Results 41 to 50 of about 59,107 (225)
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
RAVEN / CROW IN MYTH AND LANGUAGE. PART 2. COGNITIVE SEMIOTIC ANALYSIS OF MODERN ENGLISH ROCK LYRICS
The article addresses the linguocognitive and linguosemiotic features of verbalizers of the mythic concept RAVEN / CROW in modern English lyrics of rock performers.
Oleksandr KOLESNYK
doaj +1 more source
Data‐Driven Materials Science for Energy‐Sustainable Applications
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
The morphosyntactic integration of English words into Afaan Oromoo
The present study investigates the morphosyntactic integration of English lexical items into Afaan Oromoo within multilingual conversations recorded in Dambi Dollo, Oromia regional state, Western Ethiopia.
Ваквоя Міхірету +1 more
doaj +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki +2 more
wiley +1 more source
This work presents the MicroRoboScope, a highly integrated, compact, and portable microrobotic experimentation platform combining electromagnetic and acoustic actuation with real‐time visual feedback into a single, end‐to‐end device. The system enables closed‐loop control and tracking algorithm experimentation within an accessible and unified hardware ...
Max Sokolich +4 more
wiley +1 more source
Consensus Formation and Change are Enhanced by Neutrality
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag +3 more
wiley +1 more source
Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu +7 more
wiley +1 more source
In most school subjects a large language model is something a class consumes; in the preparation of informatics teachers it is something the class must be able to open, inspect, adapt, and govern - the very competencies the discipline obliges its ...
Vladyslav Ye. Velychko
doaj +1 more source

