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Log analysis plays an important role for computer failure diagnosis. With the ever increasing size and complexity of logs, the task of analyzing logs has become cumbersome to carry out manually. For this reason, recent research has focused on automatic analysis techniques for large log files. However, log messages are texts with certain formats and it is very challenging for automatic analysis to...
Data-driven fault diagnosis, known to be simple and convenient, is more suitable for diagnosing the complicated systems of satellite. Nevertheless, there are two main bottlenecks of data-driven fault diagnosis methods: rule acquisition and decision making. Although the rough set theory can solve above issues well, the obtained rules seem to be more crisp and the diagnosis decisions are not enough...
A curve fitting method based on automatically extracting subsection points is proposed to fit the wheel tread profile accurately. Firstly, the subsection points are determined by segmenting discrete points of wheel tread profile based on given errors and threshold. Secondly, the segmentation interval is determined with the respective segment point as the center, and the least squares curve fitting...
The research of false alarm judgment method has great significance to identify real alarms timely, to response emergency rapidly and monitor network security status correctly. In this paper, in the point of view of alarm data distribution, several methods of false alarm decision are elaborated, and the advantages and disadvantages of each method are analyzed. Studying the false alarm judgment analysis...
In the background of large data, information security faces more opportunities and challenges. Image steganography as an important means of information hiding, is widely used in military, medical, commercial and other important occasions. Two-dimensional code image as a convenient means of information exchange everywhere. In this paper, an improved LSB information hiding algorithm is designed based...
Cluster analysis aims at classifying data elements into different categories according to their similarity. It is a common task in data mining and useful in various field including pattern recognition, machine learning, information retrieval and so on. As an extensive studied area, many clustering methods are proposed in literature. Among them, some methods are focused on mining clusters with arbitrary...
Clustering is an important task in data mining area, especially in the area of continuous stream of data, i.e. ?data stream?. However, some characteristic of this kind of data is neglected during the existing clustering approaches. The similarity in temporal dimension between entities is underestimated. Forgetting mechanism is adopted to remove the old patterns to save computation resources. However,...
Active detection technology was widely used in the traditional tampering detection. Firstly, those mainstream technologies of active detection were introduced. Then, some necessary improvements for the tampering detection algorithm were proposed in this paper, for example, the steganography information was cross-embedded to enhance the safety of the images, and the chaos function was simplified to...
Building extraction from remote sensing images is a longstanding topic in land use analysis and applications of remote sensing. Variations in shape and appearance of buildings, occlusions and other unpredictable factors increase the hardness of automatic building extraction. Numerous methods have been proposed during the last several decays, but most of these works are task oriented and lack of generalization...
Morphological attribute profiles (MAPs) are one of the most effective methodologies to characterize the spatial information in remote sensing images. This technique extracts components able to accurately describe objects in the surface of the Earth. In this work, we present a new method for impervious surface extraction from multispectral images using morphological attribute profiles. The proposed...
Sampling methods are becoming in demand due to the rapid growth of big data applications. The term “Big Data” not only means the large size of data volume but also indicates the high speed of data generation, which plagues many existing data mining and analytic applications owing to the limited capability of processing large volume of data for real time analysis. Therefore, the demands for the use...
In this study, 5 compact polarimetric (CP) data were simulated from 5 consecutive fully polarimetric images, which covered the whole rape growth period. Four groups including 25 CP parameters were extracted from each CP image at different rape growth stages, respectively. With the analysis of the relationships between CP parameters and LAI, g3 in stokes parameter group, Uc in stokes child parameters...
Opinion target extraction aims to find the object to which an opinion is expressed. It is helpful in getting a comprehensive understanding about public opinions on hot spot social events. In Chinese microblog posts analysis, due to the absence of words with emotional tendency (opinion words), traditional approaches relying on opinion words are not suitable. In this paper, we propose an unsupervised...
Computer software size continues to grow recently. But it is difficult to collect information to support software development and maintenances. Data mining technology can be used to automatically discover knowledge from software testing data. It is helpful to increase software developing process and improve software quality. At first, correlation analysis is adopted to study the relevance among the...
Estimating and measuring building height has become one of the significant factors in urban planning, legal and illegal construction inspection, urban disaster warning and assessing, as well as providing initial mapping data for creating three dimensional (3D) digital city models. In this paper we examine the feasibility of extracting building height information using computer vision algorithms with...
Synonyms extraction is a fundamental research, which is helpful to text mining and information retrieval. In this paper, we propose method to extract synonymy from text, the method employs spectral clustering and word2vec. First, the word2vec model is trained by a large-scale English Wikipedia corpus. Then, we extract keywords from a text and use the trained model to generate similarities among these...
With complex pathogenesis, Chronic Obstructive Pulmonary Disease (COPD) is difficult to treat. Traditional Chinese Medicine (TCM) showed obvious effect in treating COPD. However, invaluable TCM experience lacks of systematic summarization and study. Association rule is used to discover the relationships among data items in a large amount of data. Because of clear and useful results, association rule...
For nonlinear estimation, the Gaussian sum filter (GSF) provides a flexible and effective framework. It approximates the posterior probability density function (pdf) by a Gaussian mixture in which each Gaussian component is obtained using a linear minimum mean squared error (LMMSE) estimator. However, for a highly nonlinear problem with large measurement noise, the estimation performance of the LMMSE...
This paper proposes an attack pattern mining algorithm to extract attack pattern in massive security logs. The improved fuzzy clustering algorithm is used to generate sequence set. Then PrefixSpan is used to mine frequent sequence from the sequence set. The experimental results show that this algorithm can effectively mine the attack pattern, improve the accuracy and generate more valuable attack...
Knowledge graph technology belongs to the field of artificial intelligence. It is widely used in semantic search and intelligent question answering. Construction of Uyghur's knowledge graph has the great value of Uyghur information processing and Uyghur application software development. Firstly, this paper describes the definition and structure of the knowledge graph, then it reviews the related research...
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