At present, Chinas civil aviation industry has entered a new stage of steady development, and various types of civil aircraft emerge in one after another. Aircraft as a special equipment, in order to ensure the safety...At present, Chinas civil aviation industry has entered a new stage of steady development, and various types of civil aircraft emerge in one after another. Aircraft as a special equipment, in order to ensure the safety of flight, airworthiness information management has extremely high requirements. In order to improve the level of airworthiness management, the introduction of information management means, make airworthiness management more scientific, consider from multiple goals and multiple dimensions, and improve the scientific nature and reliability of airworthiness management, so as to further improve the safety and stability of aircraft operation.展开更多
为了保证运维阶段桥梁结构安全,提升桥梁运维工作的效率,开展公路混凝土梁式桥运维阶段建筑信息模型(building information modeling,BIM)技术应用研究。在对公路桥梁现行编码体系进行扩展的基础上,提出1种参数化快速建模方法,以快速完...为了保证运维阶段桥梁结构安全,提升桥梁运维工作的效率,开展公路混凝土梁式桥运维阶段建筑信息模型(building information modeling,BIM)技术应用研究。在对公路桥梁现行编码体系进行扩展的基础上,提出1种参数化快速建模方法,以快速完成桥梁构件族的创建与整体模型的集成。借助Autodesk Revit软件应用程序编程接口(application programming interface,API),采用C#语言,开发公路混凝土梁式桥智慧运维状态评估系统,以实际工程应用进行验证分析。研究结果表明:全面统一的桥梁信息编码体系,能够提高桥梁信息统计与检索效率;提出的快速建模方法能够显著减少建模工作量,建模时间较传统建模方法可减少60%,并保证模型的准确性与规范性;运维状态评估系统能够实现养护数据的充分利用与桥梁评定工作的自动化,通过对桥梁运维信息的有效组织,实现服役性能的长期追踪,从而确保运营期桥梁结构状态安全稳定。研究结果可为公路混凝土梁式桥运维管理提供技术支撑,提升桥梁运维的数字化水平。展开更多
Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters accordi...Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.展开更多
This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble lear...This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.展开更多
With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration wi...With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.展开更多
In recent years,Volunteered Geographic Information(VGI)has emerged as a crucial source of mapping data,contributed by users through crowdsourcing platforms such as OpenStreetMap.This paper presents a novel approach th...In recent years,Volunteered Geographic Information(VGI)has emerged as a crucial source of mapping data,contributed by users through crowdsourcing platforms such as OpenStreetMap.This paper presents a novel approach that Integrates Large Language Models(LLMs)into a fully automated mapping workflow,utilizing VGI data.The process leverages Prompt Engineering,which involves designing and optimizing input instructions to ensure the LLM produces desired mapping outputs.By constructing precise and detailed prompts,LLM agents are able to accurately interpret mapping requirements,and autonomously extract,analyze,and process VGI geospatial data.They dynamically interact with mapping tools to automate the entire mapping process—from data acquisition to map generation.This approach significantly streamlines the creation of high-quality mapping outputs,reducing the time and resources typically required for such tasks.Moreover,the system lowers the barrier for non-expert users,enabling them to generate accurate maps without extensive technical expertise.Through various case studies,we demonstrate the LLM application across different mapping scenarios,highlighting its potential to enhance the efficiency,accuracy,and accessibility of map production.The results suggest that LLM-powered mapping systems can not only optimize VGI data processing but also expand the usability of ubiquitous mapping across diverse fields,including urban planning and infrastructure development.展开更多
The ongoing revolution in information technology is reshaping human life. In the realm of health behavior, wearable technology emerges as a leading digital solution,capturing physical behaviors (i.e., physical activit...The ongoing revolution in information technology is reshaping human life. In the realm of health behavior, wearable technology emerges as a leading digital solution,capturing physical behaviors (i.e., physical activity, sedentary habits, sleep patterns) within the 24-h cycle of daily life. Wearables are applied in research, clinical practice, and as lifestyle devices;most obvious, they promise to be a key element for increasing human physical activity, one of the biggest health challenges nowadays.展开更多
An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyram...An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyramid network(FPN)structure of the original YOLOv8 mode is replaced by the generalized-FPN(GFPN)structure in GiraffeDet to realize the"cross-layer"and"cross-scale"adaptive feature fusion,to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model.Secondly,a pyramid-pool module of multi atrous spatial pyramid pooling(MASPP)is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features,so as to improve the processing ability of the model for multi-scale objects.The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92%and mean average precision(mAP)is 87.9%,respectively 3.5%and 1.7%higher than those of the original model.It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved.展开更多
Sensors are the source of information technology and the first unit of intelligent systems,providing real-world"data"for artificial intelligence.They play a crucial role in various aspects of the national ec...Sensors are the source of information technology and the first unit of intelligent systems,providing real-world"data"for artificial intelligence.They play a crucial role in various aspects of the national economy and the people's livelihood,such as national defense security and the development of new quality productive forces.This paper provides a comprehensive survey of how sensors should adapt to the current upsurge of artificial intelligence,analyzing their technical connotations,application characteristics,and inherent limitations.Furthermore,with a sensor-oriented mindset,it is proposed that sensors will dominate information technology,upgrade connotations,advance ubiquitous bionic intelligence and engage in a"symbiotic dance"with artificial intelligence.This overview provides a promising direction for the higher-level development of sensors and artificial intelligence.展开更多
Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detectio...Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detection accuracy.Using multiple methods to carry out a comprehensive evaluation can eff ectively improve the accuracy of advanced geological prediction results.In this study,geological information is combined with the detection results of geophysical methods,including transient electromagnetic,induced polarization,and tunnel seismic prediction,to establish a comprehensive analysis method of adverse geology.First,the possible main adverse geological problems are determined according to the geological information.Subsequently,various physical parameters of the rock mass in front of the tunnel face can then be derived on the basis of multisource geophysical data.Finally,based on the analysis results of geological information,the multisource data fusion algorithm is used to determine the type,location,and scale of adverse geology.The advanced geological prediction results that can provide eff ective guidance for tunnel construction can then be obtained.展开更多
BACKGROUND Inflammatory bowel disease(IBD)is a global health burden that affects millions of individuals worldwide,necessitating extensive patient education.Large language models(LLMs)hold promise for addressing patie...BACKGROUND Inflammatory bowel disease(IBD)is a global health burden that affects millions of individuals worldwide,necessitating extensive patient education.Large language models(LLMs)hold promise for addressing patient information needs.However,LLM use to deliver accurate and comprehensible IBD-related medical information has yet to be thoroughly investigated.AIM To assess the utility of three LLMs(ChatGPT-4.0,Claude-3-Opus,and Gemini-1.5-Pro)as a reference point for patients with IBD.METHODS In this comparative study,two gastroenterology experts generated 15 IBD-related questions that reflected common patient concerns.These questions were used to evaluate the performance of the three LLMs.The answers provided by each model were independently assessed by three IBD-related medical experts using a Likert scale focusing on accuracy,comprehensibility,and correlation.Simultaneously,three patients were invited to evaluate the comprehensibility of their answers.Finally,a readability assessment was performed.RESULTS Overall,each of the LLMs achieved satisfactory levels of accuracy,comprehensibility,and completeness when answering IBD-related questions,although their performance varies.All of the investigated models demonstrated strengths in providing basic disease information such as IBD definition as well as its common symptoms and diagnostic methods.Nevertheless,when dealing with more complex medical advice,such as medication side effects,dietary adjustments,and complication risks,the quality of answers was inconsistent between the LLMs.Notably,Claude-3-Opus generated answers with better readability than the other two models.CONCLUSION LLMs have the potential as educational tools for patients with IBD;however,there are discrepancies between the models.Further optimization and the development of specialized models are necessary to ensure the accuracy and safety of the information provided.展开更多
It is difficult to improve both energy consumption and detection accuracy simultaneously,and even to obtain the trade-off between them,when detecting and tracking moving targets,especially for Underwater Wireless Sens...It is difficult to improve both energy consumption and detection accuracy simultaneously,and even to obtain the trade-off between them,when detecting and tracking moving targets,especially for Underwater Wireless Sensor Networks(UWSNs).To this end,this paper investigates the relationship between the Degree of Target Change(DoTC)and the detection period,as well as the impact of individual nodes.A Hierarchical Detection and Tracking Approach(HDTA)is proposed.Firstly,the network detection period is determined according to DoTC,which reflects the variation of target motion.Secondly,during the network detection period,each detection node calculates its own node detection period based on the detection mutual information.Taking DoTC as pheromone,an ant colony algorithm is proposed to adaptively adjust the network detection period.The simulation results show that the proposed HDTA with the optimizations of network level and node level significantly improves the detection accuracy by 25%and the network energy consumption by 10%simultaneously,compared to the traditional adaptive period detection schemes.展开更多
Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environ...Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.展开更多
The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(E...The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole(IOD)events.The detailed processes of ENSO and/or IOD induced anomalies impacting on the ITF,however,are still not clear.In this study,this issue is investigated through causal relation,statistical,and dynamical analyses based on satellite observation.The results show that the driven mechanisms of ENSO on the ITF include two aspects.Firstly,the ENSO related wind field anomalies driven anomalous cyclonic ocean circulation in the western Pacific,and off equatorial upwelling Rossby waves propagating westward to arrive at the western boundary of the Pacific,both tend to induce negative sea surface height anomalies(SSHA)in the western Pacific,favoring ITF reduction since the develop of the El Niño through the following year.Secondly,the ENSO events modulate equatorial Indian Ocean zonal winds through Walker Circulation,which in turn trigger eastward propagating upwelling Kelvin waves and westward propagating downwelling Rossby waves.The Rossby waves are reflected into downwelling Kelvin waves,which then propagate eastward along the equator and the Sumatra-Java coast in the Indian Ocean.As a result,the wave dynamics tend to generate negative(positive)SSHA in the eastern Indian Ocean,and thus enhance(reduce)the ITF transport with time lag of 0-6 months(9-12 months),respectively.Under the IOD condition,the wave dynamics also tend to enhance the ITF in the positive IOD year,and reduce the ITF in the following year.展开更多
The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of user...The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.展开更多
With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions...With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying reasons.This comprehension is crucial for making informed strategic decisions in various business and societal contexts.However,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause extraction.To address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment mechanisms.The model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause pairs.Second,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among tasks.The proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 score.Experimental results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its effectiveness.This research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-cause pair extraction.However,the study’s limitation lies in the data sources,potentially restricting the generalizability of the findings.展开更多
1.C.Li,"Holding‘China Inc.’Together:The CCP and The Rise of China’s Yangqi",The China Quarterly,Vol.228,2016,pp.927-949.2.J.Gao,"‘Bypass the Lying Mouths’:How Does the CCP Tackle Information Distor...1.C.Li,"Holding‘China Inc.’Together:The CCP and The Rise of China’s Yangqi",The China Quarterly,Vol.228,2016,pp.927-949.2.J.Gao,"‘Bypass the Lying Mouths’:How Does the CCP Tackle Information Distortion at Local Levels?",The China Quarterly,Vol.228,2016,pp.950-969.3.C.Sorace,"Party Spirit Made Flesh:The Production of Legitimacy in the Aftermath of the 2008Sichuan Earthquake",The China Journal,Vol.76,2016,pp.41-62.4.Y.Yeo,"Complementing the Local Discipline Inspection Commissions of the CCP:Empowerment of the Central Inspection Groups",Journal of Contemporary China,Vol.25,No.97,2016,pp.59-74.展开更多
This study analyzes the User Interface(UI)and User Experience(UX)of information systems that provide local government information.The systems analyzed are the Local Administrative Comprehensive Information Disclosure ...This study analyzes the User Interface(UI)and User Experience(UX)of information systems that provide local government information.The systems analyzed are the Local Administrative Comprehensive Information Disclosure System(Zheripan),the Integrated Local Financial Disclosure System(Qinching Online),and the Local Regulations Information System(12348 Zhejiang Legal Network).The Local Administrative Comprehensive Information Disclosure System offers public service and personnel information,while the Integrated Local Financial Disclosure System provides financial information,and the Local Regulations Information System offers legal information as its main content.The analysis framework utilized three elements:objective data,psychological factors,and heuristic evaluation.The results of the first objective data analysis show that approximately 70%of visits to Zheripan and Qinching Online are through search,and the time spent on the homepage is short.In contrast,about 70%of visits to the 12348 Zhejiang Legal Network are direct visits,with users browsing multiple pages with a clear purpose.In terms of data provision methods,Zheripan provides two types of data in three formats,Qinching Online offers 28 types of data in five formats,and 12348 Zhejiang Legal Network provides one type of information in a single format.The second psychological factor analysis found that all three websites had a number of menus suitable for short-term cognitive capacity.However,only one of the sites had a layout that considered the user’s eye movement.Finally,the heuristic evaluation revealed that most of the evaluation criteria were not met.While the design is relatively simple and follows standards,feedback for users,error prevention,and help options were lacking.Moreover,the user-specific usability was low,and the systems remained at the information-providing level.Based on these findings,both short-term and long-term improvement measures for creating an interactive system beyond simple information disclosure are proposed.展开更多
Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information ...Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information and providing navigation services.展开更多
文摘At present, Chinas civil aviation industry has entered a new stage of steady development, and various types of civil aircraft emerge in one after another. Aircraft as a special equipment, in order to ensure the safety of flight, airworthiness information management has extremely high requirements. In order to improve the level of airworthiness management, the introduction of information management means, make airworthiness management more scientific, consider from multiple goals and multiple dimensions, and improve the scientific nature and reliability of airworthiness management, so as to further improve the safety and stability of aircraft operation.
基金supported by the Innovation Foundation of Provincial Education Department of Gansu(2024B-005)the Gansu Province National Science Foundation(22YF7GA182)the Fundamental Research Funds for the Central Universities(No.lzujbky2022-kb01)。
文摘Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.
基金the University of Transport Technology under the project entitled“Application of Machine Learning Algorithms in Landslide Susceptibility Mapping in Mountainous Areas”with grant number DTTD2022-16.
文摘This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of 0.926.These results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.
基金Under the auspices of National Natural Science Foundation of China(No.42330510)。
文摘With the development of smart cities and smart technologies,parks,as functional units of the city,are facing smart transformation.The development of smart parks can help address challenges of technology integration within urban spaces and serve as testbeds for exploring smart city planning and governance models.Information models facilitate the effective integration of technology into space.Building Information Modeling(BIM)and City Information Modeling(CIM)have been widely used in urban construction.However,the existing information models have limitations in the application of the park,so it is necessary to develop an information model suitable for the park.This paper first traces the evolution of park smart transformation,reviews the global landscape of smart park development,and identifies key trends and persistent challenges.Addressing the particularities of parks,the concept of Park Information Modeling(PIM)is proposed.PIM leverages smart technologies such as artificial intelligence,digital twins,and collaborative sensing to help form a‘space-technology-system’smart structure,enabling systematic management of diverse park spaces,addressing the deficiency in park-level information models,and aiming to achieve scale articulation between BIM and CIM.Finally,through a detailed top-level design application case study of the Nanjing Smart Education Park in China,this paper illustrates the translation process of the PIM concept into practice,showcasing its potential to provide smart management tools for park managers and enhance services for park stakeholders,although further empirical validation is required.
基金National Natural Science Foundation of china(No.42371446)Natural Science Foundatiorof Hubei Province(No.2024AFD412)Fundamental Research Funds for National Universities,China University of Geosciences(Wuhan)(No.2024XLA17).
文摘In recent years,Volunteered Geographic Information(VGI)has emerged as a crucial source of mapping data,contributed by users through crowdsourcing platforms such as OpenStreetMap.This paper presents a novel approach that Integrates Large Language Models(LLMs)into a fully automated mapping workflow,utilizing VGI data.The process leverages Prompt Engineering,which involves designing and optimizing input instructions to ensure the LLM produces desired mapping outputs.By constructing precise and detailed prompts,LLM agents are able to accurately interpret mapping requirements,and autonomously extract,analyze,and process VGI geospatial data.They dynamically interact with mapping tools to automate the entire mapping process—from data acquisition to map generation.This approach significantly streamlines the creation of high-quality mapping outputs,reducing the time and resources typically required for such tasks.Moreover,the system lowers the barrier for non-expert users,enabling them to generate accurate maps without extensive technical expertise.Through various case studies,we demonstrate the LLM application across different mapping scenarios,highlighting its potential to enhance the efficiency,accuracy,and accessibility of map production.The results suggest that LLM-powered mapping systems can not only optimize VGI data processing but also expand the usability of ubiquitous mapping across diverse fields,including urban planning and infrastructure development.
基金funded in part by the German Research Foundation(Grant reference:496846758).
文摘The ongoing revolution in information technology is reshaping human life. In the realm of health behavior, wearable technology emerges as a leading digital solution,capturing physical behaviors (i.e., physical activity, sedentary habits, sleep patterns) within the 24-h cycle of daily life. Wearables are applied in research, clinical practice, and as lifestyle devices;most obvious, they promise to be a key element for increasing human physical activity, one of the biggest health challenges nowadays.
基金supported by the National Natural Science Foundation of China(No.62241109)the Tianjin Science and Technology Commissioner Project(No.20YDTPJC01110)。
文摘An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyramid network(FPN)structure of the original YOLOv8 mode is replaced by the generalized-FPN(GFPN)structure in GiraffeDet to realize the"cross-layer"and"cross-scale"adaptive feature fusion,to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model.Secondly,a pyramid-pool module of multi atrous spatial pyramid pooling(MASPP)is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features,so as to improve the processing ability of the model for multi-scale objects.The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92%and mean average precision(mAP)is 87.9%,respectively 3.5%and 1.7%higher than those of the original model.It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved.
基金funded by National Natural Science Foundation of China(52175492)Pilot Project for the Establishment of Virtual Teaching and Research Offices in Beijing's Higher Education Institutions(Grant No.4313054 and 4313055)Beijing Undergraduate Teaching Reform and Innovation Project of Higher Education(Grant No.ZF211B2002 and ZF211B2405).
文摘Sensors are the source of information technology and the first unit of intelligent systems,providing real-world"data"for artificial intelligence.They play a crucial role in various aspects of the national economy and the people's livelihood,such as national defense security and the development of new quality productive forces.This paper provides a comprehensive survey of how sensors should adapt to the current upsurge of artificial intelligence,analyzing their technical connotations,application characteristics,and inherent limitations.Furthermore,with a sensor-oriented mindset,it is proposed that sensors will dominate information technology,upgrade connotations,advance ubiquitous bionic intelligence and engage in a"symbiotic dance"with artificial intelligence.This overview provides a promising direction for the higher-level development of sensors and artificial intelligence.
基金National Natural Science Foundation of China(grant numbers 42293351,41877239,51422904 and 51379112).
文摘Advanced geological prediction is a crucial means to ensure safety and efficiency in tunnel construction.However,diff erent advanced geological forecasting methods have their own limitations,resulting in poor detection accuracy.Using multiple methods to carry out a comprehensive evaluation can eff ectively improve the accuracy of advanced geological prediction results.In this study,geological information is combined with the detection results of geophysical methods,including transient electromagnetic,induced polarization,and tunnel seismic prediction,to establish a comprehensive analysis method of adverse geology.First,the possible main adverse geological problems are determined according to the geological information.Subsequently,various physical parameters of the rock mass in front of the tunnel face can then be derived on the basis of multisource geophysical data.Finally,based on the analysis results of geological information,the multisource data fusion algorithm is used to determine the type,location,and scale of adverse geology.The advanced geological prediction results that can provide eff ective guidance for tunnel construction can then be obtained.
基金Supported by the China Health Promotion Foundation Young Doctors'Research Foundation for Inflammatory Bowel Disease,the Taishan Scholars Program of Shandong Province,China,No.tsqn202306343National Natural Science Foundation of China,No.82270578.
文摘BACKGROUND Inflammatory bowel disease(IBD)is a global health burden that affects millions of individuals worldwide,necessitating extensive patient education.Large language models(LLMs)hold promise for addressing patient information needs.However,LLM use to deliver accurate and comprehensible IBD-related medical information has yet to be thoroughly investigated.AIM To assess the utility of three LLMs(ChatGPT-4.0,Claude-3-Opus,and Gemini-1.5-Pro)as a reference point for patients with IBD.METHODS In this comparative study,two gastroenterology experts generated 15 IBD-related questions that reflected common patient concerns.These questions were used to evaluate the performance of the three LLMs.The answers provided by each model were independently assessed by three IBD-related medical experts using a Likert scale focusing on accuracy,comprehensibility,and correlation.Simultaneously,three patients were invited to evaluate the comprehensibility of their answers.Finally,a readability assessment was performed.RESULTS Overall,each of the LLMs achieved satisfactory levels of accuracy,comprehensibility,and completeness when answering IBD-related questions,although their performance varies.All of the investigated models demonstrated strengths in providing basic disease information such as IBD definition as well as its common symptoms and diagnostic methods.Nevertheless,when dealing with more complex medical advice,such as medication side effects,dietary adjustments,and complication risks,the quality of answers was inconsistent between the LLMs.Notably,Claude-3-Opus generated answers with better readability than the other two models.CONCLUSION LLMs have the potential as educational tools for patients with IBD;however,there are discrepancies between the models.Further optimization and the development of specialized models are necessary to ensure the accuracy and safety of the information provided.
文摘It is difficult to improve both energy consumption and detection accuracy simultaneously,and even to obtain the trade-off between them,when detecting and tracking moving targets,especially for Underwater Wireless Sensor Networks(UWSNs).To this end,this paper investigates the relationship between the Degree of Target Change(DoTC)and the detection period,as well as the impact of individual nodes.A Hierarchical Detection and Tracking Approach(HDTA)is proposed.Firstly,the network detection period is determined according to DoTC,which reflects the variation of target motion.Secondly,during the network detection period,each detection node calculates its own node detection period based on the detection mutual information.Taking DoTC as pheromone,an ant colony algorithm is proposed to adaptively adjust the network detection period.The simulation results show that the proposed HDTA with the optimizations of network level and node level significantly improves the detection accuracy by 25%and the network energy consumption by 10%simultaneously,compared to the traditional adaptive period detection schemes.
基金supported by the project“GEF9874:Strengthening Coordinated Approaches to Reduce Invasive Alien Species(lAS)Threats to Globally Significant Agrobiodiversity and Agroecosystems in China”funding from the Excellent Talent Training Funding Project in Dongcheng District,Beijing,with project number 2024-dchrcpyzz-9.
文摘Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.
基金The Fund of Laoshan Laboratory under contract No.LSKJ202202700the Basic Scientific Fund for National Public Research Institutes of China under contract No.2024Q02+1 种基金the National Natural Science Foundation of China under contract Nos 42076023 and 42430402the Global Change and Air-Sea InteractionⅡProject under contract No.GASI-01-ATP-STwin.
文摘The Indonesian Throughflow(ITF)plays important roles in global ocean circulation and climate systems.Previous studies suggested the ITF interannual variability is driven by both the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole(IOD)events.The detailed processes of ENSO and/or IOD induced anomalies impacting on the ITF,however,are still not clear.In this study,this issue is investigated through causal relation,statistical,and dynamical analyses based on satellite observation.The results show that the driven mechanisms of ENSO on the ITF include two aspects.Firstly,the ENSO related wind field anomalies driven anomalous cyclonic ocean circulation in the western Pacific,and off equatorial upwelling Rossby waves propagating westward to arrive at the western boundary of the Pacific,both tend to induce negative sea surface height anomalies(SSHA)in the western Pacific,favoring ITF reduction since the develop of the El Niño through the following year.Secondly,the ENSO events modulate equatorial Indian Ocean zonal winds through Walker Circulation,which in turn trigger eastward propagating upwelling Kelvin waves and westward propagating downwelling Rossby waves.The Rossby waves are reflected into downwelling Kelvin waves,which then propagate eastward along the equator and the Sumatra-Java coast in the Indian Ocean.As a result,the wave dynamics tend to generate negative(positive)SSHA in the eastern Indian Ocean,and thus enhance(reduce)the ITF transport with time lag of 0-6 months(9-12 months),respectively.Under the IOD condition,the wave dynamics also tend to enhance the ITF in the positive IOD year,and reduce the ITF in the following year.
基金funding from King Saud University through Researchers Supporting Project number(RSP2024R387),King Saud University,Riyadh,Saudi Arabia.
文摘The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile networks.These networks are sufficiently scaled to interconnect billions of users and devices.Researchers in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous vehicles.NextG continuously improves its network functionality to support these applications.Multiple input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in conjunctionwithNextG.This article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial attacks.The technique aims to create long-lasting and secure NextG networks using this extended approach.The viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this research.Moreover,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.
文摘With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant importance.Emotion-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying reasons.This comprehension is crucial for making informed strategic decisions in various business and societal contexts.However,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause extraction.To address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment mechanisms.The model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause pairs.Second,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among tasks.The proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 score.Experimental results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its effectiveness.This research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-cause pair extraction.However,the study’s limitation lies in the data sources,potentially restricting the generalizability of the findings.
文摘1.C.Li,"Holding‘China Inc.’Together:The CCP and The Rise of China’s Yangqi",The China Quarterly,Vol.228,2016,pp.927-949.2.J.Gao,"‘Bypass the Lying Mouths’:How Does the CCP Tackle Information Distortion at Local Levels?",The China Quarterly,Vol.228,2016,pp.950-969.3.C.Sorace,"Party Spirit Made Flesh:The Production of Legitimacy in the Aftermath of the 2008Sichuan Earthquake",The China Journal,Vol.76,2016,pp.41-62.4.Y.Yeo,"Complementing the Local Discipline Inspection Commissions of the CCP:Empowerment of the Central Inspection Groups",Journal of Contemporary China,Vol.25,No.97,2016,pp.59-74.
文摘This study analyzes the User Interface(UI)and User Experience(UX)of information systems that provide local government information.The systems analyzed are the Local Administrative Comprehensive Information Disclosure System(Zheripan),the Integrated Local Financial Disclosure System(Qinching Online),and the Local Regulations Information System(12348 Zhejiang Legal Network).The Local Administrative Comprehensive Information Disclosure System offers public service and personnel information,while the Integrated Local Financial Disclosure System provides financial information,and the Local Regulations Information System offers legal information as its main content.The analysis framework utilized three elements:objective data,psychological factors,and heuristic evaluation.The results of the first objective data analysis show that approximately 70%of visits to Zheripan and Qinching Online are through search,and the time spent on the homepage is short.In contrast,about 70%of visits to the 12348 Zhejiang Legal Network are direct visits,with users browsing multiple pages with a clear purpose.In terms of data provision methods,Zheripan provides two types of data in three formats,Qinching Online offers 28 types of data in five formats,and 12348 Zhejiang Legal Network provides one type of information in a single format.The second psychological factor analysis found that all three websites had a number of menus suitable for short-term cognitive capacity.However,only one of the sites had a layout that considered the user’s eye movement.Finally,the heuristic evaluation revealed that most of the evaluation criteria were not met.While the design is relatively simple and follows standards,feedback for users,error prevention,and help options were lacking.Moreover,the user-specific usability was low,and the systems remained at the information-providing level.Based on these findings,both short-term and long-term improvement measures for creating an interactive system beyond simple information disclosure are proposed.
文摘Nowadays,spatiotemporal information,positioning,and navigation services have become critical components of new infrastructure.Precise positioning technology is indispensable for determining spatiotemporal information and providing navigation services.
