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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...
Indentifying potential pollution sources from the monitoring water quality data is desirable for water quality management. A simple expert system module was developed in this paper to infer the latent pollution sources and explain variation in water quality parameters. It contains three parts. The first part is water quality mining and analyzing component implemented by multivariate statistical techniques...
In the past decade the massive growth of the Internet brought huge changes in the way humans live their daily life; however, the biggest concern with rapid growth of digital information is how to efficiently manage and filter unwanted data. In this paper, we propose a method for managing RSS feeds from various news websites. A Web service was developed to provide filtered news items extracted from...
To meet the requirements for being geared to the international standards and to meet the demand for self-development of an enterprise, it becomes more and more common for an enterprise to execute EPC projects. The EPC model compares with the traditional contract model, the risk of general contactor is the biggest undoubtedly. Through the analysis of the EPC model to determine the risk source and loss...
Today, large scale computer systems have become an important component in production and scientific computing and lead to rapid advances in many disciplines. However, the size, and complexity of systems make them very difficult to detect unusual nodes automatically and traditional host monitoring tools are not capable of dealing with the need of anomaly detection in large amount of nodes. In this...
Enterprise informationization in Chinese manufacturing industry has marched for long time. Facing much more new technologies and more and more complex IT systems, enterprises are encountering the challenge of improving and providing the business value of IT. How to plan an enterprise-wide IT systems blueprint to fulfill the enterprise business demands and get the great value of IT is a critical factor...
The temporal and spectral differences of click-evoked otoacoustic emissions (CEOAEs) under different click intensities have been elaborated. However, CEOAE nonlinearities regarding frequency changes along with time, or time-frequency (TF) pattern dependence on stimulus intensity have been barely acknowledged so far. The analysis of shape and localization of the pattern on the time-frequency plane...
According to the features of Dai Characters and the status quo of Dai Information processing, this paper puts forward a making method of common outline fonts of the Dai characters. Based on the analysis on the types of outline fonts, outline extraction method of Dai font is designed and realized in Linux. Dai outline font as basis for Dai information processing provides strong support for promoting...
As the only hieroglyph still being used in the world, NaXi pictograph performs an important role in studying the evolutionary history of human character. In the past, the NaXi pictograph was processed by hand which is very inefficient. Through analyzing the characteristics of NaXi pictograph and the present situation of information processing, this paper proposes an input method that can transfer...
The dissipative particle dynamics simulation is usually used to study polymer in mesoscopic space. The traditional methods are resource intensive, especially when the scale of research is large. Therefore, improving computing efficiency is a key point in this research area. Two major issues are addressed in this paper. First, the DPD methods are analysed and the most time-consuming parts are identified:...
Branch and bound for semi-supervised support vector machines as an exact, globally optimal solution is useful for benchmarking different practical S3VM implementation. But, global optimization can be computationally very demanding. Parallel implementation of the algorithm enables us to reduce computational time significantly and to solve larger problems. Focusing on the time consuming problem of BBS3VM,...
The driving mode by two hydraulic motors and reducer is widely used in many types of equipment, which adjusts velocity and torque by the way of changing the relationship of the two motors- series connection or parallel connection. It is generally believed that the power distributions on the two motors are the same, which is to say that the two motors' load-bearing states are identical. In this paper,...
Spectral clustering is a widely-used algorithm in the field of information retrieval, data mining, machine learning and many others. It can help to cluster a large number of data into several categories without requiring any additional information about the dataset or the categories, so that people can find information by categories easily. In this paper, we parallelize the algorithm proposed by Andrew...
In order to find rules of disaster weather from the history data and provide some support for the weather forecast, rough set theory was introduced into the field and a weather data model based on it was built. The model included the processes of data discretization, attributes reduction and rules extracting. For the rules extracting a new method based on discriminated matrix was proposed. The method...
This article introduces a mining method of Web data in adoption of Web page comparison & analysis within a Web site in light of free chemistry database on Internet. On the basis of treeing and blocking Web pages, the data block of Web page is retrieved after compared and analyzed, and then the data is extracted via the comparison and judgment of more than one page of the same structure and format...
Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. In particular, clustering algorithms that build meaningful hierarchies out of large document collections are ideal tools for their interactive visualization and exploration as they...
This paper evaluates the performance of different criterion functions in the context of partitional clustering algorithms for document datasets. Our study involves a total of seven different criterion functions, three of which are introduced in this paper and four that have been proposed in the past. We present a comprehensive experimental evaluation involving 15 different datasets, as well as an...
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