Refine
Year of publication
Document Type
- Conference Proceeding (642) (remove)
Language
- English (492)
- German (149)
- Multiple languages (1)
Keywords
- 360-degree coverage (1)
- 3D Extended Object Tracking (1)
- 3D Extended Object Tracking (EOT) (2)
- 3D shape tracking (1)
- 3D ship detection (1)
- AAL (1)
- ADAM (1)
- AHI (1)
- Abrasive grain material (1)
- Abtragsprinzip (1)
Institute
- Fakultät Bauingenieurwesen (9)
- Fakultät Elektrotechnik und Informationstechnik (10)
- Fakultät Informatik (50)
- Fakultät Maschinenbau (9)
- Fakultät Wirtschafts-, Kultur- und Rechtswissenschaften (8)
- Institut für Angewandte Forschung - IAF (53)
- Institut für Optische Systeme - IOS (19)
- Institut für Strategische Innovation und Technologiemanagement - IST (29)
- Institut für Systemdynamik - ISD (64)
- Institut für Werkstoffsystemtechnik Konstanz - WIK (5)
This work proposes an efficient hardware Implementation of sequential stack decoding of binary block codes. The decoder can be applied for 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.
Many resource-constrained systems still rely on symmetric cryptography for verification and authentication. Asymmetric cryptographic systems provide higher security levels, but are very computational intensive. Hence, embedded systems can benefit from hardware assistance, i.e., coprocessors optimized for the required public key operations. In this work, we propose an elliptic curve cryptographic coprocessors design for resource-constrained systems. Many such coprocessor designs consider only special (Solinas) prime fields, which enable a low-complexity modulo arithmetic. Other implementations support arbitrary prime curves using the Montgomery reduction. These implementations typically require more time for the point multiplication. We present a coprocessor design that has low area requirements and enables a trade-off between performance and flexibility. The point multiplication can be performed either using a fast arithmetic based on Solinas primes or using a slower, but flexible Montgomery modular arithmetic.
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.
In the digital age, information technology (IT) is a strategic asset for organizations. As a result, the IT costs are rising, and the cost-effective management of IT is crucial. Nevertheless, organizations still face major challenges and former studies lack comprehensiveness and depth. The goal of this paper is to generate a deep and holistic view on current management challenges of IT costs. In 15 expert interviews, we identify 23 challenges divided into 7 categories. The main challenges are to ensure transparency on IT cost information, to demonstrate the business impact of IT as well as to change the mindset for the value of IT and overcoming them requires attention to their interactions. Hence, this paper leads to a better understanding of the issues that IT cost management (ITCM) faces in the digital age and builds a base for future research.
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.
An IT-GRC approach in SME
(2022)
The digital transformation of business processes and the integration of IT systems leads to opportunities and risks for small and medium-sized enterprises (SMEs). Risks that can result in a lack of IT compliance. The purpose of this research-in-progress paper is to present the current state of a IT-Governance-Risk-Compliance (IT-GRC) research-project. First, the results of an already conducted literature research will be discussed, combined with qualitative interviews (expert survey) of persons close to IT compliance. In the context of this paper, a first design approach will be developed by selecting relevant existing frameworks and standards and the identification of SME-specific conditions. The first design is intended to contribute a further artefact conception of tailoring approaches and standards and the creation of a guidance.
Regional economies clearly benefit from thriving entrepreneurial ecosystems. However, ecosystems are not yet entirely gender-inclusive and therefore are not tapping their full potential. This is most critical with respect to technology-based entrepreneurship which features the largest gender imbalance. Despite the considerably growing amount of literature in the two research fields of female entrepreneurship and entrepreneurial ecosystems, the intersection of the two areas has not yet been outlined. We depict the state of knowledge with a structured review of the literature highlighting bibliometric information, methods used, and the main topics addressed in current articles. From there, recommendations for future research are derived.
Das klinische Standardverfahren und Referenz der Schlafmessung und der Klassifizierung der einzelnen Schlafstadien ist die Polysomnographie (PSG). Alternative Ansätze zu diesem aufwändigen Verfahren könnten einige Vorteile bieten, wenn die Messungen auf eine komfortablere Weise durchgeführt werden. Das Hauptziel dieser Forschung Studie ist es, einen Algorithmus für die automatische Klassifizierung von Schlafstadien zu entwickeln, der ausschließlich Bewegungs- und Atmungssignale verwendet.
This paper describes the effectiveness and efficiency of Virtual Reality training during a commissioning process. Therefore, 500 picking orders with more than 2000 part-picking operations with 30 test persons have been conducted and analyzed in the Modellfabrik Bodensee. The study points out the advantages and disadvantages of virtual training in comparison to a real execution of a picking process with and without any training.
This work is a study about a comparison of survey tools and it should help developers in selecting a suited tool for application in an AAL environment. The first step was to identify the basic required functionality of the survey tools used for AAL technologies and to compare these tools by their functionality and assignments. The comparative study was derived from the data obtained, previous literature studies and further technical data. A list of requirements was stated and ordered in terms of relevance to the target application domain. With the help of an integrated assessment method, the calculation of a generalized estimate value was performed and the result is explained. Finally, the planned application of this tool in a running project is explained.
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.
oday many scientific works are using deep learning algorithms and time series, which can detect physiological events of interest. In sleep medicine, this is particularly relevant in detecting sleep apnea, specifically in detecting obstructive sleep apnea events. Deep learning algorithms with different architectures are used to achieve decent results in accuracy, sensitivity, etc. Although there are models that can reliably determine apnea and hypopnea events, another essential aspect to consider is the explainability of these models, i.e., why a model makes a particular decision. Another critical factor is how these deep learning models determine how severe obstructive sleep apnea is in patients based on the apnea-hypopnea index (AHI). Deep learning models trained by two approaches for AHI determination are exposed in this work. Approaches vary depending on the data format the models are fed: full-time series and window-based time series.
The first part of this work shows the development and application of a new material system using high strength duplex stainless steel wires as net material with environmentally compatible antifouling properties for off-shore fish farm cages. Current net materials from textiles (polyamide) shall be partially replaced by high strength duplex stainless steel in order to have a more environmentally compatible system which meets the more severe mechanical loads (waves, storms, predatores (sharks, seals)). With a new antifouling strategy current issues like reduced ecological damage (e.g. due to copper disposal), lower maintenance costs (e.g. cleaning) and reduced durability shall be resolved.
High strength steel wires are also widely used in geological protection systems, for example rockfall protection or slope stabilisation. Normally hot-dip galvanised carbon steel is used in this case. But in highly corrosive environments like coastal areas, volcanic areas or mines for example, other solutions with a high corrosion resistance and sufficient mechanical properties are necessary. Protection systems made of high strength duplex stainless steel wires enable a significantly longer service life of the portection systems and therefore a higher level of security.
Text produced by entrepreneurs represents a data source in entrepreneurship research on venture performance and fund-raising success. Manual text coding of single variables is increasingly assisted or replaced by computer-aided text analysis. Yet, for the development of prediction models with several variables, such dictionary-based text analysis methods are less suitable. Natural language processing techniques are an alternative; however, the implementation is more complex and requires substantial programming skills. More work is required to understand how text analytics can advance entrepreneurship research. This study hence experiments with different artificial intelligence methods rooted in Natural Language Processing and deep learning. It uses 766 business plans to train a model for the automated measurement of transaction relations, a construct which is an indicator for new technology-based firm survival. Empirical findings show that the accuracy of construct measurement can be significantly increased with automated methods and improves with larger amounts of training data. Language complexity sets limits to the precision of automated construct measurement though. We therefore recommend a hybrid approach: making use of the inherent advantages of combining automated with human coding until the amount of training data is sufficiently large to substitute the human coding completely. The study provides insights into the applicability of different text analytics methods in entrepreneurship research and points at future research potential.
Domain-specific modelling is increasingly adopted in the software development industry. While open source metamodels like Ecore have a wide impact, they still have some problems. The independent storage of nodes (classes) and edges (references) is currently only possible with complex, specific solutions. Furthermore the developed models are stored in the extensible markup language (XML) data format, which leads to problems with large models in terms of scaling. In this paper we describe an approach that solves the problem of independent classes and references in metamodels and we store the models in the JavaScript Object Notation (JSON) data format to support high scalability. First results of our tests show that the developed approach works and classes and references can be defined independently. In addition, our approach reduces the amount of characters per model by a factor of approximately two compared to Ecore. The entire project is made available as open source under the name MoDiGen. This paper focuses on the description of the metamodel definition in terms of scaling.
Today, many resource-constrained systems, such as embedded systems, still rely on symmetric cryptography for authentication and digital signatures. Asymmetric cryptography provide a higher security level, but software implementations of public-key algorithms on small embedded systems are extremely slow. Hence, such embedded systems require hardware assistance, i.e. crypto coprocessors optimized for public key operations. Many such coprocessor designs aim on high computational performance. In this work, an area efficient elliptic curve cryptography (ECC) coprocessor is presented for applications in small embedded systems where high performance coprocessors are too costly. We propose a simple control unit with a small instruction set that supports different ECC point multiplication (PM) algorithms. The control unit reduces the logic and number of registers compared with other implementations of ECC point multiplications.
We present an alternative approach to grid management in low voltage grids by the use of artificial intelligence. The developed decision support system is based on an artificial neural network (ANN). Due to the fast reaction time of our system, real time grid management will be possible. Remote controllable switches and tap changers in transformer stations are used to actively manage the grid infrastructure. The algorithm can support the distribution system operators to keep the grid in a safe state at any time. Its functionality is demonstrated by a case study using a virtual test grid. The ANN achieves a prediction rate of around 90% for the different grid management strategies. By considering the four most likely solutions proposed by the ANN, the prediction rate increases to 98.8%, with a 0.1 second increase in the running time of the model.
Assessment Literacy
(2015)
The influence of sleep on human health is enormous. Accordingly, sleep disorders can have a negative impact on it. To avoid this, they should be identified and treated in time. For this purpose, objective (with an appropriate device) or subjective (based on perceived values) measurement methods are used for sleep analysis to understand the problem. The aim of this work is to find out whether an exchange of the two methods is possible and can provide reliable results. In accordance with this goal, a study was conducted with people aged over 65 years old (a total of 154 night-time recordings) in which both measurement methods were compared. Sleep questionnaires and electronic devices for sleep assessment placed under the mattress were applied to achieve the study aims. The obtained results indicated that the correlation between both measurement methods could be observed for sleep characteristics such as total sleep time, total time in bed and sleep efficiency. However, there are also significant differences in absolute values of the two measurement approaches for some subjects/nights, which leads us to conclude that the substitution is more likely to be considered in case of long-term monitoring where the trends are of more importance and not the absolute values for individual nights.
Home health applications have evolved over the last few decades. Assistive systems such as a data platform in connection with health devices can allow for health-related data to be automatically transmitted to a database. However, there remain significant challenges concerning intermodular communication. Central among them is the challenge of achieving interoperability, the ability of devices to communicate and share data with each other. A major goal of this project was to extend an existing data platform (COMES®) and establish working interoperability by connecting assistive devices with differing approaches. We describe this process for a sleep monitoring and a physical exercise device. Furthermore, we aimed to test this setup and the implementation with a data platform in both a laboratory and an in-home setting with 11 elderly participants. The platform modification was realized, and the relevant changes were made so that the incoming data could be processed by the data platform, as well as visually displayed in real-time. Data was recorded by the respective device and transmitted into the data server with minor disruptions. Our observations affirmed that difficulties and data loss are far more likely to occur with increasing technical complexity, in the event of instable internet connection, or when the device setup requires (elderly) subjects to take specific steps for proper functioning. We emphasize the importance for tests and evaluations of home health technologies in real-life circumstances.
In diesem Beitrag wird eine Methode des maschinellen Lernens entwickelt, die die Schlafstadienerkennung untersucht. Übliche Methoden der Schlafanalyse basieren auf der Polysomnographie (PSG). Der präsentierte Ansatz basiert auf Signalen, die ausschließlich nicht-invasiv in einer häuslichen Umgebung gemessen werden können. Bewegungs-, Herzschlags- und Atmungssignale können vergleichsweise leicht erfasst werden aber die Erkennung der Schlafstadien ist dadurch erschwert. Die Signale werden als Zeitreihenfolge strukturiert und in Epochen überführt. Die Leistungsfähigkeit von maschinellem Lernen wird der Polysomnographie gegenübergestellt und bewertet.
Martensitic stainless steels has a wide use, for example for blades, knifes or cutter. The best corrosion resistance of these materials is in hardened condition. For better mechanical properties a tempering is normally applied to increase the durability. The tempering is also reducing the hardness and finally the corrosion resistance. Austempering is meanly used at low alloyed steels and brings a good compromise between durability, hardness and corrosion resistance. For martensitic stainless steels, austempering is normally not a topic because of the very long tempering times.
This work shows first results of austempering of some standard martensitic stainless steels and the influence to corrosion resistance. For reference, hardened and also hardened and tempered specimens were investigated. The corrosions resistance was investigated by electrochemical methods.
The trajectory tracking problem for a fully-actuated real-scaled surface vessel is addressed in this paper by designing a backstepping controller with a multivariable integral action, considering the thruster allocation problem. The performance and robustness of this controller are evaluated in simulation, taking into account environmental disturbance forces and modeling mismatch, using a docking maneuver as a reference trajectory. Furthermore, a comparison between the backstepping controller and a nonlinear position PID-Control with flatness based-feedforward is also analyzed.
Bauhäusler am Bodensee
(2016)
Unter bestimmten Kontaktbedingungen zwischen Rad und Schiene können selbsterregte Schwingungen angeregt werden, die zu gegenphasigen Drehbewegungen der Radscheiben und hohen Torsionsmomenten in der Radsatzwelle führen. Zur Bestimmung des maximalen Torsionsmoments sind bislang aufwendige Testfahrten erforderlich, da keine Verfahren bekannt waren, die eine konservative Berechnung des Torsionsmoments ermöglichen [1]. In den vergangenen Jahren wurden die drei folgenden Berechnungsmethoden vertieft untersucht, um das maximale, dynamische Torsionsmoment zu berechnen:
- Simulationen von komplexen Mehrkörpersystemen (MKS)
- Differentialgleichungssysteme mit numerischer Berechnung
- Analytische Berechnung durch Reduktion auf ein Minimalmodell
In dieser Publikation sollen diese Berechnungsmethoden näher vorgestellt werden und durch eine Gegenüberstellung der jeweils berechneten und gemessenen Ergebnisse deren Möglichkeiten aber auch Limitationen aufgezeigt werden.
Beyond the SDG compass
(2015)
This policy brief presents the possibilities of using big data analytics for safe, decarbonised and climate-resilient infrastructure. The policy brief focuses on current constraints and limitations to applying big data analytics to the infrastructure ecosystem and presents several examples and best practices for different infrastructure sectors and at different policy levels (national, municipal) to highlight recommendations and policy requirements needed for deep digital transformation and sustainable solutions in infrastructure planning and delivery.
It is well known that signal constellations which are based on a hexagonal grid, so-called Eisenstein constellations, exhibit a performance gain over conventional QAM ones. This benefit is realized by a packing and shaping gain of the Eisenstein (hexagonal) integers in comparison to the Gaussian (complex) integers. Such constellations are especially relevant in transmission schemes that utilize lattice structures, e.g., in MIMO communications. However, for coded modulation, the straightforward approach is to combine Eisenstein constellations with ternary channel codes. In this paper, a multilevel-coding approach is proposed where encoding and multistage decoding can directly be performed with state-of-the-art binary channel codes. An associated mapping and a binary set partitioning are derived. The performance of the proposed approach is contrasted to classical multilevel coding over QAM constellations. To this end, both the single-user AWGN scenario and the (multiuser) MIMO broadcast scenario using lattice-reduction-aided preequalization are considered. Results obtained from numerical simulations with LDPC codes complement the theoretical aspects.
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.
The reliability of flash memories suffers from various error causes. Program/erase cycles, read disturb, and cell to cell interference impact the threshold voltages and cause bit errors during the read process. Hence, error correction is required to ensure reliable data storage. In this work, we investigate the bit-labeling of triple level cell (TLC) memories. This labeling determines the page capacities and the latency of the read process. The page capacity defines the redundancy that is required for error correction coding. Typically, Gray codes are used to encode the cell state such that the codes of adjacent states differ in a single digit. These Gray codes minimize the latency for random access reads but cannot balance the page capacities. Based on measured voltage distributions, we investigate the page capacities and propose a labeling that provides a better rate balancing than Gray labeling.