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- tensile membrane structure, lightweight structure, parametric design, visual programming, interoperability, BIM, IFC, RF-COM, Grasshopper3D, Rhinoceros, Revit, Allplan (1)
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Institute
- Fakultät Architektur und Gestaltung (41)
- Fakultät Bauingenieurwesen (105)
- Fakultät Elektrotechnik und Informationstechnik (34)
- Fakultät Informatik (121)
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- Fakultät Wirtschafts-, Kultur- und Rechtswissenschaften (106)
- Institut für Angewandte Forschung - IAF (115)
- Institut für Naturwissenschaften und Mathematik - INM (3)
- Institut für Optische Systeme - IOS (40)
- Institut für Strategische Innovation und Technologiemanagement - IST (60)
Die energetische Sanierung von Gebäuden ist von großer Relevanz, um die gesetzlichen Klimaziele zu erreichen. Die Methode des seriellen Sanierens spielt hierbei eine wichtige Rolle. Sie gilt als ganzheitliche Maßnahme zur energetischen Aufwertung von Bestandsgebäuden, durch die nicht nur die Gebäudehülle und die Anlagentechnik, wie etwa das Heizungssystem, effektiv verbessert werden, sondern auch eine Integration von Anlagen zur Strom- und Warmwasseraufbereitung erfolgt. Bei der seriellen Sanierung wird, in Anlehnung an die Industrie und an die modulare Bauweise, eine Vorfertigung der Fassaden-
und Dachelemente durchgeführt. Im Nachgang werden die einzelnen Bauelemente und Anlagen montiert bzw. installiert. Durch die Auslagerung der Produktion und durch die Vorfertigung der Elemente besteht das Potenzial, die Montagezeit und die damit verbundenen Einschränkungen vor Ort für die Bewohner deutlich zu reduzieren.
Black-box variational inference (BBVI) is a technique to approximate the posterior of Bayesian models by optimization. Similar to MCMC, the user only needs to specify the model; then, the inference procedure is done automatically. In contrast to MCMC, BBVI scales to many observations, is faster for some applications, and can take advantage of highly optimized deep learning frameworks since it can be formulated as a minimization task. In the case of complex posteriors, however, other state-of-the-art BBVI approaches often yield unsatisfactory posterior approximations. This paper presents Bernstein flow variational inference (BF-VI), a robust and easy-to-use method flexible enough to approximate complex multivariate posteriors. BF-VI combines ideas from normalizing flows and Bernstein polynomial-based transformation models. In benchmark experiments, we compare BF-VI solutions with exact posteriors, MCMC solutions, and state-of-the-art BBVI methods, including normalizing flow-based BBVI. We show for low-dimensional models that BF-VI accurately approximates the true posterior; in higher-dimensional models, BF-VI compares favorably against other BBVI methods. Further, using BF-VI, we develop a Bayesian model for the semi-structured melanoma challenge data, combining a CNN model part for image data with an interpretable model part for tabular data, and demonstrate, for the first time, the use of BBVI in semi-structured models.
IT-Kosten machen heute einen immer größeren Anteil an den Gesamtkosten von Unternehmen aus. Die Verantwortlichen sind aufgefordert die IT-Kosten zu senken oder zumindest ein effizientes Management sicherzustellen. Oftmals fehlt es dafür an Transparenz und Verständnis für diese Ausgaben. Die Analyse der IT-Kostentreiber ermöglicht ein tieferes Verständnis der Ursachen und Auswirkungen strategischer Entscheidungen. Dieser Beitrag zielt darauf ab, die strategischen IT-Kostentreiber bezüglich des Wirkungshorizonts und des Entscheidungsortes zu analysieren. Die durchgeführte Delphi-Studie zeigt, dass Entscheidungen über diese Kostentreiber größtenteils mittel- bis langfristige Auswirkungen haben. Zudem wird deutlich, dass die IT-Abteilung zwar in den Entscheidungsprozess eingebunden ist, während die finalen Entscheidungen häufig stärker im Fachbereich liegen. Zusammenarbeit und effektive Kommunikation sind deshalb entscheidend und die Verantwortung für IT-Kosten sollte von allen EntscheidungsträgerInnen getragen werden. Dieser Beitrag erweitert die Forschung im IT-Kostenmanagement und sensibilisiert PraktikerInnen für Kostenbeeinflussungshebel und die strategische Diskussion über IT-Kosten und das Wertversprechen der IT.
Apnea is a sleep disorder characterized by breathing interruptions during sleep, impacting cardiorespiratory function and overall health. Traditional diagnostic methods, like polysomnography (PSG), are unobtrusive, leading to noninvasive monitoring. This study aims to develop and validate a novel sleep monitoring system using noninvasive sensor technology to estimate cardiorespiratory parameters and detect sleep apnea. We designed a seamless monitoring system integrating noncontact force-sensitive resistor sensors to collect ballistocardiogram signals associated with cardiorespiratory activity. We enhanced the sensor’s sensitivity and reduced the noise by designing a new concept of edge-measuring sensor using a hemisphere dome and mechanical hanger to distribute the force and mechanically amplify the micromovement caused by cardiac and respiration activities. In total, we deployed three edge-measuring sensors, two deployed under the thoracic and one under the abdominal regions. The system is supported with onboard signal preprocessing in multiple physical layers deployed under the mattress. We collected the data in four sleeping positions from 16 subjects and analyzed them using ensemble empirical mode decomposition (EMD) to avoid frequency mixing. We also developed an adaptive thresholding method to identify sleep apnea. The error was reduced to 3.98 and 1.43 beats/min (BPM) in heart rate (HR) and respiration estimation, respectively. The apnea was detected with an accuracy of 87%. We optimized the system such that only one edge-measuring sensor can measure the cardiorespiratory parameters. Such a reduction in the complexity and simplification of the instruction of use shows excellent potential for in-home and continuous monitoring.
Die folgende Masterarbeit gibt eine Übersicht zu modernen AR-Technologien für den Einsatz in der Lehre mit dem Ziel eine geeignete Software zu identifizieren, die eine AR-Anwendungserstellung sowie die Integration dieser in das Vorlesungsgeschehen der HTWG ermöglicht. Diese Arbeit baut auf einer Literaturrecherche auf, welche den gegenwärtigen Einsatz von AR in der Lehrpraxis analysiert. Es wird der aktuelle Stand der Entwicklung in Bezug auf verschiedenste Hard- und Softwarelösungen dargestellt, einschließlich der Funktionsweise von AR-Anwendungen sowie relevanter Systemkomponenten. Anschließend werden sowohl der Einsatz von Augmented Reality im Bildungsbereich betrachtet als auch andere Sektoren wie Medizin und Industrie einbezogen, um eine umfassende Übersicht zu Fallstudien sowie Praxisbeispielen zu gewährleisten. Der Auswahlprozess der Software wird ebenfalls thematisiert und eine Anleitung zur Benutzung des gewählten Tools, Vuforia Studio, wird dargeboten.
Die Analyse ergab, dass AR-Anwendungen es den Schülern und Studierenden ermöglichen, aktiv am Unterricht bzw. den Vorlesungen teilzunehmen und Inhalte interaktiv zu erkunden, was das Interesse am Lehrinhalt steigert sowie eigenständiges Lernen fördert. Dem Einsatz von AR in der Lehre stehen jedoch Herausforderungen gegenüber. Insbesondere eine pädagogisch angemessene AR-Inhaltserstellung erweist sich als schwierig. Sowohl die Anfertigung
eines 3D-Modells als auch das Arbeiten mit Programmen wie Vuforia Studio selbst stellen sich als zeitintensiv und technologisch anspruchsvoll heraus. Von Seiten der Bildungseinrichtung müssen finanzielle Mittel bereitgestellt werden, denn ohne entsprechende Schulungen und Ressourcen wird auch die Bereitschaft der Lehrenden, sich mit neuen Technologien auseinanderzusetzen, nicht ausreichend sein, um hochwertige AR-Inhalte zu konzipieren. Obwohl die
technologische Infrastruktur zwar deutlich besser ausgebaut ist als noch vor einigen Jahren, vor allem, weil flächendeckendes Internet zur Verfügung steht und die Lernenden zum Großteil eigene Smartgeräte besitzen, ist eine kontinuierliche Investition in Hard- und Software sowie das Pflegen der gesammelten Daten und genutzten Server unerlässlich.
Insgesamt bietet der Einsatz von Augmented Reality in der Lehre vielversprechende Möglichkeiten, um das Lernerlebnis zu verbessern und die Bildungsergebnisse zu optimieren, jedoch müssen die genannten Herausforderungen überwunden werden, um das gesamte Potenzial von Augmented Reality Technologien in der Lehre auszuschöpfen.
Incremental one-class learning using regularized null-space training for industrial defect detection
(2024)
One-class incremental learning is a special case of class-incremental learning, where only a single novel class is incrementally added to an existing classifier instead of multiple classes. This case is relevant in industrial defect detection scenarios, where novel defects usually appear during operation. Existing rolled-out classifiers must be updated incrementally in this scenario with only a few novel examples. In addition, it is often required that the base classifier must not be altered due to approval and warranty restrictions. While simple finetuning often gives the best performance across old and new classes, it comes with the drawback of potentially losing performance on the base classes (catastrophic forgetting [1]). Simple prototype approaches [2] work without changing existing weights and perform very well when the classes are well separated but fail dramatically when not. In theory, null-space training (NSCL) [3] should retain the basis classifier entirely, as parameter updates are restricted to the null space of the network with respect to existing classes. However, as we show, this technique promotes overfitting in the case of one-class incremental learning. In our experiments, we found that unconstrained weight growth in null space is the underlying issue, leading us to propose a regularization term (R-NSCL) that penalizes the magnitude of amplification. The regularization term is added to the standard classification loss and stabilizes null-space training in the one-class scenario by counteracting overfitting. We test the method’s capabilities on two industrial datasets, namely AITEX and MVTec, and compare the performance to state-of-the-art algorithms for class-incremental learning.
Particularly for manufactured products subject to aesthetic evaluation, the industrial manufacturing process must be monitored, and visual defects detected. For this purpose, more and more computer vision-integrated inspection systems are being used. In optical inspection based on cameras or range scanners, only a few examples are typically known before novel examples are inspected. Consequently, no large data set of non-defective and defective examples could be used to train a classifier, and methods that work with limited or weak supervision must be applied. For such scenarios, I propose new data-efficient machine learning approaches based on one-class learning that reduce the need for supervision in industrial computer vision tasks. The developed novelty detection model automatically extracts features from the input images and is trained only on available non-defective reference data. On top of the feature extractor, a one-class classifier based on recent developments in deep learning is placed. I evaluate the novelty detector in an industrial inspection scenario and state-of-the-art benchmarks from the machine learning community. In the second part of this work, the model gets improved by using a small number of novel defective examples, and hence, another source of supervision gets incorporated. The targeted real-world inspection unit is based on a camera array and a flashing light illumination, allowing inline capturing of multichannel images at a high rate. Optionally, the integration of range data, such as laser or Lidar signals, is possible by using the developed targetless data fusion method.
Das Freistellungssemester 2020 wurde für Recherchen zu unterschiedlichen Aufmaßsystemen in der historischen Bauforschung genutzt. Durch die Covid-19-Pandemie entwickelte sich das Arbeitsprogramm jedoch anders als geplant und verlagerte sich weitgehend in den virtuellen Raum. In der Disziplin der historischen Bauforschung entstand gerade durch die zeitweise Unmöglichkeit des Reisens und der Präsenzlehre ein intensiver Austausch zur Methodik in zahlreichen Onlinekonferenzen.
Using multi-camera matching techniques for 3d reconstruction there is usually the trade-off between the quality of the computed depth map and the speed of the computations. Whereas high quality matching methods take several seconds to several minutes to compute a depth map for one set of images, real-time methods achieve only low quality results. In this paper we present a multi-camera matching method that runs in real-time and yields high resolution depth maps. Our method is based on a novel multi-level combination of normalized cross correlation, deformed matching windows based on the multi-level depth map information, and sub-pixel precise disparity maps. The whole process is implemented completely on the GPU. With this approach we can process four 0.7 megapixel images in 129 milliseconds to a full resolution 3d depth map. Our technique is tailored for the recognition of non-technical shapes, because our target application is face recognition.
Diese Masterarbeit erforscht das Potenzial großer Sprachmodelle in der Bauindustrie mit einem Fokus auf digitale Transformation, Effizienzsteigerung und Nachhaltigkeit. Durch eine umfassende Literaturanalyse und qualitative Experteninterviews werden spezifische Anwendungsfälle, Herausforderungen bei der Implementierung und ethische sowie datenschutzrechtliche Überlegungen untersucht.
Die Arbeit hebt hervor, wie große Sprachmodelle die Planungsprozesse optimieren, das Risikomanagement verbessern und maßgeschneiderte Lösungen entwickeln können, um ökonomische und ökologische Vorteile zu erzielen. Zudem werden praxisorientierte Empfehlungen für eine erfolgreiche Integration dieser Technik in das Bauwesen präsentiert, die sowohl die technologische Machbarkeit als auch soziale Akzeptanz berücksichtigen.
Abschließend werden zukünftige Forschungsrichtungen aufgezeigt, die darauf abzielen, die digitale Transformation im Bauwesen unter Einbeziehung ethischer Standards und Datenschutz zu beschleunigen.
Die Ergebnisse dieser Arbeit demonstrieren das Potenzial von großen Sprachmodellen, traditionelle Bauprozesse zu revolutionieren, und betonen die Notwendigkeit einer sorgfältigen Implementierung, um die Vorteile dieser Technologie vollständig auszuschöpfen.
This paper broadens the resource-based approach to explaining survival of new technology-based firms (NTBFs) by focusing on the entrepreneur's ability to transform resources in response to triggers resulting from market interactions. Network theory is used to define a construct that allows determining the status of venture emergence (VE).The operationalization of the VE construct is built on the firm's value network maturity in the four market dimensions customer, investor, partner, and human resource. Business plans of NTBFs represent the artifact that contains this data in the form of transaction relation descriptions. Using content analysis, a multi-step combined human and computer coding process has been developed to empirically determine NTBFs' status of VE.Results of the business plan analysis suggests that the level of transaction relations allows to draw conclusions on the status of VE. Moreover, applying the developed process, a business plan coding test shows that the transaction relation based VE status significantly relates to NTBFs' survival capabilities.
Research Report
(2024)
We quantify the effects of GATT/WTO membership on trade and welfare. Using an extensive database covering manufacturing trade for 186 countries over the period 1980–2016, we find that the average partial equilibrium impact of GATT/WTO membership on trade among member countries is large, positive, and significant. We contribute to the literature by estimating country-specific estimates and find them to vary widely across the countries in our sample with poorer members benefitting more. Using these estimates, we simulate the general equilibrium effects of GATT/WTO on welfare, which are sizable and heterogeneous across members. We show that countries not experiencing positive trade effects from joining GATT/WTO can still gain in terms of welfare, due to lower import prices and higher export demand.
Misbehave like Nobody’s Watching? Investor Attention to Corporate Misconduct and its Implications
(2023)
Der Bericht dokumentiert die Aktivitäten, die ich während des Wintersemesters 2023/24 im Rahmen meines Fortbildungssemesters durchgeführt habe. Der Forschungsschwerpunkt lag dabei auf der Umsetzung eines gemeinschaftlichen Projekts zur Bewertung mündlicher Prüfungen. Zusätzlich erfolgten Aufenthalte zur Förderung der internationalen Kooperationen an Partnerhochschulen.
IT-Compliance in KMU
(2023)
Healthy and good sleep is a prerequisite for a rested mind and body. Both form the basis for physical and mental health. Healthy sleep is hindered by sleep disorders, the medically diagnosed frequency of which increases sharply from the age of 40. This chapter describes the formal specification of an on-course practical implementation for a non-invasive system based on biomedical signal processing to support the diagnosis and treatment of sleep-related diseases. The system aims to continuously monitor vital data during sleep in a patient’s home environment over long periods by using non-invasive technologies. At the center of the development is the MORPHEUS Box (MoBo), which consists of five main conceptualizations: the MoBo core, the MoBo-HW, the MoBo algorithm, the MoBo API, and the MoBo app. These synergistic elements aim to support the diagnosis and treatment of sleep-related diseases. Although there are related developments in individual aspects concerning the system, no comparative approach is known that gives a similar scope of functionality, deployment flexibility, extensibility, or the possibility to use multiple user groups. With the specification provided in this chapter, the MORPHEUS project sets a good platform, data model, and transmission strategies to bring an innovative proposal to measure sleep quality and detect sleep diseases from non-invasive sensors.
With the advancement in sensor technology and the trend shift of health measurement from treatment after diagnosis to abnormalities detection long before the occurrence, the approach of turning private spaces into diagnostic spaces has gained much attention. In this work, we designed and implemented a low-cost and compact form factor module that can be deployed on the steering wheel of cars as well as most frequently touch objects at home in order to measure physiological signals from the fingertip of the subject as well as environmental parameters. We estimated the heart rate and SpO2 with the error of 2.83 bpm and 3.52%, respectively. The signal evaluation of skin temperature shows a promising output with respect to environmental recalibration. In addition, the electrodermal activity sensor followed the reference signal, appropriately which indicates the potential for further development and application in stress measurement.
The perception of the amount of stress is subjective to every person, and the perception of it changes depending on many factors. One of the factors that has an impact on perceived stress is the emotional state. In this work, we compare the emotional state of 40 German driving students and present different partitions that can be advantageous for using artificial intelligence and classification. Like this, we evaluate the data quality and prepare for the specific use. The Stress Perceived Questionnaire (PSQ20) was employed to assess the level of stress experienced by individuals while participating in a driving simulation for 5 and 25 min. As a result of our analysis, we present a categorisation of various emotional states into intervals, comparing different classifications and facilitating a more straightforward implementation of artificial intelligence for classification purposes.
Evaluation of a Contactless Accelerometer Sensor System for Heart Rate Monitoring During Sleep
(2024)
The monitoring of a patient's heart rate (HR) is critical in the diagnosis of diseases. In the detection of sleep disorders, it also plays an important role. Several techniques have been proposed, including using sensors to record physiological signals that are automatically examined and analysed. This work aims to evaluate using a contactless HR monitoring system based on an accelerometer sensor during sleep. For this purpose, the oscillations caused by chest movements during heart contractions are recorded by an installation mounted under the bed mattress. The processing algorithm presented in this paper filters the signals and determines the HR. As a result, an average error of about 5 bpm has been documented, i.e., the system can be considered to be used for the forecasted domain.
Infrastructure-making in interwar India was a dynamic, multilayered process involving roads and vehicles in urban and rural sites. One of their strongest playgrounds was Bombay Presidency and the Central Provinces in central and western India. Focusing on this region in the interwar period, this paper analyzes the varied relationship between peasant households and town-centred modernizing agents in the making of road transport infrastructures. The central argument of this paper is about the persistence of bullock carts over motor cars in the region. This persistence was grounded in the specific regional environment, the effects of the 1930s economic depression, and the priorities of social classes. Pinpointing these connections, the paper highlights that “modernization” of infrastructure was not a simple, linear process of progressivist change, nor did it mean the survival of apparently “old” technologies in the modern era. Instead, the paper pays attention to conflicting social complexities, implications, and meanings of the connection between infrastructure and modernity that modernization assumptions often overlook. Here, the paper shows how technological change occurred as a result of real, material class interests pulling infrastructural technology in different directions. This was where and why arguments of road-motor lobbyists and cart advocates eventually clashed, and Gandhian social workers resisted motor transport in defense of peasant interests.
Trotz des dringenden Erfordernisses einer nachhaltigen und unabhängigen Energieerzeugung und bereits steigender Anteile photovoltaisch erzeugten Stroms stockt die Verbreitung der bauwerkintegrierten Photovoltaik (BIPV). Zahlreiche „Leuchtturm“-Projekte zeigen das große ästhetische Potential solaraktiver Bauteile und dennoch werden insbesondere von Architekt/innen-Seite neben vermeintlichen Einschränkungen in der planerischen Freiheit immer wieder auch gestalterische Vorbehalte angeführt.
Bisher wurde im Zusammenhang mit PV-Bauteilen schwerpunktmäßig die technische und konstruktive Einfügung thematisiert. Um einen Beitrag zur Diskussion um die Entwicklung visuell überzeugender Ergebnisse zu leisten, die verhindern, dass photovoltaische Bauteile am Gebäude als Fremdkörper wahrgenommen werden, ermittelt die vorliegende Arbeit auf der Grundlage ästhetischer Architekturtheorien allgemeingültige Kriterien für architektonische Wirkungsqualität und transferiert diese auf den Bereich der BIPV-Gestaltung.
Dabei werden zum Verständnis erforderliche Grundlagen der BIPV-Systemtechnik vermittelt sowie verfügbare Bauteile und die unterschiedlichen Akteure und Ziele bei der Gestaltung von BIPV aufzeigt. Auch die speziellen funktionalen und technischen Anforderungen, die PV-Bauteile als „aktive“ Bauteile stellen, werden berücksichtigt und hinsichtlich ihrer hemmenden oder synergetischen Wechselwirkungen differenziert.
Im Rahmen einer Projektstudie finden die oben genannten Kriterien Anwendung auf 13 „best practice“-Beispiele aktueller Wettbewerbsgewinner des vom Solarenergieförderverein Bayern e. V. (SeV) ausgelobten „Architekturpreis Gebäudeintegrierte Solartechnik“, die in Form von Steckbriefen vergleichend dargestellt werden.
Das Ergebnis ist die Synthese eines Kriterienkatalogs als Orientierungs-, Planungs- und Kommunikationswerkzeug, in dem alle Ergebnisse systematisiert zusammengestellt werden.
Ergänzend wird in einem kurzen Exkurs auf von der Hauptuntersuchung ausgenommene, für die Praxis aber relevante Schnittstellen zu wirtschaftlichen Aspekten eingegangen.
In the digital age, information technology (IT) is a strategic asset for organizations. As a result, the IT costs are rising, and the cost-effective management of IT is crucial. Nevertheless, organizations still face major challenges and former studies lack comprehensiveness and depth. The goal of this paper is to generate a deep and holistic view on current management challenges of IT costs. In 15 expert interviews, we identify 23 challenges divided into 7 categories. The main challenges are to ensure transparency on IT cost information, to demonstrate the business impact of IT as well as to change the mindset for the value of IT and overcoming them requires attention to their interactions. Hence, this paper leads to a better understanding of the issues that IT cost management (ITCM) faces in the digital age and builds a base for future research.
Nowadays, organizations must invest strategically in information technology (IT) and choose the right digital initiatives to maximize their benefit. Nevertheless, Chief Information Officers still struggle to communicate IT costs and demonstrate the business value of IT. The goal of this paper is to support their effective communication. In focus groups, we analyzed how different stakeholders perceive IT costs and the business value of IT as the basis of communication. We identified 16 success factors to establish effective communication. Hence, this paper enables a better understanding of the perception and the operationalization of effective communication.
Prior quantitative research identified in the text of technology-based ventures' business plans distinctive performance patterns of evolving business models. Accordingly, interactions with customers, financiers, and people and the patenting strategy's status evolved and served as indicators of early-stage tech ventures' performance. With longitudinal data from five venture cases, this research sheds light on the evolving business model by validating the performance patterns, and elucidating how and why the ventures' business models evolved. Based on a generic systems theory framework for the indicators, the explanatory case studies re-contextualize the performance patterns taken from the snapshot perspective of business plans to the longitudinal perspective of technology-based ventures' life-cycle. This research confirms the relation of business model patterns of digital and non-digital ventures to the performance groups of failure, survival, or success and suggests a broader systems perspective for further research.
The digital transformation of business processes and the integration of IT systems leads to opportunities and risks for small and medium-sized enterprises (SMEs). Risks that can result in a lack of IT Governance, Risk and Compliance (GRC). The purpose of this paper is to present the Design and Evaluation phase of creating an artefact, to reduce these risks. With this, the Design Science Research approach based on Hevner is using. The artefact will be developed by selecting relevant existing frameworks and the identification of SME-specific competencies. The method enables IT-GRC managers to transfer or adapt the frameworks to an SME organizational structure. The results from ten interviews and further three feedback loops showed that the method can be applied in practice and that a tailoring of established frameworks can take place. Contrary to the previous basic orientation of the research, this paper focuses on the concretization of approaches.
This study aims to adapt CEFR in developing an integrative approach-based teaching material model for a pre-basic BISOL class. The method used in this research is the development research design by Borg and Gall. This study was development research. The stages are identification of the problem, formulation of a hypothetical draft model; feasibility testing by experts; product revision; and test product effectiveness. The data were collected through survey techniques, interviews, and documentation. The needs identification results revealed data encompassing 10 themes, 5 tasks per theme, and diverse evaluations comprising theory, in-class practice, and real-world field assignments, both on an individual and group basis. These identified needs require alignment with CEFR A1 for the development of BISOL learning. These findings were subsequently incorporated into the design of the teaching material model, and the results indicated that tailoring CEFR to BISOL as an integrative language teaching material model was feasible for application in the classroom, as assessed by experts. The implications suggest that integrating CEFR into BISOL is highly feasible for the development of teaching materials, and teachers can leverage this instructional model to enhance students' proficiency in the Indonesian language.
The random matrix approach is a robust algorithm to filter the mean and covariance matrix of noisy observations of a dynamic object. Afterward, virtual measurement models can be used to find iteratively the extent parameters of an object that would cause the same statistical moments within their measurements. In previous work, this was limited to elliptical targets and only contour measurements.In this paper, we introduce the parallel use of an elliptical, triangular and rectangular-shaped virtual measurement model and a shape classification that selects the model that fits best to the measurements. The measurement likelihood is modeled either via ray tracing, a uniformly or normally spatial distribution over the object’s extent or as a combination of those.The results show that the extent estimation works precisely and that the classification accuracy highly depends on the measurement noise.
In this work, a storage study was conducted to find suitable packaging material for tomato powder storage. Experiments were laid out in a single factor completely randomized design (CRD) to study the effect of packaging materials on lycopene, vitamin C moisture content, and water activity of tomato powder; The factor (packaging materials) has three levels (low‐density polyethylene bag, polypropylene bottle, wrapped with aluminum foils, and packed in low‐density polyethylene bag) and is replicated three times. During the study, a twin layer solar tunnel dried tomato slices of var. Galilea was used. The dried tomato slices were then ground and packed (40 g each) in the packaging materials and stored at room temperature. Samples were drawn from the packages at 2‐month interval for quality analysis and SAS (version 9.2) software was used for statistical analysis. From the result, higher retention of lycopene (80.13%) and vitamin C (49.32%) and a nonsignificant increase in moisture content and water activity were observed for tomato powder packed in polypropylene bottles after 6 months of storage. For low‐density polyethylene packed samples and samples wrapped with aluminum foil and packed in a low‐density polyethylene bag, 57.06% and 60.45% lycopene retention and 42.9% and 49.23% Vitamin C retention were observed, respectively, after 6 months of storage. Considering the results found, it can be concluded that lycopene and vitamin C content of twin layer solar tunnel dried tomato powder can be preserved at ambient temperature storage by packing in a polypropylene bottle with a safe range of moisture content and water activity levels for 6 months.
Southeast Asia
(2023)
Southeast Asia continues to inspire and intrigue observers from all walks
of life due to its diverse cultural traditions and its interwoven threads of
geographical, historical, and social transformation. This essay will explore some of these threads by highlighting Southeast Asia’s (1) deep-rooted diversity, (2) decolonial nation-building, (3) digital leapfrogging, and (4) under-rated prospects
Dieses Buch bietet eine kompakte Einführung in die systemische Denkweise und die Methodik des Vernetzten Denkens. Tragfähige Entscheidungen und Handlungen in unserer vernetzten und komplexen Welt erfordern, sich mit anderen Denk- und Sichtweisen vertraut zu machen und in systemisch-vernetzten Zusammenhängen zu denken. Dazu benötigen die Entscheider ein tiefergehendes Verständnis über das Denken in Wirkungszusammenhängen und wie sich diese bildhaft darstellen lassen. Mittels vieler motivierender Beispiele zeigt dieses essential, was Systemdenken ausmacht und wie sich diese Denkweise in die eigene Entscheidungspraxis umsetzen lässt.
Praktische Rhetorik
(2023)
Times of high dynamic and growing new knowledge demand for entrepreneurial education and university engagement. Higher education institutions (HEIs) have established intensive knowledge and resources about entrepreneurial education and relating activities and formats over the last years. As smaller companies (SMEs) are increasingly experimenting with entrepreneurship, they seem to struggle with setting up entrepreneurial activities within their established corporate strategy and innovation structures. It is beneficial for them to collaborate with higher education institutions to minimize the risk and uncertainty associated with implementing entrepreneurship education (EE) and catch up with larger corporates. Further, research lacks a systematic characterization of EE activities in those companies and classification of collaboration formats. Therefore, this study uses qualitative research methods to analyze data from interviews conducted with two German SMEs. Our study contributes to a better understanding of EE in SME and respective HEI collaborations by (1) characterizing EE in SME and SME-HEI collaboration based on attributes and collaboration types defined by their locus of collaboration and intensity of knowledge inflow and (2) identifying differences among EE in SME and HEI. We provide implications to practice—corporate and university EE initiatives—for a more effective design and implementation of EE in SMEs and the SME-HEI collaborations themselves.
Business Partner Compliance
(2022)
Arbeitsrecht für Dummies
(2023)
Unsere Wirtschaft ist ohne Verständnis des Arbeitsrechts schwer zu begreifen. Oliver Haag erklärt Ihnen von den Rechtsquellen bis hin zum Betriebsverfassungsrecht alles, was Sie über das Arbeitsrecht wissen sollten. Anhand von Übungsfällen können Sie Ihr Wissen direkt überprüfen.
Oliver Haag erklärt Ihnen, was Sie für Ihr Studium über Arbeitsrecht wissen sollten. Er führt Sie in die juristische Denk- und Arbeitsweise ein und erklärt Ihnen die allgemeinen Grundlagen des Arbeitsrechts. Sie erfahren außerdem, was es mit den Details des Individualarbeitsrechts und des Kollektivarbeitsrechts auf sich hat. Zum Abschluss lernen Sie anhand von Übungsfällen, wie Sie sich mit dem Arbeitsrecht in Klausuren auseinandersetzen sollten. So ist dieses Buch unverzichtbar bei Ihren ersten Schritten in diesem wichtigen, aber manchmal auch recht komplizierten Thema.
Physik Methoden
(2023)
Regional economies clearly benefit from thriving entrepreneurial ecosystems. However, ecosystems are not yet entirely gender-inclusive and therefore are not tapping their full potential. This is most critical with respect to technology-based entrepreneurship which features the largest gender imbalance. Despite the considerably growing amount of literature in the two research fields of female entrepreneurship and entrepreneurial ecosystems, the intersection of the two areas has not yet been outlined. We depict the state of knowledge with a structured review of the literature highlighting bibliometric information, methods used, and the main topics addressed in current articles. From there, recommendations for future research are derived.
Think BIQ: Gender Differences, Entrepreneurship Support and the Quality of Business Idea Description
(2023)
Entrepreneurship support, its influencing factors and female entrepreneurship are recently discussed topics with great relevance for society and politics. However, research on the subject has been divergent in its results and lacks a focus on the impact of support programs’ characteristics concerning different types of entrepreneurs. Thus, we conduct a fuzzy-set Qualitative Comparative Analysis on entrepreneurship support characteristics aiming to shed light on possible gender differences occurring in respective programs. We investigate the quality of business idea descriptions, as a predecessor for a high-potential business model, operationalized using inter alia causation and effectuation theory and social role theory as possible explanations. In our fuzzy-set Qualitative Comparative Analysis on a sample of 911 Norwegian ventures, we find a variety of differences related to the entrepreneurs’ gender. For instance, that financial support combined with a well described key contribution or careful planning seem to be more important antecedents for female entrepreneurs’ business idea quality than for males. Moreover, it seems a well-described key contribution has a positive effect on the outcome variable in most cases. Another interesting finding concerns the entrepreneurs’ network partners, where we found evident gender differences in our combinations. Female entrepreneurs seemingly benefitted from rather small networks, and males from big networks, although the former possess larger networks in the sample. In conclusion, we find that gender differences in combinations of entrepreneurship support for high business idea quality still occur even in a country like Norway, calling for an adaption of the provided support and environment.
Strategic renewal and the development of new types of innovation pose special challenges to established small and medium-sized companies. The paper at hand aims at answering the questions what the underlying mechanism of these challenges are and which approaches might help to properly counteracting them. This case study investigates the strategic renewal process and its corresponding interventions in a high-tech SME company during a four-year period. We analyse the findings in relation to existing frameworks for dynamic capabilities and strategic learning and provide new recommendations for practice and future research.
Research credits corporate entrepreneurship (CE) with enabling established companies to create new types of innovation. Scholars have focused on the organizational design of CE activities, proposing specific organizational units. These semi-autonomous units create a tense management situation between the core organization and its CE activities. Management and organization research considers control as a key managerial function for help. However, control has received limited research attention regarding CE units, leaving design issues for appropriate control of CE units unanswered. In this study, we link management control and CE to illustrate how control is understood in the context of CE. For this, we scanned the CE literature to identify underlying attributes and characteristics that allow specifying control for CE. We identified 11 attributes to describe control for CE activities in a first round and to derive future research paths.
Corporate Entrepreneurship (CE) units have become an increasingly important part of established companies’ development activities enabling them to also create more discontinuous innovations. As a result, companies have developed and implemented different forms of CE units, such as corporate accelerators, incubators, startup supplier programs, and corporate venture capital. Driven by the need to innovate, companies have even begun to use multiple CE units simultaneously. However, this has not been empirically investigated yet. Thus, with this study, we aim to shed some light on this by investigating the parallel use of multiple CE units in the German business landscape. We conducted an extensive desk research, combining, coding, and analyzing different sources. We found that 55 out of 165 large established companies have multiple CE units, which allowed us to characterize the parallel use and identify differences and similarities, e.g., in terms of industry, company size, and CE forms implemented. We conclude by presenting different implications for both practice and research and by pointing out directions for future research.
The aim of this paper is to find out in how accommodation providers in the Seychelles perceive climate change and what mitigation and adaptation measures they can provide. In order to answer these questions, a qualitative mixed-method-approach, comprised of twenty semi-structured interviews, an online-survey and participant observation was used. Results show that accommodation providers especially perceive the effects of climate change that directly affect their business and that they have already partly implemented some mitigation and adaptation measures. However, strategies and regulations are needed at the Seychelles’ government level and on a global level to actually achieve CO2 neutral travel.
This chapter takes a detailed look at the developmental state model and its manifestations in regional development policies. Developmentalist ideas have been waxing and waning across periods of economic boom and bust. Recent years, however, have seen a renaissance of East Asian developmentalism – reminiscent of its heyday in the 1980s and 1990s and most notably driven by the region’s continued economic strength.
The endorsement of state-led modernization, preferential policies, and close state-business relations – which underpinned Japan/Korea/China’s transformations – has also left its mark on current ODA practices in the region and beyond. East Asia’s state agencies are pushing ahead with colossal infrastructure programs – in close cooperation with commercial actors – that advance broad development goals and, at the same time, promotes national interests. Compared to Western OECD peers, Asian development cooperation tends to focus less on neoliberal and democratic principles and, instead, places greater emphasis on state-corporatist and meritocratic ideas.
To what extent East Asia’s infrastructural megaprojects and connectivity corridors across Eurasia and Africa (BRI, EAI, and Partnership for Quality Infrastructure) will generate political momentum for an emergent developmental consensus remains uncertain. The jury is still out when it comes to whether and how Asian developmentalism will take center stage in global development debates. What is clear, however, is that the changing zeitgeist of a less Anglo/Euro-centric world bodes well for more heterodox and diverse ideas on development cooperation.
Nach heutigem Stand der Technik kommen für die Dekontamination von Störstellen wie z.B. Ecken und Innenkanten, weitestgehend Technik aus dem konventionellen Sanierungsbereich zum Einsatz. Maschinen wie Nadelpistolen und Stockgeräte belasten das Arbeitspersonal mit starken Vibrationen und hohen Rückstellkräften. Daher sind entsprechend lange Pausenzeiten erforderlich, wodurch die ohnehin schon geringe Abtragleistung weiter gesenkt wird. Neben dem zusätzlichen Mehraufwand kann die Technik, aufgrund fehlender Absaugungseinrichtungen, unter Umständen zu einer Kontaminationsverschleppung führen. Hierbei werden in bereits dekontaminierten Bereichen kontaminierte Partikel verteilt, wodurch die erzielten Bearbeitungsfortschritte teilweise rückgängig gemacht werden.
Aufgrund der Vielzahl von Nachteilen, die bei den bisher eingesetzten Geräten auftreten, wurde das Forschungsprojekt EKONT-1 zur „Entwicklung eines innovativen, teilautomatisierten Gerätes für eine trocken-mechanische Ecken-, Kanten- und Störstellendekontamination in kerntechnischen Anlagen“ angestoßen und durchgeführt. Im Rahmen dieses Projektes konnten viele neue Erkenntnisse gewonnen und mehrere funktionsfähige Prototypen entwickelt, gebaut und sowohl im Labor als auch im praktischen Einsatz getestet werden. Da im Laufe der Versuche noch einige Verbesserungspotenziale aufgetreten sind, wurde zum 01.07.23 das Folge Projekt EKONT-2 gestartet, was sich mit der Weiterentwicklung der existierenden Prototypen beschäftigt.
Der Wandel des Einzelhandels
(2023)
Die Ursachen der existentiellen Bedrohung vieler Einzelhandelsunternehmen sind nicht nur auf die Nachwirkungen der Coronapandemie und den Ukraine-Krieg mit der daraus resultierenden Inflation und Kaufzurückhaltung zurückzuführen. Auch die Digitalisierung und die wachsende Onlinekonkurrenz sowie ein verändertes Einkaufs- und Konsumverhalten der Kund:innen setzt den Einzelhandel unter Druck. Dabei scheint besonders die junge Generation Z, die mit dem Internet, sozialen Medien und digitalen Anwendungen aufgewachsen ist, nicht mehr den traditionellen Konsummustern zu entsprechen, und erwartet eine Ausrichtung des Einzelhandels an ihre Bedürfnisse. Doch wie ticken junge Konsument:innen und wie unterscheiden sich ihre Erwartungen an den Handel von älteren Generationen? Im Beitrag werden Antworten auf diese Fragen gegeben.
Unintrusive health monitoring systems is important when continuous monitoring of the patient vital signals is required. In this paper, signals obtained from accelerometers placed under a bed are processed with ballistocardiography algorithms and compared with synchronized electrocardiographic signals.
Cardiovascular diseases (CVD) are leading contributors to global mortality, necessitating advanced methods for vital sign monitoring. Heart Rate Variability (HRV) and Respiratory Rate, key indicators of cardiovascular health, are traditionally monitored via Electrocardiogram (ECG). However, ECG's obtrusiveness limits its practicality, prompting the exploration of Ballistocardiography (BCG) as a non-invasive alternative. BCG records the mechanical activity of the body with each heartbeat, offering a contactless method for HRV monitoring. Despite its benefits, BCG signals are susceptible to external interference and present a challenge in accurately detecting J-Peaks. This research uses advanced signal processing and deep learning techniques to overcome these limitations. Our approach integrates accelerometers for long-term BCG data collection during sleep, applying Discrete Wavelet Transforms (DWT) and Ensemble Empirical Mode Decomposition (EEMD) for feature extraction. The Bi-LSTM model, leveraging these features, enhances heartbeat detection, offering improved reliability over traditional methods. The study's findings indicate that the combined use of DWT, EEMD, and Bi-LSTM for J-Peak detection in BCG signals is effective, with potential applications in unobtrusive long-term cardiovascular monitoring. Our results suggest that this methodology could contribute to HRV monitoring, particularly in home settings, enhancing patient comfort and compliance.
This study investigates the application of Force Sensing Resistor (FSR) sensors and machine learning algorithms for non-invasive body position monitoring during sleep. Although reliable, traditional methods like Polysomnography (PSG) are invasive and unsuited for extended home-based monitoring. Our approach utilizes FSR sensors placed beneath the mattress to detect body positions effectively. We employed machine learning techniques, specifically Random Forest (RF), K-Nearest Neighbors (KNN), and XGBoost algorithms, to analyze the sensor data. The models were trained and tested using data from a controlled study with 15 subjects assuming various sleep positions. The performance of these models was evaluated based on accuracy and confusion matrices. The results indicate XGBoost as the most effective model for this application, followed by RF and KNN, offering promising avenues for home-based sleep monitoring systems.
The massive use of patient data for the training of artificial intelligence algorithms is common nowadays in medicine. In this scientific work, a statistical analysis of one of the most used datasets for the training of artificial intelligence models for the detection of sleep disorders is performed: sleep health heart study 2. This study focuses on determining whether the gender and age of the patients have a relevant influence to consider working with differentiated datasets based on these variables for the training of artificial intelligence models.
Accurate monitoring of a patient's heart rate is a key element in the medical observation and health monitoring. In particular, its importance extends to the identification of sleep-related disorders. Various methods have been established that involve sensor-based recording of physiological signals followed by automated examination and analysis. This study attempts to evaluate the efficacy of a non-invasive HR monitoring framework based on an accelerometer sensor specifically during sleep. To achieve this goal, the motion induced by thoracic movements during cardiac contractions is captured by a device installed under the mattress. Signal filtering techniques and heart rate estimation using the symlets6 wavelet are part of the implemented computational framework described in this article. Subsequent analysis indicates the potential applicability of this system in the prognostic domain, with an average error margin of approximately 3 beats per minute. The results obtained represent a promising advancement in non-invasive heart rate monitoring during sleep, with potential implications for improved diagnosis and management of cardiovascular and sleep-related disorders.
This paper compares two popular scripting implementations for hardware prototyping: Python scripts exe- cut from User-Space and C-based Linux-Driver processes executed from Kernel-Space, which can provide information to researchers when considering one or another in their implementations. Conclusions exhibit that deploying software scripts in the kernel space makes it possible to grant a certain quality of sensor information using a Raspberry Pi without the need for advanced real-time operational systems.
Spatial modulation (SM) is a low-complexity multiple-input/multiple-output transmission technique that combines index modulation and quadrature amplitude modulation for wireless communications. In this work, we consider the problem of link adaption for generalized spatial modulation (GSM) systems that use multiple active transmit antennas simultaneously. Link adaption algorithms require a real-time estimation of the link quality of the time-variant communication channels, e.g., by means of estimating the mutual information. However, determining the mutual information of SM is challenging because no closed-form expressions have been found so far. Recently, multilayer feedforward neural networks were applied to compute the achievable rate of an index modulation link. However, only a small SM system with two transmit and two receive antennas was considered. In this work, we consider a similar approach but investigate larger GSM systems with multiple active antennas. We analyze the portions of mutual information related to antenna selection and the IQ modulation processes, which depend on the GSM variant and the signal constellation.
Reliability is a crucial aspect of non-volatile NAND flash memories, and it is essential to thoroughly analyze the channel to prevent errors and ensure accurate readout. Es-timating the read reference voltages (RRV s) is a significant challenge due to the multitude of physical effects involved. The question arises which features are useful and necessary for the RRV estimation. Various possible features require specialized hardware or specific readout techniques to be usable. In contrast we consider sparse histograms based on the decision thresholds for hard-input and soft-input decoding. These offer a distinct advantage as they are derived directly from the raw readout data without the need for decoding. This paper focuses on the information-theoretic study of different features, especially on the exploration of the mutual information (MI) between feature vector and RRV. In particular, we investigate the dependency of the MI on the resolution of the histograms. With respect to the RRV estimation, sparse histograms provide sufficient information for near-optimum estimation.
Sleep is a multi-dimensional influencing factor on physical health, cognitive function, emotional well-being, mental health, daily performance, and productivity. The barriers such as time-consuming, invasiveness, and expense have caused a gradual shift in sleep monitoring from traditional and standard in-lab approach, e. g., polysomnography (PSG) to unobtrusive and noninvasive in-home sleep monitoring, yet further improvement is required. Despite an increasing interest in fiberoptic-based methods for cardiorespiratory estimation, the traditional mechanical-based sensors consist of force-sensitive resistors (FSR), lead zirconate titanate piezoelectric (PZT), and accelerometers yet serve as the dominant approach. The part of popularity lies in reducing the system’s complexity, expense, easy maintenance, and user-friendliness. However, care must be taken regarding the performance of such sensors with respect to accuracy and calibration.
Das klinische Standardverfahren und Referenz der Schlafmessung und der Klassifizierung der einzelnen Schlafstadien ist die Polysomnographie (PSG). Alternative Ansätze zu diesem aufwändigen Verfahren könnten einige Vorteile bieten, wenn die Messungen auf eine komfortablere Weise durchgeführt werden. Das Hauptziel dieser Forschung Studie ist es, einen Algorithmus für die automatische Klassifizierung von Schlafstadien zu entwickeln, der ausschließlich Bewegungs- und Atmungssignale verwendet.
A post-growth economy is a comparatively new paradigm in the tourism discourse. The aim of this article is to find out the commonalities between this concept and Māori tourism and in which way the latter can contribute to a post-growth economy. A qualitative mixed method approach, including in-depth-interviews, participant observation, and secondary analysis is applied. The results show that there is a lot of overlap between Māori tourism and a post-growth economy. Differences are visible, as well, regarding the value approach of Māori tourism and the indicator approach of a post-growth economy. Especially the social innovation created in Aotearoa New Zealand at the instigation of Māori groups of granting legal personhood to parts of nature may serve as a driver for a form of tourism that is in line with the idea of a post-growth economy.
This paper applies the concept of Soja’s Thirdspace to the phenomenon of Lazgi dance and tourism in Uzbekistan. In doing so it analyses the different levels of perception (including Firstspace and Secondspace) of Lazgi and tourism via an autoethnographic lens. Complemented by expert interviews, the interaction of Lazgi and tourism is examined and characteristics of the Lazgisphere (world of Lazgi) in Uzbekistan are distilled. The results show that Lazgi is often directly or indirectly connected with tourism in Uzbekistan, but even more so serves to reaffirm national identity.
While driving, stress is caused by situations in which the driver estimates their ability to manage the driving demands as insufficient or loses the capability to handle the situation. This leads to increased numbers of driver mistakes and traffic violations. Additional stressing factors are time pressure, road conditions, or dislike for driving. Therefore, stress affects driver and road safety. Stress is classified into two categories depending on its duration and the effects on the body and psyche: short-term eustress and constantly present distress, which causes degenerative effects. In this work, we focus on distress. Wearable sensors are handy tools for collecting biosignals like heart rate, activity, etc. Easy installation and non-intrusive nature make them convenient for calculating stress. This study focuses on the investigation of stress and its implications. Specifically, the research conducts an analysis of stress within a select group of individuals from both Spain and Germany. The primary objective is to examine the influence of recognized psychological factors, including personality traits such as neuroticism, extroversion, psychoticism, stress and road safety. The estimation of stress levels was accomplished through the collection of physiological parameters (R-R intervals) using a Polar H10 chest strap. We observed that personality traits, such as extroversion, exhibited similar trends during relaxation, with an average heart rate 6% higher in Spain and 3% higher in Germany. However, while driving, introverts, on average, experienced more stress, with rates 4% and 1% lower than extroverts in Spain and Germany, respectively.
Analysing observability is an important step in the
process of designing state feedback controllers. While for linear
systems observability has been widely studied and easy-to-check
necessary and sufficient conditions are available, for nonlinear
systems, such a general recipe does not exist and different classes
of systems require different techniques. In this paper, we analyse
observability for an industrial heating process where a stripe-
shaped plastic workpiece is moving through a heating zone where
it is heated up to a specific temperature by applying hot air to its
surface through a nozzle. A modeling approach for this process
is briefly presented, yielding a nonlinear Ordinary Differential
Equation model. Sensitivity-based observability analysis is used
to identify unobservable states and make suggestions for addi-
tional sensor locations. In practice, however, it is not possible
to place additional sensors, so the available measurements are
used to implement a simple open-loop state estimator with
offset compensation and numerical and experimental results are
presented.
Study design:
Retrospective, mono-centric cohort research study.
Objectives:
The purpose of this study is to validate a novel artificial intelligence (AI)-based algorithm against human-generated ground truth for radiographic parameters of adolescent idiopathic scoliosis (AIS).
Methods:
An AI-algorithm was developed that is capable of detecting anatomical structures of interest (clavicles, cervical, thoracic, lumbar spine and sacrum) and calculate essential radiographic parameters in AP spine X-rays fully automatically. The evaluated parameters included T1-tilt, clavicle angle (CA), coronal balance (CB), lumbar modifier, and Cobb angles in the proximal thoracic (C-PT), thoracic, and thoracolumbar regions. Measurements from 2 experienced physicians on 100 preoperative AP full spine X-rays of AIS patients were used as ground truth and to evaluate inter-rater and intra-rater reliability. The agreement between human raters and AI was compared by means of single measure Intra-class Correlation Coefficients (ICC; absolute agreement; .75 rated as excellent), mean error and additional statistical metrics.
Results:
The comparison between human raters resulted in excellent ICC values for intra- (range: .97-1) and inter-rater (.85-.99) reliability. The algorithm was able to determine all parameters in 100% of images with excellent ICC values (.78-.98). Consistently with the human raters, ICC values were typically smallest for C-PT (eg, rater 1A vs AI: .78, mean error: 4.7°) and largest for CB (.96, -.5 mm) as well as CA (.98, .2°).
Conclusions:
The AI-algorithm shows excellent reliability and agreement with human raters for coronal parameters in preoperative full spine images. The reliability and speed offered by the AI-algorithm could contribute to the efficient analysis of large datasets (eg, registry studies) and measurements in clinical practice.
Designing cities
(2023)
Manual for Urban Design
Urban design is based on planning and design principles that need to meet functional demands on the one hand, but on the other hand bring the design elements together into a distinctive whole. The basic compositional principles are, for the most part, timeless. Designing Cities examines the most important design and presentation principles of urban design, using historical examples and contemporary international competition entries designed by practices including Foster + Partners, KCAP Architects & Planners, MVRDV, and OMA.
At the core of the publication is the question of how the projects were designed and what methods and tools were available to the designer: such as parametric design, in which variable parameters automatically influence the design and provide a range of possible solutions.
- Tools for urban design
- Current projects and award-winning competition entries by renowned international practices
- A textbook for students and a practical design aid for practicing architects and planners
Requirements Engineering in Business Analytics for Innovation and Product Lifecycle Management
(2014)
Considering Requirements Engineering (RE) in business analytics, involving market oriented management, computer science and statistics, may be valuable for managing innovation in Product Lifecycle Management (PLM). RE and business analytics can help maximize the value of corporate product information throughout the value chain starting with innovation management. Innovation and PLM must address 1) big data, 2) development of well-defined business goals and principles, 3) cost/benefit analysis, 4) continuous change management, and 5) statistical and report science. This paper is a positioning note that addresses some business case considerations for analytics project involving PLM data, patents, and innovations. We describe a number of research challenges in RE that addresses business analytics when high PLM data should be turned into a successful market oriented innovation management strategy. We provide a draft on how to address these research challenges.
Digitalization is one of the most frequently discussed topics in industry. New technologies, platform concepts and integrated data models do enable disruptive business models and drive changes in organization, processes, and tools. The goal is to make a company more efficient, productive and ultimately profitable. However, many companies are facing the challenge of how to approach digital transformation in a structured way and to realize these potential benefits. What they realize is that Product Lifecycle Management plays a key role in digitalization intends, as object, structure and process management along the life cycle is a foundation for many digitalization use cases. The introduced maturity model for assessing a firm’s capabilities along the product lifecycle has been used almost two hundred times. It allows a company to compare its performance with an industry specific benchmark to reveal individual strengths and weaknesses. Furthermore, an empirical study produced multidimensional correlation coefficients, which identify dependencies between business model characteristics and the maturity level of capabilities.
Low-Code Development Plattformen (LCDPs) fördern die digitale Transformation von Organisationen, indem sie die Applikationsentwicklung durch FachbereichsmitarbeiterInnen ohne tiefgreifende Programmierkenntnisse – sogenannte Citizen Developer – ermöglichen. Marktforschungsinstitute prognostizieren, dass in den nächsten Jahren mehr als die Hälfte aller Applikationen mit LCDPs entwickelt werden. Nichtsdestotrotz stehen Organisationen vor der Herausforderung, sich für die richtigen Implementierungs- und Anwendungsansätze von LCDPs zu entscheiden. Dieser Artikel liefert daher ein umfassendes Bild über das praktische Verständnis und aktuelle Ansätze in verschiedenen Organisationen und leitet daraus Handlungsempfehlungen ab. Dafür wurden 16 Experteninterviews durchgeführt und wissenschaftlich analysiert. Die Ergebnisse zeigen, dass die Praxis grundsätzlich ein ähnliches Verständnis des Begriffs LCDP hat. Die Initiative für die Einführung kommt meist aus den Fachbereichen, die Entscheidung für oder gegen die LCDP-Implementierung wird jedoch meist von der Geschäftsführung in Kooperation mit der IT-Abteilung getroffen. Dabei unterscheiden sich die aktuellen Anwendungsansätze: Unternehmen nutzen entweder einen Self-Service-Ansatz durch die Fachbereiche oder integrieren die Entscheidung über eine potenzielle LCDP-Entwicklung durch die Citizen Developer in das bestehende Demand-Management der IT-Abteilung. Eine etablierte und adaptive Governance ist für beide Ansätze eine wichtige Voraussetzung. Die Erkenntnisse des Beitrags tragen zur wissenschaftlichen Diskussion bei, da dieser Artikel eine der ersten umfassenden und wissenschaftlich fundierten qualitativen Analysen über aktuelle praktische Adoptionsansätze der Praxis liefert. PraktikerInnen erfahren zudem, wie andere Unternehmen mit aktuellen Herausforderungen umgehen und welche Ansätze erfolgversprechend sind.
Nowadays established companies use Corporate Entrepreneurship (CE) as a means to create discontinuous innovations. Many companies thereby even implement multiple CE units that typically involve several entrepreneurial activities. This explorative study aimed to identify the reasons why established companies implement multiple CE units concurrently. In conducting a comparative case study with eight companies from different industries, valuable insights for science and practice were gained. We provide an overview of different 11 reasons for implementing multiple CE units. This shows that the combination of CE units used by companies differs depending on the reason. It further allowed to derive general approaches of established companies to the implementation of CE units. Last, we identify the concept of co-specialization to be a central driver explaining the creation of the need to set up multiple units. We conclude by indicating implications and subjects for future research.
Entrepreneurial motivations have become a frequently discussed topic in entrepreneurship research. However, few studies investigated entrepreneurs' motivation across gender and different venture types and tend to rely on surveys or case studies. By using a text mining approach, we investigate if there are differences between male and female entrepreneurs' motivation and if female entrepreneurs' motivation differs across different venture types. This text mining approach in combination with a qualitative content analysis was used to examine unique motivational data from 472 entrepreneurial projects from three different entrepreneurship support programs in Norway and Sweden. Findings suggest that motivation of female and male entrepreneurs differ only slightly, while motivation of female entrepreneurs differs according to the different venture types. We thus contribute to a better understanding of entrepreneurial motivation and to a better understanding of why female entrepreneurs start a business. This can, for instance, benefit the improvement of future female entrepreneurship support programs.
Corporate Entrepreneurship (CE) has now evolved into an imperative innovation practice of established companies. Despite organizational design models for CE activities and companies' frequent initiation of new activities, effectively managing them remains a challenging endeavor which results in disappointment about the outcomes of CE and its early termination. We assume specific types of goals for CE as one element of this unresolved management issue. While both practice and literature address goals in different contexts, no uniform picture has emerged so far. Although goals are commonly used to categorize CE activities, they seldomly seem to be the core subject of investigation. Based on this preliminary analysis and consolidation, we put the goals of CE in focus. In a systematic literature review, we reveal aspects of goals to unmask the different types of goals and their underlying dimensions and characteristics. Our review contributes to a better understanding of goals by (1) organizing relevant literature on goals of CE in a specific classification process, (2) describing dimensions and attributes for a systematic classification of CE goals; and (3) providing a framework showing differences of goals for the CE context. We conclude with a discussion and hints for future research paths.
In the last decade, both sustainability and business models for sustainability have increased in importance. Sustainability issues have become the focus of discussion. These issues are interlinked and often negatively impact each other. They are complex and include socio-ecological dilemmas, exist in almost every aspect of our society (economic, environmental, social), and are hard to formulate. They may have multiple, incompatible solutions, competing objectives, and open timeframes. Previous research has not developed satisfactory ways to comprehend and solve problems of this nature. Life Cycle Assessment (LCA) the widely used method to assess sustainable development has reached its limitation to achieve sustainable social goals. System Dynamics (SD) is a valuable methodology that enhances understanding of the structure and internal dynamic behaviours of large, complex, and dynamic systems, leading to improved decision-making. It offers a philosophy and set of tools for modelling, analysing, and simulating dynamic systems. This research applied system dynamics methods in conjunction with simulation software to assess the potential impact of a solution on environmental, social, and economic aspects of a complex system, aims to gain insights into the system's behaviour and identify the potential consequences of interventions or policy changes across multiple dimensions. This paper responds to the urgent need for a new business model by presenting a concept for an adapted dynamic business modelling for sustainability (aDBMfS) using system dynamics. Case studies in the smartphone industry are applied.
“Crowd contamination”?
(2023)
Misconduct allegations have been found to not only affect the alleged firm but also other, unalleged firms in form of reputational and financial spillover effects. It has remained unexplored, however, how the number of prior allegations against other firms matters for an individual firm currently facing an allegation. Building on behavioral decision theory, we argue that the relationship between allegation prevalence among other firms and investor reaction to a focal allegation is inverted U-shaped. The inverted U-shaped effect is theorized to emerge from the combination of two effects: In the absence of prior allegations against other firms, investors fail to anticipate the focal allegation, and hence react particularly negatively (“anticipation effect”). In the case of many prior allegations against other firms, investors also react particularly negatively because investors perceive the focal allegation as more warranted (“evaluation effect”). The multi-industry, empirical analysis of 8,802 misconduct allegations against US firms between 2007 and 2017 provides support for our predicted, inverted U-shaped effect. Our study complements recent misconduct research on spillover effects by highlighting that not only a current allegation against an individual firm can “contaminate” other, unalleged firms but that also prior allegations against other firms can “contaminate” investor reaction to a focal allegation against an individual firm.
Compliance meets CSR
(2023)
Was früher Gegenstand freiwilliger Selbstverpflichtung war, wird seit einiger Zeit zunehmend reguliert: die Wahrnehmung der unternehmensspezifischen Verantwortung gegenüber Umwelt und Gesellschaft, neudeutsch Corporate Social Responsibility (CSR). CSR und Compliance rücken damit näher zusammen. Vieles, was früher durch CSR-Abteilungen im besten Fall systematisch gemanagt wurde, ist nun gesetzlich vorgeschrieben und fällt damit in den Aufgabenbereich von Compliance. Liegt es da nicht nahe, die beiden Bereiche miteinander zu verschmelzen respektive CSR dem Bereich unterzuordnen, der seit den spektakulären Korruptions- und Bilanzfälschungsskandalen zu Beginn dieses Jahrtausends über die größere Management-Awareness verfügt?
Der vorliegende Beitrag versucht deutlich zu machen, wie das Verhältnis sachlich-fachlich einzuordnen ist und welche Schlussfolgerungen in der Praxis daraus gezogen werden könnten.
This paper compares novel methods to efficiently include input constraints using the nonlinear Model Predictive Path Integral (MPPI) approach. The MPPI algorithm solves stochastic optimal control problems and is based on sampled trajectories. MPPI results from the physical path integral framework. Sample-based algorithms are characterized by the fact that they can be computed in parallel and offer the possibility to handle discontinuous dynamics and cost functions. However, using standard MPPI the input costs in the Lagrange term have to be chosen quadratic. This fact is unfavorable for various real applications. Further, in standard nonlinear model predictive control (NMPC) approaches hard box constraints on the control input trajectory can be treated directly. In this contribution, novel architectures based on integrator action are compared. The investigated input constraint MPPI controllers were tested on an autonomous self-balancing vehicle. Therefore both, simulation and real-world experiments are presented. This paper addresses the question of how the MPPI algorithm can be further developed to consider input box constraints. Videos of the self-balancing vehicle are available at: https: https://tinyurl.com/mvn8j7vf
Comparison of Data-Driven Modeling and Identification Approaches for a Self-Balancing Vehicle
(2023)
This paper gives a systematic comparison of different state–of–the–art modeling approaches and the corresponding parameter identification processes for a self–balancing vehicle. In detail, a nonlinear grey box model, its extension to consider friction effects, a parametric black box model based on regression neural networks, and a hybrid approach are presented. The parameters of the models are identified by solving a nonlinear least squares problem. The training, validation, and test datasets are collected in full–scale experiments using a self–balancing vehicle. The performance of the different models used for ego–motion prediction are compared in full–scale scenarios, as well. The investigated model architectures can be used to improve both, simulation environments and model–based controller design. This paper shows the upsides and downsides arising from using the different modeling approaches. Videos showing the self–balancing vehicle in action are available at: https://tinyurl.com/mvn8j7vf22nd
Urlaub, Urlaub und kein Ende – Die aktuelle Rechtslage auf Basis der Rechtsprechung von EuGH und BAG
(2023)
Die jüngeren Entscheidungen des EuGH sowie des BAG zur Arbeitszeiterfassung haben trotz ihrer eigentlich klaren Aussagen in der betrieblichen Praxis zu teils erheblichen Verunsicherungen geführt: Müssen nun wirklich die Arbeitszeiten der Beschäftigten erfasst werden und wie wirkt sich das auf die in vielen Unternehmen gelebte „Vertrauensarbeitszeit“ aus?