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Tourist tracking
(2015)
Autism spectrum disorders (ASD) affect a large number of children both in the Russian Federation and in Germany. Early diagnosis is key for these children, because the sooner parents notice such disorders in a child and the rehabilitation and treatment program starts, the higher the likelihood of his social adaptation. The difficulties in raising such a child lie in the complexity of his learning outside of children's groups and the complexity of his medical care. In this regard, the development of digital applications that facilitate medical care and education of such children at home is important and relevant. The purpose of the project is to improve the availability and quality of healthcare and social adaptation at home of children with ASD through the use of digital technologies.
Deep 3D
(2017)
In the reverse engineering process one has to classify parts of point clouds with the correct type of geometric primitive. Features based on different geometric properties like point relations, normals, and curvature information can be used, to train classifiers like Support Vector Machines (SVM). These geometric features are estimated in the local neighborhood of a point of the point cloud. The multitude of different features makes an in-depth comparison necessary. In this work we evaluate 23 features for the classification of geometric primitives in point clouds. Their performance is evaluated on SVMs when used to classify geometric primitives in simulated and real laser scanned point clouds. We also introduce a normalization of point cloud density to improve classification generalization.
Klimawandel
(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.
RC-Beton im Hochbau
(2017)
Kreativwirtschaft Bodensee
(2017)
InBetween
(2017)
The goal of this paper pretends to show how a bed system with an embedded system with sensor is able to analyze a person’s movement, breathing and recognizing the positions that the subject is lying on the bed during the night without any additional physical contact. The measurements are performed with sensors placed between the mattress and the frame. An Intel Edison board was used as an endpoint that served as a communication node from the mesh network to external service. Two nodes and Intel Edison are attached to the bottom of the bed frame and they are connected to the sensors.
The exposure to the light has a great influence on human beings in their everyday life. Various lighting sources produce light that reaches the human eye and influences a rhythmic release of melatonin hormone, that is a sleep promoting factor.
Since the development of new technologies provides more control over illuminance, this work uses an IoT based lighting system to set up dim and bright scenarios. A small study has been performed on the influence of illuminance on sleep latency. The system consists of different light bulbs, sensors and a central bridge which are interconnected like a mesh network. Also, a mobile app has been developed, that allows to adjust the lighting in various rooms. With the help of a ferro-electret sensor, like applied in sleep monitoring systems, a subject’s sleep was monitored. The sensor is placed below the mattress and it collects data, which is stored and processed in a cloud or in other alternative locations.
The research was conducted on healthy young subjects after being previously exposed to the preconfigured illuminance for at least three hours before bedtime. The results indicate correlation between sleep onset latency and exposure to different illuminance before bedtime. In a dimmed environment, the subject fell asleep in average 28% faster compared to the brighter environment.
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.
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 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.
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.
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.
Konventionelle, von Dieselmotoren angetriebene Radlader beeinträchtigen die Lebensqualität der Menschen in ihrer unmittelbaren Umgebung mit Lärm- und Schadstoffemissionen. Das vom BMBF geförderte Forschungsvorhaben "Emissionsarmer Elektroradlader" verfolgt das Ziel, die lokalen Emissionen von Radladern deutlich herabzusetzen und die Effizienz des Fahrzeugs zu steigern. Im Rahmen des Vorhabens wurde ein konventioneller Radlader auf elektrische Antriebe umgerüstet. Als Energiespeicher dient eine LiFeYPO4-Batterie, die für eine Betriebsdauer von vier Stunden ausgelegt ist. In ersten praktischen Untersuchungen wurde die Energiebilanz des Emissionsarmen Elektro-Radladers mit der des konventionellen Serienfahrzeugs verglichen. Dazu wurde ein modifizierter Y-Arbeitszyklus entworfen, der sich an den üblichen Arbeitsaufgaben des Radladers orientiert und sich durch eine hohe Reproduzierbarkeit auszeichnet. Für die vollständige Bewertung wird die komplette Kette der Energieumwandlung betrachtet, beginnend mit der Energie im Kraftstoff bzw. der dem Stromnetz entnommenen Energie, bis zur mechanischen Arbeit, die das Gerät verrichtet. Daraus lassen sich Rückschlüsse auf die unterschiedlichen CO2-Emissionen beider Fahrzeuge ableiten.
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 work investigates soft input decoding for generalized concatenated (GC) codes. The GC codes are constructed from inner nested binary Bose-Chaudhuri-Hocquenghem (BCH)codes and outer Reed-Solomon (RS) codes. In order to enable soft input decoding for the inner BCH block codes, a sequential stack decoding algorithm is used. Ordinary stack decoding of binary block codes requires the complete trellis of the code.
In this work a representation of the block codes based on the trellises of supercodes is proposed in order to reduce the memory requirements for the representation of the BCH codes. Results for the decoding performance of the overall GC code are presented.
Furthermore, an efficient hardware implementation of the GC decoder is proposed.
In this paper an approach towards databased fault diagnosis of linear electromagnetic actuators is presented. Time and time-frequency-domain methods were applied to extract fault related features from current and voltage measurements. The resulting features were transformed to enhance class separability using either Principal Component Analysis (PCA) or Optimal Transformation. Feature selection and dimensionality reduction was performed employing a modified Fisher-ratio. Fault detection was carried out using a Support-Vector-Machine classifier trained with randomly selected data subsets. Results showed, that not only the used feature sets (time-domain/time-frequency-domain) are crucial for fault detection and classification, but also feature pre-processing. PCA transformed time-domain features allow fault detection and classification without misclassification, relying on current and voltage measurements making two sensors necessary to generate the data. Optimal transformed time-frequency-domain features allow a misclassification free result as well, but as they are calculated from current measurements only, a dedicated voltage sensor is not necessary. Using those features is a promising alternative even for detecting purely supply voltage related faults.
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.
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%.
The investigation of stress requires to distinguish between stress caused by physical activity and stress that is caused by psychosocial factors. The behaviour of the heart in response to stress and physical activity is very similar in case the set of monitored parameters is reduced to one. Currently, the differentiation remains difficult and methods which only use the heart rate are not able to differentiate between stress and physical activity, without using additional sensor data input. The approach focusses on methods which generate signals providing characteristics that are useful for detecting stress, physical activity, no activity and relaxation.
Product development and product manufacturing are entering a new era, namely an era where engineering tasks are executed under collaboration of all involved parties. Engineers and potential customers work together mainly in a virtual world for the design and realization of the product. We address this so called “crowdsourcing” trend in the automotive industry that lowers cost and accelerates production of new car. Current practice and prior studies fail to handle data management and collaboration aspects in sufficient detail. We propose a PLM based crowdsourcing platform that applies best practices to the established approach and adapt it with new methods for handling specific requirements. Our work provides a basis for establishing an improved collaboration platform to support a Gig Economy in the automotive industry.
It is widely recognized that sustainability is a new challenge for many manufacturing companies. In this paper, we tackle this issue by presenting an approach that deals with material and substance compliance within Product Lifecycle Management in a complex value chain. Our analysis explains why, how and when sustainable manufacturing arises, and it identifies, quantifies and evaluates the environmental impact of a new product. We propose (I) a Life Cycle Assessment tool (LCA) and (II) a model to validate this approach and evaluate the risk of noncompliance in supply chain. Our LCA approach provides comprehensive information on environmental impacts of a product.
Product and materials cycles are parallel and intersecting, making it challenging to integrate Material Selection Process across Product Lifecycle Management, Integration of LCA with PLM. We provide only a foundation. Further research in systems engineering is necessary. LCA is sensitive to data quality. Outsourcing production and having problems in supplier cooperation can result in material mismatch (such as property, composition mismatching) in the production process due to that may cause misleading of LCA results.
This paper also describes research challenges using riskbased due diligence.
The paper investigates an innovative actuator combination based on the magnetic shape memory technology. The actuator is composed of an electromagnet, which is activated to produce motion, and a magnetic shape memory element, which is used passively to yield multistability, i.e. the possibility of holding a position without input power. Based on the experimental open-loop frequency characterization of the actuator, a position controller is developed and tested in several experiments.
Deep neural networks have been successfully applied to problems such as image segmentation, image super-resolution, coloration and image inpainting. In this work we propose the use of convolutional neural networks (CNN) for image inpainting of large regions in high-resolution textures. Due to limited computational resources processing high-resolution images with neural networks is still an open problem. Existing methods separate inpainting of global structure and the transfer of details, which leads to blurry results and loss of global coherence in the detail transfer step. Based on advances in texture synthesis using CNNs we propose patch-based image inpainting by a single network topology that is able to optimize for global as well as detail texture statistics. Our method is capable of filling large inpainting regions, oftentimes exceeding quality of comparable methods for images of high-resolution (2048x2048px). For reference patch look-up we propose to use the same summary statistics that are used in the inpainting process.
In this paper we present a method using deep learning to compute parametrizations for B-spline curve approximation. Existing methods consider the computation of parametric values and a knot vector as separate problems. We propose to train interdependent deep neural networks to predict parametric values and knots. We show that it is possible to include B-spline curve approximation directly into the neural network architecture. The resulting parametrizations yield tight approximations and are able to outperform state-of-the-art methods.
Der DEX Deutscher Ethik Index® gibt Auskunft darüber, ob der Erfolg eines Unternehmens auf anständige Weise erreicht wurde. Zielgruppe des veröffentlichten DEX sind alle Anspruchsgruppen (Stakeholder) und die Gesellschaft. Der DEX informiert darüber, ob das Unternehmen einen Mehrwert für alle seine Stakeholder schafft (= Stakeholder Value). Der DEX unterstützt Entscheidungen der Öffentlichkeit, ob einer Organisation aufgrund ihres Beitrags für die Gesellschaft die „License to Operate“ erteilt wird (= Shared Value).
SDG Voyager - A practical guide to align business excellence with Sustainable Development Goals
(2018)
By now, an inflationary high number of international publications on the topic “Agenda 2030” exist. But unanswered to this day seems to be the question of how the CSR-management of a company can make a concrete contribution to the SDGs. Instead of unilaterally demanding the reporting of companies’ sustainability activities, the SDG Voyager starts earlier in the process with the intention of encouraging companies of all sizes to become familiar with the fields of action for corporate responsibility and to attend to these issues without feeling overwhelmed. Many companies will find that they are already making a big contribution to sustainable development in a number of fields. In other areas, however, there will still be an urgent need for action. The SDG Voyager aims to acquaint companies with these topics and support them to fulfill their responsibilities towards their stakeholders and society.
Investigation of magnetic effects on austenitic stainless steels after low temperature carburization
(2018)
Sleep study can be used for detection of sleep quality and in general bed behaviors. These results can helpful for regulating sleep and recognizing different sleeping disorders of human. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this work is a non-invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable Actigraphy devices tends to be uncomfortable. Besides, these methods not only decrease practicality due to the process of having to put them on, but they are also very expensive. The system proposed in this paper classifies respiration and body movement with only one type of sensor and also in a noninvasive 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 excellent results in the classification of breathing rate and body movements.
We consider the problem of increasing the informative value of electrocardiographic (ECG) surveys using data from multichannel electrocardiographic leads, that include both recorded electrocardiosignals and the coordinates of the electrodes placed on the surface of the human torso. In this area, we were interested in reconstruction of the surface distribution of the equivalent sources during the cardiac cycle at relatively low hardware cost. In our work, we propose to reconstruct the equivalent electrical sources by numerical methods, based on integral connection between the density of electrical sources and potential in a conductive medium. We consider maps of distributions of equivalent electric sources on the heart surface (HSSM), presenting source distributions in the form of a simple or double electrical layer. We indicate the dynamics of the heart electrical activity by the space-time mapping of equivalent electrical sources in HSSM.
The process of restoring our body and brain from fatigue is directly depend-ing on the quality of sleep. It can be determined from the report of the sleep study results. Classification of sleep stages is the first step of this study and this includes the measurement of biovital data and its further processing.
In this work, the sleep analysis system is based on a hardware sensor net, namely a grid of 24 pressure sensors, supporting sleep phase recognition. In comparison to the leading standard, which is polysomnography, the proposed approach is a non-invasive system. It recognises respiration and body move-ment with only one type of low-cost pressure sensors forming a mesh archi-tecture. The nodes implement as a series of pressure sensors connected to a low-power and performant microcontroller. All nodes are connected via a system wide bus with address arbitration. The embedded processor is the mesh network endpoint that enables network configuration, storing and pre-processing of the data, external data access and visualization.
The system was tested by executing experiments recording the sleep of different healthy young subjects. The results obtained have indicated the po-tential to detect breathing rate and body movement. A major difference of this system in comparison to other approaches is the innovative way to place the sensors under the mattress. This characteristic facilitates the continuous using of the system without any influence on the common sleep process.
Long-term sleep monitoring can be done primarily in the home environment. Good patient acceptance requires low user and installation barriers. The selection of parameters in this approach is significantly limited compared to a PSG session. The aim is a qualified selection of parameters, which on the one hand allow a sufficiently good classification of sleep phases and on the other hand can be detected by non-invasive methods.
Einfluss der Oberfläche
(2018)
Corporate venturing is one way for corporations to
introduce strategic renewal into their business portfolios, which is
imperative for ongoing success in innovation-driven industries.
Prior research finds that corporate ventures should be separated
from the mainstream business in loosely coupled sub-units, but
scholars continue to discuss how loose or tight the ventures should
be to balance exploration and exploitation. Hence, the antecedents
for successful venture management are yet to be fully explored and
our study contributes to this effort. The study shows that
corporate venture success is enhanced when corporate
management grants job and strategic autonomy to the venture
managers. This is further amplified when corporate management
simultaneously imposes an exploitative policy that forces venture
managers to prioritize extensions to and improvements of existing
competences and product-market offerings.
Corporate venturing has gained much attention due
to challenges and changes that occur because of discontinuous
innovations – which seem to be promoted by digitalization. In this
context, open innovation has become a promising tool for
established companies to strengthen their innovation capabilities.
While the external opening of the innovation process has gained
much attention, the internal opening lacks on investigations.
Especially new organizational forms, such as Internal Corporate
Accelerators, have not been investigated sufficiently. This study,
which is based on 13 interviews from two German tech-companies,
contributes to a better understanding of this new form of corporate
venturing and the resulting effects on the organizational renewal.
Influence of Temperature on the Corrosion behaviour of Stainless Steels under Tribological Stress
(2018)
Posterpräsentation
This paper presents a bed system able to analyze a person’s movement, breathing and recognize the positions that the subject is lying on the bed during the night without any additional physical contact. The measurements are performed with sensors placed between the mattress and the bed-frame. An Intel Edison board was used as an endpoint that served as a communication node from the mesh network to external service. Two nodes and Intel Edison are attached to the bottom of the bed frame and they are connected to the sensors. First test results have indicated the potential of the proposed approach for the recognition of sleep positions with 83% of correct recognized positions.
The IETF, concerned with the evolution of the Internet architecture, nowadays also looks into industrial automation processes. The contributions of a variety of IETF activities, initiated during the last ten years, enable now the replacement of proprietary standards by an open standardized protocol stack. This stack, denoted in the following as 6TiSCH-stack, is tailored for industrial internet of things (IIoTs). The suitability of 6TiSCH-stack for Industry 4.0 is yet to explore. In this paper, we identify four challenges that, in our opinion, may delay or hinder its adoption. As a prime example of that, we focus on the initial 6TiSCHnetwork
formation, highlighting the shortcomings of the default procedure and introducing our current work for a fast and reliable formation of dense network.