Results 111 to 120 of about 4,047,455 (275)
Measuring New Venture Legitimacy: A Multi‐dimensional Approach Using Computational Textual Analysis
Abstract Legitimacy is critical for the growth, survival and performance of ventures, yet efforts to measure legitimacy empirically typically focus on a single dimension of this multi‐dimensional construct. In this article, we develop a multi‐dimensional framework for measuring legitimacy using computational text analysis.
Ali Ghods +3 more
wiley +1 more source
On Recovering Sturm--Liouville-Type Operator with Delay and Jump Conditions [PDF]
In this manuscript, the second order differential operators with constant delay and transmission boundary conditions are studied. The asymptotic forms of the characteristic functions and eigenvalues of the operators are obtained.
Mohammad Shahriari, Vladimir Vladicic
doaj +1 more source
Diophantine Approximation and Dirichlet Series
H. Queffélec, M. Queffélec
semanticscholar +1 more source
Abstract This study develops an explainable machine learning model to predict cryptocurrency delistings using Binance data. It combines quantitative indicators (price, volume) with qualitative data from real‐time news and Reddit. Latent Dirichlet Allocation (LDA) is used to extract topic trends and community reactions, which are transformed into time ...
Sungju Yang, Hunyeong Kwon
wiley +1 more source
An extension of the basic local independence model to multiple observed classifications
Abstract The basic local independence model (BLIM) is appropriate in situations where populations do not differ in the probabilities of the knowledge states and the probabilities of careless errors and lucky guesses of the items. In some situations, this is not the case. This work introduces the multiple observed classification local independence model
Pasquale Anselmi +8 more
wiley +1 more source
Reliability measures in knowledge structure theory
Abstract In knowledge structure theory (KST) framework, this study evaluates the reliability of knowledge state estimation by introducing two key measures: the expected accuracy rate and the expected discrepancy. The accuracy rate quantifies the likelihood that the estimated knowledge state aligns with the true state, while the expected discrepancy ...
Debora de Chiusole +3 more
wiley +1 more source
From tetrachoric to kappa: How to assess reliability on binary scales
Abstract Reliability is crucial in psychometrics, reflecting the extent to which a measurement instrument can discriminate between individuals or items. While classical test theory and intraclass correlation coefficients are well‐established for quantitative scales, estimating reliability for binary outcomes presents unique challenges due to their ...
Sophie Vanbelle
wiley +1 more source
LLM‐based prior elicitation for Bayesian graphical modeling
ABSTRACT In the Bayesian graphical modeling framework, priors on network structure encode theoretical assumptions and uncertainty about the topology of psychological constructs under study. For instance, the Bernoulli prior specifies the probability of each pairwise interaction, the Beta–Bernoulli prior governs expected network density, and the ...
Nikola Sekulovski +2 more
wiley +1 more source
Hierarchical Differentiable Fluid Simulation
We introduce a two‐step algorithm that significantly reduces memory usage for solving control problems using differentiable fluid simulation techniques: our method first optimizes for bulk forces at reduced resolution, then refines local details over sub‐domains while maintaining differentiability. In trading runtime for memory, it enables optimization
Xiangyu Kong +4 more
wiley +1 more source
Fast Injective Mesh Parameterization via Beltrami Coefficient Prolongation
Abstract We present a highly efficient and robust method for free boundary injective parameterization of disk‐like triangle meshes with low isometric distortion. Harmonic function–based approaches, grounded in a strong mathematical framework, are widely employed.
G. Fargion, O. Weber
wiley +1 more source

