The first excavation at Maituo, Wushan, which revealed 19 tombs, basically clarified the cultural characteristics of the Han tombs in the cemetery and preliminarily established the periodization criteria for these tom...The first excavation at Maituo, Wushan, which revealed 19 tombs, basically clarified the cultural characteristics of the Han tombs in the cemetery and preliminarily established the periodization criteria for these tombs. Among the 13 tombs uncovered in the present second excavation besides four Han tombs, there are newly discovered burial types that belong to the Warring States, Southern Dynasties and Song. They provided new data for further research into the cultural features of this graveyard in different periods. The achievements in the present excavation consist mainly in the following two aspects，The first is the discovery of three tombs belonging to the late Warring States period. They represent the Chu cultural complex in an area dominated by the Qin State. The second is the revelation of an Eastern Han high-rank tomb in a good condition (M47). The tomb contains over 100 funeral objects, including objects in gold, silver, bronze and lacquer that reflect the tomb owner's wealth, as well as rare treasures of art, such as exquisite glazed pottery tombfigurines of dancers, lamps with toad-shaped stands, and large-sized pottery, tomb guardians, animals, human figures and statues of the Western Queen Mother that are represented in various positions. The unearthed pottery models of buildings, such as those of theatres and watchtowers delicate in workmanship and clear in layout, are valuable to studying Han architecture. These finds provide precious data for systematically studying Han period production technology, culture and art, building style, religion, and burial customs.展开更多
OBJECTIVE: To explore the relationships between different lifestyle-behavioral factors and phlegm wetness type of Traditional Chinese Medicine constitution,so as to provide health management strategies for phlegm-wetn...OBJECTIVE: To explore the relationships between different lifestyle-behavioral factors and phlegm wetness type of Traditional Chinese Medicine constitution,so as to provide health management strategies for phlegm-wetness constitution.METHODS: A case-control study was conducted with the cases selected from the database of Chinese constitution survey in 9 provinces or municipalities of China. 1380 cases met the diagnostic criteria of phlegm-wetness type were taken as the case group, and 1380 cases were randomly selected from gentleness type as the control group. Using Chi-square test to compare the differences of lifestyle-behavior composition in each group; single factor and multiple logistic regression analysis were used to compare the relationships of life-style-behavioral factors and phlegm-wetness type.RESULTS: There were statistically significant differences between phlegm-wetness type group and gentleness type group in lifestyle behaviors(dietary habits, tobacco and liquor consumptions, exercise habits, sleeping habits). The results of single factor logistic regression analysis demonstrated that the risk of phlegm-wetness constitution decreased significantly in light diet(odds ratio, OR=0.68);The risk factors of phlegm-wetness type were fatty food intake(OR=2.36), sleeping early and getting up late(OR=1.87), tobacco smoking(OR=1.83),barbecued food intake(OR=1.68), alcohol drinking(OR=1.63), salty food intake(OR=1.44), sleeping erratically(OR=1.43), less physical activities(OR=1.42), sweet food intake(OR=1.29), sleeping and getting up late(OR=1.26), and pungent food intake(OR=1.21), respectively. Regardless of the interaction among lifestyle-behavioral factors, the results of the multiple logistic regression analysis revealed that the risk factors of phlegm-wetness type were sleeping early and getting up late(OR=1.94), fatty food intake(OR=1.80), tobacco smoking(OR=1.50),sleeping erratically(OR=1.50), barbecued food intake(OR=1.40), sleeping and getting up late(OR=1.40), less physical activities(OR=1.31), sle展开更多
The standard approach to tackling computer vision problems is to train deep convolutional neural network(CNN)models using large-scale image datasets that are representative of the target task.However,in many scenarios...The standard approach to tackling computer vision problems is to train deep convolutional neural network(CNN)models using large-scale image datasets that are representative of the target task.However,in many scenarios,it is often challenging to obtain sufficient image data for the target task.Data augmentation is a way to mitigate this challenge.A common practice is to explicitly transform existing images in desired ways to create the required volume and variability of training data necessary to achieve good generalization performance.In situations where data for the target domain are not accessible,a viable workaround is to synthesize training data from scratch,i.e.,synthetic data augmentation.This paper presents an extensive review of synthetic data augmentation techniques.It covers data synthesis approaches based on realistic 3D graphics modelling,neural style transfer(NST),differential neural rendering,and generative modelling using generative adversarial networks(GANs)and variational autoencoders(VAEs).For each of these classes of methods,we focus on the important data generation and augmentation techniques,general scope of application and specific use-cases,as well as existing limitations and possible workarounds.Additionally,we provide a summary of common synthetic datasets for training computer vision models,highlighting the main features,application domains and supported tasks.Finally,we discuss the effectiveness of synthetic data augmentation methods.Since this is the first paper to explore synthetic data augmentation methods in great detail,we are hoping to equip readers with the necessary background information and in-depth knowledge of existing methods and their attendant issues.展开更多
针对现有的风格迁移方法在对水表进行数据增强后导致颜色失真,内容保留不完整等问题,提出了一种基于大卷积核的任意风格迁移算法(arbitrary style transfer algorithm of large convolutional kernel,LKAST)。首先,针对风格图像使用大...针对现有的风格迁移方法在对水表进行数据增强后导致颜色失真,内容保留不完整等问题,提出了一种基于大卷积核的任意风格迁移算法(arbitrary style transfer algorithm of large convolutional kernel,LKAST)。首先,针对风格图像使用大卷积核提取风格特征,保留风格特征的高层特征;此外,通过引入新的损失函数,更好的保留迁移结果对内容的保留;最后,通过两组对照实验验证方法的有效性。实验结果表明,该方法能够在模拟水表现场环境的同时保留足够的内容信息,在仅改变数据增强算法的前提下,单次多框目标检测(SSD)算法准确率提升6.84%,YOLOv5准确率提升6.56%。展开更多
City style is the characteristics of the city formed under the influence of natural geography,social economy,human history and other factors in the development process of the city.In the information age,the operation ...City style is the characteristics of the city formed under the influence of natural geography,social economy,human history and other factors in the development process of the city.In the information age,the operation and development of cities are deeply affected.Technical platforms such as social networks,city data,and street view maps cover all levels of the city.The resulting multi-source data provided new ideas and methods for urban landscape research.The article pointed out through the study of urban landscape that the strong coupling between urban landscape and multi-source data was a very promising multi-field cross-over study.Finally,multi-source city data,using traditional data,urban POI data,urban street scene pictures,and Weibo sign-in data,were explored to conduct perceptual research on the overall urban style,urban spatial pattern,urban architectural style and urban humanistic emotions,and construct a framework for urban style perception driven by multi-source data.展开更多
文摘The first excavation at Maituo, Wushan, which revealed 19 tombs, basically clarified the cultural characteristics of the Han tombs in the cemetery and preliminarily established the periodization criteria for these tombs. Among the 13 tombs uncovered in the present second excavation besides four Han tombs, there are newly discovered burial types that belong to the Warring States, Southern Dynasties and Song. They provided new data for further research into the cultural features of this graveyard in different periods. The achievements in the present excavation consist mainly in the following two aspects，The first is the discovery of three tombs belonging to the late Warring States period. They represent the Chu cultural complex in an area dominated by the Qin State. The second is the revelation of an Eastern Han high-rank tomb in a good condition (M47). The tomb contains over 100 funeral objects, including objects in gold, silver, bronze and lacquer that reflect the tomb owner's wealth, as well as rare treasures of art, such as exquisite glazed pottery tombfigurines of dancers, lamps with toad-shaped stands, and large-sized pottery, tomb guardians, animals, human figures and statues of the Western Queen Mother that are represented in various positions. The unearthed pottery models of buildings, such as those of theatres and watchtowers delicate in workmanship and clear in layout, are valuable to studying Han architecture. These finds provide precious data for systematically studying Han period production technology, culture and art, building style, religion, and burial customs.
基金Supported by Research of Traditional Chinese Medicine Health cognition theory and Constitution Classification from the National Basic Research Program(973 Program)(No.2011CB505403)
文摘OBJECTIVE: To explore the relationships between different lifestyle-behavioral factors and phlegm wetness type of Traditional Chinese Medicine constitution,so as to provide health management strategies for phlegm-wetness constitution.METHODS: A case-control study was conducted with the cases selected from the database of Chinese constitution survey in 9 provinces or municipalities of China. 1380 cases met the diagnostic criteria of phlegm-wetness type were taken as the case group, and 1380 cases were randomly selected from gentleness type as the control group. Using Chi-square test to compare the differences of lifestyle-behavior composition in each group; single factor and multiple logistic regression analysis were used to compare the relationships of life-style-behavioral factors and phlegm-wetness type.RESULTS: There were statistically significant differences between phlegm-wetness type group and gentleness type group in lifestyle behaviors(dietary habits, tobacco and liquor consumptions, exercise habits, sleeping habits). The results of single factor logistic regression analysis demonstrated that the risk of phlegm-wetness constitution decreased significantly in light diet(odds ratio, OR=0.68);The risk factors of phlegm-wetness type were fatty food intake(OR=2.36), sleeping early and getting up late(OR=1.87), tobacco smoking(OR=1.83),barbecued food intake(OR=1.68), alcohol drinking(OR=1.63), salty food intake(OR=1.44), sleeping erratically(OR=1.43), less physical activities(OR=1.42), sweet food intake(OR=1.29), sleeping and getting up late(OR=1.26), and pungent food intake(OR=1.21), respectively. Regardless of the interaction among lifestyle-behavioral factors, the results of the multiple logistic regression analysis revealed that the risk factors of phlegm-wetness type were sleeping early and getting up late(OR=1.94), fatty food intake(OR=1.80), tobacco smoking(OR=1.50),sleeping erratically(OR=1.50), barbecued food intake(OR=1.40), sleeping and getting up late(OR=1.40), less physical activities(OR=1.31), sle
文摘The standard approach to tackling computer vision problems is to train deep convolutional neural network(CNN)models using large-scale image datasets that are representative of the target task.However,in many scenarios,it is often challenging to obtain sufficient image data for the target task.Data augmentation is a way to mitigate this challenge.A common practice is to explicitly transform existing images in desired ways to create the required volume and variability of training data necessary to achieve good generalization performance.In situations where data for the target domain are not accessible,a viable workaround is to synthesize training data from scratch,i.e.,synthetic data augmentation.This paper presents an extensive review of synthetic data augmentation techniques.It covers data synthesis approaches based on realistic 3D graphics modelling,neural style transfer(NST),differential neural rendering,and generative modelling using generative adversarial networks(GANs)and variational autoencoders(VAEs).For each of these classes of methods,we focus on the important data generation and augmentation techniques,general scope of application and specific use-cases,as well as existing limitations and possible workarounds.Additionally,we provide a summary of common synthetic datasets for training computer vision models,highlighting the main features,application domains and supported tasks.Finally,we discuss the effectiveness of synthetic data augmentation methods.Since this is the first paper to explore synthetic data augmentation methods in great detail,we are hoping to equip readers with the necessary background information and in-depth knowledge of existing methods and their attendant issues.
文摘针对现有的风格迁移方法在对水表进行数据增强后导致颜色失真,内容保留不完整等问题,提出了一种基于大卷积核的任意风格迁移算法(arbitrary style transfer algorithm of large convolutional kernel,LKAST)。首先,针对风格图像使用大卷积核提取风格特征,保留风格特征的高层特征;此外,通过引入新的损失函数,更好的保留迁移结果对内容的保留;最后,通过两组对照实验验证方法的有效性。实验结果表明,该方法能够在模拟水表现场环境的同时保留足够的内容信息,在仅改变数据增强算法的前提下,单次多框目标检测(SSD)算法准确率提升6.84%,YOLOv5准确率提升6.56%。
基金Sponsored by 2020 Topics of Hebei Provincial Social Development Studies(20200302041)2020 Planning Program of Hebei Provincial Cultural and Art Science(HB20-YB099)。
文摘City style is the characteristics of the city formed under the influence of natural geography,social economy,human history and other factors in the development process of the city.In the information age,the operation and development of cities are deeply affected.Technical platforms such as social networks,city data,and street view maps cover all levels of the city.The resulting multi-source data provided new ideas and methods for urban landscape research.The article pointed out through the study of urban landscape that the strong coupling between urban landscape and multi-source data was a very promising multi-field cross-over study.Finally,multi-source city data,using traditional data,urban POI data,urban street scene pictures,and Weibo sign-in data,were explored to conduct perceptual research on the overall urban style,urban spatial pattern,urban architectural style and urban humanistic emotions,and construct a framework for urban style perception driven by multi-source data.
