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Shadow information technology systems (SITS) coexist with formal enterprise systems in organisations. SITS pose risks but also increase flexibility of business units. Practice shows that SITS emerge, despite that Enterprise Architecture Management (EAM) aims at controling all IT systems in an organization. Studies acknowledge this problem in general. However, they neither show the specific influencing areas of SITS nor provide approaches to address them. To close this gap, we use a literature review to analyse examples of practical SITS and their interference with EAM concerns. Thus, we find that they hinder especially transparency, reduction of EA complexity and governance. Research has focused on achieving transparency, governing the evolution of the EA but lacks strategies for reducing complexity. This study contributes to research and practice by uncovering the main influencing areas of SITS on EAM, as well as by laying a foundation for future research on this topic.
One major realm of Condition Based Maintenance is finding features that reflect the current health state of the asset or component under observation. Most of the existing approaches are accompanied with high computational costs during the different feature processing phases making them infeasible in a real-world scenario. In this paper a feature generation method is evaluated compensating for two problems: (1) storing and handling large amounts of data and (2) computational complexity. Both aforementioned problems are existent e.g. when electromagnetic solenoids are artificially aged and health indicators have to be extracted or when multiple identical solenoids have to be monitored. To overcome those problems, Compressed Sensing (CS), a new research field that keeps constantly emerging into new applications, is employed. CS is a data compression technique allowing original signal reconstruction with far fewer samples than Shannon-Nyquist dictates, when some criteria are met. By applying this method to measured solenoid coil current, raw data vectors can be reduced to a way smaller set of samples that yet contain enough information for proper reconstruction. The obtained CS vector is also assumed to contain enough relevant information about solenoid degradation and faults, allowing CS samples to be used as input to fault detection or remaining useful life estimation routines. The paper gives some results demonstrating compression and reconstruction of coil current measurements and outlines the application of CS samples as condition monitoring data by determining deterioration and fault related features. Nevertheless, some unresolved issues regarding information loss during the compression stage, the design of the compression method itself and its influence on diagnostic/prognostic methods exist.
Successful project management (PM), as one of the most important key competences in the western-oriented working world, is mainly influenced by experience and social skills. As a direct impact on PM training, the degree of practice and reality is crucial for the application of lessons learned in a challenging everyday work life. This work presents a recursive approach that adapts well-known principles of PM itself for PM training. Over three years, we have developed a concept and an integrated software system that support our PM university courses. Stepwise, it transfers theoretical PM knowledge into realistic project phases by automatically adjusting to the individual learning progress. Our study reveals predictors such as degrees of collaboration or weekend work as vital aspects in the PM training progress. The chosen granularity of project phases with variances in different dimensions makes our model a canonical incarnation of seamless learning.
Corporate entrepreneurship (CE) supports the strategic renewal of established companies. Corporate venturing represents one key concept of CE that supports companies to strengthen their innovation capabilities. For the successful implementation of corporate ventures dual structures are recommended. The question, how the interface should be designed, plays a crucial role. Although it seems to be an important factor, this aspect requires further attention. One relevant element of the interface design are the different roles of the individuals that are interacting within the interface. This study is based on nine interviews that are representing six internal corporate ventures within one large German corporate from the ICT sector. The results that were mirrored with short case studies of 25 additional companies of the data sample, contribute to a better understanding of the interface design by adding insights about roles in corporate entrepreneurship. This deeper understanding about roles allows to draw conclusions on the interface design from a structural point of view.
This work proposes a decoder implementation for high-rate generalized concatenated (GC) codes. The proposed codes are well suited for error correction in flash memories for high reliability data storage. The GC codes are constructed from inner extended binary Bose-Chaudhuri-Hocquenghem (BCH) codes and outer Reed-Solomon (RS) codes. The extended BCH codes enable high-rate GC codes. Moreover, the decoder can take advantage of soft information. For the first three levels of inner codes we propose an optional Chase soft decoder. In this work, the code construction is explained and a decoder architecture is presented. Furthermore, area and throughput results are discussed.
In the automotive industry a strong effort has been undertaken to reduce the weight of modern vehicles. In order to reduce the energy consumption and to improve the environmental sustainability, the importance of weight reduction activities is even growing faster. As lightweight designing is becoming more and more expensive and show less potential savings, new approaches are needed. One promising technology could be the use of shape memory elements. In the last years a lot of potential application possibilities were presented, demonstrating the benefit of these functional elements in automotive design solutions: they often reduce complexity, weight and design space of an actuation device and enable new functions. In addition they work silently and are therefore ideally suitable for comfort applications in the passenger cabin. Because of the current trend to electric vehicle the hitherto existing drawback of a high electrical energy consumption of shape memory actuators in some design proposals is not given any more.
Leadership in a global world
(2017)
We present an analysis of how to determine security requirements for software that controls routing decisions in the distribution of discrete physical goods. Requirements are derived from stakeholder interests and threat scenarios. Three deployment scenarios are discussed: cloud and hybrid deployment as well as on-premise installation for legacy sites.
Business models (BM) are the logic of a firm on how to create, deliver and capture value. Business model innovation (BMI) is essential to organisations for keeping competitive advantage. However, the existence of barriers to BMI can impact the success of a corporate strategic alignment. Previous research has examined the internal barriers to business model innovation, however there is a lack of research on the potential external barriers that could potentially inhibit business model innovation. Drawn from an in-depth case study in a German medium size engineering company in the equestrian sports industry, we explore both internal and external barriers to business model innovation. BMI is defined as any change in one or more of the nine building blocks of the Business Model Canvas; customer segment, value propositions, channels, customer relation, revenue streams, key resources, key activities, key partners, cost structure [1]. Our results show that barriers to business model innovation can be overcome by the deployment of organisational learning mechanisms and the development of an open network capability.
Stress and physical activities are important aspects of life of people. Body reactions on stress and on physical activities can be very similar but long-term stress leads to diseases and damages the body. Currently there is no method to differentiate easily and clearly between these two aspects in a time slot. We have confronted this problem while developing a mobile system for detection and analysis of stress. This paper presents an approach, which uses a long-term monitor with ECG/EKG capabilities and analysis of the heart rate data that is extracted from the device. The focus of the work is to find characteristics that are useful for differentiation between physical activity and stress.
Many secure software development methods and tools are well-known and understood. Still, the same software security vulnerabilities keep occurring. To find out if new source code patterns evolved or the same patterns are reoccurring, we investigate SQL injections in PHP open source projects. SQL injections are well-known and a core part of software security education. For each common part of SQL injections, the source code patterns are analysed. Examples are pointed out showing that developers had software security in mind, but nevertheless created vulnerabilities. A comparison to earlier work shows that some categories are not found as often as expected. Our main contribution is the categorization of source code patterns.
We examine to what extent a transaction relation-based value network maturity status of New Technology-Based Firms (NTBFs) is related to their survival. A specific challenge of NTBFs is their lack of market-orientation, which is why the maturity of the ties they form towards the market in terms of customers, financiers, personnel and partners is supposed to be a strong indicator for survival. We analyze a sample of 170 NTBFs by capturing their value network status from business plans and defining their survival status using secondary research. Simple statistical tests and regressions suggest that the official registration of the business is a pre-step for survival that requires industry-specific value network dimension strengths. A sub-sample survival analysis shows that for all NTBFs that have reached registration, regardless of their industry, a stronger customer value network maturity dimension prevents from failure and is thus a significant predictor for survival. Moreover, the analyses partly support the idea that NTBFs from the IT sector are less dependent on a strong value network in the financier dimension to survive. The results are of relevance for both practitioners and researchers in the innovation system: a better understanding of the factors impacting on NTBF survival can help to provide more tailored support services for young firms, increase the effectiveness of resource allocations, and provide a basis for further research.
The evolution of strain induced martensite in austenitic stainless steel AISI 304 was investigated in a rolling contact on a two-discs-tribometer. The effects of surface roughness, slip and normal force as well as the number of load cycles were examined. In comparison to the investigations of martensitic phase transformation during cold rolling, the applied stresses are considerably lower. The formation of strain induced martensite was detected in-situ by means of a FERITSCOPE MP30 and ex-situ by optical microscopy after etching with Kane etchant. Both number of load cycles and magnitude of normal force appeared to be the main influencing factors regarding strain induced martensitic evolution in low stress rolling contacts.
Sleep quality and in general, behavior in bed can be detected using a sleep state analysis. These results can help a subject to regulate sleep and recognize different sleeping disorders. In this work, a sensor grid for pressure and movement detection supporting sleep phase analysis is proposed. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this project is a non-invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable Actigraphy devices tends to be uncomfortable. Besides this fact, they are also very expensive. The system represented in this work classifies respiration and body movement with only one type of sensor and also in a non-invasive way. The sensor used is a pressure sensor. This sensor is low cost and can be used for commercial proposes. The system was tested by carrying out an experiment that recorded the sleep process of a subject. These recordings showed the potential for classification of breathing rate and body movements. Although previous researches show the use of pressure sensors in recognizing posture and breathing, they have been mostly used by positioning the sensors between the mattress and bedsheet. This project however, shows an innovative way to position the sensors under the mattress.
Industry 4.0
(2017)
Deep 3D
(2017)
As a result of increasing needs and shrinking resources, aquaculture is gaining progressively significance in the recent years. Ecological issues such as negative effects on the ecological system due to the high fish density in the farms, the use of copper as antifouling strategy etc. are very present, particularly regarding the increasing number of fish going to be produced in farms in the future. Current trends focus on larger farms operated offshore. To make these farms working safe and economical, reliability has to be improved and maintenance costs need to be reduced. Also, alternatives with higher mechanical strength compared to current textile net materials as well as common metal wires might be necessary. In the last years, a new net system made of high strength duplex stainless steel wires with environmentally friendly antifouling properties suitable for offshore applications was developed. The first nets are operating for one year now as predator protection (i.e. seals) for fish farms and show a good performance in cleaning capability and predator protection. But in the real usage, some corrosion effects in the contact points of the net made of duplex stainless steel 1.4362 occur which were not observed in preliminary tests in laboratory and at different test sites around the world. These corrosion effects endanger the sustainable success of the net system. In this work, the observed corrosion effects are investigated. A laboratory test, which simulates the movement in the contact points of the net, was developed. Two pieces of wire are bent in the middle and get stucked into each other. One wire is fixed at both ends and the second wire is fixed on one end. On the other end, a circular movement with 1-2 rps and a 1 cm displacement is applied. The movement generates friction between the wires and the passive layer will be locally damaged. When the movement stops, a repassivation starts. The passivity breakdown and the repassivation were measured with electrochemical techniques. During the friction phase, when the surface will be activated, the open circuit potential breaks down. When the friction stops, the OCP increases. Between the movement phases, measurements of critical pitting potential were done. Thereby the quality of repassivation was investigated. The tests were done in a 3% sodium chloride solution. Different temperatures were tested as well as the influence of air saturation and low oxygen content.
Poster
Steps to the stage
(2017)
The binary asymmetric channel (BAC) is a model for the error characterization of multi-level cell (MLC) flash memories. This contribution presents a joint channel and source coding approach improving the reliability of MLC flash memories. The objective of the data compression algorithm is to reduce the amount of user data such that the redundancy of the error correction coding can be increased in order to improve the reliability of the data storage system. Moreover, data compression can be utilized to exploit the asymmetry of the channel to reduce the error probability. With MLC flash memories data compression has to be performed on block level considering short data blocks. We present a coding scheme suitable for blocks of 1 kilobyte of data.
Error correction coding based on soft-input decoding can significantly improve the reliability of flash memories. Such soft-input decoding algorithms require reliability information about the state of the memory cell. This work proposes a channel model for soft-input decoding that considers the asymmetric error characteristic of multi-level cell (MLC) and triple-level cell (TLC) memories. Based on this model, an estimation method for the channel state information is devised which avoids additional pilot data for channel estimation. Furthermore, the proposed method supports page-wise read operations.
Design of tension components
(2017)
The paper gives an introduction as well as background information on proposed changes and amendments in EN 1993-1-11 “Design of structures with tension components”, implemented during the ongoing revision. Due to some deficits in the currently applicable standard this revision is not only limited to some restructuring and editorial changes, but includes also major technical changes in the following fields: safety concept and structural analysis, actions and loads, robustness and rep-arability, design of tension components and design of clamps and saddles.
To assess the quality of a person’s sleep, it is essential to examine the sleep behaviour by identifying the several sleep stages, their durations and sleep cycles. The established and gold standard procedure for sleep stage scoring is overnight polysomnography (PSG) with the Rechtschaffen and Kales (R-K) method. Unfortunately, the conduct of PSG is timeconsuming and unfamiliar for the subjects and might have an impact of the recorded data. To avoid the disadvantages with PSG, it is important to make further investigations in low-cost home diagnostic systems. For this intention it is necessary to find suitable bio vital parameters for classifying sleep stages without any physical impairments at the same time.
Due to the promising results in several publications we want to analyse existing methods for sleep stage classification based on the parameters body movement,
heartbeat and respiration. Our aim was to find different behaviour patterns in the several sleep stages. Therefore, the average values of 15 wholenight PSG recordings -obtained from the ‘DREAMS Subjects Database’- where analysed in the light of heartbeat, body movement and respiration with 10 different methods.
Growth is a key indicator of the prosperity of an economy. In today's Germany the " Gründerzeit " still describes a period of enormous economic growth. Factors that lead to growth haven't been investigated in the context of the different life cycle stages of early-stage technology ventures so far. This paper proposes a model of early-stage ventures' growth based on factors. From a theoretical angle, we look at the business from the market-based view (MBV) and the resource-based view (RBV) on strategy in the longitudinal perspective of the business life cycle. With this view we get to know what are the stage specific needs and processes of new technology based ventures in order to provide appropriate support. We tested different potential growth indicators for the model with a questionnaire-based survey which was answered by 68 high-tech entrepreneurs. The results suggest that growth factors are stage specific in their relevance. While leading to growth in one stage, certain factors evince no or even negative influence on growth in other stages. Moreover, RBV factors as seen more relevant for the growth than the MBV factors. Further research requires a large and representative population to validate the results. Keywords:-growth factors, early-stage ventures, market-based view, resources based view.
Validity of the business model is a key indicator for buying into ventures in the early-stage. Business models of early-stage ventures decrease in validity when developing the business over the progressing stages of the business life-cycle. By doing so, the ventures are validating their business model when building transaction relationships to the surrounding value network. In prior research, we developed a research design based on existing business innovation proposals (onepager, pitch decks, business plans) that is assumed to evaluate the status of business model validation. The core hypothesis of the research design is that transaction relations represent a strong anchor between the business model and the business reality, thus providing information on the business model validity. In this research, we test this hypothesis by designing and analyzing a survey that was directed to founders taking part in a business plan competition. We compared the relationships described in the submitted business plans to the relations explicitely stated in the follow-up questionnaire. We identified that the described relations to customers, investors, and people (human resources) match the relationships expressed in questionnaires quite well. A significant disagreement, however, exists in the relationships to suppliers. We conclude that there is still a theoretical and empirical gap that leads to disagreement between business plans and reality in the group of suppliers.
This work investigates data compression algorithms for applications in non-volatile flash memories. The main goal of the data compression is to minimize the amount of user data such that the redundancy of the error correction coding can be increased and the reliability of the error correction can be improved. A compression algorithm is proposed that combines a modified move-to-front algorithm with Huffman coding. The proposed data compression algorithm has low complexity, but provides a compression gain comparable to the Lempel-Ziv-Welch algorithm.
In this paper, a gain-scheduled nonlinear control structure is proposed for a surface vessel, which takes advantage of extended linearisation techniques. Thereby, an accurate tracking of desired trajectories can be guaranteed that contributes to a safe and reliable water transport. The PI state feedback control is extended by a feedforward control based on an inverse system model. To achieve an accurate trajectory tracking, however, an observer-based disturbance compensation is necessary: external disturbances by cross currents or wind forces in lateral direction and wave-induced measurement disturbances are estimated by a nonlinear observer and used for a compensation. The efficiency and the achieved tracking performance are shown by simulation results using a validated model of the ship Korona at the HTWG Konstanz, Germany. Here, both tracking behaviour and rejection of disturbance forces in lateral direction are considered.
The method of signal injection is investigated for position estimation of proportional solenoid valves. A simple observer is proposed to estimate a position-dependent parameter, i.e. the eddy current resistance, from which the position is calculated analytically. Therefore, the relationship of position and impedance in the case of sinusoidal excitation is accurately described by consideration of classical electrodynamics. The observer approach is compared with a standard identification method, and evaluated by practical experiments on an off-the-shelf proportional solenoid valve.
Several possibilities of tests under load on a chassis dynamometer are presented. Consumption measurements according standard driving cycles as the New European Drive Cycle (NEDC) and Worldwide harmonized light duty test procedure/cycle (WLTP/WLTC) make special attention to the observance of the regulations necessary. The rotational masses of inertia and the load depending on velocity have to match the required values. Load tests as well allow the determination of the maximum acceleration in the current gear and the slippage of the driven wheels.
The aim of the paper is to present the simulation of the sweeping process based on a mathematical model that includes the drag force, the lift force, the sideway force, and the gravity. At the beginning, it is presented a short history of the street sweepers, some considerations about the sweeping process and the parameters of the sweeping process. Considering the developed model, in Matlab there is done some simulation for the trajectory of a spherical pebble. The obtained results are presented in graphical shape.
The magneto-mechanical behavior of magnetic shape memory (MSM) materials has been investigated by means of different simulation and modeling approaches by several research groups. The target of this paper is to simulate actuators driven by MSM alloys and to understand the MSM element behavior during actuation, which shall lead to an increased performance of the actuator. It is shown that internal and external stresses should be taken into consideration using numerical computation tools for magnetic fields in an efficient way.
Stress is recognized as a predominant disease with raising costs for rehabilitation and treatment. Currently there several different approaches that can be used for determining and calculating the stress levels. Usually the methods for determining stress are divided in two categories. The first category do not require any special equipment for measuring the stress. This category useless the variation in the behaviour patterns that occur while stress. The core disadvantage for the category is their limitation to specific use case. The second category uses laboratories instruments and biological sensors. This category allow to measure stress precisely and proficiently but on the same time they are not mobile and transportable and do not support real-time feedback. This work presents a mobile system that provides the calculation of stress. For achieving this, the of a mobile ECG sensor is analysed, processed and visualised over a mobile system like a smartphone. This work also explains the used stress measurement algorithm. The result of this work is a portable system that can be used with a mobile system like a smartphone as visual interface for reporting the current stress level.
Stress is a recognized as a predominant disease with growing costs of treatment. The approach presented here is aimed to detect stress using a light weighted, mobile, cheap and easy to use system. The result shows that stress can be detected even in case a person’s natural bio vital data is out of the main range. The system enables storage of measured data, while maintaining communication channels of online and post-processing.
Smart factory and education
(2016)
The introduction of cyber physical systems into production companies is highly changing working conditions and processes as well as business models. In practice a growing discrepancy between big and small respectively medium-sized companies can be observed. Bridging that gap a university smart factory is introduced to give that companies a platform to trial, educate employees and access consultancy. Realizing the smart factory a highly integrated, open and standardized automation concept is shown comprising single devices, production lines up to a higher automation system maintaining a community or business models.
In this paper we provide a performance analysis framework for wireless industrial networks by deriving a service curve and a bound on the delay violation probability. For this purpose we use the (min,×)stochastic network calculus as well as a recently presented recursive formula for an end-to-end delay bound of wireless heterogeneous networks. The derived results are mapped to WirelessHART networks used in process automation and were validated via simulations. In addition to WirelessHART, our results can be applied to any wireless network whose physical layer conforms the IEEE 802.15.4 standard, while its MAC protocol incorporates TDMA and channel hopping, like e.g. ISA100.11a or TSCH-based networks. The provided delay analysis is especially useful during the network design phase, offering further research potential towards optimal routing and power management in QoS-constrained wireless industrial networks.
These days computer analysis of ECG (Electrocardiograms) signals is common. There are many real-time QRS recognition algorithms; one of these algorithms is Pan-Tompkins Algorithm. Which the Pan-Tompkins Algorithm can detect QRS complexes of ECG signals. The proposed algorithm is analysed the data stream of the heartbeat based on the digital analysis of the amplitude, the bandwidth, and the slope. In addition to that, the stress algorithm compares whether the current heartbeat is similar or different to the last heartbeat after detecting the ECG signals. This algorithm determines the stress detection for the patient on the real-time. In order to implement the new algorithm with higher performance, the parallel programming language CUDA is used. The algorithm determines stress at the same time by determining the RR interval. The algorithm uses a different function as beat detector and a beat classifier of stress.
Realistic traffic modeling plays a key role in efficient Dynamic Spectrum Access (DSA) which is considered as enabler for the employment of wireless technologies in critical industrial automation applications (IAA). The majority of models of spectrum usage are not suitable for this specific use case as they are based on measurement campaigns conducted in urban or controlled laboratory environments. In this work we present a time-domain traffic model for industrial communication in the 2.4 GHz industrial, scientific, medical (ISM) band based on measurements in an industrial automotive production site. As DSA is usually implemented on Software Defined Radios (SDR), our measurement campaign is based on SDR platforms rather than sophisticated spectrum analyzers. We show through the estimation of the Hurst parameter that industrial wireless traffic possesses inherent self-similarity that could be exploited for efficient DSA. We also show that wireless traffic could be modeled as a semi-Markov model with channel on and off durations Log-normally and Pareto distributed, respectively. We finally estimate the parameters of the derived models using Maximum Likelihood estimation.
Present demographic change and a growing population of elderly people leads to new medical needs. Meeting these with state of the art technology is as a consequence a rapidly growing market. So this work is aimed at taking modern concepts of mobile and sensor technology and putting them in a medical context. By measuring a user’s vital signs on sensors which are processed on a Android smartphone, the target system is able to determine the current health state of the user and to visualize gathered information. The system also includes a weather forecasting functionality, which alerts the user on possibly dangerous future meteorological events. All information are collected centrally and distributed to users based on their location. Further, the system can correlate the client-side measurement of vital signs with a server-side weather history. This enables personalized forecasting for each user individually. Finally, a portable and affordable application was developed that continuously monitors the health status by many vital sensors, all united on a common smartphone.
A lot of procedures for estimating the spool position in linear electromagnetic actuators using voltage and current measurements only, can be found in the literature. Subject to the accuracy of the estimated spool position some achieve better, some worse results. However, in almost every approach hysteresis has a huge impact on the estimation accuracy that can be achieved. Regardless whether these effects are caused by magnetic or mechanical hysteresis, they will limit the accuracy of the position estimate, if not taken into account. In this paper, a model is introduced which covers the hysteresis effects as well as other nonlinear ities occurring in estimated position-dependent parameters. A classical Preisach model is deployed first, which is then adjusted by using novel elementary preceding Relay-Operators. The resulting model for the estimated position-dependent parameters including the adjusted Preisach model can be easily applied to position estimation tasks. It is shown that the considered model distinctly improves the accuracy for the spool position estimate, while it is kept as simple as possible for real-time implementation reasons.
When mobile devices at the network edge want to communicate with each other, they too often depend on the availability of faraway resources. For direct communication, feasible user-friendly service discovery is essential. DNS Service Discovery over Multicast DNS (DNS-SD/mDNS) is widely used for configurationless service discovery in local networks, due inno small part to the fact that it is based on the well establishedDNS, and efficient in small networks. In our research, we enhance DNS-SD/mDNS providing versatility, user control, efficiency, and privacy, while maintaining the deployment simplicity and backward compatibility. These enhancements are necessary to make it a solid, flexible foundationfor device communication in the edge of the Internet. In this paper, we focus on providing multi-link capabilities and scalable scopes for DNS-SD while being mindful of both user-friendliness and efficiency. We propose DNS-SD over StatelessDNS (DNS-SD/sDNS), a solution that allows configurationless service discovery in arbitrary self-named scopes - largely independentof the physical network layout - by leveraging ourStateless DNS technique and the Raft consensus algorithm.
Three-level inverters are used in electrical drive systems, as grid infeed inverter in PV power plants or as active power line filters. Up to now so called hard switching topologies have been used. A new 'Soft Switching Three Level Inverter (S3L Inverter)' which is now available provides reduced switching losses and higher efficiency. In this paper the S3L inverter is compared with a hard switching T-type inverter topology (H3L inverter). S3L inverters provide higher efficiency and additionally advantages in electromagnetic compatibility due to the soft switching performance, especially when using the 'Super Soft Switching Three Level Inverter (SS3L Inverter)'.
The development of native user interface components is a time consuming and repetitive process, especially for quite simple components like text fields in a form. In order to save time during development an approach is presented in this paper, abstracting the description of the elements into separate files independent from the source code. With aspects from generative and model-driven approaches this leads to simple reusable UI components without the need of deep knowledge in native programming languages.
TU Darmstadt HUMVIB-Bridge
(2016)
The simulation of the human-induced vibrations of lightweight footbridges is in general a complex problem where the dynamics of the pedestrian system meets the structural dynamics of the bridge. However, standard methods for numerical analysis of pedestrian bridges deal with this issue by using simplified approaches. The structure is mostly represented either by discretised multi mass systems or through a formulation in modal coordinates, while the excitation is typically described by a moving load.
Positive effects of the interaction between the two systems (pedestrian and structure) are usually completely neglected. This paper, which is partially
extracted from an actual research report of the Institute of Structural Mechanics and Design (TU Darmstadt), presents an experimental set-up developed for investigations of the human-structure interaction (HSI), as well as results of the preliminary investigations carried out in the same context.
In this paper we propose a method to determine the active speaker for each time-frequency point in the noisy signals of a microphone array. This detection is based on a statistical model where the speech signals as well as noise signals are assumed to be multivariate Gaussian random variables in the Fourier domain. Based on this model we derive a maximum-likelihood detector for the active speaker. The decision is based on the a posteriori signal to noise ratio (SNR) of a speaker dependent max-SNR beamformer.
Corrosion
(2016)
Nowadays there is a rich diversity of sleep monitoring systems available on the market. They promise to offer information about sleep quality of the user by recording a limited number of vital signals, mainly heart rate and body movement. Typically, fitness trackers, smart watches, smart shirts, smartphone applications or patches do not provide access to the raw sensor data. Moreover, the sleep classification algorithm and the agreement ratio with the gold standard, polysomnography (PSG) are not disclosed. Some commercial systems record and store the data on the wearable device, but the user needs to transfer and import it into specialised software applications or return it to the doctor, for clinical evaluation of the data set. Thus an immediate feedback mechanism or the possibility of remote control and supervision are lacking. Furthermore, many such systems only distinguish between sleep and wake states, or between wake, light sleep and deep sleep. It is not always clear how these stages are mapped to the four known sleep stages: REM, NREM1, NREM2, NREM3-4. [1] The goal of this research is to find a reduced complexity method to process a minimum number of bio vital signals, while providing accurate sleep classification results. The model we propose offers remote control and real time supervision capabilities, by using Internet of Things (IoT) technology. This paper focuses on the data processing method and the sleep classification logic. The body sensor network representing our data acquisition system will be described in a separate publication. Our solution showed promising results and a good potential to overcome the limitations of existing products. Further improvements will be made and subjects with different age and health conditions will be tested.
An approach for an adaptive position-dependent friction estimation for linear electromagnetic actuators with altered characteristics is proposed in this paper. The objective is to obtain a friction model that can be used to describe different stages of aging of magnetic actuators. It is compared to a classical Stribeck friction model by means of model fit, sensitivity, and parameter correlation. The identifiability of the parameters in the friction model is of special interest since the model is supposed to be used for diagnostic and prognostic purposes. A method based on the Fisher information matrix is employed to analyze the quality of the model structure and the parameter estimates.
In this paper, utilisation of an Unscented Kalman Filter for concurrently performing disturbance estimation and wave filtering is investigated. Experimental results are provided that demonstrate very good performance subject to both tasks. For the filter, a dynamic model has been used which was optimised via correlation analysis in order to obtain a minimum set of relevant parameters. This model has also been validated by experiments deploying a small vessel. A simulation study is presented to evaluate the performance using known quantities. Experimental trials have been performed on the Rhine river. The results show that for instance flow direction and varying current velocities can continuously be estimated with decent precision, even while the boat is performing turning manoeuvres. Moreover, the filtering properties are very satisfactory. This makes the filter suitable for being used, for instance, in autonomous vessel applications or assistance systems.
The IT unit is not the only provider of information technology (IT) used in business processes. Aiming for increased performance, many business workgroups autonomously implement IT resources not covered by their organizational IT service management. This is called shadow IT. Risks and inefficiencies associated with this phenomenon challenge organizations. Organizations need to decide how to deal with identified shadow IT and if the business or the IT unit should be responsible for corresponding tasks and components. This study proposes design principles for a method to control identified shadow IT following action design research in four organizational settings. The procedure results in an allocation of IT task responsibilities between the business workgroups and the IT unit following risk considerations and transaction cost economics, leading to an IT service governance. This contributes to governance research regarding adaptive and efficient arrangements with reduced risks for business-located IT activities.
For European space missions the importance of electric propulsion is strongly growing and has recently experienced a real burst in the telecom market. The initial drivers of this development were programs of the European Space Agency and projects of the European national space agencies. In addition, electric propulsion is now on the priority list of European commercial satellite manufacturers. Actual programs target orbit raising and station keeping with full electric propulsion for telecom satellites. European space industry, represented by individual companies, has developed specific and generic solutions for the electronics dedicated to powering and controlling electric propulsion systems. The European Space Agency and the European Commission providing support for enabling technology related to Power Processing Units (PPUs) and increasing competitiveness.
This paper studies suitable models for the identification of nonlinear acoustic systems. A cascaded structure of nonlinear filters is proposed that contains several parallel branches, consisting of polynomial functions followed by a linear filter for each order of nonlinearity. The second order of nonlinearity is additionally modelled with a parallel branch, containing a Volterra filter. These are followed by a long linear FIR filter that is able to model the room acoustics. The model is applied to the identification of a tube power amplifier feeding a guitar loudspeaker cabinet in an acoustic room. The adaptive identification is performed by the normalized least mean square (NLMS) algorithm. Compared with a generalized polynomial Hammerstein (GPH) model, the accuracy in modelling the dedicated real world system can be improved to a greater extend than increasing the order of nonlinearity in the GPH model.
We analyse the results of a finite element simulation of a macroscopic model, which describes the movement of a crowd, that is considered as a continuum. A new formulation based on the macroscopic model from Hughes [2] is given. We present a stable numerical algorithm by approximating with a viscosity solution. The fundamental setting is given by an arbitrary domain that can contain several obstacles, several entries and must have at least one exit. All pedestrians have the goal to leave the room as quickly as possible. Nobody prefers a particular exit.
A method is investigated by which tight bounds on the range of a multivariate rational function over a box can be computed. The approach relies on the expansion of the numerator and denominator polynomials in Bernstein polynomials. Convergence of the bounds to the range with respect to degree elevation of the Bernstein expansion, to the width of the box and to subdivision are proven and the inclusion isotonicity of the related enclosure function is shown.
The business plan is one of the most frequently available artifacts to innovation intermediaries of technology-based ventures' presentations in their early stages [1]–[4]. Agreement on the evaluations of venturing projects based on the business plans highly depends on the individual perspective of the readers [5], [6]. One reason is that little empirical proof exists for descriptions in business plans that suggest survival of early-stage technology ventures [7]–[9]. We identified descriptions of transaction relations [10]–[13] as an anchor of the snapshot model business plan to business reality [13]. In the early-stage, surviving ventures are building transaction relations to human resources, financial resources, and suppliers on the input side, and customers on the output side of the business towards a stronger ego-centric value network [10]–[13]. We conceptualized a multidimensional measurement instrument that evaluates the maturity of this ego-centric value networks based on the transaction relations of different strength levels that are described in business plans of early-stage technology ventures [13]. In this paper, the research design and the instrument are purified to achieve high agreement in the evaluation of business plans [14]–[16]. As a result, we present an overall research design that can reach acceptable quality for quantitative research. The paper so contributes to the literature on business analysis in the early-stage of technology-based ventures and the research technique of content analysis.
Digital cameras are used in a large variety of scientific and industrial applications. For most applications the acquired data should represent the real light intensity per pixel as accurately as possible. However, digital cameras are subject to different sources of noise which distort the resulting image. Noise includes photon noise, fixed pattern noise and read noise. The aim of the radiometric calibration is to improve the quality of the resulting images by reducing the influence of the different types of noise on the measured data. In this paper, a new approach for the radiometric calibration of digital cameras using sparse Gaussian process regression is presented. Gaussian process regression is a kernel based supervised machine learning technique. It is used to learn the response of a camera system from a set of training images to allow for the calibration of new images. Compared to the standard Gaussian process method or flat field correction our sparse approach allows for faster calibration and higher reconstruction quality.
Measuring the natural frequency of buildings and bridges is a possibility to get information about the stiffness of the construction. Decreasing stiffness can be detected be repeatedly measurements. Damaged parts of the construction or too high wood moisture can be reasons for decreasing stiffness. The earlier the failure is detected the better is the chance to repair it with low costs. The method of monitoring by repeatedly measuring the natural frequency is applied at timber bridges, especially on footbridges. As damages due to high wood moisture cannot be seen easily, measuring the natural frequency is a good possibility to detect them and then to repair them. Equations to calculate the natural frequencies regarding the damaged parts are shown and applied to a simple supported beam.
Cognitive radio (CR) is a key enabler of wireless in industrial applications especially for those with strict quality-of-service (QoS) requirements. The cornerstone of CR is spectrum occupancy prediction that enables agile and proactive spectrum access and efficient utilization of spectral resources. Hidden Markov Models (HMM) provide powerful and flexible tools for statistical spectrum prediction. In this paper we introduce a HMM-based spectrum prediction algorithm for industrial applications that accurately predicts multiple slots in the future. Traditional HMM prediction approaches use two hidden states enabling the prediction of only one step ahead in the future. This one step is most often not enough due to internal hardware delays that render it outdated. We show in this work that extending the number of hidden states and formulating the prediction problem as a maximum likelihood (ML) classification approach enables a prediction span of multiple slots in the future even with fine spectrum sensing resolution. We verify the suitability of our approach to industrial wireless through extensive simulations that utilize a realistic measurement-based traffic model specifically tailored for industrial automotive settings.
Recent years have seen the proposal of several different gradient-based optimization methods for training artificial neural networks. Traditional methods include steepest descent with momentum, newer methods are based on per-parameter learning rates and some approximate Newton-step updates. This work contains the result of several experiments comparing different optimization methods. The experiments were targeted at offline handwriting recognition using hierarchical subsampling networks with recurrent LSTM layers. We present an overview of the used optimization methods, the results that were achieved and a discussion of why the methods lead to different results.
Creating cages that enclose a 3D-model of some sort is part of many preprocessing pipelines in computational geometry. Creating a cage of preferably lower resolution than the original model is of special interest when performing an operation on the original model might be to costly. The desired operation can be applied to the cage first and then transferred to the enclosed model. With this paper the authors present a short survey of recent and well known methods for cage computation.
The authors would like to give the reader an insight in common methods and their differences.
The corporate entrepreneur
(2016)
Corporate entrepreneurship is one tool for established companies to strengthen their capabilities for strategic renewal and innovativeness. The question, however, which factors are influencing the success of a corporate entrepreneurship initiative requires further attention. The corporate entrepreneur who is acting as both the leader of embedded entrepreneurial teams and linking pin to the corporate, is providing one possible perspective. Based on 6 interviews conducted in 6 German organizations this study contributes to the understanding of the role of the corporate entrepreneur and how this role can be distinguished from other roles in the context of innovation.
Scoring LSP tasks
(2016)
This paper broadens the resource-based approach to explaining survival of new technology-based firms (NTBFs) by focusing on the entrepreneur's ability to transform resources in response to triggers resulting from market interactions. Network theory is used to define a construct that allows determining the status of venture emergence (VE).The operationalization of the VE construct is built on the firm's value network maturity in the four market dimensions customer, investor, partner, and human resource. Business plans of NTBFs represent the artifact that contains this data in the form of transaction relation descriptions. Using content analysis, a multi-step combined human and computer coding process has been developed to empirically determine NTBFs' status of VE.Results of the business plan analysis suggests that the level of transaction relations allows to draw conclusions on the status of VE. Moreover, applying the developed process, a business plan coding test shows that the transaction relation based VE status significantly relates to NTBFs' survival capabilities.