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5,573 results for “Optimality”
Figure 10 Optimal matrices for functions f1 (a), f2 (b), and f3 (c)-SELECTING OPERATIONS FOR ASSEMBLER ENCODING
<p>In the experiments, the following sets of operations were tested (a description of all<br> the operations specified below is presented in Appendix 1):<br> • Set 1 (all four-parameter operations used during the research reported in [15,17]):<br> CHG, CHGC0, CHGC1, CHGC2, CHGC3, CHGC4, CHGR0, CHGR1,<br> CHGR2, CHGR3, CHGR4, CHGM0, CHGM1, CHGM2, JMP;<br> • Set 2 (the most effective four-parameter operations used in the previous research):<br> CHGC0, CHGC3, CHGR0, CHGR3, CHGM0, CHGM2, JMP;<br> • Set 3: simpler variants of operations included in Set 1, the simpler operations, unlike<br> their more complex counterparts, always changed either the whole column or the<br> whole row or the whole matrix, operations from this set had maximally three<br> parameters;<br> • Set 4 (the three-parameter operations and jumps): CHG_VALUE, CHG_MEMORY,<br> JMP.</p>
Figure 2: Optimization in natural ants collective behavior: foraging and clustering (from [8])-Self-organization and social insects algorithms
<p>On figure 2, two examples of self-organization in natural ants are presented.<br> On the left side, the well-known Deneubourg experiment consists to highlight<br> with a very simple device the ant foraging problem. The ant objectives is<br> to find the optimal way from nest to food source, using pheromone trail deposition.<br> On the right side, cemetery clustering formation are shown at 4<br> successive times: ants form piles of corpses to clean their nests. Each of them<br> has elementary actions, unknowing the whole situation, but dealing only with<br> local information. There is no supervisor to lead the piles formation which<br> emerges from ant interactions.</p>
РИС. 11. ИЗображениЯ крючков глохидиев при раЗной настройке Яркости и контрастности (Anemina arcaeformis, р. Сита, Хабаровский кр.). А. Оптимальные Яркость и контрастность. В. ИЗбыточнаЯ контрастность. С. ИЗбыточнаЯ Яркость. МасШтаб 20 мкм. Микроскоп Zeiss EVO 40, напыление углеродом. FIG. 11. Imagines of glochidia hooks with different brightness and contrast value (Anemina arcaeformis, Sita River, Khabarovsk Krai). A. Optimal brightness and contrast. B. Excessive contrast. C. Excessive brightness. Scale bars 20 μm. Zeiss EVO 40 microscope, sputter coating with carbon. in Методика подготовки раковин глохидиев (Bivalvia, Unionidae) длЯ работы на сканируюЩем Электронном микроскопе
РИС. 11. ИЗображениЯ крючков глохидиев при раЗной настройке Яркости и контрастности (Anemina arcaeformis, р. Сита, Хабаровский кр.). А. Оптимальные Яркость и контрастность. В. ИЗбыточнаЯ контрастность. С. ИЗбыточнаЯ Яркость. МасШтаб 20 мкм. Микроскоп Zeiss EVO 40, напыление углеродом. FIG. 11. Imagines of glochidia hooks with different brightness and contrast value (Anemina arcaeformis, Sita River, Khabarovsk Krai). A. Optimal brightness and contrast. B. Excessive contrast. C. Excessive brightness. Scale bars 20 μm. Zeiss EVO 40 microscope, sputter coating with carbon.
AiNU data for Physics-based material parameters extraction from perovskite experiments via Bayesian optimization
<p>This file contains the AiNU data used for the article entitled by <em>Physics-based material parameters extraction from perovskite experiments via Bayesian optimization</em> (https://arxiv.org/abs/2402.11101).</p>
Optimized summary-statistic-based single-cell meta-analysis. Input files
<p>This dataset contains information about the input files used in the Optimized summary-statistic-based single-cell meta-analysis research project. </p> <p> </p>
Data and codes from "Daniel et al. What can optimized cost distances based on genetic distances offer? A simulation study on the use and misuse of ResistanceGA"
<p><span>Data and codes used for </span><span>“Daniel et al. What can optimized cost distances based on genetic distances offer? A simulation study on the use and misuse of ResistanceGA”</span></p>
Optimizing the design of a bioabsorbable metal stent using computer simulation methods: Supporting Data
<p>Data including UMATs and Abaqus input files related to the paper 'Optimizing the design of a bioabsorbable metal stent using computer simulation methods' <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.biomaterials.2013.07.010" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.biomaterials.2013.07.010</span></a></p> <p> </p>
Supplementary material for the paper: "One-shot procedures for efficient minimum compliance topology optimization"
<p>MATLAB codes and results used in the article: "One-shot procedures for efficient minimum compliance topology optimization", published in Structural and Multidisciplinary Optimization, 2024.</p>
cis/trans isomeric 1,6-Diphenylhexatrienes (DPH) optimized structures.
<p>Optimized structures and frequencies in the ground and first excited state for the six possible isomers of 1,6-Diphenylhexatriene (DPH) optimized at PBE0/def2TZVP level of theory with Gaussian16. </p> <p>all-trans - ttt</p> <p>B - tct</p> <p>C - ctt</p> <p>D - cct</p> <p>E - ctc</p> <p>F - ccc</p>
Dataset for an article "Numerical and Experimental Evaluation of Structured Material for Use in Multi-scale Topology Optimization"
<p><span>The dataset contains data from compression mechanical testing of 6 basic truss-based lattice cells with relative density between 0.3 and 0.7 in two directions (parallel and perpendicular to build direction). Additionally, the dataset contains simulation of the experiments by finite element method. Due to a big difference between results from experiment and simulation with nominal material model, parametric material model with Young's modulus set as parameter was used. Resulting Young's moduli that correspond with the experiments are also included. Details can be found in the article: “Numerical and Experimental Evaluation of Structured Material for Use in Multi-scale Topology Optimization”.</span></p>
Sparsity-constrained wavefront optimization by leveraging complex media
<div> <div>Wavefront shaping gains increasing importance in complex photonics, which can manipulate light spatially and temporally to counter the scattering effect. Important applications include deep-tissue imaging, microendoscopy, optical communications, nanofabrication, and remote sensing. However, high-speed and high-fidelity wavefront shaping is fundamentally hindered by the dimensionality limitation of hardware devices, evinced by the competition between the frame rate, pixel count, and modulation depth. To overcome the speed-fidelity tradeoff, we leverage complex media (e.g., diffusers or multimode fibers) as analogue random multiplexers for pattern compression to address the demand for high-dimensional spatiotemporal control. Sparsity-constrained wavefront optimization is designed to solve the problem by seeking a low-dimensional, robust representation of wavefronts with a carefully designed sparsity constraint. This optimization framework can achieve high-fidelity wavefront shaping through complex media using high-speed, yet relatively low-precision spatial light modulation devices (e.g., digital micromirror devices) without compromising the frame rate.</div> </div>
Supplementary material for the paper: "Mesh-based topology, shape and sizing optimization of ribbed plates"
<p>Source code and results, accompanying the paper "Mesh-based topology, shape and sizing optimization of ribbed plates", published in Structural and Multidisciplinary Optimization, 2024. </p>
Comparing long-term power sector pathways in Viet Nam: a simple cost-optimization approach with OSeMOSYS
<p>Six clicSAND files for OSeMOSYS Modelling in Viet Nam. The six files depict six different scenarios:</p> <p>1. Power Development Plan 7-based scenario</p> <p>2. Power Development Plan 8-based scenario</p> <p>3. Renewable Energy Development Strategy-based scenario</p> <p>4. Renewables-Led Pathway-based scenario</p> <p>5. Net Zero</p> <p>6. Clean Efficient Transition</p> <p>The Reference Energy System (RES) is also included to represent the relationship between estimated energy demands, energy conversion technologies, fuel mixes, and the resources required to satisfy the demands in the study.</p>
Figure 4 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases
Figure 4. Identification of PCR inhibitors in 18 biological samples positive for Aspergillus. Graph A: Ct values obtained from pure and diluted DNA samples (dilution rate 1/20). Graph B: Ct values obtained with 20 copies of a plasmid DNA systematically added to the same biological samples (undiluted and diluted) and a negative control sample (NC).
Figure 2 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases
Figure 2. Influence of proteinase K digestion (56 °C overnight) on DNA extraction. Graph A shows the Ct values obtained by quantifying THP1 cell DNA derived from direct extraction with the NucliSENS easyMAG system and extraction performed on the same quantity of cells following overnight (ON) digestion with Proteinase K. Graph B shows Leishmania quantification after extraction with the NucliSENS easyMAG system both with and without PK and quantification after extraction using a QIAamp DNA Mini kit after ON digestion with PK.
Figure 7 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases
Figure 7. Variation of the ratio between kinetoplastic DNA and nuclear DNA extraction with various Leishmania quantities in the presence of 103 THP1 cells.
Figure 5 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases
Figure 5. Yield of DNA extraction from Leishmania and THP1 cells using the NucliSENS easyMAG system.
Figure 3 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases
Figure 3. Results of the extraction experiments performed on yeast (Candida albicans) and filamentous fungi (Aspergillus fumigatus). A presents the kinetics of the extraction process after vortexing and glass-bead treatment. B shows the differences in DNA quantity obtained from fungal cells using the FastPrep system (with) compared to the same process without grinding.
Figure 6 in Application of the NucliSENS easyMAG system for nucleic acid extraction: optimization of DNA extraction for molecular diagnosis of parasitic and fungal diseases
Figure 6. Influence of the quantity of human cells (THP1 cells) on Leishmania quantification at various concentrations of host cells and parasites.
Figure 1 in Crop physiological considerations for combining variable-density planting to optimize seed costs and weed suppression
Figure 1. Schematic representation of (A) an aerial image using an unmanned aerial vehicle (UAV) to scout fields in year 1, (B) detection of areas of high (orange) and low (yellow) weed density in year 1, and (C) implementation of year 1 weed maps to calibrate precision planter to plant in high (red) and low (green) crop densities in year 2.
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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.