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An improved KNN text classification algorithm based on Simhash has been proposed by introducing Simhash and the average Hamming distance of adjacent texts as a unit, which solves the problems caused by data imbalance and the large computational overhead in the traditional KNN text classification algorithms. Experimental results demonstrate that the proposed algorithm performs a higher precision, a...
Deposition and congestion of foulants in the compressor section of gas turbine engines (GTE) degrades the compressor and leads to performance deterioration of the GTE at the system level. Compressor fouling may develop over a short time, but it is recoverable by washing and cleaning. Reliable prediction of the fouling as a function of time is helpful for planning compressor wash services. In this...
With the big success of deep convolutional neural networks (CNN) in image classification task, many proposal based networks are proposed to detect given objects in an image. Faster R-CNN is such a network that uses a region proposal network (RPN) to generate nearly cost-free region proposals, which has shown excellent performance in ILSVRC and MS COCO datasets. However, Faster R-CNN does not behave...
Prognostics of a specific asset based on data from a fleet of same assets, but operated in different environmental and operational conditions is an important and common problem in Prognostics and Health Management (PHM). Traditional data-driven models trained on all fleet data provide only a general degradation trend, without capturing the specificity of the degradation process of the different assets...
In the redundant system, Common Cause Failure (CCF) can result in failures of more than one module. Human Error is one of the most important causes among all the causes of CCF. Human factor diversity is an effective method against CCF due to human error. Although there is clear evidence that diversity can bring benefits, these benefits can be difficult to quantify. The current methods of human reliability...
This paper proposes a hybrid algorithm based on improved LLE and adaptive k-means for visual codebook generation in tourism scene classification. Firstly, we construct the improved LLE algorithm to get lower dimensional and compressed image feature representations. Then we form the adaptive k-means clustering algorithm to generate the visual codebook. Finally, we use the visual codebook histogram...
Recently, combining Conditional Random Fields (CRF) with Neural Network has shown the success of learning high-level features in sequence labeling tasks. However, such models are difficult to train because of the increase of the parameters to tune which needs enormous of labeled data to avoid over fitting. In this paper, we propose a transfer learning framework for the sequence labeling task of gesture...
Compound model PSO with stochastic inertia weight is put forward and used to optimize the parameters of wavelet neural network. The trained wavelet neural-network is applied to choosing tested position of gearbox. It is an available approach to solve the problems on choosing tested position in fault diagnosis.
In this paper, a novel method based on former cases for plastic surgery prediction is presented. This method takes a pre-operative frontal facial picture as an input. Landmarks of the face are then extracted and constitute a distance vector. As a set of facial parameters, such a vector is entered into either a support vector regression (SVR) predictor or a k-nearest neighbor (KNN) predictor which...
CDIO is a new mode in modern engineering education distinguished from traditional modes, which is project-based. CDIO stands for conceiving, designing, implementing and operating. It has been proved effective in engineering education. After the steps of CDIO analyzed, an example using CDIO is presented to show how CDIO works, and how traditional courses are changed into CDIO courses as well. The experiments...
Extension of ontology instance is the important part of ontology maintenance. In this paper, a novel and effective method is proposed to extending ontology instances from Chinese free text, which is achieved with classification using support vector machine (SVM). Firstly, classification features are extracted in terms of syntax and semantics from the training texts and the new texts based on the existed...
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