Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularl...Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularly deep learning(DL),applied and relevant to computational mechanics(solid,fluids,finite-element technology)are reviewed in detail.Both hybrid and pure machine learning(ML)methods are discussed.Hybrid methods combine traditional PDE discretizations with ML methods either(1)to help model complex nonlinear constitutive relations,(2)to nonlinearly reduce the model order for efficient simulation(turbulence),or(3)to accelerate the simulation by predicting certain components in the traditional integration methods.Here,methods(1)and(2)relied on Long-Short-Term Memory(LSTM)architecture,with method(3)relying on convolutional neural networks.Pure ML methods to solve(nonlinear)PDEs are represented by Physics-Informed Neural network(PINN)methods,which could be combined with attention mechanism to address discontinuous solutions.Both LSTM and attention architectures,together with modern and generalized classic optimizers to include stochasticity for DL networks,are extensively reviewed.Kernel machines,including Gaussian processes,are provided to sufficient depth for more advanced works such as shallow networks with infinite width.Not only addressing experts,readers are assumed familiar with computational mechanics,but not with DL,whose concepts and applications are built up from the basics,aiming at bringing first-time learners quickly to the forefront of research.History and limitations of AI are recounted and discussed,with particular attention at pointing out misstatements or misconceptions of the classics,even in well-known references.Positioning and pointing control of a large-deformable beam is given as an example.展开更多
To facilitate users to access the desired information, many researches have dedicated to the Deep Web （i.e. Web databases） integration. We focus on query translation which is an important part of the Deep Web integr...To facilitate users to access the desired information, many researches have dedicated to the Deep Web （i.e. Web databases） integration. We focus on query translation which is an important part of the Deep Web integration. Our aim is to construct automatically a set of constraints mapping rules so that the system can translate the query from the integrated interface to the Web database interfaces based on them. We construct a concept hierarchy for the attributes of the query interfaces, especially, store the synonyms and the types （e.g. Number, Text, etc.） for every concept At the same time, we construct the data hierarchies for some concepts if necessary. Then we present an algorithm to generate the constraint mapping rules based on these hierarchies. The approach is suitable for the scalability of such application and can be extended easily from one domain to another for its domain independent feature. The results of experiment show its effectiveness and efficiency.展开更多
Wearable technologies have the potential to become a valuable influence on human daily life where they may enable observing the world in new ways,including,for example,using augmented reality(AR)applications.Wearable ...Wearable technologies have the potential to become a valuable influence on human daily life where they may enable observing the world in new ways,including,for example,using augmented reality(AR)applications.Wearable technology uses electronic devices that may be carried as accessories,clothes,or even embedded in the user's body.Although the potential benefits of smart wearables are numerous,their extensive and continual usage creates several privacy concerns and tricky information security challenges.In this paper,we present a comprehensive survey of recent privacy-preserving big data analytics applications based on wearable sensors.We highlight the fundamental features of security and privacy for wearable device applications.Then,we examine the utilization of deep learning algorithms with cryptography and determine their usability for wearable sensors.We also present a case study on privacy-preserving machine learning techniques.Herein,we theoretically and empirically evaluate the privacy-preserving deep learning framework's performance.We explain the implementation details of a case study of a secure prediction service using the convolutional neural network(CNN)model and the Cheon-Kim-Kim-Song(CHKS)homomorphic encryption algorithm.Finally,we explore the obstacles and gaps in the deployment of practical real-world applications.Following a comprehensive overview,we identify the most important obstacles that must be overcome and discuss some interesting future research directions.展开更多
The fourth international conference on Web information systems and applications （WISA 2007） has received 409 submissions and has accepted 37 papers for publication in this issue. The papers cover broad research area...The fourth international conference on Web information systems and applications （WISA 2007） has received 409 submissions and has accepted 37 papers for publication in this issue. The papers cover broad research areas, including Web mining and data warehouse, Deep Web and Web integration, P2P networks, text processing and information retrieval, as well as Web Services and Web infrastructure. After briefly introducing the WISA conference, the survey outlines the current activities and future trends concerning Web information systems and applications based on the papers accepted for publication.展开更多
分析了常见的实体识别方法,提出了一种基于语义及统计分析的实体识别机制(deep Web entity identification mechanism based on semantics and statistical analysis,简称SS-EIM),能够有效解决Deep Web数据集成中数据纠错、消重及整合...分析了常见的实体识别方法,提出了一种基于语义及统计分析的实体识别机制(deep Web entity identification mechanism based on semantics and statistical analysis,简称SS-EIM),能够有效解决Deep Web数据集成中数据纠错、消重及整合等问题.SS-EIM主要由文本匹配模型、语义分析模型和分组统计模型组成,采用文本粗略匹配、表象关联关系获取以及分组统计分析的三段式逐步求精策略,基于文本特征、语义信息及约束规则来不断精化识别结果;根据可获取的有限的实例信息,采用静态分析、动态协调相结合的自适应知识维护策略,构建和完善表象关联知识库,以适应Web数据的动态性并保证表象关联知识的完备性.通过实验验证了SS-EIM中所采用的关键技术的可行性和有效性.展开更多
应急预案是应急管理的纲领性文件,为应对频发的突发事件,各应急相关部门都建立了自己的应急预案数据库。但这些数据库存在诸多不同程度的异构,阻碍了部门之间的信息共享。针对应急预案异构数据集成,采用本体及本体映射方法解决语义异构...应急预案是应急管理的纲领性文件,为应对频发的突发事件,各应急相关部门都建立了自己的应急预案数据库。但这些数据库存在诸多不同程度的异构,阻碍了部门之间的信息共享。针对应急预案异构数据集成,采用本体及本体映射方法解决语义异构的智能识别,以Tomcat+MyEclipse+SQL Server 2005作为开发环境,研究开发物化式Deep Web应急预案异构数据源的集成系统EPIS,创建应急预案中心数据库,为应急预案领域信息共享与应急预案的管理提供基础平台。展开更多
文摘Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularly deep learning(DL),applied and relevant to computational mechanics(solid,fluids,finite-element technology)are reviewed in detail.Both hybrid and pure machine learning(ML)methods are discussed.Hybrid methods combine traditional PDE discretizations with ML methods either(1)to help model complex nonlinear constitutive relations,(2)to nonlinearly reduce the model order for efficient simulation(turbulence),or(3)to accelerate the simulation by predicting certain components in the traditional integration methods.Here,methods(1)and(2)relied on Long-Short-Term Memory(LSTM)architecture,with method(3)relying on convolutional neural networks.Pure ML methods to solve(nonlinear)PDEs are represented by Physics-Informed Neural network(PINN)methods,which could be combined with attention mechanism to address discontinuous solutions.Both LSTM and attention architectures,together with modern and generalized classic optimizers to include stochasticity for DL networks,are extensively reviewed.Kernel machines,including Gaussian processes,are provided to sufficient depth for more advanced works such as shallow networks with infinite width.Not only addressing experts,readers are assumed familiar with computational mechanics,but not with DL,whose concepts and applications are built up from the basics,aiming at bringing first-time learners quickly to the forefront of research.History and limitations of AI are recounted and discussed,with particular attention at pointing out misstatements or misconceptions of the classics,even in well-known references.Positioning and pointing control of a large-deformable beam is given as an example.
基金Supported by the National Natural Science Foundation of China (60573091)the Natural Science Foundation of Beijing(4073035)the Key Project of Ministry of Education of China (03044)
文摘To facilitate users to access the desired information, many researches have dedicated to the Deep Web （i.e. Web databases） integration. We focus on query translation which is an important part of the Deep Web integration. Our aim is to construct automatically a set of constraints mapping rules so that the system can translate the query from the integrated interface to the Web database interfaces based on them. We construct a concept hierarchy for the attributes of the query interfaces, especially, store the synonyms and the types （e.g. Number, Text, etc.） for every concept At the same time, we construct the data hierarchies for some concepts if necessary. Then we present an algorithm to generate the constraint mapping rules based on these hierarchies. The approach is suitable for the scalability of such application and can be extended easily from one domain to another for its domain independent feature. The results of experiment show its effectiveness and efficiency.
文摘Wearable technologies have the potential to become a valuable influence on human daily life where they may enable observing the world in new ways,including,for example,using augmented reality(AR)applications.Wearable technology uses electronic devices that may be carried as accessories,clothes,or even embedded in the user's body.Although the potential benefits of smart wearables are numerous,their extensive and continual usage creates several privacy concerns and tricky information security challenges.In this paper,we present a comprehensive survey of recent privacy-preserving big data analytics applications based on wearable sensors.We highlight the fundamental features of security and privacy for wearable device applications.Then,we examine the utilization of deep learning algorithms with cryptography and determine their usability for wearable sensors.We also present a case study on privacy-preserving machine learning techniques.Herein,we theoretically and empirically evaluate the privacy-preserving deep learning framework's performance.We explain the implementation details of a case study of a secure prediction service using the convolutional neural network(CNN)model and the Cheon-Kim-Kim-Song(CHKS)homomorphic encryption algorithm.Finally,we explore the obstacles and gaps in the deployment of practical real-world applications.Following a comprehensive overview,we identify the most important obstacles that must be overcome and discuss some interesting future research directions.
文摘The fourth international conference on Web information systems and applications （WISA 2007） has received 409 submissions and has accepted 37 papers for publication in this issue. The papers cover broad research areas, including Web mining and data warehouse, Deep Web and Web integration, P2P networks, text processing and information retrieval, as well as Web Services and Web infrastructure. After briefly introducing the WISA conference, the survey outlines the current activities and future trends concerning Web information systems and applications based on the papers accepted for publication.
基金Supported by the National Natural Science Foundation of China under Grant No.60673139 (国家自然科学基金)
文摘分析了常见的实体识别方法,提出了一种基于语义及统计分析的实体识别机制(deep Web entity identification mechanism based on semantics and statistical analysis,简称SS-EIM),能够有效解决Deep Web数据集成中数据纠错、消重及整合等问题.SS-EIM主要由文本匹配模型、语义分析模型和分组统计模型组成,采用文本粗略匹配、表象关联关系获取以及分组统计分析的三段式逐步求精策略,基于文本特征、语义信息及约束规则来不断精化识别结果;根据可获取的有限的实例信息,采用静态分析、动态协调相结合的自适应知识维护策略,构建和完善表象关联知识库,以适应Web数据的动态性并保证表象关联知识的完备性.通过实验验证了SS-EIM中所采用的关键技术的可行性和有效性.
文摘应急预案是应急管理的纲领性文件,为应对频发的突发事件,各应急相关部门都建立了自己的应急预案数据库。但这些数据库存在诸多不同程度的异构,阻碍了部门之间的信息共享。针对应急预案异构数据集成,采用本体及本体映射方法解决语义异构的智能识别,以Tomcat+MyEclipse+SQL Server 2005作为开发环境,研究开发物化式Deep Web应急预案异构数据源的集成系统EPIS,创建应急预案中心数据库,为应急预案领域信息共享与应急预案的管理提供基础平台。
