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The paper illustrates the status quo of a research project for the development of a control system enabling CHP units for a demand-oriented electricity production by an intelligent management of the heat storage tank. Thereby the focus of the project is twofold. One is the compensation of the fluctuating power production by the renewable energies solar and wind. Secondly, a reduction of the load on the power grid is intended by better matching local electricity demand and production.
In detail, the general control strategy is outlined, the method utilized for forecasting heat and electricity demand is illustrated as well as a correlation method for the temperature distribution in the heat storage tank based on a Sigmoid function is proposed. Moreover, the simulation model for verification and optimization of the control system and the two field test sites for implementing and testing the system are introduced.
Applications often need to be deployed in different variants due to different customer requirements. However, since modern applications often need to be deployed using multiple deployment technologies in combination, such as Ansible and Terraform, the deployment variability must be considered in a holistic way. To tackle this, we previously developed Variability4TOSCA and the prototype OpenTOSCA Vintner, which is a TOSCA preprocessing and management layer that implements Variability4TOSCA. In this demonstration, we present a detailed case study that shows how to model a deployment using Variability4TOSCA, how to resolve the variability using Vintner, and how the result can be deployed.
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.
Engineers of the research project “Digital Product Life-Cycle” are using a graph-based design language to model all aspects of the product they are working on. This abstract model is the base for all further investigations, developments and implementations. In particular at early stages of development, collaborative decision making is very important. We propose a semantic augmented knowledge space by means of mixed reality technology, to support engineering teams. Therefore we present an interaction prototype consisting of a pico projector and a camera. In our usage scenario engineers are augmenting different artefacts in a virtual working environment. The concept of our prototype contains both an interaction and a technical concept. To realise implicit and natural interactions, we conducted two prototype tests: (1) A test with a low-fidelity prototype and (2) a test by using the method Wizard of Oz. As a result, we present a prototype with interaction selection using augmentation spotlighting and an interaction zoom as a semantic zoom.
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.
A sequence of transactions represents a complex and multi dimensional type of data. Feature construction can be used to reduce the data´s dimensionality to find behavioural patterns within such sequences. The patterns can be expressed using the blue prints of the constructed relevant features. These blue prints can then be used for real time classification on other sequences.
The coupling of the heat and power sector is required as supply and demand in the German electricity mix drift further and further apart with a high percentage of renewable energy. Heat pumps in combination with thermal energy storage systems can be a useful way to couple the heat and power sectors. This paper presents a hardware-in the-loop test bench for experimental investigation of optimized control strategies for heat pumps. 24-hour experiments are carried out to test whether the heat pump is able to serve optimized schedules generated by a MATLAB algorithm. The results show that the heat pump is capable of following the generated schedules, and the maximum deviation of the operational time between schedule and experiment is only 3%. Additionally, the system can serve the demand for space heating and DHW at any time.
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.
Going forward with the requirements of missions to the Moon and further into deep space, the European Space Agency is investigating new methods of astronaut training that can help accelerate learning, increase availability and reduce complexity and cost in comparison to currently used methods. To achieve this, technologies such as virtual reality may be utilized. In this paper, an investigation into the benefits of using virtual reality as a means for extravehicular activity training in comparison to conventional training methods, such as neutral buoyancy pools is given. To help determine the requirements and current uses of virtual reality for extravehicular activity training first hand tests of currently available software as well as expert interviews are utilized. With this knowledge a concept is developed that may be used to further advance training methods in virtual reality. The resulting concept is used as a basis for development of a prototype to showcase user interactions and locomotion in microgravity simulations.
The stimulation of user engagement has received significant attention in extant research. However, the theory of antecedents for user engagement with an initial electronic word-of-mouth (eWoM) communication is relatively less developed. In an investigation of 576 unique user postings across independent Facebook (FB) communities for two German firms, we contribute to the extant knowledge on user engagement in two different ways. First, we explicate senders’ prior usage experience and the extent of their acquaintance with other community members as the two key drivers of user engagement across a product and a service community. Second, we reveal that these main effects differ according to the type of community. In service communities, experience has a stronger impact on user engagement; whereas, in product communities, acquaintance is more important.
This paper examines the efficacy of social media systems in customer complaint handling. The emergence of social media, as a useful complement and (possibly) a viable alternative to the traditional channels of service delivery, motivates this research. The theoretical framework, developed from literature on social media and complaint handling, is tested against data collected from two different channels (hotline and social media) of a German telecommunication services provider, in order to gain insights into channel efficacy in complaint handling. We contribute to the understanding of firm’s technology usage for complaint handling in two ways:
(a) by conceptualizing and evaluating complaint handling quality across traditional and social media channels and (b) by comparing the impact of complaint handling quality on key performance outcomes such as customer loyalty, positive word-of-mouth, and crosspurchase intentions across traditional and social media channels.
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.
Durch das stetige Wachstum an neuen Technologien und Möglichkeiten steht der Verschmelzung von Technologien mit dem Menschen kaum noch etwas im Wege. Die Untersuchung der Implantate und die damit verbundenen Risiken sind ein Teil dieser Arbeit. Von Bedeutung sind hier die Funktionsweise und die IT-Sicherheitsaspekte. Alle in dieser Arbeit dargestellten Implantate benötigen eine Kommunikation nach außen. Diese Kommunikationsmöglichkeit birgt Risiken, die nicht nur auf die Daten der Träger beschränkt sind, sondern auch gesundheitliche Risiken beinhalten.
Eines der gängigsten bildgebenden Verfahren in der Medizin ist die Sonografie. Jedoch ist die Reproduzierbarkeit der Ultraschalldiagnostik bis heute noch immer ein Problem, wodurch Fehldiagnosen gestellt werden. Durch das in diesem Papier vorgestellte prototypische System zur Unterstützung für Medizinstudenten in Ultraschallseminaren sollen Anforderungen zur Reproduzierbarkeit einer Ultraschalluntersuchung definiert werden. Durch Experteninterviews wurden Einblicke in die klinischen Abläufe und den Krankenhaus-Alltag gewonnen, welche Inhalte relevant sind, um die Reproduzierbarkeit von Ultraschalluntersuchungen zu ermöglichen.
Universelle OTA-Testbench
(2014)
Es wird eine universell einsetzbare Testbench zur Simulation von integrierten Schaltungen innerhalb der OTA-Schaltungsklasse (Operational Transconductance Amplifier; Transkonduktanzverstärker) vorgestellt. Transkonduktanzverstärker sind in der analogen Schaltungstechnik weit verbreitet und daher von großer Bedeutung. Sie treten sowohl als eigenständige Schaltungen innerhalb eines Chips, sowie als Bestandteil anderer Schaltungen (z.B. als erste und zweite Stufe von Operationsverstärkern) auf. Es kann davon ausgegangen werden, dass heute kaum ein analoger oder Mixed-Signal-Chip gefertigt wird, in dem keine Transkonduktanzverstärker verbaut sind. Die Entscheidungsfindung des Entwicklers bei der Auslegung eines OTAs beruht maßgeblich auf einer anwendungsspezifischen Simulation. Die Erstellung einer eigenen Testbench für jede Anwendung bedeutet allerdings einen hohen Zeitaufwand und erschwert den Vergleich der Simulationsergebnisse unterschiedlicher Schaltungsvarianten. Durch eine universelle Testbench kann zum einen der Zeitaufwand verringert werden, zum anderen können nun Simulationsergebnisse direkt miteinander verglichen werden. Hierdurch wird die Entscheidungsfindung des Entwicklers objektiviert und beschleunigt. Neben dem Vergleich unterschiedlicher Schaltungen innerhalb einer Technologie ist auch der Vergleich einer Schaltung in unterschiedlichen Technologien denkbar. Die Idee einer universell anwendbaren Testbench lässt sich auch auf andere analoge Schaltungsklassen anwenden und damit als Prinzip verallgemeinern.
Forecasting demand is challenging. Various products exhibit different demand patterns. While demand may be constant and regular for one product, it may be sporadic for another, as well as when demand occurs, it may fluctuate significantly. Forecasting errors are costly and result in obsolete inventory or unsatisfied demand. Methods from statistics, machine learning, and deep learning have been used to predict such demand patterns. Nevertheless, it is not clear for what demand pattern, which algorithm would achieve the best forecast. Therefore, even today a large number of models are used to forecast on a test period. The model with the best result on the test period is used for the actual forecast. This approach is computationally and time intensive and, in most cases, uneconomical. In our paper we show the possibility to use a machine learning classification algorithm, which predicts the best possible model based on the characteristics of a time series. The approach was developed and evaluated on a dataset from a B2B-technical-retailer. The machine learning classification algorithm achieves a mean ROC-AUC of 89%, which emphasizes the skill of the model.
Intermittent time series forecasting is a challenging task which still needs particular attention of researchers. The more unregularly events occur, the more difficult is it to predict them. With Croston’s approach in 1972 (1.Nr. 3:289–303), intermittence and demand of a time series were investigated the first time separately. He proposes an exponential smoothing in his attempt to generate a forecast which corresponds to the demand per period in average. Although this algorithm produces good results in the field of stock control, it does not capture the typical characteristics of intermittent time series within the final prediction. In this paper, we investigate a time series’ intermittence and demand individually, forecast the upcoming demand value and inter-demand interval length using recent machine learning algorithms, such as long-short-term-memories and light-gradient-boosting machines, and reassemble both information to generate a prediction which preserves the characteristics of an intermittent time series. We compare the results against Croston’s approach, as well as recent forecast procedures where no split is performed.
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.
Strategic alliances have become important strategic options for firms to achieve competitive advantage. Yet, there are many examples of alliance failures. Scholars have studied this phenomenon and identified many reasons for alliance failure, including lack of trust between the partnering firms. Paradoxically, the concept of trust is still not fully understood, specifically how and under what conditions trust comes to break down within the broader process of alliance building. We synthesize a process model that describes the “alliance capability”, including trust, openness, partner contributions, and relational rents. We then translate this framework into a formal simulation model and analyze it thoroughly. In analyzing trust dynamics we identify and explore a tipping boundary, separating a regime of alliance failures and successes. We apply our core findings to openness strategies – decisions about how much knowledge to share with partners. Our analyses reveal that strategies informed by a static mental model of trust, contributions, and openness, under undervalue openness. Further, too little openness risks early failure due to the being trapped in a vicious cycle of trust depletion.
This research addresses the question of why employees use enterprise social networks (ESN). Against the background of technology acceptance research, we propose an extended unified theory of acceptance and use of technology (UTAUT) model, adapt it to an ESN context, and test our model against data from ESN users of large and medium-sized enterprises. We use partial least squares structural equation modeling to gain insights into the determinants of ESN use. This paper contributes to ESN acceptance research by evaluating a model containing determinants of ESN use. It also examines the effects of determinants on five different usage dimensions of ESN. The results reveal that facilitating conditions are the main driver of ESN use while the impact of intention to use is comparably small. Implications for theory and practice are discussed.
Die Alterungsbeständigkeit von geschirmten Kabeln und Kontaktpaaren gewinnt angesichts des zunehmenden Einsatzes elektronischer softwarebasierter Steuerungen in Transportmitteln an Relevanz. Elektro- und Hybridantriebe sowie die Implementierung von Fahrassistenzsystemen bis hin zu autonom fahrenden Fahrzeugen führen zu komplexen Kabelbäumen mit einer großen Zahl von geschirmten Kabeln und Steckverbindern.
Um die Stabilität von Kontaktsystemen hinsichtlich ihrer Stabilität zu prüfen, werden Hochspannungskabel unterschiedlicher Hersteller und Dimensionierung für den Einsatz in Hybridfahrzeugen untersucht. Diese wurden mit Modellsteckern versehen, die die Schimung kontaktierten und hinreichend gewährleisteten.
Impedanz und Schirmwirkungsdämpfung wurden an thermisch belasteten Kabeln und Kontaktpaaren vergleichend zu Neuteilen untersucht. Der Einfluss der in Anlehnung an die LV 214 induzierten thermischen Alterung auf das frequenzabhängige Übertragungsprofil sowie den Gesamtstreuverlust wurde messtechnisch ermittelt. Zusätzlich wurden die Alterungseffekte an den Leitungsmaterialien mittels moderner bildgebender Analytik dokumentiert.
Das Ziel dieser Arbeit war die Umsetzung eines Wahrnehmungsensors für Softwareagenten, die über ein virtuelles Menschmodell in einer dreidimensionalen Umgebung agieren. Hierbei sollen die Agenten über den Sensor in der Lage sein, semantische Informationen zu geometrischen Objekten in der Umgebung zu erhalten. Hierfür wurden zwei Verfahren umgesetzt, die das menschliche Sehen simulieren, indem Objekte erkannt werden, wenn diese innerhalb eines Sichtfelds liegen. Ein Problem, das dabei gelöst werden muss, ist die Identifizierung möglicher Verdeckungen der Objekte. Ein Ansatz, dieses Problem zu lösen, ist der Ray-Tracing Ansatz, welcher für das erste Verfahren umgesetzt wurde. Das zweite Verfahren verwendet den Occlusion-Culling Ansatz. Auswertungen beider Verfahren haben gezeigt, dass der Ray-Tracing Ansatz eine schnellere Laufzeit aufweist, der Occlusion-Culling Ansatz jedoch mehr unverdeckte Objekte im Sichtfeld erkennt.
Two Stream Hypothesis: Adaptationseffekte bei sozialen Interaktionen mit Avataren in Virtual Reality
(2015)
In diesem Paper wird ein Experiment zur Two-Streams-Hypothese vorgestellt. Dabei werden zunächst die psychologischen und technischen Grundlagen erarbeitet, welche für das Experiment benötigt werden. Anschließend wird die Forschungsfrage definiert und der Versuchsaufbau erörtert. Im Experiment soll getestet werden, ob es unterschiedliche Adaptationseffekte bei der Erkennung und dem Ausführen von nicht-eindeutigen sozialen Handlungen gibt. Es wird ein Versuchsaufbau entwickelt, bei welchem Probanden entweder aktiv durch komplementäre Handlungen auf die Handlungen von virtuellen Avataren reagieren sollen oder passiv durch das Drücken von Buttons. Abschließend werden die Ergebnisse ausgewertet und ein Fazit
gezogen.
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.
Suppliers need to improve their relational capabilities if they are to enhance customer trust. Debate about such capabilities is dominated by an interpersonal approach. This paper provieds novel marketing options by expanding insights into alternative types of relational capabilities. Furthermore, the moderating role of customer preferences on the effectiveness of relational capabilities is evaluated.
Coopetitive endeavors offer valuable strategic options for firms. Yet, many of them are failure-prone as partners must balance collective and private interest. While interpartner trust is considered central for alliance success, paradoxically, the role and dynamics of trust is still not understood. We synthesize a computational model, capturing relational dynamics of an alliance, encompassing coevolution of trust, partner contributions, and (relative) alliance interactions. Analyzing alliance dynamics using simulation we find and explore a tipping boundary, separating a regime of alliance failure and success. We identify implications for collaborative (aspirations) and private strategies (openness). Our analyses reveal that strategies informed by a static mental model of partner trust, contributions, and openness tend to yield subpar alliance results and hidden failure-risk. We discuss implications for management theory.
Context: Companies need capabilities to evaluate the customer value of software intensive products and services. One way of systematically acquiring data on customer value is running continuous experiments as part of the overall development process. Objective: This paper investigates the first steps of transitioning towards continuous experimentation in a large company, including the challenges faced. Method: We conduct a single-case study using participant observation, interviews, and qualitative analysis of the collected data. Results: Results show that continuous experimentation was well received by the practitioners and practising experimentation helped them to enhance understanding of their product value and user needs. Although the complexities of a large multi-stakeholder business to-business (B2B) environment presented several challenges such as inaccessible users, it was possible to address impediments and integrate an experiment in an ongoing development project. Conclusion: Developing the capability for continuous experimentation in large organisations is a learning process which can be supported by a systematic introduction approach with the guidance of experts. We gained experience by introducing the approach on a small scale in a large organisation, and one of the major steps for future work is to understand how this can be scaled up to the whole development organisation.
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.
The experimental characterization of the thermal impedance Zth of large power MOSFETs is commonly done by measuring the junction temperature Tj in the cooling phase after the device has been heated, preferably to a high junction temperature for increased accuracy. However, turning off a large heating current (as required by modern MOSFETs with low on-state resistances) takes some time because of parasitic inductances in the measurement system. Thus, most setups do not allow the characterization of the junction temperature in the time range below several tens of μs.
In this paper, an optimized measurement setup is presented which allows accurate Tj characterization already 3 μs after turn-off of heating. With this, it becomes possible to experimentally investigate the influence of thermal capacitances close to the active region of the device. Measurement results will be presented for advanced power MOSFETs with very large heating currents up to 220 A. Three bonding variants are investigated and the observed differences will be explained.
This paper aims at presenting a solution that enables end customers of the energy system to participate in new local micro-energy-markets by providing them with a distributed, decentralized, transparent and secure Peer to Peer (P2P) payment system, which functions automatically applying new concepts of Machine to Machine (M2M) communication technologies. This work was performed within the German project VK_2G, funded by the DBU. The key results were: Providing means to perform microtransactions in a P2P fashion between end consumers and prosumers in local communities at low cost in a transparent and secure manner; Developing a platform with pre-defined smart contracts able to be tailored to different end customers ‘needs in an easy way and; Integrating both the market platform as well as the local control of generation and loads. This solution has been developed, integrated and tested in a laboratory prototype. This paper discusses this solution and presents the results of the first test.
Today, companies face increasing market dynamics, rapidly evolving technologies, and rapid changes in customer behavior. Traditional approaches to product development typically fail in such environments and require companies to transform their often feature-driven mindset into a product-led mindset. A promising first step on the way to a product-led company is a better understanding of how product planning can be adapted to the requirements of an increasingly dynamic and uncertain market environment in the sense of product roadmapping. The authors developed the DEEP product roadmap assessment tool to help companies evaluate their current product roadmap practices and identify appropriate actions to transition to a more product-led company. Objective: The goal of this paper is to gain insight into the applicability and usefulness of version 1.1 of the DEEP model. In addition, the benefits, and implications of using the DEEP model in corporate contexts will be explored. Method: We conducted a multiple case study in which participants were observed using the DEEP model. We then interviewed each participant to understand their perceptions of the DEEP model. In addition, we conducted interviews with each company's product management department to learn how the application of the DEEP model influenced their attitudes toward product roadmapping. Results: The study showed that by applying the DEEP model, participants better understood which artifacts and methods were critical to product roadmapping success in a dynamic and uncertain market environment. In addition, the application of the DEEP model helped convince management and other stakeholders of the need to change current product roadmapping practices. The application also proved to be a suitable starting point for the transformation in the participating companies.
Transaction processing is of growing importance for mobile computing. Booking tickets, flight reservation, banking, ePayment, and booking holiday arrangements are just a few examples for mobile transactions. Due to temporarily disconnected situations the synchronisation and consistent transaction processing are key issues. Serializability is a too strong criteria for correctness when the semantics of a transaction is known. We introduce a transaction model that allows higher concurrency for a certain class of transactions defined by its semantic. The transaction results are ”escrow serializable” and the synchronisation mechanism is non-blocking. Experimental implementation showed higher concurrency, transaction throughput, and less resources used than common locking or optimistic protocols.
Industrial practice is characterized by random events, also referred to as internal and external turbulences, which disturb the target-oriented planning and execution of production and logistics processes. Methods of probabilistic forecasting, in contrast to single value predictions, allow an estimation of the probability of various future outcomes of a random variable in the form of a probability density function instead of predicting the probability of a specific single outcome. Probabilistic forecasting methods, which are embedded into the analytics process to gain insights for the future based on historical data, therefore offer great potential for incorporating uncertainty into planning and control in industrial environments. In order to familiarize students with these potentials, a training module on the application of probabilistic forecasting methods in production and intralogistics was developed in the learning factory 'Werk150' of the ESB Business School (Reutlingen University). The theoretical introduction to the topic of analytics, probabilistic forecasting methods and the transition to the application domain of intralogistics is done based on examples from other disciplines such as weather forecasting and energy consumption forecasting. In addition, data sets of the learning factory are used to familiarize the students with the steps of the analytics process in a practice-oriented manner. After this, the students are given the task of identifying the influencing factors and required information to capture intralogistics turbulences based on defined turbulence scenarios (e.g. failure of a logistical resource) in the learning factory. Within practical production scenario runs, the students apply probabilistic forecasting using and comparing different probabilistic forecasting methods. The graduate training module allows the students to experience the potentials of using probabilistic forecasting methods to improve production and intralogistics processes in context with turbulences and to build up corresponding professional and methodological competencies.
Die Entwicklung eines Medizinproduktes benötigt in der Regel mehrere Jahre. Gesetzliche Vorgaben, wie zum Beispiel das Medizinprodukte Durchführungsgesetz, bestimmen, welche Schritte während der Entwicklung durchgeführt werden müssen. Deren Einhaltung muss in der technischen Dokumentation nachgewiesen werden. Die darin enthaltenen technischen Dokumente entstehen im Verlauf der Entwicklung. Diese bauen aufeinander auf und verweisen sich gegenseitig. Dadurch entstehen heterogene und unübersichtliche Strukturen. Eine Lösung für dieses Problem bietet Traceability. Traceability sorgt dafür, dass die Anforderungen an das Medizinprodukt mit Dokumenten, wie dem Anforderungskatalog, Lastenheft oder der Spezifikation verknüpft werden können. Somit ist jederzeit nachvollziehbar, welche Anforderungen mit welchem Test, welchen Änderungen oder welchen Ergebnissen zusammenhängen. Ein wichtiger Prozess bei der Entwicklung von Medizinprodukten ist zudem das Usability Engineering, wodurch die Sicherheit eines Medizinprodukts sichergestellt und Risiken bei der Anwendung minimiert werden sollen. In diesem Prozess entstehen viele Artefakte, wie zum Beispiel Usability-Berichte. Um den Überblick über alle Usability-Daten behalten zu können, können diese mithilfe von Traceability verknüpft werden. In diesem Artikel wird herausgestellt, welche Voraussetzungen für das Usability Engineering in der Medizintechnik an Traceability gestellt
werden.
Enterprise Architectures (EA) consists of many architecture elements, which stand in manifold relationships to each other. Therefore Architecture Analysis is important and very difficult for stakeholders. Due changing an architecture element has impacts on other elements different stakeholders are involved. In practice EAs are often analyzed using visualizations. This article aims at contributing to the field of visual analytics in EAM by analyzing how state of-the-art software platforms in EAM support stakeholders with respect to providing and visualizing the “right” information for decision-making tasks. We investigate the collaborative decision-making process in an experiment with master students using professional EAM tools by developing a research study and accomplishing them in a master’s level class with students.
Ambitious goals set by the European Union strategy towards the emission reduction of multimodal logistic chains and new requirements for intermodal terminals set by the evolution of customer needs, contribute to a shift in the driver for the infrastructure development: from economy of scale to economy of density. This paper aims to present an innovative method for designing a process oriented technology chain for intermodal terminals in order to fulfill these new demanding requirements. The results of the case study of the Zero Emission Logistic Terminal Reutlingen are presented, highlighting how this particular context enables the design and development of a modular concept, paving the way for the generalization of the findings towards the transfer to similar contexts of other European cities.
In this paper it is first identified the trade-off among costs, flexibility and performances of autonomous robotic solutions for material handling processes, where adding value with automation is not as trivial as in production processes: hence the requirement for automated solutions to be simple, lean and efficient becomes even stricter. Then a method for modelling and comparing differential performances and costs of manual and autonomous solutions is developed. As a result of the method, a smart man-machine collaborative interface is designed and its impact evaluated on a specific case of study. Results are then generalized and prove the strong conclusions that in unconstrained environments, where full standardization cannot be achieved, the risk of investing in autonomous solutions can only be mitigated by creating a fast and smart man-machine collaborative interface.
Facial expressions play a dominant role in facilitating social interactions. We endeavor to develop tactile displays to reinstate facial expression modulated communication. The high spatial and temporal dimensionality of facial movements poses a unique challenge when designing tactile encodings of them. A further challenge is developing encodings that are at-tuned to the perceptual characteristics of our skin. A caveat of using vibrotactile displays is that tactile stimuli have been shown to induce perceptual tactile aftereffects when used on the fingers, arm and face. However, at present, despite the prevalence of waist-worn tactile displays, no such investigations of tactile aftereffects at the waist region exist in the literature, though they are warranted by the unique sensory and perceptual signalling characteristics of this area. Using an adaptation paradigm we investigated the presence of perceptual tactile aftereffects induced by continuous and burst vibrotactile stimuli delivered at the navel, side and spinal regions of the waist. We report evidence that the tactile perception topology of the waist is non-uniform, and specifically that the navel and spine regions are resistant to adaptive aftereffects while side regions are more prone to perceptual adaptations to continuous but not burst stimulations. Results of our current investigations highlight the unique set of challenges posed by designing waist-worn tactile displays. These and future perceptual studies can directly inform more realistic and effective implementations of complex high-dimensional spatiotemporal social cues.
Due to the consequential impact of technological breakdowns, companies have to be prepared to deal with breakdowns or even better prevent them. In today's information technology, several methods and tools exist to downscale this concern. Therefore, this paper deals with the initial determination of a resilient enterprise architecture supporting predictive maintenance in the information technology domain and furthermore, concerns several mechanisms on how to reactively and proactively secure the state of resiliency on several abstraction levels. The objective of this paper is to give an overview on existing mechanisms for resiliency and to describe the foundation of an optimized approach, combining infrastructure and process mining techniques.
IT environments that consist of a very large number of rather small structures like microservices, Internet of Things (IoT) components, or mobility systems are emerging to support flexible and agile products and services in the age of digital transformation. Biological metaphors of living and adaptable ecosystems with service-oriented enterprise architectures provide the foundation for self-optimizing, resilient run-time environments and distributed information systems. We are extending Enterprise Architecture (EA) methodologies and models that cover a high degree of heterogeneity and distribution to support the digital transformation and related information systems with micro-granular architectures. Our aim is to support flexibility and agile transformation for both IT and business capabilities within adaptable digital enterprise architectures. The present research paper investigates mechanisms for integrating Microservice Architectures (MSA) by extending original enterprise architecture reference models with elements for more flexible architectural metamodels and EA-mini-descriptions.
The aim of this work is the development of artificial intelligence (AI) application to support the recruiting process that elevates the domain of human resource management by advancing its capabilities and effectiveness. This affects recruiting processes and includes solutions for active sourcing, i.e. active recruitment, pre-sorting, evaluating structured video interviews and discovering internal training potential. This work highlights four novel approaches to ethical machine learning. The first is precise machine learning for ethically relevant properties in image recognition, which focuses on accurately detecting and analysing these properties. The second is the detection of bias in training data, allowing for the identification and removal of distortions that could skew results. The third is minimising bias, which involves actively working to reduce bias in machine learning models. Finally, an unsupervised architecture is introduced that can learn fair results even without ground truth data. Together, these approaches represent important steps forward in creating ethical and unbiased machine learning systems.
AI technologies such as deep learning provide promising advances in many areas. Using these technologies, enterprises and organizations implement new business models and capabilities. In the beginning, AI-technologies have been deployed in an experimental environment. AI-based applications have been created in an ad-hoc manner and without methodological guidance or engineering approach. Due to the increasing importance of AI-technologies, however, a more structured approach is necessary that enable the methodological engineering of AI-based applications. Therefore, we develop in this paper first steps towards methodological engineering of AI-based applications. First, we identify some important differences between the technological foundations of AI- technologies, in particular deep learning, and traditional information technologies. Then we create a framework that enables to engineer AI-applications using four steps: identification of an AI-application type, sub-type identification, lifecycle phase, and definition of details. The introduced framework considers that AI-applications use an inductive approach to infer knowledge from huge collections and streams of data. It not only enables the rapid development of AI-application but also the efficient sharing of knowledge on AI-applications.
Distraction of the driver is one of the most frequent causes for car accidents. We aim for a computational cognitive model predicting the driver’s degree of distraction during driving while performing a secondary task, such as talking with co-passengers. The secondary task might cognitively involve the driver to differing degrees depending on the topic of the conversation or the number of co-passengers. In order to detect these subtle differences in everyday driving situations, we aim to analyse in-car audio signals and combine this information with head pose and face tracking information. In the first step, we will assess driving, video and audio parameters reliably predicting cognitive distraction of the driver. These parameters will be used to train the cognitive model in estimating the degree of the driver’s distraction. In the second step, we will train and test the cognitive model during conversations of the driver with co-passengers during active driving. This paper describes the work in progress of our first experiment with preliminary results concerning driving parameters corresponding to the driver’s degree of distraction. In addition, the technical implementation of our experiment combining driving, video and audio data and first methodological results concerning the auditory analysis will be presented. The overall aim for the application of the cognitive distraction model is the development of a mobile user profile computing the individual distraction degree and being applicable also to other systems.
A large body of literature is concerned with models of presence— the sensory illusion of being part of a virtual scene— but there is still no general agreement on how to measure it objectively and reliably. For the presented study, we applied contemporary theory to measure presence in virtual reality. Thirty-seven participants explored an existing commercial game in order to complete a collection task. Two startle events were naturally embedded in the game progression to evoke physical reactions and head tracking data was collected in response to these events. Subjective presence was recorded using a post-study questionnaire and real-time assessments. Our novel implementation of behavioral measures lead to insights which could inform future presence research: We propose a measure in which startle reflexes are evoked through specific events in the virtual environment, and head tracking data is compared to the range and speed of baseline interactions.
Continuous refactoring is necessary to maintain source code quality and to cope with technical debt. Since manual refactoring is inefficient and error prone, various solutions for automated refactoring have been proposed in the past. However, empirical studies have shown that these solutions are not widely accepted by software developers and most refactorings are still performed manually. For example, developers reported that refactoring tools should support functionality for reviewing changes. They also criticized that introducing such tools would require substantial effort for configuration and integration into the current development environment.
In this paper, we present our work towards the Refactoring-Bot, an autonomous bot that integrates into the team like a human developer via the existing version control platform. The bot automatically performs refactorings to resolve code smells and presents the changes to a developer for asynchronous review via pull requests. This way, developers are not interrupted in their workflow and can review the changes at any time with familiar tools. Proposed refactorings can then be integrated into the code base via the push of a button. We elaborate on our vision, discuss design decisions, describe the current state of development, and give an outlook on planned development and research activities.
Digital transformation has changed corporate reality and, with that, firms’ IT environments and IT governance (ITG). As such, the perspective of ITG has shifted from the design of a relatively stable, closed and controllable system of a self-sufficient enterprise to a relatively fluid, open, agile and transformational system of networked co adaptive entities. Related to this paradigm shift in ITG, this paper aims to clarify how the concept of an effective ITG framework has changed in terms of the demand for agility in organizations. Thus, this study conducted 33 qualitative interviews with executives and senior managers from the banking industry in Germany, Switzerland and Austria. Analysis of the interviews focused on the formation of categories and the assignment of individual text parts (codings) to these categories to allow for a quantitative evaluation of the codings per category. Regarding traditional and agile ITG dimensions, 22 traditional and 25 agile dimensions were identified. Moreover, agile strategies within the agile ITG construct and ten ITG patterns were identified from the interview data. The data show relevant perspectives on the implementation of traditional and new ITG dimensions and highlight ambidextrous aspects in ITG frameworks.
While there has been increased digitization of private homes, only little has been done to understand these specific home technologies, how they serve consumers, among other issues. “Smart home technology” (SHT) refer to a wide range of artifacts from cleaning aids to energy advisors. Given this breadth, clarity surrounding the key characteristics and the multi-faceted impact of SHT is needed to conduct more directed research on SHT. We propose a taxonomy to help outline the salient intended outcomes of SHT. Through a process involving five iterations, we analyzed and classified 79 technologies (gathered from literature and industry reports). This uncovered seven dimensions encompassing 20 salient characteristics. We believe these dimensions/characteristics will help researchers and organizations better design and study the impacts of these technologies. Our long-term agenda is to use the proposed taxonomy for an exploratory inquiry to understand tensions occurring when personal and sustainability-related outcomes compete.
Towards a practical maintainability quality model for service- and microservice-based systems
(2017)
Although current literature mentions a lot of different metrics related to the maintainability of service-based systems (SBSs), there is no comprehensive quality model (QM) with automatic evaluation and practical focus. To fill this gap, we propose a Maintainability Model for Services (MM4S), a layered maintainability QM consisting of service properties (SPs) related with automatically collectable Service Metrics (SMs). This research artifact created within an ongoing Design Science Research (DSR) project is the first version ready for detailed evaluation and critical feedback. The goal of MM4S is to serve as a simple and practical tool for basic maintainability estimation and control in the context of BSs and their specialization
microservice-based systems (μSBSs).
While there are several theoretical comparisons of Object Orientation (OO) and Service Orientation (SO), little empirical research on the maintainability of the two paradigms exists. To provide support for a generalizable comparison, we conducted a study with four related parts. Two functionally equivalent systems (one OO and one SO version) were analyzed with coupling and cohesion metrics as well as via a controlled experiment, where participants had to extend the systems. We also conducted a survey with 32 software professionals and interviewed 8 industry experts on the topic. Results indicate that the SO version of our system possesses a higher degree of cohesion, a lower degree of coupling, and could be extended faster. Survey and interview results suggest that industry sees systems built with SO as more loosely coupled, modifiable, and reusable. OO systems, however, were described as less complex and easier to test.
Current approaches for enterprise architecture lack analytical instruments for cyclic evaluations of business and system architectures in real business enterprise system environments. This impedes the broad use of enterprise architecture methodologies. Furthermore, the permanent evolution of systems desynchronizes quickly model representation and reality. Therefore we are introducing an approach for complementing the existing top-down approach for the creation of enterprise architecture with a bottom approach. Enterprise Architecture Analytics uses the architectural information contained in many infrastructures to provide architectural information. By applying Big Data technologies it is possible to exploit this information and to create architectural information. That means, Enterprise Architectures may be discovered, analyzed and optimized using analytics. The increased availability of architectural data also improves the possibilities to verify the compliance of Enterprise Architectures. Architectural decisions are linked to clustered architecture artifacts and categories according to a holistic EAM Reference Architecture with specific architecture metamodels. A special suited EAM Maturity Framework provides the base for systematic and analytics supported assessments of architecture capabilities.