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Volterra and Wiener series
(2011)
Volterra and Wiener series are two classes of polynomial representations of nonlinear systems. They are perhaps the best understood and most widely used nonlinear system representations in signal processing and system identification. A Volterra or Wiener representation can be thought of as a natural extension of the classical linear system representation. In addition to the convolution of the input signal with the system's impulse response, the system representation includes a series of nonlinear terms that contain products of increasing order of the input signal with itself. It can be shown that these polynomial extension terms allow for representing a large class of nonlinear systems which basically encompasses all systems with scalar outputs that are time-invariant and have noninfinite memory.
Characterization of NiTi Shape Memory Damping Elements designed for Automotive Safety Systems
(2014)
Actuator elements made of NiTi shape memory material are more and more known in industry because of their unique properties. Due to the martensitic phase change, they can revert to their original shape by heating when subjected to an appropriate treatment. This thermal shape memory effect (SME) can show a significant shape change combined with a considerable force. Therefore such elements can be used to solve many technical tasks in the field of actuating elements and mechatronics and will play an increasing role in the next years, especially within the automotive technology, energy management, power, and mechanical engineering as well as medical technology. Beside this thermal SME, these materials also show a mechanical SME, characterized by a superelastic plateau with reversible elongations in the range of 8%. This behavior is based on the building of stress-induced martensite of loaded austenite material at constant temperature and facilitates a lot of applications especially in the medical field. Both SMEs are attended by energy dissipation during the martensitic phase change. This paper describes the first results obtained on different actuator and superelastic NiTi wires concerning their use as damping elements in automotive safety systems. In a first step, the damping behavior of small NiTi wires up to 0.5 mm diameter was examined at testing speeds varying between 0.1 and 50 mm/s upon an adapted tensile testing machine. In order to realize higher testing speeds, a drop impact testing machine was designed, which allows testing speeds up to 4000 mm/s. After introducing this new type of testing machine, the first results of vertical-shock tests of superelastic and electrically activated actuator wires are presented. The characterization of these high dynamic phase change parameters represents the basis for new applications for shape memory damping elements, especially in automotive safety systems.
Cyberspace: a world at war. Our privacy, freedom of speech, and with them the very foundations of democracy are under attack. In the virtual world frontiers are not set by nations or states, they are set by those, who control the flows of information. And control is, what everybody wants.
The Five Eyes are watching, storing, and evaluating every transmission. Internet corporations compete for our data and decide if, when, and how we gain access to that data and to their pretended free services. Search engines control what information we are allowed - or want - to consume. Network access providers and carriers are fighting for control of larger networks and for better ways to shape the traffic. Interest groups and copyright holders struggle to limit access to specific content. Network operators try to keep their networks and their data safe from outside - or inside - adversaries.
And users? Many of them just don’t care. Trust in concepts and techniques is implicit. Those who do care try to take back control of the Internet through privacy-preserving techniques.
This leads to an arms race between those who try to classify the traffic, and those who try to obfuscate it. But good or bad lies in the eye of the beholder, and one will find himself fighting on both sides.
Network Traffic Classification is an important tool for network security. It allows identification of malicious traffic and possible intruders, and can also optimize network usage. Network Traffic Obfuscation is required to protect transmissions of important data from unauthorized observers, to keep the information private. However, with security and privacy both crumbling under the grip of legal and illegal black hat crackers, we dare say that contemporary traffic classification and obfuscation techniques are fundamentally flawed. The underlying concepts cannot keep up with technological evolution. Their implementation is insufficient, inefficient and requires too much resources.
We provide (1) a unified view on the apparently opposed fields of traffic classification and obfuscation, their deficiencies and limitations, and how they can be improved. We show that (2) using multiple classification techniques, optimized for specific tasks improves overall resource requirements and subsequently increases classification speed. (3) Classification based on application domain behavior leads to more accurate information than trying to identify communication protocols. (4) Current approaches to identify signatures in packet content are slow and require much space or memory. Enhanced methods reduce these requirements and allow faster matching. (5) Simple and easy to implement obfuscation techniques allow circumvention of even sophisticated contemporary classification systems. (6) Trust and privacy can be increased by reducing communication to a required minimum and limit it to known and trustworthy communication partners.
Our techniques improve both security and privacy and can be applied efficiently on a large scale. It is but a small step in taking back the Web.
Requirements Engineering in Business Analytics for Innovation and Product Lifecycle Management
(2014)
Considering Requirements Engineering (RE) in business analytics, involving market oriented management, computer science and statistics, may be valuable for managing innovation in Product Lifecycle Management (PLM). RE and business analytics can help maximize the value of corporate product information throughout the value chain starting with innovation management. Innovation and PLM must address 1) big data, 2) development of well-defined business goals and principles, 3) cost/benefit analysis, 4) continuous change management, and 5) statistical and report science. This paper is a positioning note that addresses some business case considerations for analytics project involving PLM data, patents, and innovations. We describe a number of research challenges in RE that addresses business analytics when high PLM data should be turned into a successful market oriented innovation management strategy. We provide a draft on how to address these research challenges.
Vortrag auf dem Doktorandenkolloquium des Kooperativen Promotionskollegs der HTWG, 09.07.2015
Vortrag auf dem Doktorandenkolloquium des Kooperativen Promotionskollegs der HTWG, 09.07.2015
RELOAD
(2015)
Vortrag auf dem Doktorandenkolloquium des Kooperativen Promotionskollegs der HTWG, 09.07.2015
Vortrag auf dem Doktorandenkolloquium des Kooperativen Promotionskollegs der HTWG, 09.07.2015