Surgical automation can improve the accessibility and consistency of life saving procedures. Most surgeries require separating layers of tissue to access the surgical site, and suturing to reattach incisions. These tasks involve deformable manipulati...
This paper presents the results of a study on the perception of illness and adaptation parameters in patients with type 2 diabetes. The study involved 173 patients diagnosed with "Type 2 Diabetes" (ICD-11 code 5 A 11). The average age of the patients...
Photometric observations for the totally eclipsing binary system TYC 4002-2628-1, were obtained between November 2020 and November 2021. To determine the stellar atmospheric parameters, a spectral image was taken with the 2.16 m telescope at National...
In this paper we use H II starburst galaxy apparent magnitude versus redshift data from Siegel et al. (2005) to constrain dark energy cosmological model parameters. These constraints are generally consistent with those derived using other data sets,...
Neutrino oscillations, a quantum effect manifesting at macroscopic scales, are governed by lepton flavor mixing angles and neutrino mass-squared differences that are fundamental parameters of particle physics, representing phenomena beyond the Standa...
We introduce the \emph{parameter-geometrization} to the Hitchin system, a paradigm embedding deformation parameters into geometry via the coupled Hitchin-He equations on a surface with boundary. A boundary term couples a second Higgs field $ψ$, reco...
Jan 17, 2024 · As the title said, I'm looking for a way to display a single command in an Azure CLI inline script on multiple lines. It is purely for visibility since I happen to have a lot of parameters for the ...
The top quark mass is one of the most intriguing parameters of the standard model (SM). Its value indicates a Yukawa coupling close to unity, and the resulting strong ties to Higgs physics make the top quark mass a crucial ingredient for understandin...
Computational efficiency is an important consideration for deploying machine learning models for time series prediction in an online setting. Machine learning algorithms adjust model parameters automatically based on the data, but often require users...
In January 1969, Peter M. Neumann wrote a paper entitled "Primitive permutation groups of degree 3p". The main theorem placed restrictions on the parameters of a primitive but not 2-transitive permutation group of degree three times a prime. The pape...
Streamlined prediction of the electronic properties of photoactive materials warrants a Density Functional Theory (DFT) based approach that (i) yields reliable bandgaps, (ii) is free of empirically tuned parameters, and (iii) exhibits low computation...
Estimated AC power consumption ranges from ~280 MW (1) to 416 MW (2) for a 350 GeV E_cm 80 km circumference colliding beam storage ring complex with parameters given in (1). The difference between the two estimates is from differing assumptions conce...
Modern Natural Language Processing (NLP) models based on Transformer structures represent the state of the art in terms of performance on very diverse tasks. However, these models are complex and represent several hundred million parameters for the s...
Final project for Dr. Steve Chase's Neural Data Analysis class. The final product is a MATLAB GUI that allows users to manipulate parameters and observe their effect on decoder accuracy. (⭐ 2)
robotic missions. This framework defines cost, schedule and technical risk parameters to enable competitive selection of missions involving mission candidates
(plutonium(III) bromide structure), space group Ccmm (No. 63), lattice parameters a = 430pm, b = 1403pm and c = 995pm. Holleman, Arnold Frederik; Wiberg, Egon (2001)
Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object r…
Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object r…
An algorithm for sampling exactly from the normal distribution is given. The algorithm reads some number of uniformly distributed random digits in a given base and generates an initial portion of the representation of a normal deviate in the same base. Thereaf…
Points: 33 | Comments: 23 | Author: sogen