Forest wildfires pose significant and growing threats to human safety, wildlife habitat, regional economies and global climate change. It is crucial that forest fires be subject to timely and accurate monitoring by fo...Forest wildfires pose significant and growing threats to human safety, wildlife habitat, regional economies and global climate change. It is crucial that forest fires be subject to timely and accurate monitoring by forest fire managers and other stake-holders. Measurement by spaceborne equipment has become a practical and appealing method to monitor the occurrence and development of forest wildfires. Here we present an overview of the principles and case studies of forest fire monitoring（FFM） with satelliteand drone-mounted infrared remote sensing（IRRS）. This review includes four types of FFM-relevant IRRS algorithms： bi-spectral methods, fixed threshold methods, spatial contextual methods, and multi-temporal methods. The spatial contextual methods are presented in detail since they can be applied easily with commonly available satellite IRRS data, including MODIS, VIIRS, and Landsat 8 OLI. This review also evaluates typical cases of FFM using NOAAAVHRR, EOS-MODIS, S-NPP VIIRS, Landsat 8 OLI,MSG-SEVIRI, and drone infrared data. To better implement IRRS applications in FFM, it is important to develop accurate forest masks, carry out systematic comparative studies of various forest fire detection systems（known as forest fire products）, and improve methods for assessing the accuracy of forest fire detection. Medium-resolution IRRS data are effective for landscape-scale FFM, and the VIIRS 375 m contextual algorithm and RST-FIRES algorithm are helpful for closely tracking forest fires（including small and shortlived fires） and forest-fire early warning.展开更多
多臂赌博机问题是强化学习中研究探索和利用两者平衡的经典问题,其中,随机多臂赌博机问题是最经典的一类多臂赌博机问题,是众多新型多臂赌博机问题的基础.针对现有多臂赌博机算法未能充分使用环境反馈信息以及泛化能力较弱的问题,提出...多臂赌博机问题是强化学习中研究探索和利用两者平衡的经典问题,其中,随机多臂赌博机问题是最经典的一类多臂赌博机问题,是众多新型多臂赌博机问题的基础.针对现有多臂赌博机算法未能充分使用环境反馈信息以及泛化能力较弱的问题,提出一种自适应的多臂赌博机算法.该算法利用当前估计值最小的动作被选择的次数来调整探索和利用的概率(chosen number of arm with minimal estimation, CNAME),有效缓解了探索和利用不平衡的问题.同时,该算法不依赖于上下文信息,在不同场景的多臂赌博机问题中有更好的泛化能力.通过理论分析给出了该算法的悔值(regret)上界,并通过不同场景的实验结果表明:CNAME算法可以高效地获得较高的奖赏和较低的悔值,并且具有更好的泛化能力.展开更多
Historically,vision research in China was one of a few distinct research programs within the Chinese Academy of Sciences(CAS).With improved funding opportunities and research environment in neuroscience,vision researc...Historically,vision research in China was one of a few distinct research programs within the Chinese Academy of Sciences(CAS).With improved funding opportunities and research environment in neuroscience,vision research at several research institutes within the academy has made significant progress not only in the quantity of publications,but also in the quality of the work.Based on our own expertise,this review is mainly focused on the findings that have advanced the understanding of visual processing in the central visual pathway,visual perceptual learning,visual development and eye diseases.展开更多
Automatic bridge detection is an important application of SAR images. Differed from the classical CFAR method, a new knowledge-based bridge detection approach is proposed. The method not only uses the backscattering i...Automatic bridge detection is an important application of SAR images. Differed from the classical CFAR method, a new knowledge-based bridge detection approach is proposed. The method not only uses the backscattering intensity difference between targets and background but also applies the contextual information and spatial relationship between objects. According to bridges＇ special characteristics and scattering properties in SAR images, the new knowledge-based method includes three processes： river segmentation, potential bridge areas detection and bridge discrimination. The application to AIRSAR data shows that the new method is not sensitive to rivers＇ shape. Moreover, this method can detect bridges successfully when river segmentation is not very exact and is more robust than the radius projection method.展开更多
Contextual question answering （CQA）, in which user information needs are satisfied through an interactive question answering （QA） dialog, has recently attracted more research attention. One challenge is to fuse co...Contextual question answering （CQA）, in which user information needs are satisfied through an interactive question answering （QA） dialog, has recently attracted more research attention. One challenge is to fuse contextual information into the understanding process of relevant questions. In this paper, a discourse structure is proposed to maintain semantic information, and approaches for recognition of relevancy type and fusion of contextual information according to relevancy type are proposed. The system is evaluated on real contextual QA data. The results show that better performance is achieved than a baseline system and almost the same performance as when these contextual phenomena are resolved manually. A detailed evaluation analysis is presented.展开更多
Database system is the infrastructure of the modern information system. The R＆D in the database system and its technologies is one of the important research topics in the field. The database R＆D in China took off la...Database system is the infrastructure of the modern information system. The R＆D in the database system and its technologies is one of the important research topics in the field. The database R＆D in China took off later but it moves along by giant steps. This report presents the achievements Renmin University of China （RUC） has made in the past 25 years and at the same time addresses some of the research projects we, RUC, are currently working on. The National Natural Science Foundation of China supports and initiates most of our research projects and these successfully conducted projects have produced fruitful results.展开更多
Accumulating evidence indicates that inhalation anesthetics induce or increase the risk of cognitive impairment. GLYX-13（rapastinel） acts on the glycine site of N-methyl-D-aspartate receptors（NMDARs） and has been ...Accumulating evidence indicates that inhalation anesthetics induce or increase the risk of cognitive impairment. GLYX-13（rapastinel） acts on the glycine site of N-methyl-D-aspartate receptors（NMDARs） and has been shown to enhance hippocampus-dependent learning and memory function. However, the mechanisms by which GLYX-13 affects learning and memory function are still unclear. In this study, we investigated these mechanisms in a mouse model of long-term anesthesia exposure. Mice were intravenously administered 1 mg/kg GLYX-13 at 2 hours before isoflurane exposure（1.5% for 6 hours）. Cognitive function was assessed using the contextual fear conditioning test and the novel object recognition test. The mRNA expression and phosphorylated protein levels of NMDAR pathway components, N-methyl-D-aspartate receptor subunit 2B（NR2B）-Ca2+/calmodulin dependent protein kinase II（CaMKII）-cyclic adenosine monophosphate response element binding protein（CREB）, in the hippocampus were evaluated by quantitative RT-PCR and western blot assay. Pretreatment with GLYX-13 ameliorated isoflurane exposure-induced cognitive impairment and restored NR2B, CaMKII and CREB mRNA and phosphorylated protein levels. Intracerebroventricular injection of KN93, a selective CaMKII inhibitor, significantly diminished the effect of GLYX-13 on cognitive function and NR2B, CaMKII and CREB levels in the hippocampus. Taken together, our findings suggest that GLYX-13 pretreatment alleviates isoflurane-induced cognitive dysfunction by protecting against perturbation of the NR2B/CaMKII/CREB signaling pathway in the hippocampus. Therefore, GLYX-13 may have therapeutic potential for the treatment of anesthesia-induced cognitive dysfunction. This study was approved by the Experimental Animal Ethics Committee of Drum Tower Hospital affiliated to the Medical College of Nanjing University, China（approval No. 20171102） on November 20, 2017.展开更多
The discourse analysis task,which focuses on understanding the semantics of long text spans,has received increasing attention in recent years.As a critical component of discourse analysis,discourse relation recognitio...The discourse analysis task,which focuses on understanding the semantics of long text spans,has received increasing attention in recent years.As a critical component of discourse analysis,discourse relation recognition aims to identify the rhetorical relations between adjacent discourse units(e.g.,clauses,sentences,and sentence groups),called arguments,in a document.Previous works focused on capturing the semantic interactions between arguments to recognize their discourse relations,ignoring important textual information in the surrounding contexts.However,in many cases,more than capturing semantic interactions from the texts of the two arguments are needed to identify their rhetorical relations,requiring mining more contextual clues.In this paper,we propose a method to convert the RST-style discourse trees in the training set into dependency-based trees and train a contextual evidence selector on these transformed structures.In this way,the selector can learn the ability to automatically pick critical textual information from the context(i.e.,as evidence)for arguments to assist in discriminating their relations.Then we encode the arguments concatenated with corresponding evidence to obtain the enhanced argument representations.Finally,we combine original and enhanced argument representations to recognize their relations.In addition,we introduce auxiliary tasks to guide the training of the evidence selector to strengthen its selection ability.The experimental results on the Chinese CDTB dataset show that our method outperforms several state-of-the-art baselines in both micro and macro F1 scores.展开更多
This study explores the application of Abrams’Fourfold Model in the classification of Western literary criticism.Abrams’framework categorizes literary criticism into four fundamental elements:text,author,world,and a...This study explores the application of Abrams’Fourfold Model in the classification of Western literary criticism.Abrams’framework categorizes literary criticism into four fundamental elements:text,author,world,and audience.The text is viewed as an independent entity with intrinsic artistic value,necessitating a detailed analysis of its structure,style,themes,and symbols.Author study delves into the creator’s life and socio-cultural context,often to uncover the work’s deeper meanings.Contextual study situates the work within its historical and social milieu,examining its reflection of or response to societal norms and events.Audience response analysis considers the diverse interpretations shaped by readers’backgrounds,emphasizing the reader’s role in constructing the work’s meaning.The study concludes that Abrams’Fourfold Model offers a comprehensive and flexible analytical tool,enabling critics to engage with literary works from multiple perspectives,thereby enriching the understanding of literary complexity and diversity.展开更多
Most existing image inpainting methods aim to fill in the missing content in the inside-hole region of the target image. However, the areas to be restored in realistically degraded images are unspecified. Previous stu...Most existing image inpainting methods aim to fill in the missing content in the inside-hole region of the target image. However, the areas to be restored in realistically degraded images are unspecified. Previous studies have failed to recover the degradations due to the absence of the explicit mask indication. Meanwhile, inconsistent patterns are blended complexly with the image content. Therefore, estimating whether certain pixels are out of distribution and considering whether the object is consistent with the context is necessary. Motivated by these observations, a two-stage blind image inpainting network, which utilizes global semantic features of the image to locate semantically inconsistent regions and then generates reasonable content in the areas, is proposed. Specifically, the representation differences between inconsistent and available content are first amplified, iteratively predicting the region to be restored from coarse to fine. A confidence-driven inpainting network based on prediction masks is then used to estimate the information regarding missing regions. Furthermore, a multiscale contextual aggregation module is introduced for spatial feature transfer to refine the generated contents. Extensive experiments over multiple datasets demonstrate that the proposed method can generate visually plausible and structurally complete results that are particularly effective in recovering diverse degraded images.展开更多
Contextual advertising is a major revenue source for today＇s companies. Keyword extraction is a key step in this kind of advertising, through which appropriate advertising keywords are extracted from Web pages so tha...Contextual advertising is a major revenue source for today＇s companies. Keyword extraction is a key step in this kind of advertising, through which appropriate advertising keywords are extracted from Web pages so that corresponding ads can be triggered. This paper describes a system that learns how to extract keywords from web pages for advertisement targeting. Firstly a text network for a single webpage is build, then PageRank is applied in the network to decide on the importance of a word, finally top-ranked words are selected as keywords of the webpage. The algorithm is tested on the corpus ofblog pages, and the experimental results prove practical and effective.展开更多
Self-attention aggregates similar feature information to enhance the features. However, the attention covers nonface areas in face alignment, which may be disturbed in challenging cases, such as occlusions, and fails ...Self-attention aggregates similar feature information to enhance the features. However, the attention covers nonface areas in face alignment, which may be disturbed in challenging cases, such as occlusions, and fails to predict landmarks. In addition, the learned feature similarity variance is not large enough in the experiment. To this end, we propose structural dependence learning based on self-attention for face alignment (SSFA). It limits the self-attention learning to the facial range and adaptively builds the significant landmark structure dependency. Compared with other state-of-the-art methods, SSFA effectively improves the performance on several standard facial landmark detection benchmarks and adapts more in challenging cases.展开更多
基金financially supported by The National Natural Science Foundation of China[41471366]The Mc Intire-Stennis Cooperative Forestry Research Program
文摘Forest wildfires pose significant and growing threats to human safety, wildlife habitat, regional economies and global climate change. It is crucial that forest fires be subject to timely and accurate monitoring by forest fire managers and other stake-holders. Measurement by spaceborne equipment has become a practical and appealing method to monitor the occurrence and development of forest wildfires. Here we present an overview of the principles and case studies of forest fire monitoring（FFM） with satelliteand drone-mounted infrared remote sensing（IRRS）. This review includes four types of FFM-relevant IRRS algorithms： bi-spectral methods, fixed threshold methods, spatial contextual methods, and multi-temporal methods. The spatial contextual methods are presented in detail since they can be applied easily with commonly available satellite IRRS data, including MODIS, VIIRS, and Landsat 8 OLI. This review also evaluates typical cases of FFM using NOAAAVHRR, EOS-MODIS, S-NPP VIIRS, Landsat 8 OLI,MSG-SEVIRI, and drone infrared data. To better implement IRRS applications in FFM, it is important to develop accurate forest masks, carry out systematic comparative studies of various forest fire detection systems（known as forest fire products）, and improve methods for assessing the accuracy of forest fire detection. Medium-resolution IRRS data are effective for landscape-scale FFM, and the VIIRS 375 m contextual algorithm and RST-FIRES algorithm are helpful for closely tracking forest fires（including small and shortlived fires） and forest-fire early warning.
文摘多臂赌博机问题是强化学习中研究探索和利用两者平衡的经典问题,其中,随机多臂赌博机问题是最经典的一类多臂赌博机问题,是众多新型多臂赌博机问题的基础.针对现有多臂赌博机算法未能充分使用环境反馈信息以及泛化能力较弱的问题,提出一种自适应的多臂赌博机算法.该算法利用当前估计值最小的动作被选择的次数来调整探索和利用的概率(chosen number of arm with minimal estimation, CNAME),有效缓解了探索和利用不平衡的问题.同时,该算法不依赖于上下文信息,在不同场景的多臂赌博机问题中有更好的泛化能力.通过理论分析给出了该算法的悔值(regret)上界,并通过不同场景的实验结果表明:CNAME算法可以高效地获得较高的奖赏和较低的悔值,并且具有更好的泛化能力.
文摘Historically,vision research in China was one of a few distinct research programs within the Chinese Academy of Sciences(CAS).With improved funding opportunities and research environment in neuroscience,vision research at several research institutes within the academy has made significant progress not only in the quantity of publications,but also in the quality of the work.Based on our own expertise,this review is mainly focused on the findings that have advanced the understanding of visual processing in the central visual pathway,visual perceptual learning,visual development and eye diseases.
基金supported by the National Key Laboratory of ATR(9140C8002010706).
文摘Automatic bridge detection is an important application of SAR images. Differed from the classical CFAR method, a new knowledge-based bridge detection approach is proposed. The method not only uses the backscattering intensity difference between targets and background but also applies the contextual information and spatial relationship between objects. According to bridges＇ special characteristics and scattering properties in SAR images, the new knowledge-based method includes three processes： river segmentation, potential bridge areas detection and bridge discrimination. The application to AIRSAR data shows that the new method is not sensitive to rivers＇ shape. Moreover, this method can detect bridges successfully when river segmentation is not very exact and is more robust than the radius projection method.
文摘Contextual question answering （CQA）, in which user information needs are satisfied through an interactive question answering （QA） dialog, has recently attracted more research attention. One challenge is to fuse contextual information into the understanding process of relevant questions. In this paper, a discourse structure is proposed to maintain semantic information, and approaches for recognition of relevancy type and fusion of contextual information according to relevancy type are proposed. The system is evaluated on real contextual QA data. The results show that better performance is achieved than a baseline system and almost the same performance as when these contextual phenomena are resolved manually. A detailed evaluation analysis is presented.
基金Supported by the National Natural Science Foundation of China. Acknowledgements The National Science Foundation of China supported these works. Thanks to NSFC and all the members of the research groups in Renmin University of China.
文摘Database system is the infrastructure of the modern information system. The R＆D in the database system and its technologies is one of the important research topics in the field. The database R＆D in China took off later but it moves along by giant steps. This report presents the achievements Renmin University of China （RUC） has made in the past 25 years and at the same time addresses some of the research projects we, RUC, are currently working on. The National Natural Science Foundation of China supports and initiates most of our research projects and these successfully conducted projects have produced fruitful results.
基金supported by the National Natural Science Foundation of China,No.81730033(to XPG),81701371(to TJX),81801380(to XZ)Natural Science Foundation of Jiangsu Province of China,No.BK20170654(to TJX),BK20170129(to XZ)
文摘Accumulating evidence indicates that inhalation anesthetics induce or increase the risk of cognitive impairment. GLYX-13（rapastinel） acts on the glycine site of N-methyl-D-aspartate receptors（NMDARs） and has been shown to enhance hippocampus-dependent learning and memory function. However, the mechanisms by which GLYX-13 affects learning and memory function are still unclear. In this study, we investigated these mechanisms in a mouse model of long-term anesthesia exposure. Mice were intravenously administered 1 mg/kg GLYX-13 at 2 hours before isoflurane exposure（1.5% for 6 hours）. Cognitive function was assessed using the contextual fear conditioning test and the novel object recognition test. The mRNA expression and phosphorylated protein levels of NMDAR pathway components, N-methyl-D-aspartate receptor subunit 2B（NR2B）-Ca2+/calmodulin dependent protein kinase II（CaMKII）-cyclic adenosine monophosphate response element binding protein（CREB）, in the hippocampus were evaluated by quantitative RT-PCR and western blot assay. Pretreatment with GLYX-13 ameliorated isoflurane exposure-induced cognitive impairment and restored NR2B, CaMKII and CREB mRNA and phosphorylated protein levels. Intracerebroventricular injection of KN93, a selective CaMKII inhibitor, significantly diminished the effect of GLYX-13 on cognitive function and NR2B, CaMKII and CREB levels in the hippocampus. Taken together, our findings suggest that GLYX-13 pretreatment alleviates isoflurane-induced cognitive dysfunction by protecting against perturbation of the NR2B/CaMKII/CREB signaling pathway in the hippocampus. Therefore, GLYX-13 may have therapeutic potential for the treatment of anesthesia-induced cognitive dysfunction. This study was approved by the Experimental Animal Ethics Committee of Drum Tower Hospital affiliated to the Medical College of Nanjing University, China（approval No. 20171102） on November 20, 2017.
基金supported by the National Natural Science Foundation of China(Grant Nos.61836007,61773276)the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions.
文摘The discourse analysis task,which focuses on understanding the semantics of long text spans,has received increasing attention in recent years.As a critical component of discourse analysis,discourse relation recognition aims to identify the rhetorical relations between adjacent discourse units(e.g.,clauses,sentences,and sentence groups),called arguments,in a document.Previous works focused on capturing the semantic interactions between arguments to recognize their discourse relations,ignoring important textual information in the surrounding contexts.However,in many cases,more than capturing semantic interactions from the texts of the two arguments are needed to identify their rhetorical relations,requiring mining more contextual clues.In this paper,we propose a method to convert the RST-style discourse trees in the training set into dependency-based trees and train a contextual evidence selector on these transformed structures.In this way,the selector can learn the ability to automatically pick critical textual information from the context(i.e.,as evidence)for arguments to assist in discriminating their relations.Then we encode the arguments concatenated with corresponding evidence to obtain the enhanced argument representations.Finally,we combine original and enhanced argument representations to recognize their relations.In addition,we introduce auxiliary tasks to guide the training of the evidence selector to strengthen its selection ability.The experimental results on the Chinese CDTB dataset show that our method outperforms several state-of-the-art baselines in both micro and macro F1 scores.
基金The paper was supported by Henan Province Teaching Reform and Practice Project(Project Fund No.135)-Research on the Reform of Literary Theory Courses for English Majors in Universities.
文摘This study explores the application of Abrams’Fourfold Model in the classification of Western literary criticism.Abrams’framework categorizes literary criticism into four fundamental elements:text,author,world,and audience.The text is viewed as an independent entity with intrinsic artistic value,necessitating a detailed analysis of its structure,style,themes,and symbols.Author study delves into the creator’s life and socio-cultural context,often to uncover the work’s deeper meanings.Contextual study situates the work within its historical and social milieu,examining its reflection of or response to societal norms and events.Audience response analysis considers the diverse interpretations shaped by readers’backgrounds,emphasizing the reader’s role in constructing the work’s meaning.The study concludes that Abrams’Fourfold Model offers a comprehensive and flexible analytical tool,enabling critics to engage with literary works from multiple perspectives,thereby enriching the understanding of literary complexity and diversity.
基金supported by the Natural Science Foundation of Shandong Province of China(No.ZR2020MF140)the Major Scientific and Technological Projects of CNPC(No.ZD2019-183-004)the Fundamental Research Funds for the Central Universities(No.20CX05019A).
文摘Most existing image inpainting methods aim to fill in the missing content in the inside-hole region of the target image. However, the areas to be restored in realistically degraded images are unspecified. Previous studies have failed to recover the degradations due to the absence of the explicit mask indication. Meanwhile, inconsistent patterns are blended complexly with the image content. Therefore, estimating whether certain pixels are out of distribution and considering whether the object is consistent with the context is necessary. Motivated by these observations, a two-stage blind image inpainting network, which utilizes global semantic features of the image to locate semantically inconsistent regions and then generates reasonable content in the areas, is proposed. Specifically, the representation differences between inconsistent and available content are first amplified, iteratively predicting the region to be restored from coarse to fine. A confidence-driven inpainting network based on prediction masks is then used to estimate the information regarding missing regions. Furthermore, a multiscale contextual aggregation module is introduced for spatial feature transfer to refine the generated contents. Extensive experiments over multiple datasets demonstrate that the proposed method can generate visually plausible and structurally complete results that are particularly effective in recovering diverse degraded images.
基金This study is supported by Beijing Natural Science Foundation of （4092029） and the Fundamental Research Funds for the Central Universities （2009RC0217）.
文摘Contextual advertising is a major revenue source for today＇s companies. Keyword extraction is a key step in this kind of advertising, through which appropriate advertising keywords are extracted from Web pages so that corresponding ads can be triggered. This paper describes a system that learns how to extract keywords from web pages for advertisement targeting. Firstly a text network for a single webpage is build, then PageRank is applied in the network to decide on the importance of a word, finally top-ranked words are selected as keywords of the webpage. The algorithm is tested on the corpus ofblog pages, and the experimental results prove practical and effective.
基金supported by the National Key R&D Program of China(No.2021YFE0205700)the National Natural Science Foundation of China(Nos.62076235,62276260 and 62002356)+1 种基金sponsored by the Zhejiang Lab(No.2021KH0AB07)the Ministry of Education Industry-University Cooperative Education Program(Wei Qiao Venture Group,No.E1425201).
文摘Self-attention aggregates similar feature information to enhance the features. However, the attention covers nonface areas in face alignment, which may be disturbed in challenging cases, such as occlusions, and fails to predict landmarks. In addition, the learned feature similarity variance is not large enough in the experiment. To this end, we propose structural dependence learning based on self-attention for face alignment (SSFA). It limits the self-attention learning to the facial range and adaptively builds the significant landmark structure dependency. Compared with other state-of-the-art methods, SSFA effectively improves the performance on several standard facial landmark detection benchmarks and adapts more in challenging cases.
