With a ten-year horizon from concept to reality, it is time now to start thinking about what will the sixth-generation(6G) mobile communications be on the eve of the fifth-generation(5G) deployment. To pave the way fo...With a ten-year horizon from concept to reality, it is time now to start thinking about what will the sixth-generation(6G) mobile communications be on the eve of the fifth-generation(5G) deployment. To pave the way for the development of 6G and beyond, we provide 6G visions in this paper. We first introduce the state-of-the-art technologies in 5G and indicate the necessity to study 6G. By taking the current and emerging development of wireless communications into consideration, we envision 6G to include three major aspects, namely, mobile ultra-broadband, super Internet-of-Things(IoT), and artificial intelligence(AI). Then, we review key technologies to realize each aspect. In particular, teraherz(THz) communications can be used to support mobile ultra-broadband, symbiotic radio and satellite-assisted communications can be used to achieve super IoT, and machine learning techniques are promising candidates for AI. For each technology, we provide the basic principle, key challenges, and state-of-the-art approaches and solutions.展开更多
Utopian visions between China and Western society differed in their early stage. Words reflecting early Chinese utopian visions scattered in many ancient classics. Most of them were general depiction of an ideal socie...Utopian visions between China and Western society differed in their early stage. Words reflecting early Chinese utopian visions scattered in many ancient classics. Most of them were general depiction of an ideal society featured with equality, sympathy, preference for community autonomy and the social order ＂the whole world as one community＂. Early Western society witnessed many utopian monographs. Most of them offered detailed construction of social frame with emphasis on social function division, request for ideal authority, and property co-ownership as core of an ideal society.展开更多
There are increasing calls for engaging citizens in the development of future outlooks. At the same time, large-scale public engagement activities warrant appropriate methods for analyzing their outcomes. This paper r...There are increasing calls for engaging citizens in the development of future outlooks. At the same time, large-scale public engagement activities warrant appropriate methods for analyzing their outcomes. This paper reviews how topic modeling could provide such a methodology, which both accounts for all textual data collected in public engagement activities, however large in scope, yet also allows for meaningful topical analysis. It compares topic modeling results concerning a corpus of 179 citizen visions from 30 European countries on desirable and sustainable futures to those acquired through deliberative analysis. While both methodologies contend that European citizens＇ outlook consists of education, sustainability in the economy, health concerns, and fairness in communities, and the particular strengths of topic modeling relate to its documentability, repeatability, cost efficiency, and scalability. Topic modeling can also be considered to support public engagement analytically from the perspective of knowledge formation rather than that of common sense.展开更多
Architecture and the city are two major constituents of human development which, today more than ever, have to be present in the long-term. The Year of France in China is, for the first time, the occasion to present t...Architecture and the city are two major constituents of human development which, today more than ever, have to be present in the long-term. The Year of France in China is, for the first time, the occasion to present to the Chinese public a vision of the contemporary French architectural production, not only in France but also in China.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
基金supported in part by National Natural Science Foundation of China under Grants 61631005, 61801101, U1801261, and 61571100
文摘With a ten-year horizon from concept to reality, it is time now to start thinking about what will the sixth-generation(6G) mobile communications be on the eve of the fifth-generation(5G) deployment. To pave the way for the development of 6G and beyond, we provide 6G visions in this paper. We first introduce the state-of-the-art technologies in 5G and indicate the necessity to study 6G. By taking the current and emerging development of wireless communications into consideration, we envision 6G to include three major aspects, namely, mobile ultra-broadband, super Internet-of-Things(IoT), and artificial intelligence(AI). Then, we review key technologies to realize each aspect. In particular, teraherz(THz) communications can be used to support mobile ultra-broadband, symbiotic radio and satellite-assisted communications can be used to achieve super IoT, and machine learning techniques are promising candidates for AI. For each technology, we provide the basic principle, key challenges, and state-of-the-art approaches and solutions.
文摘Utopian visions between China and Western society differed in their early stage. Words reflecting early Chinese utopian visions scattered in many ancient classics. Most of them were general depiction of an ideal society featured with equality, sympathy, preference for community autonomy and the social order ＂the whole world as one community＂. Early Western society witnessed many utopian monographs. Most of them offered detailed construction of social frame with emphasis on social function division, request for ideal authority, and property co-ownership as core of an ideal society.
文摘There are increasing calls for engaging citizens in the development of future outlooks. At the same time, large-scale public engagement activities warrant appropriate methods for analyzing their outcomes. This paper reviews how topic modeling could provide such a methodology, which both accounts for all textual data collected in public engagement activities, however large in scope, yet also allows for meaningful topical analysis. It compares topic modeling results concerning a corpus of 179 citizen visions from 30 European countries on desirable and sustainable futures to those acquired through deliberative analysis. While both methodologies contend that European citizens＇ outlook consists of education, sustainability in the economy, health concerns, and fairness in communities, and the particular strengths of topic modeling relate to its documentability, repeatability, cost efficiency, and scalability. Topic modeling can also be considered to support public engagement analytically from the perspective of knowledge formation rather than that of common sense.
文摘Architecture and the city are two major constituents of human development which, today more than ever, have to be present in the long-term. The Year of France in China is, for the first time, the occasion to present to the Chinese public a vision of the contemporary French architectural production, not only in France but also in China.
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.
