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Stress is becoming an important topic in modern life. The influence of stress results in a higher rate of health disorders such as burnout, heart problems, obesity, asthma, diabetes, depressions and many others. Furthermore individual’s behavior and capabilities could be directly affected leading to altered cognition, inappropriate decision making and problem solving skills. In a dynamic and unpredictable environment, such as automotive, this can result in a higher risk for accidents. Different papers faced the estimation as well as prediction of drivers’ stress level during driving. Another important question is not only the stress level of the driver himself, but also the influence on and of a group of other drivers in the near area. This paper proposes a system, which determines a group of drivers in a near area as clusters and it derives the individual stress level. This information will be analyzed to generate a stress map, which represents a graphical view about road section with a higher stress influence. Aggregated data can be used to generate navigation routes with a lower stress influence to decrease stress influenced driving as well as improve road safety.
Sleep is an important aspect in life of every human being. The average sleep duration for an adult is approximately 7 h per day. Sleep is necessary to regenerate physical and psychological state of a human. A bad sleep quality has a major impact on the health status and can lead to different diseases. In this paper an approach will be presented, which uses a long-term monitoring of vital data gathered by a body sensor during the day and the night supported by mobile application connected to an analyzing system, to estimate sleep quality of its user as well as give recommendations to improve it in real-time. Actimetry and historical data will be used to improve the individual recommendations, based on common techniques used in the area of machine learning and big data analysis.
Traggerüste
(2016)
Increasing robustness of handwriting recognition using character N-Gram decoding on large lexica
(2016)
Offline handwriting recognition systems often include a decoding step, that is retrieving the most likely character sequence from the underlying machine learning algorithm. Decoding is sensitive to ranges of weakly predicted characters, caused e.g. by obstructions in the scanned document. We present a new algorithm for robust decoding of handwriting recognizer outputs using character n-grams. Multidimensional hierarchical subsampling artificial neural networks with Long-Short-Term-Memory cells have been successfully applied to offline handwriting recognition. Output activations from such networks, trained with Connectionist Temporal Classification, can be decoded with several different algorithms in order to retrieve the most likely literal string that it represents. We present a new algorithm for decoding the network output while restricting the possible strings to a large lexicon. The index used for this work is an n-gram index with tri-grams used for experimental comparisons. N-grams are extracted from the network output using a backtracking algorithm and each n-gram assigned a mean probability. The decoding result is obtained by intersecting the n-gram hit lists while calculating the total probability for each matched lexicon entry. We conclude with an experimental comparison of different decoding algorithms on a large lexicon.
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.
„Das Gedächtnis des Sees“
(2016)
Wie können archäologische Forschungsergebnisse einer breiten Öffentlichkeit möglichst eindrücklich und nachvollziehbar vermittelt werden? Am Beispiel der UNESCO-Welterbestätte Pfahlbausiedlung Hornstaad demonstrieren Studierende der Hochschule für Technik, Wirtschaft und Gestaltung Konstanz (HTWG) die Visualisierung komplexer wissenschaftlicher Inhalte mithilfe moderner Virtual-
Reality-Brillen-Technologie (VR-Brillen). Eine dreidimensionale digitale Rekonstruktion der Pfahlbausiedlung und Simulation von Tages- und Jahresverlauf in Verbindung mit der realen Bewegung im Ausstellungsraum ermöglichen dem Betrachter das hautnahe Erleben des Alltags in einer neolithischen Siedlung.
Das Ausstellungsprojekt „Das Gedächtnis des Sees“ wird im Rahmen der Großen Landesaustellung „4000 Jahre Pfahlbauten“ zu sehen sein.
Navigation on the Danube
(2016)
This report contains two parts: The first part presents an overview on studies concerning the Danube, inland navigation or the impact of climate change on either of those. The second part gives a more detailed analysis of inland navigation on the Danube, partly based on studies presented in part one. Part two covers the current situation along the Danube by covering the topic of bottlenecks and other limitations for shipping along the Danube. Based on these informations, an estimation of the economic impacts of low water periods on inland navigation is made. As a last step, measures to reduce the impact of low water on inland navigations are presented. The report shows, that inland navigation still is an important transport mode, along the Danube as well as in other european regions. Especially in Romania, inland navigation still has a large share of more than 20% and rising in total transport. However, inland navigation depends strongly on good conditions of its infrastructure. These good conditions are limited mainly by two factors: one are the so called bottlenecks. Those are areas with sub-optimal shipping conditions e.g. due to solid rock formations in the river that lead to a reduced water depths. The other factor is the weather (and, on a longer time scale, the climate) which, mostly depending on precipitation and evaporation, can lead to low water levels seasonally. In addition to these two natural factors, laws which e.g. regulate the maximum number of barges allowed. Human build structures like locks limit the size of vessels as well as the speed they can travel with. These limiting factors are identified and located in the first chapter of part two of this report, before the water depth needed by several ship sizes as well as the cargo fleet available along the Danube are presented. One of the targets of this report is to estimate the economic impact of low water periods. All the factors named above as well as the freight prices charged for connections along the Danube are used to each this target in chapter II.4. To estimate the impact of low water periods on the freight prices, a method developed by Jonkeren et al. (2007) for the Rhine is transfered to the Danube. By transfering Jonkeren et al. (2007) method, regression equations for several transport connections along the Danube are identified that give a first estimate for the connection of freight prices and water levels. With the help of these regression equations, an estimation of the total expenses for transport via inland navigation for several years is possible. The yearly and seasonal variability is identified as well as the additional expenses due to water levels below 280cm. But additional expenses are not the only impact of changing water levels on inland navigation. Another is, that while the demand for transport stays at the same level, sometimes the water levels are not sufficient enough to use the full capacity of the fleet. Therefore, the (theoretical) amount of cargo that could not be transported due to low water levels is calculated as well and presented in chapter II.5. Finally, some measures to overcome some of the here named problems of inland navigation due to low water levels are presented. These are separated into two general approches: change the ship or change the river. Both methods have their advantages and disadvantages due to technical as well as regulatory and other factors. The list presented here however is incomplete and only gives a few ideas of how some problems can be overcome. In the end, an individual mix for the different regions along the river and sometimes for the individual companies must be found.
Integritätsmanagement
(2016)
Compliance hat in der Vergangenheit oftmals versagt, der aktuelle „VW-Abgasskandal“ ist nur ein Beispiel. Es muss nicht alles neu erfunden werden, und nicht alles, was Unternehmen in der Vergangenheit im Bereich Compliance taten, ist schlecht. Aber es ist an der Zeit, Compliance neu zu denken. Worauf kommt es wirklich an im Compliance Management 2.0? Meine Antwort lautet, dass Ernsthaftigkeit und Glaubwürdigkeit gefördert werden müssen und gefördert werden können. Wie, das versuche ich im Rahmen von sechs Thesen zu skizzieren.
Digital bedruckte Oberflächen müssen strengen funktionalen und ästhetischen Anforderungen genügen. Diese Eigenschaften werden im Rahmen der Qualitätsprüfung kontrolliert. Hierbei wirken sich Oberflächendefekte oftmals erst dann aus, wenn diese auch vom Menschen wahrgenommen werden. Aufgrund der hohen Produktionsgeschwindigkeit kann eine solche Bewertung der Sichtbarkeit von Defekten bisher nur außerhalb des Produktionsflusses durch manuelle - subjektiv geprägte - Inspektion erfolgen. Ziel des Projektes ist (1) die Modellierung von Texturen in einer Form, die an das menschliche visuelle System angepasst ist und (2) die automatisierte Beurteilung der Wahrnehmung von Texturfehlern. Im Rahmen des Projekts wurde ein prototypisches System zur Inline-Erfassung von texturierten Oberflächen entwickelt. Auf Basis von realen Aufnahmen industriell produzierter Holzdekore wurde eine repräsentative Texturdatenbank erstellt. Gezeigt werden erste Resultate im Bereich der Defektdetektion auf Basis von statistischen Merkmalen. Diese Ergebnisse dienen als Grundlage für die spätere wahrnehmungsorientierte Bewertung. Letztlich sollen die im Rahmen des Projekts erlangten Ergebnisse in einen prototypischen Aufbau zur Inspektion von digital bedruckten Dekoren einfließen.
FishNet
(2016)
The corrosion resistance of stainless steels is massively influenced by the condition of their surface. The surface quality includes the topography of the surface, the structure and composition of the passive layer, and the surface near structure of the base material. These factors are influenced by final physical/chemical surface treatments. The presented work shows significantly lower corrosion resistance for mechanical machined specimens than for etched specimens. It also turns out that the rougher the surface, the lower the corrosion resistance gets. However, there is no general finding which shows if blasted or grinded surfaces are more appropriate, but a dependency on process parameters and the characteristics on corrosive exposure in terms of corrosion behavior. The results show that not only the surface roughness Ra has an influence on corrosion behavior but also the shape of peaks and valleys which are evolved by surface treatments. Imperfections in the base material, like sulfidic inclusions lead to a weaker passive layer, respectively, to a decrease of the corrosion resistance. By using special passivating techniques the corrosion resistance of stainless steels can be increased to a higher level in comparison to common passivation.
Even though immutability is a desirable property, especially in a multi-threaded environment, implementing immutable Java classes is surprisingly hard because of a lack of language support. We present a static analysis tool using abstract bytecode interpretation that checks Java classes for compliance with a set of rules that together constitute state-based immutability. Being realized as a Find Bugs plug in, the tool can easily be integrated into most IDEs and hence the software development process. Our evaluation on a large, real world codebase shows that the average run-time effort for a single class is in the range of a few milliseconds, with only a very few statistical spikes.
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.
To learn from the past, we analyse 1,088 "computer as a target" judgements for evidential reasoning by extracting four case elements: decision, intent, fact, and evidence. Analysing the decision element is essential for studying the scale of sentence severity for cross-jurisdictional comparisons. Examining the intent element can facilitate future risk assessment. Analysing the fact element can enhance an organization's capability of analysing criminal activities for future offender profiling. Examining the evidence used against a defendant from previous judgements can facilitate the preparation of evidence for upcoming legal disclosure. Follow the concepts of argumentation diagrams, we develop an automatic judgement summarizing system to enhance the accessibility of judgements and avoid repeating past mistakes. Inspired by the feasibility of extracting legal knowledge for argument construction and employing grounds of inadmissibility for probability assessment, we conduct evidential reasoning of kernel traces for forensic readiness. We integrate the narrative methods from attack graphs/languages for preventing confirmation bias, the argumentative methods from argumentation diagrams for constructing legal arguments, and the probabilistic methods from Bayesian networks for comparing hypotheses.
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.