Results 101 to 110 of about 45,402 (287)

Hairdressing in groups: a survey of combings and formal languages

open access: yes, 1997
A group is combable if it can be represented by a language of words satisfying a fellow traveller property; an automatic group has a synchronous combing which is a regular language.
Rees, Sarah
core   +1 more source

Stable Diffusion Models Reveal a Persisting Human–AI Gap in Visual Creativity

open access: yesAdvanced Science, EarlyView.
This study examines visual creativity in humans and generative AI using the TCIA framework. Human artists outperform AI overall, yet structured human guidance substantially improves AI outputs and evaluations. Findings reveal that alignment with human creativity depends critically on contextual framing, highlighting both the promise and current ...
Silvia Rondini   +8 more
wiley   +1 more source

Automata and rational expressions

open access: yes, 2015
This text is an extended version of the chapter 'Automata and rational expressions' in the AutoMathA Handbook that will appear soon, published by the European Science Foundation and edited by ...
Sakarovitch, Jacques
core  

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu   +8 more
wiley   +1 more source

Kenyan Farmers' Policy Priorities During Economic Crisis and Stability: Insights From a Best‐Worst Scaling Experiment

open access: yesApplied Economic Perspectives and Policy, EarlyView.
ABSTRACT Amid rising food and fertilizer prices, understanding farmers' policy preferences is critical for effective crisis response. We use best‐worst scaling experiment to assess Kenyan mobile‐owning crop farmers' preferences for government support under high and normal price scenarios.
Mywish K. Maredia   +4 more
wiley   +1 more source

The Role of Social Food Infrastructure in Addressing SNAP Participation Gaps: Evidence From Linked Administrative and Ground‐Sourced Data

open access: yesApplied Economic Perspectives and Policy, EarlyView.
ABSTRACT We link American Community Survey and SNAP records for 185,000 units with ground‐sourced social food infrastructure data from FindFoodIL (Illinois Extension SNAP‐Ed) to examine SNAP participation determinants among eligible units. Bivariate probit models reveal, beyond SNAP offices, quantity of social infrastructure is associated with ...
Michael Lotspeich‐Yadao   +3 more
wiley   +1 more source

Undecidability of $L(\mathcal{A})=L(\mathcal{B})$ recognized by measure many 1-way quantum automata

open access: yes, 2019
Let $L_{>\lambda}(\mathcal{A})$ and $L_{\geq\lambda}(\mathcal{A})$ be the languages recognized by {\em measure many 1-way quantum finite automata (MMQFA)} (or,{\em enhanced 1-way quantum finite automata(EQFA)}) $\mathcal{A}$ with strict, resp. non-strict
Lin, Tianrong
core  

Heterogeneity in Food Price Inflation Convergence Across the EU: Evidence From Club Dynamics and Structural Breaks

open access: yesAgribusiness, EarlyView.
ABSTRACT This study examines food price inflation rate convergence among EU27 Member States from 2005 to 2024, focusing on structural breaks, external shocks, and regional disparities. Using panel unit root tests and club convergence analysis, the findings reveal no overall convergence but identify multiple convergence clubs.
Tibor Bareith, Imre Fertő
wiley   +1 more source

Automata Theory and Formal Languages

open access: yes, 2008
In this book we present some basic notions and results on Automata Theory, For- mal Language Theory, Computability Theory, and Parsing Theory. In particular, we consider the class of regular languages which are related to the class of finite automata, and the class of the context-free languages which are related to the class of pushdown automata.
openaire   +3 more sources

Which Method Best Predicts Postoperative Complications: Deep Learning, Machine Learning, or Conventional Logistic Regression?

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Deep learning has shown promise in predicting postoperative complications, particularly when using image or time‐series data. However, on tabular clinical data such as the NCD, it often underperforms compared to conventional machine learning. Integrating multimodal data may enhance predictive accuracy and interpretability in surgical care.
Ryosuke Fukuyo   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy