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Psychosocial Group Intervention at a Low-Resource Setting Environment for Women Who Are Diagnosed and Treated for Breast Cancer: A Systematic Review
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作者 Motlalepule Lekeka 《Health》 2023年第10期1150-1170,共21页
Africa faces significant challenges in terms of material and personnel resources for oncology interventions. This is particularly evident in South Africa, where resources are divided into high- and low-resource settin... Africa faces significant challenges in terms of material and personnel resources for oncology interventions. This is particularly evident in South Africa, where resources are divided into high- and low-resource settings. High-resource settings cater to those with financial means to access private oncology facilities. However, many breast cancer patients receive care in South Africa’s low-resource settings, such as public hospital oncology clinics. Unfortunately, these settings have limited service providers and fail to offer comprehensive interventions, resulting in poor outcomes. However, recent research has highlighted the significance of socially supportive relationships in promoting healing and overall individual well-being, and spirituality has been identified as a source of positive outcomes in cancer patients. This systematic review paper explores the feasibility of implementing support group cancer care and interventions that incorporate social support networks available in community settings, and spiritual practices facilitated by traditional healers, and religious/spiritual leaders. These interventions can be provided within low-resource settings to women diagnosed with breast cancer. Inclusive participation of spouses, children, and extended family in the support group cancer care can facilitate healing for the entire system. Focusing on the strengths and resources within communities and incorporating these complementary services, can enhance the well-being and quality of life for Black African women diagnosed with breast cancer, despite low-resource settings. This approach acknowledges the potential of community-based support networks and encourages collaboration between various stakeholders, including community health educators, nurses, lay counselors, and community volunteers, to address the complex needs of these patients. 展开更多
关键词 Breast Cancer Low Socioeconomic Status Social Support System The Collective Unconscious low-resource Setting Intervention
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Labetalol versus Hydralazine in the Management of Severe Pre-Eclampsia at Tertiary Hospitals in a Low-Resource Setting: A Randomised Controlled Trial
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作者 Uzoma Otutoaja Adeyemo Olabisi Timothy +7 位作者 Emmanuel Olumide Adewara Olufunmilayo Victoria Adebara Augustine Adebayo Adeniyi Babatunde Sunday Awoyinka Raymond Akujuobi Okere Idowu Oluseyi Adebara Adewumi Bakare Mojisola Olumide Ayankunle 《Open Journal of Obstetrics and Gynecology》 2023年第6期1058-1067,共10页
Objective: Intravenous labetalol and hydralazine are both considered first-line medications for the management of acute-onset, severe hypertension in pregnant and postpartum women. The study compared the efficacy and ... Objective: Intravenous labetalol and hydralazine are both considered first-line medications for the management of acute-onset, severe hypertension in pregnant and postpartum women. The study compared the efficacy and safety profile of intravenous labetalol and hydralazine in the control hypertension in severe pre-eclampsia. Materials and Methods: One hundred patients who presented with severe pre-eclampsia were randomized into two study groups. The fifty patients in each arm of the study received either intravenous labetalol or intravenous hydralazine for the control of blood pressure. Results: The mean age of the labetalol subjects was 28.6 ± 5.47 years while that of their hydralazine counterparts was 29.12 ± 5.77 years. The majority of respondents in both groups were primigravidae (76% vs. 78%) (P = 0.813). The number of doses of drug needed to significantly lower the mean systolic blood pressure was slightly lower in the labetalol group (2 doses) compared to the hydralazine group (5 doses) (t = 0.803<sup>Y</sup>, P = 0.977). The incidence of headaches which were the commonest complaints was comparable in both groups 8% and 10% of respondents respectively (P > 0.05). Conclusion: Although both intravenous labetalol and hydralazine are useful in patients with severe pre-eclampsia, the response to labetalol was better with comparable side effects. 展开更多
关键词 Blood Pressure HYDRALAZINE LABETALOL low-resource Setting Severe Pre-Eclampsia Side Effects
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Anesthesia for Cesarean Delivery in a Low-Resource Setting, an Initial Review
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作者 Elizabeth Ogboli-Nwasor Abdulghaffar Adeniyi Yunus 《Open Journal of Anesthesiology》 2014年第9期217-222,共6页
Background: Bearing in mind the recent advances in obstetric anesthesia, the safety of both mother and child is of paramount importance, especially in a setting where resources are limited. We set out to find the patt... Background: Bearing in mind the recent advances in obstetric anesthesia, the safety of both mother and child is of paramount importance, especially in a setting where resources are limited. We set out to find the pattern of cases presenting for cesarean delivery and the types of anesthesias provided for the management of these patients. Methods: A retrospective survey was conducted involving all anesthetics provided for cesarean delivery from January 2006 to December 2009 in Ahmadu Bello University Teaching Hospital, Zaria, Nigeria. Information such as age, indications and anesthetic technique, including drugs used, were extracted from patients’ records. Data were subjected to statistical analysis using Statistical Package for Social Sciences (SPSS) version 17.0. Results: There were a total of 577 anaesthetics conducted for cesarean delivery during the period under review out of 4277 live births, giving a cesarean delivery rate of 13.5%. General anesthesia (GA) was administered on 266 (46%) of these patients, while 279 (48%) cases were done under subarachnoid block(SAB). 16 (3%) patients had combined GA and SAB, while 16 (3%) patients received epidural anesthesia. There were 302 emergency cesarean deliveries out of 577 cases, giving an emergency cesarean delivery rate of 52%. The commonest indication for cesarean delivery was two previous cesarean deliveries. Conclusion: A large percentage of our obstetric cases are being done under general anesthesia. Though majority of the conducted regional anesthesia were spinals (SAB), only a few cases were done under epidural block. Subspecialty training of anesthetists will go a long way to improve the current trends. 展开更多
关键词 ANESTHESIA CESAREAN Delivery EPIDURAL low-resource Sub-Arachnoid BLOCK
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Enhancing low-resource cross-lingual summarization from noisy data with fine-grained reinforcement learning 被引量:1
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作者 Yuxin HUANG Huailing GU +3 位作者 Zhengtao YU Yumeng GAO Tong PAN Jialong XU 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2024年第1期121-134,共14页
Cross-lingual summarization(CLS)is the task of generating a summary in a target language from a document in a source language.Recently,end-to-end CLS models have achieved impressive results using large-scale,high-qual... Cross-lingual summarization(CLS)is the task of generating a summary in a target language from a document in a source language.Recently,end-to-end CLS models have achieved impressive results using large-scale,high-quality datasets typically constructed by translating monolingual summary corpora into CLS corpora.However,due to the limited performance of low-resource language translation models,translation noise can seriously degrade the performance of these models.In this paper,we propose a fine-grained reinforcement learning approach to address low-resource CLS based on noisy data.We introduce the source language summary as a gold signal to alleviate the impact of the translated noisy target summary.Specifically,we design a reinforcement reward by calculating the word correlation and word missing degree between the source language summary and the generated target language summary,and combine it with cross-entropy loss to optimize the CLS model.To validate the performance of our proposed model,we construct Chinese-Vietnamese and Vietnamese-Chinese CLS datasets.Experimental results show that our proposed model outperforms the baselines in terms of both the ROUGE score and BERTScore. 展开更多
关键词 Cross-lingual summarization low-resource language Noisy data Fine-grained reinforcement learning Word correlation Word missing degree
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KeyEE:Enhancing Low-Resource Generative Event Extraction with Auxiliary Keyword Sub-Prompt
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作者 Junwen Duan Xincheng Liao +1 位作者 Ying An Jianxin Wang 《Big Data Mining and Analytics》 EI CSCD 2024年第2期547-560,共14页
Event Extraction(EE)is a key task in information extraction,which requires high-quality annotated data that are often costly to obtain.Traditional classification-based methods suffer from low-resource scenarios due to... Event Extraction(EE)is a key task in information extraction,which requires high-quality annotated data that are often costly to obtain.Traditional classification-based methods suffer from low-resource scenarios due to the lack of label semantics and fine-grained annotations.While recent approaches have endeavored to address EE through a more data-efficient generative process,they often overlook event keywords,which are vital for EE.To tackle these challenges,we introduce KeyEE,a multi-prompt learning strategy that improves low-resource event extraction by Event Keywords Extraction(EKE).We suggest employing an auxiliary EKE sub-prompt and concurrently training both EE and EKE with a shared pre-trained language model.With the auxiliary sub-prompt,KeyEE learns event keywords knowledge implicitly,thereby reducing the dependence on annotated data.Furthermore,we investigate and analyze various EKE sub-prompt strategies to encourage further research in this area.Our experiments on benchmark datasets ACE2005 and ERE show that KeyEE achieves significant improvement in low-resource settings and sets new state-of-the-art results. 展开更多
关键词 natural language processing Event Extraction(EE) Multi-Prompt Learning(MPL) low-resource
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Improving Low-Resource Machine Translation Using Reinforcement Learning from Human Feedback
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作者 Liqing Wang Yiheng Xiao 《Intelligent Automation & Soft Computing》 2024年第4期619-631,共13页
Neural Machine Translation is one of the key research directions in Natural Language Processing.However,limited by the scale and quality of parallel corpus,the translation quality of low-resource Neural Machine Transl... Neural Machine Translation is one of the key research directions in Natural Language Processing.However,limited by the scale and quality of parallel corpus,the translation quality of low-resource Neural Machine Translation has always been unsatisfactory.When Reinforcement Learning from Human Feedback(RLHF)is applied to lowresource machine translation,commonly encountered issues of substandard preference data quality and the higher cost associated with manual feedback data.Therefore,a more cost-effective method for obtaining feedback data is proposed.At first,optimizing the quality of preference data through the prompt engineering of the Large Language Model(LLM),then combining human feedback to complete the evaluation.In this way,the reward model could acquire more semantic information and human preferences during the training phase,thereby enhancing feedback efficiency and the result’s quality.Experimental results demonstrate that compared with the traditional RLHF method,our method has been proven effective on multiple datasets and exhibits a notable improvement of 1.07 in BLUE.Meanwhile,it is also more favorably received in the assessments conducted by human evaluators and GPT-4o. 展开更多
关键词 low-resource neural machine translation RLHF prompt engineering LLM
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AC vector magnetometer for space-based applications using low-resource magneto-impedance sensor
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作者 YU XiangQian HUANG Cong +14 位作者 XIAO ChiJie LI JiaWei LIU Si WANG JingDong LI YunPeng QU YaNan WANG YongFu CHEN HongFei ZOU Hong SHI WeiHong ZONG QiuGang CHEN XiaoFei ZHANG XiaoXin ZONG WeiGuo WANG JingSong 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2023年第12期3663-3670,共8页
This study proposes a novel AC vector magnetometer developed using a low-resource magneto-impedance sensor for China’s Feng-Yun meteorological satellite(FY-3E).It was calibrated and characterized to determine its per... This study proposes a novel AC vector magnetometer developed using a low-resource magneto-impedance sensor for China’s Feng-Yun meteorological satellite(FY-3E).It was calibrated and characterized to determine its performance parameters.The total weight of the AC vector magnetometer is 51 g(the aluminum box excluded),while the total power consumption is 310 m W.The proposed AC vector magnetometer can detect magnetic field variations in the range of±1000 nT and noise power spectral density of≤50 pT/Hz^(1/2)@1 Hz.Furthermore,the proposed device has a maximum nonlinearity of≤0.71‰over the entire range and a nonorthogonality error of 3.07 nT or 0.15%(root mean square).The total dose hardness of the sensor is≥30 krad(Si).Furthermore,we propose the first survey results of a magnetometer equipped aboard a Chinese FY-3E satellite in a Sunsynchronous orbit.The data revealed that the AC vector magnetometer can detect transient physical signals such as quasistatic field-aligned currents(~50 nT)and waves at the auroral latitudes.These features render the proposed AC vector magnetometer suitable for space-based applications,particularly those involving the study of geomagnetic activity. 展开更多
关键词 AC vector magnetometer low-resource magneto-impedance sensor FY-3E satellite
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Enriching the Transfer Learning with Pre-Trained Lexicon Embedding for Low-Resource Neural Machine Translation 被引量:5
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作者 Mieradilijiang Maimaiti Yang Liu +1 位作者 Huanbo Luan Maosong Sun 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2022年第1期150-163,共14页
Most State-Of-The-Art(SOTA) Neural Machine Translation(NMT) systems today achieve outstanding results based only on large parallel corpora.The large-scale parallel corpora for high-resource languages is easily obtaina... Most State-Of-The-Art(SOTA) Neural Machine Translation(NMT) systems today achieve outstanding results based only on large parallel corpora.The large-scale parallel corpora for high-resource languages is easily obtainable.However,the translation quality of NMT for morphologically rich languages is still unsatisfactory,mainly because of the data sparsity problem encountered in Low-Resource Languages(LRLs).In the low-resource NMT paradigm,Transfer Learning(TL) has been developed into one of the most efficient methods.It is difficult to train the model on high-resource languages to include the information in both parent and child models,as well as the initially trained model that only contains the lexicon features and word embeddings of the parent model instead of the child languages feature.In this work,we aim to address this issue by proposing the language-independent Hybrid Transfer Learning(HTL) method for LRLs by sharing lexicon embedding between parent and child languages without leveraging back translation or manually injecting noises.First,we train the High-Resource Languages(HRLs) as the parent model with its vocabularies.Then,we combine the parent and child language pairs using the oversampling method to train the hybrid model initialized by the previously parent model.Finally,we fine-tune the morphologically rich child model using a hybrid model.Besides,we explore some exciting discoveries on the original TL approach.Experimental results show that our model consistently outperforms five SOTA methods in two languages Azerbaijani(Az) and Uzbek(Uz).Meanwhile,our approach is practical and significantly better,achieving improvements of up to 4:94 and 4:84 BLEU points for low-resource child languages Az ! Zh and Uz ! Zh,respectively. 展开更多
关键词 artificial intelligence natural language processing neural network machine translation low-resource languages transfer learning
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Feasibility of telemedicine program using a hand-held nonmydriatic retinal camera in Panama
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作者 Alexander SHimstead Janani Prasad +3 位作者 Sean Melucci Kevin MGustafson Paul EIsraelsen Andrew Browne 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2022年第6期962-966,共5页
AIM: To evaluate the image quality of a telemedicine screening program for retinal disease using a nonmydriatic camera among rural island communities in Bocas del Toro, Panama.METHODS: In June 2018, a group of three m... AIM: To evaluate the image quality of a telemedicine screening program for retinal disease using a nonmydriatic camera among rural island communities in Bocas del Toro, Panama.METHODS: In June 2018, a group of three medical students volunteered at clinics operated by the Floating Doctors in the province of Bocas del Toro, Panama. Nonmydriatic images of the retina were obtained using the Pictor Plus(Volk Optical, Mentor OH), randomized, and sent to two board-certified ophthalmologists at the University of California, Irvine for analysis using a modified version of the FOTO-ED scale. Inter-rater reliability was calculated using the kappa statistic.RESULTS: Seventy patients provided a total of 127 images. Average image quality was 3.31, and most frequent image quality was 4/5 on the FOTO-ED scale. Thirty patients had at least one eye image with ideal quality(42.86%), while only one patient had no adequate photos taken(1.43%). However, high quality images were obtained in both eyes in only 12 patients(17.14%). The inter-rater reliability between the two ophthalmologists was 0.614.CONCLUSION: Further improvements are necessary to acquire higher quality images more reliably. This may include further training and experience or mydriasis. 展开更多
关键词 TELEMEDICINE RETINA nonmydriatic camera FUNDUS screening FEASIBILITY low-resource setting
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Cross-Language Transfer Learning-based Lhasa-Tibetan Speech Recognition
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作者 Zhijie Wang Yue Zhao +3 位作者 Licheng Wu Xiaojun Bi Zhuoma Dawa Qiang Ji 《Computers, Materials & Continua》 SCIE EI 2022年第10期629-639,共11页
As one of Chinese minority languages,Tibetan speech recognition technology was not researched upon as extensively as Chinese and English were until recently.This,along with the relatively small Tibetan corpus,has resu... As one of Chinese minority languages,Tibetan speech recognition technology was not researched upon as extensively as Chinese and English were until recently.This,along with the relatively small Tibetan corpus,has resulted in an unsatisfying performance of Tibetan speech recognition based on an end-to-end model.This paper aims to achieve an accurate Tibetan speech recognition using a small amount of Tibetan training data.We demonstrate effective methods of Tibetan end-to-end speech recognition via cross-language transfer learning from three aspects:modeling unit selection,transfer learning method,and source language selection.Experimental results show that the Chinese-Tibetan multi-language learning method using multilanguage character set as the modeling unit yields the best performance on Tibetan Character Error Rate(CER)at 27.3%,which is reduced by 26.1%compared to the language-specific model.And our method also achieves the 2.2%higher accuracy using less amount of data compared with the method using Tibetan multi-dialect transfer learning under the same model structure and data set. 展开更多
关键词 Cross-language transfer learning low-resource language modeling unit Tibetan speech recognition
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Single-Use Bag Valve Masks: Evaluation of Device Design and Residual Bioburden Analytical Methods
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作者 Sarah Zemitis Melinda Harman +1 位作者 Zachary Hargett Donna Weinbrenner 《Journal of Biomedical Science and Engineering》 2018年第9期235-246,共12页
Background: A recent survey of in-hospital reprocessing in Tanzanian hospitals identified bag-valve masks (BVM) as a commonly reused single-use device. In low- and middle-income countries (LMIC), in-hospital reprocess... Background: A recent survey of in-hospital reprocessing in Tanzanian hospitals identified bag-valve masks (BVM) as a commonly reused single-use device. In low- and middle-income countries (LMIC), in-hospital reprocessing supports neonatal resuscitation strategies by helping to maintain adequate supplies of BVM. However, there is a need for device-specific protocols defining reprocessing procedures and inspection criteria to overcome variations in reprocessing practices between hospitals. The purposes of this study were: 1) to complete a comprehensive design review and identify challenges to reprocessing BVMs;and 2) to investigate three different residual bioburden analysis methods for assessing the efficacy of decontaminating a disposable BVM. Methods: New, unused bag-valve-masks were contaminated with Staphylococcus epidermidis and Artificial Mucus Soil to simulate the worst case soiling conditions. Devices underwent one of five disinfection protocols, including one currently used in a LMIC hospital. Three analytical (two quantitative and one qualitative) methods were selected to evaluate residual bioburden on the device following decontamination. Results: Of all protocols tested, only the positive control and the Soap and Bleach protocols met disinfection targets. Most cleaning outcomes were consistent from trial to trial for each protocol. However, cleaning outcomes varied greatly for the Alcohol Wipe protocol. For the residual bioburden analyses, the two quantitative methods produced similar results, but the qualitative measurement exhibited increased variability. Conclusion: While this study revealed positive disinfection outcomes for the Tanzanian hospital decontamination protocol, more studies are required to support these findings. Design features of the BVM mask presented challenges to cleaning and drying during different decontamination protocols, as seen in the variability in the Alcohol Wipe protocol performance. These findings support the case for a device-specific protocol for the BVM. Given proper hospital personnel training and available resources, in-hospital reprocessing could support neonatal resuscitation strategies and other demands for manual resuscitation by helping to maintain adequate supplies of BVM. 展开更多
关键词 Reprocessing low-resource BAG VALVE Mask Single-Use Device Low-and Middle-Income Countries Newborn Resuscitation
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Introducing a Trauma Registry in Mozambique: An Ethics Case Study
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作者 Fadi Hamadani Otilia Neves +6 位作者 Ana Olga Mocumbi Tarek Razek Kosar Khwaja Paola Fata Andrew Beckett Eunice Jetha Dan L. Deckelbaum 《International Journal of Clinical Medicine》 2014年第16期949-955,共7页
This paper presents a case study of implementing a trauma registry in Mozambique, a low-income country with limited current trauma surveillance. An outline of the importance of trauma registries is presented followed ... This paper presents a case study of implementing a trauma registry in Mozambique, a low-income country with limited current trauma surveillance. An outline of the importance of trauma registries is presented followed by an evidence-based approach to building a sustainable and ethical partnership with local stakeholders. 展开更多
关键词 GLOBAL Burden of Injury GLOBAL HEALTH ETHICS TRAUMA REGISTRY in LOW-INCOME Countries TRAUMA System in low-resource Settings GLOBAL HEALTH Partnership
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A Hospital-Based Cross-Sectional Study Assessing the Relation between Time of Birth and Perinatal Outcome
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作者 Mouhamadou Wade Papa Moctar Faye +8 位作者 Mame Diarra Ndiaye Mamour Gueye Simon Birame Ndour Abdoulaye Diakhate Ndama Niang Khalifa Fall Moussa Diallo Omar Gassama Magatte Mbaye 《Open Journal of Pediatrics》 2020年第1期217-223,共7页
Objectives:?Investigating the relation between perinatal outcomes and?hospital working shifts.?Methods:?We conducted a cross-sectional study at Philippe Maguilen Senghor health center (PMSHC) in Dakar, Senegal from Ja... Objectives:?Investigating the relation between perinatal outcomes and?hospital working shifts.?Methods:?We conducted a cross-sectional study at Philippe Maguilen Senghor health center (PMSHC) in Dakar, Senegal from January, 1st?2011 to December, 31th 2018. The study population was comprised of all mothers who had delivered at PMSHC and their newborns after completing 22 weeks of gestation. Time of delivery was?divided into three periods of working hours: morning shift (deliveries occurred between 7 am and 4:59 pm);evening shift from 5 pm to 10:59 pm and night shift from 11?pm to 6:59 am.?Maternal outcomes were assessed by mode of delivery, epsisotomy and perineal injuries.?The Apgar scoring system was used to assess newborns at first minute after they were born. Other adverse perinatal outcomes included fresh stillbirth, neonatal referral and early neonatal death. Data were analyzed using Statistical Package for Social Science software (SPSS 24, Mac version).?Results:?A total of 48,270 mothers and their newborns met eligibility criteria. Caesarean section deliveries were less likely to occur during evening (OR 0.84, 95% CI;0.79?-?0.89, p = 0.001) and night shifts (OR 0.45, CI;0.47?-?0.53, p = 0.001).?Evening shift deliveries had 1.1 the odds of poor perinatal outcome (Apgar score ?- 1.18, p = 0.012). No significant difference was found in the odds of neonate referrals and deaths across the three shifts.?Night shift deliveries had 1.1 the odds of perineal injuries compared to morning shift deliveries (OR 1.11, 95% CI;1.04?- 1.18, p = 0.001, for episiotomy and OR, 1.14;95% CI, 1.04?- 1.26, p = 0.008, for perineal tears). Conclusion:?Off-hours deliveries, particularly during the night shift, were significantly associated with higher proportions of perineal injuries compared to morning shift.?However, no significant difference was found in the odds of neonate referrals and deaths across the three shifts.?Our findings suggest to set up a Neonatology unit at the CSPMS as well as a perinatal network across the country. 展开更多
关键词 PERINATAL OUTCOME TIME of BIRTH low-resource Setting
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A Knowledge-enhanced Two-stage Generative Framework for Medical Dialogue Information Extraction
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作者 Zefa Hu Ziyi Ni +2 位作者 Jing Shi Shuang Xu Bo Xu 《Machine Intelligence Research》 EI CSCD 2024年第1期153-168,共16页
This paper focuses on term-status pair extraction from medical dialogues(MD-TSPE),which is essential in diagnosis dia-logue systems and the automatic scribe of electronic medical records(EMRs).In the past few years,wo... This paper focuses on term-status pair extraction from medical dialogues(MD-TSPE),which is essential in diagnosis dia-logue systems and the automatic scribe of electronic medical records(EMRs).In the past few years,works on MD-TSPE have attracted increasing research attention,especially after the remarkable progress made by generative methods.However,these generative methods output a whole sequence consisting of term-status pairs in one stage and ignore integrating prior knowledge,which demands a deeper un-derstanding to model the relationship between terms and infer the status of each term.This paper presents a knowledge-enhanced two-stage generative framework(KTGF)to address the above challenges.Using task-specific prompts,we employ a single model to com-plete the MD-TSPE through two phases in a unified generative form:We generate all terms the first and then generate the status of each generated term.In this way,the relationship between terms can be learned more effectively from the sequence containing only terms in the first phase,and our designed knowledge-enhanced prompt in the second phase can leverage the category and status candidates of the generated term for status generation.Furthermore,our proposed special status"not mentioned"makes more terms available and en-riches the training data in the second phase,which is critical in the low-resource setting.The experiments on the Chunyu and CMDD datasets show that the proposed method achieves superior results compared to the state-of-the-art models in the full training and low-re-sourcesettings. 展开更多
关键词 Medical dialogue understanding information extraction text generation knowledge-enhanced prompt low-resource setting dataaugmentation
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Semantic-aware entity alignment for low resource language knowledge graph
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作者 Junfei TANG Ran SONG +2 位作者 Yuxin HUANG Shengxiang GAO Zhengtao YU 《Frontiers of Computer Science》 SCIE EI CSCD 2024年第4期97-106,共10页
Entity alignment(EA)is an important technique aiming to find the same real entity between two different source knowledge graphs(KGs).Current methods typically learn the embedding of entities for EA from the structure ... Entity alignment(EA)is an important technique aiming to find the same real entity between two different source knowledge graphs(KGs).Current methods typically learn the embedding of entities for EA from the structure of KGs for EA.Most EA models are designed for rich-resource languages,requiring sufficient resources such as a parallel corpus and pre-trained language models.However,low-resource language KGs have received less attention,and current models demonstrate poor performance on those low-resource KGs.Recently,researchers have fused relation information and attributes for entity representations to enhance the entity alignment performance,but the relation semantics are often ignored.To address these issues,we propose a novel Semantic-aware Graph Neural Network(SGNN)for entity alignment.First,we generate pseudo sentences according to the relation triples and produce representations using pre-trained models.Second,our approach explores semantic information from the connected relations by a graph neural network.Our model captures expanded feature information from KGs.Experimental results using three low-resource languages demonstrate that our proposed SGNN approach out performs better than state-of-the-art alignment methods on three proposed datasets and three public datasets. 展开更多
关键词 graph neural network knowledge graph entity alignment low-resource language
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Transformer: A General Framework from Machine Translation to Others
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作者 Yang Zhao Jiajun Zhang Chengqing Zong 《Machine Intelligence Research》 EI CSCD 2023年第4期514-538,共25页
Machine translation is an important and challenging task that aims at automatically translating natural language sentences from one language into another.Recently,Transformer-based neural machine translation(NMT)has a... Machine translation is an important and challenging task that aims at automatically translating natural language sentences from one language into another.Recently,Transformer-based neural machine translation(NMT)has achieved great break-throughs and has become a new mainstream method in both methodology and applications.In this article,we conduct an overview of Transformer-based NMT and its extension to other tasks.Specifically,we first introduce the framework of Transformer,discuss the main challenges in NMT and list the representative methods for each challenge.Then,the public resources and toolkits in NMT are listed.Meanwhile,the extensions of Transformer in other tasks,including the other natural language processing tasks,computer vision tasks,audio tasks and multi-modal tasks,are briefly presented.Finally,possible future research directions are suggested. 展开更多
关键词 Neural machine translation TRANSFORMER document neural machine translation(NMT) multimodal NMT low-resource NMT
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Neural machine translation:Challenges,progress and future 被引量:11
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作者 ZHANG JiaJun ZONG ChengQing 《Science China(Technological Sciences)》 SCIE EI CAS CSCD 2020年第10期2028-2050,共23页
Machine translation(MT)is a technique that leverages computers to translate human languages automatically.Nowadays,neural machine translation(NMT)which models direct mapping between source and target languages with de... Machine translation(MT)is a technique that leverages computers to translate human languages automatically.Nowadays,neural machine translation(NMT)which models direct mapping between source and target languages with deep neural networks has achieved a big breakthrough in translation performance and become the de facto paradigm of MT.This article makes a review of NMT framework,discusses the challenges in NMT,introduces some exciting recent progresses and finally looks forward to some potential future research trends. 展开更多
关键词 neural machine translation TRANSFORMER multimodal translation low-resource translation document translation
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Expansion of China's free antiretroviral treatment program 被引量:8
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作者 ZHAO De-cai WEN Yi +7 位作者 MA Ye ZHAO Yan ZHANG Yao WU Ya-song LIU Xia Elizabeth Au LIU Zhong-fu ZHANG Fu-jie 《Chinese Medical Journal》 SCIE CAS CSCD 2012年第19期3514-3521,共8页
Background In 2003, China's National Free Antiretroviral Treatment Program (NFATP) was initiated as a pilot, which covered only 100 HIV/AIDS patients. By 2011, the pilot had evolved into a nationwide program and ha... Background In 2003, China's National Free Antiretroviral Treatment Program (NFATP) was initiated as a pilot, which covered only 100 HIV/AIDS patients. By 2011, the pilot had evolved into a nationwide program and had provided free treatment for over 150 000 patients. The objective of this study was to report and evaluate the progress of China's free antiretroviral treatment program. Methods The NFATP Database was systematically reviewed and a total of 150 692 HIV/AIDS patients were included in this study. Program progress indicators including the number of treated HIV/AIDS patients, follow-up visit rate, CD4 test rate, and viral load test rate were summarized and examined over a calendar year to evaluate the progress of NFATP quantitatively and qualitatively. Results By the end of 2011, a total of 150 692 HIV/AIDS patients had been treated through the NFATP and 122 613 of them were still on treatment. Of all patients, about 72% were enrolled during the past four years. The dominant transmission route was blood related in the early phase of the NFATP, but gradually changed to sexual contact. Besides quantitative improvements, progress indicators also demonstrated significant qualitative improvements that the program had made during the past 9 years. Conclusions Great achievement has been made by China's NFATP. China's experience indicates the importance of a comprehensive response to the success of its treatment program. However, to ensure the quality and sustainability of treatment in the long term, more attention and resources should be paid towards program management. 展开更多
关键词 China human immunodeficiency virus antiretroviral therapy low-resource setting scale-up
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Integrating Pronunciation into Chinese-Vietnamese Statistical Machine Translation 被引量:2
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作者 Anh Tran Huu Heyan Huang +2 位作者 Yuhang Guo Shumin Shi Ping Jian 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2018年第6期715-723,共9页
Statistical machine translation for low-resource language suffers from the lack of abundant training corpora. Several methods, such as the use of a pivot language, have been proposed as a bridge to translate from one ... Statistical machine translation for low-resource language suffers from the lack of abundant training corpora. Several methods, such as the use of a pivot language, have been proposed as a bridge to translate from one language to another. However, errors will accumulate during the extensive translation pipelines. In this paper, we propose an approach to low-resource language translation by exploiting the pronunciation correlations between languages. We find that the pronunciation features can improve both Chinese-Vietnamese and Vietnamese- Chinese translation qualities. Experimental results show that our proposed model yields effective improvements, and the translation performance (bilingual evaluation understudy score) is improved by a maximum value of 1.03. 展开更多
关键词 pronunciation integration low-resource languages Chinese-Vietnamese machine translation Sino-Vietnamese words
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TuLP: A Family of Lightweight Message Authentication Codes for Body Sensor Networks 被引量:2
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作者 龚征 Pieter Hartel +2 位作者 Svetla Nikova 唐韶华 朱博 《Journal of Computer Science & Technology》 SCIE EI CSCD 2014年第1期53-68,共16页
A wireless sensor network (WSN) commonly whilst a body sensor network (BSN) must be secured with requires lower level security for public information gathering, strong authenticity to protect personal health infor... A wireless sensor network (WSN) commonly whilst a body sensor network (BSN) must be secured with requires lower level security for public information gathering, strong authenticity to protect personal health information. In this paper, some practical problems with the message authentication codes (MACs), which were proposed in the popular security architectures for WSNs, are reconsidered. The analysis shows that the recommended MACs for WSNs, e.g., CBC- MAC (TinySec), OCB-MAC (MiniSec), and XCBC-MAC (SenSee), might not be exactly suitable for BSNs. Particularly an existential forgery attack is elaborated on XCBC-MAC. Considering the hardware limitations of BSNs, we propose a new family of tunable lightweight MAC based on the PRESENT block cipher. The first scheme, which is named TukP, is a new lightweight MAC with 64-bit output range. The second scheme, which is named TuLP-128, is a 128-bit variant which provides a higher resistance against internal collisions. Compared with the existing schemes, our lightweight MACs are both time and resource efficient on hardware-constrained devices. 展开更多
关键词 message authentication code body sensor network low-resource implementation
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