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180 results for “optimal control”
Data used for ECAL 2015 paper "Optimal Mutation Rate Control under Selection in Hamming Spaces"
<p>This dataset contains the evolved mutation rate control functions, obtained by following the methods described in the following paper, from which the means and standard deviations shown in the paper were calculated.</p> <p>Paper: Optimal Mutation Rate Control under Selection in Hamming Spaces, accepted for publication in Advances in Artificial Life, ECAL 2015: Proceedings of the Thirteenth European Conference on the Synthesis and Simulation of Living Systems.</p>
Scalable Co-Optimization of Morphology and control in Embodied Machines
<p>Raw Data for: Scalable Co-Optimization of Morphology and control in Embodied Machines</p> <p>Trials from Nov 2, 2015 represent phase offset controllers for resolution 1000 (10^3), trails from Nov 9, 2015 represent phase offset controllers of resolution 125 (5^3), and trails from 2016 represent neural network controllers with resolutions 1000 (10^3). </p> <p>This data was produced by the code found at: https://github.com/ncheney/morphological-innovation-protection</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>
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>
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.
Optimal control derived sensitivity-enhanced CA-CO mixing sequences for MAS solid-state NMR. Applications in sequential protein backbone assignments.
<p>Raw data pulse sequences and shapes for publication</p> <p><br> ## SEQUENCES ##<br> ./sequences_renamed<br> Pulse programs introduiced in this work. Previous pulse programs can be obtained from https://doi.org/10.5281/zenodo.7016441 or https://optimal-nmr.net/experiments.html</p> <p>## SHAPES ##<br> ./shapes_renamed<br> TROP shaped pulses for homonuclear 13C-13C homonuclear mixing discussed in this work. Heteronuclear shaped pulses can be obtained from https://doi.org/10.5281/zenodo.7016441 or https://optimal-nmr.net/sequences.html</p> <p>## RAW DATA ##<br> to decrease storage demands 3D-processed spectra were deleted and can be recovered using TopSpin command: ftnd 0<br> TopSpin NUS licence is required for processing of the NUS-sampled data. Transformed data can be obtained from authors on request.</p> <p># U-13C,15N,2H,1HN-SH3 sample at 55 kHz MAS<br> ./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/1<br> 1H saturation recovery</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/2<br> 1H hard pulse calibraton</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/3<br> 15N hard pulse calibration</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/4<br> conventional hNH with rampCP optimalization</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/5<br> sensitivity-enhahced se-hNH with TROP optimalization</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/11<br> 2D conventional hNH with rampCP </p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/12<br> 2D sensitivtiy-enhanced se-hNH with TROP </p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/13<br> CO hard pulse and hCO CP calibration</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/14<br> CA hard pulse and hCA CP calibration</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/27<br> CACO homoTROP power optimalization in sensitivity-enhanced se-hCACOHN experiment</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/28<br> CACO INEPT delay optimalization in conventional hcoCAcoHN experiment</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/31 to 38<br> comparison of hCANH experiment efficiency using combination of coherence transfer methods (rampCP, tmSPICE and TROP) for CAN and NN transfer (see experiment tiles)</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/41 to 45<br> comparison of hCONH experiment efficiency using combination of coherence transfer methods (rampCP, tmSPICE and TROP) for CON and NN transfer (see experiment tiles)</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/57 and 58<br> optimalization of selective CA and CO 90 and 180 pulse</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/59<br> COCA INEPT delay optimalization in conventional hCOcaHN experiment</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/60<br> COCA homoTROP power optimalization in sensitivity-enhanced se-hCOCAHN experiment</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/69<br> conventional 3D hCANH experiment using tmSPICE CAN transfer; with water suppression after first CP, 15% non-uniform sampled</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/70<br> sensitivity-enhanced 3D se-hCANH experiment using TROP transfer; with water suppression after first CP, 15% non-uniform sampled</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/72<br> conventional 3D hCONH experiment using tmSPICE CON transfer; with water suppression after first CP, 15% non-uniform sampled</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/73<br> sensitivity-enhanced 3D se-hCONH experiment using TROP transfer; with water suppression after first CP, 15% non-uniform sampled</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/74<br> sensitivity-enhanced 3D se-hCAcoNH experiment using TROP transfer and homoTROP; with water suppression after first CP, 15% non-uniform sampled</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/75<br> conventional se-hcoCAcoNH experiment using tmSPICE CN transfer and INEPT ‘out-and-back’ coCAco transfer; with water suppression before NH transfer, 15% non-uniform sampled</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/76<br> sensitivity-enhanced 3D se-hCOcaNH experiment using TROP transfer and homoTROP; with water suppression after first CP, 15% non-uniform sampled</p> <p>./JB.1p3mm.20221122.sh3.2H13C15N100pcbackexch/77<br> conventional 3D hCOcaNH experiment using tmSPICE CN transfer and INEPT ‘complete forward’ COca; with water suppression after first CP, 15% non-uniform sampled</p> <p><br> # U-13C,15N glycine at 16.5 kHz MAS<br> ./MAS_COCa_seTesting/62<br> sensitivity-enhanced se-hCACO experiment with homoTROP pulse without diagonal-phase control</p> <p>./MAS_COCa_seTesting/63<br> sensitivity-enhanced se-hCOCA experiment with homoTROP pulse without diagonal-phase control</p> <p><br> # U-13C,15N-fMLF at 20 kHz MAS<br> ./jb.20211102_fMLF_3.2/2<br> 13C direct excitation spectra</p> <p>./jb.20211102_fMLF_3.2/3<br> 13C and 1H hard-pulse calibration and HC CP optimalization</p> <p>./jb.20211102_fMLF_3.2/4<br> 15N hard-pulse calibration and HC CP optimalization</p> <p>./jb.20211102_fMLF_3.2/5<br> NCA rampCP optimalization</p> <p>./jb.20211102_fMLF_3.2/6<br> NCO rampCP optimalization</p> <p>./jb.20211102_fMLF_3.2/79<br> sensitivity-enhanced se-hNCACO with TROP pulses</p> <p>./jb.20211102_fMLF_3.2/83<br> sensitivity-enhanced se-hNCOCA with TROP pulses</p> <p>./jb.20211102_fMLF_3.2/87<br> conventional hNCACO with rampCP and DREAM mixing</p> <p>./jb.20211102_fMLF_3.2/87<br> conventional hNCOCA with rampCP and DREAM mixing</p>
Data from: Hierarchical power control of a large-scale wind farm by using a data-driven optimization method
<p><span>With the participation in automatic generation control (AGC), a large-scale wind farm should distribute the real-time AGC signal to numerous wind turbines (WTs). This easily leads to an expensive computation for a high-quality dispatch scheme, especially considering the wake effect among WTs. To address this problem, a hierarchical power control (HPC) is constructed based on the geographical layout and electrical connection of all the WTs. Firstly, the real-time AGC signal of the whole wind farm is distributed to multiple decoupled groups in proportion of their regulation capacities. Secondly, the AGC signal of each group is distributed to multiple WTs via the data-driven surrogate-assisted optimization, which can dramatically reduce the computation time with a small number of time-consuming objective evaluations. Besides, a high-quality dispatch scheme can be acquired by the efficient local search based on the dynamic surrogate. The effectiveness of the proposed technique is thoroughly verified with different AGC signals under different wind speeds and directions.</span></p>
Microvascular Changes in OCT-angiography in Type 1 Diabetes Mellitus at the Onset of the Disease and After Optimization of Glycemic Control.
ClinicalTrials.gov study NCT04888598. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
DORADO-AC - Optimized Doses of Darusentan as Compared to an Active Control in Resistant Hypertension
ClinicalTrials.gov study NCT00389779. IPD Sharing: Not stated. Countries: 10. Publications: 1.
Improving Outcomes In Diabetic Patients During CABG Surgery By Optimizing Glycemic Control
ClinicalTrials.gov study NCT00460499. IPD Sharing: Not stated. Countries: 1. Publications: 2.
A Study of RO4917838 (Bitopertin) in Patients With Sub-optimally Controlled Symptoms of Schizophrenia (WN25305)
ClinicalTrials.gov study NCT01235559. IPD Sharing: Not stated. Countries: 7. Publications: 1.
Optimal Control of Liver Metastases From Colorectal Cancer With Cetuximab and Hepatic Artery Infusion of Chemotherapy
ClinicalTrials.gov study NCT00852228. IPD Sharing: Not stated. Countries: 4. Publications: 2.
The YourMove Study: Optimizing Individualized and Adaptive mHealth Interventions Via Control Systems Engineering Methods
ClinicalTrials.gov study NCT05598996. IPD Sharing: NO. Countries: 1. Publications: 2.
Optimal Dose of a Cognitive Control Training for Depression Vulnerability
ClinicalTrials.gov study NCT05166798. IPD Sharing: YES. Countries: 1. Publications: 2.
A Stepped Wedge Cluster Randomized Controlled Trial to Assess a Strategy Aiming to Optimize Psychosocial Outcomes in Patients With Cancer
ClinicalTrials.gov study NCT03008993. IPD Sharing: Not stated. Countries: 1. Publications: 2.
A Randomized Blinded Controlled Trial Assessing Hormonal Optimization: Late vs. Immediate Start After Discontinuation of Oral Contraceptives in Assisted Reproductive technologY (HOLIDAY)
ClinicalTrials.gov study NCT07225660. IPD Sharing: NO. Countries: 1. Publications: 16.
Optimized Glycemic Control in Heart Failure Patients With DM2:"Effect on Left Ventricular Function and Skeletal Muscle"
ClinicalTrials.gov study NCT01213784. IPD Sharing: Not stated. Countries: 1. Publications: 1.
The Effects of Febuxostat Dose Tapering in Gout Patients Optimally Controlled for 5 Years or More
ClinicalTrials.gov study NCT06622603. IPD Sharing: NO. Countries: 1. Publications: 20.
Closing the Loop in Adults With Sub-optimally Controlled Type 1 Diabetes Under Free Living Conditions
ClinicalTrials.gov study NCT01961622. IPD Sharing: Not stated. Countries: 3. Publications: 5.
SH T00186 Phase II/ III Optimal Drospirenone (DRSP) Dose Finding and Placebo-controlled Comparative Study
ClinicalTrials.gov study NCT00511797. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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.