Results 61 to 70 of about 67,162,078 (293)

Learner Corpus Approach for Automatic Distractor Generation

, 2023
Accepted abstract at the Graduate Student Conference in Learner Corpus Research 2023 (LCRGradConf23)
Login, Nikita
core   +1 more source

Organoid Brain‐Machine‐Interface Devices for Central Nervous System Repair

Advanced Science, EarlyView.
We envision organoid brain‐machine‐interface (Organoid‐BMI) devices as new biohybrid bidirectional communication pathways to connect the human CNS and the external world for personalized CNS repair and regeneration. ABSTRACT Central nervous system (CNS) repair and regeneration suffer from tremendous clinical challenges due to current limitations in ...
Yantao Xing, Yang Yang, Zichen Hong, Chunhui Tian, Huiyu Chu, Susanne Clara Prokop, Hongwei Cai, Mingxia Gu, Jason Tchieu, Ken Mackie, Feng Guo   +10 more
wiley   +1 more source

Lexical bundles in learner and expert academic writing

Bellaterra Journal of Teaching & Learning Language & Literature, 2019
Lexical bundles (LBs) have been described as the ‘building blocks of discourse’; in addition to being highly frequent in writing and reducing processing time for readers and writers, they also perform important functions in language.
Noelia Navarro Gil, Elena Martínez Caro
doaj   +1 more source

Variability in learner corpora

, 2015
Corpora and corpus-based methods can make a contribution to the study of variability in learner language for two main reasons. One reason is that the study of linguistic variation itself is particularly amenable to quantitative and corpus-based analysis.
Ädel, Annelie,
core  

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

The Development of an Error-tagged Learner Corpus: TELC (Turkish-English Learner Corpus) and its Web-interface

Dilbilim Araştırmaları Dergisi
Though rather rare and not favoured by corpus linguists due to computationally hard-to-handle problems, learner corpora consisting of spoken and written texts by students from different L1 backgrounds can benefit both researchers in the field of second ...
Hakan CANGIR, Kutay UZUN, Taner CAN, Enis OĞUZ, Ömer Faruk KAYA   +4 more
doaj   +1 more source

Words, clauses, sentences, and T-units in learner language: Precise and objective units of measure?

Journal of the European Second Language Association, 2020
In research on learner language complexity, accuracy and fluency (CAF), syntactic complexity is often studied with quantitative measures based on words, clauses, sentences, and T-units.
Taina Mylläri
doaj   +1 more source

Corpus-based learner language research : contrasting speech and writing

Deeds and Days, 2012
Straipsnyje nagrinėjami lietuvių gimtosios kalbos vartotojų, besimokančių anglų kaip svetimosios, sakytinės ir rašytinės kalbos skirtumai. Lietuvių studentų vartojama anglų kalba, ypač sakytinė, iki šiol mažai tyrinėta. Straipsnyje pristatomi Vilniaus universiteto Filologijos fakulteto Anglų filologijos katedroje sukaupti mokinio kalbos tekstynai ...
Grigaliūnienė, Jonė, Juknevičienė, Rita   +1 more
openaire   +3 more sources

Exploring the base of the iceberg: Writing processes in learner corpus research

, 2023
Learner corpus research has made an important contribution to the study of L2 writing through the analysis of large databases of authentic texts written by representative samples of learners. So far, however, the almost exclusive focus on the final texts,
Gilquin, Gaëtanelle, XIV International Conference on Corpus Linguistics (CILC2023)   +1 more
core  

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source