Purpose:Citations can be used in evaluative bibliometrics to measure the impact of papers.However,citation analysis can be extended by a multi-dimensional perspective on citation impact which is intended to receive mo...Purpose:Citations can be used in evaluative bibliometrics to measure the impact of papers.However,citation analysis can be extended by a multi-dimensional perspective on citation impact which is intended to receive more specific information about the kind of received impact.Design/methodology/approach:Bornmann,Wray,and Haunschild(2019)introduced citation concept analysis(CCA)for capturing the importance and usefulness certain concepts have in subsequent research.The method is based on the analysis of citances-the contexts of citations in citing papers.This study applies the method by investigating the impact of various concepts introduced in the oeuvre of the world-leading French sociologist Pierre Bourdieu.Findings:We found that the most cited concepts are‘social capital’(with about 34%of the citances in the citing papers),‘cultural capital’,and‘habitus’(both with about 24%).On the other hand,the concepts‘doxa’and‘reflexivity’score only about 1%each.Research limitations:The formulation of search terms for identifying the concepts in the data and the citation context coverage are the most important limitations of the study.Practical implications:The results of this explorative study reflect the historical development of Bourdieu’s thought and its interface with different fields of study.Originality/value:The study demonstrates the high explanatory power of the CCA method.展开更多
Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based ...Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation tasks.In order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian components.Then,the obtained information about non-Gaussian components can be used to whiten the array data.Based on these considerations,a novel practical sonar array whitening method was proposed.Specifically,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array data.With the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation tasks.Experimental results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.展开更多
文摘在缺乏先验信息的复杂电磁环境中,传统的监督型算法难以满足战场的即时性需求,雷达辐射源个体的精确识别任务面临显著挑战。为此,提出了一种在全盲标签条件下,采用基于典型相关分析(canonical correlation analysis,CCA)的多域特征融合技术和相关系数的特征选取方法,并结合自适应基于密度的带噪声空间聚类算法(density-based spatial clustering of applications with noise,DBSCAN)实现雷达辐射源个体的盲聚类。鉴于不同特征在时域结构上存在的显著差异,采取时域对齐方法处理雷达信号的包络上升沿,进而从对齐后的信号中提取多维度的时域及时频域特征。针对多域特征在空间结构上的差异性,提出了一种基于相关系数的特征选取策略,以优化后续处理流程。为了有效发挥CCA算法在多域互补特征融合的作用,进而突出多域互补特征在基于数据密度类聚类算法的适应性,在后端引入了DBSCAN聚类算法。鉴于无监督聚类算法DBSCAN对参数设置的敏感性,引入了一种自适应参数优化方法,以实现聚类效果的最优化。最后,实验验证了所提融合特征盲聚类方法的有效性。
文摘Purpose:Citations can be used in evaluative bibliometrics to measure the impact of papers.However,citation analysis can be extended by a multi-dimensional perspective on citation impact which is intended to receive more specific information about the kind of received impact.Design/methodology/approach:Bornmann,Wray,and Haunschild(2019)introduced citation concept analysis(CCA)for capturing the importance and usefulness certain concepts have in subsequent research.The method is based on the analysis of citances-the contexts of citations in citing papers.This study applies the method by investigating the impact of various concepts introduced in the oeuvre of the world-leading French sociologist Pierre Bourdieu.Findings:We found that the most cited concepts are‘social capital’(with about 34%of the citances in the citing papers),‘cultural capital’,and‘habitus’(both with about 24%).On the other hand,the concepts‘doxa’and‘reflexivity’score only about 1%each.Research limitations:The formulation of search terms for identifying the concepts in the data and the citation context coverage are the most important limitations of the study.Practical implications:The results of this explorative study reflect the historical development of Bourdieu’s thought and its interface with different fields of study.Originality/value:The study demonstrates the high explanatory power of the CCA method.
基金supported by the National Natural Science Foundation of China(No.51279033).
文摘Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation tasks.In order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian components.Then,the obtained information about non-Gaussian components can be used to whiten the array data.Based on these considerations,a novel practical sonar array whitening method was proposed.Specifically,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array data.With the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation tasks.Experimental results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.
