Robust vehicle suspension system by converting active and passive control of a vehicle to semi-active control ystem analytically

This research article deals with a simplified translational model of an automotive suspension system which is constructed by considering the translation motion of one wheel of a car. Passive Vehicle Suspension System is converted into Semi Active Vehicle System. Major advantage achieved by this system is that it adjusts the damping of the suspension system without the application of any actuator by using MATLAB® simulations. The semi-active control is found to control the vibration of suspension system very well

The impact of sensor positioning on the array manifold

Published versio

Manifold studies of nonlinear antenna array geometries

Published versio

An Unsupervised Technique to Extract Information from Semi-structured Web Pages

We propose a technique that takes two or more web pages generated by the same server-side template and tries to learn a regular expression that represents it and helps extract relevant information from similar pages. Our experimental results on real-world web sites demonstrate that our technique outperforms others in terms of both effectiveness and efficiency and is not affected by HTML errors.Ministerio de Ciencia y Tecnología TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010- 21744Ministerio de Economía, Industria y Competitividad TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-EMinisterio de Economía y Competitividad TIN2011-15497-

A Survey on Region Extractors from Web Documents

Extracting information from web documents has become a research area in which new proposals sprout out year after year. This has motivated several researchers to work on surveys that attempt to provide an overall picture of the many existing proposals. Unfortunately, none of these surveys provide a complete picture, because they do not take region extractors into account. These tools are kind of preprocessors, because they help information extractors focus on the regions of a web document that contain relevant information. With the increasing complexity of web documents, region extractors are becoming a must to extract information from many websites. Beyond information extraction, region extractors have also found their way into information retrieval, focused web crawling, topic distillation, adaptive content delivery, mashups, and metasearch engines. In this paper, we survey the existing proposals regarding region extractors and compare them side by side.Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08- TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010-21744Ministerio de Economía, Industria y Competitividad TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-

Information Extraction Framework

The literature provides many techniques to infer rules that can be used to configure web information extractors. Unfortunately, these techniques have been developed independently, which makes it very difficult to compare the results: there is not even a collection of datasets on which these techniques can be assessed. Furthermore, there is not a common infrastructure to implement these techniques, which makes implementing them costly. In this paper, we propose a framework that helps software engineers implement their techniques and compare the results. Having such a framework allows comparing techniques side by side and our experiments prove that it helps reduce development costs.Ministerio de Ciencia e Innovación TIN2010-21744-C02-01Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010-09988-

A Reference Architecture to Devise Web Information Extractors

The Web is the largest repository of human-friendly information. Unfortunately, web information is embedded in formatting tags and is surrounded by irrelevant information. Researchers are working on information extractors that allow transforming this information into structured data for its later integration into automated processes. Devising a new information extraction technique requires an array of tasks that are specific to this technique and many tasks that are actually common between all techniques. The lack of a reference architectural proposal in the literature to guide software engineers in the design and implementation of information extractors, amounts to little reuse and the focus is usually blurred because of irrelevant details. In this paper, we present a reference architecture to design and implement rule learners for information extractors. We have implemented a software framework to support our architecture, and we have validated it by means of four case studies and a number of experiments that prove that our proposal helps reduce development costs significantly.Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010-21744Ministerio de Economía, Industria y Competitividad TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-

Trinity: On Using Trinary Trees for Unsupervised Web Data Extraction

Web data extractors are used to extract data from web documents in order to feed automated processes. In this article, we propose a technique that works on two or more web documents generated by the same server-side template and learns a regular expression that models it and can later be used to extract data from similar documents. The technique builds on the hypothesis that the template introduces some shared patterns that do not provide any relevant data and can thus be ignored. We have evaluated and compared our technique to others in the literature on a large collection of web documents; our results demonstrate that our proposal performs better than the others and that input errors do not have a negative impact on its effectiveness; furthermore, its efficiency can be easily boosted by means of a couple of parameters, without sacrificing its effectiveness.Ministerio de Ciencia y Tecnología TIN2007-64119Junta de Andalucía P07- TIC-2602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010- 21744Ministerio de Economía, Industria y Competitividad TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-EMinisterio de Economía y Competitividad TIN2011-15497-

ARIEX: Automated ranking of information extractors

Information extractors are used to transform the user-friendly information in a web document into structured information that can be used to feed a knowledge-based system. Researchers are interested in ranking them to find out which one performs the best. Unfortunately, many rankings in the literature are deficient. There are a number of formal methods to rank information extractors, but they also have many problems and have not reached widespread popularity. In this article, we present ARIEX, which is an automated method to rank web information extraction proposals. It does not have any of the problems that we have identified in the literature. Our proposal shall definitely help authors make sure that they have advanced the state of the art not only conceptually, but from an empirical point of view; it shall also help practitioners make informed decisions on which proposal is the most adequate for a particular problem.Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010-21744Ministerio de Economía, Industria y Competitividad TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-EMinisterio de Economía y Competitividad TIN2011-15497-EMinisterio de Economía y Competitividad TIN2013-40848-