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In order to meet the needs of China higher education of training students with strong foundation ability and innovation in the filed computer science, in recent years, the computer basic teaching team of Beijing Jiaotong University has carried out a series of scientific and effective educational reforms research and practice: 1. Carrying out “MOOC + SPOC + Flipped classroom” practice; 2. Construction...
School-enterprise cooperation has become an important guiding ideology for developing vocational education in China. This paper introduces a successful experience to build a lifelong learning system for employees. The developed lifelong learning platform has worked in the following way. Senior engineers of the enterprises train college teachers. Using rich teaching experience, the teachers can transform...
In order to solve the problem of time-consuming dictionary training process, we propose an image super-resolution reconstruction approach based on fusion of K-SVD algorithm and semi-coupled dictionary learning framework. In this paper, we use K-SVD algorithm to training the dictionary pair in the semi-coupled dictionary learning model. In comparison with the existing methods, experiment results on...
Incremental Attribute Learning (IAL) is a feasible machine learning strategy for solving high-dimensional pattern classification problems. It gradually trains features one by one, which is quite different from those conventional machine learning approaches where features are trained in one batch. Preprocessing, such as feature selection, feature ordering and feature extraction, has been verified as...
Feature Extraction (FE) based on Principal Component Analysis (PCA) can effectively improve classification results by reducing the interference among features. However, such a good method has not been employed in previous studies of Incremental Attribute Learning (IAL), a novel machine learning strategy, where features are gradually trained one by one in order to remove interference among features...
With the popularity of various software applications in cloud computing, software exception becomes an important issue. How to detect the exceptions more quickly seems to be crucial for the software service company. To solve the above problem, this paper presents an efficient log anomaly detection method named PADM (Page Rank-based Anomaly Detection Method) based on the graph computing algorithm....
The purpose of the present study was to develop new statistically validated in silico models to predict the toxicity of organic chemicals using multiple linear regression (MLR) and principal components analysis (PCA). This model applied a diverse set of theoretical molecular descriptors for a set of 468 heterogeneous chemicals with the toxicity data of (LC50)96h in Pimephales promela. The established...
Solving the main problems of the disconnect between computer application talent cultivation and real world marketplace demands and the existing deficiency in engineering and innovation ability of higher education programs. This paper gives an analysis of current engineering programs, the reengineering effort of computer engineering programs and the CDIO Model, describes a new refined program based...
The static evaluation used in Chinese chess computer game currently could neither reflect the strength trend of game players objectively nor accomplish the strategic purpose of game players, so a situation-evaluating matrix is defined and the dynamic character of the situation-evaluating strategy is analysed based on game situation's influence. Furthermore, a high-class evaluation method based on...
In this paper, a six degree of freedom half body vehicle suspension system is developed. The neural network algorithm is used to control the suspension system. With the aid of software Matlab/Simulink, the simulation model is achieved. With changing of neural network coefficients, such as changing of training epoch and changing of the network structure, a lot of simulation work is done. Simulation...
In this paper, we present a novel no-reference (NR) model for perceptual video quality assessment, which can make quality prediction for high definition (HD) videos. This model is based on an artificial neural network (ANN) implemented by the back-propagation algorithm (BP), named as BP-ANN. Six video features are extracted from temporal and spatial domains as the input vectors. Subjective assessments...
Most methods for multiclass objects learning have large computational complexity and samples scale complexity. In this paper, within the framework of boosting, we propose a novel method called JointBoosting-GA. It is suitable to all datasets from small to very large, and results in a much faster classifier at run time. To achieve it, we combine two ideas: 1) Firstly, we introduce a novel technique,...
One of the main drawbacks of boosting is its overfitting and poor predictive accuracy when the training dataset is small and imbalanced. In this paper, we introduce a novel learning algorithm Boost-BFKO, which combines boosting and data generation. It is suitable for small and imbalanced training datasets. To enlarge training sets, Boost-BFKO uses the adaptive Balanced Feature Knockout procedure (BFKO)...
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