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Service flow in SOA systems need to detect quality of service (QoS) problems and to guarantee end-to-end performance. In previous work, we have proposed two faulty service identification methods: a dependency matrix based diagnosis and a Bayesian network based diagnosis. In this paper, we present a hybrid diagnosis to achieve high diagnosis accuracy and low diagnosis cost. The hybrid diagnosis reduces...
In this paper, we propose a channel estimation approach based on Bayesian compressive sensing that has the advantage of computation simplicity, noise robust to some extent and the sparse result. UWB channel estimation is absolutely vital to the design of the receiver and is predicament of the UWB system implement. We show that our proposed method relies on the time domain sparse of the impulse response...
Bayesian compressive sensing (BCS) utilizes the prior distribution of signal coefficients to reconstruct the original signal. The widely used prior is Laplace and Gaussian distributed. In this paper, we use the scene of L sets of signal sparse coefficients which are statistically related and take advantage of Laplace prior and statistically interrelationship among signals to propose the Laplace prior...
A neural networks are able to give solutions to complex problems in business intelligence and financial engineering due to their nonlinear processing. This paper consists of a survey of various business intelligence and financial engineering and so on applications based on the neural networks, and also a summary of the recent techniques such as still evolutionary algorithms, cellular computing, Bayesian...
It has been found that non-point source pollution - excessive nitrogen loading is one of the main reasons for the eutrophication of Miyun Reservoir, Beijing, China. At present, the research about eutrophication is still confined to a single level of analysis lacking a full perspective of monitoring, integrated simulation and evaluation. The model domain is the area of Miyun Reservoir, Beijing. This...
Collocation is the frequent bi-grams of semantic meanings and grammatical functions. Adjacent and long distance collocations are extracted as features for a Bayesian classifier in spam filtering. Compared to the common unigram feature, collocation-based classifier shows improvement in all the evaluation metrics. The influence of mail header information is studied for the classifier, which shows a...
Video comprises multiple types of textual, audio and visual information, and each of them contains abundant semantic information. Therefore multimodal features query and fusion are necessary in video retrieval. In this paper, we propose a new video retrieval model, which adopts multi-model including text, image, semantic concept and camera motion to query video. Then relation algebra expression is...
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