the proceedings contain 111 papers. the topics discussed include: identification and validation of real-time health events through social media;active storage mechanism for cluster-wide RAID system;SMASH: a cloud-base...
ISBN:
(纸本)9781509002146
the proceedings contain 111 papers. the topics discussed include: identification and validation of real-time health events through social media;active storage mechanism for cluster-wide RAID system;SMASH: a cloud-based architecture for big data processing and visualization of traffic data;sequential pattern mining system for analysis of programming learning history;a mixed and batching authentication protocol for grouped tags in mobile RFID system;scalable data representation in risk management information systems using an XQuery extension;operation-level performance control in the object store for distributed storage systems;exploiting collective spontaneous mobility to improve location prediction of mobile phone users;an event-based framework for the specification and runtime checking of timing constraints in wireless sensor and actuator networks;flow-control policies for wireless sequencer-based causal and total order communication;and malicious node traceback in opportunistic networks using Merkle trees.
Creating music in an automatic way has been studied since the beginning of artificial intelligence. One of the biggest obstacles of music generation is the vagueness and subjectivity of the mood or emotion transmitted...
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the extraction of recurrent patterns from sequences is a popular and intensive application, ubiquitous to many domains. Often, however, the process exposes more candidates than one can afford to inspect, thereby defyi...
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Our aim is to propose a new look at the dimensionality reduction in patternrecognition problems by extracting part of variables that are further called external context variables. We show how to incorporate them into...
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ISBN:
(纸本)9783642293467;9783642293474
Our aim is to propose a new look at the dimensionality reduction in patternrecognition problems by extracting part of variables that are further called external context variables. We show how to incorporate them into the Bayes classification scheme with loss functions that depend on class labels that are ordered. then, the general form of the optimal context sensitive classifier is derived and the learning method that is based on kernel approximation is proposed.
Polar Harmonic Transform (PHT) is termed to represent a set of transforms those kernels are basic waves and harmonic in nature. PHTs consist of Polar Complex Exponential Transform (PCET), Polar Cosine Transform (PCT) ...
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ISBN:
(纸本)9781424478132
Polar Harmonic Transform (PHT) is termed to represent a set of transforms those kernels are basic waves and harmonic in nature. PHTs consist of Polar Complex Exponential Transform (PCET), Polar Cosine Transform (PCT) and Polar Sine Transform (PST). they are proposed to represent invariant image patterns for two dimensional image retrieval and patternrecognition tasks. they are demonstrated to show superiorities comparing with other methods on describing rotation invariant patterns for images. Kernel computation of PHTs is also simple and has no numerical stability issue. However in order to increase the computation speed, fast computation method is needed especially for real world applications like limited computing environments, large image databases and realtime systems. this paper presents Fast Polar Harmonic Transforms (FPHTs) including Fast Polar Complex Exponential Transform (FPCET), Fast Polar Cosine Transform (FPCT) and Fast Polar Sine Transform (FPST) that are deduced based on mathematical properties of trigonometric functions. the proposed FPHTs are averagely over 6 similar to 8 times faster than PHTs that significantly boost computation process. the experimental results on both synthetic and real data are given to illustrate the effectiveness of the proposed fast transforms.
Cloud computing in healthcare becomes a growing field for improvement. the advent of cloud technology provides efficient and reliable outcomes to support healthcare services. Cloud technology reduces these costs for c...
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Motors occupies an important position in the manufacturing *** at the problem of low accuracy of motor fault recognition,the temporal convolutional neural network(TCN) and attention mechanism are introduced. the fault...
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Health information needs are also changing the information-fetching behavior, and that is observed around the globe. In this paper author has suggested the possibility of combining edge computing and machine learning ...
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Design pattern detection is a popular re-engineering job in software development. It provides essential information to the developers to recognize, sustain, and recycle the software. this article proposes a graph matc...
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Deep learning's progress has resulted in a multi-layered character in a variety of applications in this field. Artificial Neural Networks are becoming the old procedure in the wide region of computing, using fifty...
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