Open Access

Nowadays, information technology (IT) is a strategic asset for organizations. As a result, the IT costs are rising and there is a need for transparency about their root causes. Cost drivers as an instrument in IT cost management enable a better transparency and understanding of costs. However, there is a lack of IT cost driver research with a focus on the strategic position of IT within organizations. The goal of this paper is to develop a comprehensive overview of strategic drivers of IT costs. The Delphi study leads to the identification and validation of 17 strategic drivers. Hence, this paper builds a base for cost driver analysis and contributes to a better understanding of the causes of costs. It facilitates future research regarding cost behavior and the business value of IT. Additionally, practitioners gain awareness of levers to influence IT costs and consequences of managerial decisions on their IT spend.

This paper presents a modeling approach of an industrial heating process where a stripe-shaped workpiece is heated up to a specific temperature by applying hot air through a nozzle. The workpiece is moving through the heating zone and is considered to be of infinite length. The speed of the substrate is varying over time. The derived model is supposed to be computationally cheap to enable its use in a model-based control setting. We start by formulating the governing PDE and the corresponding boundary conditions. The PDE is then discretized on a spatial grid using finite differences and two different integration schemes, explicit and implicit, are derived. The two models are evaluated in terms of computational effort and accuracy. It turns out that the implicit approach is favorable for the regarded process. We optimize the grid of the model to achieve a low number of grid nodes while maintaining a sufficient amount of accuracy. Finally, the thermodynamical parameters are optimized in order to fit the model's output to real-world data that was obtained by experiments.

The trajectory tracking problem for a real-scaled fully-actuated surface vessel is addressed in this paper. A nonlinear model predictive control (NMPC) scheme was designed to track a reference trajectory, considering state and input constraints, and environmental disturbances, which were assumed to be constant over the prediction horizon. The controller was tested by performing docking maneuvers using the real-scaled research vessel from the University of Applied Sciences Konstanz at the Rhine river in Germany. A comparison between the experimental results and the simulated ones was analyzed to validate the NMPC controller.

Bei der internationalen Norm DIN ISO 26000, deren englische Originalfassung unter dem Titel Guidance on Social Responsibility (ISO 26000: 2010) veröffentlicht wurde, handelt es sich um den ersten und einzigen Standard zum Thema, der eine eindeutige, international konsensfähige Definition gesellschaftlicher Verantwortung von Unternehmen (CSR) vorgelegt hat und der empfiehlt, die damit verbundenen Aspekte nicht isoliert zu betrachten und zu managen. Aufgrund der Entwicklung im Rahmen eines aufwendigen globalen Multistakeholderprozesses auf der Basis des Konsensprinzips verfügen ihre Inhalte zudem über ein hohes Maß an Legitimität. Neben einer Betrachtung der Inhalte und Besonderheiten der Norm soll deutlich gemacht werden, dass und warum es für Organisationen aller Art lohnend sein kann, sich auch zehn Jahre nach der Veröffentlichung mit diesem umfassendsten Standard zum Thema auseinanderzusetzen: Welche Hinweise und Ratschläge für ein zeitgemäßes Management von CSR bzw. Nachhaltigkeit lassen sich für die Praxis daraus nach wie vor entnehmen? Welche Antworten bietet die ISO 26000 zu neueren gesellschaftlichen und wirtschaftspolitischen Trends, zu den heutigen Anforderungen an ein Nachhaltigkeitsmanagement? War man bei ihrer inhaltlichen Konzeption und Ausarbeitung dem Mainstream der damaligen Zeit vielleicht sogar voraus?

In order to support entrepreneurs in the Business Model Innovation (BMI) process, practice-oriented frameworks such as the St. Gallen Business Model NavigatorTM (BMN) are considered to be a powerful tool. The aim of this paper is to identify strengths and limitations of the BMN when applied to start-ups in their early stages and to contribute to the optimization of the BMN in terms of applicability for start-ups. Furthermore, the paper aims to emphasize the importance of BMI for start-ups and the relevance of a supporting framework as well as formulating a unified catalogue of requirements of BMI frameworks for start-ups.

Der Beitrag erläutert, wie eine innovative Unternehmenskultur entsteht, wie diese im Rahmen des Change Management entwickelt werden kann und welchen Beitrag "Digital Leadership" leisten kann.

Die Problemstellung, die diesem neuen Arbeitspapier zugrunde liegt, ist die Kritik an der bisherigen Etablierung des Datenschutzes in der ESG-Dimension und die Berücksichtigung dessen in dem ESG-Score, welcher eine grundlegende Orientierung für Investitionsentscheidungen von ESG-Anlegern darstellt.

While managerial mobility is ubiquitously seen as an integral part of the success in firms’ internationalization, discerning its empirical merits has been impaired by the paucity of quasi-experimental evidence, or adequate instrumental variables. To overcome these objective limitations, this paper proposes a novel identification strategy, which uses a control function based on on-the-job search theory to correct estimates for the presence of self-selected mobility flows. Our analysis confirms the finding that managers’ specific market experience matters for firms’ internationalization, especially when it derives from longer tenures at the former jobs. Regarding the attributes of managerial knowledge, our results reveal that on-the-job earned experience is at least as effective for firms’ internationalization as in born knowledge (i.e. origins) and that managers’ personal network of customers is an important asset in managers’ fund of expertise for the expansion into new markets.

Die nun vorliegende vollständig überarbeitete und aktualisierte zehnte Auflage des bewährten Lehrbuches deckt die wesentlichen Inhalte des zivilrechtlichen Lehrstoffes ab. Es werden in kompakter Form der Allgemeine Teil des BGB, das (Allgemeine und Besondere) Schuldrecht sowie das Sachenrecht dargestellt. Vervollständigt wird dieses Buch mit einem abschließenden Kapitel zum Zivilprozessrecht. Geschult werden das Verständnis für die Strukturen und Zusammenhänge im Bürgerlichen Recht und das Verständnis für die Verbindungen mit dem Zivilprozessrecht. Eine Vielzahl von Beispielen aus der Praxis, einprägsame Illustrationen, zahlreiche Schemata und Fälle mit Lösungsvorschlägen ermöglichen damit gleichzeitig auch ein anwendungsorientiertes bzw. fallorientiertes Lernen. Seine inhaltliche Kompaktheit macht es so zu einem idealen studienbegleitenden Lehrbuch für Studierende an Universitäten, Hochschulen, Berufsakademien und anderen Bildungseinrichtungen.

Ökonomische Aktivitäten sind auf den Input hochwertiger Energieträger angewiesen; diese sind knapp und werden in der fossil-nuklearen Energiewirtschaft aufgrund einer qualitativen Fehlanpassung zwischen Primärenergieeinsatz und Nutzenergiebedarf verschwenderisch genutzt. Daraus resultieren ökologische Probleme, insbesondere der Klimawandel, mit entsprechenden externen Kosten. Ein Umstieg auf erneuerbare Energien und effizientere Nutzungsstrukturen unterliegt diversen Pfadabhängigkeiten und ist aufgrund der multiplen Lernkosten mit hohen Pfadwechselkosten verbunden, die ebenfalls von der Gesellschaft getragen werden müssen. Unterschiedliche politökonomische Interessen der maßgeblichen Staaten verhindern derzeit harmonische weltweite Lösungen. Für eine evolutorische Energieökonomik ergeben sich einige Herausforderungen, insbesondere hinsichtlich der Klärung von sekundären und tertiären Pfadabhängigkeiten, der Erfassung systemischer Wechselwirkungen sowie der Problematik von Interventionsspiralen und der Formulierung von evolutorischen Designregeln für Energie- und Zertifikatemärkte.

At the early stage of a successful tech venture's life cycle, it is assumed that the business model will evolve to higher quality over time. However, there are few empirical insights into business model evolution patterns for the performance-related classification of early-stage tech ventures. We created relevant variables evaluating the evolution of the venture-centric network and the technological proposition of both digital and non-digital ventures' business models using the text of submissions to the official business plan award in the German State of Baden-Württemberg between 2006 and 2012. Applying a principal component analysis/rough set theory mixed methodology, we explore performance-related business model classification rules in the heterogeneous sample of business plans. We find that ventures need to demonstrate real interactions with their customers' needs to survive. The distinguishing success rules are related to patent applications, risk capital, and scaling of the organisation. The rules help practitioners to classify business models in a way that allows them to prioritise action for performance.

Sleep analysis using a Polysomnography system is difficult and expensive. That is why we suggest a non-invasive and unobtrusive measurement. Very few people want the cables or devices attached to their bodies during sleep. The proposed approach is to implement a monitoring system, so the subject is not bothered. As a result, the idea is a non-invasive monitoring system based on detecting pressure distribution. This system should be able to measure the pressure differences that occur during a single heartbeat and during breathing through the mattress. The system consists of two blocks signal acquisition and signal processing. This whole technology should be economical to be affordable enough for every user. As a result, preprocessed data is obtained for further detailed analysis using different filters for heartbeat and respiration detection. In the initial stage of filtration, Butterworth filters are used.

Random matrices are widely used to estimate the extent of an elliptically contoured object. Usually, it is assumed that the measurements follow a normal distribution, with its standard deviation being proportional to the object’s extent. However, the random matrix approach can filter the center of gravity and the covariance matrix of measurements independently of the measurement model. This work considers the whole chain from data acquisition to the linear Kalman Filter with extension estimation as a reference plant. The input is the (unknown) ground truth (position and extent). The output is the filtered center of gravity and the filtered covariance matrix of the measurement distribution. A virtual measurement model emulates the behavior of the reference plant. The input of the virtual measurement model is adapted using the proposed algorithm until the output parameters of the virtual measurement model match the result of the reference plant. After the adaptation, the input to the virtual measurement model is considered an estimation for position and extent. The main contribution of this paper is the reference model concept and an adaptation algorithm to optimize the input of the virtual measurement model.

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.

Continuous monitoring of a patient's vital signs is essential in many chronic illnesses. The respiratory rate (RR) is one of the vital signs indicating breathing diseases. This article proposes the initial investigation for determining the accelerometric sensor position of a non-invasive and unobtrusive respiratory rate monitoring system. This research aims to determine the sensor position in relation to the patient, which can provide the most accurate values of the mentioned physiological parameter. In order to achieve the result, the particular system setup, including a mechanical sensor holder construction was used. The breathing signals from 5 participants were analyzed corresponding to the relaxed state. The main criterion for selecting a suitable sensor position was each patient's average acceleration amplitude excursion, which corresponds to the respiratory signal. As a result, we provided one more defined important parameter for the considered system, which was not determined before.

The Unscented Kalman Filter (UKF) is widely used for the state, disturbance, and parameter estimation of nonlinear dynamic systems, for which both process and measurement uncertainties are represented in a probabilistic form. Although the UKF can often be shown to be more reliable for nonlinear processes than the linearization-based Extended Kalman Filter (EKF) due to the enhanced approximation capabilities of its underlying probability distribution, it is not a priori obvious whether its strategy for selecting sigma points is sufficiently accurate to handle nonlinearities in the system dynamics and output equations. Such inaccuracies may arise for sufficiently strong nonlinearities in combination with large state, disturbance, and parameter covariances. Then, computationally more demanding approaches such as particle filters or the representation of (multi-modal) probability densities with the help of (Gaussian) mixture representations are possible ways to resolve this issue. To detect cases in a systematic manner that are not reliably handled by a standard EKF or UKF, this paper proposes the computation of outer bounds for state domains that are compatible with a certain percentage of confidence under the assumption of normally distributed states with the help of a set-based ellipsoidal calculus. The practical applicability of this approach is demonstrated for the estimation of state variables and parameters for the nonlinear dynamics of an unmanned surface vessel (USV).

There have been substantial research efforts for algorithms to improve continuous and automated assessment of various health-related questions in recent years. This paper addresses the deployment gap between those improving algorithms and their usability in care and mobile health applications. In practice, most algorithms require significant and founded technical knowledge to be deployed at home or support healthcare professionals. Therefore, the digital participation of persons in need of health care professionals lacks a usable interface to use the current technological advances. In this paper, we propose applying algorithms taken from research as web-based microservices following the common approach of a RESTful service to bridge the gap and make algorithms accessible to caregivers and patients without technical knowledge and extended hardware capabilities. We address implementation details, interpretation and realization of guidelines, and privacy concerns using our self-implemented example. Also, we address further usability guidelines and our approach to those.

The respiratory rate is a vital sign indicating breathing illness. It is necessary to analyze the mechanical oscillations of the patient's body arising from chest movements. An inappropriate holder on which the sensor is mounted, or an inappropriate sensor position is some of the external factors which should be minimized during signal registration. This paper considers using a non-invasive device placed under the bed mattress and evaluates the respiratory rate. The aim of the work is the development of an accelerometer sensor holder for this system. The normal and deep breathing signals were analyzed, corresponding to the relaxed state and when taking deep breaths. The evaluation criterion for the holder's model is its influence on the patient's respiratory signal amplitude for each state. As a result, we offer a non-invasive system of respiratory rate detection, including the mechanical component providing the most accurate values of mentioned respiratory rate.

In this paper, a novel feature-based sampling strategy for nonlinear Model Predictive Path Integral (MPPI) control is presented. Using the MPPI approach, the optimal feedback control is calculated by solving a stochastic optimal control (OCP) problem online by evaluating the weighted inference of sampled stochastic trajectories. While the MPPI algorithm can be excellently parallelized, the closed-loop performance strongly depends on the information quality of the sampled trajectories. To draw samples, a proposal density is used. The solver’s and thus, the controller’s performance is of high quality if the sampled trajectories drawn from this proposal density are located in low-cost regions of state-space. In classical MPPI control, the explored state-space is strongly constrained by assumptions that refer to the control value’s covariance matrix, which are necessary for transforming the stochastic Hamilton–Jacobi–Bellman (HJB) equation into a linear second-order partial differential equation. To achieve excellent performance even with discontinuous cost functions, in this novel approach, knowledge-based features are introduced to constitute the proposal density and thus the low-cost region of state-space for exploration. This paper addresses the question of how the performance of the MPPI algorithm can be improved using a feature-based mixture of base densities. Furthermore, the developed algorithm is applied to an autonomous vessel that follows a track and concurrently avoids collisions using an emergency braking feature. Therefore, the presented feature-based MPPI algorithm is applied and analyzed in both simulation and full-scale experiments.

One of the most critical factors for a successful road trip is a high degree of alertness while driving. Even a split second of inattention or sleepiness in a crucial moment, will make the difference between life and death. Several prestigious car manufacturers are currently pursuing the aim of automated drowsiness identification to resolve this problem. The path between neuro-scientific research in connection with artificial intelligence and the preservation of the dignity of human individual’s and its inviolability, is very narrow. The key contribution of this work is a system of data analysis for EEGs during a driving session, which draws on previous studies analyzing heart rate (ECG), brain waves (EEG), and eye function (EOG). The gathered data is hereby treated as sensitive as possible, taking ethical regulations into consideration. Obtaining evaluable signs of evolving exhaustion includes techniques that obtain sleeping stage frequencies, problematic are hereby the correlated interference’s in the signal. This research focuses on a processing chain for EEG band splitting that involves band-pass filtering, principal component analysis (PCA), independent component analysis (ICA) with automatic artefact severance, and fast fourier transformation (FFT). The classification is based on a step-by-step adaptive deep learning analysis that detects theta rhythms as a drowsiness predictor in the pre-processed data. It was possible to obtain an offline detection rate of 89% and an online detection rate of 73%. The method is linked to the simulated driving scenario for which it was developed. This leaves space for more optimization on laboratory methods and data collection during wakefulness-dependent operations.

In many cases continuous monitoring of vital signals is required and low intrusiveness is an important requirement. Incorporating monitoring systems in the hospital or home bed could have benefits for patients and caregivers. The objective of this work is the definition of a measurement protocol and the creation of a data set of measurements using commercial and low-cost prototypes devices to estimate heart rate and breathing rate. The experimental data will be used to compare results achieved by the devices and to develop algorithms for feature extraction of vital signals.

Der Beitrag beschreibt beispielhaft die administrativen, organisatorischen und sozialen Voraussetzungen gelungener Austauschprogramme mit chinesischen Partnerhochschulen. Hierzu gehört neben einer intensiven Beziehungspflege mit diesen Partnerinstitutionen eine gelebte Willkommenskultur für chinesische Studierende an der deutschen Hochschule. Letztere beinhaltet eine über die notwendigen administrativen Prozesse hinausgehende Betreuung, besondere Kursangebote sowie eine kontinuierliche Vernetzung und Einbindung der chinesischen Studierenden durch verschiedene extracurriculare Aktivitäten zur Integration in den Studienalltag und in das Alltagsleben über verschiedene Phasen hinweg (vor der Ausreise, bei der Ankunft, im Verlauf des Studiums, bei der Gestaltung von Praxisphasen sowie beim Übergang ins Berufsleben). Als Teil dieses Maßnahmenplans fördern interkulturelle Kursangebote in kulturell gemischten Gruppen nicht nur die Integration der chinesischen Studierenden. Sie leisten auch einen wichtigen Beitrag zur Stärkung der internationalen Ausbildung deutscher Studierender im Sinne einer internationalization@home. Entsprechende Angebote erhöhen damit die Wertschätzung von Internationalisierung als Mehrwert für die gesamte Hochschule. Gleichzeitig unterstützen sie den Ausbau interkultureller Sensibilität als wichtiger Qualifikation für das zukünftige Berufsleben für die Studierenden beider Seiten. Um all diese Maßnahmen zu verwalten und umzusetzen, sind personelle Ressourcen zur Betreuung und Evaluation der Programme erforderlich. Darüber hinaus bedarf es einer konstruktiven Kommunikationskultur zwischen verschiedenen Abteilungen der Hochschule sowie hinreichend mit China-Kompetenz ausgestatteter Akteur*innen (Mitarbeiter*innen im Akademischen Auslandsamt, Professor*innen, Auslands- und Regionalbeauftragte etc.).

Angesichts des rasanten wirtschaftlichen und wissenschaftlichen Aufstrebens Chinas offenbart sich an deutschen Hochschulen ein deutlicher Mangel an China-Kompetenzen auf allen Ebenen. Wie sind chinesische Kooperationspartner*innen einzuschätzen? Wie sollten Studierende ausgebildet werden, damit sie in Zukunft informiert und (selbst-)bewusst zusammenarbeiten können? Wie kann erreicht werden, dass chinesische Studierende ihre Zeit in Deutschland als akademisch und persönlich bereichernd empfinden? Best practice-Beispiele von elf deutschen Hochschulen geben Anregungen, die sich auch übergreifend auf verschiedene Bildungseinrichtungen und Partnerländer übertragen lassen.

Die zunehmende internationale Vernetzung der akademischen Welt, die sich in den aktuellen Internationalisierungsbemühungen deutscher Hochschulen widerspiegelt, erfordert eine Auseinandersetzung mit interkulturellen Aspekten der Hochschuldidaktik. Unterschiedliche Lernstile und Rollenerwartungen an Lehrende und Studierende beeinflussen die gegenseitige Wahrnehmung und den Studienerfolg. Der Beitrag reflektiert Erfahrungen deutscher/westlicher Lehrender und chinesischer Studierender: Aus verschiedenen Perspektiven und auf unterschiedlichen Ebenen werden Diskrepanzen zwischen Erwartungen und tatsächlichen Gegebenheiten aufgezeigt und im Kontext unterschiedlicher Lerntraditionen erklärt. Dabei stehen die Anforderungen an die Lehrenden als den zentralen Akteur*innen einer erfolgreichen Wissensvermittlung im Vordergrund. Im internationalen Kontext sind ihre interkulturellen Kompetenzen ähnlich wichtig wie ihre Fachkompetenzen. Die chinesische Lerntradition erschwert chinesischen Studierenden einen direkten Anschluss an die Studienkultur im deutschen Hochschulsystem. Zu dem Hemmnis, in einer Fremdsprache zu studieren, kommt die Schwierigkeit, Debattenkultur und Wissenschaftsstreit als angemessene Auseinandersetzungsformen zu verstehen. Der direkte, offene und häufig nur aus westlicher Sicht als objektiv empfundene Umgang mit Themen kann aufgrund unterschiedlicher kultureller Prägung dazu beitragen, dass das Studium in Deutschland als anstrengend und befremdlich empfunden wird. In diesem Beitrag werden erfahrungsbasierte Überlegungen geteilt, wie chinesische Studierende an die Debattenkultur an deutschen Hochschulen herangeführt werden können. Der Beitrag endet mit Hinweisen und guidelines für deutsche Lehrende im Umgang mit chinesischen Studierenden.

Recognition of sleep and wake states is one of the relevant parts of sleep analysis. Performing this measurement in a contactless way increases comfort for the users. We present an approach evaluating only movement and respiratory signals to achieve recognition, which can be measured non-obtrusively. The algorithm is based on multinomial logistic regression and analyses features extracted out of mentioned above signals. These features were identified and developed after performing fundamental research on characteristics of vital signals during sleep. The achieved accuracy of 87% with the Cohen’s kappa of 0.40 demonstrates the appropriateness of a chosen method and encourages continuing research on this topic.

Nowadays, the importance of early active patient mobilization in the recovery and rehabilitation phase has increased significantly. One way to involve patients in the treatment is a gamification-like approach, which is one of the methods of motivation in various life processes. This article shows a system prototype for patients who require physical activity because of active early mobilization after medical interventions or during illness. Bedridden patients and people with a sedentary lifestyle (predominantly lying in bed) are also potential users. The main idea for the concept was non-contact system implementation for the patients making them feel effortless during its usage. The system consists of three related parts: hardware, software, and game application. To test the relevance and coherence of the system, it was used by 35 people. The participants were asked to play a video game requiring them to make body movements while lying down. Then they were asked to take part in a small survey to evaluate the system's usability. As a result, we offer a prototype consisting of hardware and software parts that can increase and diversify physical activity during active early mobilization of patients and prevent the occurrence of possible health problems due to predominantly low activity. The proposed design can be possibly implemented in hospitals, rehabilitation centers, and even at home.

In recent decades, it can be observed that a steady increase in the volume of tourism is a stable trend. To offer travel opportunities to all groups, it is also necessary to prepare offers for people in need of long-term care or people with disabilities. One of the ways to improve accessibility could be digital technologies, which could help in planning as well as in carrying out trips. In the work presented, a study of barriers was first conducted, which led to selecting technologies for a test setup after analysis. The main focus was on a mobile app with travel information and 360° tours. The evaluation results showed that both technologies could increase accessibility, but some essential aspects (such as usability, completeness, relevance, etc.) need to be considered when implementing them.

The digital twin concept has been widely known for asset monitoring in the industry for a long time. A clear example is the automotive industry. Recently, there has also been significant interest in the application of digital twins in healthcare, especially in genomics in what is known as precision medicine. This work focuses on another medical speciality where digital twins can be applied, sleep medicine. However, there is still great controversy about the fundamentals that constitute digital twins, such as what this concept is based on and how it can be included in healthcare effectively and sustainably. This article reviews digital twins and their role so far in what is known as personalized medicine. In addition, a series of steps will be exposed for a possible implementation of a digital twin for a patient suffering from sleep disorders. For this, artificial intelligence techniques, clinical data management, and possible solutions for explaining the results derived from artificial intelligence models will be addressed.

This paper presents the docking control of an autonomous vessel using the nonlinear Model Predictive Path Integral (MPPI) approach. This algorithm is based on a path integral over stochastic trajectories and can be parallelized easily. The controller parameters are tuned offline using knowledge of the system and simulations, including nonlinear state and disturbance observer. The cost function implicitly contains information regarding the surrounding of the docking position. This approach allows continuous optimization of the trajectory with respect to the system state, disturbance state and actuator dynamics. The control strategy has been tested in full-scale experiments using the solar research vessel Solgenia. The investigated MPPI controller has demonstrated excellent performance in both, simulation and real-world experiments. This paper addresses the question of how the MPPI algorithm can be applied to dock a fully-actuated vessel and what benefits its application achieves.

Zur Bewertung von Strategien und Handlungsoptionen im Themenfeld Bioökonomie ist es naheliegend, eine naturinspirierte Bewertungsmethodik zu verwenden. Dieser Beitrag stellt daher den biokybernetischen Ansatz nach Frederic Vester als Methodik in den Mittelpunkt, um nachhaltigkeitskonforme Passungskriterien für bioökonomische Innovationen und Konzepte zu beschreiben sowie insbesondere die systemischen Wechselwirkungen und damit die Komplexität dieses Themenfeldes zu erfassen. So wird auch die Ambivalenz von Innovationen im Themen- und Handlungsfeld Bioökonomie thematisiert. Letztlich können mit diesem Ansatz die prinzipiellen Voraussetzungen für nachhaltigkeitsorientierte bioökonomische Innovationen in Richtung Erneuerbarkeit, Zirkularität, Effizienz, ökologische Verträglichkeit und Klimaneutralität geklärt werden.

Large persistent memory is crucial for many applications in embedded systems and automotive computing like AI databases, ADAS, and cutting-edge infotainment systems. Such applications require reliable NAND flash memories made for harsh automotive conditions. However, due to high memory densities and production tolerances, the error probability of NAND flash memories has risen. As the number of program/erase cycles and the data retention times increase, non-volatile NAND flash memories' performance and dependability suffer. The read reference voltages of the flash cells vary due to these aging processes. In this work, we consider the issue of reference voltage adaption. The considered estimation procedure uses shallow neural networks to estimate the read reference voltages for different life-cycle conditions with the help of histogram measurements. We demonstrate that the training data for the neural networks can be enhanced by using shifted histograms, i.e., a training of the neural networks is possible based on a few measurements of some extreme points used as training data. The trained neural networks generalize well for other life-cycle conditions.

Personalized remote healthcare monitoring is in continuous development due to the technology improvements of sensors and wearable electronic systems. A state of the art of research works on wearable sensors for healthcare applications is presented in this work. Furthermore, a state of the art of wearable devices, chest and wrist band and smartwatches available on the market for health and sport monitoring is presented in this paper. Many activity trackers are commercially available. The prices are continuously reducing and the performances are improving, but commercial devices do not provide raw data and are therefore not useful for research purposes.

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.

Die vorliegende Studie analysiert die Barrierefreiheit der Stadt Konstanz im Hinblick auf Angebote für und Nachfrage von Touristinnen und Touristen. Die Datenerhebung basierte auf einem Methodenmix aus Interviews und Umfragen von Probanden und Probandinnen mit Behinderungen und zuständigen Akteurinnen und Akteuren in der Stadtplanung sowie Begehungen vor Ort. Als theoretische Grundlage wird das Modell der Unabhängigkeit nach Nosek and Fuhrer (1992) verwendet. Die Untersuchung zeigt, dass der Bedarf an barrierefreien Angeboten sehr divers ist und die Umsetzung im Sinne eines Universal Design durch die zunehmende Nachfrage zentral. Die Analyse des Tourismusraum Konstanz zeigt Schwachpunkte und Stärken, mit denen sich Implikationen für andere Tourismusregionen ableiten lassen.

Reed-Muller (RM) codes have recently regained some interest in the context of low latency communications and due to their relation to polar codes. RM codes can be constructed based on the Plotkin construction. In this work, we consider concatenated codes based on the Plotkin construction, where extended Bose-Chaudhuri-Hocquenghem (BCH) codes are used as component codes. This leads to improved code parameters compared to RM codes. Moreover, this construction is more flexible concerning the attainable code rates. Additionally, new soft-input decoding algorithms are proposed that exploit the recursive structure of the concatenation and the cyclic structure of the component codes. First, we consider the decoding of the cyclic component codes and propose a low complexity hybrid ordered statistics decoding algorithm. Next, this algorithm is applied to list decoding of the Plotkin construction. The proposed list decoding approach achieves near-maximum-likelihood performance for codes with medium lengths. The performance is comparable to state-of-the-art decoders, whereas the complexity is reduced.

Large-scale quantum computers threaten the security of today's public-key cryptography. The McEliece cryptosystem is one of the most promising candidates for post-quantum cryptography. However, the McEliece system has the drawback of large key sizes for the public key. Similar to other public-key cryptosystems, the McEliece system has a comparably high computational complexity. Embedded devices often lack the required computational resources to compute those systems with sufficiently low latency. Hence, those systems require hardware acceleration. Lately, a generalized concatenated code construction was proposed together with a restrictive channel model, which allows for much smaller public keys for comparable security levels. In this work, we propose a hardware decoder suitable for a McEliece system based on these generalized concatenated codes. The results show that those systems are suitable for resource-constrained embedded devices.

Code-based cryptosystems are promising candidates for post-quantum cryptography. Recently, generalized concatenated codes over Gaussian and Eisenstein integers were proposed for those systems. For a channel model with errors of restricted weight, those q-ary codes lead to high error correction capabilities. Hence, these codes achieve high work factors for information set decoding attacks. In this work, we adapt this concept to codes for the weight-one error channel, i.e., a binary channel model where at most one bit-error occurs in each block of m bits. We also propose a low complexity decoding algorithm for the proposed codes. Compared to codes over Gaussian and Eisenstein integers, these codes achieve higher minimum Hamming distances for the dual codes of the inner component codes. This property increases the work factor for a structural attack on concatenated codes leading to higher overall security. For comparable security, the key size for the proposed code construction is significantly smaller than for the classic McEliece scheme based on Goppa codes.

Nowadays, most digital modulation schemes are based on conventional signal constellations that have no algebraic group, ring, or field properties, e.g. square quadrature-amplitude modulation constellations. Signal constellations with algebraic structure can enhance the system performance. For instance, multidimensional signal constellations based on dense lattices can achieve performance gains due to the dense packing. The algebraic structure enables low-complexity decoding and detection schemes. In this work, signal constellations with algebraic properties and their application in spatial modulation transmission schemes are investigated. Several design approaches of two- and four-dimensional signal constellations based on Gaussian, Eisenstein, and Hurwitz integers are shown. Detection algorithms with reduced complexity are proposed. It is shown, that the proposed Eisenstein and Hurwitz constellations combined with the proposed suboptimal detection can outperform conventional two-dimensional constellations with ML detection.

Im Kapitel "Unternehmensberatung" geht es um die Themen, inhaltlichen Schwerpunkte und möglichen Ansätze von Beratungsdienstleistungen im Kontext heutiger angewandter Unternehmensethik. Von der Gestaltung einer Unternehmenskultur der Integrität zur Prävention von Wirtschaftskriminalität bis zur Entwicklung eines ganzheitlichen unternehmerischen Verantwortungsmanagements, das neben Nachhaltigkeitsaspekten auch einen ethisch reflektierten Umgang mit Digitalisierung und KI umfasst.

Wie gehen mittelständische Unternehmen mit internationaler Geschäftstätigkeit mit Compliance-Risiken um? Wie gelingt das Risikomanagement spezifischer Herausforderungen der Regelkonformität in Wachstumsländern, die aus Compliance-Gesichtspunkten als Hochrisikoländer eingestuft werden? Und was beschäftigt dabei Compliance-Officer im Mittelstand? Diesen Fragen widmete sich ein anwendungsorientiertes Forschungsprojekt am Konstanz Institut für Corporate Governance.

Welche Kompetenzen brauchen Führungskräfte, damit der Ansatz Compliance und Integrity als Führungsaufgabe in Organisationen verfängt? Und wie lassen sich diese systematisch nutzen und trainieren? Der Beitrag stellt den ersten Baustein eines am Konstanz Institut für Corporate Governance angesiedelten Forschungsprojekts vor, das darauf abzielt, bestehende Compliance-Systeme in Unternehmen praxistauglicher zu machen und die Wirksamkeit der Maßnahmen eines Compliance-Management-Systems (CMS) zu steigern.

Dieser Beitrag untersucht, ob externe Interventionen, in Form von Forschung und/oder Wissenschaftskommunikation, als Mediator für Innovationen in Krisenzeiten in der Tourismusbranche fungieren können. Dabei wird anhand dreier Case Studies diskutiert, inwiefern die Corona-Krise ein Window- of-opportunity für innovative Geschäftsmodelle im Tourismus darstellen konnte. Die Projektergebnisse geben Hinweise darauf, dass Krisen im Allgemeinen und Wissenschaftskommunikation im Speziellen als Push-Faktoren Innovationen befördern können. Zwar kam es bei den Projektpartnern zu einer Entwicklung von Innovationen im Projektzeitraum, jedoch wurde die Implementierung vermehrt in eine unbestimmte Zukunft verschoben. Durch die damit verbundene Rückkehr zum Status-Quo blieben die angestoßenen Innovationen zu einem Großteil auf einer konzeptionellen Ebene. Dies deutet auf eine Attitude-behavior-gap in Bezug auf die Schaffung und Umsetzung von Innovationen in Krisenzeiten.

In this paper, we propose a novel method for real-time control of electric distribution grids with a limited number of measurements. The method copes with the changing grid behaviour caused by the increasing number of renewable energies and electric vehicles. Three AI based models are used. Firstly, a probabilistic forecasting estimates possible scenarios at unobserved grid nodes. Secondly, a state estimation is used to detect grid congestion. Finally, a grid control suggests multiple possible solutions for the detected problem. The best countermeasures are then detected by evaluating the systems stability for the next time-step.

This paper presents a systematic comparison of different advanced approaches for motion prediction of vessels for docking scenarios. Therefore, a conventional nonlinear gray-box-model, its extension to a hybrid model using an additional regression neural network (RNN) and a black-box-model only based on a RNN are compared. The optimal hyperparameters are found by grid search. The training and validation data for the different models is collected in full-scale experiments using the solar research vessel Solgenia. The performances of the different prediction models are compared in full-scale scenarios. %To use the investigated approaches for controller design, a general optimal control problem containing the advanced models is described. These can improve advanced control strategies e.g., nonlinear model predictive control (NMPC) or reinforcement learning (RL). This paper explores the question of what the advantages and disadvantages of the different presented prediction approaches are and how they can be used to improve the docking behavior of a vessel.

This paper aims to focus on the development of a vision for the Lake Constance region, Germany, as an e-destination, i.e. a destination where tourism mobility would be predominantly electric in the future.