为了实现主船体大板架中纵向强力构件的三维模型快速创建,提升一体化三维数字设计的效率,压缩船舶设计周期,提出二维图纸信息读取技术和二维驱动三维参数化建模技术,通过对AutoCAD与Smart3D的二次开发,建立从二维图纸数据到三维模型快...为了实现主船体大板架中纵向强力构件的三维模型快速创建,提升一体化三维数字设计的效率,压缩船舶设计周期,提出二维图纸信息读取技术和二维驱动三维参数化建模技术,通过对AutoCAD与Smart3D的二次开发,建立从二维图纸数据到三维模型快速创建的设计流程,开发出主船体纵向强力构件快速建模工具。以30万t超大型油船(Very Large Crude Carrier,VLCC)作为实例进行验证,通过与传统参数化设计工具及软件自带设计模块的对比分析,验证了该工具的准确性与高效性。所开发的快速建模工具对压缩船舶设计周期、提高船舶设计效率具有显著作用,可为船舶三维数字设计提供有力支持。展开更多
The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health monitoring.The integration of wearable sensors with intelligent systems is an over...The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health monitoring.The integration of wearable sensors with intelligent systems is an overwhelming tendency,providing powerful tools for remote health monitoring and personal health management.Among many candidates,two-dimensional(2D)materials stand out due to several exotic mechanical,electrical,optical,and chemical properties that can be efficiently integrated into atomic-thin films.While previous reviews on 2D materials for biodevices primarily focus on conventional configurations and materials like graphene,the rapid development of new 2D materials with exotic properties has opened up novel applications,particularly in smart interaction and integrated functionalities.This review aims to consolidate recent progress,highlight the unique advantages of 2D materials,and guide future research by discussing existing challenges and opportunities in applying 2D materials for smart wearable biodevices.We begin with an in-depth analysis of the advantages,sensing mechanisms,and potential applications of 2D materials in wearable biodevice fabrication.Following this,we systematically discuss state-of-the-art biodevices based on 2D materials for monitoring various physiological signals within the human body.Special attention is given to showcasing the integration of multi-functionality in 2D smart devices,mainly including self-power supply,integrated diagnosis/treatment,and human–machine interaction.Finally,the review concludes with a concise summary of existing challenges and prospective solutions concerning the utilization of2D materials for advanced biodevices.展开更多
This paper discusses the development characteristics of urban horticulture under the background of smart agriculture,as well as the application of artificial intelligence technology in it.It analyzes the importance of...This paper discusses the development characteristics of urban horticulture under the background of smart agriculture,as well as the application of artificial intelligence technology in it.It analyzes the importance of highly skilled talents in urban agriculture in the era of smart agriculture and their cultivation pathways and practices.It proposes measures such as building multi-level practical teaching platforms,implementing the“Enjoy Horticulture”series of high-quality activities,and establishing the“1234”applied talent training model to cultivate high-quality talents that meet the development needs of modern urban horticulture industry.Taking Beijing University of Agriculture and other universities as examples,the paper analyzes the practical cases and effects of the urban horticulture discipline’s industry-education-research collaborative talent training model,which has reference significance for further improving and perfecting the urban horticulture industry-education-research collaborative talent training plan.展开更多
Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and ...Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.展开更多
Advances in wearable electronics and information technology drive sports data collection and analysis toward real-time visualization and precision. The growing pursuit of athleticism and healthy life makes it appealin...Advances in wearable electronics and information technology drive sports data collection and analysis toward real-time visualization and precision. The growing pursuit of athleticism and healthy life makes it appealing for individuals to track their real-time health and exercise data seamlessly. While numerous devices enable sports and health monitoring, maintaining comfort over long periods remains a considerable challenge, especially in high-intensity and sweaty sports scenarios. Textiles, with their breathability, deformability, and moisture-wicking abilities, ensure exceptional comfort during prolonged wear, making them ideal for wearable platforms. This review summarized the progress of research on textile-based sports monitoring devices. First, the design principles and fabrication methods of smart textiles were introduced systematically. Textiles undergo a distinctive fiber-yarn-fabric or fiber-fabric manufacturing process that allows for the regulation of performance and the integration of functional elements at every step. Then, the performance requirements for precise sports data collection of smart textiles, including main vital signs, joint movement, and data transmission, were discussed. Lastly, the applications of smart textiles in various sports scenarios are demonstrated. Additionally, the review provides an in-depth analysis of the emerging challenges, strategies, and opportunities for the research and development of sports-oriented smart textiles. Smart textiles not only maintain comfort and accuracy in sports, but also serve as inexpensive and efficient information-gathering terminals. Therefore, developing multifunctional, cost-effective textile-based systems for personalized sports and healthcare is a pressing need for the future of intelligent sports.展开更多
Rapid industrialization advancements have grabbed worldwide attention to integrate a very large number of electronic components into a smaller space for performing multifunctional operations.To fulfill the growing com...Rapid industrialization advancements have grabbed worldwide attention to integrate a very large number of electronic components into a smaller space for performing multifunctional operations.To fulfill the growing computing demand state-of-the-art materials are required for substituting traditional silicon and metal oxide semiconductors frameworks.Two-dimensional(2D)materials have shown their tremendous potential surpassing the limitations of conventional materials for developing smart devices.Despite their ground-breaking progress over the last two decades,systematic studies providing in-depth insights into the exciting physics of 2D materials are still lacking.Therefore,in this review,we discuss the importance of 2D materials in bridging the gap between conventional and advanced technologies due to their distinct statistical and quantum physics.Moreover,the inherent properties of these materials could easily be tailored to meet the specific requirements of smart devices.Hence,we discuss the physics of various 2D materials enabling them to fabricate smart devices.We also shed light on promising opportunities in developing smart devices and identified the formidable challenges that need to be addressed.展开更多
Diabetes is highly prevalent among the elderly worldwide,with the highest number of diabetes cases in China.Yet,the management of diabetes remains unsatisfactory.Recent advances in digital health technologies have fac...Diabetes is highly prevalent among the elderly worldwide,with the highest number of diabetes cases in China.Yet,the management of diabetes remains unsatisfactory.Recent advances in digital health technologies have facilitated the establishment of smart wards for diabetes patients.There is a lack of smart wards tailored specifically for older diabetes patients who encounter unique challenges in glycemic control and diabetes management,including an increased vulnerability to hypoglycemia,the presence of multiple chronic diseases,and cognitive decline.In this review,studies on digital health technologies for diabetes in China and beyond were summarized to elucidate how the adoption of digital health technologies,such as real-time continuous glucose monitoring,sensor-augmented pump technology,and their integration with 5th generation networks,big data cloud storage,and hospital information systems,can address issues specifically related to elderly diabetes patients in hospital wards.Furthermore,the challenges and future directions for establishing and implementing smart wards for elderly diabetes patients are discussed,and these challenges may also be applicable to other countries worldwide,not just in China.Taken together,the smart wards may enhance clinical outcomes,address specific issues,and eventually improve patient-centered hospital care for elderly patients with diabetes.展开更多
This paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innova tive approaches aligned with the Sustainable Development Goals. While traditional tools and linear models ...This paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innova tive approaches aligned with the Sustainable Development Goals. While traditional tools and linear models offer insights, they fall short in presenting a holistic view of complex urban challenges. System dynamics (SD) models that are often utilized to provide holistic, systematic understanding of a research subject, like the urban system, emerge as valuable tools, but data scarcity and theoretical inadequacy pose challenges. The research reviews relevant papers on recent SD model applications in urban sustainability since 2018, categorizing them based on nine key indicators. Among the reviewed papers, data limitations and model assumptions were identified as ma jor challenges in applying SD models to urban sustainability. This led to exploring the transformative potential of big data analytics, a rare approach in this field as identified by this study, to enhance SD models’ empirical foundation. Integrating big data could provide data-driven calibration, potentially improving predictive accuracy and reducing reliance on simplified assumptions. The paper concludes by advocating for new approaches that reduce assumptions and promote real-time applicable models, contributing to a comprehensive understanding of urban sustainability through the synergy of big data and SD models.展开更多
This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model...This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model follows a“three-stage”and“two-subject”framework,incorporating a structured design for teaching content and assessment methods before,during,and after class.Practical results indicate that this approach significantly enhances teaching effectiveness and improves students’learning autonomy.展开更多
Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,re...Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product quality.In light of the recent advancement of Industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing process.In this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual weaknesses.We evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different classes.The ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted averaging.Our evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and F1-score.Comparative analysis with recent studies also showed the superior performance of our methodology.展开更多
文摘为了实现主船体大板架中纵向强力构件的三维模型快速创建,提升一体化三维数字设计的效率,压缩船舶设计周期,提出二维图纸信息读取技术和二维驱动三维参数化建模技术,通过对AutoCAD与Smart3D的二次开发,建立从二维图纸数据到三维模型快速创建的设计流程,开发出主船体纵向强力构件快速建模工具。以30万t超大型油船(Very Large Crude Carrier,VLCC)作为实例进行验证,通过与传统参数化设计工具及软件自带设计模块的对比分析,验证了该工具的准确性与高效性。所开发的快速建模工具对压缩船舶设计周期、提高船舶设计效率具有显著作用,可为船舶三维数字设计提供有力支持。
基金the support from the National Natural Science Foundation of China(22272004,62272041)the Fundamental Research Funds for the Central Universities(YWF-22-L-1256)+1 种基金the National Key R&D Program of China(2023YFC3402600)the Beijing Institute of Technology Research Fund Program for Young Scholars(No.1870011182126)。
文摘The proliferation of wearable biodevices has boosted the development of soft,innovative,and multifunctional materials for human health monitoring.The integration of wearable sensors with intelligent systems is an overwhelming tendency,providing powerful tools for remote health monitoring and personal health management.Among many candidates,two-dimensional(2D)materials stand out due to several exotic mechanical,electrical,optical,and chemical properties that can be efficiently integrated into atomic-thin films.While previous reviews on 2D materials for biodevices primarily focus on conventional configurations and materials like graphene,the rapid development of new 2D materials with exotic properties has opened up novel applications,particularly in smart interaction and integrated functionalities.This review aims to consolidate recent progress,highlight the unique advantages of 2D materials,and guide future research by discussing existing challenges and opportunities in applying 2D materials for smart wearable biodevices.We begin with an in-depth analysis of the advantages,sensing mechanisms,and potential applications of 2D materials in wearable biodevice fabrication.Following this,we systematically discuss state-of-the-art biodevices based on 2D materials for monitoring various physiological signals within the human body.Special attention is given to showcasing the integration of multi-functionality in 2D smart devices,mainly including self-power supply,integrated diagnosis/treatment,and human–machine interaction.Finally,the review concludes with a concise summary of existing challenges and prospective solutions concerning the utilization of2D materials for advanced biodevices.
基金The Enhancement Project of Young Teachers Research Innovation Ability(JKC2022006)Beijing Municipal Higher Education Institutions’Teacher Team Construction Support Plan-High-Level Teaching Innovation Team(BPHR20220211)+1 种基金Beijing Higher Education Undergraduate Teaching Reform and Innovation Project(2023003)2024 Beijing University of Agriculture Student Party Members“Vanguard Force Action”Project。
文摘This paper discusses the development characteristics of urban horticulture under the background of smart agriculture,as well as the application of artificial intelligence technology in it.It analyzes the importance of highly skilled talents in urban agriculture in the era of smart agriculture and their cultivation pathways and practices.It proposes measures such as building multi-level practical teaching platforms,implementing the“Enjoy Horticulture”series of high-quality activities,and establishing the“1234”applied talent training model to cultivate high-quality talents that meet the development needs of modern urban horticulture industry.Taking Beijing University of Agriculture and other universities as examples,the paper analyzes the practical cases and effects of the urban horticulture discipline’s industry-education-research collaborative talent training model,which has reference significance for further improving and perfecting the urban horticulture industry-education-research collaborative talent training plan.
基金supported by the Deanship of Scientific Research and Graduate Studies at King Khalid University under research grant number(R.G.P.2/93/45).
文摘Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.
基金financially supported by the National Natural Science Foundation of China (52073051, 52373054)the Fundamental Research Funds for the Central Universities (2232022A-04, 24D110109/005, 2232024G-06-01)+1 种基金Natural Science Foundation of Shanghai (23ZR1400900)Shanghai Frontier Science Research Center for Modern Textiles。
文摘Advances in wearable electronics and information technology drive sports data collection and analysis toward real-time visualization and precision. The growing pursuit of athleticism and healthy life makes it appealing for individuals to track their real-time health and exercise data seamlessly. While numerous devices enable sports and health monitoring, maintaining comfort over long periods remains a considerable challenge, especially in high-intensity and sweaty sports scenarios. Textiles, with their breathability, deformability, and moisture-wicking abilities, ensure exceptional comfort during prolonged wear, making them ideal for wearable platforms. This review summarized the progress of research on textile-based sports monitoring devices. First, the design principles and fabrication methods of smart textiles were introduced systematically. Textiles undergo a distinctive fiber-yarn-fabric or fiber-fabric manufacturing process that allows for the regulation of performance and the integration of functional elements at every step. Then, the performance requirements for precise sports data collection of smart textiles, including main vital signs, joint movement, and data transmission, were discussed. Lastly, the applications of smart textiles in various sports scenarios are demonstrated. Additionally, the review provides an in-depth analysis of the emerging challenges, strategies, and opportunities for the research and development of sports-oriented smart textiles. Smart textiles not only maintain comfort and accuracy in sports, but also serve as inexpensive and efficient information-gathering terminals. Therefore, developing multifunctional, cost-effective textile-based systems for personalized sports and healthcare is a pressing need for the future of intelligent sports.
文摘Rapid industrialization advancements have grabbed worldwide attention to integrate a very large number of electronic components into a smaller space for performing multifunctional operations.To fulfill the growing computing demand state-of-the-art materials are required for substituting traditional silicon and metal oxide semiconductors frameworks.Two-dimensional(2D)materials have shown their tremendous potential surpassing the limitations of conventional materials for developing smart devices.Despite their ground-breaking progress over the last two decades,systematic studies providing in-depth insights into the exciting physics of 2D materials are still lacking.Therefore,in this review,we discuss the importance of 2D materials in bridging the gap between conventional and advanced technologies due to their distinct statistical and quantum physics.Moreover,the inherent properties of these materials could easily be tailored to meet the specific requirements of smart devices.Hence,we discuss the physics of various 2D materials enabling them to fabricate smart devices.We also shed light on promising opportunities in developing smart devices and identified the formidable challenges that need to be addressed.
基金Supported by Post-Subsidy Funds from the National Clinical Research Center,Ministry of Science and Technology of China,No.303-01-001-0272-08Beijing Municipal Administration of Hospitals Incubating Program,No.PX2022032Beijing Municipal Public Welfare Development and Reform Pilot Project for Medical Research Institutes(PWD&RPP-MRI),No.JYY2023-13.
文摘Diabetes is highly prevalent among the elderly worldwide,with the highest number of diabetes cases in China.Yet,the management of diabetes remains unsatisfactory.Recent advances in digital health technologies have facilitated the establishment of smart wards for diabetes patients.There is a lack of smart wards tailored specifically for older diabetes patients who encounter unique challenges in glycemic control and diabetes management,including an increased vulnerability to hypoglycemia,the presence of multiple chronic diseases,and cognitive decline.In this review,studies on digital health technologies for diabetes in China and beyond were summarized to elucidate how the adoption of digital health technologies,such as real-time continuous glucose monitoring,sensor-augmented pump technology,and their integration with 5th generation networks,big data cloud storage,and hospital information systems,can address issues specifically related to elderly diabetes patients in hospital wards.Furthermore,the challenges and future directions for establishing and implementing smart wards for elderly diabetes patients are discussed,and these challenges may also be applicable to other countries worldwide,not just in China.Taken together,the smart wards may enhance clinical outcomes,address specific issues,and eventually improve patient-centered hospital care for elderly patients with diabetes.
基金sponsored by the U.S.Department of Housing and Urban Development(Grant No.NJLTS0027-22)The opinions expressed in this study are the authors alone,and do not represent the U.S.Depart-ment of HUD’s opinions.
文摘This paper addresses urban sustainability challenges amid global urbanization, emphasizing the need for innova tive approaches aligned with the Sustainable Development Goals. While traditional tools and linear models offer insights, they fall short in presenting a holistic view of complex urban challenges. System dynamics (SD) models that are often utilized to provide holistic, systematic understanding of a research subject, like the urban system, emerge as valuable tools, but data scarcity and theoretical inadequacy pose challenges. The research reviews relevant papers on recent SD model applications in urban sustainability since 2018, categorizing them based on nine key indicators. Among the reviewed papers, data limitations and model assumptions were identified as ma jor challenges in applying SD models to urban sustainability. This led to exploring the transformative potential of big data analytics, a rare approach in this field as identified by this study, to enhance SD models’ empirical foundation. Integrating big data could provide data-driven calibration, potentially improving predictive accuracy and reducing reliance on simplified assumptions. The paper concludes by advocating for new approaches that reduce assumptions and promote real-time applicable models, contributing to a comprehensive understanding of urban sustainability through the synergy of big data and SD models.
基金2024 Anqing Normal University University-Level Key Project(ZK2024062D)。
文摘This study examines the Big Data Collection and Preprocessing course at Anhui Institute of Information Engineering,implementing a hybrid teaching reform using the Bosi Smart Learning Platform.The proposed hybrid model follows a“three-stage”and“two-subject”framework,incorporating a structured design for teaching content and assessment methods before,during,and after class.Practical results indicate that this approach significantly enhances teaching effectiveness and improves students’learning autonomy.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2022R1I1A3063493).
文摘Smart manufacturing and Industry 4.0 are transforming traditional manufacturing processes by utilizing innovative technologies such as the artificial intelligence(AI)and internet of things(IoT)to enhance efficiency,reduce costs,and ensure product quality.In light of the recent advancement of Industry 4.0,identifying defects has become important for ensuring the quality of products during the manufacturing process.In this research,we present an ensemble methodology for accurately classifying hot rolled steel surface defects by combining the strengths of four pre-trained convolutional neural network(CNN)architectures:VGG16,VGG19,Xception,and Mobile-Net V2,compensating for their individual weaknesses.We evaluated our methodology on the Xsteel surface defect dataset(XSDD),which comprises seven different classes.The ensemble methodology integrated the predictions of individual models through two methods:model averaging and weighted averaging.Our evaluation showed that the model averaging ensemble achieved an accuracy of 98.89%,a recall of 98.92%,a precision of 99.05%,and an F1-score of 98.97%,while the weighted averaging ensemble reached an accuracy of 99.72%,a recall of 99.74%,a precision of 99.67%,and an F1-score of 99.70%.The proposed weighted averaging ensemble model outperformed the model averaging method and the individual models in detecting defects in terms of accuracy,recall,precision,and F1-score.Comparative analysis with recent studies also showed the superior performance of our methodology.
