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A Lightweight Network with Dual Encoder and Cross Feature Fusion for Cement Pavement Crack Detection

Computer Modeling in Engineering & Sciences 2024年第7期140卷 255-273页

作者： zhong qu Guoqing Mu Bin Yuan School of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing400065China School of Software Engineering Chongqing University of Posts and TelecommunicationsChongqing400065China

Automatic crack detection of cement pavement chiefly benefits from the rapid development of deep learning,with convolutional neural networks(CNN)playing an important role in this field.However,as the performance of crack detection in cement pavement improves,the depth and width of the network structure are significantly increased,which necessitates more computing power and storage space.This limitation hampers the practical implementation of crack detection models on various platforms,particularly portable devices like small mobile devices.To solve these problems,we propose a dual-encoder-based network architecture that focuses on extracting more comprehensive fracture feature information and combines cross-fusion modules and coordinated attention mechanisms formore efficient feature fusion.Firstly,we use small channel convolution to construct shallow feature extractionmodule(SFEM)to extract low-level feature information of cracks in cement pavement images,in order to obtainmore information about cracks in the shallowfeatures of images.In addition,we construct large kernel atrous convolution(LKAC)to enhance crack information,which incorporates coordination attention mechanism for non-crack information filtering,and large kernel atrous convolution with different cores,using different receptive fields to extract more detailed edge and context information.Finally,the three-stage feature map outputs from the shallow feature extraction module is cross-fused with the two-stage feature map outputs from the large kernel atrous convolution module,and the shallow feature and detailed edge feature are fully fused to obtain the final crack prediction map.We evaluate our method on three public crack datasets:DeepCrack,CFD,and Crack500.Experimental results on theDeepCrack dataset demonstrate the effectiveness of our proposed method compared to state-of-the-art crack detection methods,which achieves Precision(P)87.2%,Recall(R)87.7%,and F-score(F1)87.4%.Thanks to our lightweight crack detectionmodel,the parameter count of the mo

关键词： Shallow feature extraction module large kernel atrous convolution dual encoder lightweight network crack detection

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An object detection approach with residual feature fusion and second-order term attention mechanism

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 411-424页

作者： Cuijin Li zhong qu Shengye Wang College of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqingChina College of Electronic Information Chongqing Institute of EngineeringChongqingChina

Automatically detecting and locating remote occlusion small objects from the images of complex traffic environments is a valuable and challenging research.Since the boundary box location is not sufficiently accurate and it is difficult to distinguish overlapping and occluded objects,the authors propose a network model with a second-order term attention mechanism and occlusion loss.First,the backbone network is built on CSPDarkNet53.Then a method is designed for the feature extraction network based on an item-wise attention mechanism,which uses the filtered weighted feature vector to replace the original residual fusion and adds a second-order term to reduce the information loss in the process of fusion and accelerate the convergence of the model.Finally,an objected occlusion regression loss function is studied to reduce the problems of missed detections caused by dense objects.Sufficient experimental results demonstrate that the authors’method achieved state-of-the-art performance without reducing the detection speed.The mAP@.5 of the method is 85.8%on the Foggy_cityscapes dataset and the mAP@.5 of the method is 97.8%on the KITTI dataset.

关键词： artificial intelligence computer vision image processing machine learning neural network object recognition

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Process synthesis for the separation of coal-to-ethanol products

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Chinese Journal of Chemical Engineering 2024年第5期69卷 263-278页

作者： Qingping qu Daoyan Liu Hao Lyu Jinsheng sun School of Chemical Engineering and Technology Tianjin UniversityTianjin 300072China Sustainable Energy and Environment Thrust The Hong Kong University of Science and Technology(Guangzhou)Nansha 511400China

The coal-to-ethanol process,as the clean coal utilization,faces challenges from the energy-intensive distillation that separates multi-component effluents for pure ethanol.Referring to at least eight columns,the synthesis of the ethanol distillation system is impracticable for exhaustive comparison and difficult for conventional superstructure-based optimization as rigorous models are used.This work adopts a superstructure-based framework,which combines the strategy that adaptively selects branches of the state-equipment network and the parallel stochastic algorithm for process synthesis.High-performance computing significantly reduces time consumption,and the adaptive strategy substantially lowers the complexity of the superstructure model.Moreover,parallel computing,elite search,population redistribution,and retention strategies for irrelevant parameters are used to improve the optimization efficiency further.The optimization terminates after 3000 generations,providing a flowsheet solution that applies two non-sharp splitting options in its distillation sequence.As a result,the 59-dimension superstructure-based optimization was solved efficiently via a differential evolution algorithm,and a high-quality solution with a 28.34%lower total annual cost than the benchmark was obtained.Meanwhile,the solution of the superstructure-based optimization is comparable to that obtained by optimizing a single specific configuration one by one.It indicates that the superstructure-based optimization that combines the adaptive strategy can be a promising approach to handling the process synthesis of large-scale and complex chemical processes.

关键词： Coal-to-ethanol Process synthesis Superstructure-based optimization Differential evolution algorithm Distillation

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Improving the high cycle fatigue property of Ti6Al4V ELI alloy by optimizing the surface integrity through electric pulse combined with ultrasonic surface rolling process

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Journal of Materials Science & Technology 2024年第3期170卷 103-121页

作者： Pengfei sun Shengguan qu Chenfeng Duan Xiongfeng Hu Xiaoqiang Li National Engineering Research Center of Near-Net-Shape Forming for Metallic Materials South China University of TechnologyGuangzhou 510640China School of Mechanical and Automotive Engineering South China University of TechnologyGuangzhou 510640China

To improve the surface integrity and high cycle fatigue property of Ti6Al4V ELI alloy,the electric pulse has been introduced into the ultrasonic surface rolling process(USRP),which is called electric pulse-assisted ultrasonic surface rolling process(EUSRP).With the help of“electroplasticity”of the electric pulse,the thickness of the surface gradient deformation layer was about three times of the USRP specimens by adjusting the pulse current level.However,the surface hardness decreases due to the continuous effect of the pulse current and the“skin effect”during treatment.It is worth noting that the higher the applied pulse current,the more severe the softening.This paradox causes the fatigue performance of EUSRP specimens lower than that of USRP specimens.To break this paradox,the EUSRP treatment is followed by a USRP treatment.The EUSRP-2(with a pulse current of 200 A)+USRP specimens exhibit excellent surface hardness,a gradient deformation layer thickness of about 400μm,low surface roughness and high compressive residual compressive stress.Besides,the hardening mechanisms of the different surface strengthening specimens have been quantitatively analyzed in combination with microstructure analysis.The fatigue life of Ti6Al4V ELI alloy can be improved by about 25 times at 780 MPa using the EUSRP-2+USRP treatment,the main reason for the highest fatigue life is the deepest surface gradient layer and the deepest crack initiation site.The fatigue limit of the EUSRP-2+USRP specimens is not the highest because too much surface hardening causes compressive residual stress relaxation during cycling and the beneficial effect of compressive residual stress is eliminated.

关键词： Ti6Al4V ELI alloy Combined surface treatment Transmission electron microscopy Residual stress Fatigue performance

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A novel profile modification HPF-Co gel satisfied with fractured low permeability reservoirs in high temperature and high salinity

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Petroleum Science 2024年第1期21卷 683-693页

作者： Ya-Kai Li Ji-Rui Hou Wei-Peng Wu Ming qu Tuo Liang Wei-Xin zhong Yu-Chen Wen Hai-Tong sun Yi-Nuo Pan China University of Petroleum Beijing Beijing102249China PetroChina Tarim Oilfield Company Korla 841000XinjiangChina Key Laboratory of Improving Oil and Gas Recovery of Ministry of Education Northeast Petroleum University Daqing 163318HeilongjiangChina Xi'an Shiyou University Xi'an 710065ShaanxiChina Northwest Oilfield Company SINOPECUrumqi 830011XinjiangChina

Conformance control and water plugging are a widely used EOR method in mature oilfields.However,majority of conformance control and water plugging agents are unavoidable dehydrated situation in high-temperature and high-salinity low permeability reservoirs.Consequently,a novel conformance control system HPF-Co gel,based on high-temperature stabilizer(CoCl_(2)·H_(2)O,CCH)is developed.The HPF-Co bulk gel has better performances with high temperature(120℃)and high salinity(1×10^(5)mg/L).According to Sydansk coding system,the gel strength of HPF-Co with CCH is increased to code G.The dehydration rate of HPF-Co gel is 32.0%after aging for 150 d at 120℃,showing excellent thermal stability.The rheological properties of HPF gel and HPF-Co gel are also studied.The results show that the storage modulus(G′)of HPF-Co gel is always greater than that of HPF gel.The effect of CCH on the microstructure of the gel is studied.The results show that the HPF-Co gel with CCH has a denser gel network,and the diameter of the three-dimensional network skeleton is 1.5-3.5μm.After 90 d of aging,HPF-Co gel still has a good three-dimensional structure.Infrared spectroscopy results show that CCH forms coordination bonds with N and O atoms in the gel amide group,which can suppress the vibration of cross-linked sites and improve the stability at high temperature.Fractured core plugging test determines the optimized polymer gel injection strategy and injection velocity with HPF-Co bulk gel system,plugging rate exceeding 98%.Moreover,the results of subsequent waterflooding recovery can be improved by 17%.

关键词： Low permeability reservoir High-temperature resistant gel Complexation reaction Polymer gel injection strategy Plugging rate Enhanced oil recovery

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Cardiovascular computed tomography in cardiovascular disease:An overview of its applications from diagnosis to prediction

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Journal of Geriatric Cardiology 2024年第5期21卷 550-576页

作者： zhong-Hua sun Discipline of Medical Radiation Science Curtin Medical SchoolCurtin UniversityPerthAustralia Curtin Health Innovation Research Institute(CHIRI) Curtin UniversityPerth 6012Australia

Cardiovascular computed tomography angiography(CTA)is a widely used imaging modality in the diagnosis of cardiovascular disease.Advancements in CT imaging technology have further advanced its applications from high diagnostic value to minimising radiation exposure to patients.In addition to the standard application of assessing vascular lumen changes,CTA-derived applications including 3D printed personalised models,3D visualisations such as virtual endoscopy,virtual reality,augmented reality and mixed reality,as well as CT-derived hemodynamic flow analysis and fractional flow reserve(FFRCT)greatly enhance the diagnostic performance of CTA in cardiovascular disease.The widespread application of artificial intelligence in medicine also significantly contributes to the clinical value of CTA in cardiovascular disease.Clinical value of CTA has extended from the initial diagnosis to identification of vulnerable lesions,and prediction of disease extent,hence improving patient care and management.In this review article,as an active researcher in cardiovascular imaging for more than 20 years,I will provide an overview of cardiovascular CTA in cardiovascular disease.It is expected that this review will provide readers with an update of CTA applications,from the initial lumen assessment to recent developments utilising latest novel imaging and visualisation technologies.It will serve as a useful resource for researchers and clinicians to judiciously use the cardiovascular CT in clinical practice.

关键词： diagnosis cardiovascular prediction

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Albumin–bilirubin grade as a predictor of survival in hepatocellular carcinoma patients with thrombocytopenia

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World Journal of Gastrointestinal Oncology 2024年第5期16卷 1763-1772页

作者： zhong-Ran Man Xuan-Kun Gong Kang-Lin qu Qing Pang Bin-quan Wu Department of Hepatobiliary Surgery The First Affiliated Hospital of Bengbu Medical CollegeBengbu 233000Anhui ProvinceChina Department of Hepatobiliary Surgery Anhui No.2 Provincial People’s HospitalHefei 230041Anhui ProvinceChina

BACKGROUND The models for assessing liver function,mainly the Child–Pugh(CP),albuminbilirubin(ALBI),and platelet–ALBI(PALBI)classifications,have been validated for use in estimating the prognosis of hepatocellular carcinoma(HCC)patients.However,thrombocytopenia is a common finding and may influence the prognostic value of the three models in HCC.AIM To investigate and compare the prognostic performance of the above three models in thrombocytopenic HCC patients.METHODS A total of 135 patients with thrombocytopenic HCC who underwent radical surgery were retrospectively analyzed.Preoperative scores on the CP,ALBI and PALBI classifications were estimated accordingly.Kaplan–Meier curves with logrank tests and Cox regression models were used to explore the significant factors associated with overall survival(OS)and recurrence-free survival(RFS).RESULTS The preoperative platelet counts were significantly different among the CP,ALBI and PALBI groups.After a median follow-up of 28 mo,39.3%(53/135)of the patients experienced postoperative recurrence,and 36.3%(49/135)died.Univariate analysis suggested thatα-fetoprotein levels,tumor size,vascular invasion,and ALBI grade were significant predictors of OS and RFS.According to the multivariate Cox regression model,ALBI was identified as an independent prognostic factor.However,CP and PALBI grades were not statistically significant prognostic indicators.CONCLUSION The ALBI grade,rather than CP or PALBI grade,is a significant prognostic indicator for thrombocytopenic HCC patients.

关键词： Hepatocellular carcinoma Thrombocytopenia Child-Pugh Albumin-bilirubin Platelet-albumin-bilirubin

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Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system

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Chinese Journal of Chemical Engineering 2024年第3期67卷 182-194页

作者： Shan Liu Wenqi zhong Li sun Xi Chen Rafal Madonski School of Energy and Environment Key Laboratory of Energy Thermal Conversion and Control of Ministry of EducationSoutheast UniversityNanjing 210096China Faculty of Automatic Control Electronics and Computer ScienceSilesian University of TechnologyGliwise 44-100Poland

Wet flue gas desulphurization technology is widely used in the industrial process for its capability of efficient pollution removal.The desulphurization control system,however,is subjected to complex reaction mechanisms and severe disturbances,which make for it difficult to achieve certain practically relevant control goals including emission and economic performances as well as system robustness.To address these challenges,a new robust control scheme based on uncertainty and disturbance estimator(UDE)and model predictive control(MPC)is proposed in this paper.The UDE is used to estimate and dynamically compensate acting disturbances,whereas MPC is deployed for optimal feedback regulation of the resultant dynamics.By viewing the system nonlinearities and unknown dynamics as disturbances,the proposed control framework allows to locally treat the considered nonlinear plant as a linear one.The obtained simulation results confirm that the utilization of UDE makes the tracking error negligibly small,even in the presence of unmodeled dynamics.In the conducted comparison study,the introduced control scheme outperforms both the standard MPC and PID(proportional-integral-derivative)control strategies in terms of transient performance and robustness.Furthermore,the results reveal that a lowpass-filter time constant has a significant effect on the robustness and the convergence range of the tracking error.

关键词： Desulphurization system Disturbance rejection Model predictive control Uncertainty and disturbance estimator Nonlinear system

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Machine learning-based radiomics score improves prognostic prediction accuracy of stage II/III gastric cancer: A multi-cohort study

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World Journal of Gastrointestinal Surgery 2024年第2期16卷 345-356页

作者： Ying-Hao Xiang Huan Mou Bo qu Hui-Rong sun Department of General Surgery Lichuan People's HospitalEnshi 445400Hubei ProvinceChina

BACKGROUND Although accurately evaluating the overall survival(OS)of gastric cancer patients remains difficult,radiomics is considered an important option for studying pro-gnosis.AIM To develop a robust and unbiased biomarker for predicting OS using machine learning and computed tomography(CT)image radiomics.METHODS This study included 181 stage II/III gastric cancer patients,141 from Lichuan People's Hospital,and 40 from the Cancer Imaging Archive(TCIA).Primary tumors in the preoperative unenhanced CT images were outlined as regions of interest(ROI),and approximately 1700 radiomics features were extracted from each ROI.The skeletal muscle index(SMI)and skeletal muscle density(SMD)were measured using CT images from the lower margin of the third lumbar vertebra.Using the least absolute shrinkage and selection operator regression with 5-fold cross-validation,36 radiomics features were identified as important predictors,and the OS-associated CT image radiomics score(OACRS)was cal-culated for each patient using these important predictors.RESULTS Patients with a high OACRS had a poorer prognosis than those with a low OACRS score(P<0.05)and those in the TCIA cohort.Univariate and multivariate analyses revealed that OACRS was a risk factor[RR=3.023(1.896-4.365),P<0.001]independent of SMI,SMD,and pathological features.Moreover,OACRS outperformed SMI and SMD and could improve OS prediction(P<0.05).CONCLUSION A novel biomarker based on machine learning and radiomics was developed that exhibited exceptional OS discrimination potential.

关键词： Radiomics Machine learning Gastric cancer Skeletal muscle density Skeletal muscle index

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Artificial intelligence-assisted repair of peripheral nerve injury: a new research hotspot and associated challenges

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Neural Regeneration Research 2024年第3期19卷 663-670页

作者： Yang Guo Liying sun Wenyao zhong Nan Zhang Zongxuan Zhao Wen Tian Department of Hand Surgery Beijing Jishuitan HospitalBeijingChina

Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future re

关键词： artificial intelligence artificial prosthesis medical-industrial integration brain-machine interface deep learning machine learning networked hand prosthesis neural interface neural network neural regeneration peripheral nerve

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