bimetallic and trimetallic nickel-based single-atom alloys for bio-oil upgrading toward hydrogen production
<p>Supplementary Data for the "Rational design of optimal <em>bimetallic</em> and <em>trimetallic</em> nickel-based single-atom alloys for bio-oil upgrading toward hydrogen production".</p>
MD simulations of water systems for On the Path to Optimal Alchemistry
<p>These are the water simulation files (input and output) for the article.</p>
DMSO-TMP-ACN-H2O Co-solvent Bayesian Optimization with Reproducibility and Gas Analysis via OEMS Data
<p>The zipped files contain the data collected and used for the Bayesian optimization (BO) of Coulombic efficiency (and discharge capacity) from the exploration of 4 co-solvents (dimethyl sulfoxide, trimethyl phosphate, acetonitrile, and water) and 2 salts (lithium perchlorate and LiTFSI).</p> <p>The cycling data and the BO clients are contained in BayesianOptimization.zip.</p> <p>The gas analysis data via online electrochemical mass spectrometry (OEMS) are contained in OEMS_data.zip.</p> <p>The cycling data of select repeats from the BO are contained in Reproducibility_data.zip.</p> <p>These are the raw datafiles. Preprocessing and analysis is not included.</p>
Optimization of the thermomechanical behaviour of TRC composites
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Optimizing heavy metal removal: A comparative analysis of Cd(II), Zn(II), and Pb(II) adsorption on tailored bulk and nanobiochars
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ScienceDex guides
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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.