Results 91 to 100 of about 2,018 (260)

Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)

Advanced Intelligent Systems, EarlyView.
This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley   +1 more source

MusicSwarm: Biologically Inspired Intelligence for Music Composition

Advanced Intelligent Systems, EarlyView.
Biologically inspired swarms of frozen foundation models self‐organize to compose complex music without fine‐tuning. By coordinating through stigmergic signals, decentralized agents dynamically evolve specialized roles and adapt to solve complex tasks.
Markus J. Buehler
wiley   +1 more source

Dynamic Searchable Symmetric Encryption with Physical Deletion and Small Leakage

, 2017
Dynamic Searchable Symmetric Encryption (DSSE) allows a client not only to search over ciphertexts as the traditional searchable symmetric encryption does, but also to update these ciphertexts according to requirements, e.g., adding or deleting some ciphertexts. It has been recognized as a fundamental and promising method to build secure cloud storage.
Xu, Peng, Liang, Shuai, Wang, Wei, Susilo, Willy, Wu, Qianhong, Jin, Hai   +5 more
openaire   +3 more sources

A Hybrid Semi‐Inverse Variational and Machine Learning Approach for the Schrödinger Equation

Advanced Physics Research, EarlyView.
A hybrid semi‐inverse variational and machine‐learning framework is presented for solving the Schrödinger equation with complex quantum potentials. Physics‐based variational solutions generate high‐quality training data, enabling Random Forest and Neural Network models to deliver near‐perfect energy predictions.
Khalid Reggab, Houssam Eddine Hailouf, Kingsley Onyebuchi Obodo, Mireille Megnidio‐Tchoukouegno, Mohammed Benali Kanoun, Souraya Goumri‐Said   +5 more
wiley   +1 more source

A critical reappraisal of the carotid sinus and carotid bulb: Distinguishing neurohistological function from vascular geometry

The Anatomical Record, EarlyView.
This review redefines the carotid bulb (CB) as a variable geometric dilation shaped by hemodynamics and the carotid sinus (CS) as a conserved neurohistological baroreceptor field. Distinguishing these entities clarifies a century of anatomical confusion and links geometry, neurohistology, and clinical interpretation within a unified framework ...
Răzvan Costin Tudose, Nicolae Radu, Mugurel Constantin Rusu   +2 more
wiley   +1 more source

An Indicator‐Based Decision Framework for Circular Bioeconomy Transition in the Steel Industry: Integrating Multiphase Learning and Cooperative Game Modelling

Business Strategy and the Environment, EarlyView.
ABSTRACT Despite growing attention to the circular bioeconomy (CBE), the steel industry currently lacks a standardised, sectoral measurement framework to facilitate a low‐carbon transition. In this study, a decision‐support framework for evaluating CBE performance in the steel industry is proposed.
Ali Zamani Babgohari, Mohammadreza Sadeghi‐Moghadam, Hannan Amoozad Mahdiraji   +2 more
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Molecular Dynamics Simulations of γ‐Belite(010)–Water Interfaces With High‐Dimensional Neural Network Potentials

Chemistry – A European Journal, EarlyView.
Several γ$\gamma$‐belite(010)–water interfaces have been studied by molecular dynamics simulations using a high‐dimensional neural network potential. The structure and reactivity of interfacial water have been analyzed and two types of surface defects could be identified, which indicate the possible existence of a wide range of surface structures ...
Bernadeta Prus, Jörg Behler
wiley   +1 more source

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

The Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales, Francisco Izaias da Silva Aires, Paulo Gonçalves de Sousa Junior, Calebe Da Rocha Silva, Emanuel Lino Rodrigues, Maria Cristiane Martins de Souza, José C. S. dos Santos   +6 more
wiley   +1 more source

Hybrid machine learning and genetic algorithm approach for catalyst and process optimization in Fischer–Tropsch synthesis toward sustainable fuel production

The Canadian Journal of Chemical Engineering, EarlyView.
Graphical representation of a data‐driven framework for Fischer‐Tropsch synthesis (FTS) modelling and optimization. Abstract This study presents a data‐driven approach for predicting the relationships between catalyst design, process conditions, and product selectivity in Fischer–Tropsch synthesis (FTS).
Doaa M. Hassan, Ryan Gosselin, Nicolas Abatzoglou   +2 more
wiley   +1 more source