Results 151 to 160 of about 9,574,302 (235)

Integrating Reinforcement Learning With Explainable Artificial Intelligence for Real‐Time Clinical Decision Support in Dynamic Healthcare Environments

Advanced Intelligent Systems, EarlyView.
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha, MD Faiaz Zaman Dehan, Kazi Md. Tanvir Anzum   +2 more
wiley   +1 more source

Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers

Advanced Intelligent Systems, EarlyView.
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica, Kostya S. Novoselov, Seongmin Kim, Yousung Jung, Silvana Botti, Miguel A. L. Marques, Tigany Zarrouk, Miguel A. Caro, Sanggyu Chong, Michele Ceriotti, Marivi Fernandez‐Serra, Sara Navarro‐Rodriguez, Aakash Ashok Naik, Janine George, Ömer Hasan Omar, Victor Trinquet, Gian‐Marco Rignanese, Andrey Ustyuzhanin, Sonia Conesa‐Boj, Juan Rojo, Minh‐Tuan Dau, Simon M.‐M. Dubois, Jean‐Christophe Charlier, Jose H. Garcia, Romain Gautier, Rachid Laref, Junfeng Qiao, Giovanni Pizzi, Nicola Marzari, Camilla Coletti, Antonio Rossi, Jan‐Lucas Uslu, Chiara Zanardi, Vincenzo Palermo, Wide Hogenhout, Natalia Konchakova, Peter Klein, Tejs Vegge, Stephan Roche   +38 more
wiley   +1 more source

A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines

Advanced Intelligent Systems, EarlyView.
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe, Eleonora Raimondo, Andrea Grimaldi, Pedram Khalili Amiri, Stefano Chiappini, Anna Giordano, Mario Carpentieri, Hyunsoo Yang, Massimo Chiappini, Giovanni Finocchio   +9 more
wiley   +1 more source

A Multidimensional Perspective on Network Conditions in Telesurgery

Advanced Intelligent Systems, EarlyView.
A multidimensional framework systematically evaluates how combined network impairments influence telesurgical performance. By jointly analyzing latency, jitter, bandwidth, and packet loss, the proposed methodology identifies relevant network condition parameters and their interactions, supporting the design of reliable and safe telesurgical systems ...
Florian Heemeyer, Marco Cina, Ege Cem Kirci, Laurent Vanbever, Quentin Boehler   +4 more
wiley   +1 more source

The causal effect of agricultural landscape simplification on Germany's grasslands during a compound drought and heatwave in 2018

American Journal of Agricultural Economics, EarlyView.
Abstract Preserving ecosystem services, along with economic and environmental benefits, will require future landscape policies to identify and incorporate relevant landscape features. In this paper, we investigate the causal effect of agricultural landscape simplification on drought‐related grassland damages.
Marco Ferro, Jan Börner, Silke Hüttel, Katja Kowalski, Patrick Hostert, Krisztina Kis‐Katos   +5 more
wiley   +1 more source

Optimization of Saponification Process for Quantification of Individual and Total Tocopherols and Phytosterols in Canola Oil Refining By‐Products

Journal of the American Oil Chemists' Society, EarlyView.
ABSTRACT In this study, saponification variables were optimized using a face‐centred central composite design‐response surface methodology. The variables included reaction temperature (50°C–120°C), reaction time (30–180 min), KOH concentration (0.5–3 M) and pyrogallol concentration (0–1% w/v).
Milad Kazemi, Paul Prenzler, Lachlan Schwarz, Michael Loughlin, Randy Adjonu   +4 more
wiley   +1 more source

APPROXIMATION OF TRANSITION FUNCTIONS BY FRACTIONAL ORDER POLYNOMIALS

, 2014
B. Kopchak
semanticscholar   +1 more source

Grid Independence Study and a Finite Difference Collocation Approach for Magnetized CeO2‐Ti3C2/H2O Hybrid Nanofluid Flow Over an Inclined Spinning Disk With Newtonian Heating

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT This work examines magnetohydrodynamic (CeO2, Ti3C2/H2O) hybrid nanofluid (HNF) flow on an inclined revolving disk with effects of Newtonian heating. HNF is obtained by suspending the nanoparticles (NPs) of CeO2 and Ti3C2 in water (H2O). The flow is affected by mixed convection, Joule heating, nonlinear thermally radiative and dissipative ...
Ebrahem A. Algehyne, Abdul Bariq, Mounirah Areshi, Fahad Maqbul Alamrani, Zehba Raizah, Izharul Haq, Anwar Saeed   +6 more
wiley   +1 more source

Ajuste de polinomios fraccionarios a curvas de crecimiento / Fit the fractional polynomials to curves growth

, 2010
En esta tesis se propone una metodología que permite ajustar curvas de crecimiento a través de polinomios fraccionarios, se utiliza la transformación propuesta por Potthoff y Roy (1964) que permite medir el efecto de la curva de crecimiento a través del ...
Acosta C., Libia Cristina
core  

Optimizing Charpy Impact Strength of Material‐Extruded PLA Through Layer Height, Raster Angle, and Infill Geometry

Journal of Applied Polymer Science, EarlyView.
Charpy impact performance of material‐extruded PLA is governed by the coupled effects of layer height, raster angle, and infill geometry. Full‐factorial testing identifies layer height as the dominant factor and reveals a strong layer‐height–raster‐angle interaction.
Yazan Mashaki, Luis Hoi Fan, Shafahat Ali, Salman Pervaiz, Ibrahim Deiab   +4 more
wiley   +1 more source