With the increasing number of remote sensing satellites,the diversification of observation modals,and the continuous advancement of artificial intelligence algorithms,historically opportunities have been brought to th...With the increasing number of remote sensing satellites,the diversification of observation modals,and the continuous advancement of artificial intelligence algorithms,historically opportunities have been brought to the applications of earth observation and information retrieval,including climate change monitoring,natural resource investigation,ecological environment protection,and territorial space planning.Over the past decade,artificial intelligence technology represented by deep learning has made significant contributions to the field of Earth observation.Therefore,this review will focus on the bottlenecks and development process of using deep learning methods for land use/land cover mapping of the Earth’s surface.Firstly,it introduces the basic framework of semantic segmentation network models for land use/land cover mapping.Then,we summarize the development of semantic segmentation models in geographical field,focusing on spatial and semantic feature extraction,context relationship perception,multi-scale effects modelling,and the transferability of models under geographical differences.Then,the application of semantic segmentation models in agricultural management,building boundary extraction,single tree segmentation and inter-species classification are reviewed.Finally,we discuss the future development prospects of deep learning technology in the context of remote sensing big data.展开更多
Based on the study of the current situation of badminton teaching in colleges and universities, this paper puts forward some strategies to strengthen the teaching effect of badminton, which can effectively improve stu...Based on the study of the current situation of badminton teaching in colleges and universities, this paper puts forward some strategies to strengthen the teaching effect of badminton, which can effectively improve students' badminton skills and develop students' good physical quality. Promote the healthy and happy growth of students. Badminton combines fun, fitness and competition. The development of badminton in colleges and universities can train students' thoughts and sentiments, improve students' psychological pleasure, improve their judgment, and promote students' healthy growth. Through learning to learn badminton, students can cultivate their team spirit of cooperation and dare to challenge, so as to grow healthily and happily.展开更多
目的:探讨缺血性脑卒中恢复期患者血瘀证候与认知功能的相关性以及其辨证分型的分布规律,为该病后期认知功能的恢复和中医辨证治疗提供依据。方法:收集符合纳入与排除标准的230例患者的中医证型、血瘀证候、神经功能缺损程度评定、认知...目的:探讨缺血性脑卒中恢复期患者血瘀证候与认知功能的相关性以及其辨证分型的分布规律,为该病后期认知功能的恢复和中医辨证治疗提供依据。方法:收集符合纳入与排除标准的230例患者的中医证型、血瘀证候、神经功能缺损程度评定、认知功能评分等资料,运用统计描述、相关性分析和方差分析等统计学方法对收集的资料进行分析。结果:血瘀证候评分与蒙特利尔认知评估量表(Montreal Cognitive Assessment,MoCA)评分、日常生活能力量表(Activity of Daily Living,ADL)评分负相关(P<0.01);各辨证分型之间的性别分布差异无统计学意义(χ^(2)=1.205,P>0.05);男性、女性均以气虚血瘀型常见,分别占36.36%(56/154)和35.53%(27/76);各年龄层在辨证分型之间的分布差异具有统计学意义(χ^(2)=3.008,P<0.05);不同的神经功能缺损程度与辨证分型之间的差异无统计学意义(χ^(2)=0.674,P>0.05);美国国立卫生研究院卒中量表(National Institutes of Health Stroke Scale,NIHSS)评分以5~15分(中度卒中)为主。结论:在本研究230例缺血性脑卒中恢复期患者中,其血瘀证候评分和认知功能密切相关,中医证型多见气虚血瘀证,患者多表现为中度脑卒中的状态。展开更多
目前,现有的储能系统控制策略难以使得荷电容量(State of Charge,SOC)保持在安全范围内。为满足风光发电波动对海上油气平台造成的储能系统充放电需求,延长储能系统使用寿命,强调引入风能、光能及储能技术的必要性,本文设计了一种集群...目前,现有的储能系统控制策略难以使得荷电容量(State of Charge,SOC)保持在安全范围内。为满足风光发电波动对海上油气平台造成的储能系统充放电需求,延长储能系统使用寿命,强调引入风能、光能及储能技术的必要性,本文设计了一种集群式发电系统规划方案,整合了风电、光伏发电与储能系统的优化配置。在系统控制方面,采用集合经验模态分解法得到不同类型储能设备需要平抑的功率,提出一种储能系统超前模糊控制策略,以确保系统运行的稳定性和能效优化。通过MATLAB仿真与实验验证了所提方案的可行性和效果,证明该系统在提高能源利用效率及减少环境影响方面具有显著优势。展开更多
基金National Natural Science Foundation of China(Nos.42371406,42071441,42222106,61976234).
文摘With the increasing number of remote sensing satellites,the diversification of observation modals,and the continuous advancement of artificial intelligence algorithms,historically opportunities have been brought to the applications of earth observation and information retrieval,including climate change monitoring,natural resource investigation,ecological environment protection,and territorial space planning.Over the past decade,artificial intelligence technology represented by deep learning has made significant contributions to the field of Earth observation.Therefore,this review will focus on the bottlenecks and development process of using deep learning methods for land use/land cover mapping of the Earth’s surface.Firstly,it introduces the basic framework of semantic segmentation network models for land use/land cover mapping.Then,we summarize the development of semantic segmentation models in geographical field,focusing on spatial and semantic feature extraction,context relationship perception,multi-scale effects modelling,and the transferability of models under geographical differences.Then,the application of semantic segmentation models in agricultural management,building boundary extraction,single tree segmentation and inter-species classification are reviewed.Finally,we discuss the future development prospects of deep learning technology in the context of remote sensing big data.
文摘Based on the study of the current situation of badminton teaching in colleges and universities, this paper puts forward some strategies to strengthen the teaching effect of badminton, which can effectively improve students' badminton skills and develop students' good physical quality. Promote the healthy and happy growth of students. Badminton combines fun, fitness and competition. The development of badminton in colleges and universities can train students' thoughts and sentiments, improve students' psychological pleasure, improve their judgment, and promote students' healthy growth. Through learning to learn badminton, students can cultivate their team spirit of cooperation and dare to challenge, so as to grow healthily and happily.
文摘目的:探讨缺血性脑卒中恢复期患者血瘀证候与认知功能的相关性以及其辨证分型的分布规律,为该病后期认知功能的恢复和中医辨证治疗提供依据。方法:收集符合纳入与排除标准的230例患者的中医证型、血瘀证候、神经功能缺损程度评定、认知功能评分等资料,运用统计描述、相关性分析和方差分析等统计学方法对收集的资料进行分析。结果:血瘀证候评分与蒙特利尔认知评估量表(Montreal Cognitive Assessment,MoCA)评分、日常生活能力量表(Activity of Daily Living,ADL)评分负相关(P<0.01);各辨证分型之间的性别分布差异无统计学意义(χ^(2)=1.205,P>0.05);男性、女性均以气虚血瘀型常见,分别占36.36%(56/154)和35.53%(27/76);各年龄层在辨证分型之间的分布差异具有统计学意义(χ^(2)=3.008,P<0.05);不同的神经功能缺损程度与辨证分型之间的差异无统计学意义(χ^(2)=0.674,P>0.05);美国国立卫生研究院卒中量表(National Institutes of Health Stroke Scale,NIHSS)评分以5~15分(中度卒中)为主。结论:在本研究230例缺血性脑卒中恢复期患者中,其血瘀证候评分和认知功能密切相关,中医证型多见气虚血瘀证,患者多表现为中度脑卒中的状态。
文摘目前,现有的储能系统控制策略难以使得荷电容量(State of Charge,SOC)保持在安全范围内。为满足风光发电波动对海上油气平台造成的储能系统充放电需求,延长储能系统使用寿命,强调引入风能、光能及储能技术的必要性,本文设计了一种集群式发电系统规划方案,整合了风电、光伏发电与储能系统的优化配置。在系统控制方面,采用集合经验模态分解法得到不同类型储能设备需要平抑的功率,提出一种储能系统超前模糊控制策略,以确保系统运行的稳定性和能效优化。通过MATLAB仿真与实验验证了所提方案的可行性和效果,证明该系统在提高能源利用效率及减少环境影响方面具有显著优势。
