Results 31 to 40 of about 1,103,641 (160)

Maternal near miss in low‐resource areas [PDF]

open access: yesInternational Journal of Gynecology & Obstetrics, 2017
AbstractObjectiveTo describe the Global Network Near‐Miss Maternal Mortality System and its application in seven sites.MethodsIn a population‐based study, pregnant women eligible for enrollment in the Maternal and Newborn Health Registry at seven sites (Democratic Republic of the Congo; Guatemala; Belagavi and Nagpur, India; Kenya; Pakistan; and Zambia)
Goldenberg, Robert L.   +29 more
openaire   +3 more sources

Regulation of Interface Compatibility and Performance in Soft Magnetic Composites with Inorganic Insulation Layers by FePO4 Intermediate Transition Layer

open access: yesMolecules
In the fabrication of soft magnetic composites, the lattice mismatch between the inorganic insulation layer and the iron matrix often leads to the formation of cracks during the molding process, which significantly impairs the operational performance of ...
Sanao Huang   +6 more
doaj   +1 more source

Trivial Transfer Learning for Low-Resource Neural Machine Translation

open access: yes, 2018
Transfer learning has been proven as an effective technique for neural machine translation under low-resource conditions. Existing methods require a common target language, language relatedness, or specific training tricks and regimes.
Bojar, Ondřej, Kocmi, Tom
core   +1 more source

Neonatal Hypothermia in Low-Resource Settings [PDF]

open access: yesSeminars in Perinatology, 2010
Hypothermia among newborns is considered an important contributor to neonatal morbidity and mortality in low-resource settings. However, in these settings only limited progress has been made towards understanding the risk of mortality after hypothermia, describing how this relationship is dependent on both the degree or severity of exposure and the ...
openaire   +2 more sources

Transfer Learning, Style Control, and Speaker Reconstruction Loss for Zero-Shot Multilingual Multi-Speaker Text-to-Speech on Low-Resource Languages

open access: yesIEEE Access, 2022
Deep neural network (DNN)-based systems generally require large amounts of training data, so they have data scarcity problems in low-resource languages.
Kurniawati Azizah, Wisnu Jatmiko
doaj   +1 more source

The Development of a Kazakh Speech Recognition Model Using a Convolutional Neural Network with Fixed Character Level Filters

open access: yesBig Data and Cognitive Computing, 2023
This study is devoted to the transcription of human speech in the Kazakh language in dynamically changing conditions. It discusses key aspects related to the phonetic structure of the Kazakh language, technical considerations in collecting the ...
Nurgali Kadyrbek   +3 more
doaj   +1 more source

Endangered Languages are not Low-Resourced [PDF]

open access: yes, 2021
The term low-resourced has been tossed around in the field of natural language processing to a degree that almost any language that is not English can be called "low-resourced"; sometimes even just for the sake of making a mundane or mediocre paper appear more interesting and insightful.
openaire   +3 more sources

Inadequate Bioavailability of Intramuscular Epinephrine in a Neonatal Asphyxia Model

open access: yesFrontiers in Pediatrics, 2022
BackgroundOver half a million newborn deaths are attributed to intrapartum related events annually, the majority of which occur in low resource settings.
Sara K. Berkelhamer   +7 more
doaj   +1 more source

Zero-shot Neural Transfer for Cross-lingual Entity Linking

open access: yes, 2018
Cross-lingual entity linking maps an entity mention in a source language to its corresponding entry in a structured knowledge base that is in a different (target) language.
Carbonell, Jaime   +3 more
core   +1 more source

Model Transfer for Tagging Low-resource Languages using a Bilingual Dictionary

open access: yes, 2017
Cross-lingual model transfer is a compelling and popular method for predicting annotations in a low-resource language, whereby parallel corpora provide a bridge to a high-resource language and its associated annotated corpora.
Cohn, Trevor, Fang, Meng
core   +1 more source

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