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"KI first" braucht Verlierer
(2023)
Aktuell vergeht kaum eine Woche, in der nicht ein Unternehmen den Kampf um die Vorherrschaft im Bereich der Künstlichen Intelligenz (KI) aufnimmt. Tech-Konzerne versprechen sich auch von KI-gesteuerten Bildgeneratoren satte Gewinne. Diese ahmen mit synthetischen Mischbildern stilprägende Künstler/innen nach. Dabei wird auf die Rechtslage verwiesen, die eine zustimmungs- und vergütungsfreie Vervielfältigung ihrer Kunstwerke für Trainingszwecke angeblich zulässt. Doch Widerstand von Künstlern/innen hiergegen ist gesellschaftlich dringend geboten und wäre im Übrigen auch rechtlich gedeckt.
100 Jahre Türkische Republik
(2023)
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.
Large-scale quantum computers threaten the security of today's public-key cryptography. The McEliece cryptosystem is one of the most promising candidates for post-quantum cryptography. However, the McEliece system has the drawback of large key sizes for the public key. Similar to other public-key cryptosystems, the McEliece system has a comparably high computational complexity. Embedded devices often lack the required computational resources to compute those systems with sufficiently low latency. Hence, those systems require hardware acceleration. Lately, a generalized concatenated code construction was proposed together with a restrictive channel model, which allows for much smaller public keys for comparable security levels. In this work, we propose a hardware decoder suitable for a McEliece system based on these generalized concatenated codes. The results show that those systems are suitable for resource-constrained embedded devices.
Background
This is a systematic review protocol to identify automated features, applied technologies, and algorithms in the electronic early warning/track and triage system (EW/TTS) developed to predict clinical deterioration (CD).
Methodology
This study will be conducted using PubMed, Scopus, and Web of Science databases to evaluate the features of EW/TTS in terms of their automated features, technologies, and algorithms. To this end, we will include any English articles reporting an EW/TTS without time limitation. Retrieved records will be independently screened by two authors and relevant data will be extracted from studies and abstracted for further analysis. The included articles will be evaluated independently using the JBI critical appraisal checklist by two researchers.
Discussion
This study is an effort to address the available automated features in the electronic version of the EW/TTS to shed light on the applied technologies, automated level of systems, and utilized algorithms in order to smooth the road toward the fully automated EW/TTS as one of the potential solutions of prevention CD and its adverse consequences.
The development of automatic solutions for the detection of physiological events of interest is booming. Improvements in the collection and storage of large amounts of healthcare data allow access to these data faster and more efficiently. This fact means that the development of artificial intelligence models for the detection and monitoring of a large number of pathologies is becoming increasingly common in the medical field. In particular, developing deep learning models for detecting obstructive apnea (OSA) events is at the forefront. Numerous scientific studies focus on the architecture of the models and the results that these models can provide in terms of OSA classification and Apnea-Hypopnea-Index (AHI) calculation. However, little focus is put on other aspects of great relevance that are crucial for the training and performance of the models. Among these aspects can be found the set of physiological signals used and the preprocessing tasks prior to model training. This paper covers the essential requirements that must be considered before training the deep learning model for obstructive sleep apnea detection, in addition to covering solutions that currently exist in the scientific literature by analyzing the preprocessing tasks prior to training.
Sleep is an essential part of human existence, as we are in this state for approximately a third of our lives. Sleep disorders are common conditions that can affect many aspects of life. Sleep disorders are diagnosed in special laboratories with a polysomnography system, a costly procedure requiring much effort for the patient. Several systems have been proposed to address this situation, including performing the examination and analysis at the patient's home, using sensors to detect physiological signals automatically analysed by algorithms. This work aims to evaluate the use of a contactless respiratory recording system based on an accelerometer sensor in sleep apnea detection. For this purpose, an installation mounted under the bed mattress records the oscillations caused by the chest movements during the breathing process. The presented processing algorithm performs filtering of the obtained signals and determines the apnea events presence. The performance of the developed system and algorithm of apnea event detection (average values of accuracy, specificity and sensitivity are 94.6%, 95.3%, and 93.7% respectively) confirms the suitability of the proposed method and system for further ambulatory and in-home use.
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.
Regional economies clearly benefit from thriving entrepreneurial ecosystems. However, ecosystems are not yet entirely gender-inclusive and therefore are not tapping their full potential. This is most critical with respect to technology-based entrepreneurship which features the largest gender imbalance. Despite the considerably growing amount of literature in the two research fields of female entrepreneurship and entrepreneurial ecosystems, the intersection of the two areas has not yet been outlined. We depict the state of knowledge with a structured review of the literature highlighting bibliometric information, methods used, and the main topics addressed in current articles. From there, recommendations for future research are derived.
Das klinische Standardverfahren und Referenz der Schlafmessung und der Klassifizierung der einzelnen Schlafstadien ist die Polysomnographie (PSG). Alternative Ansätze zu diesem aufwändigen Verfahren könnten einige Vorteile bieten, wenn die Messungen auf eine komfortablere Weise durchgeführt werden. Das Hauptziel dieser Forschung Studie ist es, einen Algorithmus für die automatische Klassifizierung von Schlafstadien zu entwickeln, der ausschließlich Bewegungs- und Atmungssignale verwendet.
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.
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.
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.
In order to ensure sufficient recovery of the human body and brain, healthy sleep is indispensable. For this purpose, appropriate therapy should be initiated at an early stage in the case of sleep disorders. For some sleep disorders (e.g., insomnia), a sleep diary is essential for diagnosis and therapy monitoring. However, subjective measurement with a sleep diary has several disadvantages, requiring regular action from the user and leading to decreased comfort and potential data loss. To automate sleep monitoring and increase user comfort, one could consider replacing a sleep diary with an automatic measurement, such as a smartwatch, which would not disturb sleep. To obtain accurate results on the evaluation of the possibility of such a replacement, a field study was conducted with a total of 166 overnight recordings, followed by an analysis of the results. In this evaluation, objective sleep measurement with a Samsung Galaxy Watch 4 was compared to a subjective approach with a sleep diary, which is a standard method in sleep medicine. The focus was on comparing four relevant sleep characteristics: falling asleep time, waking up time, total sleep time (TST), and sleep efficiency (SE). After evaluating the results, it was concluded that a smartwatch could replace subjective measurement to determine falling asleep and waking up time, considering some level of inaccuracy. In the case of SE, substitution was also proved to be possible. However, some individual recordings showed a higher discrepancy in results between the two approaches. For its part, the evaluation of the TST measurement currently does not allow us to recommend substituting the measurement method for this sleep parameter. The appropriateness of replacing sleep diary measurement with a smartwatch depends on the acceptable levels of discrepancy. We propose four levels of similarity of results, defining ranges of absolute differences between objective and subjective measurements. By considering the values in the provided table and knowing the required accuracy, it is possible to determine the suitability of substitution in each individual case. The introduction of a “similarity level” parameter increases the adaptability and reusability of study findings in individual practical cases.
The influence of sleep on human health is enormous. Accordingly, sleep disorders can have a negative impact on it. To avoid this, they should be identified and treated in time. For this purpose, objective (with an appropriate device) or subjective (based on perceived values) measurement methods are used for sleep analysis to understand the problem. The aim of this work is to find out whether an exchange of the two methods is possible and can provide reliable results. In accordance with this goal, a study was conducted with people aged over 65 years old (a total of 154 night-time recordings) in which both measurement methods were compared. Sleep questionnaires and electronic devices for sleep assessment placed under the mattress were applied to achieve the study aims. The obtained results indicated that the correlation between both measurement methods could be observed for sleep characteristics such as total sleep time, total time in bed and sleep efficiency. However, there are also significant differences in absolute values of the two measurement approaches for some subjects/nights, which leads us to conclude that the substitution is more likely to be considered in case of long-term monitoring where the trends are of more importance and not the absolute values for individual nights.
Service in der Investitionsgüterindustrie wird heutzutage in der Regel immer noch manuell und vor Ort beim Kunden ausgeführt. Dazu braucht es qualifizierte Service-Techniker:innen, die über das nötige Produkt- Prozesswissen verfügen. Für kleine und mittelständische Unternehmen (KMU) der Investitionsgüterindustrie stellt insbesondere die Internationalisierung eine Herausforderung dar, da qualifizierte Service-Techniker:innen eine rare Ressource sind. Es gilt sie möglichst effektiv und effizient einzusetzen. Zu diesem Zweck wurde im Rahmen des SerWiss-Projektes eine Lösung entwickelt, die es KMU ermöglicht, service-rele-
vantes Wissen effizient zu generieren, zu strukturieren und am Point-of-Service bereitzustellen sowie im Rahmen geeigneter Geschäftsmodelle zu vermarkten. Im Beitrawird erläutert, wie sich dieses erfasste Wissen als kundenorientiertes Wertangebot einsetzen und erlöswirksam in entsprechenden Geschäftsmodellen umsetzen lässt.
Die Berücksichtigung ökologischer und sozialer Gesichtspunkte in der Konzeption, Planung und Errichtung von Gebäuden hat in den vergangenen Jahren großen Einfluss auf Marktfähigkeit der Immobilien gewonnen. Regulatorische Rahmenwerke wie die Taxonomie-Verordnung der Europäischen Union formulieren die klare Anforderung an die Bauwirtschaft dem Schutz von Mensch und Natur mehr Bedeutung einzuräumen. Nur mit einem wesentlichen Beitrag zu den Klimazielen der Europäischen Union wird es der Branche langfristig möglich sein sich einen uneingeschränkten Zugang zum Investorenmarkt zu sichern.
Die vorliegende wissenschaftliche Arbeit widmet sich dem Kriterienkatalog der Deutschen Gesellschaft für Nachhaltiges Bauen e.V. und legt Übereinstimmungen mit den technischen Bewertungskriterien der EU-Taxonomie Verordnung offen. Der im Frühjahr 2023 erschienen Kriterienkatalog umfasst eine Vielzahl von Kriterien, anhand derer Gebäude auf Nachhaltigkeit geprüft werden. Im Vergleich zu der Vorgängerversion aus dem Jahr 2018 wurden erhebliche Änderungen eingearbeitet. Besonders hervorzuheben sind neue technische Prüfkriterien im Bereich Klimaschutz, Ressourcengewinnung, Biodiversität und Kreislaufwirtschaft. Die Angleichung der Berechnungsmethode für die Ökobilanzen an das bundeseigene „Qualitätssiegel Nachhaltiges Gebäude“, die Mindestanforderung nach dem erhöhten Einsatz von nachhaltig gewachsenem Holz, die Prüfung spezifischer Zielquoten bei dem Einsatz von Recyclingbeton sowie Anforderungen an die Zirkularität sind nur ein Teil der Neuerungen. Für die zusätzlichen Anforderung müssen Projektentwickler mit Mehrkosten im hohen sechsstelligen Bereich im Vergleich zu der Vorgängerversion rechnen. Vorteile der Neuauflage des Kriterienkataloges sind eine erhöhte Übereinstimmung mit den Nachhaltigkeitsanforderungen der Europäischen Union. Es werden jedoch nicht alle Anforderungen erfüllt. Nachweise für den Primärenergiebedarf, die Schadstoffbelastung von Bauteilen bzw. -materialien und eine Umweltverträglichkeitsprüfung müssen zusätzlich zu dem Kriterienkatalog der Deutschen Gesellschaft für Nachhaltiges Bauen geleistet werden. Insgesamt ebnen die Kriterien der Deutschen Gesellschaft für Nachhaltiges Bauen aber den Weg hin zu einer EU-Konformität und helfen Projektentwicklern Immobilien erfolgreich auf dem Markt zu positionieren.
This study aims to investigate the utilization of Bayesian techniques for the calibration of micro-electro-mechanical system (MEMS) accelerometers. These devices have garnered substantial interest in various practical applications and typically require calibration through error-correcting functions. The parameters of these error-correcting functions are determined during a calibration process. However, due to various sources of noise, these parameters cannot be determined with precision, making it desirable to incorporate uncertainty in the calibration models. Bayesian modeling offers a natural and complete way of reflecting uncertainty by treating the model parameters as variables rather than fixed values. In addition, Bayesian modeling enables the incorporation of prior knowledge, making it an ideal choice for calibration. Nevertheless, it is infrequently used in sensor calibration. This study introduces Bayesian methods for the calibration of MEMS accelerometer data in a straightforward manner using recent advances in probabilistic programming.
Unter bestimmten Kontaktbedingungen zwischen Rad und Schiene können selbsterregte Schwingungen angeregt werden, die zu gegenphasigen Drehbewegungen der Radscheiben und hohen Torsionsmomenten in der Radsatzwelle führen. Zur Bestimmung des maximalen Torsionsmoments sind bislang aufwendige Testfahrten erforderlich, da keine Verfahren bekannt waren, die eine konservative Berechnung des Torsionsmoments ermöglichen [1]. In den vergangenen Jahren wurden die drei folgenden Berechnungsmethoden vertieft untersucht, um das maximale, dynamische Torsionsmoment zu berechnen:
- Simulationen von komplexen Mehrkörpersystemen (MKS)
- Differentialgleichungssysteme mit numerischer Berechnung
- Analytische Berechnung durch Reduktion auf ein Minimalmodell
In dieser Publikation sollen diese Berechnungsmethoden näher vorgestellt werden und durch eine Gegenüberstellung der jeweils berechneten und gemessenen Ergebnisse deren Möglichkeiten aber auch Limitationen aufgezeigt werden.
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 may lead to false reactions of the driver assistance system. In this paper, the Boids flocking algorithm is used to generate semantic neighborhood information between tracked objects which in turn can significantly improve the overall performance. Two different variants were developed: First, a free-moving flock whereby a separate flock is generated per tracked object and second, a formation-controlled flock where boids of a single flock move along the future road course in a pre-defined formation. In the first approach, the interaction between the flocks as well as the interaction between the boids within a flock is used to generate additional information, which in turn can be used to improve, for example, lane change detection. For the latter approach, new behavioral rules have been developed, so that the boids can reliably identify control-relevant objects to a driver assistance system. Finally, the performance of the presented methods is verified through extensive simulations.
Bribery
(2023)
Carroll, A.B.
(2023)
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.
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.
The architecture, engineering and construction (AEC) industry is currently in transformation. Within this transformation, digitalization has a leading function, whereby a higher level of efficiency is pursued. In order to ensure a coordinated information exchange within the digitalization, the concept of the Common Data Environment (CDE) has been developed in the last years. A CDE is a cloud based collaborative platform that is used to exchange project information and data between the different stakeholders of a construction project. The main objective of this thesis is the implementation of a suitable CDE solution for the purpose of a construction management company.
For this purpose, an evaluation of different CDE software on the market, based on the functions and usability of the different software, has been complied to identify the most suitable solution. Secondly, a concept for the setup and implementation of a CDE solution has been developed. Therefore, advice for a successful change-management has been established to ensure the good implementation of the CDE.
The first part of the thesis includes a literature review through which the current state of the information management in the AEC industry is analyzed. The advantages of a CDE for the information management are also analyzed. Therefore, a synthesis of the functions and requirements to a CDE has been complied.
The second part of the thesis links the concept of Building Information Modelling (BIM) with the CDE. The advantages of a CDE in the BIM process has been established.
The third part of the thesis treats the evaluation of CDE software. This evaluation has been complied with a scoring method. As basis of the evaluation, a requirement list has been developed in which all the required functions of a CDE are listed.
In the fourth part of the thesis, a concept for the establishment of a CDE has been developed. The developed concept is a practical application of the standards specifications to CDE. The concept has been developed with CDE expert and CDE power users. The developed concept treats overall of the structuration, the standardization, and the implementation of a CDE.
The last part treats of the change process engender by the implementation of a CDE.
Summary, this thesis provides a structure for the implementation of a CDE software and serves as framework for companies of the AEC industry to select and establish a CDE.
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.
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
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.
Healthy sleep is one of the prerequisites for a good human body and brain condition, including general well-being. Unfortunately, there are several sleep disorders that can negatively affect this. One of the most common is sleep apnoea, in which breathing is impaired. Studies have shown that this disorder often remains undiagnosed. To avoid this, developing a system that can be widely used in a home environment to detect apnoea and monitor the changes once therapy has been initiated is essential. The conceptualisation of such a system is the main aim of this research. After a thorough analysis of the available literature and state of the art in this area of knowledge, a concept of the system was created, which includes the following main components: data acquisition (including two parts), storage of the data, apnoea detection algorithm, user and device management, data visualisation. The modules are interchangeable, and interfaces have been defined for data transfer, most of which operate using the MQTT protocol. System diagrams and detailed component descriptions, including signal requirements and visualisation mockups, have also been developed. The system's design includes the necessary concepts for the implementation and can be realised in a prototype in the next phase.
Sleep is essential to physical and mental health. However, the traditional approach to sleep analysis—polysomnography (PSG)—is intrusive and expensive. Therefore, there is great interest in the development of non-contact, non-invasive, and non-intrusive sleep monitoring systems and technologies that can reliably and accurately measure cardiorespiratory parameters with minimal impact on the patient. This has led to the development of other relevant approaches, which are characterised, for example, by the fact that they allow greater freedom of movement and do not require direct contact with the body, i.e., they are non-contact. This systematic review discusses the relevant methods and technologies for non-contact monitoring of cardiorespiratory activity during sleep. Taking into account the current state of the art in non-intrusive technologies, we can identify the methods of non-intrusive monitoring of cardiac and respiratory activity, the technologies and types of sensors used, and the possible physiological parameters available for analysis. To do this, we conducted a literature review and summarised current research on the use of non-contact technologies for non-intrusive monitoring of cardiac and respiratory activity. The inclusion and exclusion criteria for the selection of publications were established prior to the start of the search. Publications were assessed using one main question and several specific questions. We obtained 3774 unique articles from four literature databases (Web of Science, IEEE Xplore, PubMed, and Scopus) and checked them for relevance, resulting in 54 articles that were analysed in a structured way using terminology. The result was 15 different types of sensors and devices (e.g., radar, temperature sensors, motion sensors, cameras) that can be installed in hospital wards and departments or in the environment. The ability to detect heart rate, respiratory rate, and sleep disorders such as apnoea was among the characteristics examined to investigate the overall effectiveness of the systems and technologies considered for cardiorespiratory monitoring. In addition, the advantages and disadvantages of the considered systems and technologies were identified by answering the identified research questions. The results obtained allow us to determine the current trends and the vector of development of medical technologies in sleep medicine for future researchers and research.
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.
Creative Coding - void draw
(2023)
Creative Coding ist eines der vielen trendigen Schlagwörter, die in letzter Zeit in der Designbranche auftauchen. Wie so oft ist Creative Coding aber prinzipiell gar nicht so neu, sondern eine Wortschöpfung, die etwas beschreibt, was DesignerInnen schon lange betreiben, was jedoch nun breiter diskutiert wird und als wichtiges Konzept für Designer anerkannt ist.
CSR Pyramid
(2023)
The scoring of sleep stages is one of the essential tasks in sleep analysis. Since a manual procedure requires considerable human and financial resources, and incorporates some subjectivity, an automated approach could result in several advantages. There have been many developments in this area, and in order to provide a comprehensive overview, it is essential to review relevant recent works and summarise the characteristics of the approaches, which is the main aim of this article. To achieve it, we examined articles published between 2018 and 2022 that dealt with the automated scoring of sleep stages. In the final selection for in-depth analysis, 125 articles were included after reviewing a total of 515 publications. The results revealed that automatic scoring demonstrates good quality (with Cohen's kappa up to over 0.80 and accuracy up to over 90%) in analysing EEG/EEG + EOG + EMG signals. At the same time, it should be noted that there has been no breakthrough in the quality of results using these signals in recent years. Systems involving other signals that could potentially be acquired more conveniently for the user (e.g. respiratory, cardiac or movement signals) remain more challenging in the implementation with a high level of reliability but have considerable innovation capability. In general, automatic sleep stage scoring has excellent potential to assist medical professionals while providing an objective assessment.
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.
Digital federated platforms and data cooperatives for secure, trusted and sovereign data exchange will play a central role in the construction industry of the future. With the help of platforms, cooperatives and their novel value creation, the digital transformation and the degree of organization of the construction value chain can be taken to a new level of collaboration. The goal of this research project was to develop an experimental prototype for a federated innovation data platform along with a suitable exemplary use case. The prototype is to serve the construction industry as a demonstrator for further developments and form the basis for an innovation platform. It exemplifies how an overall concept is concretely implemented along one or more use cases that address high-priority industry pain points. This concept will create a blueprint and a framework for further developments, which will then be further established in the market. The research project illuminates the perspective of various governance innovations to increase industry collaboration, productivity and capital project performance and transparency as well as the overall potential of possible platform business models. However, a comprehensive expert survey revealed that there are considerable obstacles to trust-based data exchange between the key stakeholders in the industry value network. The obstacles to cooperation are predominantly not of a technical nature but rather of a competitive, predominantly trust-related nature. To overcome these obstacles and create a pre-competitive space of trust, the authors therefore propose the governance structure of a data cooperative model, which is discussed in detail in this paper.
Der Kundenservice von morgen
(2023)
Die digitale Selbstbedienung im Einzelhandel und anderen Dienstleistungsbereichen verändert die Konsumwelt. Self-Services werden zunehmend von Konsumenten aller Altersklassen genutzt. Der Handel muss seine Servicekanäle hinterfragen und vermehrt auf Self-Service als Kundenkontaktpunkt setzen. Andere Branchen haben diesbezüglich bereits Lösungen umgesetzt. Vor diesem Hintergrund analysiert der Beitrag die Nutzung von Self-Service-Lösungen in Abhängigkeit von der Generationen-Zugehörigkeit und gibt Handlungsempfehlungen für KMU aus dem Einzelhandel.
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.
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
Linear and nonlinear response functions (RF) are extracted for the climate system and the carbon cycle represented by the MPI-ESM and cGENIE models, respectively. Appropriately designed simulations are run for this purpose. Joining these RFs, we have a climate emulator with carbon emissions as the forcing and any desired observable quantity (provided the data is saved), such as the surface air temperature or precipitation, as the predictand. Like e.g. for atmospheric CO2 concentration, we also have RFs for the solar constant as a forcing — mimicking solar radiation management (SRM) geoengineering. We consider two application cases. 1. One is based on the Paris 2015 agreement, determining the necessary least amount of SRM geoengineering needed to keep the global mean surface air temperature below a certain threshold, e.g. 1.5 or 2 [oC], given a certain amount of carbon emission abatement (ABA) and carbon dioxide removal (CDR) geoengineering. 2. The other application considers the conservation of the Greenland ice sheet (GrIS). Using a zero-dimensional simplification of a complex ice sheet model, we determine (a) if we need SRM given some ABA and CDR, and, if possible, (b) the required least amount of SRM to avoid the collapse of the GrIS. Keeping temperatures below 2 [oC] even is hardly possible without sustained SRM (1.); however, the collapse of the GrIS can be avoided applying SRM even for moderate levels of CDR and ABA, an overshoot being affordable (2.).
Development of an expert system to overpass citizens technological barriers on smart home and living
(2023)
Adopting new technologies can be overwhelming, even for people with experience in the field. For the general public, learning about new implementations, releases, brands, and enhancements can cause them to lose interest. There is a clear need to create point sources and platforms that provide helpful information about the novel and smart technologies, assisting users, technicians, and providers with products and technologies. The purpose of these platforms is twofold, as they can gather and share information on interests common to manufacturers and vendors. This paper presents the ”Finde-Dein-SmartHome” tool. Developed in association with the Smart Home & Living competence center [5] to help users learn about, understand, and purchase available technologies that meet their home automation needs. This tool aims to lower the usability barrier and guide potential customers to clear their doubts about privacy and pricing. Communities can use the information provided by this tool to identify market trends that could eventually lower costs for providers and incentivize access to innovative home technologies and devices supporting long-term care.
Die Relevanzanalyse
(2023)
Ordnungsgemäße Unternehmensführung ohne adäquates Risiko- und Compliance-Management ist kaum noch vor- und darstellbar. Rechtsprechung, Literatur, Politik und Gesellschaft stellen (mehr oder weniger) klare Anforderungen an ordnungsgemäßes unternehmerisches Verhalten und sanktionieren tatsächliche (und vermeintliche) Regelverstöße. Um die unternehmensspezifischen Risiken zu erfassen ist die Durchführung einer Risikoanalyse (Compliance Risk Assessment – CRA) unumgänglich1. Der eigentlichen Risikoanalyse ist eine Relevanzanalyse voranzustellen, um sich der bei unternehmerischen Aktivitäten naturgemäß nahezu unüberschaubaren potenziellen Risikomenge anzunähern und diese „abarbeitbar“ zu erfassen. Wird diese Relevanzanalyse professionell und strukturiert durchgeführt und dokumentiert, so kann sie einen wertvollen Beitrag zum Schutz und zur Hilfe gegen Compliance-Verstöße und deren Sanktionierung leisten. Der nachfolgende Beitrag stellt die Grundlagen, Ziele, Anforderungen und Ansätze der Relevanzanalyse dar. In einem weiteren Beitrag (erscheint in CB 11/2023) werden sich die Autoren der Durchführung der Relevanzanalyse widmen und Hinweise zu deren Ablauf und Inhalt geben.
Die Relevanzanalyse
(2023)
Um unternehmensspezifische Risiken zu erfassen ist die Risikoanalyse unumgänglich. Ihr ist wiederum eine Relevanzanalyse voranzustellen. Nachdem im Heft 10 des Compliance Berater 2023, S. 400-404 die Grundlagen, Ziele, Anforderungen und Ansätze der Relevanzanalyse dargestellt wurden, widmet sich der nachfolgende Beitrag der Durchführung der Relevanzanalyse und gibt Hinweise zu deren Ablauf und Inhalt.
Die Vermessung der Stadt
(2023)
Sanktionen stellen Zwangsmaßnahmen dar, die bei der Bewältigung politischer Spannungen zwischen Nationen eine lange und wiederkehrende Stellung einnehmen. Sie werden sowohl einseitig als auch in Staatenbündnissen verhängt und besonders nach dem 2. Weltkrieg mit zunehmender Häufigkeit eingesetzt. Während im letzten Jahrhundert, insbesondere vor dem 2. Weltkrieg, Handelsbeschränkungen und umfassende Wirtschaftsblockaden die vorherrschenden Sanktionsinstrumente darstellten, werden heute in einer stärker integrierten und globalisierten Welt Sanktionen in verschiedenen weiteren Formen verhängt, einschließlich internationaler Finanzbeschränkungen, Reiseverbote, Handelseinschränkungen für bestimmte Gütergruppen, Aufhebung militärischer Hilfen und spezifische Einschränkungen, wie beispielsweise Flugverbote und Hafensperrungen.
Digitalisierung im Bauwesen
(2023)
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.
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.
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
Die Kleinwasserkraft stand zuletzt zunehmend in der öffentlichen Kritik wegen des ökologischen Einflusses und der verhältnismäßigen geringen Stromerzeugung. Der vorliegende Beitrag beschreibt die Einschätzung von KWK-Betreibern zum Potenzial einer Effizienzsteigerung ihrer bestehenden Anlagen durch eine intelligente Informationsvernetzung innerhalb des Flusslaufes der Radolfzeller Aach im Süden Baden-Württembergs, um somit die Stromerzeugung der einzelnen Anlagen zu erhöhen.
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.
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.
Entwicklung und Analyse eines Turmes aus Buchenfurnierschichtholz für eine Kleinwindkraftanlage
(2023)
Die Energiepreise in Deutschland steigen und viele Immobilienbesitzer wollen unabhängiger von den Stromerzeugern werden, weshalb sie in eine eigene Stromproduktion investieren. Eine optimale Ergänzung zu einer Photovoltaikanlage stellt dabei eine Kleinwindkraftanlage dar, die im Vergleich zu den großen Anlagen geringere Umweltbelastungen verursacht. Allerdings entstehen beim Bau einer Kleinwindkraftanlage hohe Kosten, weshalb dieses Konzept kaum verbreitet ist.
Die Türme von Windkraftanlagen werden normalerweise aus Stahl hergestellt. Bei der Herstellung dieses Baustoffs werden große Mengen an Treibhausgasen freigesetzt. Ein umweltfreundlicheres Material ist der nachwachsende Rohstoff Holz. Die Herstellung der Türme in Holzbauweise ist bisher kaum zu finden. Daher wird in dieser Arbeit untersucht, ob ein Holzturm eine Alternative zum Stahlturm sein kann und ob dadurch die Investitionskosten für eine Kleinwindkraftanlage gesenkt werden können.
Um die Forschungsfrage zu beantworten, wurde ein Konzept für einen Holzturm aus Buchenfurnierschichtholz entwickelt. Zunächst wurde die Bedeutung von Buchenholz im Bauwesen erarbeitet. Anschließend wurden die Grundlagen für den Bau von Kleinwindkraftanlagen erforscht und die Abmessungen einer fiktiven Anlage festgelegt. Es wurden die relevanten Einwirkungen ermittelt und die Anlage mittels einer Finiten-Elemente-Berechnung untersucht. Zuletzt wurden die Nachweise für die Tragfähigkeit und die Ermüdungssicherheit des Querschnittes und der Verbindungsmittel geführt.
Bei den Untersuchungen der Randbedingungen konnten keine Argumente gefunden werden, die gegen die Verwendung von Holz sprechen. In einigen Punkten wie beispielsweise in der Herstellungs- und Errichtungsphase sind sogar Vorteile gegenüber dem Stahl zu erkennen. Zudem wurde in einer Kostenschätzung herausgefunden, dass ein Holzturm auch preislich mithalten kann und dass die Herstellungskosten sogar gesenkt werden können. Die Gesamtkosten für eine Kleinwindkraftanlage können dennoch nur unwesentlich gesenkt werden. Die Investition ist daher nur sinnvoll, wenn am geplanten Standort genügend Wind zur Verfügung steht und wenn der produzierte Strom größtenteils selbst genutzt werden kann.
Entwicklung eines Prozesses für die Software-Funktionsvorentwicklung am Fahrzeug mittels Matlab/Simulink, um einen Machbarkeitsnachweis neuer Funktionen vor Beginn der Software-Serienentwicklung sicherzustellen. Der Prozess beinhaltet die Anforderungserhebung, die Systementwicklung in den Bereichen Hydraulik und Elektrik, die Software-Funktionsentwicklung in Matlab/Simulink sowie die Funktionsprüfung am Fahrzeug.
Contemporary empirical applications frequently require flexible regression models for complex response types and large tabular or non-tabular, including image or text, data. Classical regression models either break down under the computational load of processing such data or require additional manual feature extraction to make these problems tractable. Here, we present deeptrafo, a package for fitting flexible regression models for conditional distributions using a tensorflow backend with numerous additional processors, such as neural networks, penalties, and smoothing splines. Package deeptrafo implements deep conditional transformation models (DCTMs) for binary, ordinal, count, survival, continuous, and time series responses, potentially with uninformative censoring. Unlike other available methods, DCTMs do not assume a parametric family of distributions for the response. Further, the data analyst may trade off interpretability and flexibility by supplying custom neural network architectures and smoothers for each term in an intuitive formula interface. We demonstrate how to set up, fit, and work with DCTMs for several response types. We further showcase how to construct ensembles of these models, evaluate models using inbuilt cross-validation, and use other convenience functions for DCTMs in several applications. Lastly, we discuss DCTMs in light of other approaches to regression with non-tabular data.
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.
The principal objective of this study is to investigate the impact of perceived stress on traffic and road safety. Therefore, we designed a study that allows the generation and collection of stress-relevant data. Drivers often experience stress due to their perception of lack of control during the driving process. This can lead to an increased likelihood of traffic accidents, driver errors, and traffic violations. To explore this phenomenon, we used the Stress Perceived Questionnaire (PSQ) to evaluate perceived stress levels during driving simulations and the EPQR questionnaire to determine the personality of the driver. With the presented study, participants can categorised based on their emotional stability and personality traits. Wearable devices were utilised to monitor each participant's instantaneous heart rate (HR) due to their non-intrusive and portable nature. The findings of this study deliver an overview of the link between stress and traffic and road safety. These findings can be utilised for future research and implementing strategies to reduce road accidents and promote traffic safety.
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.
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 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.
Random matrices are used to filter the center of gravity (CoG) and the covariance matrix of measurements. However, these quantities do not always correspond directly to the position and the extent of the object, e.g. when a lidar sensor is used.In this paper, we propose a Gaussian processes regression model (GPRM) to predict the position and extension of the object from the filtered CoG and covariance matrix of the measurements. Training data for the GPRM are generated by a sampling method and a virtual measurement model (VMM). The VMM is a function that generates artificial measurements using ray tracing and allows us to obtain the CoG and covariance matrix that any object would cause. This enables the GPRM to be trained without real data but still be applied to real data due to the precise modeling in the VMM. The results show an accurate extension estimation as long as the reality behaves like the modeling and e.g. lidar measurements only occur on the side facing the sensor.
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.
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.
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.
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.
Measuring cardiorespiratory parameters in sleep, using non-contact sensors and the Ballistocardiography technique has received much attention due to the low-cost, unobtrusive, and non-invasive method. Designing a user-friendly, simple-to-use, and easy-to-deployment preserving less errorprone remains open and challenging due to the complex morphology of the signal. In this work, using four forcesensitive resistor sensors, we conducted a study by designing four distributions of sensors, in order to simplify the complexity of the system by identifying the region of interest for heartbeat and respiration measurement. The sensors are deployed under the mattress and attached to the bed frame without any interference with the subjects. The four distributions are combined in two linear horizontal, one linear vertical, and one square, covering the influencing region in cardiorespiratory activities. We recruited 4 subjects and acquired data in four regular sleeping positions, each for a duration of 80 seconds. The signal processing was performed using discrete wavelet transform bior 3.9 and smooth level of 4 as well as bandpass filtering. The results indicate that we have achieved the mean absolute error of 2.35 and 4.34 for respiration and heartbeat, respectively. The results recommend the efficiency of a triangleshaped structure of three sensors for measuring heartbeat and respiration parameters in all four regular sleeping positions.
Cities around the world are facing the implications of a changing climate as an increasingly pressing issue. The negative effects of climate change are already being felt today. Therefore, adaptation to these changes is a mission that every city must master. Leading practices worldwide demonstrate various urban efforts on climate change adaptation (CCA) which are already underway. Above all, the integration of climate data, remote sensing, and in situ data is key to a successful and measurable adaptation strategy. Furthermore, these data can act as a timely decision support tool for municipalities to develop an adaptation strategy, decide which actions to prioritize, and gain the necessary buy-in from local policymakers. The implementation of agile data workflows can facilitate the integration of climate data into climate-resilient urban planning. Due to local specificities, (supra)national, regional, and municipal policies and (by) laws, as well as geographic and related climatic differences worldwide, there is no single path to climate-resilient urban planning. Agile data workflows can support interdepartmental collaboration and, therefore, need to be integrated into existing management processes and government structures. Agile management, which has its origins in software development, can be a way to break down traditional management practices, such as static waterfall models and sluggish stage-gate processes, and enable an increased level of flexibility and agility required when urgent. This paper presents the findings of an empirical case study conducted in cooperation with the City of Constance in southern Germany, which is pursuing a transdisciplinary and trans-sectoral co-development approach to make management processes more agile in the context of climate change adaptation. The aim is to present a possible way of integrating climate data into CCA planning by changing the management approach and implementing a toolbox for low-threshold access to climate data. The city administration, in collaboration with the University of Applied Sciences Constance, the Climate Service Center Germany (GERICS), and the University of Stuttgart, developed a co-creative and participatory project, CoKLIMAx, with the objective of integrating climate data into administrative processes in the form of a toolbox. One key element of CoKLIMAx is the involvement of the population, the city administration, and political decision-makers through targeted communication and regular feedback loops among all involved departments and stakeholder groups. Based on the results of a survey of 72 administrative staff members and a literature review on agile management in municipalities and city administrations, recommendations on a workflow and communication structure for cross-departmental strategies for resilient urban planning in the City of Constance were developed.
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.
Online-Reisebewertungsplattformen sind der Treffpunkt für Touristen, um ihre Erlebnisse zu teilen und einander zu beeinflussen. Die Untersuchung des Besuchererlebnisses beim Besuch eines Museums kann sich positiv auf die Museumsentwicklung auswirken. In dieser Arbeit wurde eine qualitative Inhaltsanalyse verwendet, um die positiven und negativen Aspekte von Museumsbesuchen im indonesischen Nationalmuseum zu untersuchen. Durch die Datenanalyse von 420 TripAdvisor-Bewertungen des Nationalmuseums wurden die Aspekte ermittelt, die zur Zufriedenheit oder Unzufriedenheit der Besucher beitragen. Dadurch werden Museumsfachleute in die Lage versetzt, Museumsbesuche weiterzuentwickeln und zu verbessern.
Das Ergebnis dieser Studie zeigt, dass es 12 wichtige Themen gibt, die direkt mit der Erlebniswelt der Besucher im Museum verbunden sind, nämlich Ausstellungsdesign, Museumsidentität, First-hand Experience, Zugänglichkeit, Dienstleistungsumfeld, Architektur, Orientierung und Beschilderung, Annehmlichkeiten, Führungen, Wartungsarbeiten, Geschenkladen und Café, Mitarbeiter. Zu den positiven Aspekten der 12 Themen gehören die umfassenden Sammlungen, die Ausstellungsgestaltung, die Möglichkeit, Neues zu lernen, die günstigen Eintrittspreise, die strategische Lage des Museums, die informativen Museumsführer und die Dienstleistungen für eine Vielzahl von Museumsbesuchern. Bei den negativen Aspekten des Museums konzentrierten sich die Klagen der Besucher im Allgemeinen auf den Mangel an Interaktivität, Beschreibung, Kontext und Beleuchtung der Exponate. Darüber hinaus beklagten sich die Besucher über die Überfüllung an den Wochenenden, die ungepflegten Toiletten, das Verhalten des Personals und die Renovierungsarbeiten, die während der Öffnungszeiten des Museums durchgeführt wurden. Zur Verbesserung der Besuchsqualität sollte das Museum die Interaktivität und die Pflege der Sammlungen intensivieren, eine bessere Beleuchtung installieren, ausführliche Informationen über die Exponate bereitstellen, den Kundenservice und Mitarbeiterschulungen verbessern, Führungen für Kinder anbieten und einen offiziellen Museumsladen eröffnen.
Dieser Beitrag untersucht, ob externe Interventionen, in Form von Forschung und/oder Wissenschaftskommunikation, als Mediator für Innovationen in Krisenzeiten in der Tourismusbranche fungieren können. Dabei wird anhand dreier Case Studies diskutiert, inwiefern die Corona-Krise ein Window-
of-opportunity für innovative Geschäftsmodelle im Tourismus darstellen konnte. Die Projektergebnisse geben Hinweise darauf, dass Krisen im Allgemeinen und Wissenschaftskommunikation im Speziellen als Push-Faktoren Innovationen befördern können. Zwar kam es bei den Projektpartnern zu einer Entwicklung von Innovationen im Projektzeitraum, jedoch wurde die Implementierung vermehrt in eine unbestimmte Zukunft verschoben. Durch die damit verbundene Rückkehr zum Status-Quo blieben die angestoßenen Innovationen zu einem Großteil auf einer konzeptionellen Ebene. Dies deutet auf eine Attitude-behavior-gap in Bezug auf die Schaffung und Umsetzung von Innovationen in Krisenzeiten.
Insecurity Refactoring is a change to the internal structure of software to inject a vulnerability without changing the observable behavior in a normal use case scenario. An implementation of Insecurity Refactoring is formally explained to inject vulnerabilities in source code projects by using static code analysis. It creates learning examples with source code patterns from known vulnerabilities.
Insecurity Refactoring is achieved by creating an Adversary Controlled Input Dataflow tree based on a Code Property Graph. The tree is used to find possible injection paths. Transformation of the possible injection paths allows to inject vulnerabilities. Insertion of data flow patterns introduces different code patterns from related Common Vulnerabilities and Exposures (CVE) reports. The approach is evaluated on 307 open source projects. Additionally, insecurity-refactored projects are deployed in virtual machines to be used as learning examples. Different static code analysis tools, dynamic tools and manual inspections are used with modified projects to confirm the presence of vulnerabilities.
The results show that in 8.1% of the open source projects it is possible to inject vulnerabilities. Different inspected code patterns from CVE reports can be inserted using corresponding data flow patterns. Furthermore the results reveal that the injected vulnerabilities are useful for a small sample size of attendees (n=16). Insecurity Refactoring is useful to automatically generate learning examples to improve software security training. It uses real projects as base whereas the injected vulnerabilities stem from real CVE reports. This makes the injected vulnerabilities unique and realistic.
Die durch kleine und mittelständische Unternehmen geprägte Investitionsgüterindustrie steht aufgrund der zunehmenden Internationalisierung im Servicegeschäft vor großen Herausforderungen. Mitarbeiterengpässe, hohe Prozesskosten und unzureichendes Wissensmanagement machen den Service zur potenziellen betriebs- und volkswirtschaftlichen Wachstumsbremse. Durch die Digitalisierung entstehen aber auch große Nutzenpotenziale im Servicegeschäft. Ziel des im Projekt SerWiss entwickelten integrierten Ansatzes ist es, kleine und mittelständische Anbieter von Investitionsgütern zu befähigen, Servicewissen auf der Basis eines digitalen Lösungsansatzes unter Gewährleistung einer humanen Arbeitsgestaltung effizient zu generieren, zu strukturieren und international bereitzustellen bzw. zu vermarkten.
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.