基于NLP构建病历后结构化专病数据库探索与实践

目的/意义建设基于结构化电子病历的专病数据库,提高专病数据库规范性和可用性,提高临床科研工作效率。方法/过程采用模板化输入、自然语言处理等技术,将非结构化电子病历转化为结构化电子病历,基于结构化电子病历构建专病数据库。结果/结论龙华医院基于结构化电子病历建设的银屑病专病数据库分中心,为临床科研人员提供结构化科研数据源,辅助提升分析效率;同时有效支撑上海申康“基于多中心的银屑病专病大数据临床科研随访一体化平台”建设,有助于专病数据库高质量、规模化发展。

一种提高跨语言理解的NLP迁移学习

随着互联网信息的发展,如何有效地表示不同语言所含的信息已成为自然语言处理(Natural Language Processing,NLP)领域的一项重要任务.然而,很多传统的机器学习模型依赖在高资源语言中进行训练,无法迁移到低资源语言中使用.为了解决这一问题,结合迁移学习和深度学习模型,提出一种多语言双向编码器表征量(Multi-lingual Bidirectional Encoder Representations from Transformers,M-BERT)的迁移学习方法.该方法利用M-BERT作为特征提取器,在源语言领域和目标语言领域之间进行特征转换,减小不同语言领域之间的差异,从而提高目标任务在不同领域之间的泛化能力.首先,在构建BERT模型的基础上,通过数据收集处理、训练设置、参数估计和模型训练等预训练操作完成M-BERT模型的构建,并在目标任务上进行微调.然后,利用迁移学习实现M-BERT模型在跨语言文本分析方面的应用.最后,在从英语到法语和德语的跨语言迁移实验中,证明了本文模型具有较高的性能质量和较小的计算量,并在联合训练方案中达到了96.2%的准确率.研究结果表明,该文模型实现了跨语言数据迁移,且验证了其在跨语言NLP领域的有效性和创新性.

NLP技术在红色文化传播领域中的应用分析

红色文化作为中国共产党的宝贵精神财富,蕴含着丰富的革命历史、光荣传统和崇高精神,是新时代大学生思想政治教育的重要资源。随着自然语言处理(NaturalLanguageProcessing,NLP)技术的飞速发展,将其应用于红色文化的传播和教育已成为新的研究方向。NLP技术以其智能化、交互性、个性化的特点,为红色文化的数字化呈现、智能化推荐、交互式体验等提供了有力支撑,有助于提升红色文化传播的效率,促进红色文化在青年学生中的创新传承。本文将聚焦NLP技术在高校红色文化传播中的应用,深入剖析其应用优势、应用思路与应用展望,以期为新时代高校红色文化传播教育提供新思路、新方法,为培养担当民族复兴大任的时代新人提供智力支持。

基于NLP的油气非常规作业风险识别及管控措施推送

本文介绍了一种基于自然语言处理(NLP)技术的油气非常规作业风险识别及管控措施推送方法。该方法通过构建非常规作业JSA知识库和风险智能识别模型,并集成于非常规作业许可管理系统中,实现了对油气非常规作业风险的高效自动识别和针对风险的管控措施精准推送,最终提高油气非常规作业风险管控水平。

自然语言处理(NLP)技术在大型企业采购物料主数据治理实践中的应用研究——以某集团为例

对主数据的研究背景及国内外研究应用现状进行全面介绍;进行企业主数据治理的理论研究,包括主数据治理的构成、方法论及成熟度模型评估;以某集团为例,对物料主数据管理进行需求调研分析,剖析在信息化建设中遇到的问题,引入自然语言处理(NLP)技术,通过模型设计和逐步优化,实现物料分类梳理、属性提取、数据结构化、数据标准化、数据查重等环节的质效提升,设计出了一套适合某集团的物料主数据治理方案;对主数据管理平台进行架构设计、功能模块设计和接口集成设计,使其满足物料主数据管理的要求。与传统物料主数据建设模式比,本技术的核心在于:物料数据识别处理由智能算法代替人工,提高了工作质效,符合技术发展趋势,为包括某集团在内的众多大型企业采购物料标准化建设提供了新路径。

Unlocking the Potential:A Comprehensive Systematic Review of ChatGPT in Natural Language Processing Tasks

As Natural Language Processing(NLP)continues to advance,driven by the emergence of sophisticated large language models such as ChatGPT,there has been a notable growth in research activity.This rapid uptake reflects increasing interest in the field and induces critical inquiries into ChatGPT’s applicability in the NLP domain.This review paper systematically investigates the role of ChatGPT in diverse NLP tasks,including information extraction,Name Entity Recognition(NER),event extraction,relation extraction,Part of Speech(PoS)tagging,text classification,sentiment analysis,emotion recognition and text annotation.The novelty of this work lies in its comprehensive analysis of the existing literature,addressing a critical gap in understanding ChatGPT’s adaptability,limitations,and optimal application.In this paper,we employed a systematic stepwise approach following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)framework to direct our search process and seek relevant studies.Our review reveals ChatGPT’s significant potential in enhancing various NLP tasks.Its adaptability in information extraction tasks,sentiment analysis,and text classification showcases its ability to comprehend diverse contexts and extract meaningful details.Additionally,ChatGPT’s flexibility in annotation tasks reducesmanual efforts and accelerates the annotation process,making it a valuable asset in NLP development and research.Furthermore,GPT-4 and prompt engineering emerge as a complementary mechanism,empowering users to guide the model and enhance overall accuracy.Despite its promising potential,challenges persist.The performance of ChatGP Tneeds tobe testedusingmore extensivedatasets anddiversedata structures.Subsequently,its limitations in handling domain-specific language and the need for fine-tuning in specific applications highlight the importance of further investigations to address these issues.

NLP技术在企业采购管理中的应用探索

企业采购管理是一项十分复杂的工程,因为无论是生产服务、业务开展还是日常运营都需要进行大量采购。随着行业的发展、技术的进步与管理的革新,企业采购项目越来越复杂,且出现了采购计划不科学、重复采购等问题,这严重影响了企业高质量经营管理目标的实现。因此,企业需要在采购管理中融入新观念,运用新方法、新技术来提升采购管理质量。自然语言处理(Natural Language Processing,NLP)技术可以在企业采购计划编制环节,以采购目录为依据对采购需求进行模糊匹配、自动纠错、分类整合,形成精简、科学的采购计划草案,并综合利用近几年采购计划相关资料,对采购项目进行横向与纵向比较。基于此,文章阐述NLP技术在企业采购管理中应用的积极作用,提出NLP技术在企业采购管理中的应用策略,以供参考。

Constraints on Characteristics and Distribution of Gas Hydrate and Free Gas Using Broad-Band Processing of Three-Dimensional Seismic Data

Gas hydrate drilling expeditions in the Pearl River Mouth Basin,South China Sea,have identified concentrated gas hydrates with variable thickness.Moreover,free gas and the coexistence of gas hydrate and free gas have been confirmed by logging,coring,and production tests in the foraminifera-rich silty sediments with complex bottom-simulating reflectors(BSRs).The broad-band processing is conducted on conventional three-dimensional(3D)seismic data to improve the image and detection accuracy of gas hydratebearing layers and delineate the saturation and thickness of gas hydrate-and free gas-bearing sediments.Several geophysical attributes extracted along the base of the gas hydrate stability zone are used to demonstrate the variable distribution and the controlling factors for the differential enrichment of gas hydrate.The inverted gas hydrate saturation at the production zone is over 40% with a thickness of 90 m,showing the interbedded distribution with different boundaries between gas hydrate-and free gas-bearing layers.However,the gas hydrate saturation value at the adjacent canyon is 70%,with 30-m-thick patches and linear features.The lithological and fault controls on gas hydrate and free gas distributions are demonstrated by tracing each gas hydrate-bearing layer.Moreover,the BSR depths based on broad-band reprocessed 3D seismic data not only exhibit variations due to small-scale topographic changes caused by seafloor sedimentation and erosion but also show the upward shift of BSR and the blocky distribution of the coexistence of gas hydrate and free gas in the Pearl River Mouth Basin.

基于Arduino与Processing的心率检测计设计研究

随着社会经济的高速发展,人们的物质生活也有了极大的提高,但同时也伴随着各种疾病的到来,身体健康已经成为人们普遍关注的焦点,因此,心率检测仪、血压计、血糖仪等各种家用医疗监测仪器已经逐渐融入日常生活。心脏病是人们难以预防的突发致命疾病之一,本文介绍的是一款基于Arduino【是基于易用硬件和软件的原型开源平台,包由可编程的电路板(简称微控制器),以及集成开发环境(称为Arduino IDE)的现成软件组成】Processing(开源编程语言,包括编辑器、编译器、展示器)的简易心率检测计系统,其功能实用、操作简单,可以测量心率,当超出正常心率范围时及时预警,是一款便携的实时心率测试仪。

Investigation on taste characteristics and sensory perception of soft-boiled chicken during oral processing based on electronic tongue and electronic nose

The sensory perception of food is a dynamic process,which is closely related to the release of flavor substances during oral processing.It’s not only affected by the food material,but also subjected to the individual oral environment.To explore the oral processing characteristics of soft-boiled chicken,the sensory properties,texture,particle size,viscosity,characteristic values of electronic nose and tongue of different chicken samples were investigated.The correlation analysis showed that the physical characteristics especially the cohesiveness,springiness,resilience of the sample determined oral processing behavior.The addition of chicken skin played a role in lubrication during oral processing.The particle size of the bolus was heightened at the early stage,and the fluidity was enhanced in the end,which reduced the chewing time to the swallowing point and raised the aromatic compounds signal of electronic nose.But the effect of chicken skin on chicken thigh with relatively high fat content,was opposite in electronic nose,which had a certain masking effect on the perception of umami and sweet taste.In conclusion,fat played a critical role in chicken oral processing and chicken thigh had obvious advantages in comprehensive evaluation of soft-boiled chicken,which was more popular among people.

基于NLP技术构建AI运维机器人的探索与实践

随着网络业务的快速发展和网络技术的快速演进,人们对网络运维的要求也随之提高。当下的网络运维存在技术门槛高、闭环效率低、运维一致性差等问题。AI运维机器人基于NLP(Natural Language Processing,自然语言处理)技术,为运维人员提供极简的“对话式”运维操作,智能识别运维意图和操作对象,高效自动化执行任务,有效降低了运维人员的技术门槛,替代烦琐人工操作,有效提升了运维效率,实现了网络运维的提质增效。

A new insight into LPSO phase transformation and mechanical properties uniformity of large-scale Mg-Gd-Y-Zn-Zr alloy prepared by multi-pass friction stir processing

A large-scale fine-grained Mg-Gd-Y-Zn-Zr alloy plate with high strength and ductility was successfully prepared by multi-pass friction stir processing(MFSP)technology in this work.The structure of grains and long period stacking ordered(LPSO)phase were characterized,and the mechanical properties uniformity was investigated.Moreover,a quantitative relationship between the microstructure and tensile yield strength was established.The results showed that the grains in the processed zone(PZ)and interfacial zone(IZ)were refined from 50μm to 3μm and 4μm,respectively,and numerous original LPSO phases were broken.In IZ,some block-shaped 18R LPSO phases were transformed into needle-like 14H LPSO phases due to stacking faults and the short-range diffusion of solute atoms.The severe shear deformation in the form of kinetic energy caused profuse stacking fault to be generated and move rapidly,greatly increasing the transformation rate of LPSO phase.After MFSP,the ultimate tensile strength,yield strength and elongation to failure of the large-scale plate were 367 MPa,305 MPa and 18.0% respectively.Grain refinement and LPSO phase strengthening were the major strengthening mechanisms for the MFSP sample.In particularly,the strength of IZ was comparable to that of PZ because the strength contribution of the 14H LPSO phase offsets the lack of grain refinement strengthening in IZ.This result opposes the widely accepted notion that IZ is a weak region in MFSP-prepared large-scale fine-grained plate.

基于自然语言处理(NLP)的医学知识挖掘探索与实践

目的通过对医学健康知识的挖掘,为人工智能等的健康科普知识支撑提供实践经验。方法采用基于自然语言处理(NLP)技术对徐汇区疾病预防控制中心2010年1月—2021年1月积累的科普文章进行结构拆分、阅读理解、实体识别等,处理流程包括文档预处理、特征提取、段落筛选、阅读理解、答案排序、审核和发布。结果通过直接文档结构拆分,得到5395条问答;通过阅读理解,得到857条问答;通过抽取数字问答,得到1668条,初步形成问答形式的医学健康知识库。结论自然语言处理(NLP)技术为人工智能技术需要的大量语料素材提供了有效制作方法。

NLP技术在智能语音质检中的应用

在数字化时代,智能语音质检成为企业提升工作效率的重要工具,其中自然语言处理(Natural Language Processing,NLP)技术的应用为智能语音质检提供了技术支持。NLP技术通过情感分析、语义分析等手段,使得质检过程更加高效、准确,并降低了质检成本。基于此,探讨了NLP技术在智能语音质检中的应用优势和具体实现方式。

Development and Validation of Integrated Nutrient Management Practices of Industrial Processing Varieties: Asterix and Courage in Bangladesh

An experiment was meticulously conducted at the research field of Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur, Bangladesh, during the 2011-2012 potato growing season to develop integrated crop management practices for the potato seed production of industrial processing varieties Asterix and Courage. Significantly, higher growth and yield parameters were found in the BADC-recommended practice. Later, another experiment was conducted to validate the BADC practice during the 2013-2014 potato growing season in two locations in Bangladesh. Results showed that the production of tuber per hill, tuber weight per hill as well as gross tuber yield per plot, higher proportion of storable seed tubers, and more quality seed potatoes (A-grade and B-grade) seed tubers were found significantly higher in the “BADC developed practice” compared to other treatments. Viral diseases (PLRV and PVY) prevalence was lower in “BADC developed practice”. Moreover, “BADC developed practice” contributed more economic yield by minimizing input cost compared to “Munshiganj advanced farmers’ practice”. Therefore, the “BADC developed practice” was found “superior” regarding yield, quality, and profitability in seed potato production of industrial varieties—Asterix and Courage in Bangladesh.

Literature classification and its applications in condensed matter physics and materials science by natural language processing

The exponential growth of literature is constraining researchers’access to comprehensive information in related fields.While natural language processing(NLP)may offer an effective solution to literature classification,it remains hindered by the lack of labelled dataset.In this article,we introduce a novel method for generating literature classification models through semi-supervised learning,which can generate labelled dataset iteratively with limited human input.We apply this method to train NLP models for classifying literatures related to several research directions,i.e.,battery,superconductor,topological material,and artificial intelligence(AI)in materials science.The trained NLP‘battery’model applied on a larger dataset different from the training and testing dataset can achieve F1 score of 0.738,which indicates the accuracy and reliability of this scheme.Furthermore,our approach demonstrates that even with insufficient data,the not-well-trained model in the first few cycles can identify the relationships among different research fields and facilitate the discovery and understanding of interdisciplinary directions.

基于NLP模型的智能外呼系统研究与设计

自然语言处理(Natural Language Processing,NLP)是人工智能(Artificial Intelligence,AI)领域的重要分支,主要研究使计算机能够理解、翻译、生成和修改人类的自然语言。它利用机器学习算法和模型从海量的语料库中学习语言知识,并应用于自然语言处理,从而实现自动化处理自然语言的目标。基于这一技术,通过建设外呼平台,实现自动拨打电话给客户并在沟通过程中利用机器人对实时语音流进行语音识别,以挖掘客户意图,根据预设的话术模板以真人语音录音或TTS播报形式与客户进行交流。通过识别和筛选单通话内容,高效准确地锁定潜在意向客户,从而实现提高效率、降低成本的目标。

基于NLP的数据采集系统设计与实现研究

NLP作为人工智能领域的一个重要分支,在数据采集系统的发展和研究中起到了关键作用。它帮助人们解决了从大量的文本数据中抽取有价值信息的问题,促进了数据采集的自动化和智能化,文章对NLP在数据采集系统中的应用进行了研究。

Fresh Processing Technology in Polygonatum odoratum Production Area and Its Comparison with Traditional Processing

[Objectives]To compare the effects of traditional processing and fresh processing on the quality of Polygonatum odoratum decoction piece.[Methods]The effects of fresh processing and traditional processing on the quality of P.odoratum decoction piece were compared and analyzed with appearance characteristics,total ash content,extract content,total polysaccharides content,and total flavonoids content as the evaluation indexes.[Results]Fresh processing method in different production areas has different effects on P.odoratum decoction piece.P.odoratum was dried in oven of 50℃.When moisture content was 41.44%-59.67%,it was cut.After complete drying at 50℃,the moisture content of dried P.odoratum was 8.94%-9.60%,and ethanol-soluble extract content was 77.29%-78.20%,and water-soluble extract was 77.7%-78.14%.At this time,the appearance characteristics of section of P.odoratum decoction piece were better than that of traditional processing,which was yellowish white.The total polysaccharide content was higher than that of traditional processing,and the content of total flavonoids was statistically significant different from that of traditional processing.[Conclusions]The quality of P.odoratum decoction piece by fresh processing is better than that of the traditional processing,and it is feasible to use fresh processing.

Modulation of starch digestibility using non-thermal processing techniques:A review

Obesity and type 2 diabetes are widespread throughout the world, especially in developed countries. Starch is an important part of human staple food, the modulating of starch digestibility is conducive to reducing postprandial blood glucose levels and alleviating the chronic disease caused by high caloric intake. The digestion properties of starch are correlated with its structural features, including crystallization, amylose/amylopectin ratio, non-starch components, etc. Among the modified methods applied to regulate starch digestibility, non-thermal processing techniques(NTPT) receive extensive attention due to the characteristics of safety, environmental friendliness and high efficiency. The influence and mechanism of NTPT on the digestion properties of starch are discussed in this review, including ultrasounds, high pressure, γ-irradiation, etc. NTPT induces the alternation of morphological and structural characteristics of native starch, changing their sensitivity to enzymes. The effects of NTPT on the digestibility of starch are highly related to the processing parameters and structure characteristics of native starch. The review shows that NTPT is an effective way to modulate the digestion properties of starch and prevent people from suffering from chronic diseases such as obesity and type 2 diabetes.