Characterizing the subsurface structure is an important parameter for the improvement of seismic hazard assessment.Due to the tectonic complexity of the earth,some deep fractures do not reach the earth's surface a...Characterizing the subsurface structure is an important parameter for the improvement of seismic hazard assessment.Due to the tectonic complexity of the earth,some deep fractures do not reach the earth's surface and are not detectable with visual analysis.Therefore,the lack of knowledge of faults and fractures can result in disasters,especially in urban planning.Many geophysical methods can be used to estimate subsurface structure characterization.However,a more reliable method is required to assess seismic hazards and reduce potential damage in metropolitan areas without destroying buildings and structures.This paper aims to identify hidden faults and structures using shear wave velocity sections.To do this,surface wave dispersion curve was extracted from the vertical component of microtremor array recording using the spatial autocorrelation(SPAC)method in two profiles and 13 array stations(perpendicular to the altitudes)to obtain shear wave velocity structure(Vs)in the west of Mashhad,northeast of Iran.The results of shear wave velocity profiles(Vs)indicate sudden changes in the thickness of sediments.This can be related to the displacement of a normal fault in this area causing the bottom rock to fall and an increase in the alluvial thickness in the central part of the plain.The velocity in the floor rock is 2000 meters per second in this area.According to the surface outcrops and water wells data,its material is slate and Phyllite metamorphic rocks that are exposed in the adjacent heights.Besides,the seismic profile results were well consistent with electrical resistance data and well logs indicating that the tool array method is flexible,non-invasive,relatively fast,and effective for urban areas with satisfactory accuracy.展开更多
MicroRNAs( miRNAs) are reported to be associated with various diseases. The identification of disease-related miRNAs would be beneficial to the disease diagnosis and prognosis. However,in contrast with the widely avai...MicroRNAs( miRNAs) are reported to be associated with various diseases. The identification of disease-related miRNAs would be beneficial to the disease diagnosis and prognosis. However,in contrast with the widely available expression profiling, the limited knowledge of molecular function restrict the development of previous methods based on network similarity measure. To construct reliable training data,the decision fusion method is used to prioritize the results of existing methods. After that,the performance of decision fusion method is validated. Furthermore,in consideration of the long range dependencies of successive expression values,Hidden Conditional Random Field model( HCRF) is selected and applied to miRNA expression profiling to infer disease-associated miRNAs. The results show that HCRF achieves superior performance and outperforms the previous methods. The results also demonstrate the power of using expression profiling for discovering disease-associated miRNAs.展开更多
To solve the problem that traditional pull based information service can’t meet the demand of long term users getting domain information timely and properly, an adaptive and active computing paradigm (AACP) for per...To solve the problem that traditional pull based information service can’t meet the demand of long term users getting domain information timely and properly, an adaptive and active computing paradigm (AACP) for personalized information service in heterogeneous environment is proposed to provide user centered, push based higsh quality information service timely in a proper way, the motivation of which is generalized as R 4 Service: the right information at the right time in the right way to the right person, upon which formalized algorithms framework of adaptive user profile management, incremental information retrieval, information filtering, and active delivery mechanism are discussed in details. The AACP paradigm serves users in a push based, event driven, interest related, adaptive and active information service mode, which is useful and promising for long term user to gain fresh information instead of polling from kinds of information sources.展开更多
In this letter, we briefly describe a program of self adapting hidden Markov model (SA HMM) and its application in multiple sequences alignment. Program consists of two stage optimisation algorithm.
在决策任务中,团队由于拥有来自不同成员的多样信息,因此通常被认为能够较个体做出更高质量的决策。但大量的研究结果表明,团队对于信息的利用并非十分有效,表现在团队会更多地讨论所有成员都拥有的信息(即共享信息),而相对忽视了每个...在决策任务中,团队由于拥有来自不同成员的多样信息,因此通常被认为能够较个体做出更高质量的决策。但大量的研究结果表明,团队对于信息的利用并非十分有效,表现在团队会更多地讨论所有成员都拥有的信息(即共享信息),而相对忽视了每个成员所独有的信息(即非共享信息),这种现象被称为"共享信息偏差(Shared information bias)"(Stasser&Titus,1985)。共享信息偏差的存在阻碍了团队获取更高质量的决策结果。本文基于隐藏文档范式,针对共享信息偏差的产生原因,分别介绍了信息取样模型、动态信息取样模型、相互提升效应、偏好效应这4种解释机制,并归纳总结了信息分布、团队任务特征、成员特征及动机因素这4类影响因素的作用。最后,从结合团队认知、探究情绪因素及整合团队有效性框架这三个方面对未来的研究进行了展望。展开更多
行为画像技术利用无标注历史数据构建用户行为"常态",是检测企业内部威胁的有效手段。当前标签式画像方法依赖人工提取特征,多用简单统计方法处理数据,导致用户画像模型缺少细节、不够全面。提出了一种行为特征自动提取和局...行为画像技术利用无标注历史数据构建用户行为"常态",是检测企业内部威胁的有效手段。当前标签式画像方法依赖人工提取特征,多用简单统计方法处理数据,导致用户画像模型缺少细节、不够全面。提出了一种行为特征自动提取和局部全细节行为画像方法,以及一种行为序列划分和全局业务状态转移预测方法,能够较全面地刻画用户行为模式。构建了一个基于行为画像的内部威胁检测框架,将局部描写与全局预测相结合,提高了检测准确率。最后用CMU-CERT数据集进行了实验,AUC(area under curve)得分0.88,F1得分0.925,可有效应用于内部威胁检测过程中。展开更多
文摘Characterizing the subsurface structure is an important parameter for the improvement of seismic hazard assessment.Due to the tectonic complexity of the earth,some deep fractures do not reach the earth's surface and are not detectable with visual analysis.Therefore,the lack of knowledge of faults and fractures can result in disasters,especially in urban planning.Many geophysical methods can be used to estimate subsurface structure characterization.However,a more reliable method is required to assess seismic hazards and reduce potential damage in metropolitan areas without destroying buildings and structures.This paper aims to identify hidden faults and structures using shear wave velocity sections.To do this,surface wave dispersion curve was extracted from the vertical component of microtremor array recording using the spatial autocorrelation(SPAC)method in two profiles and 13 array stations(perpendicular to the altitudes)to obtain shear wave velocity structure(Vs)in the west of Mashhad,northeast of Iran.The results of shear wave velocity profiles(Vs)indicate sudden changes in the thickness of sediments.This can be related to the displacement of a normal fault in this area causing the bottom rock to fall and an increase in the alluvial thickness in the central part of the plain.The velocity in the floor rock is 2000 meters per second in this area.According to the surface outcrops and water wells data,its material is slate and Phyllite metamorphic rocks that are exposed in the adjacent heights.Besides,the seismic profile results were well consistent with electrical resistance data and well logs indicating that the tool array method is flexible,non-invasive,relatively fast,and effective for urban areas with satisfactory accuracy.
基金Sponsored by the National Natural Science Foundation of China(Grant Nos.61271346,61571163,61532014,61402132 and 91335112)
文摘MicroRNAs( miRNAs) are reported to be associated with various diseases. The identification of disease-related miRNAs would be beneficial to the disease diagnosis and prognosis. However,in contrast with the widely available expression profiling, the limited knowledge of molecular function restrict the development of previous methods based on network similarity measure. To construct reliable training data,the decision fusion method is used to prioritize the results of existing methods. After that,the performance of decision fusion method is validated. Furthermore,in consideration of the long range dependencies of successive expression values,Hidden Conditional Random Field model( HCRF) is selected and applied to miRNA expression profiling to infer disease-associated miRNAs. The results show that HCRF achieves superior performance and outperforms the previous methods. The results also demonstrate the power of using expression profiling for discovering disease-associated miRNAs.
文摘To solve the problem that traditional pull based information service can’t meet the demand of long term users getting domain information timely and properly, an adaptive and active computing paradigm (AACP) for personalized information service in heterogeneous environment is proposed to provide user centered, push based higsh quality information service timely in a proper way, the motivation of which is generalized as R 4 Service: the right information at the right time in the right way to the right person, upon which formalized algorithms framework of adaptive user profile management, incremental information retrieval, information filtering, and active delivery mechanism are discussed in details. The AACP paradigm serves users in a push based, event driven, interest related, adaptive and active information service mode, which is useful and promising for long term user to gain fresh information instead of polling from kinds of information sources.
文摘In this letter, we briefly describe a program of self adapting hidden Markov model (SA HMM) and its application in multiple sequences alignment. Program consists of two stage optimisation algorithm.
文摘在决策任务中,团队由于拥有来自不同成员的多样信息,因此通常被认为能够较个体做出更高质量的决策。但大量的研究结果表明,团队对于信息的利用并非十分有效,表现在团队会更多地讨论所有成员都拥有的信息(即共享信息),而相对忽视了每个成员所独有的信息(即非共享信息),这种现象被称为"共享信息偏差(Shared information bias)"(Stasser&Titus,1985)。共享信息偏差的存在阻碍了团队获取更高质量的决策结果。本文基于隐藏文档范式,针对共享信息偏差的产生原因,分别介绍了信息取样模型、动态信息取样模型、相互提升效应、偏好效应这4种解释机制,并归纳总结了信息分布、团队任务特征、成员特征及动机因素这4类影响因素的作用。最后,从结合团队认知、探究情绪因素及整合团队有效性框架这三个方面对未来的研究进行了展望。
文摘行为画像技术利用无标注历史数据构建用户行为"常态",是检测企业内部威胁的有效手段。当前标签式画像方法依赖人工提取特征,多用简单统计方法处理数据,导致用户画像模型缺少细节、不够全面。提出了一种行为特征自动提取和局部全细节行为画像方法,以及一种行为序列划分和全局业务状态转移预测方法,能够较全面地刻画用户行为模式。构建了一个基于行为画像的内部威胁检测框架,将局部描写与全局预测相结合,提高了检测准确率。最后用CMU-CERT数据集进行了实验,AUC(area under curve)得分0.88,F1得分0.925,可有效应用于内部威胁检测过程中。
