Unsupervised methods based on density representation have shown their abilities in anomaly detection,but detection performance still needs to be improved.Specifically,approaches using normalizing flows can accurately ...Unsupervised methods based on density representation have shown their abilities in anomaly detection,but detection performance still needs to be improved.Specifically,approaches using normalizing flows can accurately evaluate sample distributions,mapping normal features to the normal distribution and anomalous features outside it.Consequently,this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network(NF-BMR).It utilizes pre-trained Convolutional Neural Networks(CNN)and normalizing flows to construct discriminative source and target domain feature spaces.Additionally,to better learn feature information in both domain spaces,we propose the Bidirectional Mapping Residual Network(BMR),which maps sample features to these two spaces for anomaly detection.The two detection spaces effectively complement each other’s deficiencies and provide a comprehensive feature evaluation from two perspectives,which leads to the improvement of detection performance.Comparative experimental results on the MVTec AD and DAGM datasets against the Bidirectional Pre-trained Feature Mapping Network(B-PFM)and other state-of-the-art methods demonstrate that the proposed approach achieves superior performance.On the MVTec AD dataset,NF-BMR achieves an average AUROC of 98.7%for all 15 categories.Especially,it achieves 100%optimal detection performance in five categories.On the DAGM dataset,the average AUROC across ten categories is 98.7%,which is very close to supervised methods.展开更多
Research papers in the field of SLA published between 2009 and 2019 are analyzed in terms of research status of domes⁃tic SLA researchers,research institutions,research frontiers and hotspots in the paper,and maps the...Research papers in the field of SLA published between 2009 and 2019 are analyzed in terms of research status of domes⁃tic SLA researchers,research institutions,research frontiers and hotspots in the paper,and maps the knowledge domains of SLA re⁃searches.The data are retrieved from 10 core journals of linguistics via the CNKI journal database.By means of CiteSpace 5.3,an analysis of the overall trend of studies on SLA in China is made.展开更多
AIM:To track the knowledge structure,topics in focus,and trends in emerging research in pterygium in the past 20 y.METHODS:Base on the Web of Science Core Collection(Wo SCC),studies related to pterygium in the past 20...AIM:To track the knowledge structure,topics in focus,and trends in emerging research in pterygium in the past 20 y.METHODS:Base on the Web of Science Core Collection(Wo SCC),studies related to pterygium in the past 20 y from 2000-2019 have been included.With the help of VOSviewer software,a knowledge map was constructed and the distribution of countries,institutions,journals,and authors in the field of pterygium noted.Meanwhile,using cocitation analysis of references and co-occurrence analysis of keywords,we identified basis and hotspots,thereby obtaining an overview of this field.RESULTS:The search retrieved 1516 publications from Wo SCC on pterygium published between 2000 and 2019.In the past two decades,the annual number of publications is on the rise and fluctuated a little.Most productive institutions are from Singapore but the most prolific and active country is the United States.Journal Cornea published the most articles and Coroneo MT contributed the most publications on pterygium.From cooccurrence analysis,the keywords formed 3 clusters:1)surgical therapeutic techniques and adjuvant of pterygium,2)occurrence process and pathogenesis of pterygium,and 3)epidemiology,and etiology of pterygium formation.These three clusters were consistent with the clustering in co-citation analysis,in which Cluster 1 contained the most references(74 publications,47.74%),Cluster 2 contained 53 publications,accounting for 34.19%,and Cluster 3 focused on epidemiology with 18.06%of total 155 cocitation publications.CONCLUSION:This study demonstrates that the research of pterygium is gradually attracting the attention of scholars and researchers.The interaction between authors,institutions,and countries is lack of.Even though,the research hotspot,distribution,and research status in pterygium in this study could provide valuable information for scholars and researchers.展开更多
Neural stem cells,which are capable of multi-potential differentiation and self-renewal,have recently been shown to have clinical potential for repairing central nervous system tissue damage.However,the theme trends a...Neural stem cells,which are capable of multi-potential differentiation and self-renewal,have recently been shown to have clinical potential for repairing central nervous system tissue damage.However,the theme trends and knowledge structures for human neural stem cells have not yet been studied bibliometrically.In this study,we retrieved 2742 articles from the PubMed database from 2013 to 2018 using "Neural Stem Cells" as the retrieval word.Co-word analysis was conducted to statistically quantify the characteristics and popular themes of human neural stem cell-related studies.Bibliographic data matrices were generated with the Bibliographic Item Co-Occurrence Matrix Builder.We identified 78 high-frequency Medical Subject Heading(MeSH)terms.A visual matrix was built with the repeated bisection method in gCLUTO software.A social network analysis network was generated with Ucinet 6.0 software and GraphPad Prism 5 software.The analyses demonstrated that in the 6-year period,hot topics were clustered into five categories.As suggested by the constructed strategic diagram,studies related to cytology and physiology were well-developed,whereas those related to neural stem cell applications,tissue engineering,metabolism and cell signaling,and neural stem cell pathology and virology remained immature.Neural stem cell therapy for stroke and Parkinson’s disease,the genetics of microRNAs and brain neoplasms,as well as neuroprotective agents,Zika virus,Notch receptor,neural crest and embryonic stem cells were identified as emerging hot spots.These undeveloped themes and popular topics are potential points of focus for new studies on human neural stem cells.展开更多
Background:Military medicine is a research field that seeks to solve the medical problems that occur in modern war conditions based on public medicine theory.Methods:We explore the main research topics of military hea...Background:Military medicine is a research field that seeks to solve the medical problems that occur in modern war conditions based on public medicine theory.Methods:We explore the main research topics of military health and medical research in the Web of Science?core collection(Wo SCC)from 2007 to 2016,and the goal of this work is to serve as a reference for orientation and development in military health and medicine.Based on Cite Space III,a reference co-citation analysis is performed for 7921 papers published in the Wo SCC from 2007 to 2016.In addition,a cluster analysis of research topics is performed with a comprehensive analysis of high-yield authors,outstanding research institutions and their cooperative networks.Results:Currently,the research topics in military health and medicine mainly focus on the following seven aspects:mental health diagnoses and interventions,an army study to assess risk and resilience in service members(STARRS),large-scale military action,brain science,veterans,soldier parents and children of wartime,and wound infection.We also observed that the annual publication rate increased with time.Wessely S,Greenberg N,Fear NT,Smith TC,Smith B,Jones N,Ryan MAK,Boyko EJ,Hull L,and Rona RJ were the top 10 authors in military health and medicine research.The top 10 institutes were the Uniformed Services University of the Health Sciences,the United States Army,the United States Navy,Kings College London,Walter Reed National Military Medical Center,Boston University,Walter Reed Army Institute of Research,Walter Reed Army Medical Center,Naval Health Research Center,and the VA Boston Healthcare System.Conclusion:We are able to perform a comprehensive analysis of studies in military health and medicine research and summarize the current research climate and the developmental trends in the Wo SCC.However,further studies and collaborations are needed worldwide.Overall,our findings provide valuable information and new perspectives and shape future research directions for further research in the area of military health and medicine.展开更多
Immune evolutionary algorithms with domain knowledge were presented to solve the problem of simultaneous localization and mapping for a mobile robot in unknown environments. Two operators with domain knowledge were de...Immune evolutionary algorithms with domain knowledge were presented to solve the problem of simultaneous localization and mapping for a mobile robot in unknown environments. Two operators with domain knowledge were designed in algorithms, where the feature of parallel line segments without the problem of data association was used to construct a vaccination operator, and the characters of convex vertices in polygonal obstacle were extended to develop a pulling operator of key point grid. The experimental results of a real mobile robot show that the computational expensiveness of algorithms designed is less than other evolutionary algorithms for simultaneous localization and mapping and the maps obtained are very accurate. Because immune evolutionary algorithms with domain knowledge have some advantages, the convergence rate of designed algorithms is about 44% higher than those of other algorithms.展开更多
With the rapid development and popularization of web services, the available information types and structure are becoming more and more complex and challenging. Actually web services involve the need for dynamic integ...With the rapid development and popularization of web services, the available information types and structure are becoming more and more complex and challenging. Actually web services involve the need for dynamic integration and transparent knowledge integration, in light of the urgent information changing track. Under this situation, the traditional search engine and information integration cannot finish this challenge, thereby bringing the opportunity for knowledge fusion and synchronization. This paper proposes a multi-matching strategy ontology mapping method for web information, i.e., ubiquitous ontology mapping method (U-Mapping), which can be viewed as a base collection of information on multiple ontologies made to appear anytime and everywhere. This approach is usually built independently by different information providers, avoiding the grammatical and semantic conflict. Finally, the ontology case information can be utilized under the consolidation of the U-Mapping, concerning language technology and machine learning methods.展开更多
Objective:To uncover and identify the hot topic and frontier of Chinese medicines treatment of type 2 diabetes mellitus(T2DM).Methods:Web of Science TM was searched for published articles for Chinese medicines treatme...Objective:To uncover and identify the hot topic and frontier of Chinese medicines treatment of type 2 diabetes mellitus(T2DM).Methods:Web of Science TM was searched for published articles for Chinese medicines treatment of T2DM ranging from January 1st,2002 to July 6th,2016.Knowledge maps of the international Chinese medicines treatment of T2DM are visualized by using document cooccurrence analysis and word frequency analysis(Institution and Journal),co-citation clustering analysis(Co-reference),keyword co-occurrence clustering analysis with CiteSpac III,a tool of scientometrics.Results:Universidad Nacional Autonoma de Mexico is the institution with the highest number of published papers that had been cited in this field,while China has four institutions among the top 10.The journal of the highest frequency of co-cited journal was Diabetes Care,a core one in the field.Keywords co-occurrence network was composed of 185 nodes,541 lines,and divided into 10 clusters.Co-citation network of co-reference was composed of 407 nodes,1199 lines,and divided into 20 clusters.Using Chinese medicine to improve insulin resistance and Chinese medicine research on blood glucose control are the hot topics.The frontier contains two aspects:new drugs development and application of intestinal insulin treatment and development and use of traditional Chinese medicine antidiabetic plants.Conclusion:Institutions from China still plays a major role in TCM-focused T2DM studies.The effect of TCM herbs on insulin resistance is the hot topic of the domain.Developing new TCM herbal medicine that regulates incretin effect is the domain frontier.Research on the Chinese medicines treatment of T2DM needs more high-quality evidence to support,and its mechanism requires further exploration.展开更多
Based on bibliometrics and knowledge mapping analysis method,this paper uses CiteSpace,a visual literature analysis tool,to analyze 3794 related documents with the theme of“economic economy”in SCI and SSCI databases...Based on bibliometrics and knowledge mapping analysis method,this paper uses CiteSpace,a visual literature analysis tool,to analyze 3794 related documents with the theme of“economic economy”in SCI and SSCI databases from 2010 to 2020,including authors,institutions,subject headings and literature co-citation,so as to reveal the development and hot spots of ecological economic research.The results show that in recent years,the number of documents on ecological economic research has been increasing,and developed countries are dominant.China’s research in this field has developed rapidly and has certain advantages in terms of quantity and quality.The institution with the largest number of papers is Chinese Academy Science,followed by Beijing Normal University,University of Chinese Academy of Sciences,Peking University and Universitat autonomy de Barcelona;research hotspots in recent 10 years include“sustainability”,“management”,“climate change”,“impact”,“economy”,“china”,“conservation”,“ecosystem service”,etc.The top three journals are Sustainability,Journal of Cleaner Production,and Ecological Economics,accounting for about 10%of the total number of papers published.The hot spots of ecological economic research in 2010-2020 can be divided into three stages,with different theme words emerging in each stage.From 2018 to 2020,the theme word of high-strength emergence is“anthropocene”,which indicates that“anthropocene”may be the focus of future research.展开更多
We mainly discuss the invariance of some subclasses of biholomorphic mappings under the generalized Roper-Suffridge operators on Bergman-Hartogs domains which are based on the unit ball Bn. Using the geometric propert...We mainly discuss the invariance of some subclasses of biholomorphic mappings under the generalized Roper-Suffridge operators on Bergman-Hartogs domains which are based on the unit ball Bn. Using the geometric properties and the distortion results of subclasses of biholomorphic mappings, we obtain the geometric characters of almost spirallike mappings of type β and order α, S_?~*(β, A, B), strong and almost spirallike mappings of type βand order α maintained under the generalized Roper-Suffridge operators on Bergman-Hartogs domains. Sequentially, we conclude that the generalized operators and the known operators preserve the same properties under some conditions. The conclusions generalize some known results.展开更多
This paper studies the linkage problem between the result of high-level synthesis and back-end technology, presents a method of high-level technology mapping based on knowl edge, and studies deeply all of its importan...This paper studies the linkage problem between the result of high-level synthesis and back-end technology, presents a method of high-level technology mapping based on knowl edge, and studies deeply all of its important links such as knowledge representation, knowledge utility and knowledge acquisition. It includes: (1) present a kind of expanded production about knowledge of circuit structure; (2) present a VHDL-based method to acquire knowledge of tech nology mapping; (3) provide solution control strategy and algorithm of knowledge utility; (4)present a half-automatic maintenance method, which can find redundance and contradiction of knowledge base; (5) present a practical method to embed the algorithm into knowledge system to decrease complexity of knowledge base. A system has been developed and linked with three kinds of technologies, so verified the work of this paper.展开更多
In this paper, we give a property of normalized biholomorphic convex mappings on the first, second and third classical domains: for any Z0 belongs to the classical domains,f maps each neighbourhood with the center Z0,...In this paper, we give a property of normalized biholomorphic convex mappings on the first, second and third classical domains: for any Z0 belongs to the classical domains,f maps each neighbourhood with the center Z0, which is contained in the classical domains,to a convex domain.展开更多
Dear Editor,Zhang et al[1] recently published a bibliometric paper entitled "Trends in research related to high myopia from 2010 to 2019: A bibliometric and knowledge mapping analysis". The authors mentioned...Dear Editor,Zhang et al[1] recently published a bibliometric paper entitled "Trends in research related to high myopia from 2010 to 2019: A bibliometric and knowledge mapping analysis". The authors mentioned in section Data Source and Research Strategy that "we retrieved Wo SCC(https://webofknowledge.com/) in the Science Citation Index Expanded(SCIE) database online as data source".展开更多
<div style="text-align:justify;"> <span style="font-family:Verdana;">In order to understand the current status and future trends of China’s science and technology evaluation research, ...<div style="text-align:justify;"> <span style="font-family:Verdana;">In order to understand the current status and future trends of China’s science and technology evaluation research, we use the visual analysis tool CiteSpace to use the source journals included in the Chinese social science citations from 1998-2019 as the data source, and evaluate the domestic science and technology evaluation papers from the number of publications, the co-occurrence of authors, Institutional co-occurrence and subject clustering are analyzed. The study found that: the total amount of literature in the field of domestic science and technology evaluation is showing an overall upward trend;a relatively obvious author cooperation network has been formed, but the core author group has not yet been formed;institutional cooperation clusters have appeared, but the cooperation between institutions is still relatively scattered;The research topics focus on three aspects: science and technology evaluation index system, evaluation method and evaluation system.</span> </div>展开更多
Text event mining,as an indispensable method of text mining processing,has attracted the extensive attention of researchers.A modeling method for knowledge graph of events based on mutual information among neighbor do...Text event mining,as an indispensable method of text mining processing,has attracted the extensive attention of researchers.A modeling method for knowledge graph of events based on mutual information among neighbor domains and sparse representation is proposed in this paper,i.e.UKGE-MS.Specifically,UKGE-MS can improve the existing text mining technology's ability of understanding and discovering high-dimensional unmarked information,and solves the problems of traditional unsupervised feature selection methods,which only focus on selecting features from a global perspective and ignoring the impact of local connection of samples.Firstly,considering the influence of local information of samples in feature correlation evaluation,a feature clustering algorithm based on average neighborhood mutual information is proposed,and the feature clusters with certain event correlation are obtained;Secondly,an unsupervised feature selection method based on the high-order correlation of multi-dimensional statistical data is designed by combining the dimension reduction advantage of local linear embedding algorithm and the feature selection ability of sparse representation,so as to enhance the generalization ability of the selected feature items.Finally,the events knowledge graph is constructed by means of sparse representation and l1 norm.Extensive experiments are carried out on five real datasets and synthetic datasets,and the UKGE-MS are compared with five corresponding algorithms.The experimental results show that UKGE-MS is better than the traditional method in event clustering and feature selection,and has some advantages over other methods in text event recognition and discovery.展开更多
The aim of the paper is to identify and explore leading thematic areas within the research field related to Business Schools Accreditation in China.Based on data from the China National Knowledge Infrastructure(CNKI)d...The aim of the paper is to identify and explore leading thematic areas within the research field related to Business Schools Accreditation in China.Based on data from the China National Knowledge Infrastructure(CNKI)database,the keywords frequency was analyzed,and the theory of mapping knowledge domain was used to visualize the keywords co-occurrence network to make further research of the heated issues.The findings indicate that the research scope involved in business school accreditation research is broad,and research content focus on teaching,management,talent cultivation.According to the results of keywords co-occurrence analysis of different stages,AACSB,AACSB Accreditation,international accreditation,business school,AOL,internationalization,accreditation are the most important issues to business school research in China,given their position and role in the research network.The paper generates the added value mainly from the point of view of theory development.展开更多
In this paper, we will investigate convex domains and starlike domains whichcontain the image set of normalized holomorphic mappings on bounded starlike circulardomains in
Most existing domain adaptation(DA) methods aim to explore favorable performance under complicated environments by sampling.However,there are three unsolved problems that limit their efficiencies:ⅰ) they adopt global...Most existing domain adaptation(DA) methods aim to explore favorable performance under complicated environments by sampling.However,there are three unsolved problems that limit their efficiencies:ⅰ) they adopt global sampling but neglect to exploit global and local sampling simultaneously;ⅱ)they either transfer knowledge from a global perspective or a local perspective,while overlooking transmission of confident knowledge from both perspectives;and ⅲ) they apply repeated sampling during iteration,which takes a lot of time.To address these problems,knowledge transfer learning via dual density sampling(KTL-DDS) is proposed in this study,which consists of three parts:ⅰ) Dual density sampling(DDS) that jointly leverages two sampling methods associated with different views,i.e.,global density sampling that extracts representative samples with the most common features and local density sampling that selects representative samples with critical boundary information;ⅱ)Consistent maximum mean discrepancy(CMMD) that reduces intra-and cross-domain risks and guarantees high consistency of knowledge by shortening the distances of every two subsets among the four subsets collected by DDS;and ⅲ) Knowledge dissemination(KD) that transmits confident and consistent knowledge from the representative target samples with global and local properties to the whole target domain by preserving the neighboring relationships of the target domain.Mathematical analyses show that DDS avoids repeated sampling during the iteration.With the above three actions,confident knowledge with both global and local properties is transferred,and the memory and running time are greatly reduced.In addition,a general framework named dual density sampling approximation(DDSA) is extended,which can be easily applied to other DA algorithms.Extensive experiments on five datasets in clean,label corruption(LC),feature missing(FM),and LC&FM environments demonstrate the encouraging performance of KTL-DDS.展开更多
The aim of the paper is to identify and explore leading development situation within the research field related to student classroom engagement.Using knowledge mapping tools,this paper conducted the visualization anal...The aim of the paper is to identify and explore leading development situation within the research field related to student classroom engagement.Using knowledge mapping tools,this paper conducted the visualization analysis on internationalliteraturein relation to student classroom engagementfrom the Web of Science databases.By combination of the statistical data and visualizationmapping,this paper studied on the research relationship networks and status for the co-authors'countries/institutions,co-citation documents/journalsand co-occurring keywordsbased on the sample datafromliterature.The results indicate that the number ofpublished papershasincreased obviously and expanded graduallysince 2000.Main countries and institutions of researches were the UnitedStates,Australia,United Kingdom,Canada and China in order,and these countries had intense collaboration.The theoretical basis of the research come from education and teaching,psychology.The hotspots of researches fromthe global literature coveredvarious fields including achievement,motivation,behavior,education,performance.As a result of the multidisciplinary integration,many relevant internationalresearch constantly expanded the research scopes,which promoted the combination and development of theories.展开更多
基金This work was supported in part by the National Key R&D Program of China 2021YFE0110500in part by the National Natural Science Foundation of China under Grant 62062021in part by the Guiyang Scientific Plan Project[2023]48-11.
文摘Unsupervised methods based on density representation have shown their abilities in anomaly detection,but detection performance still needs to be improved.Specifically,approaches using normalizing flows can accurately evaluate sample distributions,mapping normal features to the normal distribution and anomalous features outside it.Consequently,this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network(NF-BMR).It utilizes pre-trained Convolutional Neural Networks(CNN)and normalizing flows to construct discriminative source and target domain feature spaces.Additionally,to better learn feature information in both domain spaces,we propose the Bidirectional Mapping Residual Network(BMR),which maps sample features to these two spaces for anomaly detection.The two detection spaces effectively complement each other’s deficiencies and provide a comprehensive feature evaluation from two perspectives,which leads to the improvement of detection performance.Comparative experimental results on the MVTec AD and DAGM datasets against the Bidirectional Pre-trained Feature Mapping Network(B-PFM)and other state-of-the-art methods demonstrate that the proposed approach achieves superior performance.On the MVTec AD dataset,NF-BMR achieves an average AUROC of 98.7%for all 15 categories.Especially,it achieves 100%optimal detection performance in five categories.On the DAGM dataset,the average AUROC across ten categories is 98.7%,which is very close to supervised methods.
文摘Research papers in the field of SLA published between 2009 and 2019 are analyzed in terms of research status of domes⁃tic SLA researchers,research institutions,research frontiers and hotspots in the paper,and maps the knowledge domains of SLA re⁃searches.The data are retrieved from 10 core journals of linguistics via the CNKI journal database.By means of CiteSpace 5.3,an analysis of the overall trend of studies on SLA in China is made.
基金the National Natural Science Foundation of China(No.81870644)。
文摘AIM:To track the knowledge structure,topics in focus,and trends in emerging research in pterygium in the past 20 y.METHODS:Base on the Web of Science Core Collection(Wo SCC),studies related to pterygium in the past 20 y from 2000-2019 have been included.With the help of VOSviewer software,a knowledge map was constructed and the distribution of countries,institutions,journals,and authors in the field of pterygium noted.Meanwhile,using cocitation analysis of references and co-occurrence analysis of keywords,we identified basis and hotspots,thereby obtaining an overview of this field.RESULTS:The search retrieved 1516 publications from Wo SCC on pterygium published between 2000 and 2019.In the past two decades,the annual number of publications is on the rise and fluctuated a little.Most productive institutions are from Singapore but the most prolific and active country is the United States.Journal Cornea published the most articles and Coroneo MT contributed the most publications on pterygium.From cooccurrence analysis,the keywords formed 3 clusters:1)surgical therapeutic techniques and adjuvant of pterygium,2)occurrence process and pathogenesis of pterygium,and 3)epidemiology,and etiology of pterygium formation.These three clusters were consistent with the clustering in co-citation analysis,in which Cluster 1 contained the most references(74 publications,47.74%),Cluster 2 contained 53 publications,accounting for 34.19%,and Cluster 3 focused on epidemiology with 18.06%of total 155 cocitation publications.CONCLUSION:This study demonstrates that the research of pterygium is gradually attracting the attention of scholars and researchers.The interaction between authors,institutions,and countries is lack of.Even though,the research hotspot,distribution,and research status in pterygium in this study could provide valuable information for scholars and researchers.
基金supported by the National Natural Science Foundation of China,No.81471308(to JL)the Stem Cell Clinical Research Project in China,No.CMR-20161129-1003(to JL)the Innovation Technology Funding of Dalian in China,No.2018J11CY025(to JL)
文摘Neural stem cells,which are capable of multi-potential differentiation and self-renewal,have recently been shown to have clinical potential for repairing central nervous system tissue damage.However,the theme trends and knowledge structures for human neural stem cells have not yet been studied bibliometrically.In this study,we retrieved 2742 articles from the PubMed database from 2013 to 2018 using "Neural Stem Cells" as the retrieval word.Co-word analysis was conducted to statistically quantify the characteristics and popular themes of human neural stem cell-related studies.Bibliographic data matrices were generated with the Bibliographic Item Co-Occurrence Matrix Builder.We identified 78 high-frequency Medical Subject Heading(MeSH)terms.A visual matrix was built with the repeated bisection method in gCLUTO software.A social network analysis network was generated with Ucinet 6.0 software and GraphPad Prism 5 software.The analyses demonstrated that in the 6-year period,hot topics were clustered into five categories.As suggested by the constructed strategic diagram,studies related to cytology and physiology were well-developed,whereas those related to neural stem cell applications,tissue engineering,metabolism and cell signaling,and neural stem cell pathology and virology remained immature.Neural stem cell therapy for stroke and Parkinson’s disease,the genetics of microRNAs and brain neoplasms,as well as neuroprotective agents,Zika virus,Notch receptor,neural crest and embryonic stem cells were identified as emerging hot spots.These undeveloped themes and popular topics are potential points of focus for new studies on human neural stem cells.
基金supported financially by the Project of the“12th FiveYear”for Medical Scientific and Technology(CWS11L050)of the PLAthe Science and Technology Development Fund of China Academy of Engineering Physics(wss-2014-03).
文摘Background:Military medicine is a research field that seeks to solve the medical problems that occur in modern war conditions based on public medicine theory.Methods:We explore the main research topics of military health and medical research in the Web of Science?core collection(Wo SCC)from 2007 to 2016,and the goal of this work is to serve as a reference for orientation and development in military health and medicine.Based on Cite Space III,a reference co-citation analysis is performed for 7921 papers published in the Wo SCC from 2007 to 2016.In addition,a cluster analysis of research topics is performed with a comprehensive analysis of high-yield authors,outstanding research institutions and their cooperative networks.Results:Currently,the research topics in military health and medicine mainly focus on the following seven aspects:mental health diagnoses and interventions,an army study to assess risk and resilience in service members(STARRS),large-scale military action,brain science,veterans,soldier parents and children of wartime,and wound infection.We also observed that the annual publication rate increased with time.Wessely S,Greenberg N,Fear NT,Smith TC,Smith B,Jones N,Ryan MAK,Boyko EJ,Hull L,and Rona RJ were the top 10 authors in military health and medicine research.The top 10 institutes were the Uniformed Services University of the Health Sciences,the United States Army,the United States Navy,Kings College London,Walter Reed National Military Medical Center,Boston University,Walter Reed Army Institute of Research,Walter Reed Army Medical Center,Naval Health Research Center,and the VA Boston Healthcare System.Conclusion:We are able to perform a comprehensive analysis of studies in military health and medicine research and summarize the current research climate and the developmental trends in the Wo SCC.However,further studies and collaborations are needed worldwide.Overall,our findings provide valuable information and new perspectives and shape future research directions for further research in the area of military health and medicine.
基金Projects(60234030 60404021) supported by the National Natural Science Foundation of China
文摘Immune evolutionary algorithms with domain knowledge were presented to solve the problem of simultaneous localization and mapping for a mobile robot in unknown environments. Two operators with domain knowledge were designed in algorithms, where the feature of parallel line segments without the problem of data association was used to construct a vaccination operator, and the characters of convex vertices in polygonal obstacle were extended to develop a pulling operator of key point grid. The experimental results of a real mobile robot show that the computational expensiveness of algorithms designed is less than other evolutionary algorithms for simultaneous localization and mapping and the maps obtained are very accurate. Because immune evolutionary algorithms with domain knowledge have some advantages, the convergence rate of designed algorithms is about 44% higher than those of other algorithms.
文摘With the rapid development and popularization of web services, the available information types and structure are becoming more and more complex and challenging. Actually web services involve the need for dynamic integration and transparent knowledge integration, in light of the urgent information changing track. Under this situation, the traditional search engine and information integration cannot finish this challenge, thereby bringing the opportunity for knowledge fusion and synchronization. This paper proposes a multi-matching strategy ontology mapping method for web information, i.e., ubiquitous ontology mapping method (U-Mapping), which can be viewed as a base collection of information on multiple ontologies made to appear anytime and everywhere. This approach is usually built independently by different information providers, avoiding the grammatical and semantic conflict. Finally, the ontology case information can be utilized under the consolidation of the U-Mapping, concerning language technology and machine learning methods.
基金National Natural Science Foundation of China(No.81273876).
文摘Objective:To uncover and identify the hot topic and frontier of Chinese medicines treatment of type 2 diabetes mellitus(T2DM).Methods:Web of Science TM was searched for published articles for Chinese medicines treatment of T2DM ranging from January 1st,2002 to July 6th,2016.Knowledge maps of the international Chinese medicines treatment of T2DM are visualized by using document cooccurrence analysis and word frequency analysis(Institution and Journal),co-citation clustering analysis(Co-reference),keyword co-occurrence clustering analysis with CiteSpac III,a tool of scientometrics.Results:Universidad Nacional Autonoma de Mexico is the institution with the highest number of published papers that had been cited in this field,while China has four institutions among the top 10.The journal of the highest frequency of co-cited journal was Diabetes Care,a core one in the field.Keywords co-occurrence network was composed of 185 nodes,541 lines,and divided into 10 clusters.Co-citation network of co-reference was composed of 407 nodes,1199 lines,and divided into 20 clusters.Using Chinese medicine to improve insulin resistance and Chinese medicine research on blood glucose control are the hot topics.The frontier contains two aspects:new drugs development and application of intestinal insulin treatment and development and use of traditional Chinese medicine antidiabetic plants.Conclusion:Institutions from China still plays a major role in TCM-focused T2DM studies.The effect of TCM herbs on insulin resistance is the hot topic of the domain.Developing new TCM herbal medicine that regulates incretin effect is the domain frontier.Research on the Chinese medicines treatment of T2DM needs more high-quality evidence to support,and its mechanism requires further exploration.
文摘Based on bibliometrics and knowledge mapping analysis method,this paper uses CiteSpace,a visual literature analysis tool,to analyze 3794 related documents with the theme of“economic economy”in SCI and SSCI databases from 2010 to 2020,including authors,institutions,subject headings and literature co-citation,so as to reveal the development and hot spots of ecological economic research.The results show that in recent years,the number of documents on ecological economic research has been increasing,and developed countries are dominant.China’s research in this field has developed rapidly and has certain advantages in terms of quantity and quality.The institution with the largest number of papers is Chinese Academy Science,followed by Beijing Normal University,University of Chinese Academy of Sciences,Peking University and Universitat autonomy de Barcelona;research hotspots in recent 10 years include“sustainability”,“management”,“climate change”,“impact”,“economy”,“china”,“conservation”,“ecosystem service”,etc.The top three journals are Sustainability,Journal of Cleaner Production,and Ecological Economics,accounting for about 10%of the total number of papers published.The hot spots of ecological economic research in 2010-2020 can be divided into three stages,with different theme words emerging in each stage.From 2018 to 2020,the theme word of high-strength emergence is“anthropocene”,which indicates that“anthropocene”may be the focus of future research.
基金supported by NSF of China(11271359,11471098)Science and Technology Research Projects of Henan Provincial Education Department(17A110041)Scientific Research and Innovation Fund Projects of Zhoukou Normal University(ZKNUA201805)
文摘We mainly discuss the invariance of some subclasses of biholomorphic mappings under the generalized Roper-Suffridge operators on Bergman-Hartogs domains which are based on the unit ball Bn. Using the geometric properties and the distortion results of subclasses of biholomorphic mappings, we obtain the geometric characters of almost spirallike mappings of type β and order α, S_?~*(β, A, B), strong and almost spirallike mappings of type βand order α maintained under the generalized Roper-Suffridge operators on Bergman-Hartogs domains. Sequentially, we conclude that the generalized operators and the known operators preserve the same properties under some conditions. The conclusions generalize some known results.
文摘This paper studies the linkage problem between the result of high-level synthesis and back-end technology, presents a method of high-level technology mapping based on knowl edge, and studies deeply all of its important links such as knowledge representation, knowledge utility and knowledge acquisition. It includes: (1) present a kind of expanded production about knowledge of circuit structure; (2) present a VHDL-based method to acquire knowledge of tech nology mapping; (3) provide solution control strategy and algorithm of knowledge utility; (4)present a half-automatic maintenance method, which can find redundance and contradiction of knowledge base; (5) present a practical method to embed the algorithm into knowledge system to decrease complexity of knowledge base. A system has been developed and linked with three kinds of technologies, so verified the work of this paper.
基金Foundation item： Supported by the National Natural Science Foundation of China（11001074, 11061015, 11101124）
文摘In this paper, we give a property of normalized biholomorphic convex mappings on the first, second and third classical domains: for any Z0 belongs to the classical domains,f maps each neighbourhood with the center Z0, which is contained in the classical domains,to a convex domain.
文摘Dear Editor,Zhang et al[1] recently published a bibliometric paper entitled "Trends in research related to high myopia from 2010 to 2019: A bibliometric and knowledge mapping analysis". The authors mentioned in section Data Source and Research Strategy that "we retrieved Wo SCC(https://webofknowledge.com/) in the Science Citation Index Expanded(SCIE) database online as data source".
文摘<div style="text-align:justify;"> <span style="font-family:Verdana;">In order to understand the current status and future trends of China’s science and technology evaluation research, we use the visual analysis tool CiteSpace to use the source journals included in the Chinese social science citations from 1998-2019 as the data source, and evaluate the domestic science and technology evaluation papers from the number of publications, the co-occurrence of authors, Institutional co-occurrence and subject clustering are analyzed. The study found that: the total amount of literature in the field of domestic science and technology evaluation is showing an overall upward trend;a relatively obvious author cooperation network has been formed, but the core author group has not yet been formed;institutional cooperation clusters have appeared, but the cooperation between institutions is still relatively scattered;The research topics focus on three aspects: science and technology evaluation index system, evaluation method and evaluation system.</span> </div>
基金This study was funded by the International Science and Technology Cooperation Program of the Science and Technology Department of Shaanxi Province,China(No.2021KW-16)the Science and Technology Project in Xi’an(No.2019218114GXRC017CG018-GXYD17.11),Thesis work was supported by the special fund construction project of Key Disciplines in Ordinary Colleges and Universities in Shaanxi Province,the authors would like to thank the anonymous reviewers for their helpful comments and suggestions.
文摘Text event mining,as an indispensable method of text mining processing,has attracted the extensive attention of researchers.A modeling method for knowledge graph of events based on mutual information among neighbor domains and sparse representation is proposed in this paper,i.e.UKGE-MS.Specifically,UKGE-MS can improve the existing text mining technology's ability of understanding and discovering high-dimensional unmarked information,and solves the problems of traditional unsupervised feature selection methods,which only focus on selecting features from a global perspective and ignoring the impact of local connection of samples.Firstly,considering the influence of local information of samples in feature correlation evaluation,a feature clustering algorithm based on average neighborhood mutual information is proposed,and the feature clusters with certain event correlation are obtained;Secondly,an unsupervised feature selection method based on the high-order correlation of multi-dimensional statistical data is designed by combining the dimension reduction advantage of local linear embedding algorithm and the feature selection ability of sparse representation,so as to enhance the generalization ability of the selected feature items.Finally,the events knowledge graph is constructed by means of sparse representation and l1 norm.Extensive experiments are carried out on five real datasets and synthetic datasets,and the UKGE-MS are compared with five corresponding algorithms.The experimental results show that UKGE-MS is better than the traditional method in event clustering and feature selection,and has some advantages over other methods in text event recognition and discovery.
文摘The aim of the paper is to identify and explore leading thematic areas within the research field related to Business Schools Accreditation in China.Based on data from the China National Knowledge Infrastructure(CNKI)database,the keywords frequency was analyzed,and the theory of mapping knowledge domain was used to visualize the keywords co-occurrence network to make further research of the heated issues.The findings indicate that the research scope involved in business school accreditation research is broad,and research content focus on teaching,management,talent cultivation.According to the results of keywords co-occurrence analysis of different stages,AACSB,AACSB Accreditation,international accreditation,business school,AOL,internationalization,accreditation are the most important issues to business school research in China,given their position and role in the research network.The paper generates the added value mainly from the point of view of theory development.
文摘In this paper, we will investigate convex domains and starlike domains whichcontain the image set of normalized holomorphic mappings on bounded starlike circulardomains in
基金supported in part by the Key-Area Research and Development Program of Guangdong Province (2020B010166006)the National Natural Science Foundation of China (61972102)+1 种基金the Guangzhou Science and Technology Plan Project (023A04J1729)the Science and Technology development fund (FDCT),Macao SAR (015/2020/AMJ)。
文摘Most existing domain adaptation(DA) methods aim to explore favorable performance under complicated environments by sampling.However,there are three unsolved problems that limit their efficiencies:ⅰ) they adopt global sampling but neglect to exploit global and local sampling simultaneously;ⅱ)they either transfer knowledge from a global perspective or a local perspective,while overlooking transmission of confident knowledge from both perspectives;and ⅲ) they apply repeated sampling during iteration,which takes a lot of time.To address these problems,knowledge transfer learning via dual density sampling(KTL-DDS) is proposed in this study,which consists of three parts:ⅰ) Dual density sampling(DDS) that jointly leverages two sampling methods associated with different views,i.e.,global density sampling that extracts representative samples with the most common features and local density sampling that selects representative samples with critical boundary information;ⅱ)Consistent maximum mean discrepancy(CMMD) that reduces intra-and cross-domain risks and guarantees high consistency of knowledge by shortening the distances of every two subsets among the four subsets collected by DDS;and ⅲ) Knowledge dissemination(KD) that transmits confident and consistent knowledge from the representative target samples with global and local properties to the whole target domain by preserving the neighboring relationships of the target domain.Mathematical analyses show that DDS avoids repeated sampling during the iteration.With the above three actions,confident knowledge with both global and local properties is transferred,and the memory and running time are greatly reduced.In addition,a general framework named dual density sampling approximation(DDSA) is extended,which can be easily applied to other DA algorithms.Extensive experiments on five datasets in clean,label corruption(LC),feature missing(FM),and LC&FM environments demonstrate the encouraging performance of KTL-DDS.
基金This work was supported by the Research Project of Postgraduate Education Reform in Harbin Institute of Technology,Research Project of Postgraduate Education and Teaching Reform in Harbin Institute of Technology(Weihai).
文摘The aim of the paper is to identify and explore leading development situation within the research field related to student classroom engagement.Using knowledge mapping tools,this paper conducted the visualization analysis on internationalliteraturein relation to student classroom engagementfrom the Web of Science databases.By combination of the statistical data and visualizationmapping,this paper studied on the research relationship networks and status for the co-authors'countries/institutions,co-citation documents/journalsand co-occurring keywordsbased on the sample datafromliterature.The results indicate that the number ofpublished papershasincreased obviously and expanded graduallysince 2000.Main countries and institutions of researches were the UnitedStates,Australia,United Kingdom,Canada and China in order,and these countries had intense collaboration.The theoretical basis of the research come from education and teaching,psychology.The hotspots of researches fromthe global literature coveredvarious fields including achievement,motivation,behavior,education,performance.As a result of the multidisciplinary integration,many relevant internationalresearch constantly expanded the research scopes,which promoted the combination and development of theories.
