Results 41 to 50 of about 138,439 (148)

Circularity, Sustainability, and the Quality of Coffee Sold via Vending Machines: What Do Italian Consumers Prefer?

Agribusiness, EarlyView.
ABSTRACT Vending is an important sector in the daily lives of many people, and coffee is the most frequently consumed product in the European market. Like many other sectors, vending is responding to the challenge of sustainable development by taking various actions, such as offering increasingly ecologically sound coffee while maintaining/improving ...
Alberto Bertossi, Stefania Troiano, Francesco Marangon   +2 more
wiley   +1 more source

Import Wheat Tenders and the Effects of the Russian Invasion

Agribusiness, EarlyView.
ABSTRACT Risk and volatility for many commodities escalated sharply following the Russian invasion of Ukraine, creating numerous uncertainties for trading firms and importers. The purpose of this study is to analyze the bidding behavior in Egyptian wheat import tenders in the pre‐ and post‐invasion periods.
William W. Wilson, Sumadhur Shakya, Isaac Dubovoy   +2 more
wiley   +1 more source

Advancements in Machine Learning for Microrobotics in Biomedicine

Advanced Intelligent Systems, EarlyView.
Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi, Soleiman Hosseinpour, Nasrollah Tabatabaei, Mahmoud Soltani Firouz, Niloufar Zadebana, Richard Nauber, Mariana Medina‐Sánchez   +6 more
wiley   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

Generative Inverse Design of Metamaterials with Functional Responses by Interpretable Learning

Advanced Intelligent Systems, EarlyView.
This work introduces random‐forest‐based interpretable generative inverse design (RIGID), a new single‐shot inverse design method for metamaterials using interpretable machine learning and Markov chain Monte Carlo sampling. Once trained on a small dataset, RIGID can estimate the likelihood of designs achieving target behaviors (e.g., wave‐based ...
Wei (Wayne) Chen, Rachel Sun, Doksoo Lee, Carlos M. Portela, Wei Chen   +4 more
wiley   +1 more source

Machine Learning‐Assisted Simulations and Predictions for Battery Interfaces

Advanced Intelligent Systems, EarlyView.
This review summarizes machine learning (ML)‐assisted simulations and predictions at battery interfaces. It highlights how employing ML algorithms with machine vision, enables the lithium dendrite growth simulation, the solid–electrolyte interphase formation, and other interfacial dynamics.
Zhaojun Sun, Xin Li, Yiming Wu, Qilin Gu, Shiyou Zheng   +4 more
wiley   +1 more source

Multi‐Distance Spatial‐Temporal Graph Neural Network for Anomaly Detection in Blockchain Transactions

Advanced Intelligent Systems, EarlyView.
This paper presents a novel Multi‐Distance Spatial‐Temporal Graph Neural Network for detecting anomalies in blockchain transactions. The model combines multi‐distance graph convolutions with adaptive temporal modeling to capture complex patterns in anonymized cryptocurrency networks.
Shiyang Chen, Yang Liu, Qun Zhang, Zhouhang Shao, Zewei Wang   +4 more
wiley   +1 more source

Applied Artificial Intelligence in Materials Science and Material Design

Advanced Intelligent Systems, EarlyView.
AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material ...
Emigdio Chávez‐Angel, Martin Børstad Eriksen, Alejandro Castro‐Alvarez, Jose H. Garcia, Marc Botifoll, Oscar Avalos‐Ovando, Jordi Arbiol, Aitor Mugarza   +7 more
wiley   +1 more source

A Novel Semi‐Automated Pipeline for Optimizing 3D‐Printed Drug Formulations

Advanced Intelligent Systems, EarlyView.
A novel, semi‐automated deep learning and differential evolution pipeline designed for generating medicines for 3D‐printed medicines is introduced. This pipeline successfully generates a diverse range of drug formulations with an 80% printing success rate and 92% accuracy in predicting printing parameters.
Youssef Abdalla, Martin Ferianc, Haya Alfassam, Atheer Awad, Ruochen Qiao, Miguel Rodrigues, Mine Orlu, Abdul W. Basit, David Shorthouse   +8 more
wiley   +1 more source

Exploring Skill Generalization with an Extra Robotic Arm for Motor Augmentation

Advanced Intelligent Systems, EarlyView.
Extra robotic arms promise to augment human motor functions during multitasking. Herein, diaphragmatic‐controlled extra robotic arm (XRA) is investigated, demonstrating significant performance improvements—true functional augmentation—in trimanual tasks. However, limited generalization to tasks requiring fine motor skills is identified.
Daniel Leal Pinheiro, Giulia Dominijanni, Francesca Paola Maenza, Hugo Dirat, Solaiman Shokur, Silvestro Micera   +5 more
wiley   +1 more source