As embodied intelligence(EI),large language models(LLMs),and cloud computing continue to advance,Industry5.0 facilitates the development of industrial artificial intelligence(Ind AI)through cyber-physical-social syste...As embodied intelligence(EI),large language models(LLMs),and cloud computing continue to advance,Industry5.0 facilitates the development of industrial artificial intelligence(Ind AI)through cyber-physical-social systems(CPSSs)with a human-centric focus.These technologies are organized by the system-wide approach of Industry 5.0,in order to empower the manufacturing industry to achieve broader societal goals of job creation,economic growth,and green production.This survey first provides a general framework of smart manufacturing in the context of Industry 5.0.Wherein,the embodied agents,like robots,sensors,and actuators,are the carriers for Ind AI,facilitating the development of the self-learning intelligence in individual entities,the collaborative intelligence in production lines and factories(smart systems),and the swarm intelligence within industrial clusters(systems of smart systems).Through the framework of CPSSs,the key technologies and their possible applications for supporting the single-agent,multi-agent and swarm-agent embodied Ind AI have been reviewed,such as the embodied perception,interaction,scheduling,multi-mode large language models,and collaborative training.Finally,to stimulate future research in this area,the open challenges and opportunities of applying Industry 5.0 to smart manufacturing are identified and discussed.The perspective of Industry 5.0-driven manufacturing industry aims to enhance operational productivity and efficiency by seamlessly integrating the virtual and physical worlds in a human-centered manner,thereby fostering an intelligent,sustainable,and resilient industrial landscape.展开更多
The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-lear...The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.展开更多
In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and ta...In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.展开更多
Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important r...Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.展开更多
Single Pilot Operations(SPO),as a NextGen concept of operation,can save both crew costs and human resources for airlines,and has attracted the attention of aviation researchers.To explore in advance the problems that ...Single Pilot Operations(SPO),as a NextGen concept of operation,can save both crew costs and human resources for airlines,and has attracted the attention of aviation researchers.To explore in advance the problems that the introduction of SPO into the aviation system would bring,the Human-Centered Design(HCD)approach has been widely used in the development of SPO.A systematic review of the progress of HCD approach in SPO research can promote further development of SPO.In this paper,the literature resources of SPO were firstly retrieved from scientific research databases by subject search and were used as the input of scientometric analysis to obtain the highly cited literature,the number of annual publications,and the co-authorship network,which enables readers to understand the research trends and research groups of current SPO.Secondly,the development,application,and research process of the HCD approach were introduced in detail,and the progress of the HCD approach in SPO research was reviewed systematically from three aspects:concept design,function allocation,and system evaluation.Finally,limitations of current SPO research and future research directions for applying the HCD approach to SPO were also discussed.展开更多
Although there are certain differences in the center of gravity between rural revitalization and human-centered urbanization,their connotations and goals require that both must be promoted in concert.Therefore,based o...Although there are certain differences in the center of gravity between rural revitalization and human-centered urbanization,their connotations and goals require that both must be promoted in concert.Therefore,based on a deep understanding of the connotation of rural revitalization and human-centered urbanization,it is necessary to clarify the goals of the two through the two-way flow of elements between urban and rural areas,the urban-rural linkage of industries,to achieve coordinated promotion of rural revitalization and human-centered urbanization in China.展开更多
The special issue aims to address a broad spectrum of topics ranging from human-centered intelligent robots acting as a servant,secretary,or companion to intelligent robotic functions.The special issue publishes origi...The special issue aims to address a broad spectrum of topics ranging from human-centered intelligent robots acting as a servant,secretary,or companion to intelligent robotic functions.The special issue publishes original papers of innovative ideas and concepts,new discoveries,and novel applications and business models relevant to the field of human-centered intelligent robots.In this special issue,modeling,intelligent control,展开更多
This letter proposes a categorization matrix to analyze the playing style of a computer game player for a shooting game genre. Our aim is to use human-centered modeling as a strategy for adaptive games based on entert...This letter proposes a categorization matrix to analyze the playing style of a computer game player for a shooting game genre. Our aim is to use human-centered modeling as a strategy for adaptive games based on entertainment measure to evaluate the playing experience. We utilized a self-organizing map (SOM) to cluster the player's style with the data obtained while playing the game. We further argued that style-based adaptation contributes to higher enjoyment, and this is reflected in our experiment using a supervised multilayered perceptron (MLP) network.展开更多
Detecting pavement cracks is critical for road safety and infrastructure management.Traditional methods,relying on manual inspection and basic image processing,are time-consuming and prone to errors.Recent deep-learni...Detecting pavement cracks is critical for road safety and infrastructure management.Traditional methods,relying on manual inspection and basic image processing,are time-consuming and prone to errors.Recent deep-learning(DL)methods automate crack detection,but many still struggle with variable crack patterns and environmental conditions.This study aims to address these limitations by introducing the Masker Transformer,a novel hybrid deep learning model that integrates the precise localization capabilities of Mask Region-based Convolutional Neural Network(Mask R-CNN)with the global contextual awareness of Vision Transformer(ViT).The research focuses on leveraging the strengths of both architectures to enhance segmentation accuracy and adaptability across different pavement conditions.We evaluated the performance of theMaskerTransformer against other state-of-theartmodels such asU-Net,TransformerU-Net(TransUNet),U-NetTransformer(UNETr),SwinU-NetTransformer(Swin-UNETr),You Only Look Once version 8(YoloV8),and Mask R-CNN using two benchmark datasets:Crack500 and DeepCrack.The findings reveal that the MaskerTransformer significantly outperforms the existing models,achieving the highest Dice SimilarityCoefficient(DSC),precision,recall,and F1-Score across both datasets.Specifically,the model attained a DSC of 80.04%on Crack500 and 91.37%on DeepCrack,demonstrating superior segmentation accuracy and reliability.The high precision and recall rates further substantiate its effectiveness in real-world applications,suggesting that the Masker Transformer can serve as a robust tool for automated pavement crack detection,potentially replacing more traditional methods.展开更多
This paper first introduces the development process of urban street green landscape in China and the human-centered thinking of the design of urban street green landscape.On the basis of detailed elaboration of the ba...This paper first introduces the development process of urban street green landscape in China and the human-centered thinking of the design of urban street green landscape.On the basis of detailed elaboration of the basic theories of urban street green landscape,it analyzes the existing problems and causes for urban street green landscape.Then,from the perspective of human-centered thought,it comes up with several measures for optimizing the green landscape design of urban streets,to provide much more human-centered experience of urban street green landscape.展开更多
With the development of mechanization popularity in rural area, agricultural machinery product not only needs to meet the production goals, and also requires the simple operation and human-centered. Human-centered des...With the development of mechanization popularity in rural area, agricultural machinery product not only needs to meet the production goals, and also requires the simple operation and human-centered. Human-centered design is always, on the basis of the user＇ s requirement and usage, to think over the issues by regarding operator as the center, and to design the products by emphasizing the ease of use and understandability during design and manufacture. In this study, Stubble-Mulch Rotocultivator for Boat Tractor （SMRBT） is chosen as the design object. The coordination approach of the user, machine and environment is discussed by deeply investigating their relationship, which is an empirical study of the human-centered technology of agricultural machinery.展开更多
To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is deve...To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.展开更多
Recently,for developing neuromorphic visual systems,adaptive optoelectronic devices become one of the main research directions and attract extensive focus to achieve optoelectronic transistors with high performances a...Recently,for developing neuromorphic visual systems,adaptive optoelectronic devices become one of the main research directions and attract extensive focus to achieve optoelectronic transistors with high performances and flexible func-tionalities.In this review,based on a description of the biological adaptive functions that are favorable for dynamically perceiv-ing,filtering,and processing information in the varying environment,we summarize the representative strategies for achiev-ing these adaptabilities in optoelectronic transistors,including the adaptation for detecting information,adaptive synaptic weight change,and history-dependent plasticity.Moreover,the key points of the corresponding strategies are comprehen-sively discussed.And the applications of these adaptive optoelectronic transistors,including the adaptive color detection,sig-nal filtering,extending the response range of light intensity,and improve learning efficiency,are also illustrated separately.Lastly,the challenges faced in developing adaptive optoelectronic transistor for artificial vision system are discussed.The descrip-tion of biological adaptive functions and the corresponding inspired neuromorphic devices are expected to provide insights for the design and application of next-generation artificial visual systems.展开更多
基金supported by the National Key Research and Development Program of China(2021YFB1714300)the National Natural Science Foundation of China(62233005,U2441245,62173141)+3 种基金CNPC Innovation Found(2024DQ02-0507)Shanghai Natural Science(24ZR1416400)Shanghai Baiyu Lan Talent Program Pujiang Project(24PJD020)the Programme of Introducing Talents of Discipline to Universities(the 111 Project)(B17017)
文摘As embodied intelligence(EI),large language models(LLMs),and cloud computing continue to advance,Industry5.0 facilitates the development of industrial artificial intelligence(Ind AI)through cyber-physical-social systems(CPSSs)with a human-centric focus.These technologies are organized by the system-wide approach of Industry 5.0,in order to empower the manufacturing industry to achieve broader societal goals of job creation,economic growth,and green production.This survey first provides a general framework of smart manufacturing in the context of Industry 5.0.Wherein,the embodied agents,like robots,sensors,and actuators,are the carriers for Ind AI,facilitating the development of the self-learning intelligence in individual entities,the collaborative intelligence in production lines and factories(smart systems),and the swarm intelligence within industrial clusters(systems of smart systems).Through the framework of CPSSs,the key technologies and their possible applications for supporting the single-agent,multi-agent and swarm-agent embodied Ind AI have been reviewed,such as the embodied perception,interaction,scheduling,multi-mode large language models,and collaborative training.Finally,to stimulate future research in this area,the open challenges and opportunities of applying Industry 5.0 to smart manufacturing are identified and discussed.The perspective of Industry 5.0-driven manufacturing industry aims to enhance operational productivity and efficiency by seamlessly integrating the virtual and physical worlds in a human-centered manner,thereby fostering an intelligent,sustainable,and resilient industrial landscape.
基金financially supported by the National Science Fund for Distinguished Young Scholars,China(No.52025041)the National Natural Science Foundation of China(Nos.52450003,U2341267,and 52174294)+1 种基金the National Postdoctoral Program for Innovative Talents,China(No.BX20240437)the Fundamental Research Funds for the Central Universities,China(Nos.FRF-IDRY-23-037 and FRF-TP-20-02C2)。
文摘The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.
文摘In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.
基金supported in part by the National Natural Science Foundation of China(61573147,91520201,61625303,61522302,61761130080)Guangzhou Research Collaborative Innovation Projects(2014Y2-00507)+2 种基金Guangdong Science and Technology Research Collaborative Innovation Projects(20138010102010,20148090901056,20158020214003)Guangdong Science and Technology Plan Project(Application Technology Research Foundation)(2015B020233006)National High-Tech Research and De-velopment Program of China(863 Program)(2015AA042303)
文摘Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.
基金This research was funded by the Natural Science Foundation of Shanghai,China(No.20ZR1427800)the New Young Teachers Launch Program of Shanghai Jiao Tong University,China(No.20X100040036).
文摘Single Pilot Operations(SPO),as a NextGen concept of operation,can save both crew costs and human resources for airlines,and has attracted the attention of aviation researchers.To explore in advance the problems that the introduction of SPO into the aviation system would bring,the Human-Centered Design(HCD)approach has been widely used in the development of SPO.A systematic review of the progress of HCD approach in SPO research can promote further development of SPO.In this paper,the literature resources of SPO were firstly retrieved from scientific research databases by subject search and were used as the input of scientometric analysis to obtain the highly cited literature,the number of annual publications,and the co-authorship network,which enables readers to understand the research trends and research groups of current SPO.Secondly,the development,application,and research process of the HCD approach were introduced in detail,and the progress of the HCD approach in SPO research was reviewed systematically from three aspects:concept design,function allocation,and system evaluation.Finally,limitations of current SPO research and future research directions for applying the HCD approach to SPO were also discussed.
基金Supported by Key Project of Humanities and Social Sciences of Hubei Provincial Education Department——"Research on the Agricultural Supply-side Structural Reform Based on the Integration of Three Rural Industries"(18D031).
文摘Although there are certain differences in the center of gravity between rural revitalization and human-centered urbanization,their connotations and goals require that both must be promoted in concert.Therefore,based on a deep understanding of the connotation of rural revitalization and human-centered urbanization,it is necessary to clarify the goals of the two through the two-way flow of elements between urban and rural areas,the urban-rural linkage of industries,to achieve coordinated promotion of rural revitalization and human-centered urbanization in China.
文摘The special issue aims to address a broad spectrum of topics ranging from human-centered intelligent robots acting as a servant,secretary,or companion to intelligent robotic functions.The special issue publishes original papers of innovative ideas and concepts,new discoveries,and novel applications and business models relevant to the field of human-centered intelligent robots.In this special issue,modeling,intelligent control,
基金supported by the Soongsil University Research Fundthe Information Technology Research Center (ITRC) Support Program of the Ministry of Knowledge Economy (MKE), Korea
文摘This letter proposes a categorization matrix to analyze the playing style of a computer game player for a shooting game genre. Our aim is to use human-centered modeling as a strategy for adaptive games based on entertainment measure to evaluate the playing experience. We utilized a self-organizing map (SOM) to cluster the player's style with the data obtained while playing the game. We further argued that style-based adaptation contributes to higher enjoyment, and this is reflected in our experiment using a supervised multilayered perceptron (MLP) network.
文摘Detecting pavement cracks is critical for road safety and infrastructure management.Traditional methods,relying on manual inspection and basic image processing,are time-consuming and prone to errors.Recent deep-learning(DL)methods automate crack detection,but many still struggle with variable crack patterns and environmental conditions.This study aims to address these limitations by introducing the Masker Transformer,a novel hybrid deep learning model that integrates the precise localization capabilities of Mask Region-based Convolutional Neural Network(Mask R-CNN)with the global contextual awareness of Vision Transformer(ViT).The research focuses on leveraging the strengths of both architectures to enhance segmentation accuracy and adaptability across different pavement conditions.We evaluated the performance of theMaskerTransformer against other state-of-theartmodels such asU-Net,TransformerU-Net(TransUNet),U-NetTransformer(UNETr),SwinU-NetTransformer(Swin-UNETr),You Only Look Once version 8(YoloV8),and Mask R-CNN using two benchmark datasets:Crack500 and DeepCrack.The findings reveal that the MaskerTransformer significantly outperforms the existing models,achieving the highest Dice SimilarityCoefficient(DSC),precision,recall,and F1-Score across both datasets.Specifically,the model attained a DSC of 80.04%on Crack500 and 91.37%on DeepCrack,demonstrating superior segmentation accuracy and reliability.The high precision and recall rates further substantiate its effectiveness in real-world applications,suggesting that the Masker Transformer can serve as a robust tool for automated pavement crack detection,potentially replacing more traditional methods.
文摘This paper first introduces the development process of urban street green landscape in China and the human-centered thinking of the design of urban street green landscape.On the basis of detailed elaboration of the basic theories of urban street green landscape,it analyzes the existing problems and causes for urban street green landscape.Then,from the perspective of human-centered thought,it comes up with several measures for optimizing the green landscape design of urban streets,to provide much more human-centered experience of urban street green landscape.
文摘With the development of mechanization popularity in rural area, agricultural machinery product not only needs to meet the production goals, and also requires the simple operation and human-centered. Human-centered design is always, on the basis of the user＇ s requirement and usage, to think over the issues by regarding operator as the center, and to design the products by emphasizing the ease of use and understandability during design and manufacture. In this study, Stubble-Mulch Rotocultivator for Boat Tractor （SMRBT） is chosen as the design object. The coordination approach of the user, machine and environment is discussed by deeply investigating their relationship, which is an empirical study of the human-centered technology of agricultural machinery.
基金The National Natural Science Foundation of China(No.52338011,52378291)Young Elite Scientists Sponsorship Program by CAST(No.2022-2024QNRC0101).
文摘To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.
基金the National Key Research and Development Program of China(2021YFA0717900)National Natural Science Foundation of China(62471251,62405144,62288102,22275098,and 62174089)+1 种基金Basic Research Program of Jiangsu(BK20240033,BK20243057)Jiangsu Funding Program for Excellent Postdoctoral Talent(2022ZB402).
文摘Recently,for developing neuromorphic visual systems,adaptive optoelectronic devices become one of the main research directions and attract extensive focus to achieve optoelectronic transistors with high performances and flexible func-tionalities.In this review,based on a description of the biological adaptive functions that are favorable for dynamically perceiv-ing,filtering,and processing information in the varying environment,we summarize the representative strategies for achiev-ing these adaptabilities in optoelectronic transistors,including the adaptation for detecting information,adaptive synaptic weight change,and history-dependent plasticity.Moreover,the key points of the corresponding strategies are comprehen-sively discussed.And the applications of these adaptive optoelectronic transistors,including the adaptive color detection,sig-nal filtering,extending the response range of light intensity,and improve learning efficiency,are also illustrated separately.Lastly,the challenges faced in developing adaptive optoelectronic transistor for artificial vision system are discussed.The descrip-tion of biological adaptive functions and the corresponding inspired neuromorphic devices are expected to provide insights for the design and application of next-generation artificial visual systems.
