The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Violations of listed companies to disclose accounting information will mislead the ordinary investors seriously and bring huge losses to investors. Therefore, it is particularly necessary to analyze and identify the violations of listed companies based on scientific and effective methods to avoid investment risks in advance. In this paper, we firstly use t-statistic to select eight useful and characteristic...
Automatic signature generation approaches have been widely applied in recent traffic classification. However, they are not suitable for LightWeight Deep Packet Inspection (LW_DPI) since their generated signatures are matched through a search of the entire application data. On the basis of LW_DPI schemes, we present two Hierarchical Clustering (HC) algorithms: HC_TCP and HC_UDP, which can generate...
In this paper, a novel method for gender classifications with support vector machines based on our constructed bivariate compactly supported non-tensor product pre-wavelets is proposed. Utilizing the non-tensor product pre-wavelets to extract the more excellent gender classification features, then these features are fed into support vector machines to automatically perform gender classification. The...
The source number estimation is a basic problem in the smart antenna technology. Some classic estimation algorithms have been developed in past twenty years like `AIC', `MDL', hypothesis test (`HPY'), Gerschgorin Radii (`GDE'), etc .But the estimation error will be great in the circumstances of low S/N, small sample with these algorithms. This paper develops a novel method based on support vector...
In this paper, a new method for time-series pattern finding is proposed. The time-series curve is modeled as sequence of straight lines by piecewise linear approximation and the correspondent Arctg(slopes) of the lines are obtained as samples. Classification accuracy of time-series pattern finding algorithm is improved by using artificial neural network (ANN) and hierarchical processing technology...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.