Foundations and guidelines for high-quality three-dimensional models using photogrammetry: a technical note on the future of neuroanatomy education.
Sign Up to like & getrecommendations! Published in 2023 at "Anatomical sciences education"
DOI: 10.1002/ase.2274
Abstract: Hands-on dissections using cadaveric tissues for neuroanatomical education are not easily available in many educational institutions due to financial, safety and ethical factors. Supplementary pedagogical tools, for instance 3D models of anatomical specimens acquired with… read more here.
Keywords: models using; foundations guidelines; education; education foundations ... See more keywords
Agreement of in vitro orthodontic measurements on dental plaster casts and digital models using Maestro 3D ortho studio software
Sign Up to like & getrecommendations! Published in 2022 at "Clinical and Experimental Dental Research"
DOI: 10.1002/cre2.605
Abstract: Diagnostic casts are one of the standard components of orthodontic records. But they have several drawbacks such as the need for physical space for storage and the risk of breaking due to their brittle composition.… read more here.
Keywords: maestro ortho; casts digital; models using; digital models ... See more keywords
Comparing stress prediction models using smartwatch physiological signals and participant self-reports
Sign Up to like & getrecommendations! Published in 2021 at "Computer methods and programs in biomedicine"
DOI: 10.1016/j.cmpb.2021.106207
Abstract: Recent advances in wearable technology have facilitated the non-obtrusive monitoring of physiological signals, creating opportunities to monitor and predict stress. Researchers have utilized machine learning methods using these physiological signals to develop stress prediction models.… read more here.
Keywords: self reports; models using; stress; physiological signals ... See more keywords
Developing atomistic glass models using potential-free Monte Carlo method: From simple to complex structures
Sign Up to like & getrecommendations! Published in 2022 at "Computational Materials Science"
DOI: 10.1016/j.commatsci.2021.110943
Abstract: We propose here a method to generate random networked amorphous structure using only readily available short-range properties like bond lengths, bond angles and connectivity of the constituents. This method is a variant of MonteCarlo (MC)… read more here.
Keywords: glass models; glass; models using; method ... See more keywords
Presence-only species distribution models are sensitive to sample prevalence: Evaluating models using spatial prediction stability and accuracy metrics
Sign Up to like & getrecommendations! Published in 2020 at "Ecological Modelling"
DOI: 10.1016/j.ecolmodel.2020.109194
Abstract: Abstract Species distribution modelling (SDM) is an important tool for ecologists, but different algorithms and different sampling strategies produce different results. Using virtual species with differing characteristics, this study investigated the effect of sampling strategy… read more here.
Keywords: spatial prediction; stability; models using; prediction stability ... See more keywords
Evaluation and modification of geospatial liquefaction models using land damage observational data from the 2010–2011 Canterbury Earthquake Sequence
Sign Up to like & getrecommendations! Published in 2021 at "Engineering Geology"
DOI: 10.1016/j.enggeo.2021.106099
Abstract: Abstract This paper evaluates existing geospatial liquefaction models using the observed land performance across four events of the Canterbury Earthquake Sequence and analyses the influence of region specific input variables on the models' potential to… read more here.
Keywords: geospatial liquefaction; liquefaction models; models using; liquefaction ... See more keywords
TopoLink: evaluation of structural models using chemical crosslinking distance constraints
Sign Up to like & getrecommendations! Published in 2019 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btz014
Abstract: Summary A software was developed to evaluate structural models using chemical crosslinking experiments. The user provides the types of linkers used and their reactivity, and the observed crosslinks and dead-ends. The software computes the minimum… read more here.
Keywords: chemical crosslinking; using chemical; distance; models using ... See more keywords
Simulation of XXZ Spin Models Using Sideband Transitions in Trapped Bosonic Gases.
Sign Up to like & getrecommendations! Published in 2020 at "Physical review letters"
DOI: 10.1103/physrevlett.125.240504
Abstract: We theoretically propose and experimentally demonstrate the use of motional sidebands in a trapped ensemble of ^{87}Rb atoms to engineer tunable long-range XXZ spin models. We benchmark our simulator by probing a ferromagnetic to paramagnetic… read more here.
Keywords: xxz spin; spin models; xxz; models using ... See more keywords
Fitting Nonlinear Signal Models Using the Increasing-Data Criterion
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3177352
Abstract: To extract important information about the nonlinear signals, this letter makes the utmost of the fitting advantages of Gaussian and polynomial functions, and proposes a nonlinear signal model with broader applications. Then we focus on… read more here.
Keywords: nonlinear signals; using increasing; fitting nonlinear; models using ... See more keywords
Flexible Mobility Models Using Stochastic Differential Equations
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2022.3146407
Abstract: We develop a family of tractable models for UAV mobility. Based on a system of coupled stochastic differential equations, the resulting models exhibit realistic trajectories and flexible covariance structures, making them suitable for both small… read more here.
Keywords: mobility models; stochastic differential; models using; flexible mobility ... See more keywords
Simplified Transfer Learning for Chest Radiography Models Using Less Data.
Sign Up to like & getrecommendations! Published in 2022 at "Radiology"
DOI: 10.1148/radiol.212482
Abstract: Background Developing deep learning models for radiology requires large data sets and substantial computational resources. Data set size limitations can be further exacerbated by distribution shifts, such as rapid changes in patient populations and standard… read more here.
Keywords: radiology; models using; chest radiography; transfer learning ... See more keywords