Bertram Nickolay – författare

In our modern information societies, we not only use and welcome computers; we are highly dependent upon them. There is a downside of this kind of progress, however. Computers are not 100% reliable. They are insecure. They are vulnerable to attackers. They can either be attacked directly, to disrupt their services, or they can be abused in clever ways to do the bidding of an attacker as a dysfunctional user.Decision-makers and experts alike always struggle with the amount of interdisciplinary knowledge needed to understand the nuts and bolts of modern information societies and their relation to security, the implications of technological or political progress or the lack thereof. This holds in particular for new challenges to come. These are harder to understand and to categorize; their development is difficult to predict. To mitigate this problem and to enable more foresight, The Secure Information Society provides an interdisciplinary spotlight onto some new and unfolding aspects of the uneasy relationship between information technology and information society, to aid the dialogue not only in its current and ongoing struggle, but to anticipate the future in time and prepare perspectives for the challenges ahead.

In our modern information societies, we not only use and welcome computers; we are highly dependent upon them. There is a downside of this kind of progress, however. Computers are not 100% reliable. They are insecure. They are vulnerable to attackers. They can either be attacked directly, to disrupt their services, or they can be abused in clever ways to do the bidding of an attacker as a dysfunctional user.Decision-makers and experts alike always struggle with the amount of interdisciplinary knowledge needed to understand the nuts and bolts of modern information societies and their relation to security, the implications of technological or political progress or the lack thereof. This holds in particular for new challenges to come. These are harder to understand and to categorize; their development is difficult to predict. To mitigate this problem and to enable more foresight, The Secure Information Society provides an interdisciplinary spotlight onto some new and unfolding aspects of the uneasy relationship between information technology and information society, to aid the dialogue not only in its current and ongoing struggle, but to anticipate the future in time and prepare perspectives for the challenges ahead.

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.

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.

This book constitutes the refereed proceedings of the 28th Symposium of the German Association for Pattern Recognition, DAGM 2006. The book presents 32 revised full papers and 44 revised poster papers together with 5 invited papers. Topical sections include image filtering, restoration and segmentation, shape analysis and representation, recognition, categorization and detection, computer vision and image retrieval, machine learning and statistical data analysis, biomedical data analysis, and more.

Flexible Fertigungs- und Produktionstechnik ist ohne Sensoren nicht mehr vorstellbar. Die notwendige Meßwerterfassung physikalischer Größen erfolgt durch Sensoren oder Sensorsysteme. Dieses Werk schildert die notwendigen Grundlagen zur Meßwerterfassung und beschreibt die Anwendungsfelder in der Produktion. Bauliche Ausführungsformen und Einbaubeispiele mit den Schwerpunkten Handhabungstechnik, Fügetechnik, Materialfluß sowie spanende Fertigung und Kunststoffverarbeitung liefern dem Leser reichlich praxisnahe Informationen. Die Autoren sind in der anwendungsnahen Forschung und Entwicklung tätig und können auf eine lange Praxis im Umgang mit Sensoren aufbauen.