Results 71 to 80 of about 314,969 (284)

An Ultrafast Self‐Gelling Versatile Hydrogel for Rapid Infected Burn Wound Repair in Military Medicine

Advanced Functional Materials, EarlyView.
A self‐gelling PG@PAC (POD/Gel‐CDH@PA/CHX) powder is developed for infected burn care in austere settings. Upon contact with wound exudate, it instantly forms an adhesive hydrogel, providing simultaneous hemostasis, broad‐spectrum antibacterial activity, reactive oxygen species scavenging, and immunomodulation. In a murine model of S.
Liping Zhang, Zhangrui Wu, Xiansheng Zhao, Geng Wang, Quyang Yang, Minxia zhang, Xiaowei Wang, Xiujun Cheng, Changyue Wu, Dan Wu, Yutian Yang, Canbin Dong, Tao Zhang, Weiqiang Tan, Ningwen Zhu   +14 more
wiley   +1 more source

Integrated Model for Morphological Analysis and Named Entity Recognition Based on Label Attention Networks in Korean

Applied Sciences, 2020
In well-spaced Korean sentences, morphological analysis is the first step in natural language processing, in which a Korean sentence is segmented into a sequence of morphemes and the parts of speech of the segmented morphemes are determined. Named entity
Hongjin Kim, Harksoo Kim
doaj   +1 more source

Hybrid Nanofibers for Multimodal Accelerated Wound Healing

Advanced Healthcare Materials, EarlyView.
Fabrication of wound healing scaffolds based on biocompatible nanofibers. Nanofibers offering high surface area, flexibility, and biocompatibility significantly improved the healing outcome in vivo. Histological, immunological, and anti‐inflammatory markers are noticeably better in treated wounds.
Viraj P. Nirwan, Bence Bajusz, Norbert Fabók, Marina Rudan Dimlic, Jelena Budimir, Tshepang Mqatywa, Miklós Gyöngy, Márton Ferencz, Dorottya Kocsis, Olexandr Bondarenko, Mariia Rolduhina, Milena Lengyel, Istvan Antal, Rebecca Hengsbach, Franciska Erdő, Amir Fahmi   +15 more
wiley   +1 more source

Federated Named Entity Recognition

, 2022
We present an analysis of the performance of Federated Learning in a paradigmatic natural-language processing task: Named-Entity Recognition (NER). For our evaluation, we use the language-independent CoNLL-2003 dataset as our benchmark dataset and a Bi-LSTM-CRF model as our benchmark NER model.
Mathew, Joel, Stripelis, Dimitris, Ambite, José Luis   +2 more
openaire   +1 more source

A named entity recognition dataset for Turkish

2016 24th Signal Processing and Communication Application Conference (SIU), 2016
Named entity recognition is one of the important topics in the research area of natural language processing. Named entity recognition studies conducted on Turkish texts are quite limited, compared to the studies on other languages. Besides, the lack of common data sets makes the comparison of different approaches harder.
Kucuk, Dilek, Kucuk, Dogan, Arici, Nursal   +2 more
openaire   +3 more sources

Text Mining of CVD Synthesis Recipes for 2D Materials

Advanced Materials, EarlyView.
A lightweight, multi‐stage natural language processing framework utilizes fine‐tuned BERT models to extract chemical vapor deposition synthesis knowledge from diverse 2D materials literature. The domain‐adapted workflow integrates classification, named entity recognition, and extractive question answering to systematically retrieve categorical and ...
Ang‐Yu Lu, Richard A. Chen, Aijia Yao, Meng‐Chi Chen, Ji‐Hoon Park, Tianyi Zhang, Xudong Zheng, Nannan Mao, Jiangtao Wang, Zhien Wang, Tomás Palacios, Jing Kong   +11 more
wiley   +1 more source

Chinese Named Entity Recognition Integrating Positional and Entity Category Information [PDF]

Jisuanji gongcheng
Words play a crucial role as contextual information in Chinese Named Entity Recognition (NER) tasks. Although character-based methods have achieved some success, existing methods simplistically embed word information and use a limited feature capture ...
YANG Junhui, LI Sujin
doaj   +1 more source

Optimising Selective Sampling for Bootstrapping Named Entity Recognition [PDF]

, 2005
Training a statistical named entity recognition system in a new domain requires costly manual annotation of large quantities of in-domain data. Active learning promises to reduce the annotation cost by selecting only highly informative data points.
Alex, Beatrice, Becker, Markus, Grover, Claire, Hachey, Ben   +3 more
core   +1 more source

Boosting Named Entity Recognition with Neural Character Embeddings

, 2015
Most state-of-the-art named entity recognition (NER) systems rely on handcrafted features and on the output of other NLP tasks such as part-of-speech (POS) tagging and text chunking.
Guimarães, Victor, Santos, Cicero Nogueira dos   +1 more
core   +1 more source

Named entity recognition in Wikipedia [PDF]

Proceedings of the 2009 Workshop on The People's Web Meets NLP Collaboratively Constructed Semantic Resources - People's Web '09, 2009
Named entity recognition (NER) is used in many domains beyond the newswire text that comprises current gold-standard corpora. Recent work has used Wikipedia's link structure to automatically generate near gold-standard annotations. Until now, these resources have only been evaluated on newswire corpora or themselves.
Dominic Balasuriya, Nicky Ringland, Joel Nothman, Tara Murphy, James R. Curran   +4 more
openaire   +1 more source