Enhancing Relational Triple Extraction in Specific Domains:Semantic Enhancement and Synergy of Large Language Models and Small Pre-Trained Language Models

In the process of constructing domain-specific knowledge graphs,the task of relational triple extraction plays a critical role in transforming unstructured text into structured information.Existing relational triple extraction models facemultiple challenges when processing domain-specific data,including insufficient utilization of semantic interaction information between entities and relations,difficulties in handling challenging samples,and the scarcity of domain-specific datasets.To address these issues,our study introduces three innovative components:Relation semantic enhancement,data augmentation,and a voting strategy,all designed to significantly improve the model’s performance in tackling domain-specific relational triple extraction tasks.We first propose an innovative attention interaction module.This method significantly enhances the semantic interaction capabilities between entities and relations by integrating semantic information fromrelation labels.Second,we propose a voting strategy that effectively combines the strengths of large languagemodels(LLMs)and fine-tuned small pre-trained language models(SLMs)to reevaluate challenging samples,thereby improving the model’s adaptability in specific domains.Additionally,we explore the use of LLMs for data augmentation,aiming to generate domain-specific datasets to alleviate the scarcity of domain data.Experiments conducted on three domain-specific datasets demonstrate that our model outperforms existing comparative models in several aspects,with F1 scores exceeding the State of the Art models by 2%,1.6%,and 0.6%,respectively,validating the effectiveness and generalizability of our approach.

Mechatronic Modeling and Domain Transformation of Multi-physics Systems

The enhanced definition of Mechatronics involves the four underlying characteristics of integrated,unified,unique,and systematic approaches.In this realm,Mechatronics is not limited to electro-mechanical systems,in the multi-physics sense,but involves other physical domains such as fluid and thermal.This paper summarizes the mechatronic approach to modeling.Linear graphs facilitate the development of state-space models of mechatronic systems,through this approach.The use of linear graphs in mechatronic modeling is outlined and an illustrative example of sound system modeling is given.Both time-domain and frequency-domain approaches are presented for the use of linear graphs.A mechatronic model of a multi-physics system may be simplified by converting all the physical domains into an equivalent single-domain system that is entirely in the output domain of the system.This approach of converting(transforming)physical domains is presented.An illustrative example of a pressure-controlled hydraulic actuator system that operates a mechanical load is given.

Capability requirements modeling and verification based on fuzzy ontology

The capability requirements of the command, control, communication, computing, intelligence, surveillance, reconnaissance （C41SR） systems are full of uncertain and vague information, which makes it difficult to model the C41SR architecture. The paper presents an approach to modeling the capability requirements with the fuzzy unified modeling language （UML） and building domain ontologies with fuzzy description logic （DL）. The UML modeling constructs are extended according to the meta model of Depart- ment of Defense Architecture Framework to improve their domain applicability, the fuzzy modeling mechanism is introduced to model the fuzzy efficiency features of capabilities, and the capability requirement models are converted into ontologies formalized in fuzzy DL so that the model consistency and reasonability can be checked with a DL reasoning system. Finally, a case study of C41SR capability requirements model checking is provided to demonstrate the availability and applicability of the method.

Formalization and Verification of Business Process Modeling Based on UML and Petri Nets

In order to provide a quantitative analysis and verification method for activity diagrams based business process modeling, a formal definition of activity diagrams is introduced. And the basic requirements for activity diagrams based business process models are proposed. Furthermore, the standardized transformation technique between business process models and basic Petri nets is presented and the analysis method for the soundness and well-structured properties of business processes is introduced.

A UML profile for framework modeling

The current standard Unified Modeling Language(UML) could not model framework flexibility and extendibility adequately due to lack of appropriate constructs to distinguish framework hot-spots from kernel elements. A new UML profile that may customize UML for framework modeling was presented using the extension mechanisms of UML, providing a group of UML extensions to meet the needs of framework modeling. In this profile, the extended class diagrams and sequence diagrams were defined to straightforwardly identify the hot-spots and describe their instantiation restrictions. A transformation model based on design patterns was also put forward, such that the profile based framework design diagrams could be automatically mapped to the corresponding implementation diagrams. It was proved that the presented profile makes framework modeling more straightforwardly and therefore easier to understand and instantiate.

Spatial data modeling for coalfield geological environment

Presented a study on the design and implementation of spatial data modelingand application in the spatial data organization and management of a coalfield geologicalenvironment database.Based on analysis of a number of existing data models and takinginto account the unique data structure and characteristic, methodology and key techniquesin the object-oriented spatial data modeling were proposed for the coalfield geological environment.The model building process was developed using object-oriented technologyand the Unified Modeling Language (UML) on the platform of ESRI geodatabase datamodels.A case study of spatial data modeling in UML was presented with successful implementationin the spatial database of the coalfield geological environment.The modelbuilding and implementation provided an effective way of representing the complexity andspecificity of coalfield geological environment spatial data and an integrated managementof spatial and property data.

Modeling and OLAP Cubes for Database of Ground and Municipal Water Supply

Modeling plays an important role for the solution of the complex research problems. When the database became large and complex then it is necessary to create a unified model for getting the desired information in the minimum time and to implement the model in a better way. The present paper deals with the modeling for searching of the desired information from a large database by storing the data inside the three dimensional data cubes. A sample case study is considered as a real data related to the ground water and municipal water supply, which contains the data from the various localities of a city. For the demonstration purpose, a sample size is taken as nine but when it becomes very large for number of localities of different cities then it is necessary to store the data inside data cubes. A well known object-oriented Unified Modeling Language (UML) is used to create Unified class and state models. For verification purpose, sample queries are also performed and corresponding results are depicted.

An Embedded Software Modeling and Process by Using Aspect-Oriented Approach

In recent years, mobile devices have become widespread and refined, and they have offered increased convenience in human life. For these reasons, a variety of embedded systems have been designed. Therefore, improving methods for developing of embedded software systematically has become an important issue. Platform-based design is one example of an embedded-system design method that can reduce the design cost via improving a design’s abstraction level. However, platform-based design lacks precise definitions for platforms and design processes. This paper provides an approach that combines the aspects and platform-based design methods for developing embedded software. The approach is built on platform-based design methodology and uses the separating of concerns (SoC) concept to define the aspects and to reduce the crosscutting concerns in embedded system modeling. For aspect issues, we use the extended UML notation with aspects to describe both the static structure and the dynamic structure of the embedded system. We used an example of a digital photo frame system to demonstrate our approach.

MODELING OF FMS BASED ON UML AND OPNS

As the main component of computer integrated manufacturing system (CIMS), flexible manufacturing system (FMS) should be an open system with reusability and extenchaility. Moreover, as FMS is a complex asynchronous concurrent system, its model also should have the abilities to express the concurrency in the system and to analyze the behavior of the system. It is difficult to use any one method to model such a complex system as FMS. A modeling method using Object-oriented modeling language-unified modeling language (UML) and object-Oriented Petri nets (OPNs) is proposed. Class diagram in UML is used to represent the static relations among the objects in FMS. OPNs are used to model the dynamic behavior of the objects and conduct performance analysis. OPNs also can be used to identify the attributes and operations of the objects. The model can describe the system integrally and can be used to design FMS control software naturally.

基于MBSE的作战能力跨域描述元建模方法

针对作战能力跨域描述存在语义二义性、不利于交流等问题,提出一种基于模型系统工程的元建模方法。抽象出作战能力元模型并给出形式化定义;从能力、作战和信息视角扩展作战能力元模型定义作战能力描述语言;通过UML Profile技术实现作战能力描述语言建模工具;借鉴面向对象分析方法思路提出作战能力描述语言建模方法。以美军“分布式防御”概念为例对提出方法进行实例验证。结果表明,提出的方法易于理解、可靠性和可扩展性强,有效消除语义二义性的同时满足多视角跨域描述作战能力的需求。

基于模型驱动的密码算法可视化开发平台研究

针对密码算法开发平台普适性差、无法跨平台的问题,本文采用模型驱动实现密码算法开发的方法,设计了一种基于模型驱动的密码算法可视化开发平台,提出了一种基于模型驱动的密码算法开发的领域语言—MCL密码元语言;实现了基于模型的代码生成器和代码映射器.实验证明,该开发平台仅需要开发者拖拽图形块的操作就可以实现密码算法模型的建立,然后平台可以根据建立的密码算法模型生成不同编程环境下的代码.平台实现了C和python的代码映射器模块,密码算法模型可快速映射为C、python代码.平台有较好的实用性,开发者的密码算法实现过程简洁、高效,不同编程环境下的代码均可以通过平台自动生成,提高了密码算法实现的跨平台性.

基于语言模型的蛋白质结构域边界预测方法

蛋白质结构域对于蛋白质结构和功能研究具有重要意义。针对目前从头预测蛋白质结构域的方法普遍存在精度不高、耗费资源多等问题,提出了一种基于语言模型的蛋白质结构域边界预测方法DomTransformer,该方法基于蛋白质结构分类数据库(CATH)、蛋白质结构预测关键评估(CASP)竞赛数据,以及在AFDB(AlphaFold protein structure database)基础上建立的域数据库等共同构建数据集,搭建了基于Transformer网络架构和稀疏多头自注意力机制的网络模型,引入了新的特征、接触数和域级MSA(Domain multiple sequence alignment),通过直接预测结构域边界来解决数据不平衡等问题。在独立测试集上的测试结果表明了DomTransformer的有效性。

基于半监督学习的域适应实体解析算法

实体解析旨在查找两个数据实体是否引用同一实体,是许多自然语言处理任务中的一项基本任务。现有的基于深度学习的实体解析解决方案通常需要大量的标注数据,即使利用预训练的语言模型进行训练,仍然需要数千个标签才能达到令人满意的准确性。现实场景中,这些标注数据并不容易获得。针对上述问题,提出了一个基于半监督学习的域适应实体解析模型。首先,在源域上训练一个分类器,然后利用域适应减小源域和目标域的分布差异,同时用数据增强后的目标域软伪标签加入源域迭代训练,从而实现从源域到目标域的知识迁移。在13个来自相同或不同领域的数据集上对所提模型进行了对比实验和消融实验,实验结果表明,与无监督基线模型相比,所提模型在多个数据集上的F1值平均提升了2.84%,9.16%和7.1%;与有监督基线模型相比,所提模型只需要20%~40%的标签就可以达到与有监督学习相当的性能。消融实验进一步证明了所提模型的有效性,其总体上可以获得更好的实体解析结果(相关代码已开源1))。

融合领域词典嵌入的航空不安全事件命名实体识别

针对航空不安全事件领域命名实体识别任务,以航空安全信息周报为数据源,分析并构建航空不安全事件命名实体识别数据集和领域词典。为解决传统命名实体识别模型对于捕获领域实体边界性能较差的问题,基于BERT(bidirectional encoder representations from transformers)预训练语言模型提出融合领域词典嵌入的领域语义信息增强的方法。在自建数据集上进行多次对比实验,结果表明:所提出的方法可以进一步提升实体边界的识别率,相较于传统的双向长短期记忆网络-条件随机场(bi-directional long short term memory-conditional random field,BiLSTM-CRF)命名实体识别模型,性能提升约5%。

Modelica语言及其多领域统一建模与仿真机理

详细介绍了Modelica语言及其主要特点,系统地阐述了Modelica语言的多领域统一建模与仿真原理,分析了Modelica语言适合于复杂系统建模的内在原因,探讨了基于Modelica语言的复杂产品建模方法,综述了基于Modelica语言的建模仿真工具研究现状,总结了采用Modelica语言进行多领域统一建模的优势。

面向业务自动化转型的铁路运输调度业务数据模型构建方法研究

铁路运输生产调度业务自动化、智能化转型改进是推动铁路运输效率提升的重要手段。探讨业务转型过程中对业务各场景各颗粒度控制逻辑和信息流通的梳理建模方法,从而推动业务高效转型,在对运输生产调度业务深入分析的基础上,抽象了调度业务组织的关键影响要素和关键关联关系,梳理了工作流、信息流、信息流通机制与上述抽象的调度业务要素及这些要素间关联关系的对应关系,设计了一种刻画业务工作流、信息流和信息流通机制的数据模型构建方法。考虑到铁路运输生产调度业务分散协作、多级耦合的多层级多场景特点,设计了工作流、信息流数据模型的分化、细化关联机制,以实现对不同层级、场景调度业务的数据模型间有机关系的刻画,最后结合实际调度业务进行了应用分析。结果表明该方法构建的数据模型可以规范调度业务在不同场景、不同颗粒度下的控制逻辑和信息流通,从而为业务自动化转型过程中的信息系统开发和作业流程再造提供参考。

基于知识图谱和预训练语言模型深度融合的可解释生物医学推理

基于预训练语言模型(LM)和知识图谱(KG)的联合推理在应用于生物医学领域时,因其专业术语表示方式多样、语义歧义以及知识图谱存在大量噪声等问题,联合推理模型并未取得较好的效果。基于此,提出一种面向生物医学领域的可解释推理方法DF-GNN。该方法统一了文本和知识图谱的实体表示方式,利用大型生物医学知识库构造子图并进行去噪,改进文本和子图实体的信息交互方式,增加对应文本和子图节点的直接交互,使得两个模态的信息能够深度融合。同时,利用知识图谱的路径信息对模型推理过程提供了可解释性。在公开数据集MedQA-USMLE和MedMCQA上的测试结果表明,与现有的生物医学领域联合推理模型相比,DF-GNN可以更可靠地利用结构化知识进行推理并提供解释性。

多领域建模语言Modelica类型解析研究与实现

类型解析是编译器开发的一项重要工作,也是语义分析的一个最重要组成部分。基于Modelica建模语言,研究了编译器类型系统的作用域、类型检查等关键技术,提出了类型系统的解析和查找机制,实现了类型检查及错误处理机制,并在多领域物理系统建模与仿真平台MWorks系统中得到应用。

多体动力学模型的Modelica语言建模

对Adams多体模型结构及Modelica模型的转换方法进行了研究。对多体动力学模型结构及建模方式进行分析,根据Adams多体模型结构设计了对应的Modelica多体模型结构。研究了Adams多体模型各组件包含的信息,以及与Modelica模型的异同,提出了各多体组件的转换方法。最后给出了多体模型转换验证实例与结果。该研究有助于提高多领域仿真系统的多体建模效率及与传统多体系统的兼容性。

问答式林业预训练语言模型ForestBERT

【目的】针对林业文本利用率低、通用领域预训练语言模型对林业知识理解不足以及手动标注数据耗时费力等问题,基于大量林业文本,提出一种融合林业领域知识的预训练语言模型,并通过自动标注训练数据,高效实现林业抽取式问答,为林业决策管理提供智能化信息服务。【方法】首先,基于网络爬虫技术构建包含术语、法律法规和文献3个主题的林业语料库,使用该语料库对通用领域预训练语言模型BERT进行继续预训练,再通过掩码语言模型和下一句预测这2个任务进行自监督学习,使BERT能够有效地学习林业语义信息,得到具有林业文本通用特征的预训练语言模型ForestBERT。然后,对预训练语言模型mT5进行微调,实现样本的自动标注,通过人工校正后,构建包含3个主题共2280个样本的林业抽取式问答数据集。基于该数据集对BERT、RoBERTa、MacBERT、PERT、ELECTRA、LERT 6个通用领域的中文预训练语言模型以及本研究构建的ForestBERT进行训练和验证,以明确ForestBERT的优势。为探究不同主题对模型性能的影响,分别基于林业术语、林业法律法规、林业文献3个主题数据集对所有模型进行微调。将ForestBERT与BERT在林业文献中的问答结果进行可视化比较,以更直观展现ForestBERT的优势。【结果】ForestBERT在林业领域的抽取式问答任务中整体表现优于其他6个对比模型,与基础模型BERT相比,精确匹配(EM)分数和F1分数分别提升1.6%和1.72%,在另外5个模型的平均性能上也均提升0.96%。在各个模型最优划分比例下,ForestBERT在EM上分别优于BERT和其他5个模型2.12%和1.2%,在F1上分别优于1.88%和1.26%。此外,ForestBERT在3个林业主题上也均表现优异,术语、法律法规、文献任务的评估分数分别比其他6个模型平均提升3.06%、1.73%、2.76%。在所有模型中,术语任务表现最佳,F1的平均值达到87.63%,表现较差的法律法规也达到82.32%。在文献抽取式问答任务中,ForestBERT相比BERT可提供更准确、全面的答案。【结论】采用继续预训练的方式增强通用领域预训练语言模型的林业专业知识,可有效提升模型在林业抽取式问答任务中的表现,为林业文本和其他领域的文本处理和应用提供一种新思路。