AvesTerra is a distributed knowledge representation framework for integrating many large and disparate data systems and analytic components at global scale. this framework allows data created or curated by many differ...
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ISBN:
(纸本)9781450384049
AvesTerra is a distributed knowledge representation framework for integrating many large and disparate data systems and analytic components at global scale. this framework allows data created or curated by many different institutions to be linked into a single unified, dynamic knowledge representation structure. the resulting fabric provides participants with a means to engage in multidisciplinary research and collaboration spanning many information systems without requiring a sophisticated computer science understanding of the mechanics of "Big Data" manipulation. Furthermore, AvesTerra enables this integration without the need for centralized data aggregation or local high-performance computational infrastructure, leveraging instead the distributed resources of a diverse and highly distributed analytic *** a core technical level, AvesTerra consists of a system of peer-to-peer servers that collectively form a readily scalable knowledge space. the mathematical structure of this space is that of a generalized, recursive hypergraph, enabling the representation of complex dependency structures often encountered when working towards global scale. the framework incorporates numerous computational constructs including event publication and subscription, parallel threading and timer support, a unique distributed rendezvous mechanism for agent-based organization, privacy isolation, and semantic structure execution. this presentation provides an overview of the full framework and a sampling of the applications currently under development.
Withthe introduction of edge analytics, IoT devices are becoming smarter and ready for AI applications. However, any increase in the training data results in a linear increase in the space complexity of the trained M...
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the proceedings contain 43 papers. the topics discussed include: fast star identification of super large infrared star catalog;semi-supervised learning for fault identification in electricity distribution networks;rob...
ISBN:
(纸本)9781510642751
the proceedings contain 43 papers. the topics discussed include: fast star identification of super large infrared star catalog;semi-supervised learning for fault identification in electricity distribution networks;robust subspace tracking methods based on fast and stable DPM algorithm;fast factorized back-projection for circular synthetic aperture sonar imaging;an improved depth learning method for surface defect detection;sparse tensor recovery based method for MIMO radar high resolution three-dimensional imaging;the application of Lanczos interpolation in video scaling system based on FPGA;analog and digital wireless video transmission: a survey;and video abnormal event detection based on CNN and multiple instance learning.
the proceedings contain 64 papers. the topics discussed include: combining computational thinking and chibitronics and Makey Makey to develop a social story teaching aid system to improve social reciprocity and emotio...
ISBN:
(纸本)9781450388542
the proceedings contain 64 papers. the topics discussed include: combining computational thinking and chibitronics and Makey Makey to develop a social story teaching aid system to improve social reciprocity and emotional expression skills for autistic children;integrating mathematical modeling in seesaw to enhance engagement and problem - solving performance;development of e-module for teaching the concept of monsoons to grade 7 students in the context of disaster risk reduction;modeling and simulation of a magnetic levitation virtual module for undergraduate rotodynamic teaching;research on the modernization of higher education governance in China: theme evolution, hot spotlight and research prospect: based on the visual analysis of knowledge map of CNKI documents from 2000 to 2018;development of a virtual learning module using graphic interface for remote teaching of photovoltaic systems;and problems of task cycle implementation into L2 English course for technical students within task based L2 language teaching in the context of e-learning environment.
Smart or controlled charging is widely seen as a potential solution to alleviate stress caused by mass uptake of electric vehicles on existing networks. While analyses with completely uncontrolled charging result in u...
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Materialize is a system that presents to users as SQL against continually changing data. It transforms inbound streams of *change data capture* events into streams that exactly correspond to transformed data, and main...
ISBN:
(纸本)9781450393089
Materialize is a system that presents to users as SQL against continually changing data. It transforms inbound streams of *change data capture* events into streams that exactly correspond to transformed data, and maintains indexed representations of the results for efficient access and operation. SQL over changing data is surprisingly (for me) expressive: Materialize can operate on unbounded data, implement data-driven windows, and perform event-based queries, all with ANSI standard SQL. We will discuss what an event-based SQL system looks like, SQL idioms that give rise to traditionally stream-exclusive behavior, and how one architects such a system to scale across multiple dimensions.
the reliability acceptance test (RAT) is to check whether the product meets the reliability requirement. It is essential to choose a test plan with controllable customer's and the producer's risks. the reliabi...
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Aiming at the need of video abnormal events to be located in pixel-level regions, a video abnormal event detection method based on CNN (Convolutional Neural Networks) and multiple instance learning is proposed. Firstl...
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ISBN:
(纸本)9781510642768;9781510642751
Aiming at the need of video abnormal events to be located in pixel-level regions, a video abnormal event detection method based on CNN (Convolutional Neural Networks) and multiple instance learning is proposed. Firstly, the Gaussian background model is used to extract the moving targets in the video, and the connected regions of the moving targets are obtained by the image processing method. Secondly, the pre-trained VGG16 model is used to extract the features of the connected regions what construct multiple instance learning packages. Finally, the multiple instance learning model is trained using MISVM (Multiple-Instance Support Vector Machines) and NSK (Normalized Set Kernel) algorithms and predicted at the pixel-level. the experimental results show that the video anomaly detection method based on CNN and multiple instance learning can accurately locate the abnormal events in the pixel-level region.
Existing approaches to dynamic scaling of streaming applications often fail to incorporate uncertainty arising from performance variability of shared computing infrastructures, and rapid changes in offered load. We ex...
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this article presents a conceptual model of sport events legacy based on the Olympic and Paralympic Games as a reference. the legacy of mega sport events has gained ever more importance during recent years for both ac...
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ISBN:
(纸本)9789897584749
this article presents a conceptual model of sport events legacy based on the Olympic and Paralympic Games as a reference. the legacy of mega sport events has gained ever more importance during recent years for both academics and practitioners. the international Olympic Committee looked at the concept of legacy, as it is the best argument with which to illustrate the lasting benefits that are derived from the Olympic Games. the Legacy is the way to structure the capitalization of the benefits and lessons related to the organization of major sporting events. So, our motivation is to develop a tool of the sport events legacy. the aims of the article are first, to investigate the legacy sport events literature, second, to propose a Legacy Conceptual Model (LCM) and to transpose it to a database which will be support to analyse the changes related to legacy. this research target also has a practical implication. So, we investigate how the LCM helps to analyze the legacy left by a sport event using a case study.
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