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.

QUICK ASSESSMENT METHODOLOGY FOR RELIABILITY OF SOLDER JOINTS IN BALL GRID ARRAY (BGA) ASSEMBLY——PART Ⅰ: CREEP CONSTITUTIVE RELATION AND FATIGUE MODEL

In this study, a new unified creep constitutive relation and a mod- ified energy-based fatigue model have been established respectively to describe the creep flow and predict the fatigue life of Sn-Pb solders. It is found that the relation successfully elucidates the creep mechanism related to current constitutive relations. The model can be used to describe the temperature and frequency dependent low cycle fatigue behavior of the solder. The relation and the model are further employed in part Ⅱ to develop the numerical simulation approach for the long-term reliability assessment of the plastic ball grid array (BGA) assembly.

Method of Numerical Modeling for Constitutive Relations of Clay

In order to study the method of numerical modeling for constitutive relations of clay, on the basis of the principle of interaction between plastic volumetric strain and plastic generalized shear strain, the two constitutive functionals that include the function of stress path were used as the basic framework of the constitutive model, which are able to demonstrate the dependence of stress path. The two partial differential cross terms appear in the expression of stress-strain increment relation, which are used to demonstrate the interaction between plastic volumetric strain and plastic generalized shear strain. The elasoplastic constitutive models of clay under two kinds of stress paths, CTC and TC, have been constracted using the triaxtal test results. The three basic characteristics of deformation of soils, pressure sensitivity, dilatancy, and dependence of stress path, are well explained using these two models. Using visualization, the three-dimensional surfaces of shear and volume strains in the whole stress field under stress paths of CTC and TC are given. In addition, the two families of shear and volmetric yield Ioei under CTC and TC paths are plotted respectively. By comparing the results of deformation under these two stress paths, it has been found that, there are obvious differences in the strain peaks, the shapes of strain surfaces, and the trends of variation of volumetric yield loci, however both families of shear yield loci are similar. These results demonstrate that the influences of stress path on the constitutive relations of clay are considerably large and not negligible. The nmericul modeling method that can sufficiently reflect the dependence of stress path is superior to the traditional one.

Neural Network Model for the Constitutive Relations of Soil

The soil constitutive relation is one of the important issues in soil mechanics. It is very difficult to establish mathematical models because of the complexity of soil mechanical behavior. We propose a new method of neural network analysis for establishing soil constitutive models. Based on triaxial experiments of sand in the laboratory, the nonlinear constitutive models of sand expressed by the neural network were set up. In comparison with Duncan\|Chang's model, the neural network method for sand modeling has been proved to be more convenient, accurate and it has a strong fault\|tolerance function.

Artificial neural network model of constitutive relations for shock-prestrained copper

Data from the deformation on Split Hopkinson Bar were used for constructing an artificial neural network model. When putting the thermodynamic parameters of the metals into the trained network model, the corresponding yielding stress can be predicted. The results show that the systematic error is small when the objective function is 0.5 , the number of the nodes in the hidden layer is 6 and the learning rate is about 0.1 , and the accuracy of the rate error is less than 3%. [

Theory of numerical modeling of constitutive relation for geotechnical materials

Under the direction of the principle of interaction between plastic volumetric and shear strains, the general expression of constitutive relation for geotechnical materials has been derived within the framework of irreversible thermo- dynamics. The constitutive modeling, in fact, is an inverse problem that belongs to the medium inverse problems of model identification, which is expressed as a reversion of coefficient of differential equation. Thus the constitutive modeling of geotechnical materials will become the reversion of coefficient functions of the general expression of constitutive relation, which is carried out in the stress field （p,q） by means Of numerical techniques, so that is called numerical modeling. Applying the numerical modeling, a number of plasticity-based models for clay and sand have been obtained, which are able to characterize the fundamental features of deformation for geotechnieal materials. In addition, the approach of numerical modeling also can be applied to the situation of unsaturated soils by means of the Bishop＇s effective stress formula and Khalili＇s expression of effective stress parameter.

Solving Arithmetic Word Problems of Entailing Deep Implicit Relations by Qualia Syntax-Semantic Model

Solving arithmetic word problems that entail deep implicit relations is still a challenging problem.However,significant progress has been made in solving Arithmetic Word Problems(AWP)over the past six decades.This paper proposes to discover deep implicit relations by qualia inference to solve Arithmetic Word Problems entailing Deep Implicit Relations(DIR-AWP),such as entailing commonsense or subject-domain knowledge involved in the problem-solving process.This paper proposes to take three steps to solve DIR-AWPs,in which the first three steps are used to conduct the qualia inference process.The first step uses the prepared set of qualia-quantity models to identify qualia scenes from the explicit relations extracted by the Syntax-Semantic(S2)method from the given problem.The second step adds missing entities and deep implicit relations in order using the identified qualia scenes and the qualia-quantity models,respectively.The third step distills the relations for solving the given problem by pruning the spare branches of the qualia dependency graph of all the acquired relations.The research contributes to the field by presenting a comprehensive approach combining explicit and implicit knowledge to enhance reasoning abilities.The experimental results on Math23K demonstrate hat the proposed algorithm is superior to the baseline algorithms in solving AWPs requiring deep implicit relations.

Interpersonal Perception in Virtual Groups: Examining Homophily, Identification and Individual Attraction Using Social Relations Model in Network

With the penetration of the Internet, virtual groups have become more and more popular. The reliability and accuracy of interpersonal perception in the virtual environment is an intriguing issue. Using the Social relations model (SRM) [1], this paper investigates interpersonal perception in virtual groups from a multilevel perspective. In particular, it examines the following three areas: homophily, identification, and individual attraction, and explores how much of these directional and dyadic relational evaluations can be attributed to the effect of the actor, the partner, and the relationship.

ELASTIC-PLASTIC CONSTITUTIVE RELATION OF PARTICLE REINFORCED COMPOSITES

In this paper, a systematic approach is proposed to obtain the macroscopic elastic-plastic constitutive relation of particle reinforced composites (PRC). The strain energy density of PRC is analyzed based on the cell model, and the analytical formula for the macro-constitutive relation of PRC is obtained. The strength effects of volume fraction of the particle and the strain hardening exponent of matrix material on the macro-constitutive relation are investigated, the relation curve of strain versus stress of PRC is calculated in detail. The present results are consistent with the results given in the existing references.

Conducting a Correlation Model Between TCM Constitution and Physical Examination Index Based on BPNN Algorithm

This paper studies the correlation between Traditional Chinese Medicine(TCM)Constitution discrimination and physical examination index based on BPNN algorithm.253cases of routine urine test were used to build a linkage model between TCM Constitution and physical indicators via BPNN algorithm.According to the test,the correct rate of learning and test group are60%and40%,respectively.A strong correlation was found between TCM Constitution and physical examination indexes.By applying cutting-edge knowledge and technologies,the development and modernization process of TCM can be greatly promoted.

One-dimensional Incremental Constitutive Relation of SMA Wire Reinforced Smart Composites with Damages

A new Martensitic transformation kinetic model for shape memory alloy （SMA） is proposed based on the phenomenological description of the Martensitic transformation heat flow-temperature curve and on the linear relationship between the partial derivatives of Martensite fraction and of Gbbis free energy with respect to the temperature. A meso-mechanical model is developed to describe the longitudinal stiffness reduction and thermo-dilatation variation of the composites caused by fiber breaking or fiber peeling off the base material. One-dimensional incremental constitutive relation is then established for SMA wire reinforced smart composites with damages by introducing three parameters to respectively describe the extent of fiber breaking, fiber peeling off the base material and interface weakening. The results presented herein may provide a theoretical basis for further studying on SMA smart composites with damages.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

θ-improved limited tolerance relation model of incomplete information system for evaluation of water conservancy project management modernization

The modernization of water conservancy project management is a complicated engineering system involving a management system, a management method, management personnel, the exertion of social, economic, and ecological effects, and so on. However, indices for evaluating the modernization of water conservancy project management are usually unobtainable in practical applications. Conducting appropriate extension of the classical rough set theory and then applying it to an incomplete information system are the key to the application of the rough set theory Based on analysis of some extended rough set models in incomplete information systems, a rough set model based on the θ-improved limited tolerance relation is put forward. At the same time, upper approximation and lower approximation are defined under this improved relation. According to the evaluation index system and management practices, the threshold for θ is defined. An example study indicates the practicability and maneuverability of the model.

Seepage-stress coupling constitutive model of anisotropic soft rock

To provide a seepage-stress coupling constitutive model that can directly describe the seepage-stress coupling relationship, a series of one-dimensional seepage-stress coupling tests on two kinds of soft rock (argillaceous siltstone and brown mudstone) were performed by using an MTS-815.02 tri-axial rock mechanics test system, with which the stress-strain curves according to the seepage variation were obtained. Based on the experimental results and by employing Hooke's law, the formulation of the coefficient of strain-dependent permeability was presented and introduced to establish a coupling model. In addition, the mathematical expression and the incremental formulation for coupling model were advanced, in which five parameters that can be respectively determined by using the experimental results were included. The calculated results show that the proposed coupling model is capable of simulating the stress-strain relationship with considering the seepage-stress coupling in the nonlinear elastic stage of two kinds of soft rock.

On grey relation projection model based on projection pursuit

Multidimensional grey relation projection value can be synthesized as one-dimensional projection value by using projection pursuit model. The larger the projection value is,the better the model. Thus,according to the projection value,the best one can be chosen from the model aggregation. Because projection pursuit modeling based on accelerating genetic algorithm can simplify the implementation procedure of the projection pursuit technique and overcome its complex calculation as well as the difficulty in implementing its program,a new method can be obtained for choosing the best grey relation projection model based on the projection pursuit technique.

Effects of the Reynolds number on a scale-similarity model of Lagrangian velocity correlations in isotropic turbulent flows

A scale-similarity model of a two-point two-time Lagrangian velocity correlation(LVC) was originally developed for the relative dispersion of tracer particles in isotropic turbulent flows(HE, G. W., JIN, G. D., and ZHAO, X. Scale-similarity model for Lagrangian velocity correlations in isotropic and stationary turbulence. Physical Review E, 80, 066313(2009)). The model can be expressed as a two-point Eulerian space correlation and the dispersion velocity V. The dispersion velocity denotes the rate at which one moving particle departs from another fixed particle. This paper numerically validates the robustness of the scale-similarity model at high Taylor micro-scale Reynolds numbers up to 373, which are much higher than the original values(R_λ = 66, 102). The effect of the Reynolds number on the dispersion velocity in the scale-similarity model is carefully investigated. The results show that the scale-similarity model is more accurate at higher Reynolds numbers because the two-point Lagrangian velocity correlations with different initial spatial separations collapse into a universal form compared with a combination of the initial separation and the temporal separation via the dispersion velocity.Moreover, the dispersion velocity V normalized by the Kolmogorov velocity V_η ≡ η/τ_η in which η and τ_η are the Kolmogorov space and time scales, respectively, scales with the Reynolds number R_λ as V/V_η ∝ R_λ^(1.39) obtained from the numerical data.

Dose-Injury Relation as a Model for Uncertainty Propagation from Input Dose to Target Dose

We study a general framework for assessing the injury probability corresponding to an input dose quantity. In many applications, the true value of input dose may not be directly measurable. Instead, the input dose is estimated from measurable/controllable quantities via numerical simulations using assumed representative parameter values. We aim at developing a simple modeling framework for accommodating all uncertainties, including the discrepancy between the estimated input dose and the true input dose. We first interpret the widely used logistic dose-injury model as the result of dose propagation uncertainty from input dose to target dose at the active site for injury where the binary outcome is completely determined by the target dose. We specify the symmetric logistic dose-injury function using two shape parameters: the median injury dose and the 10 - 90 percentile width. We relate the two shape parameters of injury function to the mean and standard deviation of the dose propagation uncertainty. We find 1) a larger total uncertainty will spread more the dose-response function, increasing the 10 - 90 percentile width and 2) a systematic over-estimate of the input dose will shift the injury probability toward the right along the estimated input dose. This framework provides a way of revising an established injury model for a particular test population to predict the injury model for a new population with different distributions of parameters that affect the dose propagation and dose estimation. In addition to modeling dose propagation uncertainty, we propose a new 3-parameter model to include the skewness of injury function. The proposed 3-parameter function form is based on shifted log-normal distribution of dose propagation uncertainty and is approximately invariant when other uncertainties are added. The proposed 3-parameter function form provides a framework for extending skewed injury model from a test population to a target population in application.

A work-hardening and softening constitutive model for sand:modified plastic strain energy approach

The paper describes an energy-based constitutive model for sand, which is modified based on the modified plastic strain energy approach, represented by a unique relationship between the modified plastic strain energy and a stress parameter, independent of stress history. The modified plastic strain energy approach was developed based on results from a series of drained plastic strain compression tests along various stress paths on saturated dense Toyoura sand with accurate stress and strain measurements. The proposed model is coupled with an isotropically work-hardening and softening, non-associtated, elasto-plastic material description. The constitutive model concerns the inherent and stress system-induced cross-anisotropic elastic deformation properties of sand. It is capable of simulating the deformation characteristics of stress history and stress path, the effects of pressure level, anisotropic strength and void ratio, and the strain localization.

Physico−mathematical model of the voltage−current characteristics of light-emitting diodes with quantum wells based on the Sah−Noyce−Shockley recombination mechanism

Herein,a physical and mathematical model of the voltage−current characteristics of a p−n heterostructure with quantum wells(QWs)is prepared using the Sah−Noyce−Shockley(SNS)recombination mechanism to show the SNS recombination rate of the correction function of the distribution of QWs in the space charge region of diode configuration.A comparison of the model voltage−current characteristics(VCCs)with the experimental ones reveals their adequacy.The technological parameters of the structure of the VCC model are determined experimentally using a nondestructive capacitive approach for determining the impurity distribution profile in the active region of the diode structure with a profile depth resolution of up to 10Å.The correction function in the expression of the recombination rate shows the possibility of determining the derivative of the VCCs of structures with QWs with a nonideality factor of up to 4.