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Components are often subject to multiple competing degradation processes. This paper presents a reliability assessment framework for multicomponent systems whose component degradation processes are modeled by multistate and physics-based models with limited statistical degradation/failure data. The piecewise-deterministic Markov process modeling approach is employed to treat dependencies between the...
Technology develops rapidly and information floods. In the information explosion era, what people lack is not the scale of information but how to obtain the needed information quickly and accurately. Personalized search and service emerges. And the key problem is to make clear the needs of the users. In this paper, we combined user interest and collaborative filtering to reorder the search results...
In this paper, a new quantitative risk analysis model of integrating fuzzy fault tree (FFT) with Bayesian Network (BN) is proposed. The first step involves describing a fuzzy fault tree analysis technique based on the Takagi and Sugeno model. The second step proposes the translation rules for converting FFT into BN. Based on this, the integration algorithm is demonstrated by an offshore fire case...
In order to improve detection efficiency of on-line web news stream, we propose a new method to accomplish detection task with window-adding, named entity recognition and suffix tree clustering. In our method, we make full use of informative elements of news stream(such as date, place, person and so on) to help detection process, and this method decreases text similarity computation greatly. Experimental...
We present a novel general framework for distributed anomaly detection. In the framework, normal behavior is first learned from data from individual data sites using standard anomaly detection algorithms and then these models are combined when predicting anomalies from a new data set. We have investigated seven semi-supervised anomaly detection algorithms for learning normal behavior, as well as proposed...
Outlier detection over data streams has attracted attention for many emerging applications, such as network intrusion detection, web click stream and aircraft health anomaly detection. Since the data stream is likely to change over time, it is important to be able to modify the outlier detection model appropriately with the evolution of the stream. Most existing approaches were using incremental or...
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