Purpose–The purpose of this study is to study the quantitative evaluation method of contact wire cracks by analyzing the changing law of eddy current signal characteristics under different cracks of contact wire of h...Purpose–The purpose of this study is to study the quantitative evaluation method of contact wire cracks by analyzing the changing law of eddy current signal characteristics under different cracks of contact wire of high-speed railway so as to provide a new way of thinking and method for the detection of contact wire injuries of high-speed railway.Design/methodology/approach–Based on the principle of eddy current detection and the specification parameters of high-speed railway contact wires in China,a finite element model for eddy current testing of contact wires was established to explore the variation patterns of crack signal characteristics in numerical simulation.A crack detection system based on eddy current detection was built,and eddy current detection voltage data was obtained for cracks of different depths and widths.By analyzing the variation law of eddy current signals,characteristic parameters were obtained and a quantitative evaluation model for crack width and depth was established based on the back propagation(BP)neural network.Findings–Numerical simulation and experimental detection of eddy current signal change rule is basically consistent,based on the law of the selected characteristics of the parameters in the BP neural network crack quantitative evaluation model also has a certain degree of effectiveness and reliability.BP neural network training results show that the classification accuracy for different widths and depths of the classification is 100 and 85.71%,respectively,and can be effectively realized on the high-speed railway contact line cracks of the quantitative evaluation classification.Originality/value–This study establishes a new type of high-speed railway contact wire crack detection and identification method,which provides a new technical means for high-speed railway contact wire injury detection.The study of eddy current characteristic law and quantitative evaluation model for different cracks in contact line has important academic value and practical significance,and it has certain guiding significance for the detection technology of contact line in high-speed railway.展开更多
Conference Theme Advanced Technologies for Emergency Planning and ResponseThe 2008 IEEE International Conference on Networking, Sensing and Control will be held in Sanya,China. The main theme of the conference is adva...Conference Theme Advanced Technologies for Emergency Planning and ResponseThe 2008 IEEE International Conference on Networking, Sensing and Control will be held in Sanya,China. The main theme of the conference is advanced technologies for emergency planning and re-展开更多
We search a variety of things over the Internet in our daily lives, and numerous search engines are available to get us more relevant results. With the rapid technological advancement, the internet has become a major ...We search a variety of things over the Internet in our daily lives, and numerous search engines are available to get us more relevant results. With the rapid technological advancement, the internet has become a major source of obtaining information. Further, the advent of the Web2.0 era has led to an increased interaction between the user and the website. It has become challenging to provide information to users as per their interests. Because of copyright restrictions, most of existing research studies are confronting the lack of availability of the content of candidates recommending articles. The content of such articles is not always available freely and hence leads to inadequate recommendation results. Moreover, various research studies base recommendation on user profiles. Therefore, their recommendation needs a significant number of registered users in the system. In recent years, research work proves that Knowledge graphs have yielded better in generating quality recommendation results and alleviating sparsity and cold start issues. Network embedding techniques try to learn high quality feature vectors automatically from network structures, enabling vector-based measurers of node relatedness. Keeping the strength of Network embedding techniques, the proposed citation-based recommendation approach makes use of heterogeneous network embedding in generating recommendation results. The novelty of this paper is in exploiting the performance of a network embedding approach i.e., matapath2vec to generate paper recommendations. Unlike existing approaches, the proposed method has the capability of learning low-dimensional latent representation of nodes (i.e., research papers) in a network. We apply metapath2vec on a knowledge network built by the ACL Anthology Network (all about NLP) and use the node relatedness to generate item (research article) recommendations.展开更多
目的:分析全球类器官领域的科研竞争与合作态势。方法:2024年1月,在Web of Science中检索类器官相关论文,通过共被引分析、文献计量学分析和社会网络分析识别研究热点以及领先国家、机构和研究者。结果:1990年至今,全球类器官领域科技...目的:分析全球类器官领域的科研竞争与合作态势。方法:2024年1月,在Web of Science中检索类器官相关论文,通过共被引分析、文献计量学分析和社会网络分析识别研究热点以及领先国家、机构和研究者。结果:1990年至今,全球类器官领域科技论文共计10477篇,其中2018年至今占82.4%,研究集中在肿瘤、肝肾、肠道上皮、人脑和视网膜等类器官的构建。美国发文最多(4632篇),且合作对象数量(75个)和次数(3405次)也最多。中国发文量居第2位(1970篇),但合作对象数量(54个)和次数(1194次)远少于美国。机构层面,哈佛大学的发文量(534篇)、合作对象数量(347个)和次数(1495次)均领先,来自美国之外的中国科学院、荷兰乌特勒支大学、英国剑桥大学、德国癌症研究中心等也有较高的合作排名。荷兰Hans Clevers教授发文最多,我国秦建华团队和华国强团队发文较多。结论:类器官领域在过去10年间快速发展,众多研究集中在肿瘤、肝脏、肠道、脑和视网膜等类器官的构建。美国绝对领先,中国也是国际合作的重要参与者。哈佛大学实力突出,是全球合作中心,来自中国、荷兰、英国、德国的个别机构则是各自区域的中心。展开更多
Purpose–Traffic density is one of the most important parameters to consider in the traffic operationfield.Owing to limited data sources,traditional methods cannot extract traffic density directly.In the vehicular ad hoc ...Purpose–Traffic density is one of the most important parameters to consider in the traffic operationfield.Owing to limited data sources,traditional methods cannot extract traffic density directly.In the vehicular ad hoc network(VANET)environment,the vehicle-to-vehicle(V2V)and vehicle-to-infrastructure(V2I)interaction technologies create better conditions for collecting the whole time-space and refined traffic data,which provides a new approach to solving this problem.Design/methodology/approach–On that basis,a real-time traffic density extraction method has been proposed,including lane density,segment density and network density.Meanwhile,using SUMO and OMNet11 as traffic simulator and network simulator,respectively,the Veins framework as middleware and the two-way coupling VANET simulation platform was constructed.Findings–Based on the simulation platform,a simulated intersection in Shanghai was developed to investigate the adaptability of the model.Originality/value–Most research studies use separate simulation methods,importing trace data obtained by using from the simulation software to the communication simulation software.In this paper,the tight coupling simulation method is applied.Using real-time data and history data,the research focuses on the establishment and validation of the traffic density extraction model.展开更多
为满足情报学科研人员对跨学科论文的需求,本文构建了基于学术网络的跨学科论文推荐模型。首先,根据论文关键词耦合网络及作者对论文的引用网络特征,挖掘作者与论文的相关性,实现基于关键词耦合的论文推荐;其次,利用作者引文耦合网络特...为满足情报学科研人员对跨学科论文的需求,本文构建了基于学术网络的跨学科论文推荐模型。首先,根据论文关键词耦合网络及作者对论文的引用网络特征,挖掘作者与论文的相关性,实现基于关键词耦合的论文推荐;其次,利用作者引文耦合网络特征及作者跨学科引用关系、论文共被引关系与论文的学科属性,分别挖掘作者与论文的跨学科性,并计算跨学科性相似度,实现基于学科相似性的论文推荐;最后,结合基于关键词耦合的论文推荐和基于学科相似性的论文推荐,实现跨学科论文混合推荐。以CSSCI(Chinese Social Sciences Citation Index)数据库中的数据对模型进行验证,实证结果表明,本文提出的推荐模型推荐结果具备跨学科性;与基于关键词耦合的论文推荐方法相比,结合跨学科特征后在作者推荐成功率、平均准确率和平均召回率上均有提高。展开更多
AIzheimer＇s disease patients diagnosed with the Chinese Classification of Mental Disorders diagnostic criteria were selected from the community through on-site sampling. Levels of macro and trace elements were measur...AIzheimer＇s disease patients diagnosed with the Chinese Classification of Mental Disorders diagnostic criteria were selected from the community through on-site sampling. Levels of macro and trace elements were measured in blood samples using an atomic absorption method, and neurotransmitters were measured using a radioimmunoassay method. SPSS 13.0 was used to establish a database, and a back propagation artificial neural network for Alzheimer＇s disease prediction was simulated using Clementine 12.0 software. With scores of activities of daily living, creatinine, 5-hydroxytryptamine, age, dopamine and aluminum as input variables, the results revealed that the area under the curve in our back propagation artificial neural network was 0.929 （95% confidence interval： 0.868-0.968）, sensitivity was 90.00%, specificity was 95.00%, and accuracy was 92.50%. The findings indicated that the results of back propagation artificial neural network established based on the above six variables were satisfactory for screening and diagnosis of Alzheimer＇s disease in patients selected from the community.展开更多
工业控制系统通常应用于化工、电力和造纸等诸多行业。随着信息技术的不断升级和工业控制系统的逐步完善,企业工控网络的安全越来越受重视。基于此,简述了造纸企业工控网络所存在的种种安全隐患,重点基于深度学习算法,结合异常流量检测...工业控制系统通常应用于化工、电力和造纸等诸多行业。随着信息技术的不断升级和工业控制系统的逐步完善,企业工控网络的安全越来越受重视。基于此,简述了造纸企业工控网络所存在的种种安全隐患,重点基于深度学习算法,结合异常流量检测对造纸企业工控网络的安全管理问题展开研究,提出一种多尺度跳跃激励网络结构对卷积神经网络进行优化,构建了工控网络安全管理模型,并使用KDD CUP 99数据集进行试验验证,该模型能够对工控网络中的异常流量进行深度检测,且准确率比普通模型更高。展开更多
文摘Purpose–The purpose of this study is to study the quantitative evaluation method of contact wire cracks by analyzing the changing law of eddy current signal characteristics under different cracks of contact wire of high-speed railway so as to provide a new way of thinking and method for the detection of contact wire injuries of high-speed railway.Design/methodology/approach–Based on the principle of eddy current detection and the specification parameters of high-speed railway contact wires in China,a finite element model for eddy current testing of contact wires was established to explore the variation patterns of crack signal characteristics in numerical simulation.A crack detection system based on eddy current detection was built,and eddy current detection voltage data was obtained for cracks of different depths and widths.By analyzing the variation law of eddy current signals,characteristic parameters were obtained and a quantitative evaluation model for crack width and depth was established based on the back propagation(BP)neural network.Findings–Numerical simulation and experimental detection of eddy current signal change rule is basically consistent,based on the law of the selected characteristics of the parameters in the BP neural network crack quantitative evaluation model also has a certain degree of effectiveness and reliability.BP neural network training results show that the classification accuracy for different widths and depths of the classification is 100 and 85.71%,respectively,and can be effectively realized on the high-speed railway contact line cracks of the quantitative evaluation classification.Originality/value–This study establishes a new type of high-speed railway contact wire crack detection and identification method,which provides a new technical means for high-speed railway contact wire injury detection.The study of eddy current characteristic law and quantitative evaluation model for different cracks in contact line has important academic value and practical significance,and it has certain guiding significance for the detection technology of contact line in high-speed railway.
文摘Conference Theme Advanced Technologies for Emergency Planning and ResponseThe 2008 IEEE International Conference on Networking, Sensing and Control will be held in Sanya,China. The main theme of the conference is advanced technologies for emergency planning and re-
文摘We search a variety of things over the Internet in our daily lives, and numerous search engines are available to get us more relevant results. With the rapid technological advancement, the internet has become a major source of obtaining information. Further, the advent of the Web2.0 era has led to an increased interaction between the user and the website. It has become challenging to provide information to users as per their interests. Because of copyright restrictions, most of existing research studies are confronting the lack of availability of the content of candidates recommending articles. The content of such articles is not always available freely and hence leads to inadequate recommendation results. Moreover, various research studies base recommendation on user profiles. Therefore, their recommendation needs a significant number of registered users in the system. In recent years, research work proves that Knowledge graphs have yielded better in generating quality recommendation results and alleviating sparsity and cold start issues. Network embedding techniques try to learn high quality feature vectors automatically from network structures, enabling vector-based measurers of node relatedness. Keeping the strength of Network embedding techniques, the proposed citation-based recommendation approach makes use of heterogeneous network embedding in generating recommendation results. The novelty of this paper is in exploiting the performance of a network embedding approach i.e., matapath2vec to generate paper recommendations. Unlike existing approaches, the proposed method has the capability of learning low-dimensional latent representation of nodes (i.e., research papers) in a network. We apply metapath2vec on a knowledge network built by the ACL Anthology Network (all about NLP) and use the node relatedness to generate item (research article) recommendations.
文摘目的:分析全球类器官领域的科研竞争与合作态势。方法:2024年1月,在Web of Science中检索类器官相关论文,通过共被引分析、文献计量学分析和社会网络分析识别研究热点以及领先国家、机构和研究者。结果:1990年至今,全球类器官领域科技论文共计10477篇,其中2018年至今占82.4%,研究集中在肿瘤、肝肾、肠道上皮、人脑和视网膜等类器官的构建。美国发文最多(4632篇),且合作对象数量(75个)和次数(3405次)也最多。中国发文量居第2位(1970篇),但合作对象数量(54个)和次数(1194次)远少于美国。机构层面,哈佛大学的发文量(534篇)、合作对象数量(347个)和次数(1495次)均领先,来自美国之外的中国科学院、荷兰乌特勒支大学、英国剑桥大学、德国癌症研究中心等也有较高的合作排名。荷兰Hans Clevers教授发文最多,我国秦建华团队和华国强团队发文较多。结论:类器官领域在过去10年间快速发展,众多研究集中在肿瘤、肝脏、肠道、脑和视网膜等类器官的构建。美国绝对领先,中国也是国际合作的重要参与者。哈佛大学实力突出,是全球合作中心,来自中国、荷兰、英国、德国的个别机构则是各自区域的中心。
文摘Purpose–Traffic density is one of the most important parameters to consider in the traffic operationfield.Owing to limited data sources,traditional methods cannot extract traffic density directly.In the vehicular ad hoc network(VANET)environment,the vehicle-to-vehicle(V2V)and vehicle-to-infrastructure(V2I)interaction technologies create better conditions for collecting the whole time-space and refined traffic data,which provides a new approach to solving this problem.Design/methodology/approach–On that basis,a real-time traffic density extraction method has been proposed,including lane density,segment density and network density.Meanwhile,using SUMO and OMNet11 as traffic simulator and network simulator,respectively,the Veins framework as middleware and the two-way coupling VANET simulation platform was constructed.Findings–Based on the simulation platform,a simulated intersection in Shanghai was developed to investigate the adaptability of the model.Originality/value–Most research studies use separate simulation methods,importing trace data obtained by using from the simulation software to the communication simulation software.In this paper,the tight coupling simulation method is applied.Using real-time data and history data,the research focuses on the establishment and validation of the traffic density extraction model.
文摘为满足情报学科研人员对跨学科论文的需求,本文构建了基于学术网络的跨学科论文推荐模型。首先,根据论文关键词耦合网络及作者对论文的引用网络特征,挖掘作者与论文的相关性,实现基于关键词耦合的论文推荐;其次,利用作者引文耦合网络特征及作者跨学科引用关系、论文共被引关系与论文的学科属性,分别挖掘作者与论文的跨学科性,并计算跨学科性相似度,实现基于学科相似性的论文推荐;最后,结合基于关键词耦合的论文推荐和基于学科相似性的论文推荐,实现跨学科论文混合推荐。以CSSCI(Chinese Social Sciences Citation Index)数据库中的数据对模型进行验证,实证结果表明,本文提出的推荐模型推荐结果具备跨学科性;与基于关键词耦合的论文推荐方法相比,结合跨学科特征后在作者推荐成功率、平均准确率和平均召回率上均有提高。
基金supported by the National Natural Science Foundation of China,No.30760214
文摘AIzheimer＇s disease patients diagnosed with the Chinese Classification of Mental Disorders diagnostic criteria were selected from the community through on-site sampling. Levels of macro and trace elements were measured in blood samples using an atomic absorption method, and neurotransmitters were measured using a radioimmunoassay method. SPSS 13.0 was used to establish a database, and a back propagation artificial neural network for Alzheimer＇s disease prediction was simulated using Clementine 12.0 software. With scores of activities of daily living, creatinine, 5-hydroxytryptamine, age, dopamine and aluminum as input variables, the results revealed that the area under the curve in our back propagation artificial neural network was 0.929 （95% confidence interval： 0.868-0.968）, sensitivity was 90.00%, specificity was 95.00%, and accuracy was 92.50%. The findings indicated that the results of back propagation artificial neural network established based on the above six variables were satisfactory for screening and diagnosis of Alzheimer＇s disease in patients selected from the community.
文摘工业控制系统通常应用于化工、电力和造纸等诸多行业。随着信息技术的不断升级和工业控制系统的逐步完善,企业工控网络的安全越来越受重视。基于此,简述了造纸企业工控网络所存在的种种安全隐患,重点基于深度学习算法,结合异常流量检测对造纸企业工控网络的安全管理问题展开研究,提出一种多尺度跳跃激励网络结构对卷积神经网络进行优化,构建了工控网络安全管理模型,并使用KDD CUP 99数据集进行试验验证,该模型能够对工控网络中的异常流量进行深度检测,且准确率比普通模型更高。
