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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.).
Wirtschaftsprüfung
(2022)
Vertrauen durch Integrität
(2022)
Durch eine Aufweitung des Kristallgitters mittels Niedertemperatur-Eindiffusion von Kohlenstoff und/oder Stickstoffatomen können in der Randzone von nichtrostenden Stählen eine hohe Härte und eine hohe Verschleißbeständigkeit erzeugt werden, ohne dass zusätzliche Legierungselemente verwendet werden müssen. Die metallkundlichen Hintergründe für die Härtung, die Wirkung auf Verschleißvorgänge und mögliche Anwendungsbereiche werden geschildert. Anhand von Reibwerten wird gezeigt, in welcher Weise das Reibungsverhalten bei Schraubverbindungen durch die Behandlung verändert wird. Über Migrationsversuche wird nachgewiesen, dass die Ionenabgabe durch die Oberflächenhärtung nicht erhöht, sondern sogar abgesenkt wird. Neben dem besseren Verschleißschutz und einer höheren Dauerfestigkeit sichert diese Oberflächenbehandlung am nichtrostenden Stahl den Schutz gegen die Kontamination von Pharmaprodukten durch Metallabrieb/-ionen. Tests an oberflächengehärteten Edelstahlproben ergaben weiterhin, dass durch die Oberflächenhärtung die Biokompatibilität des nichtrostenden Edelstahls nicht beeinträchtigt wird.
Unternehmenskultur
(2022)
Unternehmenskultur als die zentrale informeller Steuerungsgröße von Organisationen spielt insbesondere bei der Verankerung ethischer Werte und Prinzipien in Unternehmen eine unverzichtbare Rolle. Warum dies so ist und welchen konkreten Beitrag eine bewusste Kulturentwicklung im Kontext angewandter Unternehmensethik leisten kann, ist Gegenstand des Artikels.
Unternehmensberatung
(2022)
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.
As organizations struggle to cope with digital transformation in
an innovation environment, partnerships between startups and established
companies have become increasingly important. Building upon years of
practical experience and empirical research, we present advantages,
obstacles, and the keys to successful corporate-startup collaboration.
Low-Code Development Platforms (LCDPs) enable non-information technology (IT) personnel to develop applications and workflows independently of the IT department. Consequently, these digital platforms help to overcome the growing need for software development. However, science and practice warn of several barriers that slow down or hinder the usage of LCDPs. This publication scientifically identifies, analyzes, and discusses challenges during implementation and application of LCDPs from both perspectives in a holistic manner. Therefore, we conduct an exploratory study (data from scientific literature, expert interviews, and practical studies) and assign the challenges to the socio-technical system model. The results show that the scientific and practical communities recognize common challenges (especially knowledge transfer) but also perceive differences related to technological (science) and social (practice) aspects. This paper proposes future research directions for academia, such as governance, culture change, and value evaluation of LCDPs. Additionally, practitioners can prepare for possible challenges when using LCPDs.
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.
Traggerüste
(2022)
Virtual measurement models (VMM) can be used to generate artificial measurements and emulate complex sensor models such as Lidar. The input of the VMM is an estimation and the output is the set of measurements this estimation would cause. A Kalman filter with extension estimation based on random matrices is used to filter mean and covariance of the real measurements. If these match the mean and covariance of the artificial measurements, then the given estimation is appropriate. The optimal input of the VMM is found using an adaptation algorithm. In this paper, the VMM approach is expanded for multi-extended object tracking where objects can be occluded and are only partially visible. The occlusion can be compensated if the extension estimation is performed for all objects together. The VMM now receives as input an estimation for the multi-object state and the output are the measurements that this multi-object state would cause.
Adjusting the friction response of the wheel-rail interface is a key factor in the mitigation of wear and rollingcontact fatigue (RCF) in rails. The use of top-of-rail (TOR) friction conditioners has the potential to reduce maintenance costs significantly. Unfortunately, conflicting results on the use of commercial TOR conditioners have been presented in the literature. In this work, the performance of commercial TOR conditioners and a laboratory-made formulation were tested, both on the lab scale and in field measurements. Friction results are discussed together with the structural and chemical analysis of the tested materials.
Dissipation of heat can be a major challenge when applying sensor systems outdoors under varying environmental conditions. Typically, complex software and knowledge is needed to optimize thermal management. In this paper it is shown how the thermal optimization of a LiDAR (light detection and ranging) sensor can be performed efficiently. This approach uses standard CAD (computer aided design) software, which is readily available, and saves time and cost as the thermal design can be optimized before experimental realisation. A four-step process was developed and realized: (i) Measurement of the thermal energy distribution of the current sensor design; (ii) Simulation of the time-dependant thermal behaviour using standard CAD software; (iii) Simulation of a thermally optimized design. This was compared quantitatively with the original design and was also used for verification of sufficient increase in heat dissipation; (iv) Experimental realisation and verification of the optimized design. It could be shown that the optimized prototype shows significantly improved thermal behaviour in accordance with the predictions from the simulations. The new LiDAR sensor shows lower heat generation and optimized dissipation of thermal energy which proofs the applicability of the approach to complex sensors.
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.
Digitization extends to all areas of people's lives and processes, including public administration and government technology (GovTech for short). However, there are various problems here, such as the inappropriate development of new application systems, that are to be solved efficiently by combining two aspects: methodical digitization according to the process-driven approach and the idea of an app store for processes. This simultaneously fuels a process competition to advance methodical process digitization in the EU. Furthermore, this study explains the target-oriented use of this “firing” within the EU and concludes with a proposal of a new 3-schema architecture standard for successful process digitization within the EU.
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.
Das 'essential' behandelt die technoökonomischen Grundlagen und deren Anwendung auf die Schlüsseltechnologien der Energiewende. Zunächst erfolgt eine inhaltliche Klärung und formale Herleitung von statischen und dynamischen Skaleneffekten sowie eine Übersicht bzgl. deren unterschiedlicher Kombinationsmöglichkeiten für die Diskussion von Best- und Worst-Case-Szenarien. Für eine Anwendung dieser Grundlagen stehen zunächst die diversen brennstoffbasierten KWK-Varianten, insbesondere Blockheizkraftwerke (BHKW), im Zentrum. Anschließend erfolgt eine Ausweitung der Betrachtungen auf die regenerativen Energietechnologien Photovoltaik und Windkraft. Mit einem kurzen Blick auf weitere Technologien wie Wärmepumpen sowie elektrische und thermische Energiespeicher finden diese Darstellungen ihren Abschluss.
Targetless Lidar-camera registration is a repeating task in many computer vision and robotics applications and requires computing the extrinsic pose of a point cloud with respect to a camera or vice-versa. Existing methods based on learning or optimization lack either generalization capabilities or accuracy. Here, we propose a combination of pre-training and optimization using a neural network-based mutual information estimation technique (MINE [1]). This construction allows back-propagating the gradient to the calibration parameters and enables stochastic gradient descent. To ensure orthogonality constraints with respect to the rotation matrix we incorporate Lie-group techniques. Furthermore, instead of optimizing on entire images, we operate on local patches that are extracted from the temporally synchronized projected Lidar points and camera frames. Our experiments show that this technique not only improves over existing techniques in terms of accuracy, but also shows considerable generalization capabilities towards new Lidar-camera configurations.
Die Beständigkeit von hochlegierten korrosions- und säurebeständigen Stählen wird primär durch den Chromgehalt bestimmt. Allerdings gibt es entlang der Wertschöpfungskette von der Stahlerschmelzung bis zum fertigen Produkt eine Vielzahl weiterer Einflussfaktoren. Dem Schleifen kommt hier eine besondere Bedeutung zu, da es je nach Wahl der Prozessparameter sowohl zu einer signifikanten Verschlechterung als auch zu einer Verbesserung der Korrosionsbeständigkeit führen kann. Im vorliegenden Beitrag wird aufgezeigt, dass die erzeugte Rauheit nur eine begrenzte Aussagekraft bietet. Vielmehr erhöhen lokale Mikrodefekte die Anfälligkeit gegen Lochfraß – je nach Ausprägung und Anzahl. Die Automatisierung für die Innenbearbeitung von Behältern im pharmazeutischen Apparatebau kann dabei zu einer signifikanten Verbesserung der Oberfläche und einem homogeneren Erscheinungsbild führen.
Systematic Generation of XSS and SQLi Vulnerabilities in PHP as Test Cases for Static Code Analysis
(2022)
Synthetic static code analysis test suites are important to test the basic functionality of tools. We present a framework that uses different source code patterns to generate Cross Site Scripting and SQL injection test cases. A decision tree is used to determine if the test cases are vulnerable. The test cases are split into two test suites. The first test suite contains 258,432 test cases that have influence on the decision trees. The second test suite contains 20 vulnerable test cases with different data flow patterns. The test cases are scanned with two commercial static code analysis tools to show that they can be used to benchmark and identify problems of static code analysis tools. Expert interviews confirm that the decision tree is a solid way to determine the vulnerable test cases and that the test suites are relevant.
This paper presents the swinging up and stabilization control of a Furuta pendulum using the recently published 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 regarding the nonlinear system dynamics and simulations. Constraints in terms of state and input are taken into account in the cost function. The presented approach sequentially computes an optimal control sequence that minimizes this optimal control problem online. The control strategy has been tested in full-scale experiments using a pendulum prototype. The investigated MPPI controller has demonstrated excellent performance in simulation for the swinging up and stabilizing task. In order to also achieve outstanding performance in a real-world experiment using a controller with limited computing power, a linear quadratic controller (LQR) is designed for the stabilization task. In this paper, the determination of the controller parameters for the MPPI algorithm is described in detail. Further, a discussion treats the advantages of the nonlinear MPPI control.
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 Black Forest offers renewable energy as a specific tourist destination in the form of bioenergy villages (BEV). Particularly expert tourists tend to visit them. The results of two quantitative surveys on the supply and demand side show that there is, up to now, an untapped potential among experienceoriented
tourists for this type of niche tourism.
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.
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.
Dynamic Real-Time Range Queries (DRRQ) are a common means to handle mobile clients in high-density areas where both, clients requested by the query and the inquirers, are mobile. In contrast to the very well-known continuous range queries, only a few approaches, such as Adaptive Quad Streaming (AQS), address the mandatory scalability and real-time requirements of these so-called ad-hoc mobility challenges. In this paper we present the highly decentralized solution Adaptive Quad Streaming Flexible (AQSflex) as an extension of the already existing more theoretical AQS approach. Beside a highly distributed cell structure without data structures and a lightweight streaming communication, we use a multi-cell-assignment on limited pool resources instead of an idealistic unlimited cell-per-server assignment. The described experimental results show the potential of our local capacity balancing scheme for cell handover in a strongly decentralized setting. Leafs of a cell hierarchy define a kind of self-optimizing fuzzy edge for the processing resources in high-density systems without any centralized controlling or cloud component.
Driver assistance systems are increasingly becoming part of the standard equipment of vehicles and thus contribute to road safety. However, as they become more widespread, the requirements for cost efficiency are also increasing, and so few and inexpensive sensors are used in these systems. Especially in challenging situations, this leads to the fact that target discrimination cannot be ensured which in turn leads to a false reaction of the driver assistance system. Typically, the interaction between moving traffic participants is not modeled directly in the environmental model so that tracked objects can split, merge or disappear. The Boids flocking algorithm is used to model the interaction between road users on already tracked objects by applying the movement rules (separation, cohesion, alignment) on the boids. This facilitates the creation of semantic neighborhood information between road users. We show in a comprehensive simulation that with only 7 boids per traffic participant, the estimated median separation between objects can improve from 2.4 m to 3 m for a ground truth of 3.7 m. The bottom percentile improves from 1.85 m to 2.8 m.
Lignin is a potentially high natural source of biological aromatic substances. However, decomposition of the polymer has proven to be quite challenging, as the complex bonds are fairly difficult to break down chemically. This article is intended to provide an overview of various recent methods for the catalytic chemical depolymerization of the biopolymer lignin into chemical products. For this purpose, nickel-, zeolite- and palladium-supported catalysts were examined in detail. In order to achieve this, various experiments of the last years were collected, and the efficiency of the individual catalysts was examined. This included evaluating the reaction conditions under which the catalysts work most efficiently. The influence of co-catalysts and Lewis acidity was also investigated. The results show that it is possible to control the obtained product selectivity very well by the choice of the respective catalysts combined with the proper reaction conditions.
Reliability Assessment of an Unscented Kalman Filter by Using Ellipsoidal Enclosure Techniques
(2022)
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).
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.
As interest in the investigation of possible sources and environmental sinks of technology-critical elements (TCEs) continues to grow, the demand for reliable background level information of these elements in environmental matrices increases. In this study, a time series of ten years of sediment samples from two different regions of the German North Sea were analyzed for their mass fractions of Ga, Ge, Nb, In, REEs, and Ta (grain size fraction < 20 µm). Possible regional differences were investigated in order to determine preliminary reference values for these regions. Throughout the investigated time period, only minor variations in the mass fractions were observed and both regions did not show significant differences. Calculated local enrichment factors ranging from 0.6 to 2.3 for all TCEs indicate no or little pollution in the investigated areas. Consequently, reference values were calculated using two different approaches (Median + 2 median absolute deviation (M2MAD) and Tukey inner fence (TIF)). Both approaches resulted in consistent threshold values for the respective regions ranging from 158 µg kg−1 for In to 114 mg kg−1 for Ce. As none of the threshold values exceed the observed natural variation of TCEs in marine and freshwater sediments, they may be considered baseline values of the German Bight for future studies.
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.
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.
Nachhaltige Entwicklung umfasst verschieden weite Definitionen und konzeptionelle Zugänge. Im Zentrum der Diskussion steht die zukünftige Entwicklungsfähigkeit von Biosphäre und Anthroposphäre im Sinne einer Koevolution. Thematisiert werden die zunehmende Eingriffstiefe in die Natur sowie die intersystemische Konkurrenz zwischen diesen beiden Sphären. Das evolutorische Verständnis der naturalen Produktion unterscheidet sich vom herkömmlichen Produktionsverständnis der Ökonomik. Aus diesen verschiedenen Zugängen ergibt sich ein Problemlösungsspektrum, das sich über eine integrative Verknüpfung der drei Strategieansätze und Handlungsfelder Effizienz, Konsistenz und Suffizienz erstreckt.
Die Automobilindustrie steht wirtschaftlich aktuell besser da, als von manchem erwartet. Sie steht aber gleichzeitig großen Herausforderungen gegenüber, denn wir erleben die Überlagerung dreier Transformationen, deren Auswirkungen sich wohl in keinem Markt so gravierend niederschlagen wie in diesem. Um hierbei die Rolle als Leitmarkt zu erhalten, braucht es mehr Veränderungsintelligenz und eine noch höhere Innovationsdynamik. Diese sind mit beidhändigen Organisationen zu erreichen, die die Ambidextrie beherrschen, gleichzeitig das Kerngeschäft zu optimieren und mit strategischer Innovation Zukunft zu erfinden.
In recent years, there has been a noticeable trend towards a general contractor strategy for plant engineering companies. Multiple disciplines and departments must be administered in a joint project. In the process, different work results are often managed in various systems without any associative relationship. A possible way to address this complexity is to implement a specifically tailored PLM strategy to gain a competitive advantage. Maturity models as well as methods to evaluate possible benefits constitute increasingly applied tools during this journey. Both methods have been theoretically described in previous publications. However, this paper should provide insights in the practical application within machinery industry. Therefore, a medium-sized German plant engineering company serves as an example for determining the scope and value of a multi-national overarching Product Lifecycle Management architecture as the central piece of a future digitalization strategy. The company’s current maturity levels for several digitalization capabilities are evaluated, prioritized and benchmarked against a set of similar companies. This allows to derive suitable target states in terms of maturity levels as well as the technical specification of digitalization use cases. In order to provide profound data for cost justification the resulting benefits are quantified.
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.
The use of deep learning models with medical data is becoming more widespread. However, although numerous models have shown high accuracy in medical-related tasks, such as medical image recognition (e.g. radiographs), there are still many problems with seeing these models operating in a real healthcare environment. This article presents a series of basic requirements that must be taken into account when developing deep learning models for biomedical time series classification tasks, with the aim of facilitating the subsequent production of the models in healthcare. These requirements range from the correct collection of data, to the existing techniques for a correct explanation of the results obtained by the models. This is due to the fact that one of the main reasons why the use of deep learning models is not more widespread in healthcare settings is their lack of clarity when it comes to explaining decision making.
Leveraging differences
(2022)
Mit Effizienz- und Konsistenzlösungen lässt sich sowohl der Energiebedarf vermindern, als auch mit einer besseren ökologischen und strukturellen Passung im
Sinne der Bioökonomie versehen. Dieser Beitrag stellt die Möglichkeiten zur Steigerung der industriellen Energieeffizienz mittels lernenden Energieeffizienz-Netzwerken vor. Thematisiert werden Konzepte zur Überwindung von Hemmnissen durch Lernerfahrungen, insbesondere mittels des Synergiekonzeptes als innovativer Lernplattform sowie die systemischen Wechselwirkungen in diesem Kontext. Darüber hinaus werden hierzu korrespondierende innovationsorientierte Organisationsvarianten für das betriebliche Energiemanagement erläutert. Abschließend beleuchtet der Beitrag Konzepte von betrieblichen und überbetrieblichen Energieverbünden, insbesondere der gekoppelten Energieerzeugung und -nutzung, z. B. im Bereich der Wärmenutzung.
We are interested in computing a mini-batch-capable end-to-end algorithm to identify statistically independent components (ICA) in large scale and high-dimensional datasets. Current algorithms typically rely on pre-whitened data and do not integrate the two procedures of whitening and ICA estimation. Our online approach estimates a whitening and a rotation matrix with stochastic gradient descent on centered or uncentered data. We show that this can be done efficiently by combining Batch Karhunen-Löwe-Transformation [1] with Lie group techniques. Our algorithm is recursion-free and can be organized as feed-forward neural network which makes the use of GPU acceleration straight-forward. Because of the very fast convergence of Batch KLT, the gradient descent in the Lie group of orthogonal matrices stabilizes quickly. The optimization is further enhanced by integrating ADAM [2], an improved stochastic gradient descent (SGD) technique from the field of deep learning. We test the scaling capabilities by computing the independent components of the well-known ImageNet challenge (144 GB). Due to its robustness with respect to batch and step size, our approach can be used as a drop-in replacement for standard ICA algorithms where memory is a limiting factor.
ISO 26000
(2022)
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 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.
In diesem Beitrag stellen wir Inhalte und Methoden des Kurses »How to communicate successfully in international teams« vor. Wir zeigen auf, wie einzelne Kurselemente mittels unseres methodisch-didaktischen Ansatzes get_connected vermittelt werden. Die Darstellung basiert auf der Dokumentation eines im Sommersemester 2021 in Kooperation zwischen der HTWG Konstanz und dem Beijing Institute of Technology (online) durchgeführten Kurses. Die im Rahmen der Lehrveranstaltung dokumentierten Reflexionen, Einsichten und Evaluationen der Kursteilnehmenden weisen auf einen Kompetenzaufbau im Hinblick auf die Fähigkeit zu Perspektivenwechsel, Selbstreflexion, Frustrationstoleranz, Flexibilität und empathische Kommunikation hin.
Der Artikel stellt den methodisch-didaktischen Ansatz get_connected zur Förderung der Zusammenarbeit in kulturell gemischten Teams vor. Mit diesem Ansatz reagiert die HTWG Konstanz auf die langjährige Erfahrung, dass sich trotz grundsätzlich optimaler struktureller Bedingungen für interkulturelles Lernen – mit regelmäßiger Teilnahme chinesischer Studierender im
Fachstudium an der deutschen Hochschule – beiderseitige Vorurteile über »die anderen« nicht automatisch auflösen, sondern sich sogar verstärken können. In der konkreten Zusammenarbeit zeigt sich, dass das eigene Handeln oftmals hinter dem für sich selbst formulierten Anspruch an kulturell adäquates Verhalten zurückbleibt. Mit Methoden des erfahrungsbasierten interkulturellen Lernens
und insbesondere durch die von den Lehrenden als Coachinnen bzw. Coaches begleitete Arbeit mit Emotionen in kulturell gemischten (deutsch-chinesischen) Gruppen werden die Studierenden darin unterstützt, als Vorbereitung auf eine zukünftige Tätigkeit in international vernetzten Teams ihr
Kommunikationsverhalten zu reflektieren, den Perspektivenwechsel sowie neue emotionale bzw. kommunikative Strategien einzuüben und damit ihre interkulturelle Handlungskompetenz – auch im deutsch-chinesischen Dialog – zu verbessern. Der Beitrag stellt den im Rahmen von designbased research über mehrere Semester hinweg (weiter-)entwickelten Ansatz get_connected und
seine Umsetzung in einem Kursformat zum Erwerb interkultureller (China-)Kompetenz für Studierende aller Fachrichtungen vor. Die konkreten Erfahrungen bei der (Online-)Durchführung des Kurskonzepts im Sommersemester 2021 an der HTWG Konstanz unter Einbeziehung chinesischer (und internationaler) Studierender der Partnerhochschule Beijing Institute of Technology werden
im Folgekapitel (Beitrag von Thelen, Bai und Obendiek) dargestellt.
A novel implant system for bone elongation will be presented. With this technique, the body's own bone material, so-called callus, can be formed by gradual distraction of the tubular bones, thus achieving an extension of femur and tibia bones. The driving principle of this fully implantable bone lengthening system is based on a shape memory element. During the surgical treatment, the intramedullary nail serves to stabilize the severed bone and enables the formation of new, endogenous bone material to lengthen the limbs or to bridge bone defects. The intramedullary nail is implanted into the medullary cavity and fixed at both ends with locking bolts. A receiver coil implanted under the skin receives the necessary energy twice a day through high-frequency energy transport to activate the thermal phase transformation of the shape memory element. This gradually increases the bone gap by 0.5 mm each time and stimulates callus formation. Consequently, osteoblasts or osteocytes are formed in the area of the desired bone extension and load-bearing bone material is formed. Three nail prototypes have already been tested for their functionality in a cadaver study in a German clinic. Currently a redesign of this intelligent implant system is underway, focusing on a novel coil geometry, a monitoring sensor system and control technology and a novel connection technology for the drive components. With this intelligent implant system, it will be possible for the first time to lengthen the bones in a patient-friendly manner and to continuously monitor, document and evaluate the entire lengthening process.
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.
The development of a new product can be accelerated by using an approach called crowdsourcing. The engineers compete and try their best to provide the related solution based on the given product requirement submitted in the online crowdsourcing platform. The one who has submitted the best solution get a financial reward. This approach is proven to be three time faster than the conventional one. However, the crowdsourcing process is usually not transparent to a new user. The risk for the execution of a new project for developing a new product is not easy to be calculated [1, 2]. We developed a method InnoCrowd to handle this problem and the new user could use during the planning of a new product development project. This system uses AI concepts to generate a knowledgebase representing histories of successful product development projects. The system uses the knowledge to determine qualitative and quantitative risks of a new project. This paper describes the new method, the InnoCrowd design, and results of a validation experiment based on data from a current crowdsourcing platform. Finally, we compare InnoCrowd to related methods and systems in terms of design and benefits.
Healthy sleep is required for sufficient restoration of the human body and brain. Therefore, in the case of sleep disorders, appropriate therapy should be applied timely, which requires a prompt diagnosis. Traditionally, a sleep diary is a part of diagnosis and therapy monitoring for some sleep disorders, such as cognitive behaviour therapy for insomnia. To automatise sleep monitoring and make it more comfortable for users, substituting a sleep diary with a smartwatch measurement could be considered. With the aim of providing accurate results, a study with a total of 30 night recordings was conducted. Objective sleep measurement with a Samsung Galaxy Watch 4 was compared with a subjective approach (sleep diary), evaluating the four relevant sleep characteristics: time of getting asleep, wake up time, sleep efficiency (SE), and total sleep time (TST). The performed analysis has demonstrated that the median difference between both measurement approaches was equal to 7 and 3 minutes for a time of getting asleep and wake up time correspondingly, which allows substituting a subjective measurement with a smartwatch. The SE was determined with a median difference between the two measurement methods of 5.22%. This result also implicates a possibility of substitution. Some single recordings have indicated a higher variance between the two approaches. Therefore, the conclusion can be made that a substitution provides reliable results primarily in the case of long-term monitoring. The results of the evaluation of the TST measurement do not allow to recommend substitution of the measurement method.
Improving the tribological properties of Stainless Steels by low-temperature surface hardening
(2022)
The detection of anomalous or novel images given a training dataset of only clean reference data (inliers) is an important task in computer vision. We propose a new shallow approach that represents both inlier and outlier images as ensembles of patches, which allows us to effectively detect novelties as mean shifts between reference data and outliers with the Hotelling T2 test. Since mean-shift can only be detected when the outlier ensemble is sufficiently separate from the typical set of the inlier distribution, this typical set acts as a blind spot for novelty detection. We therefore minimize its estimated size as our selection rule for critical hyperparameters, such as, e.g., the size of the patches is crucial. To showcase the capabilities of our approach, we compare results with classical and deep learning methods on the popular datasets MNIST and CIFAR-10, and demonstrate its real-world applicability in a large-scale industrial inspection scenario.
Ignorantia doctorum
(2022)
Since the turn of the millennium, many writing centers have been established at universities in the German-speaking world, in order to support students in academic writing. This essay argues for offering subject-anchored directive guidance and using scientific texts as a basis for model learning. It states that the rhetorical tradition is hardly taken into account in the writing centers. Five arguments for this ignorance are discussed and, if possible, dispelled: the antiquity argument, which considers rhetoric outdated; the orality argument, which understands rhetoric as irrelevant to writing; the moral argument, which condemns rhetoric as a tool for demagogues; the positivist argument, which criticizes rhetoric as unempirical; and the didactic argument, which rejects rhetoric as a rigid doctrine. The discussion shows, however, that the rhetorical tradition, with its normative power and centuries of teaching practice, is a treasure trove of writing didactics that holds many resources, such as well-founded assessment criteria for the quality, appropriateness, and usefulness of texts.
Per-capita greenhouse gas emissions in cities like Bangkok or Shanghai have already reached emission levels of cities like London or Toronto. Large parts of the building stock and service infrastructure in cities in rapidly developing countries will be built in the coming decades—and may lock in high emissions pathways. A survey of projects under the Clean Development Mechanism (CDM) of the Kyoto Protocol shows that only about 1% of projects have been submitted by municipalities, mostly in the waste management and more recently in the transport sector. This is probably due to a lack of technical know-how, legal barriers, methodological challenges, long project cycles and limited “visibility” of projects for the electorate. A case study of city network ICLEI’s experience with the CDM adds practical insights. We conclude that while the new market mechanisms under Article 6 may make it easier for municipalities to engage in international market mechanisms, new forms of cooperation between actors on multiple levels, potentially facilitated by ICLEI, are required to help to realize the urban potential in international market mechanisms.
Sleep is an important part of our life that significantly influences our health and well-being. The monitoring of sleep can provide data based on which sleep quality could be improved. This paper presents a system for heart rate detection during sleep. The data is collected from sensors underneath the test subjects. Though the data contains noise, it needs to be filtered to remove it. Due to the low strength of the signals, they need to be amplified after filtering. At some points of the signal, particular heartbeats may not be tracked by sensors due to the failure of a sensor or other reasons, which should be considered. The heart rate is detected in intervals of 15 s. A tool is implemented that detects the heart rate and visualizes it. The preprocessing of the data is performed with several filters: a highpass filter, a band-reject filter, a lowpass filter, and a motion detector. After the preprocessing of the data, the quality of the signal is significantly increased, and detection is possible.
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.
With the high resolution of modern sensors such as multilayer LiDARs, estimating the 3D shape in an extended object tracking procedure is possible. In recent years, 3D shapes have been estimated in spherical coordinates using Gaussian processes, spherical double Fourier series or spherical harmonics. However, observations have shown that in many scenarios only a few measurements are obtained from top or bottom surfaces, leading to error-prone estimates in spherical coordinates. Therefore, in this paper we propose to estimate the shape in cylindrical coordinates instead, applying harmonic functions. Specifically, we derive an expansion for 3D shapes in cylindrical coordinates by solving a boundary value problem for the Laplace equation. This shape representation is then integrated in a plain greedy association model and compared to shape estimation procedures in spherical coordinates. Since the shape representation is only integrated in a basic estimator, the results are preliminary and a detailed discussion for future work is presented at the end of the paper.
Haarstylingutensil
(2022)
Ziel des Forschungsprojekts "Ekont" ist es, ein handgeführtes Gerät zum Betonabtrag an Innenkanten und Störstellen in Kernkraftwerken (KKW) zu entwickeln. Um die Reaktionskräfte zu reduzieren wird hierbei der neuartige Ansatz eines gegenläufigen Fräsprozesses untersucht. Ergebnis ist eine Getriebelösung, bei der eine mittlere Frässcheibe mit annähernd derselben Umfangsgeschwindigkeit in die entgegengesetzte Richtung von weiteren Frässcheiben rotiert.
Generating synthetic data is a relevant point in the machine learning community. As accessible data is limited, the generation of synthetic data is a significant point in protecting patients' privacy and having more possibilities to train a model for classification or other machine learning tasks. In this work, some generative adversarial networks (GAN) variants are discussed, and an overview is given of how generative adversarial networks can be used for data generation in different fields. In addition, some common problems of the GANs and possibilities to avoid them are shown. Different evaluation methods of the generated data are also described.
In this letter, we present an approach to building a new generalized multistream spatial modulation system (GMSM), where the information is conveyed by the two active antennas with signal indices and using all possible active antenna combinations. The signal constellations associated with these antennas may have different sizes. In addition, four-dimensional hybrid frequency-phase modulated signals are utilized in GMSM. Examples of GMSM systems are given and computer simulation results are presented for transmission over Rayleigh and deep Nakagami- m flat-fading channels when maximum-likelihood detection is used. The presented results indicate a significant improvement of characteristics compared to the best-known similar systems.
Code-based cryptography is a promising candidate for post-quantum public-key encryption. The classic McEliece system uses binary Goppa codes, which are known for their good error correction capability. However, the key generation and decoding procedures of the classic McEliece system have a high computation complexity. Recently, q-ary concatenated codes over Gaussian integers were proposed for the McEliece cryptosystem together with the one-Mannheim error channel, where the error values are limited to Mannheim weight one. For this channel, concatenated codes over Gaussian integers achieve a higher error correction capability than maximum distance separable (MDS) codes with bounded minimum distance decoding. This improves the work factor regarding decoding attacks based on information-set decoding. This work proposes an improved construction for codes over Gaussian integers. These generalized concatenated codes extent the rate region where the work factor is beneficial compared to MDS codes. They allow for shorter public keys for the same level of security as the classic Goppa codes. Such codes are beneficial for lightweight code-based cryptosystems.
Gamification is one of the recognized methods of motivating people in various life processes, and it has spread to many spheres of life, including healthcare. This article proposes a system design for long-term care patients using the method mentioned. The proposed system aims to increase patient engagement in the treatment and rehabilitation process via gamification. Literature research on available and earlier proposed systems was conducted to develop a suited system design. The primary target group includes bedridden patients and a sedentary lifestyle (predominantly lying in bed). One of the main criteria for selecting a suitable option was its contactless realization for the mentioned target groups in long-term care cases. As a result, we developed the system design for hardware and software that could prevent bedsores and other health problems from occurring because of low activity. The proposed design can be tested in hospitals, nursing homes, and rehabilitation centers.
In diesem Beitrag wird der finnische Tangotanztourismus
unter Berücksichtigung des Konzeptes des verkörperten Raumes (Low 2003) und des Raumverständnisses von Lefebvre (1991) auf den vielschichtig miteinander verbundenen Ebenen von Körper, Kultur und Raum analysiert. Die finnische „Kultur der Schweigsamkeit“ wird in diesem Zusammenhang im Besonderen
betrachtet. Methodisch werden hierbei sowohl Interviews mit Expertinnen und Experten, teilnehmende Beobachtung als auch die Auswertung von Filmmaterial herangezogen. Im Ergebnis zeigen sich vielfältige Wechselwirkungen von Körper, Kultur und Raum, die zusätzlich Potenziale für den finnischen Tangotanztourismus
aufzeigen.
Feature-Based Proposal Density Optimization for Nonlinear Model Predictive Path Integral Control
(2022)
This paper presents a novel feature-based sampling strategy for nonlinear Model Predictive Path Integral (MPPI) control. In MPPI control, the optimal control is calculated by solving a stochastic optimal control problem online using the weighted inference of stochastic trajectories. While the algorithm can be excellently parallelized the closed- loop performance is dependent on the information quality of the drawn samples. Because these samples are drawn using a proposal density, its quality is crucial for the solver and thus the controller performance. In classical MPPI control, the explored state-space is strongly constrained by assumptions that refer to the control value variance, which are necessary for transforming the 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 used to determine the proposal density and thus, the 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. Further, the developed algorithm is applied on an autonomous vessel that follows a track and concurrently avoids collisions using an emergency braking feature.
In this paper, approximating the shape of a sailing boat using elliptic cones is investigated. Measurements are assumed to be gathered from the target's surface recorded by 3D scanning devices such as multilayer LiDAR sensors. Therefore, different models for estimating the sailing boat's extent are presented and evaluated in simulated and real-world scenarios. In particular, the measurement source association problem is addressed in the models. Simulated investigations are conducted with a static and a moving elliptic cone. The real-world scenario was recorded with a Velodyne Alpha Prime (VLP-128) mounted on a ferry of Lake Constance. Final results of this paper constitute the extent estimation of a single sailing boat using LiDAR data applying various measurement models.
Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Virtual Measurement Model
(2022)
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.
Experimental Validation of Ellipsoidal Techniques for State Estimation in Marine Applications
(2022)
A reliable quantification of the worst-case influence of model uncertainty and external disturbances is crucial for the localization of vessels in marine applications. This is especially true if uncertain GPS-based position measurements are used to update predicted vessel locations that are obtained from the evaluation of a ship’s state equation. To reflect real-life working conditions, these state equations need to account for uncertainty in the system model, such as imperfect actuation and external disturbances due to effects such as wind and currents. As an application scenario, the GPS-based localization of autonomous DDboat robots is considered in this paper. Using experimental data, the efficiency of an ellipsoidal approach, which exploits a bounded-error representation of disturbances and uncertainties, is demonstrated.
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.
Technologiebasierte Startups leisten einen wesentlichen Beitrag zur wirtschaftlichen sowie gesellschaftlichen Entwicklung. Im Zuge ihrer Gründung benötigen sie Unterstützung in Form von Risikokapital, das in der Seed- und Early-Stage primär durch Business Angels (BAs) bereitgestellt wird. Die Abläufe und Bewertungskriterien des BA Investmentprozesses sind bisher jedoch unzureichend erforscht. Der vorliegende Beitrag nutzt Experteninterviews im Rahmen einer Fallstudie des baden-württembergischen entrepreneurialen Ökosystems zur Identifikation des Vorgehens von BAs bei der Bewertung und Auswahl technologiebasierter Startups. Zudem werden die Kriterien, nach denen BAs vielversprechende von scheiternden Startups unterscheiden abgeleitet. Somit trägt der Beitrag zur Öffnung der „Black Box” von Investmentaktivitäten in den frühsten Gründungsphasen bei.
Evaluation of tech ventures’ evolving business models: rules for performance-related classification
(2022)
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.
The importance of sleep for human life is enormous. It affects physical, mental, and psychological health. Therefore, it is vital to recognise sleep disorders in a timely manner in order to be able to initiate therapy. There are two methods for measuring sleep-related parameters - objective and subjective. Whether the substitution of a subjective method for an objective one is possible is investigated in this paper. Such replacement may bring several advantages, including increased comfort for the user. To answer this research question, a study was conducted in which 75 overnight recordings were evaluated. The primary purpose of this study was to compare both ways of measurement for total sleep time and sleep efficiency, which are essential parameters for, e.g., insomnia diagnosis and treatment. The evaluation results demonstrated that, on average, there are 32 minutes of difference between the two measurement methods when total sleep time is analysed. In contrast, on average, both measurement methods differ by 7.5% for sleep efficiency measurement. It should also be noted that people typically overestimate total sleep time and efficiency with the subjective method, where the perceived values are measured.
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.
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.
The purpose of this paper is to examine the effects of perceived stress on traffic and road safety. One of the leading causes of stress among drivers is the feeling of having a lack of control during the driving process. Stress can result in more traffic accidents, an increase in driver errors, and an increase in traffic violations. To study this phenomenon, the Stress Perceived Questionnaire (PSQ) was used to evaluate the perceived stress while driving in a simulation. The study was conducted with participants from Germany, and they were grouped into different categories based on their emotional stability. Each participant was monitored using wearable devices that measured their instantaneous heart rate (HR). The preference for wearable devices was due to their non-intrusive and portable nature. The results of this study provide an overview of how stress can affect traffic and road safety, which can be used for future research or to implement strategies to reduce road accidents and promote traffic safety.
The scoring of sleep stages is an essential part of sleep studies. The main objective of this research is to provide an algorithm for the automatic classification of sleep stages using signals that may be obtained in a non-obtrusive way. After reviewing the relevant research, the authors selected a multinomial logistic regression as the basis for their approach. Several parameters were derived from movement and breathing signals, and their combinations were investigated to develop an accurate and stable algorithm. The algorithm was implemented to produce successful results: the accuracy of the recognition of Wake/NREM/REM stages is equal to 73%, with Cohen's kappa of 0.44 for the analyzed 19324 sleep epochs of 30 seconds each. This approach has the advantage of using the only movement and breathing signals, which can be recorded with less effort than heart or brainwave signals, and requiring only four derived parameters for the calculations. Therefore, the new system is a significant improvement for non-obtrusive sleep stage identification compared to existing approaches.
For some years, universities in countries where the first language is not English choose English as the medium of instruction. In German universities, instruction in German is still the dominant form, which makes university study in Germany less accessible to international students. To attract international students and to improve career prospects for home students, many German universities offer programmes taught in English or in a combination of German and English. It is widely expected that the implementation of EMI-programmes leads to improvements in English language proficiency (ELP). However, it has emerged that substantial gains in ELP in EMI programmes will only occur as the result of content and language integrated learning.
In tomato drying, degradation in final quality may occur based on the drying method used and predrying preparation. Hence, this research was conducted to evaluate the effect of different predrying treatments on physicochemical quality and drying kinetics of twin-layer-solar-tunnel-dried tomato slices. During the experimental work, tomato slices of var. Galilea were used. As predrying treatments, 0.5% calcium chloride (CaCl2), 0.5% ascorbic acid (C6H8O6), 0.5% citric acid (C6H8O7), and 0.5% sodium chloride (NaCl) were used. The tomato samples were sliced to 5 mm thickness, socked in the pretreatments for ten minutes, and dried in a twin layer solar tunnel dryer under the weather conditions of Jimma, Ethiopia. Untreated samples were used as control. The moisture losses from the samples were monitored by weighing samples at 2 h interval from each treatment. SAS statistical software version 9.2 was used for analyzing data on the physicochemical quality of tomato slices in CRD with three replications. From the experimental result, it was observed that dried tomato slices pretreated with 0.5% ascorbic acid gave the best retention of vitamin C and total phenolic content with a high sugar/acid ratio. Better retention of lycopene and fast drying were observed in dried tomato slices pretreated with 0.5% sodium chloride, and pretreating tomatoes with 0.5% citric acid resulted in better color values than the other treatments. Compared to the control, pretreating significantly preserved the overall quality of dried tomato slices and increased the moisture removal rate in the twin layer solar tunnel dryer.
In the last decade, both sustainability (Green &
Blue Economies) and business models for sustainability
(BMfS) have increased in importance. Social life cycle
sustainability assessment has not fully achieved goal,
mainly because sustainability‐oriented business is very
complex and dynamic. System Dynamics (SD) is a powerful
methodology and computer simulation modeling technique
for framing, understanding and discussing complex issues
and problems. This paper responds to the urgent need for
a new business model by presenting a concept for dynamic
business modeling for sustainability using system dynamics.
The paper illustrates the key operating principles through
an application from the smartphone industry with help
from STELLA® software for simulation. Simulations
suggest that dynamic business modeling for sustainability
may contribute to sustainable business model research and
practice by introducing a systemic design tool that frames
environmental, social, and economic drivers of value
generation into a dynamic business model causal feedback
structure, therefore overcoming shortcomings of current
business models when applied to complex systems.
Docking Control of a Fully-Actuated Autonomous Vessel using Model Predictive Path Integral Control
(2022)
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.