Foundation models(FMs)have rapidly evolved and have achieved signicant accomplishments in computer vision tasks.Specically,the prompt mechanism conveniently allows users to integrate image prior information into the m...Foundation models(FMs)have rapidly evolved and have achieved signicant accomplishments in computer vision tasks.Specically,the prompt mechanism conveniently allows users to integrate image prior information into the model,making it possible to apply models without any training.Therefore,we proposed a workflow based on foundation models and zero training to solve the tasks of photoacoustic(PA)image processing.We employed the Segment Anything Model(SAM)by setting simple prompts and integrating the model's outputs with prior knowledge of the imaged objects to accomplish various tasks,including:(1)removing the skin signal in three-dimensional PA image rendering;(2)dual speed-of-sound reconstruction,and(3)segmentation ofnger blood vessels.Through these demonstrations,we have concluded that FMs can be directly applied in PA imaging without the requirement for network design and training.This potentially allows for a hands-on,convenient approach to achieving efficient and accurate segmentation of PA images.This paper serves as a comprehensive tutorial,facilitating the mastery of the technique through the provision of code and sample datasets.展开更多
Optical multilayer thin film structures have been widely used in numerous photonic applications.However,existing inverse design methods have many drawbacks because they either fail to quickly adapt to different design...Optical multilayer thin film structures have been widely used in numerous photonic applications.However,existing inverse design methods have many drawbacks because they either fail to quickly adapt to different design targets,or are difficult to suit for different types of structures,e.g.,designing for different materials at each layer.These methods also cannot accommodate versatile design situations under different angles and polarizations.In addition,how to benefit practical fabrications and manufacturing has not been extensively considered yet.In this work,we introduce OptoGPT(Opto Generative Pretrained Transformer),a decoder-only transformer,to solve all these drawbacks and issues simultaneously.展开更多
Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the ...Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.展开更多
This study investigates the ground and structural response of adjacent raft foundations induced by largescale surcharge by ore in soft soil areas through a 130g centrifuge modeling test with an innovative layered load...This study investigates the ground and structural response of adjacent raft foundations induced by largescale surcharge by ore in soft soil areas through a 130g centrifuge modeling test with an innovative layered loading device.The prototype of the test is a coastal iron ore yard with a natural foundation of deep soft soil.Therefore,it is necessary to adopt some measures to reduce the influence of the large-scale surcharge on the adjacent raft foundation,such as installing stone columns for foundation treatment.Under an acceleration of 130 g,the model conducts similar simulations of iron ore,stone columns,and raft foundation structures.The tested soil mass has dimensions of 900 mm×700 mm×300 mm(lengthwidthdepth),which is remodeled from the soil extracted from the drilling holes.The test conditions are consistent with the actual engineering conditions and the effects of four-level loading conditions on the composite foundation of stone columns,unreinforced zone,and raft foundations are studied.An automatic layer-by-layer loading device was innovatively developed to simulate the loading process of actual engineering more realistically.The composite foundation of stone columns had a large settlement after the loading,forming an obvious settlement trough and causing the surface of the unreinforced zone to rise.The 12 m surcharge loading causes a horizontal displacement of 13.19 cm and a vertical settlement of 1.37 m in the raft foundation.The stone columns located on both sides of the unreinforced zone suffered significant shear damage at the sand-mud interface.Due to the reinforcement effect of stone columns,the sand layer below the top of the stone columns moves less.Meanwhile,the horizontal earth pressure in the raft foundation zone increases slowly.The stone columns will form new drainage channels and accelerate the dissipation of excess pore pressure.展开更多
In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the task.The rapid development of artificial intelligence...In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the task.The rapid development of artificial intelligence(AI)foundation models provides significant support for efficient and intelligent communication interactions.In this paper,we propose an innovative semantic communication paradigm called task-oriented semantic communication system with foundation models.First,we segment the image by using task prompts based on the segment anything model(SAM)and contrastive language-image pretraining(CLIP).Meanwhile,we adopt Bezier curve to enhance the mask to improve the segmentation accuracy.Second,we have differentiated semantic compression and transmission approaches for segmented content.Third,we fuse different semantic information based on the conditional diffusion model to generate high-quality images that satisfy the users'specific task requirements.Finally,the experimental results show that the proposed system compresses the semantic information effectively and improves the robustness of semantic communication.展开更多
Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requir...Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.展开更多
We present an approach to classify medical text at a sentence level automatically.Given the inherent complexity of medical text classification,we employ adapters based on pre-trained language models to extract informa...We present an approach to classify medical text at a sentence level automatically.Given the inherent complexity of medical text classification,we employ adapters based on pre-trained language models to extract information from medical text,facilitating more accurate classification while minimizing the number of trainable parameters.Extensive experiments conducted on various datasets demonstrate the effectiveness of our approach.展开更多
The Coronavirus Disease 2019(COVID-19)is wreaking havoc around the world,bring out that the enormous pressure on national health and medical staff systems.One of the most effective and critical steps in the fight agai...The Coronavirus Disease 2019(COVID-19)is wreaking havoc around the world,bring out that the enormous pressure on national health and medical staff systems.One of the most effective and critical steps in the fight against COVID-19,is to examine the patient’s lungs based on the Chest X-ray and CT generated by radiation imaging.In this paper,five keras-related deep learning models:ResNet50,InceptionResNetV2,Xception,transfer learning and pre-trained VGGNet16 is applied to formulate an classification-detection approaches of COVID-19.Two benchmark methods SVM(Support Vector Machine),CNN(Conventional Neural Networks)are provided to compare with the classification-detection approaches based on the performance indicators,i.e.,precision,recall,F1 scores,confusion matrix,classification accuracy and three types of AUC(Area Under Curve).The highest classification accuracy derived by classification-detection based on 5857 Chest X-rays and 767 Chest CTs are respectively 84%and 75%,which shows that the keras-related deep learning approaches facilitate accurate and effective COVID-19-assisted detection.展开更多
As important geological data,a geological report contains rich expert and geological knowledge,but the challenge facing current research into geological knowledge extraction and mining is how to render accurate unders...As important geological data,a geological report contains rich expert and geological knowledge,but the challenge facing current research into geological knowledge extraction and mining is how to render accurate understanding of geological reports guided by domain knowledge.While generic named entity recognition models/tools can be utilized for the processing of geoscience reports/documents,their effectiveness is hampered by a dearth of domain-specific knowledge,which in turn leads to a pronounced decline in recognition accuracy.This study summarizes six types of typical geological entities,with reference to the ontological system of geological domains and builds a high quality corpus for the task of geological named entity recognition(GNER).In addition,Geo Wo BERT-adv BGP(Geological Word-base BERTadversarial training Bi-directional Long Short-Term Memory Global Pointer)is proposed to address the issues of ambiguity,diversity and nested entities for the geological entities.The model first uses the fine-tuned word granularitybased pre-training model Geo Wo BERT(Geological Word-base BERT)and combines the text features that are extracted using the Bi LSTM(Bi-directional Long Short-Term Memory),followed by an adversarial training algorithm to improve the robustness of the model and enhance its resistance to interference,the decoding finally being performed using a global association pointer algorithm.The experimental results show that the proposed model for the constructed dataset achieves high performance and is capable of mining the rich geological information.展开更多
To obtain the vertical earth pressure on a soft foundation box culvert and investigate the interaction of the soil-culvert-foundation system, both a centrifugal model test and a numerical simulation were conducted and...To obtain the vertical earth pressure on a soft foundation box culvert and investigate the interaction of the soil-culvert-foundation system, both a centrifugal model test and a numerical simulation were conducted and the comparisons with the current methods to determine the load on a culvert were completed. The results of the model test and numerical analysis are in satisfactory agreement, which shows that the direction of the shear stress between the culvert and the adjacent embankment depends on the differential settlement between them. A vertical earth pressure concentration appears on the culvert with a rigid piles foundation because of a downward shear stress. The ratio of the load on a soft foundation culvert and the overburden pressure above the culvert raises first and then decreases as the backfill height increases. In order to reduce the load on a culvert, it is suggested to limit the stiffness difference of the foundations under the culvert and embankment and to use a light backfill over the culvert.展开更多
The semi-rigid pile-supported composite foundation is widely used in highway projects due to its effectiveness in increasing the bearing capacity and stability of foundations.It is crucial to understand the stress dis...The semi-rigid pile-supported composite foundation is widely used in highway projects due to its effectiveness in increasing the bearing capacity and stability of foundations.It is crucial to understand the stress distribution across the embankment width and the behaviour of unreinforced foundations.Thus,five centrifuge tests were conducted to examine the bearing and deformation behaviours of NPRS(Non-Connected Piled Raft Systems)and GRPS(GeosyntheticReinforced Pile-Supported systems)with varying substratum stiffness,then a comparative analysis was conducted on embankment settlement,pressures underneath the embankments,and axial forces along the piles.The results indicated that greater substratum stiffness correlates with reduced settlement and deformation at various depths.Deformation occurring 5 meters from the embankment toe includes settlement in NPRS and upward movement in GRPS.The potential sliding surface is primarily located within the embankment in NPRS,whereas it may extend through both the embankment and foundation in GRPS.The pile-soil stress ratio and efficiency in NPRS are higher than in GRPS across the embankment.The axial force borne by end-bearing piles is significantly greater than that by floating piles.As the buried depth increases,the axial force in GRPS initially rises then declines,whereas in NPRS,it remains relatively constant within a certain range before decreasing.This study aids in assessing the applicability of composite foundations in complex railway environments and provides a reference for procedural measures under similar conditions.展开更多
To reveal the bearing capacity of the X-section concrete piles pile raft foundation in silica sand,a series of vertical load tests are carried out.The X-section concrete piles are compared with circular section pile w...To reveal the bearing capacity of the X-section concrete piles pile raft foundation in silica sand,a series of vertical load tests are carried out.The X-section concrete piles are compared with circular section pile with the same section area.The load−settlement curves,axial force and skin friction,strain on concave and convex edge of the pile,pile-sand stress ratio,distributions of side and tip resistance are presented.The results show that bearing capacity of the X section concrete pile raft foundation is much larger than that of the circular pile raft foundation.Besides,compared with the circular pile,the peak axial force of X-section piles under raft is deeper and smaller while the neutral point of X-section concrete pile is deeper.Moreover,the strain on the concave edge is much larger than that on the convex edge of the pile,and the convex edge has more potential in bearing capacity as the vertical load increases.The X-section pile has higher pile-sand stress ratios and load-sharing between side resistance and tip resistance.Above all,the X-section concrete pile can significantly increase the bearing capacity of pile-raft foundations in silica sand.展开更多
In this paper,the influence of the limited-tension interface between lid and soil on the undrained bearing capacity of the wide-shallow bucket foundation is examined by finite element(FE)analysis.The interface between...In this paper,the influence of the limited-tension interface between lid and soil on the undrained bearing capacity of the wide-shallow bucket foundation is examined by finite element(FE)analysis.The interface between the lid and the soil is modeled using a simplified approach called the surface-based cohesive behavior,with the aim of simulating the limited-tension interface.Initially,the interaction between the lid and the soil is explored under the zero-and unlimited-tension conditions by small-scale experiments.Afterward,the effects of the embedment ratio,soil strength heterogeneity,and lid-soil interface on the bearing capacity are outlined,and the failure mechanisms are explained by FE analysis.A modified closed-form formula is given to compute the moment bearing capacity with the limited-tension interface between the lid and the soil for different embedment ratios and soil strength heterogeneities.The numerical results reveal that the existing approximating solutions,which assume fully bonded interaction,accurately exhibit the shape of the normalized failure envelopes in hm and vh load space for the limited-tension interface.However,the shape of the vm envelopes differs,requiring a novel solution to estimate the combined bearing capacity of the bucket foundation based on the embedment ratio and soil strength heterogeneity with a zero-tension interface between the lid and the soil.展开更多
Local scour around offshore wind turbine foundations presents a considerable challenge due to its potential influence on structural stability,driven by hydrodynamic forces.While research has made strides in comprehend...Local scour around offshore wind turbine foundations presents a considerable challenge due to its potential influence on structural stability,driven by hydrodynamic forces.While research has made strides in comprehending scouring mechanisms,notable complexities persist,specifically with newer foundation types.Addressing these limitations is vital for advancing our understanding of scour mechanisms and for improving mitigation strategies in offshore wind energy development.This review synthesizes current findings on local scour across various offshore foundations,encompassing field observations,data-driven approaches,turbulence-sediment interactions,scour evolution processes,influencing factors,and numerical model advancements.The objective is to enrich our understanding of local scour mechanisms.In addition,future research directions are outlined,including the development of robust arti-ficial intelligence models for accurate predictions,the exploration of vortex structure characteristics,and the refinement of numerical models to strengthen prediction capabilities while minimizing computational efforts.展开更多
The traditional ground direct current method is not suitable for leakage detection of underground diaphragm walls in foundation pits because of its low accuracy and poor anti-noise ability.Here,we propose a joint surf...The traditional ground direct current method is not suitable for leakage detection of underground diaphragm walls in foundation pits because of its low accuracy and poor anti-noise ability.Here,we propose a joint surface-borehole observation device for leakage electric fi eld detection to achieve rapid measurement of the electric fi eld distribution characteristics at ground level in the foundation pit,thus enabling rapid localization of leakage points.We first establish the mechanism and basic equation of the leakage electric field response by combining the electric field formed by electrokinetic effect(EK)and the stable electric fi eld formed by conduction current in a combined leakage channel.Then,the fi nite–infi nite element coupling method is used to solve the electric fi eld equation to simulate the responses of a three-dimensional foundation pit leakage model.Furthermore,we conduct numerical simulations of diff erent pit models to investigate the infl uencing factors of the detection device and response characteristics of the change in the properties of the leakage channel.The results demonstrate that the proposed joint surface-borehole observation device can effi ciently reveal anomalous potential caused by leakage,and the amplitude of the electric fi eld generated by EK can eff ectively strengthen the leakage electric fi eld signal at the leakage,thus improving detection accuracy and effi ciency.展开更多
The influence of non-coaxial constitutive model on predictions of dense sand behavior is investigated in this paper. The non-coaxial model with strain softening plasticity is applied into finite-element program ABAQUS...The influence of non-coaxial constitutive model on predictions of dense sand behavior is investigated in this paper. The non-coaxial model with strain softening plasticity is applied into finite-element program ABAQUS, which is first used to predict the stress-strain behavior and the non-coaxial characteristic between the orientations of the principal stress and principal plastic strain rate in simple shear tests. The model is also used to predict load settlement responses and bearing capacity factors of shallow foundations. A series of centrifuge tests for shallow foundations on saturated dense sand are performed under drained conditions and the test results are compared with the corresponding numerical results. Various footing dimensions, depths of embedment, and footing shapes are considered in these tests. In view of the load settlement relationships, the stiffness of the load-displacement curves is significantly affected by the non-coaxial model compared with those predicted by the coaxial model, and a lower value of non-coaxial modulus gives a softer response. Considering the soil behavior at failure, the coaxial model predictions of bearing capacity factors are more advanced than those of centrifuge test results and the non-coaxial model results;besides, the non-coaxial model gives better predictions. The non-coaxial model predictions are closer to those of the centrifuge results when a proper non-coaxial plastic modulus is chosen.展开更多
The need for simplified physical models representing frequency dependent soil impedances has been the motivation behind many researches throughout history. Generally, such models are generated to capture impedance fun...The need for simplified physical models representing frequency dependent soil impedances has been the motivation behind many researches throughout history. Generally, such models are generated to capture impedance functions in a wide range of excitation frequencies, which leads to relatively complex models. That is while there is just a limited range of frequencies that really influence the response of the structure. Here, a new methodology based on the response-matching concept is proposed, which can lead to the development of simpler discrete models. The idea is then used to upgrade an existing simple model of surface foundations to the case of embedded foundations. The applicability of the model in both frequency domain and time domain analyses of soil-structure systems with embedded foundations is discussed. Moreover, the accuracy of the results is compared with another existing discrete model for embedded foundations.展开更多
As the top of the pile foundation in high-pile wharf is connected to the superstructure and most of the pile bodies are located below the water surface, traditional damage detection methods are greatly limited in thei...As the top of the pile foundation in high-pile wharf is connected to the superstructure and most of the pile bodies are located below the water surface, traditional damage detection methods are greatly limited in their application to pile foundation in service. In the present study, a new method for pile foundation damage detection is developed based on the curve shape of the curvature mode difference(CMD) before and after damage. In the method, the influence at each node on the overall CMD curve shape is analyzed through a data deletion model, statistical characteristic indexes are established to reflect the difference between damaged and undamaged units, and structural damage is accurately detected. The effectiveness and robustness of the method are verified by a finite element model(FEM) of high-pile wharf under different damage conditions and different intensities of Gaussian white noise. The applicability of the method is then experimentally validated by a physical model of high-pile wharf. Both the FEM and the experimental results show that the method is capable of detecting pile foundation damage in noisy curvature mode and has strong application potential.展开更多
In this paper, the cone model is applied to the vibration analysis of two foundations on a layered soil half space. In the analysis, the total stress field in the subsoil is divided into the free-field and the scatter...In this paper, the cone model is applied to the vibration analysis of two foundations on a layered soil half space. In the analysis, the total stress field in the subsoil is divided into the free-field and the scattering field. Seed＇s simplified method is adopted for the free-field analysis, while the cone model is proposed for analyzing the dynamic scattering stress wave field. The shear stress field and the compressive stress field in the layered stratum with two scattering sources are calculated by shear cone and compressive cone, respectively. Furthermore, the stress fields in the subsoil with two foundations are divided into six zones, and the P wave and S wave are analyzed in each zone. Numerical results are provided to illustrate features of the added stress field for two surface foundations under vertical and horizontal sinusoidal force excitation. The proposed cone model may be useful in handling some of the complex problems associated with multi-scattering sources.展开更多
To ensure the safety of buildings surrounding foundation pits, a study was made on a settlement monitoring and trend prediction method. A statistical testing method for analyzing the stability of a settlement monitori...To ensure the safety of buildings surrounding foundation pits, a study was made on a settlement monitoring and trend prediction method. A statistical testing method for analyzing the stability of a settlement monitoring datum has been discussed. According to a comprehensive survey, data of 16 stages at operating control point, were verified by a standard t test to determine the stability of the operating control point. A stationary auto-regression model, AR(p), used for the observation point settlement prediction has been investigated. Given the 16 stages of the settlement data at an observation point, the applicability of this model was analyzed. Settlement of last four stages was predicted using the stationary auto-regression model AR (1); the maximum difference between predicted and measured values was 0.6 mm, indicating good prediction results of the model. Hence, this model can be applied to settlement predictions for buildings surrounding foundation pits.展开更多
基金support from Strategic Project of Precision Surgery,Tsinghua UniversityInitiative Scientific Research Program,Institute for Intelligent Healthcare,Tsinghua University+5 种基金Tsinghua-Foshan Institute of Advanced ManufacturingNational Natural Science Foundation of China(61735016)Beijing Nova Program(20230484308)Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)Youth Elite Program of Beijing Friendship Hospital(YYQCJH2022-9)Science and Technology Program of Beijing Tongzhou District(KJ2023CX012).
文摘Foundation models(FMs)have rapidly evolved and have achieved signicant accomplishments in computer vision tasks.Specically,the prompt mechanism conveniently allows users to integrate image prior information into the model,making it possible to apply models without any training.Therefore,we proposed a workflow based on foundation models and zero training to solve the tasks of photoacoustic(PA)image processing.We employed the Segment Anything Model(SAM)by setting simple prompts and integrating the model's outputs with prior knowledge of the imaged objects to accomplish various tasks,including:(1)removing the skin signal in three-dimensional PA image rendering;(2)dual speed-of-sound reconstruction,and(3)segmentation ofnger blood vessels.Through these demonstrations,we have concluded that FMs can be directly applied in PA imaging without the requirement for network design and training.This potentially allows for a hands-on,convenient approach to achieving efficient and accurate segmentation of PA images.This paper serves as a comprehensive tutorial,facilitating the mastery of the technique through the provision of code and sample datasets.
基金the National Science Foundation(PFI-008513 and FET-2309403)for the support of this work.
文摘Optical multilayer thin film structures have been widely used in numerous photonic applications.However,existing inverse design methods have many drawbacks because they either fail to quickly adapt to different design targets,or are difficult to suit for different types of structures,e.g.,designing for different materials at each layer.These methods also cannot accommodate versatile design situations under different angles and polarizations.In addition,how to benefit practical fabrications and manufacturing has not been extensively considered yet.In this work,we introduce OptoGPT(Opto Generative Pretrained Transformer),a decoder-only transformer,to solve all these drawbacks and issues simultaneously.
基金We acknowledge funding from NSFC Grant 62306283.
文摘Since the 1950s,when the Turing Test was introduced,there has been notable progress in machine language intelligence.Language modeling,crucial for AI development,has evolved from statistical to neural models over the last two decades.Recently,transformer-based Pre-trained Language Models(PLM)have excelled in Natural Language Processing(NLP)tasks by leveraging large-scale training corpora.Increasing the scale of these models enhances performance significantly,introducing abilities like context learning that smaller models lack.The advancement in Large Language Models,exemplified by the development of ChatGPT,has made significant impacts both academically and industrially,capturing widespread societal interest.This survey provides an overview of the development and prospects from Large Language Models(LLM)to Large Multimodal Models(LMM).It first discusses the contributions and technological advancements of LLMs in the field of natural language processing,especially in text generation and language understanding.Then,it turns to the discussion of LMMs,which integrates various data modalities such as text,images,and sound,demonstrating advanced capabilities in understanding and generating cross-modal content,paving new pathways for the adaptability and flexibility of AI systems.Finally,the survey highlights the prospects of LMMs in terms of technological development and application potential,while also pointing out challenges in data integration,cross-modal understanding accuracy,providing a comprehensive perspective on the latest developments in this field.
基金funding support from National Key Research and Development Program of China(Grant No.2021YFF0502200)National Natural Science Foundation of China(Grant Nos.52022070 and 51978516).
文摘This study investigates the ground and structural response of adjacent raft foundations induced by largescale surcharge by ore in soft soil areas through a 130g centrifuge modeling test with an innovative layered loading device.The prototype of the test is a coastal iron ore yard with a natural foundation of deep soft soil.Therefore,it is necessary to adopt some measures to reduce the influence of the large-scale surcharge on the adjacent raft foundation,such as installing stone columns for foundation treatment.Under an acceleration of 130 g,the model conducts similar simulations of iron ore,stone columns,and raft foundation structures.The tested soil mass has dimensions of 900 mm×700 mm×300 mm(lengthwidthdepth),which is remodeled from the soil extracted from the drilling holes.The test conditions are consistent with the actual engineering conditions and the effects of four-level loading conditions on the composite foundation of stone columns,unreinforced zone,and raft foundations are studied.An automatic layer-by-layer loading device was innovatively developed to simulate the loading process of actual engineering more realistically.The composite foundation of stone columns had a large settlement after the loading,forming an obvious settlement trough and causing the surface of the unreinforced zone to rise.The 12 m surcharge loading causes a horizontal displacement of 13.19 cm and a vertical settlement of 1.37 m in the raft foundation.The stone columns located on both sides of the unreinforced zone suffered significant shear damage at the sand-mud interface.Due to the reinforcement effect of stone columns,the sand layer below the top of the stone columns moves less.Meanwhile,the horizontal earth pressure in the raft foundation zone increases slowly.The stone columns will form new drainage channels and accelerate the dissipation of excess pore pressure.
基金supported in part by the National Natural Science Foundation of China under Grant(62001246,62231017,62201277,62071255)the Natural Science Foundation of Jiangsu Province under Grant BK20220390+3 种基金Key R and D Program of Jiangsu Province Key project and topics under Grant(BE2021095,BE2023035)the Natural Science Research Startup Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(Grant No.NY221011)National Science Foundation of Xiamen,China(No.3502Z202372013)Open Project of the Key Laboratory of Underwater Acoustic Communication and Marine Information Technology(Xiamen University)of the Ministry of Education,China(No.UAC202304)。
文摘In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the task.The rapid development of artificial intelligence(AI)foundation models provides significant support for efficient and intelligent communication interactions.In this paper,we propose an innovative semantic communication paradigm called task-oriented semantic communication system with foundation models.First,we segment the image by using task prompts based on the segment anything model(SAM)and contrastive language-image pretraining(CLIP).Meanwhile,we adopt Bezier curve to enhance the mask to improve the segmentation accuracy.Second,we have differentiated semantic compression and transmission approaches for segmented content.Third,we fuse different semantic information based on the conditional diffusion model to generate high-quality images that satisfy the users'specific task requirements.Finally,the experimental results show that the proposed system compresses the semantic information effectively and improves the robustness of semantic communication.
文摘Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.
文摘We present an approach to classify medical text at a sentence level automatically.Given the inherent complexity of medical text classification,we employ adapters based on pre-trained language models to extract information from medical text,facilitating more accurate classification while minimizing the number of trainable parameters.Extensive experiments conducted on various datasets demonstrate the effectiveness of our approach.
基金This project is supported by National Natural Science Foundation of China(NSFC)(Nos.61902158,61806087)Graduate student innovation program for academic degrees in general university in Jiangsu Province(No.KYZZ16-0337).
文摘The Coronavirus Disease 2019(COVID-19)is wreaking havoc around the world,bring out that the enormous pressure on national health and medical staff systems.One of the most effective and critical steps in the fight against COVID-19,is to examine the patient’s lungs based on the Chest X-ray and CT generated by radiation imaging.In this paper,five keras-related deep learning models:ResNet50,InceptionResNetV2,Xception,transfer learning and pre-trained VGGNet16 is applied to formulate an classification-detection approaches of COVID-19.Two benchmark methods SVM(Support Vector Machine),CNN(Conventional Neural Networks)are provided to compare with the classification-detection approaches based on the performance indicators,i.e.,precision,recall,F1 scores,confusion matrix,classification accuracy and three types of AUC(Area Under Curve).The highest classification accuracy derived by classification-detection based on 5857 Chest X-rays and 767 Chest CTs are respectively 84%and 75%,which shows that the keras-related deep learning approaches facilitate accurate and effective COVID-19-assisted detection.
基金financially supported by the Natural Science Foundation of China(Grant No.42301492)the National Key R&D Program of China(Grant Nos.2022YFF0711600,2022YFF0801201,2022YFF0801200)+3 种基金the Major Special Project of Xinjiang(Grant No.2022A03009-3)the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources(Grant No.KF-2022-07014)the Opening Fund of the Key Laboratory of the Geological Survey and Evaluation of the Ministry of Education(Grant No.GLAB 2023ZR01)the Fundamental Research Funds for the Central Universities。
文摘As important geological data,a geological report contains rich expert and geological knowledge,but the challenge facing current research into geological knowledge extraction and mining is how to render accurate understanding of geological reports guided by domain knowledge.While generic named entity recognition models/tools can be utilized for the processing of geoscience reports/documents,their effectiveness is hampered by a dearth of domain-specific knowledge,which in turn leads to a pronounced decline in recognition accuracy.This study summarizes six types of typical geological entities,with reference to the ontological system of geological domains and builds a high quality corpus for the task of geological named entity recognition(GNER).In addition,Geo Wo BERT-adv BGP(Geological Word-base BERTadversarial training Bi-directional Long Short-Term Memory Global Pointer)is proposed to address the issues of ambiguity,diversity and nested entities for the geological entities.The model first uses the fine-tuned word granularitybased pre-training model Geo Wo BERT(Geological Word-base BERT)and combines the text features that are extracted using the Bi LSTM(Bi-directional Long Short-Term Memory),followed by an adversarial training algorithm to improve the robustness of the model and enhance its resistance to interference,the decoding finally being performed using a global association pointer algorithm.The experimental results show that the proposed model for the constructed dataset achieves high performance and is capable of mining the rich geological information.
基金Project(2012AA112504) supported by the National High Technology Research and Development Program of ChinaProjects(51108048,51478054) supported by the National Natural Science Foundation of China
文摘To obtain the vertical earth pressure on a soft foundation box culvert and investigate the interaction of the soil-culvert-foundation system, both a centrifugal model test and a numerical simulation were conducted and the comparisons with the current methods to determine the load on a culvert were completed. The results of the model test and numerical analysis are in satisfactory agreement, which shows that the direction of the shear stress between the culvert and the adjacent embankment depends on the differential settlement between them. A vertical earth pressure concentration appears on the culvert with a rigid piles foundation because of a downward shear stress. The ratio of the load on a soft foundation culvert and the overburden pressure above the culvert raises first and then decreases as the backfill height increases. In order to reduce the load on a culvert, it is suggested to limit the stiffness difference of the foundations under the culvert and embankment and to use a light backfill over the culvert.
基金financially supported by the National Natural Science Foundation of China(Nos.51878577 and 52378463)the Natural Science Foundation of Shandong Provincial,China(No.ZR2022ME042)the School-Enterprise Cooperation Program of China Railway 14th Bureau Group Co.(QTHT-HGLCHSD-00052)。
文摘The semi-rigid pile-supported composite foundation is widely used in highway projects due to its effectiveness in increasing the bearing capacity and stability of foundations.It is crucial to understand the stress distribution across the embankment width and the behaviour of unreinforced foundations.Thus,five centrifuge tests were conducted to examine the bearing and deformation behaviours of NPRS(Non-Connected Piled Raft Systems)and GRPS(GeosyntheticReinforced Pile-Supported systems)with varying substratum stiffness,then a comparative analysis was conducted on embankment settlement,pressures underneath the embankments,and axial forces along the piles.The results indicated that greater substratum stiffness correlates with reduced settlement and deformation at various depths.Deformation occurring 5 meters from the embankment toe includes settlement in NPRS and upward movement in GRPS.The potential sliding surface is primarily located within the embankment in NPRS,whereas it may extend through both the embankment and foundation in GRPS.The pile-soil stress ratio and efficiency in NPRS are higher than in GRPS across the embankment.The axial force borne by end-bearing piles is significantly greater than that by floating piles.As the buried depth increases,the axial force in GRPS initially rises then declines,whereas in NPRS,it remains relatively constant within a certain range before decreasing.This study aids in assessing the applicability of composite foundations in complex railway environments and provides a reference for procedural measures under similar conditions.
基金Project(51878103)supported by the National Natural Science Foundation of ChinaProject(2016YFE0200100)supported by the National Key Research and Development Program of China。
文摘To reveal the bearing capacity of the X-section concrete piles pile raft foundation in silica sand,a series of vertical load tests are carried out.The X-section concrete piles are compared with circular section pile with the same section area.The load−settlement curves,axial force and skin friction,strain on concave and convex edge of the pile,pile-sand stress ratio,distributions of side and tip resistance are presented.The results show that bearing capacity of the X section concrete pile raft foundation is much larger than that of the circular pile raft foundation.Besides,compared with the circular pile,the peak axial force of X-section piles under raft is deeper and smaller while the neutral point of X-section concrete pile is deeper.Moreover,the strain on the concave edge is much larger than that on the convex edge of the pile,and the convex edge has more potential in bearing capacity as the vertical load increases.The X-section pile has higher pile-sand stress ratios and load-sharing between side resistance and tip resistance.Above all,the X-section concrete pile can significantly increase the bearing capacity of pile-raft foundations in silica sand.
基金support funded by the National Natural Science Foundation of China Joint Fund Projects(No.U21A20164)。
文摘In this paper,the influence of the limited-tension interface between lid and soil on the undrained bearing capacity of the wide-shallow bucket foundation is examined by finite element(FE)analysis.The interface between the lid and the soil is modeled using a simplified approach called the surface-based cohesive behavior,with the aim of simulating the limited-tension interface.Initially,the interaction between the lid and the soil is explored under the zero-and unlimited-tension conditions by small-scale experiments.Afterward,the effects of the embedment ratio,soil strength heterogeneity,and lid-soil interface on the bearing capacity are outlined,and the failure mechanisms are explained by FE analysis.A modified closed-form formula is given to compute the moment bearing capacity with the limited-tension interface between the lid and the soil for different embedment ratios and soil strength heterogeneities.The numerical results reveal that the existing approximating solutions,which assume fully bonded interaction,accurately exhibit the shape of the normalized failure envelopes in hm and vh load space for the limited-tension interface.However,the shape of the vm envelopes differs,requiring a novel solution to estimate the combined bearing capacity of the bucket foundation based on the embedment ratio and soil strength heterogeneity with a zero-tension interface between the lid and the soil.
基金financially supported by the National Natural Science Foundation of China(No.52301326)the China Postdoctoral Science Foundation(No.2023M731999)the Open Foundation of the Key Laboratory of Coupling Process and Effect of Natural Resources Elements(No.2024KFKT017).
文摘Local scour around offshore wind turbine foundations presents a considerable challenge due to its potential influence on structural stability,driven by hydrodynamic forces.While research has made strides in comprehending scouring mechanisms,notable complexities persist,specifically with newer foundation types.Addressing these limitations is vital for advancing our understanding of scour mechanisms and for improving mitigation strategies in offshore wind energy development.This review synthesizes current findings on local scour across various offshore foundations,encompassing field observations,data-driven approaches,turbulence-sediment interactions,scour evolution processes,influencing factors,and numerical model advancements.The objective is to enrich our understanding of local scour mechanisms.In addition,future research directions are outlined,including the development of robust arti-ficial intelligence models for accurate predictions,the exploration of vortex structure characteristics,and the refinement of numerical models to strengthen prediction capabilities while minimizing computational efforts.
基金partially supported by the National Natural Science Foundation of China (Nos. 41864004 and 41674077)Jiangxi Provincial Academic Leaders (Youth) Training Program (No. 20204BCJL23058)Open Fund from Engineering Research Center for Seismic Disaster Prevention and Engineering Geological Disaster Detection of Jiangxi Province (SDGD202102)。
文摘The traditional ground direct current method is not suitable for leakage detection of underground diaphragm walls in foundation pits because of its low accuracy and poor anti-noise ability.Here,we propose a joint surface-borehole observation device for leakage electric fi eld detection to achieve rapid measurement of the electric fi eld distribution characteristics at ground level in the foundation pit,thus enabling rapid localization of leakage points.We first establish the mechanism and basic equation of the leakage electric field response by combining the electric field formed by electrokinetic effect(EK)and the stable electric fi eld formed by conduction current in a combined leakage channel.Then,the fi nite–infi nite element coupling method is used to solve the electric fi eld equation to simulate the responses of a three-dimensional foundation pit leakage model.Furthermore,we conduct numerical simulations of diff erent pit models to investigate the infl uencing factors of the detection device and response characteristics of the change in the properties of the leakage channel.The results demonstrate that the proposed joint surface-borehole observation device can effi ciently reveal anomalous potential caused by leakage,and the amplitude of the electric fi eld generated by EK can eff ectively strengthen the leakage electric fi eld signal at the leakage,thus improving detection accuracy and effi ciency.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.51079018 and 11202109)
文摘The influence of non-coaxial constitutive model on predictions of dense sand behavior is investigated in this paper. The non-coaxial model with strain softening plasticity is applied into finite-element program ABAQUS, which is first used to predict the stress-strain behavior and the non-coaxial characteristic between the orientations of the principal stress and principal plastic strain rate in simple shear tests. The model is also used to predict load settlement responses and bearing capacity factors of shallow foundations. A series of centrifuge tests for shallow foundations on saturated dense sand are performed under drained conditions and the test results are compared with the corresponding numerical results. Various footing dimensions, depths of embedment, and footing shapes are considered in these tests. In view of the load settlement relationships, the stiffness of the load-displacement curves is significantly affected by the non-coaxial model compared with those predicted by the coaxial model, and a lower value of non-coaxial modulus gives a softer response. Considering the soil behavior at failure, the coaxial model predictions of bearing capacity factors are more advanced than those of centrifuge test results and the non-coaxial model results;besides, the non-coaxial model gives better predictions. The non-coaxial model predictions are closer to those of the centrifuge results when a proper non-coaxial plastic modulus is chosen.
文摘The need for simplified physical models representing frequency dependent soil impedances has been the motivation behind many researches throughout history. Generally, such models are generated to capture impedance functions in a wide range of excitation frequencies, which leads to relatively complex models. That is while there is just a limited range of frequencies that really influence the response of the structure. Here, a new methodology based on the response-matching concept is proposed, which can lead to the development of simpler discrete models. The idea is then used to upgrade an existing simple model of surface foundations to the case of embedded foundations. The applicability of the model in both frequency domain and time domain analyses of soil-structure systems with embedded foundations is discussed. Moreover, the accuracy of the results is compared with another existing discrete model for embedded foundations.
基金financially supported by the National Natural Science Foundation of China (Grant Nos. 51709093 and 51679081)Fujian Provincial Department of Transportation Science and Technology Development Project (Grant No. 201708)Hohai University Student Innovation and Entrepreneurship Training Project (Grant No. 201910294014Z)。
文摘As the top of the pile foundation in high-pile wharf is connected to the superstructure and most of the pile bodies are located below the water surface, traditional damage detection methods are greatly limited in their application to pile foundation in service. In the present study, a new method for pile foundation damage detection is developed based on the curve shape of the curvature mode difference(CMD) before and after damage. In the method, the influence at each node on the overall CMD curve shape is analyzed through a data deletion model, statistical characteristic indexes are established to reflect the difference between damaged and undamaged units, and structural damage is accurately detected. The effectiveness and robustness of the method are verified by a finite element model(FEM) of high-pile wharf under different damage conditions and different intensities of Gaussian white noise. The applicability of the method is then experimentally validated by a physical model of high-pile wharf. Both the FEM and the experimental results show that the method is capable of detecting pile foundation damage in noisy curvature mode and has strong application potential.
基金National Natural Science Foundation of China Under Grant No.50678021
文摘In this paper, the cone model is applied to the vibration analysis of two foundations on a layered soil half space. In the analysis, the total stress field in the subsoil is divided into the free-field and the scattering field. Seed＇s simplified method is adopted for the free-field analysis, while the cone model is proposed for analyzing the dynamic scattering stress wave field. The shear stress field and the compressive stress field in the layered stratum with two scattering sources are calculated by shear cone and compressive cone, respectively. Furthermore, the stress fields in the subsoil with two foundations are divided into six zones, and the P wave and S wave are analyzed in each zone. Numerical results are provided to illustrate features of the added stress field for two surface foundations under vertical and horizontal sinusoidal force excitation. The proposed cone model may be useful in handling some of the complex problems associated with multi-scattering sources.
基金Project 50279005 supported by the National Natural Science Foundation of China
文摘To ensure the safety of buildings surrounding foundation pits, a study was made on a settlement monitoring and trend prediction method. A statistical testing method for analyzing the stability of a settlement monitoring datum has been discussed. According to a comprehensive survey, data of 16 stages at operating control point, were verified by a standard t test to determine the stability of the operating control point. A stationary auto-regression model, AR(p), used for the observation point settlement prediction has been investigated. Given the 16 stages of the settlement data at an observation point, the applicability of this model was analyzed. Settlement of last four stages was predicted using the stationary auto-regression model AR (1); the maximum difference between predicted and measured values was 0.6 mm, indicating good prediction results of the model. Hence, this model can be applied to settlement predictions for buildings surrounding foundation pits.
