Search results for " Network"
showing 10 items of 6428 documents
Combination of finite impulse response neural network technique with FDTD method for simulation of electromagnetic problems
1996
The finite difference time domain (FDTD) method requires long computation times for simulating resonant or high-Q structures. The authors incorporate the finite impulse response neural network technique as a predictor in order to save time in FDTD simulations. The applicability of the technique is demonstrated by carrying out an analysis of a waveguide filter.
A multiscale method for gamma/h discrimination in extensive air showers
2011
We present a new method for the identification of extensive air showers initiated by different primaries. The method uses the multiscale concept and is based on the analysis of multifractal behaviour and lacunarity of secondary particle distributions together with a properly designed and trained artificial neural network. The separation technique is particularly suited for being applied when the topology of the particle distribution in the shower front is as largely detailed as possible. Here, our method is discussed and applied to a set of fully simulated vertical showers in the experimental framework of ARGO-YBJ, taking advantage of both the space and time distribution of the detected sec…
Prefiltering for pattern recognition using wavelet transform and neural networks
2003
Publisher Summary Neural networks are built from simple units interlinked by a set of weighted connections. Generally, these units are organized in layers. Each unit of the first layer (input layer) corresponds to a feature of a pattern that is to be analyzed. The units of the last layer (output layer) produce a decision after the propagation of information. Before feeding the computational data to neural networks, the signal must undergo a preprocessing in order to (1) define the initial transformation to represent the measured signal, (2) retain important features for class discrimination and discard that is irrelevant, and (3) reduce the volume of data to be processed, for example, data …
Communication in new technology based‐firms
2013
PurposeThe paper aims at identifying the main social media applications used by new technology based‐firms (NTBFs) and at calculating the volume of followers they have in each application. It also focuses on the amount of activity generated by the firms in those social networks, identifying the key thematic content of their social media activity, analyzing the ability to create dialogue with their stakeholders and clarifying which style of communication they use.Design/methodology/approachThe paper presents an exploratory study of the use of social media tools by NTBFs, located in Spanish Science Parks, as an important resource network for firms in the corresponding sector. A total of 432 n…
Accessibility of the Italian institutional web pages: a survey on the compliance of the Italian public administration web pages to the Stanca Act and…
2014
Accessibility of the Italian public administration web pages is ruled by the Stanca Act and in particular the Decree of the Minister issued on July 8, 2005. In this paper, an objective test is performed on the official web pages of the Italian province and region chief towns to check their compliance to the 22 technical requirements defined by the Stanca Act. A sample of 976 web pages belonging to the websites of the Italian chief towns have been downloaded in the period October---December 2012. Such a data collection has been submitted to Achecker, the worldwide recognized syntax and accessibility validation service. Several accessibility and syntax errors have been found following the aut…
Mobile Search - Social Network Search Using Mobile Devices
2008
During the last years progress in Web search engines has been made to the point that relevant information can be reached easily most of the time. However very little empirical research has been carried to study Web search in highly dynamic social network environments composed of mobile devices. The aim of this work was therefore to investigate novel approaches that took advantage of the social network environment inherent to mobile peer-to-peer paradigm. The work focused mainly on the development of a prototype for mobile search concept. The prototype was built on top of Drupal content site management system. This study suggests that the methods presented can be a complement to traditional …
HTTP-level e-commerce data based on server access logs for an online store
2020
Abstract Web server logs have been extensively used as a source of data on the characteristics of Web traffic and users’ navigational patterns. In particular, Web bot detection and online purchase prediction using methods from artificial intelligence (AI) are currently key areas of research. However, in reality, it is hard to obtain logs from actual online stores and there is no common dataset that can be used across different studies. Moreover, there is a lack of studies exploring Web traffic over a longer period of time, due to the unavailability of long-term data from server logs. The need to develop reliable models of Web traffic, Web user navigation, and e-customer behaviour calls for …
Modeling a non-stationary bots’ arrival process at an e-commerce Web site
2017
Abstract The paper concerns the issue of modeling and generating a representative Web workload for Web server performance evaluation through simulation experiments. Web traffic analysis has been done from two decades, usually based on Web server log data. However, while the character of the overall Web traffic has been extensively studied and modeled, relatively few studies have been devoted to the analysis of Web traffic generated by Internet robots (Web bots). Moreover, the overwhelming majority of studies concern the traffic on non e-commerce websites. In this paper we address the problem of modeling a realistic arrival process of bots’ requests on an e-commerce Web server. Based on real…
Online Web Bot Detection Using a Sequential Classification Approach
2019
A significant problem nowadays is detection of Web traffic generated by automatic software agents (Web bots). Some studies have dealt with this task by proposing various approaches to Web traffic classification in order to distinguish the traffic stemming from human users' visits from that generated by bots. Most of previous works addressed the problem of offline bot recognition, based on available information on user sessions completed on a Web server. Very few approaches, however, have been proposed to recognize bots online, before the session completes. This paper proposes a novel approach to binary classification of a multivariate data stream incoming on a Web server, in order to recogn…
Efficient on-the-fly Web bot detection
2021
Abstract A large fraction of traffic on present-day Web servers is generated by bots — intelligent agents able to traverse the Web and execute various advanced tasks. Since bots’ activity may raise concerns about server security and performance, many studies have investigated traffic features discriminating bots from human visitors and developed methods for automated traffic classification. Very few previous works, however, aim at identifying bots on-the-fly, trying to classify active sessions as early as possible. This paper proposes a novel method for binary classification of streams of Web server requests in order to label each active session as “bot” or “human”. A machine learning appro…