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DDoS attacks bring huge threaten to network, how to effectively detect DDoS is a hot topic of information security. Currently, there are some methods designed to detect DDoS attacks, but the detection rate of them is low. Moreover, DDoS detection is easily misled by flash crowd traffic. In this paper, a new method to detect DDoS attacks based on RDF-SVM algorithm is proposed. By considering the importance...
SVM (Support Vector Machine), a state of the art classifier model is implemented on a computational mobile platform and its performances are evaluated against a low complexity classifier such as SFSVC (Super Fast Vector Support Classifier) on the same platform. For a better comparison, similar implementation for the two architectures are considered, such as using the same basic linear algebra library...
In this paper, we presented an improved vehicle detection algorithm based on object proposals. In the training part, by using Selective Search algorithm, we firstly segment the vehicle areas in the sample set as positive examples, other regions as negative examples. Then PHOG (Pyramid Histogram of Oriented Gradient) features of the positive samples and negative ones after separately being labeled...
Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurobehavioral disorders in children and electroencephalography (EEG) is one of most common used neuroimaging techniques as the most accessible and informative method. EEG can be of great help in ADHD studies. Considering the brain as the most complicated information processing system, information theories can be applied...
The interoperability testing of CTCS-3 Level Train Control System guarantees the safe operation of train running on different lines. It makes great sense to achieve automatic analysis of interoperability testing results, which could improve the efficiency and accuracy of testing. In this paper, a research was conducted on automatic analysis of testing results for on-board equipment of train control...
Systems developed to classify human activities to identify unintentional falls are highly demanding and play an important role in our daily life. Human falls are the main obstacle for elderly people to live independently and it is also a major health concern due to aging population. Different approaches are used to develop human fall detection systems for elderly and people with special needs. The...
Huge amount of data in today's world are stored in the form of electronic documents. Text mining is the process of extracting the information out of those textual documents. Text classification is the process of classifying text documents into fixed number of predefined classes. The application of text classification includes spam filtering, email routing, sentiment analysis, language identification...
With the growth of Android platform malicious application, the seperation of malicious application from nonmalicious application has become challenging. In recent years, a combination of static analysis and dynamic analysis of the idea is very popular. However, it is very costly for dynamic analysis to achieve high coverage. In this article we present an efficient, lightweight and behavior-based architecture...
Based on the spectral data from SDSS, Kernel Support Vector Machines (K-SVM) is applied to classify quasars from other celestial body. Firstly, the basic theory of the SVM(Support Vector Machine) with relaxation factor and kernel function is introduced. Then, the main parameters are designed and selected. Finally, the method is applied to the classification and identification of the quasars. The classification...
As network intrusion data's scale gets larger and larger, designing parallel schemes for intrusion detection have been becoming research focus in the field of information security. In order to solve the problem that the intrusion detection algorithm is high time-consuming, the classification of large amounts of data occupies lots of memory and the efficiency of single detection is low, a parallel...
the division of the test paper can reflect the quality of examination paper, but it is difficult to find some decisive courses in dozens of courses. In order to find out the curriculum that decides the role of different levels of students, the concept of course discrimination is proposed, which focuses on the value of course discrimination, the classification method and the proportion of special courses...
The basic idea behind the classifier ensembles is to use more than one classifier by expecting to improve the overall accuracy. It is known that the classifier ensembles boost the overall classification performance by depending on two factors namely, individual success of the base learners and diversity. One way of providing diversity is to use the same or different type of base learners. When the...
The purpose of this research is to provide a new and efficient way to identify targets in polarimetric synthetic aperture radar (PolSAR) images using the inherent properties of these images and to reduce the time and cost of calculation. In this paper, a new method is proposed to feature extraction and classification based on non-negative matrix factorization (NMF), Fisher linear discriminant analysis...
The classification and visualization for surface objects receives a great deal of attention for high spectral dimensional data processing. A lot of methods were proposed and applied in this problem over the past decade. Whereas most of them still exist some challenge issues, include pre-treatment fussily, features extraction simplify, larger data processing difficultly and classification inaccurately...
In recent years, the problem of classification for high dimensional and class-imbalanced data is found in many fields like bioinformatics and so on. High dimensional problem result in bad classification results because of some combinations of features have adverse effect on classification. Class-imbalanced problem means the number of samples of one class is more than another class, which would make...
Algorithms used in data mining techniques are of great importance in the field of health care, especially in the case of getting patterns or models that are undiscovered in databases. In the area of health care, leukemia affects the blood status and can be discovered by using the Blood Cell Counter (CBC). This study aims to predict the leukemia existence by determining the relationships of blood properties...
In this article, we explore the task of sentiment analysis for Ukrainian and Russian news, analyze different approaches and linguistics resources for sentiment analysis. We developed a corpus of Ukrainian and Russian news and annotated each text with three categories: positive, negative and neutral. Each text was marked by at least three independent annotators via the web interface and the texts marked...
This paper presents an effective approach for classification of power quality (PQ) disturbances based on wavelet transform (WT) and support vector machine (SVM). Wavelet transform was applied to disturbance signal in order to obtain decomposition coefficients at six levels that represents signal in time and frequency domain. Eight statistical methods were used to extract features that characterize...
The change of the vibration signal can reflect the mechanical state of the HV circuit breaker. An efficient method of feature extraction of the vibration signal usually pays a key role in the validity of the fault diagnosis and also lays the foundation for the fault classification in the subsequent stage. The paper presented a feature extraction method which is based on average empirical mode decomposition...
Based on learning principle of support vector machine (SVM), damage detection of bolt anchorage is studied in this paper. Characteristic matrix is composed of 17 time domain or frequency domain characteristic properties including mean value, peak value of the denoised signal, etc. Principle component analysis(PCA) is used for feature extraction and several main components with higher cumulative contribution...
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