Results 51 to 60 of about 3,064 (300)
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Extending the Cochran rule for the comparison of word frequencies between corpora [PDF]
We first describe a number of inter-related issues that need to be considered by the researcher when comparing frequencies of linguistic features in two or more corpora.
Rayson, P. +5 more
core
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source
Quantitative analysis of translation revision : contrastive corpus research on native English and Chinese translationese [PDF]
Demand for Chinese-to-English translation has increased over recent years. In contrast, resources for training translators for Chinese-to-English are few although increasing now, relative to English-to-Chinese for example. Corpus-based techniques are now
Yuan, Q. +4 more
core
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
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
Learner corpora: the case of the NOSE corpus [PDF]
This paper provides a brief overview of the scope of learner corpus research and describes a learner corpus by Spanish university students of English, the NOn-native Spanish corpus of English (NOSE). It presents the corpus data, its annotation and how it
Ana Díaz-Negrillo
doaj
This article examines the rapidly growing phenomenon of the use of English as a lingua franca (ELF) in European universities and the need to develop tests which reflect this use.
Newbold, David
doaj +1 more source
Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source
Japanese Learning Support Systems: Hinoki Project Report
In this report, we introduce the Hinoki project, which set out to develop web-based Computer-Assisted Language Learning (CALL) systems for Japanese language learners more than a decade ago.
Bor HODOŠČEK, Kikuko NISHINA
doaj +1 more source

