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With the progress of the network and technology, the perfect combination of mobile intelligent terminal and internet, people are increasingly dependent on intelligent terminals. So, it was very necessary of a model for assessing the security performance of mobile intelligent terminals, especially to establish the objective model of the security performance of mobile intelligent terminal. In this paper,...
When GeForce256 was issued in 1999, NVIDIA first proposes the concept of GPU (Graphics Processor Unit), and then a large number of complex application requirements make the whole industry flourishing. This paper first presents the development of GPU, and then briefly introduces and compares two popular development platform of GPU: CUDA (Compute Unified Device Architecture) C and OpenCL (Open Computing...
In this paper, a multi-layers method with multi-parameters based on the characteristics of the human movements acceleration signals is proposed to recognize the human daily activities. We calculate some features of the acceleration signals that are less dependent on the individuals. The features are successfully used to divide signals into different groups which are related to the human daily activities...
To address the parameter optimization problem of plate color recognition, two approaches based on IA (immune algorithm) and GA (genetic algorithm) are proposed respectively. Theoretical comparison of IA and GA is first made. Then experimental comparison of the two algorithms is given by using them to perform the parameter optimization task for color recognition of license plates. For plate color recognition...
To improve accuracy and adaptability, this paper presents a learning algorithm for color recognition of license plates. For three components of the hue-saturation-value (HSV) color space, different membership functions were defined to calculate their fuzzy degrees. Through the weighted fusion of the three membership degrees, a single map was produced to be the classification function for color recognition,...
The reasonable division of attribute spaces is a core problem in the decision tree construction and the rule extraction, which directly influences the effectiveness of the construction of decision trees. In this paper, a new two-dimension analysis method for the attribute space division is proposed, which not only reduces the analysis complexity, but also improves the efficiency of attribute division...
Color recognition of license plates is an important step to License Plate Recognition (LPR) system. In order to perform color recognition more effectively, an algorithm based on Naive Bayesian approach is proposed in this paper. To improve the efficiency of color recognition, the multiclass problem is converted into two binary problems based on the reverse color information of plate images. Color...
Fingerprint classification is crucial to reduce the processing time in a large-scale database. In this paper a fingerprint classification based on continuous orientation field and singular points is proposed. The continuous orientation field can not only filter the noises in point directional image, but also represent the basic structural feature of fingerprint more precisely. Singularities are the...
E-learning behavior analysis is an important issue to the instruction based on Internet. This paper proposed a new method to analyze the e-learning behavior. It classified e-learning behaviors into several clusters by fuzzy clustering algorithm. Behaviors in the same cluster have the most common in characters, while behaviors between clusters have the least common. Experiments fully demonstrated that...
Automatically classifying text documents is an important field in machine learning. Unsupervised text classification does not need training data but is often criticized to cluster blindly. Supervised text classification needs large quantities of labeled training data to achieve high accuracy. However, in practice, labeled samples are often difficult, expensive or time consuming to obtain. In the meanwhile,...
In computer vision system, detection of moving targets has interference in subsequent processes including classification, tracking and recognition. Background subtraction method is commonly used in image segmentation for moving region of video. This paper puts emphasis on background model update based on mixture models of Gaussian in complicated situation, and implements an adaptive learning method...
In practical issues, categorical data and numerical data usually coexist, and a unified data reduction technique for hybrid data is desirable. In this paper, an information measure is proposed for computing the discernibility power of a categorical or numeric attribute. Based on the measure, a uniform definition of significance of attributes with categorical values and numerical values is proposed...
This study focused on comparing the classification performance and accuracy for short-term urban traffic flow condition using decision tree algorithms (CHAID, CART, QUEST and C5.0). In building decision tree models, input variables were multiple roads' traffic flow condition value at current time, while, target variable was a certain road's condition value at future temporal horizon from 5-30 min...
In this paper, we propose a new method of designing and constructing ldquogoodrdquo mappings defined by kernel functions for classification task, called Optimal Successive Mappings (OSM). Kernel methods, such as Support Vector Machines (SVM), could not provide satisfactory classification accuracy on some complicated data sets, which are still not linearly separable in feature space. It means kernels...
Name ambiguity is a critical problem in many applications, in particular in the online bibliography systems, such as DBLP and CiteSeer. Previously, several clustering based methods have been proposed although, the problem still presents to be a big challenge for both research and industry communities. In this paper, we present a complementary study to the problem from another point of view. We propose...
Differential evolution (DE) and particle swarm optimization (PSO) are the evolutionary computation paradigms, and both have shown superior performance on complex nonlinear function optimization problems. This paper detects the underlying relationship between them and then qualitatively proves that the two heuristic approaches from different theoretical background are consistent in form. Within the...
Nowadays, many studies of the discovery of the relative pattern of a disease, but some of them do not consider the data privacy of patients completely, and others are not very effective to find the pattern. In this paper, we propose a novel approach to deal with the above problems. We employ intuitionistic fuzzy set, alpha-cuts, and Apriori algorithm to discovery the relative pattern of a disease...
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