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In this paper, we propose a novel image representation for scene classification. Firstly, we model multiple order statistics of image patches via Gaussian Mixture Model(GMM) in a Bayesian framework. Secondly, we combine the information of mean and covariance of the GMM and represent it as a mean-covariance supervector through a new distance metric.(More)
In order to solve the disadvantage of current ant colony optimization algorithm (ACO) which easily plunged into local optimal in dealing with Multi-Satellite Scheduling Problem (MuSSP), a hybrid ant colony optimization algorithm (HACO) is proposed. In this method, the ACO algorithm is served as a global search algorithm. According to the characteristics of(More)
This paper proposes a new SVM-based method for text-independent speaker verification using derivative kernel in the reference Gaussian mixture model (GMM) space. The model for speaker utilizes the power of SVM and GMM, reference GMM used first, and then SVM followed. Using the reference GMM, not only clusters and compacts the speech, but also distinguishes(More)
This paper presents a new unsupervised anomaly detection approach for spacecraft based on normal behavior clustering. This method takes as input a set of unlabelled historical telemetry data and automatically detects anomalies within the data. After these abnormal data are removed, the method constructs system normal behavior model based on normal data(More)
Development of intelligent fault detection and diagnosis technologies for spacecraft is one of important issues in the space engineering. In this paper, we present a new fault detection and diagnosis approach for spacecraft based on Principal Component Analysis (PCA) and Support Vector Machines (SVM). Firstly, PCA is used to extract features from input data(More)
A few literatures on the maintenance strategy (MS) decision making have been found. Moreover, they never deal with the case that the most appropriate MS is selected for a machine when two kinds of evaluations of each MS are considered: deterministic or fuzzy in relation to each evaluation criterion (EC). In order to resolve the problem, ELECTRE III based on(More)
Measuring magnetic parameters nondestructively is important for understanding fatigue phenomena of ferromagnetic materials. In this study, metal magnetic memory method is used as a new diagnostic tool to evaluate fatigue process. Both normal and tangential components of residual magnetic field have been studied on medium carbon steel specimens subjected to(More)