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Physicians in interventional radiology are exposed to high physical stress. To avoid negative long-term effects resulting from unergonomic working conditions, we demonstrated the feasibility of a system that gives feedback about unergonomic
situations arising during the intervention based on the Azure Kinect camera. The overall feasibility of the approach could be shown.
Requirements Engineering (RE) umfasst sämtliche systematische Schritte zur Entwicklung eines Systems, um die Bedürfnisse der Nutzer und Vorgaben, die an dieses gestellt werden, zu erfüllen. Das RE eines ausgewählten Herstellers für klinische Informationssysteme (KIS) wurde untersucht und es stellt sich als intransparent als auch teilweise unzureichend dar. Das Ausmaß des Einsatzes von systematischen Vorgehensweisen und Methoden zum RE wurden beim ausgewählten KIS-Hersteller analysiert. Die Analyse zeigt, dass RE weit verbreitet ist, aber differenziert betrieben wird.
Das Ziel dieser Arbeit ist es, den Stand der Technik des RE für die KIS Entwicklung zu ermitteln. Es werden wichtige Faktoren des RE für die Entwicklung von KIS beschrieben. Die Ergebnisse dieser Arbeit werden als erster Schritt für die Optimierung des RE des ausgewählten KIS-Herstellers dienen.
Recognizing human actions is a core challenge for autonomous systems as they directly share the same space with humans. Systems must be able to recognize and assess human actions in real-time. To train the corresponding data-driven algorithms, a significant amount of annotated training data is required. We demonstrate a pipeline to detect humans, estimate their pose, track them over time and recognize their actions in real-time with standard monocular camera sensors. For action recognition, we transform noisy human pose estimates in an image like format we call Encoded Human Pose Image (EHPI). This encoded information can further be classified using standard methods from the computer vision community. With this simple procedure, we achieve competitive state-of-the-art performance in pose based action detection and can ensure real-time performance. In addition, we show a use case in the context of autonomous driving to demonstrate how such a system can be trained to recognize human actions using simulation data.
Enhancing data-driven algorithms for human pose estimation and action recognition through simulation
(2020)
Recognizing human actions, reliably inferring their meaning and being able to potentially exchange mutual social information are core challenges for autonomous systems when they directly share the same space with humans. Intelligent transport systems in particular face this challenge, as interactions with people are often required. The development and testing of technical perception solutions is done mostly on standard vision benchmark datasets for which manual labelling of sensory ground truth has been a tedious but necessary task. Furthermore, rarely occurring human activities are underrepresented in these datasets, leading to algorithms not recognizing such activities. For this purpose, we introduce a modular simulation framework, which offers to train and validate algorithms on various human-centred scenarios. We describe the usage of simulation data to train a state-of-the-art human pose estimation algorithm to recognize unusual human activities in urban areas. Since the recognition of human actions can be an important component of intelligent transport systems, we investigated how simulations can be applied for his purpose. Laboratory experiments show that we can train a recurrent neural network with only simulated data based on motion capture data and 3D avatars, which achieves an almost perfect performance in the classification of those human actions on real data.
Recognizing actions of humans, reliably inferring their meaning and being able to potentially exchange mutual social information are core challenges for autonomous systems when they directly share the same space with humans. Today’s technical perception solutions have been developed and tested mostly on standard vision benchmark datasets where manual labeling of sensory ground truth is a tedious but necessary task. Furthermore, rarely occurring human activities are underrepresented in such data leading to algorithms not recognizing such activities. For this purpose, we introduce a modular simulation framework which offers to train and validate algorithms on various environmental conditions. For this paper we created a dataset, containing rare human activities in urban areas, on which a current state of the art algorithm for pose estimation fails and demonstrate how to train such rare poses with simulated data only.
Using measurement and simulation for understanding distributed development processes in the Cloud
(2017)
Organizations increasingly develop software in a distributed manner. The Cloud provides an environment to create and maintain software-based products and services. Currently, it is widely unknown which software processes are suited for Cloud-based development and what their effects in specific contexts are. This paper presents a process simulation to study distributed development in the Cloud. We contribute a simulation model, which helps analyzing different project parameters and their impact on projects carried out in the Cloud. The simulator helps reproducing activities, developers, issues and events in the project, and it generates statistics, e.g., on throughput, total time, and lead and cycle time. The aim of this simulation model is thus to analyze the tradeoffs regarding throughput, total time, project size, and team size. Furthermore, the modified simulation model aims to help project managers select the most suitable planning alternative. Based on observed projects in Finland and Spain, we simulated a distributed project using artificial and real data. Particularly, we studied the variables project size, team size, throughput, and total project duration. A comparison of the real project data with the results obtained from the simulation shows the simulation producing results close to the real data, and we could successfully replicate a distributed software project. By improving the understanding of distributed development processes, our simulation model thus supports project managers in their decision-making.
Context: Organizations increasingly develop software in a distributed manner. The cloud provides an environment to create and maintain software-based products and services. Currently, it is unknown which software processes are suited for cloud-based development and what their effects in specific contexts are.
Objective: We aim at better understanding the software process applied to distributed software development using the cloud as development environment. We further aim at providing an instrument which helps project managers comparing different solution approaches and to adapt team processes to improve future project activities and outcomes.
Method: We provide a simulation model which helps analyzing different project parameters and their impact on projects performed in the cloud. To evaluate the simulation model, we conduct different analyses using a Scrumban process and data from a project executed in Finland and Spain. An extra adaptation of the simulation model for Scrum and Kanban was used to evaluate the suitability of the simulation model to cover further process models.
Results: A comparison of the real project data with the results obtaind from the different simulation runs shows the simulation producing results close to the real data, and we could successfully replicate a distributed software project. Furthermore, we could show that the simulation model is suitable to address further process models.
Conclusion: The simulator helps reproducing activities, developers, and events in the project, and it helps analyzing potential tradeoffs, e.g., regarding throughput, total time, project size, team size and work-in-progress limits. Furthermore, the simulation model supports project managers selecting the most suitable planning alternative thus supporting decision-making processes.
Scroll-activated animations eröffnen Webentwicklern neue Möglichkeiten der Interaktion und Präsentation von Inhalten. Durch die Animation von Bildern, Texten und weiteren Elementen einer Website soll der Nutzer durch die neue Darstellungsart positiv überrascht werden. Ziel ist es, dem Nutzer die Inhalte interessanter und möglichst gezielt zu vermitteln. Es stellt sich jedoch die Frage, ob die dadurch gesteigerte User Experience zulasten der Usability erfolgt. Unter Umständen führen die Animationen beim Nutzer zwar zu einem Aha-Effekt, setzen jedoch die Benutzerfreundlichkeit herab. Aus diesem Grund geht die Arbeit auf den Aspekt der Usability und User Experience dieser Animationen ein und untersucht den tatsächlichen Mehrwert des Einsatzes von Scroll-Animationen mithilfe von Webanalysetools. Durch den Vergleich mit einer inhaltlich identischen Seite sollen die oben genannten Effekte untersucht werden. Zusätzlich sollen die Ergebnisse nach Gerätetypen aufgeschlüsselt werden, um mögliche Unterschiede aufzudecken.
Im präventiven Krisenmanagement geht es um die frühzeitige Erkennung von möglichen, unvorhersehbaren Ereignissen. Hierzu zählen beispielhaft Busunfälle, einstürzende Gebäude und ähnliche Großschadensereignisse. Krisen treten meist unerwartet auf und neigen oftmals aufgrund der knapp bemessenen Handlungszeit zu Fehlentscheidungen. Um dies zu verhindern, dient das präventive Krisenmanagement dazu, sämtliche auftretende Ereignisse mittels einer Simulation zuvor durchzuspielen, um im Falle einer reellen Krise die notwendigen Schritte bestmöglich einzuleiten. Um Simulationen für das Krisenmanagement zu präzisieren und die Ergebnisse effektiv und vereinfacht zu veranschaulichen, ist es notwendig, eine Vorauswahl an vorhandenen Szenarien für Vergleiche heraussuchen zu können. Diese Arbeit entstand im Rahmen des FP-7 EU Projekts CRISMA (Crisis Management) [1] und dient zur Evaluation eines Konzepts zur Vorauswahl geeigneter Szenarien, welche in früheren Simulationen entstanden.
Autismus-Spektrum-Störungen (ASD) bei Kindern werden häufig zu spät diagnostiziert und die Begleitung der chronischen Krankheit gestaltet sich schwierig. Der vorgestellte Ansatz erlaubt die Behandlung der Kinder in dem bekannten häuslichen Umfeld und versucht die Beziehungen zwischen Schlaf und Verhalten herauszuarbeiten. Die gewonnenen Erkenntnisse sollen die Lebensqualität der Patienten verbessern und den Eltern Hilfestellung geben. Die notwendige infrastrukturelle Unterstützung wird durch medizinisches Fachpersonal geleistet, das auf einen web-basierten Service zurückgreifen kann, der sämtliche Prozesse (Diagnostik, Datenerfassung, -aufzeichnung und Training etc.) begleitet. Die anonymisierten Daten werden in einem Diagnosesystem zentral abgelegt und können so für zukünftige Behandlungsstrategien nutzbar sein. Die umfassende Lösung setzt auf zentrale Elemente von Smart-Homes und AAL auf.
Am Körper getragenen Geräte, sog. Wearables, kommunizieren in der Regel über Bluetooth-Low-Energy (BLE) mit dem Smartphone. Viele Anwendungen, insbesondere im Bereich Gesundheit und AAL, basieren auf der Zusammenarbeit von Wearables mit SmartHome-Geräten. Diese Arbeit präsentiert die Definition und Implementierung von einem neuen BLE Profil für EKG, das Streaming der Signal zum SmartPhone und die Möglichkeit, mehrere solcher Biosignale parallel zu streamen, besitzt. Die Datenarchitektur der App erlaubt eine konfigurierbare Synchronisation der Signal mit dem SmartHome.
Enterprises and societies currently face essential challenges, and digital transformation can contribute to their resolution. Enterprise architecture (EA) is useful for promoting digital transformation in global companies and information societies covering ecosystem partners. The advancement of new business models can be promoted with digital platforms and architectures for Industry 4.0 and Society 5.0. Therefore, products from the sector of healthcare, manufacturing and energy, etc. can increase in value. The adaptive integrated digital architecture framework (AIDAF) for Industry 4.0 and the design thinking approach is expected to promote and implement the digital platforms and digital products for healthcare, manufacturing and energy communities more efficiently. In this paper, we propose various cases of digital transformation where digital platforms and products are designed and evaluated for digital IT, digital manufacturing and digital healthcare with Industry 4.0 and Society 5.0. The vision of AIDAF applications to perform digital transformation in global companies is explained and referenced, extended toward the digitalized ecosystems such as Society 5.0 and Industry 4.0.
Enterprises and societies currently face crucial challenges, while Society 5.0 can contribute to a supersmart society, especially for manufacturing and healthcare, and Industry 4.0 becomes important in the global manufacturing industry. Smart energy digital platforms are architected to manage energy supply efficiently. Furthermore, the above digital platforms are expected to collect various kinds of data and analyze Big Data for the trends in the sharing economy in ecosystems. The adaptive integrated digital architecture framework (AIDAF) for Design Thinking Approach with Risk Management is expected to make an alignment with digital IT strategy. In this paper, we propose that various energy management systems and related digital platforms are designed and implemented in an alignment to digital IT strategy for sharing economy toward Society 5.0, with the AIDAF framework for Design Thinking Approach with Risk Management. The vision of AIDAF applications to enable sharing economy and digital platforms is explained and extended in the context of Society 5.0. In addition, challenges and future activities for this area are discussed that cover the directions of smart energy for Society 5.0.
Enterprise architecture (EA) is useful for promoting digital transformation in global companies and information societies. In this paper, the authors investigated and analyzed the process for digital transformation in global companies, together with related work in using and applying an enterprise architecture framework for the digital era named the adaptive integrated digital architecture framework (AIDAF). Moreover, they position the AIDAF framework for processing digital transformation in global companies. Based on this analysis, the authors propose and describe a new enterprise architecture process for promoting digital transformation in global companies. Furthermore, the authors propose an adaptive EA cycle-based architecture board framework on digital platforms, while verifying them with case studies in global companies. Finally, the authors clarify the challenges and critical success factors of the process and framework for digital transformation with architecture board reviews in the adaptive EA cycle to assist EA practitioners with its implementation.
Enterprises and societies currently face crucial challenges, while Industry 4.0 becomes important in the global manufacturing industry all the more. Industry 4.0 offers a range of opportunities for companies to increase the flexibility and efficiency of production processes. The development of new business models can be promoted with digital platforms and architectures for Industry 4.0. Therefore, products from the healthcare sector can increase in value. The adaptive integrated digital architecture framework (AIDAF) for Industry 4.0 is expected to promote and implement the digital platforms and robotics for healthcare and medical communities efficiently. In this paper, we propose that various digital platforms and robotics are designed and evaluated for digital healthcare as for manufacturing industry with Industry 4.0. We argue that the design of an open healthcare platform “Open Healthcare Platform 2030 - OHP2030” for medical product design and robotics can be developed with AIDAF. The vision of AIDAF applications to enable Industry 4.0 in the OHP2030 research initiative is explained and referenced, extended in the context of Society 5.0.
Enterprises and information societies confront crucial challenges currently, while Industry 4.0 becomes important in the global manufacturing industry and Society 5.0 should contribute to a supersmart society, especially for healthcare. Physical activity monitoring digital platforms are architected to improve the healthcare status of patients with diabetes and other lifestyle-related diseases. Furthermore, digital platforms are expected to generate profits for health technology companies and help control costs in the healthcare ecosystem. However, current digital enterprise architecture approaches are not well-established, and the potentials have not yet been realized. Design thinking approach and agile software development methodologies can overcome these limitations, beginning with proof of concept and pilot projects and then scaling to the production environment. In this paper, we describe how that the adaptive integrated digital architecture framework (AIDAF) for Design Thinking approach is proposed and verified in a case of a university hospital in the Americas. In addition, challenges and future activities for this area are discussed that cover the directions for Society 5.0.
Internet of Things (IoT) provides a strong platform for computer users to connect objects, devices, and people to the Internet for exchanging or sharing of information with each other. IoT is growing rapidly and is expected to adapt to disciplines such as manufacturing, agriculture, healthcare, and robotics. Furthermore, the new concept of IoT is proposed and shown, especially for robotics areas as Internet of Robotics Things (IoRT). IoRT is a mixed structure of diverse technologies such as cloud computing, artificial intelligence, and machine learning. However, to promote and realize IoRT, digitization and digital transformation should be proceeded and implemented in the robotics enterprise. In this paper, we propose and architecture framework for IoRT-based digital platforms an verify it using a planned case in a global robotics enterprise. The associated challenges and future research directions in this field are also presented.
Enterprise architecture (EA) is useful for effectively structuring digital platforms with digital transformation in information societies. Moreover, digital platforms in the healthcare industry accelerate and increase the efficiency of drug discovery and development processes. However, there is the lack of knowledge concerning relationships between EA and digital platforms, in spite of the needs of it. In this paper, we investigated and analyzed the process of drug design and development within the healthcare industry, together with related work in using an enterprise architecture framework for the digital era named the Adaptive Integrated Digital Architecture Framework (AIDAF), specifically supporting the design of digital platforms there. Based on this analysis, we evaluate a method and propose a new reference architecture for promoting digital platforms in the healthcare industry, with future specific aspects of them making effective use of Artificial Intelligence (AI). The practical and theoretical contributions include: (1) Streamlined processes through digital platforms in organizations. (2) Informal knowledge supply and sharing among organizational members through digital platforms. (3) Efficiency and effectiveness in planning production and business for drug development. The findings indicate that EA with digital platforms using the AIDAF contribute to digital transformation with effectiveness for new drugs in the healthcare industry.
What might the attendee be able to do after being in your session?
Our work shows how to connect intra-operative devices via IEEE 11073 Service-oriented Device Connectivity (SDC).
Description of the Problem or Gap
Standardized device communication is essential for interoperability, availability of device data, and therefore for the intelligent operating room (OR) and arising solutions. The SDC standard was developed to make information from medical devices available in a uniform manner and enable interoperability. Existing devices are rarely SDC-capable and need interfaces to be interoperable via SDC.
Methods: What did you do to address the problem or gap?
We conceived an SDC-based architecture consisting of a service provider and service consumer. In our concept, the service provider is connected to the medical device and capable to translate the proprietary protocol of the device into SDC and vice versa. The service consumer is used to request or send information via the SDC protocol to the service provider and can function as a uniform bidirectional interface (e.g. for displaying or controlling). This concept was exemplarily demonstrated with the patient monitor MX800 of Philips to retrieve the device data (e.g. vital parameters) via SDC and partly for the operating light marLED X of KLS Martin Group.
Results: What was the outcome(s) of what you did to address the problem or gap?
The patient monitor MX800 was connected to a Raspberry Pi (RPi) via LAN, on which the service provider is running. The python script on the RPi establishes a connection to the monitor and translates incoming and outgoing messages from the proprietary protocol to SDC and vice versa to/from the service consumer. The service consumer is running on a laptop and acts as a simulation for different kinds of systems that want to get vital parameters or other information from the patient monitor. The operating light marLED X was connected to an RPi via USB-to-RS232. A python script on the RPi establishes a connection to the light and makes it possible via proprietary commands to get information of the light (e.g. status) and to control it (e.g. toggle the light, increment the intensity). A translation to SDC is not integrated yet.
Discussion of Results
Our practical implementation shows that medical devices can be accessed via external connections to get device data and control the device via commands. The example SDC implementation of the patient monitor MX800 makes it possible to request its data via the standardized communication protocol SDC. This is also possible for the operating light marLED X if its proprietary protocol is analyzed to be translatable to/from SDC. This would allow to control the device from an external system, or automatically depending on the status of the ongoing procedure. The advantage is, that existing intra-operative devices can be extended by a service provider which is capable of translating the proprietary protocol of the device in SDC and vice versa. This enables interoperability and an intelligent OR that, for example, is aware of all devices, their status, and data and can use this information to optimally support the surgeons and their team (e.g. provision of information, automated documentation). This interoperability allows that future innovations merely need to understand the SDC protocol instead of all vendor-dependent communication protocols.
Conclusion
Standardized device communication is essential to reach interoperability, and therefore intelligent ORs. Our contribution addresses the possibility of subsequently making medical devices SDC-capable. This may eliminate the need of understanding all the different proprietary protocols when developing new innovative solutions for the OR.
There are several intra-operative use cases which require the surgeon to interact with medical devices. I used the Leap Motion Controller as input device for three use-cases: 2D-interaction (e.g. advancing EPR data), selection of a value (e.g. room illumination brightness) and an application point and click scenario. I evaluated the Palm Mouse as the most suitable gesture solution to coordinate the mouse and advise to use the implementation using all fingers to perform a click. This small case study introduces the implementations and methods that result those recommendations.
There are several intra-operative use cases which require the surgeon to interact with medical devices. We used the Leap Motion Controller as input device and implemented two use-cases: 2D-Interaction (e.g. advancing EPR data) and selection of a value (e.g. room illumination brightness). The gesture detection was successful and we mapped its output to several devices and systems.
Ultra wideband real-time locating system for tracking people and devices in the operating room
(2022)
Position tracking within the OR could be one possible input for intraoperative situation recognition. Our approach demonstrates a Real-time Locating System (RTLS) using the Ultra Wideband (UWB) technology to determine the position of people or objects. The UWB RTLS was integrated into the research OR at Reutlingen University and the system’s settings were optimized regarding the four factors accuracy, susceptibility to interference, range, and latency. Therefore, different parameters were adapted and the effects on the factors were compared. Goodtracking quality could be achieved under optimal settings. These results indicate that a UWB RTLS is well suited to determine the position of people and devices in our setting. The feasibility of the system needsto be evaluated under real OR conditions.
Im Rahmen der wissenschaftlichen Vertieung werden unterschiedliche empirische Forschungsmethoden erörtert.
Im ersten Schritt werden die Grundlagen der empirischen Forschungsmethoden ermittelt und klassifiziert. Nach der Klassifikation der Forschungsmethoden werden zwei Forschunsmethoden angewandt. Die Auswahl der Methoden fällt auf die quantitative und qualitative Forschungsmethode.
Diese Forschungsmethoden werden während der Analysephase eingesetzt, um den weltweiten Ist-Zustand der Tochtergesellschaften zu ermitteln. Hierbei geht es um die Analyse des Import- und Export-Prozesses bei den Tochtergesellschaften der HUGO BOSS AG. Ziel ist es, die Ergebnisse für die Master Thesis einzusetzen. Anhand der Ergebnisse können Gemeinsamkeiten oder auch Abweichungen im Zollabwicklungsprozess aufgezeigt werden, die später in der Konzeption berücksichtigt werden.
Hierzu wird die qualitative Methode eingesetzt, welche die Basis für die Konzeptionierung der Umfrage liefert. Abschließend wurde für die Verifikation der Ergebnisse die qualitative Methode für die Interviews eingesetzt.
Intelligent Tutoring Systems (ITSs) are increasingly used in modern education to automatically give students individual feedback on their performance. The advantage for students is fast individual feedback on their answers to asked questions, while lecturers benefit from considerable time savings and easy delivery of educational material. Of course, it is important that the provided feedback is as effective as direct feedback from the lecturer. However, in digital teaching, lecturers cannot assess the student’s knowledge precisely but can only provide information on which questions were answered correctly and incorrectly. Therefore, this paper presents a concept for integrating ITS elements into the gamified e-learning platform IT-REX so that the feedback quality can be improved to support students in the best possible way.
Scheduled flexibility and individualization of knowledge transfer in foundations of computer science
(2017)
The opening of the German higher education system for new target groups involves a heterogeneous composition of students as never before and face up the universities to new challenges. Due to different educational biographies, the students don't show a homogeneous level of knowledge. Furthermore, their access to course content and their individual learning methods are very diverse. The existing lack of knowledge and the very unequal study speed have a significant influence on the learning behavior and learning motivation. During the first semesters, the dropout rate is appreciably higher. The reform project gives an overview of a didactic restructuring from a formerly conventional teaching and learning concept to a stronger combination of digital offers, combined with classical lectures in the basic modules of computer science. The teaching content is adjusted to the individual requirements and knowledge. Students with different previous knowledge get the possibility to increase their knowledge in different levels of abstraction. The aim of the reform project has to point out the possibilities, also the challenges of the digital process in higher education. At the same time the question has to be explored, how far does an accompanied and self-directed learning in own speed and in own individual depth of knowledge have a positive impact on the motivation and on the study success of a learner.
The increasing heterogenecity of students at German Universities of Applied Sciences and the growing importance of digitization call for a rethinking of teaching and learning within higher education. In the next years, changing the learning ecosystem by developing and reflecting upon new teaching and learning techniques using methods of digitalization will be both - most relevant and very challenging. The following article introduces two different learning scenarios, which exemplify the implementation of new educational models that allow discontinuity of time and place, technology and process in teaching and learning. Within a blended learning apporach, the first learning scenario aims at adapting and individualizing the knowledge transfer in the course Foundations of Computer Science by providing knowledge individually and situation-specifically. The second learning scenario proposes a web-based tool to facilitate digital learning environments and thus digital learning communities and the possibility of computer-supported learning. The overall aim of both learning scenarios is to enhance learning for diverse groups by providing a different smart learning ecosystem in stepping away from a teacher-based to a student-centered approach. Both learning scenarios exemplarily represent the educational vision of Reutlingen University - its development into an interactive university.
Ziel der wissenschaftlichen Vertiefung ist es, ein Konzept einer Benutzeroberfläche für ein Fahrassistenzsystem zu entwickeln und zu evaluieren. Das Fahrassistensystem soll dem Fahrer dabei helfen, sicher und energieeffizient zu fahren. Aufgabe ist es, ein Darstellungskonzept zu erstellen und zu evaluieren. Dabei sind die besonderen Anforderungen an Sekundärinteraktionen im Fahrzeug zu berücksichtigen. Ziel der konzeptionellen Phase ist es, eine möglichst ablenkungsfreihe Darstellung zu entwickeln. Dazu werden Normen, Guidelines und Standards der In-Car Interaction zusammenfassend beschrieben und angewendet. Ergebnis ist ein modular umsetzbares Darstellungskonzept, dessen Ablenkungsfreiheit durch einen Lane- Change-Test evaluiert wird.
Unter dem Begriff Innovation Enabling wird im Folgenden ein Konzept für die ganzheitliche Unterstützung interdisziplinärer Teams beim kreativen und innovativen Problemlösen vor-gestellt. Dieses Konzept unterstützt Moderatoren und Teilnehmergleichermaßen und ein damit realisiertes System bleibt durch die implizite Interaktion für den Nutzer im Hintergrund. Eine zentrale Rolle spielt das Konzept der Awareness Pipeline zur Implementation einer impliziten Interaktion auf Basis eines Sensor-Aktor-Systems, welches in diesem Artikel vorgestellt wird. Die Unterstützung der begleitenden Moderations- und Administrationsaufgaben, wie beispielsweise der automatisierten Dokumentation der Sitzung, sollen in Zukunft einen deutlichen Mehrwert gegenüber einer klassischen Brainstorming-Sitzung bieten.
The livestock sector is growing steadily and is responsible for around 18% of global greenhouse‐gas‐emissions, which is more than the global transport sec-tor (Steinfeld et al. 2006). This paper examines the potential of social marketing to reduce meat consumption. The aim is to understand consumers’ motivation in diet choices and to learn what opportunities social marketing can provide to counteract negative environmental and health trends. The authors believe that research to answer this question should start in metropolitan areas, be-cause measures should be especially effective there. Based on the Theory of Planned Behaviour (TPB, Ajzen 1991) and the Technology‐Acceptance‐Model by Huijts et al. (2012), an online‐study with participants from the metropolitan region (n = 708) was conducted in which central socio‐psychological constructs for a meat consumption reduction were examined. It was shown that attitude, personal norm and habit have a critical influence on the intention to reduce meat consumption. A segmentation of consumers based on these factors led to three consumer clusters: vegetarians/flexitarians, potential flexitarians and convinced meat eaters. Potential flexitarians are an especially relevant target group for the development of social‐marketing‐measures to reduce meat consumption. In co‐creation‐workshops with potential flexitarians from the metropolitan region, barriers and benefits of reducing meat consumption were identified. The factors of environmental protection, animal welfare and desire for variety turn out to be the most relevant motivational factors. Based on these factors, consumers proposed a variety of social marketing measures, such as applications and labels to inform about the environmental impact of meat products.
The energy sector in Germany, as in many other countries, is undergoing a major transformation. To achieve the climate targets, numerous measures to implement smart energy and resource efficiency are necessary. Therefore, energy companies are experiencing increasing pressure from politics and society to transform their business areas in a sustainable manner and implement smart and sustainable business models. Consequently, numerous resources are expected to flow into the development and implementation of new business models. But often these efforts remain unsuccessful in practice. There is a large amount of literature on barriers and drivers of smart and sustainable business models in the energy sector. But what are the factors that companies struggle with most when developing and implementing new business models in practice? To answer this question, the results of a systematic literature review were evaluated by conducting semi-structured interviews with experts of the German energy sector. Six categories of transformation barriers were identified: Organizational, Financial, Legal, Partner-Network, Societal and Technological barriers. To overcome these barriers, recommendations for action and key success factors are outlined by the experts interviewed. The interview study validates key barriers and drivers in terms of their significance in practice in the German energy sector and makes recommendations to advance the smart and sustainable transformation of the energy sector.
This is a report from a one-day fourth international workshop on "Information Systems in Distributed Environments" (ISDE), which was organized in conjunction with the OnTheMove Federated Conferences & Workshops (OTM 2014) October 29-30, 2014, Amantea, Calabria, Italy. The main focus of this event was to provide a venue for the discussion of challenges related to the development, operation, and maintenance of distributed information systems, and their creation in the context of global development projects. Further dissemination of research results will lead to an improvement of distributed information system development and deployment across the globe.
The implementation of a web based portal QA solution will lead to a high acceptance of the staff as the usage of commonly known standard software (e.g. web browser) allows intuitive handling. In the daily use a significant simplification of the workflow and Performance enhancement can be achieved by easy access to the check documents. As the data is now saved in a database it can easily be processed and long-term trends can be displayed. Therefore possible errors can be detected much easier and earlier. By the usage of time stamps and user authentication procedures and user responsibilities are comprehensibly documented. As the software is browser based, integration into an existing software Environment is not critical. As only technical QA data is processed, no further data security measures are necessary. A certification as a medical product is not required.
The business landscape is changing radically because of software. Companies in all industry sectors are continously finding new flexibilities in this programmable world. They are able to deliver new functionalities even after the product is already in the customer's hands. But success is far from guaranteed if they cannot validate their assumptions about what their customers actually need. A competitor with better knowledge of customer needs can disrupt the market in an instant.
This book introduces continuous experimentation, an approach to continuously and systematically test assumptions about the company's product or service strategy and verify customers' needs through experiments. By observing how customers actually use the product or early versions of it, companies can make better development decisions and avoid potentially expensive and wasteful activities. The book explains the cycle of continuous experimentation, demonstrates its use through industry cases, provides advice on how to conduct experiments with recipes, tools, and models, and lists some common pitfalls to avoid. Use it to get started with continuous experimentation and make better product and service development decisions that are in-line with your customers' needs.
Digital twins deployed in production are important in practice and interesting for research. Currently, mostly structured data coming from e.g., sensors and timestamps of related stations, are integrated into Digital Twins. However, semi- and unstructured data are also important to display the current status of a digital twin (e.g., of a machinery or produced good). Process Mining and Text Mining in combination can be used to support the use of log file data to understand the current state of the process as well as highlight issues. Therefore, issue related reactions can be taken more quickly, targeted and cost oriented. Applying a design science research approach; here a prototype as an artefact based on derived requirements is developed. This prototype helps to understand and to clarify the possibilities of Process Mining and Text Mining based on log data for production related Digital Twins. Contributions for practice and research are described. Furthermore, limitations of the research and future opportunities are pointed out.
Digitalization and enterprise architecture management: a perspective on benefits and challenges
(2023)
Many companies digitally transform their business models, processes, and services. They have also been using Enterprise Architecture Management approaches for a long time to synchronize corporate strategy and information technology. Such digitalization projects bring different challenges for Enterprise Architecture Management. Without understanding and addressing them, Enterprise Architecture Management projects will fail or not deliver the expected value. Since existing research has not yet addressed these challenges, they were investigated based on a qualitative expert study with leading industry experts from Europe. Furthermore, potential benefits of digitalization projects for Enterprise Architecture Management were researched. Our results provide a theoretical framework consisting of five identified challenges, triggers and a number of benefits. Furthermore, we discuss in what ways digitalization and EAM is a promising topic for future research.
Data analysis is becoming increasingly important to pursue organizational goals, especially in the context of Industry 4.0, where a wide variety of data is available. Here numerous challenges arise, especially when using unstructured data. However, this subject has not been focused by research so far. This research paper addresses this gap, which is interesting for science and practice as well. In a study three major challenges of using unstructured data has been identified: analytical know-how, data issues, variety. Additionally, measures how to improve the analysis of unstructured data in the industry 4.0 context are described. Therefore, the paper provides empirical insights about challenges and potential measures when analyzing unstructured data. The findings are presented in a framework, too. Hence, next steps of the research project and future research points become apparent.
Revenue management information systems are very important in the hospitality sector. Revenue decisions can be better prepared based on different information from different information systems and decision strategies. There is a lack of research about the usage of such systems in small and medium-sized hotels and architectural configurations. Our paper empirically shows the current development of revenue information systems. Furthermore, we define future developments and requirements to improve such systems and the architectural base.
New business concepts such as Enterprise 2.0 foster the use of social software in enterprises. Especially social production significantly increases the amount of data in the context of business processes. Unfortunately, these data are still an unearthed treasure in many enterprises. Due to advances in data processing such as Big Data, the exploitation of context data becomes feasible. To provide a foundation for the methodical exploitation of context data, this paper introduces a classification, based on two classes, intrinsic and extrinsic data.
Predictive maintenance information systems: the underlying conditions and technological aspects
(2020)
Predictive maintenance has the potential to improve the reliability of production and service provisioning. However, there is little knowledge about the proper implementation of predictive maintenance in research and practice. Therefore, we conducted a multi-case study and investigated underlying conditions and technological aspects for implementing a predictive maintenance system and where it leads to. We found that predictive maintenance initiatives are triggered by severe impacts of failures on revenue and profit. Furthermore, successful predictive maintenance initiatives require that pre-conditions are fulfilled: Data must be available and accessible. Very important is also the support by the management. We identified four factors important for the implementation of predictive maintenance. The integration of data is highly facilitated by Cloud-based mechanisms. The detection of events is enabled by advanced analytics. The execution of predictive maintenance operations is supported by data-driven process automation and visualization.
We introduce bloomRF as a unified method for approximate membership testing that supports both point- and range-queries. As a first core idea, bloomRF introduces novel prefix hashing to efficiently encode range information in the hash-code of the key itself. As a second key concept, bloomRF proposes novel piecewisemonotone hash-functions that preserve local order and support fast range-lookups with fewer memory accesses. bloomRF has near-optimal space complexity and constant query complexity. Although, bloomRF is designed for integer domains, it supports floating-points, and can serve as a multi-attribute filter. The evaluation in RocksDB and in a standalone library shows that it is more efficient and outperforms existing point-range-filters by up to 4× across a range of settings and distributions, while keeping the false-positive rate low.
In this note we look at anisotropic approximation of smooth functions on bounded domains with tensor product splines. The main idea is to extend such functions and then use known approximation techniques on Rd. We prove an error estimate for domains for which bounded extension operators exist. This obvious approach has some limitations. It is not applicable without restrictions on the chosen coordinate degree even if the domain is as simple as the unit disk. Further for approximation on Rd there are error estimates in which the grid widths and directional derivatives are paired in an interesting way. It seems impossible to maintain this property using extension operators.
Automatisierte Analyse von Review-Daten beschäftigt sich mit den Möglichkeiten, freien Text zu analysieren und relevante Informationen daraus zu extrahieren. Die Arbeit setzt sich dabei mit Methoden des unüberwachten Lernens auseinander. Hierbei steht die Methode der Topic Modellierung im Mittelpunkt. Es werden Verfahren betrachtet, die im Bereich der textbasierten Informationsgewinnung bekannt sind. Latent Semantic Indexing LSI, (probabilistic) pLSI und Latent Dirichlet Allocation (LDA) werden erläutert und verglichen. Die Arbeit zeigt, wie LDA genutzt wurde, um einen nhaltlichen Überblick über einen Datenkorpus von 1 Mio. Reviews zu bekommen und diesen auf einen feineren Detailgrad zu betrachten. Die Topic-basierte Analyse wird genutzt, um Erkentnisse für ein Opinion Mining System zu generieren, welches eine tiefergehende Analyse vornehmen wird. Der gesamte Prozess ist als vollständig automatisiert und maschinell unüberwacht konzeptioniert.
The troubles began when Tom, the business analyst, asked the customer what he wants. The customer came up with good ideas for software features. Tom created a brilliant roadmap and defined the requirements for a new software product. Mary, the development team leader, was already eager to start developing and happy when she got the requirements. She and her team went ahead and created the software right away. Afterwards, Paul tested the software against the requirements. As soon as the software fulfilled the requirements, Linda, the product manager, deployed it to the customer. The customer did not like the software and ignored it. Ringo, the head of software development, was fired. How come? Nowadays, we have tremendous capabilities for creating nearly all kinds of software to fulfill the needs of customers. We can apply agile practices for reacting flexibly to changing requirements, we can use distributed development, open source, or other means for creating software at low cost, we can use cloud technologies for deploying software rapidly, and we can get enormous amounts of data showing us how customers actually use software products. However, the sad reality is that around 90% of products fail, and more than 60% of the features of a typical software product are rarely or never used. But there is a silver lining – an insight regarding successful features: Around 60% of the successes stem from a significant change of an initial idea. This gives us a hint on how to build the right software for users and customers.
Due to rapidly changing technologies and business contexts, many products and services are developed under high uncertainties. It is often impossible to predict customer behaviors and outcomes upfront. Therefore, product and service developers must continuously find out what customers want, requiring a more experimental mode of management and appropriate support for continuously conducting experiments. We have analytically derived an initial model for continuous experimentation from prior work and matched it against empirical case study findings from two startup companies. We examined the preconditions for setting up an experimentation system for continuous customer experiments. The resulting RIGHT model for Continuous Experimentation (Rapid Iterative value creation Gained through High-frequency Testing) illustrates the building blocks required for such a system and the necessary infrastructure. The major findings are that a suitable experimentation system requires the ability to design, manage, and conduct experiments, create so-called minimum viable products or features, link experiment results with a product roadmap, and manage a flexible business strategy. The main challenges are proper, rapid design of experiments, advanced instrumentation of software to collect, analyse, and store relevant data, and integration of experiment results in the product development cycle, software development process, and business strategy. This summary refers to the article The RIGHT Model for Continuous Experimentation, published in the Journal of Systems and Software [Fa17].
Product roadmaps are an important tool in product development. They provide direction, enable consistent development in relation to a product vision and support communication with relevant stakeholders. There are many different formats for product roadmaps, but they are often based on the assumption that the future is highly predictable. However, especially software-intensive businesses are faced with increasing market dynamics, rapidly evolving technologies and changing user expectations. As a result, many organizations are wondering what roadmap format is appropriate for them and what components it should have to deal with an unpredictable future. Objectives: To gain a better understanding of the formats of product roadmaps and their components, this paper aims to identify suitable formats for the development and handling of product roadmaps in dynamic and uncertain markets. Method: We performed a grey literature review (GLR) according to the guidelines from Garousi. Results: A Google search identified 426 articles, 25 of which were included in this study. First, various components of the roadmap were identified, especially the product vision, themes, goals, outcomes and outputs. In addition, various product roadmap formats were discovered, such as feature-based, goal-oriented, outcome-driven and a theme-based roadmap. The roadmap components were then assigned to the various product roadmap formats. This overview aims at providing initial decision support for companies to select a suitable product roadmap format and adapt it to their own needs.
In recent years companies have faced challenges by high market dynamics, rapidly evolving technologies and shifting user expectations. Together with the adaption of lean and agile practices, it is increasingly difficult to predict upfront which products, features or services will satisfy the needs of the customers and the organization. Currently, many new products fail to produce a significant financial return. One reason is that companies are not doing enough product discovery activities. Product discovery aims at tackling the various risks before the implementation of a product starts. The academic literature only provides little guidance for conducting product discovery in practice. Objective: In order to gain a better understanding of product discovery activities in practice, this paper aims at identifying motivations, approaches, challenges, risks, and pitfalls of product discovery reported in the grey literature. Method: We performed a grey literature review (GLR) according to the guidelines to Garousi et al. Results: The study shows that the main motivation for conducting product discovery activities is to reduce the uncertainty to a level that makes it possible to start building a solution that provides value for the customers and the business. Several product discovery approaches are reported in the grey literature which include different phases such as alignment, problem exploration, ideation, and validation. Main challenges are, among others, the lack of clarity of the problem to be solved, the prescription of concrete solutions through management or experts, and the lack of cross-functional collaboration.
Objective: This paper aims at getting an understanding of current problems and challenges with roadmapping processes in companies that are facing volatile markets with innovative products. It also aims at gathering ideas and attempts on how to react to those challenges.
Method: As an initial step towards the objectice a semi-structured expert interview study with a case company in the Smart Home domain was conducted. Four employees from the case company with different roles around product roadmaps have been interviewed and a content analysis of the data has been performed.
Results: The study shows a significant consensus among the interviewees about several major challenges and the necessity to change the traditional roadmapping process and format. The interviewees stated that based on their experience traditional feature-based product roadmaps are increasingly losing their benefits (such as good planning certainty) in volatile environments. Furthermore, the ability to understand customer needs and behaviors has become highly important for creating and adjusting product roadmaps. The interviewees see the need for both, sufficiently stable goals on the roadmap and flexibility with respect to products or features to be developed. To reach this target the interviewees proposed to create roadmaps based on outcome goals instead of product features. In addition, it was proposed to decrease the level of detail of the roadmaps and to emphasize the long-term view. Decisions about which feature to develop should be open as long as possible. Expected benefits of such a new way of product roadmapping are higher user centricity, a stable overall direction, more flexibility with respect to development decisions, and less breaking of commitments.
Context: Companies in highly dynamic markets increasingly struggle with their ability to plan product development and to create reliable roadmaps. A main reason is the decreasing lack of predictability of markets, technologies, and customer behaviors. New approaches for product roadmapping seem to be necessary in order to cope with today's highly dynamic conditions. Little research is available with respect to such new approaches. Objective: In order to better understand the state of the art and to identify research gaps, this article presents a review of the scientific literature with respect to product roadmapping. Method: We performed a systematic literature review (SLR) with respect to identify papers in the field of computer science. Results: After filtering, the search resulted in a set of 23 relevant papers. The identified papers focus on different aspects such as roadmap types, processes for creating and updating roadmaps, problems and challenges with roadmapping, approaches to visualize roadmaps, generic frameworks and specific aspects such as the combination of roadmaps with business modeling. Overall, the scientific literature covers many important aspects of roadmapping but does provide only little knowledge on how to create product roadmaps under highly dynamic conditions. Research gaps address, for instance, the inclusion of goals or outcomes into product roadmaps, the alignment of a roadmap with a product vision, and the inclusion of product discovery activities in product roadmaps. In addition, the transformation from traditional roadmapping processes to new ways of roadmapping is not sufficiently addressed in the scientific literature.
Context: Organizations are increasingly challenged by dynamic and technical market environments. Traditional product roadmapping practices such as detailed and fixed long-term planning typically fail in such environments. Therefore, companies are actively seeking ways to improve their product roadmapping approach. Goal: This paper aims at identifying problems and challenges with respect to product roadmapping. In addition, it aims at understanding how companies succeed in improving their roadmapping practices in their respective company contexts. The study focuses on mid-sized and large companies developing software-intensive products in dynamic and technical market environments. Method: We conducted semi structured expert interviews with 15 experts from 13 German companies and conducted a thematic data analysis. Results: The analysis showed that a significant number of companies is still struggling with traditional feature based product-roadmapping and opinion based prioritization of features. The most promising areas for improvement are stating the outcomes a company is trying to achieve and making them part of the roadmap, sharing or co-developing the roadmap with stakeholders, and the establishing discovery activities.
Through increasing market dynamics, rapidly evolving technologies and shifting user expectations coupled with the adoption of lean and agile practices, companies are struggling with their ability to provide reliable product roadmaps by applying traditional approaches. Currently, most companies are seeking opportunities to improve their product roadmapping practices. As a first challenge they have to assess their current product roadmapping capabilities in order to better understand how to improve their practices and how to switch to a new approach. The aim of this article is to provide an initial maturity model for product roadmapping practices that is especially suited for assessing the roadmapping capabilities of companies operating in dynamic and uncertain market environments. Based on interviews with 15 experts from 13 various companies the current state of practice regarding product roadmapping was identified. Afterwards, the model development was conducted in the context of expert workshops with the Robert Bosch GmbH and researchers. The study results in the so-called DEEP 1.0 product roadmap maturity model which allows companies to conduct a self assessment of their product roadmapping practice.
Context: Organizations are increasingly challenged by high market dynamics, rapidly evolving technologies and shifting user expectations. In consequence, many organizations are struggling with their ability to provide reliable product roadmaps by applying traditional roadmapping approaches. Currently, many companies are seeking opportunities to improve their product roadmapping practices and strive for new roadmapping approaches. A typical first step towards advancing the roadmapping capabilities of an organization is to assess the current situation. Therefore, the so-called maturity model DEEP for assessing the product roadmapping capabilities of companies operating in dynamic and uncertain environments has been developed and published by the authors.
Objective: The aim of this article is to conduct an initial validation of the DEEP model in order to understand its applicability better and to see if important concepts are missing. In addition, the aim of this article is to evolve the model based on the findings from the initial validation.
Method: The model has been given to practitioners such as product managers with the request to perform a self-assessment of the current product roadmapping practices in their company. Afterwards, interviews with each participant have been conducted in order to gain insights.
Results: The initial validation revealed that some of the stages of the model need to be rearranged and minor usability issues were found. The overall structure of the model was well received. The study resulted in the development of the version 1.1 of the DEEP product roadmap maturity model which is also presented in this article.
Context: Organizations are increasingly challenged by dynamic and technical market environments. Traditional product roadmapping practices such as detailed and fixed long-term planning typically fail in such environments. Therefore, companies are actively seeking ways to improve their product roadmapping approach.
Goal: This paper aims at identifying problems and challenges with respect to product roadmapping. In addition, it aims at understanding how companies succeed in improving their roadmapping practices in their respective company contexts.
Method: We conducted semi-structured expert interviews with 15 experts from 13 German companies and conducted athematic data analysis.
Results: The analysis showed that a significant number of companies is still struggling with traditional feature-based product-roadmapping and opinion-based prioritization of features. The most promising areas for improvement are stating the outcomes a company is trying to achieve and making them part of the roadmap, sharing or co-developing the roadmap with stakeholders, and establishing discovery activities.
Workshops and tutorials
(2018)
The 19th International Conference on Product-Focused Software Process Improvement (PROFES 2018) hosted two workshops and three tutorials. The workshops and tutorials complemented and enhanced the main conference program, offering a wider knowledge perspective around the conference topics. The topics of the two workshops were Hybrid Development Approaches in Software Systems Development (HELENA) and Managing Quality in Agile & Rapid Software Development Processes (QUaSD). The topics of the tutorials were The human factor in agile transitions – using the personas concept in agile oaching, Process Management 4.0 – Best Practices, and Domain-specific languages for specification, development, and testing of autonomous systems.
The use of Wireless Sensor and Actuator Networks (WSAN) as an enabling technology for Cyber-Physical Systems has increased significantly in recent past. The challenges that arise in different application areas of Cyber- Physical Systems, in general, and in WSAN in particular, are getting the attention of academia and industry both. Since reliability issues for message delivery in wireless communication are of critical importance for certain safety related applications, it is one of the areas that has received significant focus in the research community. Additionally, the diverse needs of different applications put different demands on the lower layers in the protocol stack, thus necessitating such mechanisms in place in the lower layers which enable them to dynamically adapt. Another major issue in the realization of networked wirelessly communicating cyber-physical systems, in general, and WSAN, in particular, is the lack of approaches that tackle the reliability, configurability and application awareness issues together. One could consider tackling these issues in isolation. However, the interplay between these issues create such challenges that make the application developers spend more time on meeting these challenges, and that too not in very optimal ways, than spending their time on solving the problems related to the application being developed. Starting from some fundamental concepts, general issues and problems in cyber-physical systems, this chapter discusses such issues like energy-efficiency, application and channel-awareness for networked wirelessly communicating cyber-physical systems. Additionally, the chapter describes a middleware approach called CEACH, which is an acronym for Configurable, Energy-efficient, Application- and Channel-aware Clustering based middleware service for cyber-physical systems. The state of-the art in the area of cyberphysical systems with a special focus on communication reliability, configurability, application- and channel-awareness is described in the chapter. The chapter also describes how these features have been considered in the CEACH approach. Important node level and network level characteristics and their significance vis-àvis the design of applications for cyber physical systems is also discussed. The issue of adaptively controlling the impact of these factors vis-à-vis the application demands and network conditions is also discussed. The chapter also includes a description of Fuzzy-CEACH which is an extension of CEACH middleware service and which uses fuzzy logic principles. The fuzzy descriptors used in different stages of Fuzzy-CEACH have also been described. The fuzzy inference engine used in the Fuzzy-CEACH cluster head election process is described in detail. The Rule-Bases used by fuzzy inference engine in different stages of Fuzzy-CEACH is also included to show an insightful description of the protocol. The chapter also discusses in detail the experimental results validating the authenticity of the presented concepts in the CEACH approach. The applicability of the CEACH middleware service in different application scenarios in the domain of cyberphysical systems is also discussed. The chapter concludes by shedding light on the Publish-Subscribe mechanisms in distributed event-based systems and showing how they can make use of the CEACH middleware to reliably communicate detected events to the event-consumers or the actuators if the WSAN is modeled as a distributed event-based system.
Redirected walking techniques allow people to walk in a larger virtual space than the physical extents of the laboratory. We describe two experiments conducted to investigate human sensitivity to walking on a curved path and to validate a new redirected walking technique. In a psychophysical experiment, we found that sensitivity to walking on a curved path was significantly lower for slower walking speeds (radius of 10 meters versus 22 meters). In an applied study, we investigated the influence of a velocity-dependent dynamic gain controller and an avatar controller on the average distance that participants were able to freely walk before needing to be reoriented. The mean walked distance was significantly greater in the dynamic gain controller condition, as compared to the static controller (22 meters versus 15 meters). Our results demonstrate that perceptually motivated dynamic redirected walking techniques, in combination with reorientation techniques, allow for unaided exploration of a large virtual city model.
In this paper a method for the generation of gSPM with ontology-based generalization was presented. The resulting gSPM was modeled with BPMN/BPMNsix in an efficient way and could be executed with BPMN workflow engines. In the next step the implementation of resource concepts, anatomical structures, and transition probabilities for workflow execution will be realized.
Preface of IDEA 2015
(2016)
The present work proposes the use of modern ICT technologies such as smartphones, NFCs, internet, and web technologies, to help patients in carrying out their therapies. The implemented system provides a calendar with a reminder of the assumptions, ensures the drug identification through NFC, allows remote assistance from healthcare staff and family members to check and manage the therapy in real-time. The system also provides centralized information on the patient's therapeutic situation, helpful in choosing new compatible therapies.
Preliminary results of homomorphic deconvolution application to surface EMG signals during walking
(2021)
Homomorphic deconvolution is applied to sEMG signals recorded during walking. Gastrocnemius lateralis and tibialis anterior signals were acquired according to SENIAM recommendation. MUAP parameters like amplitude and scale were estimated, whilst the MUAP shape parameter was fixed. This features a useful time-frequency representation of sEMG signal. Estimation of scale MUAP parameter was verified extracting the mean frequency of filtered EMG signal, extracted from the scale parameter estimated with two different MUAP shape values.
Artefaktkorrektur und verfeinerte Metriken für ein EEG-basiertes System zur Müdigkeitserkennung
(2019)
Fragestellung: Müdigkeit ist ein oft unterschätztes, aber dennoch großes Problem im Straßenverkehr. Von rund 2,5 Mio. Verkehrsunfällen 2015 in Deutschland, waren 2898 Unfälle, mit insgesamt 59 Toten (~1,7 % der Todesfälle), auf Übermüdung zurückzuführen. Schätzungen gehen von einer Dunkelziffer von bis zu 20 % aus. In einer ersten eigenen Studie wurde überprüft, ob ein mobiles EEG in einem Fahrsimulator Müdigkeitszustände zuverlässig erkennen kann. Die Erkennungsrate lag lediglich bei 61 %. Ziel dieser Arbeit ist, das verwendete Messsystem zu verbessern. Dazu wird die Genauigkeit durch eine Artefaktkorrektur und mit Hilfe von verfeinerten Qualitätsmetriken erhöht. Eine erkannte Übermüdung wird dem Fahrer dann in angemessener Weise angezeigt, so dass er entsprechend reagieren kann.
Patienten und Methoden: Die Independent Component Analysis (ICA) ist ein multivariates Verfahren, um mehrere Zufallsvariablen zu analysieren. Für die Entscheidung, ob ein Fahrer gerade müde oder wach ist, wird der erstellte Merkmalsvektor für jede Sequenz mit ICA klassifiziert. Dafür wird ein trainierter Machine-Learning-Algorithmus eingesetzt, der in der Lage ist, auch unbekannte Datensätze in Klassen einzuteilen. Um die benötigten Frequenzwerte zu erhalten, wurde für jeden EEG-Kanal eine Fourier Transformation durchgeführt. Der erstellte Merkmalsvektor wird im nächsten Schritt durch ein Künstliches Neuronales Netz klassifiziert. Für das Training werden vorab erstellte Merkmalsvektoren mit den Klassen „Wach“ und „Müde“ versehen. Diese Daten werden zufällig gemischt und im Verhältnis 2:1 in eine Trainings- und Testmenge geteilt. Das Experiment wurde mit acht Personen mit jeweils zweimal 45 min Testfahrt durchgeführt.
Ergebnisse: Der komplette Datensatz besteht aus 150.000 Signalwerten, welche zu ca. 7000 Sequenzen zusammengefasst werden. Durch die Anwendung der Qualitätsmetrik bleiben 4370 Sequenzen für das Training übrig. Bei invaliden Sequenzen aufgrund von EEG-Artefakten gibt es deutliche Unterschiede. Im „Wach“ Zustand werden dreimal so viele Sequenzen verworfen als im „Müde“ Zustand. Insgesamt werden bei wachen Probanden im Schnitt ca. 50 % der Sequenzen verworfen, bei Müden lediglich 25 %. Im Durchschnitt erreicht das System eine Erkennungsrate von 73 % für beide Zustände. Vergleicht man nun das Verhältnis von „Wach“ und „Müde“ und lässt „Leichte Müdigkeit“ außen vor, liegen die Ergebnisse bei über 90 %.
Schlussfolgerungen: Die Ergebnisse zeigen, dass die Aufmerksamkeit während des Experiments abnimmt bzw. die Müdigkeit zunimmt. Dies verdeutlichen zum einen subjektive und objektive Beobachtungen von Müdigkeitsanzeichen. Zum anderen lassen sich messbare und klassifizierbare Unterschiede im EEG Signal nachweisen. Die als Merkmale eingesetzten Theta-Wellen zeigten eine niedrigere Amplitude gegen Ende des Experiments. Die Erweiterung der binären Klassifizierung führt zu einer weiteren Stabilisierung der Ergebnisse. Artefaktkorrektur und Qualitätsmetriken steigern die Güte der Daten weiter. Die entwickelte Anwendung zur Müdigkeitserkennung ermittelt messbare Zeichen von Müdigkeit und kann eine gute Entscheidung über die Fahrtauglichkeit treffen.
There is a growing consensus in research and practice that value-creating networks and ecosystems are supplementing the traditional distinction between the internal firm and market perspectives. To achieve joint value in ecosystems, it is crucial to align the various interests of independently acting ecosystem actors and create a common vision. In this paper, we argue that the ecosystem-wide use of product roadmaps may help with this. To get a better understanding of how roadmapping is conducted in the dynamic ecosystem environment, we systematize the main characteristics of product roadmaps and perform a conceptual comparison with the known challenges of ecosystem management. Comparing the two concepts of ecosystems and product roadmaps, we highlight the fit between the characteristics and objectives of the roadmaps and the challenges of ecosystem management. Hence, we propose to experiment with the ecosystem-wide use of product roadmaps as well as the empirical study of the challenges emerging in the process and the associated redesign of the roadmaps.
In the present tutorial we perform a cross-cut analysis of database systems from the perspective of modern storage technology, namely Flash memory. We argue that neither the design of modern DBMS, nor the architecture of flash storage technologies are aligned with each other. The result is needlessly suboptimal DBMS performance and inefficient flash utilisation as well as low flash storage endurance and reliability. We showcase new DBMS approaches with improved algorithms and leaner architectures, designed to leverage the properties of modern storage technologies. We cover the area of transaction management and multi-versioning, putting a special emphasis on: (i) version organisation models and invalidation mechanisms in multi-versioning DBMS; (ii) Flash storage management especially on append-based storage in tuple granularity; (iii) Flash-friendly buffer management; as well as (iv) improvements in the searching and indexing models. Furthermore, we present our NoFTL approach to native Flash access that integrates parts of the flash-management functionality into the DBMS yielding significant performance increase and simplification of the I/O stack. In addition, we cover the basics of building large Flash storage for DBMS and revisit some of the RAID techniques and principles.
In the present tutorial we perform a cross-cut analysis of database storage management from the perspective of modern storage technologies. We argue that neither the design of modern DBMS, nor the architecture of modern storage technologies are aligned with each other. Moreover, the majority of the systems rely on a complex multi-layer and compatibility oriented storage stack. The result is needlessly suboptimal DBMS performance, inefficient utilization, or significant write amplification due to outdated abstractions and interfaces. In the present tutorial we focus on the concept of native storage, which is storage operated without intermediate abstraction layers over an open native storage interface and is directly controlled by the DBMS.
A transaction is a demarcated sequence of application operations, for which the following properties are guaranteed by the underlying transaction processing system (TPS): atomicity, consistency, isolation, and durability (ACID). Transactions are therefore a general abstraction, provided by TPS that simplifies application development by relieving transactional applications from the burden of concurrency and failure handling. Apart from the ACID properties, a TPS must guarantee high and robust performance (high transactional throughput and low response times), high reliability (no data loss, ability to recover last consistent state, fault tolerance), and high availability (infrequent outages, short recovery times).
The architectures and workhorse algorithms of a high-performance TPS are built around the properties of the underlying hardware. The introduction of nonvolatile memories (NVM) as novel storage technology opens an entire new problem space, with the need to revise aspects such as the virtual memory hierarchy, storage management and data placement, access paths, and indexing. NVM are also referred to as storage-class memory (SCM).
Active storage
(2018)
In brief, Active Storage refers to an architectural hardware and software paradigm, based on collocation storage and compute units. Ideally, it will allow to execute application-defined data ... within the physical data storage. Thus Active Storage seeks to minimize expensive data movement, improving performance, scalability, and resource efficiency. The effective use of Active Storage mandates new architectures, algorithms, interfaces, and development toolchains.
Neue Modelle für digitale Unternehmensarchitekturen mit Big Data, Services & Cloud Computing, mobilen Systemen, Internet of Things sowie Industrie 4.0 Ökosystemen machen eine enge Kooperation verschiedener Partner aus Wissenschaft, Anwendungsunternehmen, öffentlichen Organisationen, Softwarehersteller und IT- Dienstleister notwendig. Ziel dieser Zusammenarbeit ist die Zusammenführung neuer Konzepte und Möglichkeiten der Informationstechnologie zur bestmöglichen Unterstützung sich verändernder Unternehmensziele und -strategien. Software- und Unternehmensarchitekturen spielen hierbei eine zentrale Rolle. So werden Anforderungen bezüglich Flexibilität und Agilität in digitalen Unternehmen wesentlich durch serviceorientierte Ansätze unterstützt. Der Ordnungsgrad und die kosteneffiziente Gestaltung komplexer IT-Landschaften soll durch Digital Enterprise Architecture Management deutlich verbessert werden – passend zu neuen Möglichkeiten von Services & Cloud Computing, Big Data, sowie kollaborativen Geschäftsprozessen.
Non-fungible tokens (NFTs) are unique digital assets that have recently gained significant popularity, particularly in the digital art sector. The success of NFTs and other blockchain-based innovations depends on their ac-acceptance and use by consumers. This study aims to understand the impact of moral values on the acceptance of NFTs. Based on a quantitative survey with over 800 complete responses, the analysis shows that moral aspects of NFTs are indeed important for potential users. However, there is an attitude-behavior gap, as the positive impact of moral values on the intention to use NFTs is not reflected in the actual current usage of NFTs by the respondents. This study contributes to knowledge by providing new empirical data on the acceptance of NFTs and highlighting the role of moral values on the acceptance decision.
Avatars are in use when interacting in virtual environments in different contexts, in collaborative work, as well as in gaming and also in virtual meetings with friends. Therefore it is important to understand how the relationship between user and avatar works. In this study, an online survey is used to determine how the perception of an avatar changes in different contexts by relating it to existing avatar relationship typologies. Additionally, it is determined whether in each context a realistic, abstract or comic-like representation is preferred by the participants. One result was a preference of low poly representations in the work context, which are associated with the perception of the avatar as a tool. In the context of meeting friends, a realistic representation is perceived as more appropriate, which is perceived as an accurate self-representation. In the gaming context, the results are less clear, which can be attributed to different gaming preferences. Here, unlike in the other contexts, a comic-like representation is also perceived as appropriate, which is associated with the perception of the avatar as a friend. A symbiotic user-avatar relationship is not directly related to any form of representation, but always lies in the midfield, which is attributed to the fact that it represents a whole spectrum between other categories.
In den letzten Jahren beschäftigten sich Forscher und Automobilhersteller mit den Voraussetzungen für die Einführung von autonomem Fahren. Für Innovationen und Geschäftsmodelle im Bereich der intelligenten Mobilität, aber auch innerhalb der digitalen Wertschöpfungskette, spielen generell Zuverlässigkeit und Qualität der digitalen Datenübertragung eine entscheidende Rolle. Bevor das autonome Fahren vollständig eingeführt wird, muss man feststellen, welche Anforderungen an die digitale Infrastruktur beachtet werden müssen, gleichzeitig muss die Bedrohungslandschaft für autonomes Fahren analysiert werden.
Die folgende Arbeit beschäftigt sich damit, die Anforderungen und Gefahren zu analysieren und allgemeine Handlungsempfehlungen vorzuschlagen.
Hintergrund: Endoskopische Operationsverfahren haben sich als Goldstandard in der Nasennebenhöhlen-(NNH-)Chirurgie etabliert. Den sich daraus ergebenden Herausforderungen für die chirurgische Ausbildung kann durch den Einsatz von Virtuelle-Realität-(VR-)Trainingssimulatoren begegnet werden. Bislang wurde eine Reihe von Simulatoren für NNH-Operationen entwickelt. Frühere Studien im Hinblick auf den Trainingseffekt wurden jedoch nur mit medizinisch vorgebildeten Probanden durchgeführt oder es wurde nicht über dessen zeitlichen Verlauf berichtet.
Methoden: Ein NNH-CT-Datensatz wurde nach der Segmentierung in ein 3-dimensionales, polygonales Oberflächenmodell überführt und mithilfe von originalem Fotomaterial texturiert. Die Interaktion mit der virtuellen Umgebung erfolgte über ein haptisches Eingabegerät. Während der Simulation wurden die Parameter Eingriffsdauer und Fehleranzahl erfasst. Zehn Probanden absolvierten jeweils eine Trainingseinheit bestehend aus je 5 Übungsdurchläufen an 10 aufeinanderfolgenden Tagen.
Ergebnisse: Vier Probanden verringerten die benötigte Zeit um mehr als 60% im Verlauf des Übungszeitraums. Vier der Probanden verringerten ihre Fehleranzahl um mehr als 60%. Acht von 10 Probanden zeigten eine Verbesserung bezüglich beider Parameter. Im Median wurde im gesamten gemessenen Zeitraum die Dauer des Eingriffs um 46 Sekunden und die Fehleranzahl um 191 reduziert. Die Überprüfung eines Zusammenhangs zwischen den 2 Parametern ergab eine positive Korrelation.
Schlussfolgerung: Zusammenfassend lässt sich feststellen, dass das Training am NNH-Simulator auch bei unerfahrenen Personen die Performance beträchtlich verbessert, sowohl in Bezug auf die Dauer als auch auf die Genauigkeit des Eingriffs.
Purpose: This paper aims to conceptualize and empirically test the determinants of service interaction quality (SIQ) as attitude, behavior and expertise of a service provider (SP). Further, the individual and simultaneous effects of SIQ and its dimensions on important marketing outcomes are tested. Design/methodology/approach – The narrative review of extant research helps formulate a conceptual model of SIQ, which is investigated using the univariate and multivariate meta-analysis.
Findings: There are interdependencies between drivers of SIQ that underlines the need to conceptualize service interaction as a dyadic phenomenon; use contemporary multilevel models, dyadic models, non-linear structural equation modeling and process studies; and study new and diverse services contexts. Meta-analysis illustrates the relative importance of the three drivers of SIQ and, in turn, their impact on consumer satisfaction and loyalty.
Research limitations/implications – The meta-analysis is based on existing research, which, unfortunately, has not examined critical services or exigency situations where SIQ is of paramount importance. Future research will be tasked with diversifying to several important domains where SIQ is a critical aspect of perceived service quality.
Practical implications: This study emphasizes that, although the expertise of an SP is important, firms would be surprised to learn that the attitude and behavior of their employees are equally important antecedents. In fact, there is a delicate balance that needs to be found; otherwise, attitudinal factors can have an overall counterproductive effect on consumer satisfaction.
Originality/value: This paper provides an empirical synthesis of SIQ and opens up interesting areas for further research.
The potentials and opportunities created by digitized healthcare can be further customized through smart data processing and analysis using accurate patient information. This development and the associated new treatment concepts basing on digital smart sensors can lead to an increase in motivation by applying gamification approaches. This effect can also be used in the field of medical treatment, e.g. with the help of a digital spirometer combined with an app. In one of our exemplary applications, we show how to control an airplane within an app by breathing respectively inhaling and exhaling. Using this biofeedback within a game allows us to increase the motivation and fun for children that need to perform necessary exercises.
Die Wahrnehmung unermesslicher Weite kann Ehrfurcht beim Menschen auslösen. Dies kann positive Reaktionen im Menschen zur Folge haben. Während Ehrfurcht theoretisch und praktisch bereits gut erforscht ist, gibt es nur sehr wenig Forschung zum Thema der unermesslichen Weite. Dieses Wissen wäre nützlich, um gezielt Ehrfurcht beim Menschen auszulösen. Aus diesem Grunde wurde eine Studie durchgeführt, mit der festgestellt werden soll, in wie weit sich ein Gefühl unermesslicher Weite in virtueller Realität unter Verwendung eines Head-Mounted Displays erzeugen lässt und ob dadurch Ehrfurcht entsteht.
Pokémon Go was the first mobile augmented reality (AR) game to reach the top of the download charts of mobile applications. However, little is known about this new generation of mobile online AR games. Existing theories provide limited applicability for user understanding. Against this background, this research provides a comprehensive framework based on uses and gratification theory, technology risk research, and flow theory. The proposed framework aims to explain the drivers of attitudinal and intentional reactions, such as continuance in gaming or willingness to invest money in in-app purchases. A survey among 642 Pokémon Go players provides insights into the psychological drivers of mobile AR games. The results show that hedonic, emotional, and social benefits and social norms drive consumer reactions while physical risks (but not data privacy risks) hinder consumer reactions. However, the importance of these drivers differs depending on the form of user behavior.
Pokémon Go was the first mobile Augmented Reality (AR) game that made it to the top of the download charts of mobile applications. However, very little is known about this new generation of mobile online Augmented Reality (AR) games. Existing media usage and technology acceptance theories provide limited applicability to the understanding of its users. Against this background, this research provides a comprehensive framework that incorporates findings from uses & gratification theory (U>), technology acceptance and risk research as well as flow theory. The proposed framework aims at explaining the drivers of attitudinal and intentional reactions, such as continuance in gaming or willingness to conduct in-app purchases. A survey among 642 Pokémon Go players provides insights into the psychological drivers of mobile AR games. Results show that hedonic, emotional and social benefits, and social norms drive, vice versa physical risks (but not privacy risks) hinder consumer reactions. However, the importance of these drivers differs between different forms of user behavior.
Im Rahmen dieser Arbeit wurde ein urbaner Mixed-Reality Fahrsimulator umgesetzt. Die reale Umgebung wird hierbei in einer Greenscreen-Kammer mit Hilfe von Kamerabildern aus Nutzersicht und einem Chroma Key Shader innerhalb der virtuellen Umgebung sichtbar gemacht. Dies soll die Immersion und die Interaktivität innerhalb der virtuellen Umgebung durch die Darstellung und Verwendung von realen Elementen erhöhen.
Als virtuelle Umgebung wurde eine zufallsgenerierte Stadt geschaffen, in der KI-Fahrzeuge fahren. Die Ergebnisse der Entwicklung dieses Fahrsimulators werden in dieser Arbeit erläutert.
Der Fahrsimulator soll der Entwicklung von menschzentrierten Human-Machine-Interfaces und Motion-Capture-Komponenten dienen.
Hybrid project management is an approach that combines traditional and agile project management techniques. The goal is to benefit from the strengths of each approach, and, at the same time avoid the weaknesses. However, due to the variety of hybrid methodologies that have been presented in the meantime, it is not easy to understand the differences or similarities of the methodologies, as well as, the advantages or disadvantages of the hybrid approach in general. Additionally, there is only fragmented knowledge about prerequisites and success factors for successfully implementing hybrid project management in organizations. Hence, the aim of this study is to provide a structured overview of the current state of research regarding the topic. To address this aim, we have conducted a systematic literature review focusing on a set of specific research questions. As a result, four different hybrid methodologies are discussed, as well as, the definition, benefits, challenges, suitability and prerequisites of hybrid project management. Our study contributes to knowledge by synthesizing and structuring prior work in this growing area of research, which serves as a basis for purposeful and targeted research in the future.
In dieser Arbeit werden drei verschiedene Testumgebungen vorgestellt, welche in ein iteratives Vorgehen einfließen, um die Entwicklung von Augmented-Reality-Anwendungen zur Darstellung von autonomen Fahrfunktionen zu unterstützen.
Gestaltungsentwürfe und Softwareentwicklungen können in den Testumgebungen für unterschiedliche Zielsetzungen von Personenbefragungen vorgestellt und bewertet werden. Das entwicklungsbegleitende Testen ermöglicht eine frühzeitige Identifizierung von Änderungshinweisen, welche für einen gültigen Lösungsentwurf eingearbeitet werden können. Die entwickelten Testumgebungen sind ein verkleinertes Modell, ein Fahrsimulator und ein reales Fahrzeug. Eigenschaften, Funktionen und Aufbauten resultieren aus Erkenntnissen der Literatur und Erfahrungen aus ersten Entwicklungen. Diese und die Einsatzmöglichkeiten werden mit dieser Arbeit aufgezeigt.
Mammographie-Geräte werden in der Diagnostik von Mammakarzinomen eingesetzt. Die ursprüngliche Technik wurde in den letzten Jahren von analogen Röntgenfilmen zu digital integrierten Systemen weiterentwickelt. Durch die Tomosynthese, bei der in einem Schnittbildverfahren mehrere Schichten des Organismus untersucht werden können, können auch überlagerte Strukturen sichtbar gemacht werden. Um als adäquate Grundlage zur Diagnostik von malignen Tumoren dienen zu können, müssen einige qualitative Anforderungen erfüllt werden. Bisher gibt es wenig Literatur, die Anforderungen und den Aufbau solcher Geräte systematisch beschreiben. Im Rahmen dieser Arbeit werden auf Basis der Literatur und bestehender Systeme die qualitativen Anforderungen identifiziert. Der prinzipielle Aufbau solcher Systeme wird anhand der einzelnen Systembausteine in der semiformalen Notationssprache SysML gezeigt. Die grundlegende Funktionsweise eines tomosynthesefähigen Mammographie Gerätes wird in dieser Arbeit zusammenfassend und anhand der einzelnen Systembausteine beschrieben. Diese Arbeit dient der Vermittlung eines umfassenden Verständnisses für die digitale Mammographie, um als Grundlage für die Dokumentation von qualitativen Anforderungen dienen zu können.
Database management systems and K/V-Stores operate on updatable datasets – massively exceeding the size of available main memory. Tree-based K/V storage management structures became particularly popular in storage engines. B+ -Trees [1, 4] allow constant search performance, however write-heavy workloads yield in inefficient write patterns to secondary storage devices and poor performance characteristics. LSM-Trees [16, 23] overcome this issue by horizontal partitioning fractions of data – small enough to fully reside in main memory, but require frequent maintenance to sustain search performance.
Firstly, we propose Multi-Version Partitioned BTrees (MV-PBT) as sole storage and index management structure in key-sorted storage engines like K/V-Stores. Secondly, we compare MV-PBT against LSM-Trees. The logical horizontal partitioning in MV-PBT allows leveraging recent advances in modern B+ -Tree techniques in a small transparent and memory resident portion of the structure. Structural properties sustain steady read performance, yielding efficient write patterns and reducing write amplification.
We integrated MV-PBT in the WiredTiger [15] KV storage engine. MV-PBT offers an up to 2× increased steady throughput in comparison to LSM-Trees and several orders of magnitude in comparison to B+ -Trees in a YCSB [5] workload.
Modern mixed (HTAP)workloads execute fast update-transactions and long running analytical queries on the same dataset and system. In multi-version (MVCC) systems, such workloads result in many short-lived versions and long version-chains as well as in increased and frequent maintenance overhead.
Consequently, the index pressure increases significantly. Firstly, the frequent modifications cause frequent creation of new versions, yielding a surge in index maintenance overhead. Secondly and more importantly, index-scans incur extra I/O overhead to determine, which of the resulting tuple versions are visible to the executing transaction (visibility-check) as current designs only store version/timestamp information in the base table – not in the index. Such index-only visibility-check is critical for HTAP workloads on large datasets.
In this paper we propose the Multi Version Partitioned B-Tree (MV-PBT) as a version-aware index structure, supporting index-only visibility checks and flash-friendly I/O patterns. The experimental evaluation indicates a 2x improvement for analytical queries and 15% higher transactional throughput under HTAP workloads. MV-PBT offers 40% higher tx. throughput compared to WiredTiger’s LSM-Tree implementation under YCSB.
Blockchains yield to new workloads in database management systems and K/V-stores. Distributed Ledger Technology (DLT) is a technique for managing transactions in ’trustless’ distributed systems. Yet, clients of nodes in blockchain networks are backed by ’trustworthy’ K/V-Stores, like LevelDB or RocksDB in Ethereum, which are based on Log-Structured Merge Trees (LSM Trees). However, LSM-Trees do not fully match the properties of blockchains and enterprise workloads.
In this paper, we claim that Partitioned B-Trees (PBT) fit the properties of this DLT: uniformly distributed hash keys, immutability, consensus, invalid blocks, unspent and off-chain transactions, reorganization and data state / version ordering in a distributed log-structure. PBT can locate records of newly inserted key-value pairs, as well as data of unspent transactions, in separate partitions in main memory. Once several blocks acquire consensus, PBTs evict a whole partition, which becomes immutable, to secondary storage. This behavior minimizes write amplification and enables a beneficial sequential write pattern on modern hardware. Furthermore, DLT implicate some type of log-based versioning. PBTs can serve as MV-store for data storage of logical blocks and indexing in multi-version concurrency control (MVCC) transaction processing.
Characteristics of modern computing and storage technologies fundamentally differ from traditional hardware. There is a need to optimally leverage their performance, endurance and energy consumption characteristics. Therefore, existing architectures and algorithms in modern high performance database management systems have to be redesigned and advanced. Multi Version Concurrency Control (MVCC) approaches in data-base management systems maintain multiple physically independent tuple versions. Snapshot isolation approaches enable high parallelism and concurrency in workloads with almost serializable consistency level. Modern hardware technologies benefit from multi-version approaches. Indexing multi-version data on modern hardware is still an open research area. In this paper, we provide a survey of popular multi-version indexing approaches and an extended scope of high performance single-version approaches. An optimal multi-version index structure brings look-up efficiency of tuple versions, which are visible to transactions, and effort on index maintenance in balance for different workloads on modern hardware technologies.
Database management systems (DBMS) are critical performance components in large scale applications under modern update intensive workloads. Additional access paths accelerate look-up performance in DBMS for frequently queried attributes, but the required maintenance slows down update performance. The ubiquitous B+ tree is a commonly used key-indexed access path that is able to support many required functionalities with logarithmic access time to requested records. Modern processing and storage technologies and their characteristics require reconsideration of matured indexing approaches for today's workloads. Partitioned B-trees (PBT) leverage characteristics of modern hardware technologies and complex memory hierarchies as well as high update rates and changes in workloads by maintaining partitions within one single B+-Tree. This paper includes an experimental evaluation of PBTs optimized write pattern and performance improvements. With PBT transactional throughput under TPC-C increases 30%; PBT results in beneficial sequential write patterns even in presence of updates and maintenance operations.
Database Management Systems (DBMS) need to handle large updatable datasets in on-line transaction processing (OLTP) workloads. Most modern DBMS provide snapshots of data in multi-version concurrency control (MVCC) transaction management scheme. Each transaction operates on a snapshot of the database, which is calculated from a set of tuple versions. High parallelism and resource-efficient append-only data placement on secondary storage is enabled. One major issue in indexing tuple versions on modern hardware technologies is the high write amplification for tree-indexes.
Partitioned B-Trees (PBT) [5] is based on the structure of the ubiquitous B+ Tree [8]. They achieve a near optimal write amplification and beneficial sequential writes on secondary storage. Yet they have not been implemented in a MVCC enabled DBMS to date.
In this paper we present the implementation of PBTs in PostgreSQL extended with SIAS. Compared to PostgreSQL’s B+–Trees PBTs have 50% better transaction throughput under TPC-C and a 30% improvement to standard PostgreSQL with Heap-Only Tuples.
Delivering value to customers in real-time requires companies to utilize real-time deployment of software to expose features to users faster, and to shorten the feedback loop. This allows for faster reaction and helps to ensure that the development is focused on features providing real value. Continuous delivery is a development practice where the software functionality is deployed continuously to customer environment. Although this practice has been established in some domains such as B2C mobile software, the B2B domain imposes specific challenges. This article presents a case study that is conducted in a medium-sized software company operating in the B2B domain. The objective of this study is to analyze the challenges and benefits of continuous delivery in this domain. The results suggest that technical challenges are only one part of the challenges a company encounters in this transition. The company must also address challenges related to the customer and procedures. The core challenges are caused by having multiple customers with diverse environments and unique properties, whose business depends on the software product. Some customers require to perform manual acceptance testing, while some are reluctant towards new versions. By utilizing continuous delivery, it is possible for the case company to shorten the feedback cycles, increase the reliability of new versions, and reduce the amount of resources required for deploying and testing new releases.
Rapid value delivery requires a company to utilize empirical evaluation of new features and products in order to avoid unnecessary product risks. This helps to make data-driven decisions and to ensure that the development is focused on features that provide real value for customers. Short feedback loops are a prerequisite as they allow for fast learning and reduced reaction times. Continuous experimentation is a development practice where the entire R&D process is guided by constantly conducting experiments and collecting feedback. Although principles of continuous experimentation have been successfully applied in domains such as game software or SAAS, it is not obvious how to transfer continuous experimentation to the business to-business domain. In this article, a case study from a medium-sized software company in the B2B domain is presented. The study objective is to analyze the challenges, benefits and organizational aspects of continuous experimentation in the B2B domain. The results suggest that technical challenges are only one part of the challenges a company encounters in this transition. The company also has to address challenges related to the customer and organizational culture. Unique properties in each customers business play a major role and need to be considered when designing experiments. Additionally, the speed by which experiments can be conducted is relative to the speed by which production deployments can be made. Finally, the article shows how the study results can be used to modify the development in the case company in a way that more feedback and data is used instead of opinions.
The goal of this paper pretends to show how a bed system with an embedded system with sensor is able to analyze a person’s movement, breathing and recognizing the positions that the subject is lying on the bed during the night without any additional physical contact. The measurements are performed with sensors placed between the mattress and the frame. An Intel Edison board was used as an endpoint that served as a communication node from the mesh network to external service. Two nodes and Intel Edison are attached to the bottom of the bed frame and they are connected to the sensors.
Deep learning-based EEG detection of mental alertness states from drivers under ethical aspects
(2021)
One of the most critical factors for a successful road trip is a high degree of alertness while driving. Even a split second of inattention or sleepiness in a crucial moment, will make the difference between life and death. Several prestigious car manufacturers are currently pursuing the aim of automated drowsiness identification to resolve this problem. The path between neuro-scientific research in connection with artificial intelligence and the preservation of the dignity of human individual’s and its inviolability, is very narrow. The key contribution of this work is a system of data analysis for EEGs during a driving session, which draws on previous studies analyzing heart rate (ECG), brain waves (EEG), and eye function (EOG). The gathered data is hereby treated as sensitive as possible, taking ethical regulations into consideration. Obtaining evaluable signs of evolving exhaustion includes techniques that obtain sleeping stage frequencies, problematic are hereby the correlated interference’s in the signal. This research focuses on a processing chain for EEG band splitting that involves band-pass filtering, principal component analysis (PCA), independent component analysis (ICA) with automatic artefact severance, and fast fourier transformation (FFT). The classification is based on a step-by-step adaptive deep learning analysis that detects theta rhythms as a drowsiness predictor in the pre-processed data. It was possible to obtain an offline detection rate of 89% and an online detection rate of 73%. The method is linked to the simulated driving scenario for which it was developed. This leaves space for more optimization on laboratory methods and data collection during wakefulness-dependent operations.
Uncontrolled movement of instruments in laparoscopic surgery can lead to inadvertent tissue damage, particularly when the dissecting or electrosurgical instrument is located outside the field of view of the laparoscopic camera. The incidence and relevance of such events are currently unknown. The present work aims to identify and quantify potentially dangerous situations using the example of laparoscopic cholecystectomy (LC). Twenty-four final year medical students were prompted to each perform four consecutive LC attempts on a well-established box trainer in a surgical training environment following a standardized protocol in a porcine model. The following situation was defined as a critical event (CE): the dissecting instrument was inadvertently located outside the laparoscopic camera’s field of view. Simultaneous activation of the electrosurgical unit was defined as a highly critical event (hCE). Primary endpoint was the incidence of CEs. While performing 96 LCs, 2895 CEs were observed. Of these, 1059 (36.6%) were hCEs. The median number of CEs per LC was 20.5 (range: 1–125; IQR: 33) and the median number of hCEs per LC was 8.0 (range: 0–54, IQR: 10). Mean total operation time was 34.7 min (range: 15.6–62.5 min, IQR: 14.3 min). Our study demonstrates the significance of CEs as a potential risk factor for collateral damage during LC. Further studies are needed to investigate the occurrence of CE in clinical practice, not just for laparoscopic cholecystectomy but also for other procedures. Systematic training of future surgeons as well as technical solutions address this safety issue.
Wie digital ist ein Unternehmen aufgestellt? Wie weit ist es im Vergleich mit anderen Unternehmen der Branche? Um dies zu eruieren, eignen sich digitale Reifegradmodelle. Sie bieten eine Beschreibung der Ist-Situation, regen zur Reflexion über die wichtigen Fragen der Digitalisierung an und zeigen, welche Faktoren sich beeinflussen. Kontinuierlich eingesetzt lassen sie sich als Monitoring des digitalen Transformationsprozesses nutzen.
Im Kundenbeziehungsmanagement besteht ein großes Interesse an der Nutzung von Social Media. Allerdings finden sich aktuell kaum konzeptionell durchdachte und empirisch überprüfte Lösungen für Social CRM.
Social Media bieten innovative Perspektiven für das Management der Kundenbeziehung. Die Nutzung dieser Möglichkeiten ist jedoch mit hohen Anforderungen an die Marketingstrategie verbunden, was zuweilen vernachlässigt wird.
Turning complainers into fans : towards a framework for customer services in social media channels
(2012)
In recent years, marketing scholars have invested heavily in exploring the role of social media in marketing theory and practice. One valuable strategy for using social media in marketing communication is to provide customer services in applications like Facebook or Twitter. This paper evaluates a) the concept of perceived service quality in different service channels and b) the impact customer service strategies have on customer loyalty, word of mouth communication, and cross-sell preferences. The framework presented here is tested cross-channel against data collected from the customer service department of a large telecommunication provider. The results elucidate the effectiveness of customer service strategies in different channels.
Der Beitrag gibt einen Überblick zum Stand der Vertrauensforschung in Marketing und Vertrieb. Dabei ist Vertrauen als Gegenstand der Forschung innerhalb des Relationship Marketing Ansatzes sehr gut etabliert. Bei der Definition des Vertrauensbegriffs stützt sich das Marketing auf die Erkenntnisse der sozialwirtschaftlichen Nachbardisziplinen. Soweit Kunden ihren Anbietern vertrauen, gehen sie grundsätzlich ein Risiko ein und machen sich hierdurch angreifbar. Man vertraut in einen Anbieter, ohne vorab genau zu wissen, ob das gewünschte Resultat einer Kooperation mit Sicherheit eintritt. Dies gilt umgekehrt auch für den Anbieter, der zum Teil erhebliche Vorinvestitionen tätigen muss, ohne vorab zu wissen, ob tatsächlich eine Geschäftsbeziehung mit einem Kunden entsteht. Vertrauen ist daher v.a. in komplexen und langfristigen Beziehungen zwischen Anbietern und Kunden eine wesentliche Ressource. Entsprechend thematisiert der Beitrag die Bedingungen und Auswirkungen von Vertrauen auf unterschiedlichen Ebenen. Dabei dominiert in Marketing und Vertrieb noch immer eine interpersonale Perspektive. Die Potentiale organisationaler Beziehungsstrategien sind zum gegenwärtigen Zeitpunkt eher schwach beleuchtet, jedoch greift der Beitrag einige Trends für die weitere Ausrichtung der Vertrauensforschung auf, die zukünftig stärker an Bedeutung gewinnen werden. Dabei ist grundsätzlich davon auszugehen, dass bei zunehmend volatilen Rahmenbedingungen das Interesse an Vertrauensfragen auch in Marketing und Vertrieb weiter zunimmt.