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.

A Railway Fastener Inspection Method Based on Abnormal Sample Generation

Regular fastener detection is necessary to ensure the safety of railways.However,the number of abnormal fasteners is significantly lower than the number of normal fasteners in real railways.Existing supervised inspectionmethods have insufficient detection ability in cases of imbalanced samples.To solve this problem,we propose an approach based on deep convolutional neural networks(DCNNs),which consists of three stages:fastener localization,abnormal fastener sample generation based on saliency detection,and fastener state inspection.First,a lightweight YOLOv5s is designed to achieve fast and precise localization of fastener regions.Then,the foreground clip region of a fastener image is extracted by the designed fastener saliency detection network(F-SDNet),combined with data augmentation to generate a large number of abnormal fastener samples and balance the number of abnormal and normal samples.Finally,a fastener inspection model called Fastener ResNet-8 is constructed by being trained with the augmented fastener dataset.Results show the effectiveness of our proposed method in solving the problem of sample imbalance in fastener detection.Qualitative and quantitative comparisons show that the proposed F-SDNet outperforms other state-of-the-art methods in clip region extraction,reaching MAE and max F-measure of 0.0215 and 0.9635,respectively.In addition,the FPS of the fastener state inspection model reached 86.2,and the average accuracy reached 98.7%on 614 augmented fastener test sets and 99.9%on 7505 real fastener datasets.

Unmanned Aerial Vehicle Inspection Routing and Scheduling for Engineering Management

Technological advancements in unmanned aerial vehicles(UAVs)have revolutionized various industries,enabling the widespread adoption of UAV-based solutions.In engineering management,UAV-based inspection has emerged as a highly efficient method for identifying hidden risks in high-risk construction environments,surpassing traditional inspection techniques.Building on this foundation,this paper delves into the optimization of UAV inspection routing and scheduling,addressing the complexity introduced by factors such as no-fly zones,monitoring-interval time windows,and multiple monitoring rounds.To tackle this challenging problem,we propose a mixed-integer linear programming(MILP)model that optimizes inspection task assignments,monitoring sequence schedules,and charging decisions.The comprehensive consideration of these factors differentiates our problem from conventional vehicle routing problem(VRP),leading to a mathematically intractable model for commercial solvers in the case of large-scale instances.To overcome this limitation,we design a tailored variable neighborhood search(VNS)metaheuristic,customizing the algorithm to efficiently solve our model.Extensive numerical experiments are conducted to validate the efficacy of our proposed algorithm,demonstrating its scalability for both large-scale and real-scale instances.Sensitivity experiments and a case study based on an actual engineering project are also conducted,providing valuable insights for engineering managers to enhance inspection work efficiency.

A Systematic Review of Computer Vision Techniques for Quality Control in End-of-Line Visual Inspection of Antenna Parts

The rapid evolution of wireless communication technologies has underscored the critical role of antennas in ensuring seamless connectivity.Antenna defects,ranging from manufacturing imperfections to environmental wear,pose significant challenges to the reliability and performance of communication systems.This review paper navigates the landscape of antenna defect detection,emphasizing the need for a nuanced understanding of various defect types and the associated challenges in visual detection.This review paper serves as a valuable resource for researchers,engineers,and practitioners engaged in the design and maintenance of communication systems.The insights presented here pave the way for enhanced reliability in antenna systems through targeted defect detection measures.In this study,a comprehensive literature analysis on computer vision algorithms that are employed in end-of-line visual inspection of antenna parts is presented.The PRISMA principles will be followed throughout the review,and its goals are to provide a summary of recent research,identify relevant computer vision techniques,and evaluate how effective these techniques are in discovering defects during inspections.It contains articles from scholarly journals as well as papers presented at conferences up until June 2023.This research utilized search phrases that were relevant,and papers were chosen based on whether or not they met certain inclusion and exclusion criteria.In this study,several different computer vision approaches,such as feature extraction and defect classification,are broken down and analyzed.Additionally,their applicability and performance are discussed.The review highlights the significance of utilizing a wide variety of datasets and measurement criteria.The findings of this study add to the existing body of knowledge and point researchers in the direction of promising new areas of investigation,such as real-time inspection systems and multispectral imaging.This review,on its whole,offers a complete study of computer vision approaches for quality control in antenna parts.It does so by providing helpful insights and drawing attention to areas that require additional exploration.

DELAY-TIME MODEL BASED ON IMPERFECT INSPECTION OF AIRCRAFT STRUCTURE WITHIN FINITE TIME SPAN

According to the failure characteristics of aircraft structure, a delay-time model is an effective method to optimize maintenance for aircraft structure. To imitate the practical situation as much as possible, imperfect inspections, thresholds and repeated intervals are concerned in delay-time models. Since the suggestion by the existing delay-time models that the inspections are implemented in an infinite time span lacks practical value, a de- lay-time model with imperfect inspection within a finite time span is proposed. In the model, the nonhomogenous Poisson process is adopted to obtain the renewal probabilities between two different successive inspections on de- fects or failures. An algorithm is applied based on the Nelder-Mead downhill simplex method to solve the model. Finally, a numerical example proves the validity and effectiveness of the model.

Inhibition of growth and metastasis of triple-negative breast cancer targeted by Traditional Chinese Medicine Tubeimu in orthotopic mice models

Objective： Triple-negative breast cancer（TNBC） is highly invasive and metastatic, which is in urgent need of transformative therapeutics. Tubeimu（TBM）, the rhizome of Bolbostemma paniculatum（Maxim.） Franquet, is one of the Chinese medicinal herbs used for breast diseases since the ancient times. The present study evaluated the efficacy, especially the anti-metastatic effects of the dichloromethane extract of Tubeimu（ETBM） on TNBC orthotopic mouse models and cell lines.Methods： We applied real-time imaging on florescent orthotopic TNBC mice model and tested cell migration and invasion abilities with MDA-MB-231 cell line. Digital gene expression sequencing was performed and Kyoto Encyclopedia of Genes and Genomes（KEGG） analysis applied to explore the pathways influenced by ETBM.Moreover, quantitative real-time polymerase chain reactions（q RT-PCR） and Western blot were delivered to confirm the gene expression changes.Results： ETBM exhibited noticeable control on tumor metastasis and growth of TNBC tumors with no obvious toxicity. In compliance with this, it also showed inhibition of cell migration and invasion in vitro. Its impact on the changed biological behavior in TNBC may be a result of decreased expression of integrin β1（ITGβ1）, integrin β8（ITGβ8） and Rho GTPase activating protein 5（ARHGAP5）, which disabled the focal adhesion pathway and caused change in cell morphology.Conclusions： This study reveals that ETBM has anti-metastatic effects on MDA-MB-231-GFP tumor and may lead to a new therapeutic agent for the integrative treatment of highly invasive TNBC.

绿色认知、组织支持对粮农绿色生产技术采纳影响--基于Triple-Hurdle模型的分析

基于粮食主产区山东省319户粮农的微观数据,将粮农的绿色生产技术采纳划分为绿色生产技术采纳意愿、采纳行为、采纳程度3个方面,运用Triple-Hurdle模型进行分析研究。结果表明:绿色认知、组织支持对粮农绿色生产技术的采纳意愿、采纳行为和采纳程度具有显著正向影响;组织支持能正向调节绿色认知对粮农绿色生产采纳的影响,但在不同阶段调节效应有差异;绿色认知对粮农的绿色生产技术采纳具有组群差异,绿色认知对于大规模粮农和年轻粮农的绿色生产技术采纳影响更大。

Modeling of a triple reduced surface field silicon-on-insulator lateral double-diffused metal–oxide–semiconductor field-effect transistor with low on-state resistance

An analytical model for a novel triple reduced surface field（RESURF） silicon-on-insulator（SOI） lateral doublediffused metal–oxide–semiconductor（LDMOS） field effect transistor with n-type top（N-top） layer, which can obtain a low on-state resistance, is proposed in this paper. The analytical model for surface potential and electric field distributions of the novel triple RESURF SOI LDMOS is presented by solving the two-dimensional（2D） Poisson＇s equation, which can also be applied to single, double and conventional triple RESURF SOI structures. The breakdown voltage（BV） is formulized to quantify the breakdown characteristic. Besides, the optimal integrated charge of N-top layer（Q_（ntop）） is derived, which can give guidance for doping the N-top layer. All the analytical results are well verified by numerical simulation results,showing the validity of the presented model. Hence, the proposed model can be a good tool for the device designers to provide accurate first-order design schemes and physical insights into the high voltage triple RESURF SOI device with N-top layer.

Modelling and Backstepping Motion Control of the Aircraft Skin Inspection Robot

Aircraft skin health concerns whether the aircraft can fly safely.In this paper,an improved mechanical structure of the aircraft skin inspection robot was introduced.Considering that the aircraft skin surface is a curved environment,we assume that the curved environment is equivalent to an inclined plane with a change in inclination.Based on this assumption,the Cartesian dynamics model of the robot is established using the Lagrange method.In order to control the robot’s movement position accurately,a position backstepping control scheme for the aircraft skin inspection robot was presented.According to the dynamic model and taking into account the problems faced by the robot during its movement,a position constrained controller of the aircraft skin inspection robot is designed using the barrier Lyapunov function.Aiming at the disturbances in the robot,we adopt a fuzzy system to approximate the unknown dynamics related with system states.Finally,the simulation results of the designed position constrained controller were compared with the sliding mode controller,and prove the validity of the position constrained controller.

Unstructured Road Extraction in UAV Images based on Lightweight Model

There is no unified planning standard for unstructured roads,and the morphological structures of these roads are complex and varied.It is important to maintain a balance between accuracy and speed for unstructured road extraction models.Unstructured road extraction algorithms based on deep learning have problems such as high model complexity,high computational cost,and the inability to adapt to current edge computing devices.Therefore,it is best to use lightweight network models.Considering the need for lightweight models and the characteristics of unstructured roads with different pattern shapes,such as blocks and strips,a TMB(Triple Multi-Block)feature extraction module is proposed,and the overall structure of the TMBNet network is described.The TMB module was compared with SS-nbt,Non-bottleneck-1D,and other modules via experiments.The feasibility and effectiveness of the TMB module design were proven through experiments and visualizations.The comparison experiment,using multiple convolution kernel categories,proved that the TMB module can improve the segmentation accuracy of the network.The comparison with different semantic segmentation networks demonstrates that the TMBNet network has advantages in terms of unstructured road extraction.

Universal triple I fuzzy reasoning algorithm of function model based on quotient space

Aiming at the deficiencies of analysis capacity from different levels and fuzzy treating method in product function modeling of conceptual design, the theory of quotient space and universal triple I fuzzy reasoning method are introduced, and then the function modeling algorithm based on the universal triple I fuzzy reasoning method is proposed. Firstly, the product function granular model based on the quotient space theory is built, with its function granular representation and computing rules defined at the same time. Secondly, in order to quickly achieve function granular model from function requirement, the function modeling method based on universal triple I fuzzy reasoning is put forward. Within the fuzzy reasoning of universal triple I method, the small-distance-activating method is proposed as the kernel of fuzzy reasoning; how to change function requirements to fuzzy ones, fuzzy computing methods, and strategy of fuzzy reasoning are respectively investigated as well; the function modeling algorithm based on the universal triple I fuzzy reasoning method is achieved. Lastly, the validity of the function granular model and function modeling algorithm is validated. Through our method, the reasonable function granular model can be quickly achieved from function requirements, and the fuzzy character of conceptual design can be well handled, which greatly improves conceptual design.

Cost-Benefit Assessment of Inspection and Repair Planning for Ship Structures Considering Corrosion Model Uncertainty

Owing to high costs and unnecessary inspections necessitated by the traditional inspection planning for ship structures, the risk-based inspection and repair planning should be investigated for the most cost-effective inspection. This paper aims to propose a cost-benefit assessment model of risk-based inspection and repair planning for ship structures subjected to corrosion deterioration. Then, the benefit-cost ratio is taken to be an index for the selection of the optimal inspection and repair strategy. The planning problem is formulated as an optimization problem where the benefit-cost ratio for the expected lifetime is maximized with a constraint on the minimum acceptalbe reliability index. To account for the effect of corrosion model uncertainty on the cost-benefit assessment, two corrosion models, namgly, Paik＇ s model and Guedes Soares＇ model, are adopted for analysis. A numerical example is presented to illustrate the proposed method. Sensitivity studies are also providet. The results indicate that the proposed method of risk-based cost-benefit analysis can effectively integrate the economy with reliability of the inspection and repair planning. A balance can be achieved between the risk cost and total expected inspection and repair costs with the proposed method, which is very. effective in selecting the optimal inspection and repair strategy. It is pointed out that the corrosion model uncertainty and parametric uncertaintg have a significant impact on the cost-benefit assessment of inspection and repair planning.

Combination Therapy of Capecitabine with Cyclophosphamide as a Second-Line Treatment after Failure of Paclitaxel plus Bevacizumab Treatment in a Human Triple Negative Breast Cancer Xenograft Model

We examined the antitumor efficacy of the capecitabine (CAPE) plus cyclophosphamide (CPA) combination as a 2nd-line therapy after paclitaxel (PTX) plus bevacizumab (BEV) treatment in a xenograft model of human triple negative breast cancer (TNBC) cell line, MX-1. After tumor growth was confirmed, PTX (20 mg/kg;i.v.) + BEV (5 mg/kg;i.p.) treatment was started (Day 1). Each agent was administered once a week for 5 weeks and tumor regression was observed for at least the first 3 weeks. For 2nd-line treatment, we selected mice in which the tumor volume had increased from day 29 to day 36 and was within 130 - 250 mm3 on day 36. After randomization of mice selected on day 36, CPA (10 mg/kg;p.o.) and CAPE (539 mg/kg;p.o.) were administered daily for 14 days (days 36 - 49), followed by cessation of the drugs for 1 week. The tumor growth on day 57 was significantly suppressed in the CPA, CAPE and CAPE + CPA groups as compared with the control group (p < 0.05). Furthermore, the antitumor activity on day 57 of CAPE + CPA was significantly stronger than that of CPA or CAPE alone (p < 0.05). The thymidine phosphorylase (TP) level in tumor tissue was evaluated by immunohistochemistry on day 50, and was significantly higher in the CPA group than those in the control group (p < 0.05). Upregulation of TP in tumor tissues by CPA treatment would increase the 5-FU level in tumor tissues treated with CAPE. This would explain the possible mechanism that made CAPE + CPA superior to CAPE alone in the 2nd-line treatment. Our preclinical results suggest that the CAPE + CPA combination therapy may be effective as 2nd-line therapy after disease progression in PTX + BEV 1st-line treatment for TNBC patients.

Dynamic simulation and experimental study of inspection robot for high-voltage transmission-line

A mobile robot developed by Wuhan University for full-path hotline inspection on 220 kV transmission lines was presented. With 4 rotating joints and 2 translational ones, such robot is capable of traveling along non- obstaclestraight-line segment and surmounting straight-line segment obstacles as well as transferring between two spans automatically. Lagrange’s equations were utilized to derive dynamic equations of all the links, including items of inertia, coupling inertia, Coriolis acceleration, centripetal acceleration and gravity. And a dynamic response experiment on elemental motions of robot prototype’s travelling along non-obstacle straight-line segment and surmounting obstacles was performed on 220 kV 1∶1 simulative overhanging transmission-line in laboratory. In addition, dynamic numerical simulation was conducted in the corresponding condition. Comparison and analysis on results of experiment and numerical simulation have validated theoretical model and simulation resolution. Therefore, the dynamic model formed hereunder can be used for the study of robot control.

Game Analysis and Countermeasures on Increasing Prices of Agricultural Products under Triple Supply Chain

From the perspective of supply chain of agricultural products,by establishing Stackelberg game model based on triple supply chain,this paper researches the price formation and profit distribution mechanism of agricultural products under circumstance of non-cooperation and cooperation.The results show the main factors responsible for the hiking of prices of agricultural products as follows:the cost of agricultural products climbs incessantly;the circulation cost hovers at high level;the factor inputs of agricultural products are short;inflation pressure is incessantly mounting;the profit distribution of supply chain is irrational.Finally,corresponding countermeasures are put forward.

Risk Based Optimal Inspection and Repair Planning for Ship Structures Subjected to Corrosion Deterioration

A framework of risk based inspection and repair planning was presented to optimize for the ship structures subjected to corrosion deterioration. The planning problem was formulated as an optimization problem where the expected lifetime costs were minimized with a constraint on the minimum acceptable reliability index. The safety margins were established for the inspection events, the repair events and the failure events for ship structures. Moreover, the formulae were derived to calculate failure probabilities and repair probabilities. Based on them, a component subjected to corrosion is investigated for illustration of the process of selecting the optimal inspection and repair strategy. Furthermore, some sensitivity studies were provided. The results show that the optimal inspection instants should take place before the reliability index reaches the minimum acceptable reliability index. The optimal target failure probability is 10 -3 . In addition, a balance can be achieved between the risk cost and total expected inspection and repair costs by means of the risk-based optimal inspection and repair method, which is very effective in selecting the optimal inspection and repair strategy.

Wafer bin map inspection based on DenseNet

Wafer bin map(WBM)inspection is a critical approach for evaluating the semiconductor manufacturing process.An excellent inspection algorithm can improve the production efficiency and yield.This paper proposes a WBM defect pattern inspection strategy based on the DenseNet deep learning model,the structure and training loss function are improved according to the characteristics of the WBM.In addition,a constrained mean filtering algorithm is proposed to filter the noise grains.In model prediction,an entropy-based Monte Carlo dropout algorithm is employed to quantify the uncertainty of the model decision.The experimental results show that the recognition ability of the improved DenseNet is better than that of traditional algorithms in terms of typical WBM defect patterns.Analyzing the model uncertainty can not only effectively reduce the miss or false detection rate but also help to identify new patterns.

Joint optimization of inspection, maintenance, and spare ordering policy considering defective products loss

This paper proposes a joint inspection-based maintenance and spare ordering optimization policy that considers the problem of integrated inspection,preventive maintenance,spare ordering,and quality control for a four-state single-unit manufacturing system.When an inspection detects a minor defect,a second phase inspection is initiated and a regular order is placed.Product quality begins to deteriorate when the system undergoes a severe defect.To counter this,an advanced replacement of the minor defective system is carried out at the Jth second phase inspection.If a severe defect is recognized prior to the Jth inspection,or if system failure occurs,preventive or corrective replacement is executed.The timeliness of replacement depends on the availability of spare.We adopt two modes of ordering:a regular order and an emergency order.Meanwhile,a threshold level is introduced to determine whether an emergency order is preferred even when the regular order is already ordered but has not yet arrived.The optimal joint inspection-based maintenance and spare ordering policy is formulated by minimizing the expected cost per unit time.A simulation algorithm is proposed to obtain the optimal two-phase inspection interval,threshold level and advanced replacement interval.Results from several numerical examples demonstrate that,in terms of the expected cost per unit time,our proposed model is superior to some existing models.

图形化本体模型到N-TRIPLES文本转化方法研究

分析了图形化本体编辑器VOEDITROR中的OWL构造子分类方法,提出了将图形化本体模型转化为N-TRIPLES格式文本的算法,解决了可视化本体建模工具与Oracle11g之间的整合问题。目前这套算法已经应用于以VOEDTIOR、VOQUERY和Ora-cle11g为核心的基于语义Web技术的网上资源整合平台中。

Structural transformation and energy analysis for pile-up dislocations at triple junction of grain boundary

An energy model for the structure transformation of pile-ups of grain boundary dislocations(GBD)at the triple-junction of the grain boundary of ultrafine-grain materials was proposed.The energy of the pile-up of the GBD in the system was calculated by the energy model,the critical geometric and mechanical conditions for the structure transformation of head dislocation of the pile-up were analyzed,and the influence of the number density of the dislocations and the angle between Burgers vectors of two decomposed dislocations on the transformation mode of head dislocation was discussed.The results show when the GBD is accumulated at triple junction,the head dislocation of the GBD is decomposed into two Burgers vectors of these dislocations unless the angle between the two vectors is less than 90°,and the increase of applied external stress can reduce the energy barrier of the dislocation decomposition.The mechanism that the ultrafine-grained metal material has both high strength and plasticity owing to the structure transformation of the pile-up of the GBD at the triple junction of the grain boundary is revealed.