Results 61 to 70 of about 82,097 (301)
AMPSO: A new Particle Swarm Method for Nearest Neighborhood Classification [PDF]
Nearest prototype methods can be quite successful on many pattern classification problems. In these methods, a collection of prototypes has to be found that accurately represents the input patterns.
Galván, Inés M. +2 more
core +1 more source
Resolving the trade-offs between suspension travel, ride comfort, road holding, vehicle handling and power consumption is the primary challenge in the design of active vehicle suspension system. Multi-loop proportional + integral + derivative controllers’
Olurotimi A Dahunsi +3 more
doaj +1 more source
Curve-Fitting on Graphics Processors Using Particle Swarm Optimization [PDF]
Curve fitting is a fundamental task in many research fields. In this paper we present results demonstrating the fitting of 2D images using CUDA (compute unified device architecture) on NVIDIA graphics processors via particle swarm optimization (PSO ...
R. T. Kneusel
doaj +1 more source
Single‐molecule DNA flow‐stretch assays for high‐throughput DNA–protein interaction studies
We describe an optimised single‐molecule DNA flow‐stretch assay that visualises DNA–protein interactions in real time. Linear DNA fragments are tethered to a surface and stretched by buffer flow for fluorescence imaging. Using λ and φX174 DNA, this protocol enhances reproducibility and accessibility, providing a versatile approach for studying diverse ...
Ayush Kumar Ganguli +8 more
wiley +1 more source
Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane +11 more
wiley +1 more source
Particle swarm for attribute selection in Bayesian classification: an application to protein function prediction [PDF]
The discrete particle swarm optimization (DPSO) algorithm is an optimization technique which belongs to the fertile paradigm of Swarm Intelligence. Designed for the task of attribute selection, the DPSO deals with discrete variables in a straightforward ...
Freitas, AA +5 more
core +1 more source
Evolutionary analysis across 32 placental mammals identified positive selection at residues H148 and W149 in the immune receptor FcγR1. Ancestral reconstruction combined with molecular dynamics simulations reveals how these mutations may influence receptor structure and dynamics, providing insight into the evolution of antibody recognition and immune ...
David A. Young +7 more
wiley +1 more source
The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong +3 more
wiley +1 more source
Directed evolution of enzymes at the crossroads of tradition and innovation
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source
The Assessment of Straightness and Flatness Errors Using Particle Swarm Optimization
The straightness and flatness errors are generally assessed by using the Least Squares Method (LSM). However, the results obtained from LSM often overestimate the tolerances, and are not consistent with the ISO standards’ definitions.
Cui, Changcai +10 more
core +1 more source

