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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
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(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
In biomechanics laboratories the ground reaction force time histories of the foot-fall of persons are usually measured using a force plate. The accelerations of the floor, in which the force plate is embedded, have to be limited, as they may influence the accuracy of the force measurements. For the numerical simulation of vibrations induced by humans in biomechanical laboratories, loading scenarios are defined. They include continuous motions of persons (walking, running) as well as jumps, typical for biomechanical investigations on athletes. The modeling of floors has to take into account the influence of floor screed in case of portable force plates. Criteria for the assessment of the measuring error provoked by floor vibrations are given. As an example a floor designed to accommodate a force platform in a biomechanical laboratory of the University Hospital in Tübingen, Germany, has been investi-gated for footfall induced vibrations. The numerical simulation by a finite element analysis has been validated by field measurements. As a result, the measuring error of the force plate installed in the laboratory is obtained for diverse scenarios.
This chapter contains three advanced topics in model order reduction (MOR): nonlinear MOR, MOR for multi-terminals (or multi-ports) and finally an application in deriving a nonlinear macromodel covering phase shift when coupling oscillators. The sections are offered in a preferred order for reading, but can be read independently.
The proposed approach applies current unsupervised clustering approaches in a different dynamic manner. Instead of taking all the data as input and finding clusters among them, the given approach clusters Holter ECG data (long-term electrocardiography data from a holter monitor) on a given interval which enables a dynamic clustering approach (DCA). Therefore advanced clustering techniques based on the well known Dynamic Time Warping algorithm are used. Having clusters e.g. on a daily basis, clusters can be compared by defining cluster shape properties. Doing this gives a measure for variation in unsupervised cluster shapes and may reveal unknown changes in healthiness. Embedding this approach into wearable devices offers advantages over the current techniques. On the one hand users get feedback if their ECG data characteristic changes unforeseeable over time which makes early detection possible. On the other hand cluster properties like biggest or smallest cluster may help a doctor in making diagnoses or observing several patients. Further, on found clusters known processing techniques like stress detection or arrhythmia classification may be applied.
The problem of vessel collisions or near-collision situations on sea, often caused by human error due to incomplete or overwhelming information, is becoming more and more important with rising maritime traffic. Approaches to supply navigators and Vessel Traffic Services with expert knowledge and suggest trajectories for all vessels to avoid collisions, are often aimed at situations where a single planner guides all vessels with perfect information. In contrast, we suggest a two-part procedure which plans trajectories using a specialised A* and negotiates trajectories until a solution is found, which is acceptable for all vessels. The solution obeys collision avoidance rules, includes a dynamic model of all vessels and negotiates trajectories to optimise globally without a global planner and extensive information disclosure. The procedure combines all components necessary to solve a multi-vessel encounter and is tested currently in simulation and on several test beds. The first results show a fast converging optimisation process which after a few negotiation rounds already produce feasible, collision free trajectories.
To evaluate the quality of a person's sleep it is essential to identify the sleep stages and their durations. Currently, the gold standard in terms of sleep analysis is overnight polysomnography (PSG), during which several techniques like EEG (eletroencephalogram), EOG (electrooculogram), EMG (electromyogram), ECG (electrocardiogram), SpO2 (blood oxygen saturation) and for example respiratory airflow and respiratory effort are recorded. These expensive and complex procedures, applied in sleep laboratories, are invasive and unfamiliar for the subjects and it is a reason why it might have an impact on the recorded data. These are the main reasons why low-cost home diagnostic systems are likely to be advantageous. Their aim is to reach a larger population by reducing the number of parameters recorded. Nowadays, many wearable devices promise to measure sleep quality using only the ECG and body-movement signals. This work presents an android application developed in order to proof the accuracy of an algorithm published in the sleep literature. The algorithm uses ECG and body movement recordings to estimate sleep stages. The pre-recorded signals fed into the algorithm have been taken from physionet1 online database. The obtained results have been compared with those of the standard method used in PSG. The mean agreement ratios between the sleep stages REM, Wake, NREM-1, NREM-2 and NREM-3 were 38.1%, 14%, 16%, 75% and 54.3%.
Technology-based ventures provide an important route for successful technology transfer [1], [2]. Their founders are supported in successful technology commercialization by innovation intermediaries [3]. Accordingly, the performance of an innovation system, at least to some extent, depends on the efficiency of these intermediaries in terms of the impact of their scarce resources on the survival and growth of technology-based ventures. To increase their efficiency, intermediaries typically optimize their "intake" by requesting a formal business plan to base their selection on as a hygiene factor [4]-[7]. Thus, some scholars argue that written business plans show significant distortion as being produced only to attract support from innovation intermediaries [6], [8]. Accordingly, they rarely serve for these addressees as a source of information for analyzing the strengths and weaknesses of ventures, in order to derive actionable conclusions and more effectively support ventures [9], [10]. Addressees search for different indicators in business plans for their evaluation [11]. The descriptions of these indicators only evince little empirical proof for the performance of technology-based venture's [8], [12]. This gap is herein addressed, in contrast to the lacking empirical insight, as the most frequently produced artifact of early-stage technology ventures is at the same time a written business plan [10], [13]. This paper addresses this gap by conceptualizing transaction relations described in the written business plan as a means for working around the inevitable inaccuracies and uncertainties that delimit the explanatory abilities [14] of the snapshot model [10] presented by a business plan. Using a qualitative content analysis, we derive from the descriptions of transaction relations in a written business plan valid indicators for the maturity of the venture's value-network in different dimensions [15]. To this extent, this paper presents the findings from a pre-study that was conducted based on a sample of forty business plans from an overall population of 800 business plans in a longitudinal sample from one of Europe's most active innovation systems, the regional State of Baden-Württemberg. Such findings may be used by innovation intermediaries to enhance their efficiency, by enabling these to not only derive individual support strategies for business acceleration but also to analyze the impact of support measures by reliably monitoring maturity progress in venture activities.