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127 results for “optimization methods”
DIRECTLib - a library of global optimization problems for DIRECT-type methods
<p><strong>DIRECTLib - a library of a box and generally-constrained global optimization problems for DIRECT-type methods</strong></p> <p>In this library, we present an extended collection of a box and generally constrained global optimization test problems (in MATLAB format) typically used in benchmarking various DIRECT-type [1] methods in the relevant literature (see, e.g., [2-6] and references given therein).</p> <p>File: <strong>WCGO_Test_results.xlsx </strong>contains<strong> </strong>experimental results presented in: <a href="https://arxiv.org/abs/2109.14912">https://arxiv.org/abs/2109.14912</a></p> <p><strong>References</strong></p> <ol> <li>Jones, D. R., Perttunen, C. D. and Stuckman, B. E. (1993) ‘Lipschitzian optimization without the Lipschitz constant’, <em>Journal of Optimization Theory and Applications</em>, 79(1), pp. 157–181. <strong>doi</strong><strong>: 10.1007/BF00941892</strong>.</li> <li> <p>R. Paulavičius, J. Žilinskas. (2014) Simplicial Global Optimization, SpringerBriefs in Optimization, Springer New York, New York, NY. <strong>doi:10.1007/978-1-4614-9093-7</strong></p> </li> <li> <p>L. Stripinis, R. Paulavičius, J. Žilinskas. (2018) Improved scheme for selection of potentially optimal hyper-rectangles in DIRECT, Optimization Letters 12 (7) 1699–1712. <strong>doi:10.1007/s11590-017-1228-4</strong></p> </li> <li> <p>L. Stripinis, R. Paulavičius, J. Žilinskas. (2019) Penalty functions and two-step selection procedure based DIRECT-type algorithm for constrained global optimization, Structural and Multidisciplinary Optimization 59 (6) 2155–2175. <strong>doi:10.1007/s00158-018-2181-2</strong>.</p> </li> <li> <p>L. Stripinis, J. Žilinskas, L. G. Casado, R. Paulavičius (2021) On MATLAB experience in accelerating DIRECT-GLce algorithm for constrained global optimization through dynamic data structures and parallelization. <em>Applied Mathematics and Computation</em>, <a href="https://doi.org/10.1016/j.amc.2020.125596">DOI: 10.1016/j.amc.2020.125596</a></p> </li> <li> <p>L. Stripinis, R. Paulavičius (2021) A new DIRECT-GLh algorithm for global optimization with hidden constraints. <em>Optimization Letters</em>, 15, p. 1865-1884, <a href="https://doi.org/10.1007/s11590-021-01726-z">DOI: 10.1007/s11590-021-01726-z</a></p> </li> </ol>
Butcher's tableaux of the optimized explicit Runge-Kutta schemes for high-order collocated discontinuous Galerkin methods for compressible fluid dynamics
<p>This folder contains the Butcher's tableaux of the optimized explicit Runge-Kutta schemes for high-order collocated discontinuous Galerkin methods for compressible fluid dynamics presented in Al Jahdali et al., "Optimized explicit Runge--Kutta schemes for high-order collocated discontinuous Galerkin methods for compressible fluid dynamics," Computers & Mathematics with Applications, 2022.</p> <p>Specifically,</p> <p><a href="https://zenodo.org/api/files/754318a5-0881-4252-9059-086da4607b49/Butcher_coefficients_ADV.txt">Butcher_coefficients_ADV.txt</a> contains the Butcher's tableaux of the explicit Runge-Kutta schemes optimized using the spectra of the 2D advection equation.</p> <p><a href="https://zenodo.org/api/files/754318a5-0881-4252-9059-086da4607b49/Butcher_coefficients_IEV.txt">Butcher_coefficients_IEV.txt</a> contains the Butcher's tableaux of the explicit Runge-Kutta schemes optimized using the spectra of the isentropic vortex propagation for the compressible Euler equations.</p> <p> </p> <p> </p> <p> </p>
EPTGODD-WHU: Ensemble Precipitation and Temperature from CMIP6 GCMs optimized by OLS-DT-DNN methods integration (1850-2100)
<p>This monthly global climate dataset EPTGODD-WHU (precipitation and mean temperature variables with grid size of 0.5°×0.5°) was ensembled from 16 selected CMIP6 GCMs. The published dataset was optimized by OLS (Ordinary Linear Square)-DT (Decision Tree)-DNN (Deep Neural Network) methods integration. The CF (Climate and Forecast) v1.6 was employed as the guideline for NetCDF4 format. The periods of temperature files can be divided into historical (1850-1900) and future (2015-2100) periods. For precipitation, this product provides future (2015-2100) period. Three future scenarios (SSP1-2.6, SSP2-4.5 and SSP5-8.5) were selected for both variables. The units of this dataset are degrees Celsius and mm/month for temperature and precipitation, respectively. Each NetCDF4 file in this dataset includes three dimensions (time, latitude (-89.75°N to 89.75°N) and longitude (-179.75°E to 179.75°E)).</p>
Optimizing sampling across methods improves the power of ecological monitoring data
Transect-based monitoring has long been a valuable tool in ecosystem monitoring. These transects are often used to measure multiple ecosystem attributes. The line-point intercept (LPI), vegetation height, and canopy gap intercept methods comprise a set of core methods, which provide indicators of ecosystem condition. However, users struggle to design a sampling strategy that optimizes the ability to detect ecological change using transect-based methods. We assessed the sensitivity of these core methods on a one-hectare plot to transect length, number, and sampling interval to determine: 1) minimum sampling required to describe ecosystem characteristics and detect change for each method and 2) optimal transect length and number for all three methods to make recommendations for future analyses and monitoring efforts. We used data from 13 National Wind Erosion Research Network locations spanning the western US, which included 151 measurements over time across five biomes. We found that longer and increased numbers of transects were more important for reducing sampling error than increased sample intensity along transects. For all methods and indicators across plots, three 100-m transects reduced sampling error so that indicator estimates fall within an 95% confidence interval of +/- 5% for canopy gap intercept and LPI-total foliar cover, +/- 5 cm for height and +/- two species for LPI-species counts. For the same criteria at 80% confidence intervals, two 100-m transects are needed. Site-scale inference was strongly affected by sample design, consequently our understanding of ecological dynamics may be influenced by sampling decisions.
The Set Increment with Limited Views Encoding Ratio (SILVER) Method for Optimizing Radial Sampling of Dynamic MRI: Supporting Data
<p>This data was created to perform the first experiments with the SILVER method of optimizing radial MRI acquisition. The files are mainly .mat files containing the numerical data used to assess the SILVER method using MATLAB (Version R2018b). Instructions on how to use the data and how to reproduce the experiments are available on https://github.com/SophieSchau/SILVER</p>
Dataset of Optimization Methods for Model-Implemented Fault Injection in Cyber-Physical Systems: A Systematic Literature Review
<p>Data set for the paper entitled “<strong>Optimization Methods for Model-Implemented Fault Injection in Cyber-Physical Systems: a Systematic Literature Review</strong>”</p> <p>In this repo, we have some pictures and Excel files.</p> <ul> <li>Pictures are screenshots from the Parsifal tool (https://parsif.al/) which we use for performing the SLR.</li> <li>Excel files are as follows:</li> </ul> <table style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 21.8789%;"><col style="width: 78.1211%;"></colgroup> <tbody> <tr> <td><strong>Excel’s file name</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>Keyword_analysis </td> <td>In this file, you can see the evolution of our keyword selection.</td> </tr> <tr> <td>Articles_InclusionExclusion_QA </td> <td>In this file, you can find all found papers until Feb. 27, 2025. In the last column of this excel file, we can see the status of each paper, if it has been included, or excluded by authors. For the included paper (their status is “Accepted”) you can see their quality score in the last column.</td> </tr> <tr> <td>Extracted_data </td> <td>In this file, we logged the result of data extraction from qualified paper. In the first sheet “Articles”, you can see a list of the read papers with corresponding data. Other sheets in this Excel file are driven from the “Article” sheet for data visualization. So, they are not important.</td> </tr> </tbody> </table> <p> <br>If you have any questions, you can read the corresponding paper and contact the authors.</p>
Effective seed sterilization methods require optimization across maize genotypes
<p>Studies of plant-microbe interactions using synthetic microbial communities (SynComs) often require the removal of seed-associated microbes by seed sterilization before inoculation to provide gnotobiotic growth conditions. A diversity of seed sterilization protocols have been developed in the past and have been used on different plant species with various amounts of validation. From these studies, it has become clear that each plant species requires its own optimized sterilization protocol. It has, however, so far not been tested if the same protocol works equally well for different varieties and seed sources of one plant species. We evaluated six seed sterilization protocols on two different varieties (Sugar Bun & B73) of maize. All unsterilized maize seeds showed fungal growth upon germination on filter paper, highlighting the need for a sterilization protocol. A short sterilization protocol with hypochlorite and ethanol was sufficient to prevent fungal growth on Sugar Bun germinants, however, a longer protocol with heat treatment and germination in fungicide was needed to obtain clean B73 germinants. This difference may have arisen from the effect of either genotype or seed source. We then tested the protocol that performed best for B73 on three additional maize genotypes from four sources. Seed germination rates and fungal contamination levels varied widely by genotype and geographic source of seeds. Our study shows that consideration of both variety and seed source is important when optimizing sterilization protocols and highlights the importance of including seed source information in plant-microbe interaction studies that use sterilized seeds.</p>
Data from: AgMate: an optimal mating software versus other mate pair designing methods on long-term breeding of Pinus taeda L
<p>Breeding objectives aim to optimize two crucial but contrasting goals of maximizing genetic gain while managing genetic diversity. In advanced generations, this becomes a challenge in monoecious conifer tree species breeding programs because they suffer from inbreeding. Developing an algorithm that maximizes genetic gain while maintaining genetic diversity for monoecious species is imperative. While methods and algorithms for animal breeding are well-established, an efficient algorithm suited to monoecious species remains elusive. Towards this goal, we have adopted an evolutionary genetic algorithm, the Differential Evolution algorithm, to optimize mate pair designing in <em>Pinus taeda</em> (loblolly pine), a widely planted pine species in the southern USA. AgMate, an optimal mating for monoecious species software, is a multi-functional, completely automated optimization software. It utilizes genetic relationships and breeding values as input to create an optimal mating list. AgMate maximizes the genetic gain and minimizes the increase in average coancestry and inbreeding in the proposed progeny. AgMate was more effective in optimizing mating lists than positive assortative mating and random mating in short-term and long-term settings. AgMate mating list resulted in an average 93% genetic gain each cycle for ten cycles while simultaneously minimizing the increase in coancestry to 0.086. The framework and methods adapted for Pinus taeda are also relevant to the breeding of other monoecious species.</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>
Figure 6. (a1), (a2), (a3), (a4), (a5), (a6), (a7) and (a8) watermarked image is degraded respectively through JPEG2000 compression, JPEG compression, median filtering, adding Salt&Pepper noise, rotating, center cropping, surrounding cropping and scaling. (b1), (b2), (b3), (b4), (b5), (b6), (b7) and (b8) The corresponding extracted watermarks.-Discrete Wavelet Transform Method: A New Optimized Robust Digital Image Watermarking Scheme
<p>This paper has described a scheme for digital watermarking of still images based on discrete<br> wavelet transform. In the proposed method, the embedded logo watermark can be extracted without<br> access to the original image. It has been confirmed that the proposed watermarking method is able<br> to extract the embedded logo watermark from the watermarked images that have degraded through<br> compression, filtering, cropping and scaling. Although this algorithm is not robust against rotation,<br> it can completely extract the watermark from watermarked images that lose about 35% of their<br> areas by cropping attack.</p>
Figure 1. (a) Original watermark (b) extracted watermarks after compression(c) merged watermark-Discrete Wavelet Transform Method: A New Optimized Robust Digital Image Watermarking Scheme
<p>Therefore, each bit of the logo watermark is stored in one coefficient of a sub-block to keep<br> the capacity of watermarking fixed.<br> When a region of the watermarked image is destroyed; the whole watermark can be<br> extracted using other regions of the watermarked image by merging extracted watermarks. Figure 1<br> shows result of merging logo watermarks that were extracted from a compressed (with JPEG2000<br> algorithm) watermarked image.</p>
Figure 4. (a) The original "Hookah" image (b) Watermarked "Hookah" with Q=35 (c) The original "Baby" image (d) Watermarked "Baby" with Q=35-Discrete Wavelet Transform Method: A New Optimized Robust Digital Image Watermarking Scheme
<p>A set of distortions is applied to the watermarked image and the watermark is extracted from<br> the distorted image. We used bit correct rate (BCR) to evaluate our proposed algorithm and it is<br> calculated from the following equation [6].</p>
Figure 2. LL2 sub-band is divided into sub-block-Discrete Wavelet Transform Method: A New Optimized Robust Digital Image Watermarking Scheme
<p>In the following experiments, two gray-level images with size of 512 by 512, “Baby” and<br> “Hookah” are the test images. The binary image “IAU” with size of 32 by 32 is used in our<br> simulations as a watermark. Figure 3 shows the watermark. In the experiments Haar wavelet filter<br> was used for discrete wavelet transform. The level of wavelet decomposition (n) and the number of<br> sub-blocks (K) were also assumed to be 2 and 16 respectively.<br> The proposed watermarking algorithm is evaluated from the point view of embedded<br> watermark transparency and robustness; the result of each is shown in next two sections.</p>
Test data set for macros accompanying the publication Multi-parameter screening method for developing optimized red fluorescent proteins
<p>This a bundle of test data can be used to run the macros accompanying the publication Multi-parameter screening method for developing optimized red fluorescent proteins.</p> <p>These data sets can be used to run the following macros that can be found on GitHub:</p> <ol> <li><a href="https://github.com/molcyto/MC-Ratio-96-wells">https://github.com/molcyto/MC-Ratio-96-wells</a></li> <li><a href="https://github.com/molcyto/MC-Ratio-Petri-dish">https://github.com/molcyto/MC-Ratio-Petri-dish</a></li> <li><a href="https://github.com/molcyto/MC-FLIM-Petri-dish">https://github.com/molcyto/MC-FLIM-Petri-dish</a></li> <li><a href="https://github.com/molcyto/MC-Bleach-96-wells">https://github.com/molcyto/MC-Bleach-96-wells</a></li> <li><a href="https://github.com/molcyto/MC-Scatter5D">https://github.com/molcyto/MC-Scatter5D</a></li> <li><a href="https://github.com/molcyto/MC-FLIM-96-wells">https://github.com/molcyto/MC-FLIM-96-wells</a></li> </ol> <p>Funding:<br> This work was supported by the NWO CW-Echo grant 711.011.018 (M.A.H. and T.W.J.G.), grant 12149 (T.W.J.G.) from the Foundation for Technological Sciences (STW) from the Netherlands</p> <p> </p>
Experimental data of "Novel flow modulation method for R744 two-phase ejectors – Proof of concept, optimization and first experimental results"
<p>Experimental data of "Novel flow modulation method for R744 two-phase ejectors – Proof of concept, optimization and first experimental results"</p>
Experimental Results for the study "The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems"
<p>This repository contains the experiment results (raw data in NPZ and CSV format and Latex tables) for the study "The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems", which is accepted in <em>Mathematical and Computational Applications</em> journal.</p> <p>The preprint version of the related paper is already online: </p> <p> </p> <p>Wang, H.; Emmerich, M.; Deutz, A.; Hernández, V.A.S.; Schütze, O. The Hypervolume Newton Method for Constrained Multi-objective Optimization Problems. <em>Preprints</em> <strong>2022</strong>, 2022110103 (doi: <a href="http://10.20944/preprints202211.0103.v1">10.20944/preprints202211.0103.v1</a>).</p> <p><strong>Data description:</strong> we benchmarked<strong> </strong>three algorithms: (1) the standalone <strong>Hypervolume Netwon Method</strong> (HVN), (2) NSGA-III, and (3) the <strong>hybridization</strong> of the standalone HVN and NSGA-III on several artificial problems.</p> <ul> <li>For the standalone HVN algorithm, we tested it on three simple artificial test problems - P1, P2, and P3 (proposed in the above paper): <ul> <li>2D-example-50*.tex: problem P1</li> <li>3D-example1*.tex: problem P2</li> <li>3D-example2*.tex: problem P3</li> </ul> </li> <li>For NSGA-III and the hybridization, we tested them on the equality-constrained DTLZ and Inverted DTLZ (IDTLZ) problems: <ul> <li>Eq1DTLZ.*npz: DTLZ problems</li> <li>Eq1IDTLZ*.npz: IDTLZ problems</li> </ul> </li> </ul>
Case study of a rapid prototyping method for optimizing soft gripper structures with integrated piezoresistive sensors
<p>Closed-loop control systems and monitoring the activities of soft robots in the natural environment require sensing elements in soft actuator modules. In this study, additive manufacturing is used for sensorized soft actuator modules to investigate the influence of the Shore hardness and design aspects of an open-source tendon-based gripper structure, in a time-efficient way. Additionally, the placement of the piezoresistive sensing element (tension or compression side on the bending soft gripper) was investigated. A user-friendly method, based on thermoplastic material extrusion, has been explored to improve the future design optimization in of active soft robotic structures successfully. A higher Shore hardness resulted in a higher total deflection and a higher force to bend the gripper structure. By increasing the geometrical stiffness of the gripper printed with low Shore hardness, the total deflection was increased, but the force needed to activate the movement was higher in comparison to high Shore hardness and low geometrical stiffness. Moreover, the sensing element on the substrate of higher Shore hardness, leads to low drift, monotonic response, with good sensitivity, independent of the sampling rate. The gripper of higher Shore hardness had a larger functional range, being capable of gripping small and larger objects.</p>
Effective seed sterilization methods require optimization across maize genotypes
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Data from: AgMate: an optimal mating software versus other mate pair designing methods on long-term breeding of Pinus taeda L
Open the record for dataset details and reuse information.
Singularity container for CGO'21 artifact description: YaskSite -- Stencil Optimization Techniques Applied to Explicit ODE Methods on Modern Architectures - version 1.2
<p>Singularity container for CGO'21 artifact description: YaskSite -- Stencil Optimization Techniques Applied to Explicit ODE Methods on Modern Architectures</p> <p> </p> <p>version 1.2</p>
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.