Abraham / de Baets / Köppen Applied Soft Computing Technologies: The Challenge of Complexity

1. Auflage 2006
ISBN: 978-3-540-31662-6
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 34, 840 Seiten, eBook

Reihe: Advances in Intelligent and Soft Computing

SVMs have emerged as very successful pattern recognition methods in recent years [16]. SVMs have yielded superior performance in various applications such as; text categorization [15], and face detection [12], content-based image retrieval [6], and learning image similarity [4]. The motivation here is detection of suspicious bags in a security situation. The usual method for bomb personnel is to blow up a suspicious bag, and any explosives contained therein. However, if the bag contains chemical, biological or radiological canisters, this may lead to disastrous results. Furthermore, the “bl- up” method also destroys important clues such as fingerprints, type of explosive, detonators and other signatures of importance for forensic analysis. Extraction of the bag contents using telerobotics avoids these problems [8]. In a telerobotic system, it is advantageous to automate bag classification which is coupled to robotic tactics such as shaking out of the bags contents. For cooperative hum- robot interaction, in situations when autonomous capabilities fail, a human may be called in to distinguish the bag type. Here we focus on the autonomous operation of such a telerobotic system. In the autonomous mode, bags are classified by type using SVMs for the purpose of identifying initial manipulator grasp points. One side of the gripper must slide under the bag, and because of slippage, the grasp may fail. Thus, it is of importance to realize the type of bag, and the location of the opening before the grasp point assessment is made.

Zielgruppe

Research

Autoren/Hrsg.

Abraham, Ajith

de Baets, Bernard

Köppen, Mario

Koeppen, Mario

Nickolay, Bertram

Inhaltsverzeichnis

Part I Plenary Presentations.- Part II Classification and Clustering.- Part III Optimization.- Part IV Diagnosis and Fault Tolerance.- Part V Tracking and Surveillance.- Part VI Scheduling and Layout.- Part VII Complexity Management.- Part VIII Manufacturing and Production.- Part IX Signal Processing.- Part X Computer Security.- Part XI Bioinformatics.- Part XII Text Processing.- Part XIII Algorithm Design.- Part XIV Control.- Part XV Hybrid Intelligent Systems using Fuzzy Logic, Neural Networks and Genetic Algorithms.- Part XVI Recent Developments in Support Vector and Kernel Machines.- Part XVII Robotics.- Part XVIII Soft Computing and Hybrid Intelligent Systems in Product Design and Development.

Leseproben

Applying Fuzzy Sets to the SemanticWeb: The Problem of Retranslation (p. 3)

Ronald R. Yager
Machine Intelligence Institute, Iona College
New Rochelle, NY 10801

Abstract: We discuss the role of Zadeh's paradigmof computing with words on the semantic web We describe thethree important steps in using computing with words. We focuson the retranslation step, selecting a term from our prescribedvocabulary to express information represented using fuzzy sets. A number of criteria of concern in this retranslation processare introduced. Some of these criteria can be seen to correspondto a desire to accurately reflect the given information. Othercriteria may correspond to a desire, on the part provider ofthe information, to give a particular perception or "spin."We discuss some methods for combining these criteria to evaluatepotential retranslations.

Keywords: Computing with Words, Fuzzy Sets, Linguistic Approximation

1. Computing with Words and the Semantic Web

The Semantic Web is invisioned as an extension of the currentweb in which information is given well-defined meaning and semantics,better enabling computers and people to work in cooperation. Among its goals is a humanlike automated manipulation of theknowledge contained on the web. While computers are good atprocessing information, they have no understanding of the meaningand semantics of the content which greatly hinders human likemanipulation. The fulfillment of the vision of the SemanticWeb requires tools that enable the computational representationof knowledge that emulates human deep understanding. Hence enablingintelligent information processing. Fuzzy subset theory andthe related paradigm of computing with words [1-3] providetools of this nature and hence will help to enable the automatedmanipulation of human knowledge.