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33 results for “PSO”
Figure 9. Performance analysis of FCM-PSO, GPC-PSO and GFCM-PSO-An Optimized Clustering Approach for Automated Detection of White Matter Lesions in MRI Brain Images
<p>All scans obtained from different image clustering models are manually ranked based on<br> values in table 1. Table 2 represents WML detection rates of optimized images. FCM, GPC and<br> GFCM clustering methods and hybrid optimized methods (FCM-PSO, GPC-PSO and GFCM-PSO)<br> are applied on a dataset of 208 images and ranking is done in terms of under detected, over<br> detected, properly detected as shown in figure 8 and figure 9.</p>
Figures -using Particle Swarm Optimization (PSO)-An Optimized Clustering Approach for Automated Detection of White Matter Lesions in MRI Brain Images
<p>The performance of WML quantification is evaluated using clustering algorithms. When the<br> image is pre-processed, contrast of the image is enhanced. The resulting enhanced image is<br> clustered using the effective clustering algorithms. Figure 3 represents the input image for WML<br> detection. In order to increase robustness, the noisy medical image is pre-processed. Figure 4<br> depicts the pre-processed image. Bright contrast stretching, which is one of the image enhancement<br> (pre-processing) techniques is applied. After pre-processing the enhanced image is subjected to<br> clustering. Three clustering models are proposed to provide accurate results.</p> <p>All scans obtained from different image clustering models are manually ranked based on<br> values in table 1. Table 2 represents WML detection rates of optimized images. FCM, GPC and<br> GFCM clustering methods and hybrid optimized methods (FCM-PSO, GPC-PSO and GFCM-PSO)<br> are applied on a dataset of 208 images and ranking is done in terms of under detected, over<br> detected, properly detected as shown in figure 8 and figure 9. The number of images detected<br> properly in GFCM is comparatively high than FCM and GPC.</p>
Figure 5. Process flow of PSO-Classification of Human Emotion from Deap EEG Signal Using Hybrid Improved Neural Networks with Cuckoo Search
<p>PSO is used to identify the best solution from collection of solution. It is a computational<br> method that optimizes a problem by iteratively trying to improve a candidate solution with regard to<br> a given measure of quality. PSO optimizes a problem by having a population of candidate solutions,<br> here dubbed particles, and moving these particles around in the search-space according to simple<br> mathematical formulae over the particle's position and velocity. Each particle's movement is<br> influenced by its local best known position but, is also guided toward the best known positions in<br> the search-space, which are updated as better positions are found by other particles. This is expected<br> to move the swarm toward the best solutions. PSO is a metaheuristic as it makes few or no<br> assumptions about the problem being optimized and can search very large spaces of candidate<br> solutions. However, metaheuristic such as PSO do not guarantee an optimal solution is ever found.<br> The following Figure 5 explains the basic flow of PSO process.</p>
Linked collectors and determiners for: Colección del Herbario PSO de la Universidad de Nariño.
Natural history specimen data linked to collectors and determiners held within, "Colección del Herbario PSO de la Universidad de Nariño". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/bdd4a614-fb1f-4f0a-a559-478f022baafb">https://bionomia.net/dataset/bdd4a614-fb1f-4f0a-a559-478f022baafb</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/bdd4a614-fb1f-4f0a-a559-478f022baafb">https://gbif.org/dataset/bdd4a614-fb1f-4f0a-a559-478f022baafb</a>. Formatted as a Frictionless Data package.
The optimization of a jet turbojet engine by PSO and searching algorithms
<p>The turbojet engine operates on the ideal Brayton cycle (gas turbine) and consists of six main parts: diffusers, compressors, combustion chambers, turbines, afterburners and nozzles. Using computer code writing in MATLAB software environment, exergy analysis on all selected turbojet engine components, exergy analysis on J85-GE-21 turbojet engine for selective height of 10008000 meters above sea level at speeds of 200 m/s and temperatures of 10, 20 and 40 ° C have been provided and then, according to the system functions, the system is optimized based on the PSO method. For the purpose of optimization, variables of Mach number, efficiency of the compressor, turbine, nozzle and compressor pressure ratio are considered in the range of 0.6 to 1.4, 0.8 to 0.95, 0.8 to 0.95 and 7 to 10, respectively. The highest exergy efficiency of different parts of the engine at sea level with an inlet air velocity of 200 m/s corresponds to a diffuser with 73.1%. Then, the nozzle and combustion chamber are respectively 68.6% and 51.5%. The lowest exergy efficiency is related to compressor with 4%. After that, the afterburner is ranked second with 11.6%. Also, the values of entropy produced and the efficiency of the second law before optimization were 1176.99 and 479 w/k respectively and the same values after optimization were 1129 and 51.4 w/k respectively which is identified. After the optimization process, the amount of entropy produced is reduced and the efficiency of the second law of thermodynamics has increased.<br> </p>
Calibration dataset for PSO scheme
<p>The PSO scheme is a practical parametric scheme for estimating benthic oxygen fluxes by overlying water temperature, average velocity and dissolved oxygen concentration, including the empirical hydrodynamic parameter and the empirical permeability parameter. This dataset provides support for the determination of these two empirical parameters.</p>
A Study to Evaluate the Efficacy and Safety of Two Dose Levels of Certolizumab Pegol (CZP) in Subjects With Plaque Psoriasis (PSO)
ClinicalTrials.gov study NCT02326272. IPD Sharing: Not stated. Countries: 4. Publications: 4.
Efficacy and Safety Study of Certolizumab Pegol (CZP) Versus Active Comparator and Placebo in Subjects With Plaque Psoriasis (PSO)
ClinicalTrials.gov study NCT02346240. IPD Sharing: Not stated. Countries: 9. Publications: 3.
An Investigational Study to Evaluate Experimental Medication BMS-986165 Compared to Placebo in Participants With Plaque Psoriasis (POETYK-PSO-3) in Mainland China, Taiwan, and South Korea
ClinicalTrials.gov study NCT04167462. IPD Sharing: Not stated. Countries: 3. Publications: 1.
An Efficacy and Safety Study of Two Dose Levels of Certolizumab Pegol (CZP) in Subjects With Plaque Psoriasis (PSO)
ClinicalTrials.gov study NCT02326298. IPD Sharing: Not stated. Countries: 5. Publications: 4.
Datasets related to paper "Crustal structure and fault geometries of the Garhwal Himalaya, India: Insight from new high-resolution gravity data modeling and PSO inversion"
<p>The files include Satellite gravity data, topography and earthquake data used in the paper "Crustal structure and fault geometries of the Garhwal Himalaya, India: Insight from new high-resolution gravity data modeling and PSO inversion" by Chamoli A., Rana S., Dwivedi D., Pandey A.K.. This has been submitted to Journal of Geophysical Research: Solid Earth. Restrictions applied to the availability of the land gravity data set.</p>
Efficacy of Nano-PSO in Parkinson's Disease.
ClinicalTrials.gov study NCT05142085. IPD Sharing: NO. Countries: 1. Publications: 12.
Assessing Impact of CCO's PSO & PC Pathway in Ambulatory HNC Clinics
ClinicalTrials.gov study NCT03266276. IPD Sharing: NO. Countries: 1. Publications: 43.
Efficacy of Nano-Pso Therapy in Menopause
ClinicalTrials.gov study NCT06432816. IPD Sharing: Not stated. Countries: 1. Publications: 11.
Neuroprotective Effect of (Nano PSO), in Patients Who Used to Consume Psychoactive Substances
ClinicalTrials.gov study NCT06550167. IPD Sharing: NO. Countries: 1. Publications: 37.
Impact of NANO-PSO on Cognition in Older Adults with Mild to Moderate Cognitive Impairment
ClinicalTrials.gov study NCT06520878. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Optimising Outpatient Care in Mild to Moderate Psoriasis (PSO-TOP)
ClinicalTrials.gov study NCT01587755. IPD Sharing: Not stated. Countries: 8. Publications: 4.
An Phase III Study of Recombinant Anti-IL-17A Humanized Monoclonal Antibody in Chinese Participants With PsO
ClinicalTrials.gov study NCT06299982. IPD Sharing: Not stated. Countries: 0. Publications: 0.
The CorEvitas Psoriasis (PSO) Registry
ClinicalTrials.gov study NCT02707341. IPD Sharing: Not stated. Countries: 0. Publications: 4.
Study To Evaluate The Impact Of Difficult To Treat Sites On Biological Response In Moderate-To-Severe Plaque Psoriasis(PsO).
ClinicalTrials.gov study NCT04428411. IPD Sharing: NO. Countries: 1. Publications: 0.
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)
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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.