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Über die letzten Jahre nehmen die Verkehrsunfälle zwischen Fahrzeugen und Fahrrädern und Motorrädern immer weiter zu. Die Ursache ist meistens eine unachtsam geöffnete Fahrzeugtür, mit der ein anfahrender Zweiradfahrer kollidiert. Diese Unfälle können verheerende Folgen für alle Beteiligten haben. Aus diesem Grund soll der technologische Fortschritt, welcher sich durch die gesamte Automobilbranche zieht, um eine zusätzliche Komponente erweitert werden. Hierbei handelt es sich um ein System für Zweiradfahrer, welches eine sich öffnende Fahrzeugtür frühzeitig erkennen soll, den Fahrer somit frühzeitig warnen kann und gegebenenfalls Strategien zu Unfallvermeidung einleiten kann. Dieses Konzept soll die Entwicklung des Systems vorgeben und grundlegend erläutern.
Cardiovascular diseases are directly or indirectly responsible for up to 38.5% of all deaths in Germany and thus represent the most frequent cause of death. At present, heart diseases are mainly discovered by chance during routine visits to the doctor or when acute symptoms occur. However, there is no practical method to proactively detect diseases or abnormalities of the heart in the daily environment and to take preventive measures for the person concerned. Long-term ECG devices, as currently used by physicians, are simply too expensive, impractical, and not widely available for everyday use. This work aims to develop an ECG device suitable for everyday use that can be worn directly on the body. For this purpose, an already existing hardware platform will be analyzed, and the corresponding potential for improvement will be identified. A precise picture of the existing data quality is obtained by metrological examination, and corresponding requirements are defined. Based on these identified optimization potentials, a new ECG device is developed. The revised ECG device is characterized by a high integration density and combines all components directly on one board except the battery and the ECG electrodes. The compact design allows the device to be attached directly to the chest. An integrated microcontroller allows digital signal processing without the need for an additional computer. Central features of the evaluation are a peak detection for detecting R-peaks and a calculation of the current heart rate based on the RR interval. To ensure the validity of the detected R-peaks, a model of the anatomical conditions is used. Thus, unrealistic RR-intervals can be excluded. The wireless interface allows continuous transmission of the calculated heart rate. Following the development of hardware and software, the results are verified, and appropriate conclusions about the data quality are drawn. As a result, a very compact and wearable ECG device with different wireless technologies, data storage, and evaluation of RR intervals was developed. Some tests yelled runtimes up to 24 hours with wireless Lan activated and streaming.
In previous studies, we used a method for detecting stress that was based exclusively on heart rate and ECG for differentiation between such situations as mental stress, physical activity, relaxation, and rest. As a response of the heart to these situations, we observed different behavior in the Root Mean Square of the Successive differences heartbeats (RMSSD). This study aims to analyze Virtual Reality via a virtual reality headset as an effective stressor for future works. The value of the Root Mean Square of the Successive Differences is an important marker for the parasympathetic effector on the heart and can provide information about stress. For these measurements, the RR interval was collected using a breast belt. In these studies, we can observe the Root Mean Square of the successive differences heartbeats. Additional sensors for the analysis were not used. We conducted experiments with ten subjects that had to drive a simulator for 25 minutes using monitors and 25 minutes using virtual reality headset. Before starting and after finishing each simulation, the subjects had to complete a survey in which they had to describe their mental state. The experiment results show that driving using virtual reality headset has some influence on the heart rate and RMSSD, but it does not significantly increase the stress of driving.
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.
To evaluate the quality of sleep, it is important to determine how much time was spent in each sleep stage during the night. The gold standard in this domain is an overnight polysomnography (PSG). But the recording of the necessary electrophysiological signals is extensive and complex and the environment of the sleep laboratory, which is unfamiliar to the patient, might lead to distorted results. In this paper, a sleep stage detection algorithm is proposed that uses only the heart rate signal, derived from electrocardiogram (ECG), as a discriminator. This would make it possible for sleep analysis to be performed at home, saving a lot of effort and money. From the heart rate, using the fast Fourier transformation (FFT), three parameters were calculated in order to distinguish between the different sleep stages. ECG data along with a hypnogram scored by professionals was used from Physionet database, making it easy to compare the results. With an agreement rate of 41.3%, this approach is a good foundation for future research.
Stress is recognized as a factor of predominant disease and in the future the costs for treatment will increase. The presented approach tries to detect stress in a very basic and easy to implement way, so that the cost for the device and effort to wear it remain low. The user should benefit from the fact that the system offers an easy interface reporting the status of his body in real time. In parallel, the system provides interfaces to pass the obtained data forward for further processing and (professional) analyses, in case the user agrees. The system is designed to be used in every day’s activities and it is not restricted to laboratory use or environments. The implementation of the enhanced prototype shows that the detection of stress and the reporting can be managed using correlation plots and automatic pattern recognition even on a very light weighted microcontroller platform.
Stress is recognized as a predominant disease with raising costs for rehabilitation and treatment. Currently there are several different approaches that can be used for determining and calculating the stress levels. Usually the methods for determining stress are divided in two categories. The first category do not require any special equipment for measuring the stress. This category useless the variation in the behaviour patterns that occur while stress. The core disadvantage for the category is their limitation to specific use case. The second category uses laboratories instruments and biological sensors. This category allow to measure stress precisely and proficiently but on the same time they are not mobile and transportable and do not support real-time feedback. This work presents a mobile system that provides the calculation of stress. For achieving this, the of a mobile ECG sensor is analysed, processed and visualised over a mobile system like a smartphone. This work also explains the used stress measurement algorithm. The result of this work is a portable system that can be used with a mobile system like a smartphone as visual interface for reporting the current stress level.
The investigation of stress requires to distinguish between stress caused by physical activity and stress that is caused by psychosocial factors. The behaviour of the heart in response to stress and physical activity is very similar in case the set of monitored parameters is reduced to one. Currently, the differentiation remains difficult and methods which only use the heart rate are not able to differentiate between stress and physical activity, without using additional sensor data input. The approach focusses on methods which generate signals providing characteristics that are useful for detecting stress, physical activity, no activity and relaxation.
The purpose of this paper is to examine the effects of perceived stress on traffic and road safety. One of the leading causes of stress among drivers is the feeling of having a lack of control during the driving process. Stress can result in more traffic accidents, an increase in driver errors, and an increase in traffic violations. To study this phenomenon, the Stress Perceived Questionnaire (PSQ) was used to evaluate the perceived stress while driving in a simulation. The study was conducted with participants from Germany, and they were grouped into different categories based on their emotional stability. Each participant was monitored using wearable devices that measured their instantaneous heart rate (HR). The preference for wearable devices was due to their non-intrusive and portable nature. The results of this study provide an overview of how stress can affect traffic and road safety, which can be used for future research or to implement strategies to reduce road accidents and promote traffic safety.
Methods based exclusively on heart rate hardly allow to differentiate between physical activity, stress, relaxation, and rest, that is why an additional sensor like activity/movement sensor added for detection and classification. The response of the heart to physical activity, stress, relaxation, and no activity can be very similar. In this study, we can observe the influence of induced stress and analyze which metrics could be considered for its detection. The changes in the Root Mean Square of the Successive Differences provide us with information about physiological changes. A set of measurements collecting the RR intervals was taken. The intervals are used as a parameter to distinguish four different stages. Parameters like skin conductivity or skin temperature were not used because the main aim is to maintain a minimum number of sensors and devices and thereby to increase the wearability in the future.
Segmentierung von Polypen in Koloskopie-Bilddaten : eine Potentialanalyse von Deep-Learning-Methoden
(2018)
Kolorektale Karzinome haben eine hohe Sterblichkeitsrate, wenn sie spät entdeckt werden. Eine frühzeitige Entfernung von bösartigen Polypen im Magen-Darm-Trakt, die deren Vorstufen bilden, bietet jedoch hohe Überlebenschancen. Bei Darmspiegelungen werden gerade kleine Polypen aber recht häufig übersehen. Zuverlässige bildverarbeitende Systeme, die Polypen in einem Koloskopie-Frame nicht nur detektieren, sondern pixelgenau segmentieren, könnten Ärzten bei Darmkrebs-Screenings helfen. Diese Arbeit analysiert den aktuellen Stand der Segmentierung von Polypen im Gastrointestinaltrakt. Weiterführend wird untersucht, inwiefern die in letzter Zeit sehr erfolgreichen Methoden des Deep Learning hier Vorteile bieten.
This paper contributes to the automatic detection of perioperative workflow by developing a binary endoscope localization. Automated situation recognition in the context of an intelligent operating room requires the automatic conversion of low level cues into more abstract high level information. Imagery from a laparoscope delivers rich content that is easy to obtain but hard to process. We introduce a system which detects if the endoscope's distal tip is inside or outsiede the patient based on the endoscope video. This information can be used as one parameter in a situation recognition pipeline. Our localization performs in real-time at a video resolution of 1280x720 and 5-fold cross validation yields mean F1-scores of up to 0,94 on videos of 7 laparoscopies.
Knowledge is an important resource, whose transfer is still not completely understood. The underlying belief of this thesis is that knowledge cannot be transferred directly from one person to another but must be converted for the transfer and therefore is subject to loss of knowledge and misunderstanding. This thesis proposes a new model for knowledge transfer and empirically evaluates this model. The model is based on the belief that knowledge must be encoded by the sender to transfer it to the receiver, who has to decode the message to obtain knowledge.
To prepare for the model this thesis provides an overview about models for knowledge transfer and factors that influence knowledge transfer. The proposed theoretical model for knowledge transfer is implemented in a prototype to demonstrate its applicability. The model describes the influence of the four layers, namely code, syntactic, semantic, and pragmatic layers, on the encoding and decoding of the message. The precise description of the influencing factors and the overlapping knowledge from sender and receiver facilitate its implementation.
The application area of the layered model for knowledge transfer was chosen to be business process modelling. Business processes incorporate an important knowledge resource of an organisation as they describe the procedures for the production of products and services. The implementation in a software prototype allows a precise description of the process by adding semantic to the simple business process modelling language used.
This thesis contributes to the body of knowledge by providing a new model for knowledge transfer, which shows the process of knowledge transfer in greater detail and highlights influencing factors. The implementation in the area of business process modelling reveals the support provided by the model. An expert evaluation indicates that the implementation of the proposed model supports knowledge transfer in business process modelling. The results of the qualitative evaluation are supported by the findings of a qualitative evaluation, performed as a quasi-experiment with a pre-test/post-test design and two experimental groups and one control group. Mann-Whitney U tests indicated that the group that used the tool that implemented the layered model performed significantly better in terms of completeness (the degree of completeness achieved in the transfer) in comparison with the group that used a standard BPM tool (Z = 3.057, p = 0.002, r = 0.59) and the control group that used pen and paper (Z = 3.859, p < 0.001, r = 0.72). The experiment indicates that the implementation of the layered model supports the creation of a business process and facilitates a more precise representation.
Knowledge transfer is very important to our knowledge-based society and many approaches have been proposed to describe this transfer. However, these approaches take a rather abstract view on knowledge transfer, which makes implementation difficult. In order to address this issue, we introduce a layered model for knowledge transfer that structures the individual steps of knowledge transfer in more detail. This paper gives a description of the process and also an example of the application of the layered model for knowledge transfer. The example is located in the area of business process modelling. Business processes contain the important knowledge describing the procedures of the company to produce products and services. Knowledge transfer is the fundamental basis in the modelling and usage of Business processes, which makes it an interesting use case for the layered model for knowledge transfer.
Business processes are important knowledge resources of a company. The knowledge contained in business processes impart procedures used to create products and services. However, modelling and application of business processes are affected by problems connected to knowledge transfer. This paper presents and implements a layered model to improve the knowledge transfer. Thus modelling and understanding of business process models is supported. An evaluation of the approach is presented and results and other areas of application are discussed.
Learning and teaching requires the transfer of knowledge from one person to another. Due to the relevance of knowledge many models have been developed for knowledge transfer. However, the process of knowledge transfer has not yet been described completely and the approaches are too vague to facilitate its implementation. This paper contributes to a better understanding of knowledge transfer to support knowledge transfer in teaching. To address this challenge, we depict a layered model for knowledge transfer. The model structures the transfer in several steps and thus identifies major influencing factors. The paper describes the knowledge transfer from one person to another step by step. An example in the area of teaching business process management illuminates the process. The main contribution of this paper is the development of a layered model and its application in teaching.
Workshop Java EE 7 : ein praktischer Einstieg in die Java Enterprise Edition mit dem Web Profile
(2015)
Dieses Arbeitsbuch bietet Ihnen eine praktische Einführung in die Entwicklung von Business- Anwendungen mit Java EE 7. Schrittweise erstellen Sie eine einfach nachvollziehbare Beispielanwendung auf Grundlage des Web Profile. Dabei lernen Sie alle wichtigen Technologien und Konzepte von Java EE 7 kennen, u.a.: Grafische Oberflächen mit JavaServer Faces und HTML5; Business-Logik mit CDI und EJB; Persistenz mit JPA; Kommunikation mit REST, SOAP und WebSockets; Erweiterte Konzepte wie Resource Library Contracts, Interceptors, Transaktionen, Timer und Security. Über Java EE 7 hinaus wird auch auf weitere praxisrelevante Themen wie Build Management und Testing eingegangen. Das Deployment wird auf den Applikationsservern WildFly 8 und Glassfish 4 sowie über das Cloud-Angebot OpenShift durchgeführt. Am Ende einer jeden Entwicklungsphase finden Sie Übungen und Fragen zur Lernkontrolle.Nach der erfolgreichen Lektüre sind Sie in der Lage, Java-EE-7-Anwendungen selbständig aufzusetzen, zu entwickeln und auf einem Anwendungsserver zu verteilen. Kenntnisse in der Entwicklung mit Java werden vorausgesetzt. Grundlagen von HTML und der Architektur von Webanwendungen sind hilfreich. In der 2. Auflage wird nun auch die Internationalisierung sowie die Erstellung funktionaler Tests mit Graphene behandelt.
A large body of literature is concerned with models of presence— the sensory illusion of being part of a virtual scene— but there is still no general agreement on how to measure it objectively and reliably. For the presented study, we applied contemporary theory to measure presence in virtual reality. Thirty-seven participants explored an existing commercial game in order to complete a collection task. Two startle events were naturally embedded in the game progression to evoke physical reactions and head tracking data was collected in response to these events. Subjective presence was recorded using a post-study questionnaire and real-time assessments. Our novel implementation of behavioral measures lead to insights which could inform future presence research: We propose a measure in which startle reflexes are evoked through specific events in the virtual environment, and head tracking data is compared to the range and speed of baseline interactions.
Private equity (PE) firms are investment firms that acquire equity shares in companies. The goal of PE firms is to exit the investment after few years with a substantial increase in value. PE firms often claim to outperform the market, i.e. to create alpha.
The overall aim of this paper is to unravel the mystery of value creation in the PE industry. First, the author presents a conceptual framework for value creation in the PE industry based on a multiple valuation model that breaks down value creation into different elements. Second, the paper evaluates whether PE firms really create value by analysing and combining results from prior empirical studies based on the conceptual framework.
The results show that existing empirical evidence is mixed but that there is indeed a tendency toward a positive evidence that PE firms create economic value in average. However, there are methodological difficulties in measuring the value creation and studies are often subject to bias. Finally, it is pointed out that the question whether PE firms really create value has to be viewed from different perspectives such as the perspective of the PE firm, the investors and the portfolio companies.
Purpose
Digital transformation of organizations has major implications for required skills and competencies of the workforce, both as a prerequisite for implementation, and, as a consequence of the transformation. The purpose of this study is to analyze required skills and competencies for digital transformation using the context of robotic process automation (RPA) as an example.
Design/methodology/approach
This study is based on an explorative, thematic coding analysis of 119 job advertisements related to RPA. The data was collected from major online job platforms, qualitatively coded and subsequently analyzed quantitatively.
Findings
The research highlights the general importance of specific skills and competencies for digital transformation and shows a gap between available skills and required skills. Moreover, it is concluded that reskilling the existing workforce might be difficult. Many emerging positions can be found in the consulting sector, which raises questions about the permanent vs temporary nature of the requirements, as well as the difficulty of acquiring the required knowledge.
Originality/value
This paper contributes to knowledge by providing new empirical findings and a novel perspective to the ongoing discussion of digital skills, employment effects and reskilling demands of the existing workforce owing to recent technological developments and automation in the overall context of digital transformation.