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Because process and product innovations are usually no longer sufficient to establish a company in the market or to generate a competitive advantage, Business Model Innovation is considered a powerful tool, especially for start-ups for which innovation is at the core of their business. Due to the complexity of this process, frameworks should help entrepreneurs with executing Business Model Innovation. However, theory and practice diverge. The aim of this paper is to identify the needs of a start-up regarding Business Model Innovation frameworks, underlining the importance of Business Model Innovation for start-ups as well as the relevance of a supporting framework. The research results aim to contribute to an ideal process for Business Model Innovation when applied to start-ups.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
Das erfolgreiche Gestalten von Organisationen setzt die systematische Analyse ihrer Prozesse voraus. Das gilt auch und insbesondere für kleine und mittelgroße Unternehmen (KMU). Die praktische Durchführung solcher in KMU ist jedoch mit besonderen Herausforderungen verbunden, die in der vorhandenen Literatur bislang kaum reflektiert werden. In diesem Beitrag werden Erfahrungen aus 20 in KMU durchgeführten Prozessanalysen geteilt. Entlang der Prozessphasen werden unterschiedliche Gestaltungsmöglichkeiten vorgestellt und ihre spezifischen Vor- und Nachteile bei der praktischen Anwendung in KMU identifiziert. Der Beitrag unterstreicht die Relevanz von Prozessanalysen in KMU und befähigt zugleich zu ihrer Durchführung.
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.