Informatik
Refine
Year of publication
- 2016 (81) (remove)
Document Type
- Conference proceeding (41)
- Book chapter (23)
- Journal article (10)
- Anthology (4)
- Book (2)
- Doctoral Thesis (1)
Is part of the Bibliography
- yes (81) (remove)
Institute
- Informatik (81)
Publisher
- Springer (24)
- Gesellschaft für Informatik (14)
- IEEE (9)
- Hochschule Reutlingen (8)
- Springer Gabler (7)
- Elsevier (5)
- ACM (1)
- De Gruyter (1)
- Elektronikpraxis, Vogel Business Media GmbH & Co. KG (1)
- IARIA (1)
- IBM Research Division (1)
- IMC Information multimedia communication AG (1)
- MCB University Press (1)
- OpenProceedings (1)
- PeerJ Ltd. (1)
- RWTH (1)
- Riga Technical University Press (1)
- Univ. de Jaén (1)
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.
A lot of people need help in their daily life to wash, select and manage their clothing. The goal of this work is to design an assistant system (eKlarA) to support the user by giving recommendations to choose the clothing combinations, to find the clothing and to wash the clothing. The idea behind eKlarA is to generate a system that uses sensors to identify the clothing and their state in the clothing cycle. The clothing cycle consists of the stations: closets, laundry basket and washing machine in one or several places. The system uses the information about the clothing, weather and calendar to support the user in the different steps of the clothing cycle. The first prototype of this system has been developed and tested. The test results are presented in this work.
Background and purpose: Transapical aortic valve replacement (TAVR) is a recent minimally invasive surgical treatment technique for elderly and high-risk patients with severe aortic stenosis. In this paper,a simple and accurate image-based method is introduced to aid the intra-operative guidance of TAVR procedure under 2-D X-ray fluoroscopy.
Methods: The proposed method fuses a 3-D aortic mesh model and anatomical valve landmarks with live 2-D fluoroscopic images. The 3-D aortic mesh model and landmarks are reconstructed from interventional X-ray C-arm CT system, and a target area for valve implantation is automatically estimated using these aortic mesh models.Based on template-based tracking approach, the overlay of visualized 3-D aortic mesh model, land-marks and target area of implantation is updated onto fluoroscopic images by approximating the aortic root motion from a pigtail catheter motion without contrast agent. Also, a rigid intensity-based registration algorithm is used to track continuously the aortic root motion in the presence of contrast agent.Furthermore, a sensorless tracking of the aortic valve prosthesis is provided to guide the physician to perform the appropriate placement of prosthesis into the estimated target area of implantation.
Results: Retrospective experiments were carried out on fifteen patient datasets from the clinical routine of the TAVR. The maximum displacement errors were less than 2.0 mm for both the dynamic overlay of aortic mesh models and image-based tracking of the prosthesis, and within the clinically accepted ranges. Moreover, high success rates of the proposed method were obtained above 91.0% for all tested patient datasets.
Conclusion: The results showed that the proposed method for computer-aided TAVR is potentially a helpful tool for physicians by automatically defining the accurate placement position of the prosthesis during the surgical procedure.
The acquisition of data for reality mining applications is a critical factor, since many mobile devices, e.g. smartphones, must be capable of capturing the required data. Otherwise, only a small target group would be able to use the reality mining application. In the course of a survey, we have identified smartphone features which might be relevant for various reality mining applications. The survey classifies these features and shows how the support of each feature has changed over the years by analyzing 143 smartphones released between 2004 and 2015. All analyzed devices can be ranked by their number of provided features. Furthermore, this paper deals with quality issues which have occurred during carrying out the survey.
Many organizations identified the opportunities of big data analytics to support the business with problem-specific insights through the exploitation of generated data. Socio-technical solutions are developed in big data projects to reach competitive advantage. Although these projects are aligned to specific business needs, common architectural challenges are not addressed in a comprehensive manner. Enterprise architecture management is a holistic approach to tackle the complex business and IT architecture. The transformation of an organization's EA is influenced by big data projects and their data-driven approach on all layers. To enable strategy oriented development of the EA it is essential to synchronize these projects supported by EA management. In
this paper, we conduct a systematic review of big data literature to analyze which requirements for the EA management discipline are proposed. Thereby, a broad overview about existing research is presented to facilitate a more detailed exploration and to foster the evolution o the EA management discipline.
Reliable and accurate car driver head pose estimation is an important function for the next generation of advanced driver assistance systems that need to consider the driver state in their analysis. For optimal performance, head pose estimation needs to be non-invasive, calibration-free and accurate for varying driving and illumination conditions. In this pilot study we investigate a 3D head pose estimation system that automatically fits a statistical 3D face model to measurements of a driver’s face, acquired with a low-cost depth sensor on challenging real-world data. We evaluate the results of our sensor-independent, driver-adaptive approach to those of a state-of-the-art camera-based 2D face tracking system as well as a non-adaptive 3D model relative to own ground-truth data, and compare to other 3D benchmarks. We find large accuracy benefits of the adaptive 3D approach.
The fast moving process of digitization1 demands flexibility in order to adapt to rapidly changing business requirements and newly emerging business opportunities. New features have to be developed and deployed to the production environment a lot faster. To be able to cope with this increased velocity and pressure, a lot of software developing companies have switched to a Microservice Architecture (MSA) approach. Applications built this way consist of several fine-grained and heterogeneous services that are independently scalable and deployable. However, the technological and business architectural impacts of microservices based applications directly affect their integration into the digital enterprise architecture. As a consequence, traditional Enterprise Architecture Management (EAM) approaches are not able to handle the extreme distribution, diversity, and volatility of micro-granular systems and services. We are therefore researching mechanisms for dynamically integrating large amounts of microservices into an adaptable digital enterprise architecture.
The Internet of Things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud services environments are emerging to support smart connected products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems with service-oriented enterprise architectures. We are investigating mechanisms for flexible adaptation and evolution for the next digital enterprise architecture systems in the context of the digital transformation. Our aim is to support flexibility and agile transformation for both business and related enterprise systems through adaptation and dynamical evolution of digital enterprise architectures. The present research paper investigates digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems. We are putting a spotlight with the example domain – Internet of Things.
In dieser Ausarbeitung geht es um den aktuellen Stand der Digitalisierung der Textilindustrie. Sie dient als Grundlage zur Master-Thesis und soll die Frage beantworten, ob ein Informations-System, das die Textilprozesskette begleitet, benötigt wird. Dazu werden die einzelnen Prozessschritte kurz erläutert. In der Ausarbeitung wird auch die Verbindung zwischen der Textilindustrie und den neuen Möglichkeiten mit dem Internet der Dinge beleuchtet.
The evolution of Services Oriented Architectures (SOA) presents many challenges due to their complex, dynamic and heterogeneous nature. We describe how SOA design principles can facilitate SOA evolvability and examine several approaches to support SOA evolution. SOA evolution approaches can be classified based on the level of granularity they address, namely, service code level, service interaction level and model level. We also discuss emerging trends, such as microservices and knowledge-based support, which can enhance the evolution of future SOA systems.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. The Internet of Things, enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud services environments are emerging to support smart connected products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems provide the logical foundation for self-optimizing and resilient run-time environments for intelligent business services and service-oriented enterprise architectures. Our aim is to support flexibility and agile transformations for both business domains and related information technology. The present research paper investigates mechanisms for decision analytics in the context of multi-perspective explorations of enterprise services and their digital enterprise architectures by extending original architecture reference models with state of art elements for agile architectural engineering for the digitization and collaborative architectural decision support. The paper’s context focuses on digital transformations of business and IT and integrates fundamental mappings between adaptable digital enterprise architectures and service-oriented information systems. We are putting a spotlight on the example domain – Internet of Things.
Data collected from internet applications are mainly stored in the form of transactions. All transactions of one user form a sequence, which shows the user´s behaviour on the site. Nowadays, it is important to be able to classify the behaviour in real time for various reasons: e.g. to increase conversion rate of customers while they are in the store or to prevent fraudulent transactions before they are placed. However, this is difficult due to the complex structure of the data sequences (i.e. a mix of categorical and continuous data types, constant data updates) and the large amounts of data that are stored. Therefore, this thesis studies the classification of complex data sequences. It surveys the fields of time series analysis (temporal data mining), sequence data mining or standard classification algorithms. It turns out that these algorithms are either difficult to be applied on data sequences or do not deliver a classification: Time series need a predefined model and are not able to handle complex data types; sequence classification algorithms such as the apriori algorithm family are not able to utilize the time aspect of the data. The strengths and weaknesses of the candidate algorithms are identified and used to build a new approach to solve the problem of classification of complex data sequences. The problem is thereby solved by a two-step process. First, feature construction is used to create and discover suitable features in a training phase. Then, the blueprints of the discovered features are used in a formula during the classification phase to perform the real time classification. The features are constructed by combining and aggregating the original data over the span of the sequence including the elapsed time by using a calculated time axis. Additionally, a combination of features and feature selection are used to simplify complex data types. This allows catching behavioural patterns that occur in the course of time. This new proposed approach combines techniques from several research fields. Part of the algorithm originates from the field of feature construction and is used to reveal behaviour over time and express this behaviour in the form of features. A combination of the features is used to highlight relations between them. The blueprints of these features can then be used to achieve classification in real time on an incoming data stream. An automated framework is presented that allows the features to adapt iteratively to a change in underlying patterns in the data stream. This core feature of the presented work is achieved by separating the feature application step from the computational costly feature construction step and by iteratively restarting the feature construction step on the new incoming data. The algorithm and the corresponding models are described in detail as well as applied to three case studies (customer churn prediction, bot detection in computer games, credit card fraud detection). The case studies show that the proposed algorithm is able to find distinctive information in data sequences and use it effectively for classification tasks. The promising results indicate that the suggested approach can be applied to a wide range of other application areas that incorporate data sequences.
Organizations identified the opportunities of big data analytics to support the business with problem-specific insights through the exploitation of generated data. Sociotechnical solutions are developed in big data projects to reach competitive advantage. Although these projects are aligned to specific business needs, common architectural challenges are not addressed in a comprehensive manner. Enterprise architecture management is a holistic approach to tackle complex business and IT architectures. The transformation of an organization’s EA is influenced by big data transformation processes and their data-driven approach on all layers. In this paper, we review big data literature to analyze which requirements for the EA management discipline are proposed. Based on a systematic literature identification, conceptual categories of requirements for EA management are elicited utilizing an inductive category formation. These conceptual categories of requirements constitute a category system that facilitates a new perspective on EA management and fosters the innovation-driven evolution of the EA management.
discipline.
The amount of image data has been rising exponentially over the last decades due to numerous trends like social networks, smartphones, automotive, biology, medicine and robotics. Traditionally, file systems are used as storage. Although they are easy to use and can handle large data volumes, they are suboptimal for efficient sequential image processing due to the limitation of data organisation on single images. Database systems and especially column-stores support more stuctured storage and access methods on the raw data level for entiere series.
In this paper we propose definitions of various layouts for an efficient storage of raw image data and metadata in a column store. These schemes are designed to improve the runtime behaviour of image processing operations. We present a tool called column-store Image Processing Toolbox (cIPT) allowing to easily combine the data layouts and operations for different image processing scenarios.
The experimental evaluation of a classification task on a real world image dataset indicates a performance increase of up to 15x on a column store compared to a traditional row-store (PostgreSQL) while the space consumption is reduced 7x. With these results cIPT provides the basis for a future mature database feature.
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.
Converting users into customers : the role of user profile information and customer journey analysis
(2016)
Due to the digital transformation, the importance of web analysis and user profiling for enterprises is increasing rapidly as customers focus on digital channels to obtain information about products and brands. While there exists a lot research on these topics, only a minority of firms use them to their advantage. This study aims to tighten the link between research and business such that experimental methods can be used for the improvement of communication strategies in practice. Therefore, a systematic literature analysis is conducted, workshops are observed and documented and an empirical study is used to integrate single steps into a framework for the
practical usage of user profiling and customer journey analysis.
The Eighth International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2016), held between June 26 - 30, 2016 - Lisbon, Portugal, continued a series of international events covering a large spectrum of topics related to advances in fundamentals on databases, evolution of relation between databases and other domains, data base technologies and content processing, as well as specifics in applications domains databases. Advances in different technologies and domains related to databases triggered substantial improvements for content processing, information indexing, and data, process and knowledge mining. The push came from Web services, artificial intelligence, and agent technologies, as well as from the generalization of the XML adoption. High-speed communications and computations, large storage capacities, and load-balancing for distributed databases access allow new approaches for content processing with incomplete patterns, advanced ranking algorithms and advanced indexing methods. Evolution on e-business, ehealth and telemedicine, bioinformatics, finance and marketing, geographical positioning systems put pressure on database communities to push the ‘de facto’ methods to support new requirements in terms of scalability, privacy, performance, indexing, and heterogeneity of both content and technology.
The Internet of Things (IoT), enterprise social networks, adaptive case management, mobility systems, analytics for big data, and cloud services environments are emerging to support smart connected products and services and the digital transformation. Biological metaphors of living and adaptable ecosystems with service oriented enterprise architectures provide the foundation for self-optimizing and resilient run-time environments for intelligent business services and related distributed information systems. We are investigating mechanisms for flexible adaptation and evolution for the next digital enterprise architecture systems in the context of the digital transformation. Our aim is to support flexibility and agile transformation for both business and related enterprise systems through adaptation and dynamical evolution of digital enterprise architectures. The present research paper investigates mechanisms for decision case management in the context of multi-perspective explorations of enterprise services and Internet of Things architectures by extending original enterprise architecture reference models with state of art elements for architectural engineering for the digitization and architectural decision support.
Diese Ausarbeitung befasst sich mit der Fragestellung, inwiefern interaktive Systeme innerhalb eines historischen Ausstellungskontextes herangezogen werden können, um die methodische Vermittlung von Informationen zu fördern und zu unterstützen. Als Anwendungsfall wird hierbei auf das Schloss Aulendorf zurückgegriffen.
Detecting the adherence of driving rules in an energy-efficient, safe and adaptive driving system
(2016)
An adaptive and rule-based driving system is being developed that tries to improve the driving behavior in terms of the energy-efficiency and safety by giving recommendations. Therefore, the driving system has to monitor the adherence of driving rules by matching the rules to the driving behavior. However, existing rule matching algorithms are not sufficient, as the data within a driving system is changing frequently. In this paper a rule matching algorithm is introduced that is able to handle frequently changing data within the context of the driving system. 15 journeys were used to evaluate the performance of the rule matching algorithms. The results showed that the introduced algorithm outperforms existing algorithms in the context of the driving system. Thus, the introduced algorithm is suited for matching frequently changing data against rules with a higher performance, why it will be used in the driving system for the detection of broken energy-efficiency of safety-relevant driving rules.
Die Kombination von Softwareproduktlinien und agiler Softwareentwicklung in der Automobilbranche ist vielversprechend. Das Ziel ist hierbei, sowohl die Vorteile agiler Methoden wie kurze Entwicklungszyklen als auch die Vorteile systematischer Wiederverwendung wie beispielsweise das effektive Management von Varianten zu erzielen. Allerdings ist die Kombination auch mit Herausforderungen verbunden und erfordert eine geeignete Einführungs- oder Transformationsstrategie. Basierend auf Erkenntnissen einer Interviewstudie und existierenden Produktlinienentwicklungen werden Herausforderungen und Lösungsideen aufgezeigt.
The digitization of our society changes the way we live, work, learn, communicate, and collaborate. This disruptive change interacts with all information processes and systems that are important business enablers for the context of digitization since years. Our aim is to support flexibility and agile transformations for both business domains and related information technology with more flexible enterprise information systems through adaptation and evolution of digital enterprise architectures. The present research paper investigates the continuous bottom-up integration of micro-granular architectures for a huge amount of dynamically growing systems and services, like microservices and the Internet of Things, as part of a new digital enterprise architecture. To integrate micro granular architecture models to living architectural model versions we are extending more traditional enterprise architecture reference models with state of art elements for agile architectural engineering to support the digitization of products, services, and processes.
The second Digital Enterprise Computing Conference DEC 16 at the Herman Hollerith Center in Böblingen brings together students, researchers, and practitioners to discuss solutions, experiences, and future developments for the digital transformation. Digitization of business and IT defines the conference agenda: technology acceptance, digital transformation, digital business & administration, digital process challenges, analytics, and big data & data processing.
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.
Digitization is more than using digital technologies to transfer data and perform computations and tasks. Digitization embraces disruptive effects of digital technologies on economy and society. To capture these effects, two perspectives are introduced, the product and the value-creation perspective. In the product perspective, digitization enables the transition from material, static products to interactive and configurable services. In the value-creation perspective, digitization facilitates the transition from centralized, isolated models of value creation, to bidirectional, co-creation oriented approaches of value creation.
Software development consists to a large extent of human-based processes with continuously increasing demands regarding interdisciplinary team work. Understanding the dynamics of software teams can be seen as highly important to successful project execution. Hence, for future project managers, knowledge about non-technical processes in teams is significant. In this paper, we present a course unit that provides an environment in which students can learn and experience the role of different communication patterns in distributed agile software development. In particular, students gain awareness about the importance of communication by experiencing the impact of limitations of communication channels and the effects on collaboration and team performance. The course unit presented uses the controlled experiment instrument to provide the basic organization of a small software project carried out in virtual teams. We provide a detailed design of the course unit to allow for implementation in further courses. Furthermore, we provide experiences obtained from implementing this course unit with 16 graduate students. We observed students struggling with technical aspects and team coordination in general, while not realizing the importance of communication channels (or their absence). Furthermore, we could show the students that lacking communication protocols impact team coordination and performance regardless of the communication channels used.
Purpose – This paper aims to complement the current understanding about user engagement in electronic word-of-mouth (eWoM) communications across online services and product communities. It examines the effect of the senders’ prior experience with products and services, and their extent of acquaintance with other community members, on user engagement with the eWoM.
Design/methodology/approach – The study used a sample of 576 unique user postings from the corporate fan page of two German firms: a service community of a telecom provider and a product community of a car manufacturer. Multiple regression analysis is used to test the conceptual model.
Findings – Senders’ prior experience and acquaintance positively affect user engagement with eWoM, and these effects differ across communities for products and services and across their influence on “likes” and “comments”. The results also suggest that communities for products are orientated toward information sharing, while those discussing services engage in information building.
Research limitations/implications – This research explains mechanisms of user engagement with eWoM and opens directions for future research around motives, content and social media tools within the structures of online communities. The insights on information-handling dimensions of online tools and antecedents to their use contribute to the research on two prioritized topics by the Marketing Science Institute – "Measuring and
Communicating the Value of Online Marketing Activities and Investments" and "Leveraging Digital/Social/Mobile Technology".
Practical implications – This research offers insights for firms to leverage user engagement and facilitate eWoM generation through members who have a higher number of acquaintances or who have more experience with the product or service. Executives should concentrate their community engagement strategies on the identification and utilization of power users. The conceptualization and empirical test about the role of likes and comments will help social media managers to create and better capture value from their social media metrics.
Originality/value – The insights about the underlying factors that influence engagement with eWoM advance our understanding about the usage of online content.
Wie sieht eine erfolgreiche Einführung von Industrie 4.0 aus? Dieses Buch stellt das Konzept, die Paradigmen und relevanten Technologien von Industrie 4.0 sowie deren Gesamtzusammenhänge systematisch vor. Entgegen der gängigen, rein technologischen und anwendungsbezogenen Betrachtungsweise, führt das Buch zusätzlich strategische, taktische und operative Betrachtungsebenen zu einem integrativen Strang zusammen. Zentrales Herzstück dabei ist ein Vorgehensmodell, das den Handlungsbedarf auf strategischer und operativer Ebene beschreibt. Ein Praxisfall, unterschiedliche Industrie 4.0-Use Cases und namhafte Experten aus Forschung und Praxis machen diese Lektüre interessant für Neueinsteiger, aber auch für Umsetzungsinteressierte des mittleren und oberen Managements, die eine neue Sichtweise auf die Komplexität des Themas gewinnen möchten. Das Glossar macht das Buch zum wertvollen Nachschlagewerk für das Thema Industrie 4.0.
This book presents emerging trends in the evolution of service-oriented and enterprise architectures. New architectures and methods of both business and IT are integrating services to support mobility systems, internet of things, ubiquitous computing, collaborative and adaptive business processes, big data, and cloud ecosystems. They inspire current and future digital strategies and create new opportunities for the digital transformation of next digital products and services. Services Oriented Architectures (SOA) and Enterprise Architectures (EA) have emerged as a useful framework for developing interoperable, large-scale systems, typically implementing various standards, like web services, REST, and microservices. Managing the adaptation and evolution of such systems presents a great challenge. Service-Oriented Architecture enables flexibility through loose coupling, both between the services themselves and between the IT organizations that manage them. Enterprises evolve continuously by transforming and extending their services, processes and information systems. Enterprise Architectures provide a holistic blueprint to help define the structure and operation of an organization with the goal of determining how an organization can most effectively achieve its objectives. The book proposes several approaches to address the challenges of the service-oriented evolution of digital enterprise and software architectures.
Enterprise Social Networks : Einführung in die Thematik und Ableitung relevanter Forschungsfelder
(2016)
Die Relevanz von Enterprise Social Networks (ESN) für den Arbeitsalltag in Wissensorganisationen steigt. Diese Netzwerke unterstützen die Kommunikation, Zusammenarbeit und das Wissensmanagement in Unternehmen. Der vorliegende Beitrag beinhaltet eine Einführung in das Themengebiet ESN und skizziert Einsatzmöglichkeiten, Potenziale und Herausforderungen. Er gibt einen Überblick zu wesentlichen Fachartikeln, die eine Übersicht zu Forschungsarbeiten im Bereich ESN beinhalten. Anschließend werden einzelne Forschungsbeiträge analysiert und weitere Forschungspotenziale abgeleitet. Dies führt zu acht Erfolg versprechenden Bereichen für die weitere Forschung: 1) Nutzerverhalten, 2) Effekte des Einsatzes von ESN, 3) Management, Leadership und Governance für ESN, 4) Wertbestimmung und Erfolgsmessung, 5) kulturelle Auswirkungen, 6) Architektur und Design von ESN, 7) Theorien, Forschungsdesigns und Methoden, sowie 8) weitere Herausforderungen in Bezug auf ESN. Der Beitrag charakterisiert diese Bereiche und formuliert exemplarisch offene Fragestellungen für die zukünftige Forschung.
Dieser Herausgeberband beleuchtet die Erfolgsfaktoren für die Implementierung und den Betrieb von ESN. Der erste Teil des Bandes umfasst akademische Beiträge zur aktuellen Forschung und beinhaltet fundierte wissenschaftliche Konzepte für den Einsatz von ESN. In den Beiträgen des zweiten Teils stehen Konzepte aus der Praxis im Fokus, bevor im dritten Teil Anwendererfahrungen in Form von Fallstudien betrachtet werden. In der digitalen Transformation setzen Unternehmen verstärkt Social Software ein, um positive Wirkungseffekte in den Bereichen Mitarbeiterzufriedenheit, Wissenstransfer, Innovationsdynamik, Produktivität oder Führungsakzeptanz zu erzielen. Diese Enterprise Social Networks (ESN) verändern die interne Kommunikation und erlauben einen ungebremsten Informationsfluss und überwinden organisationale Silos. Jedoch werden die in ESN gesetzten Erwartungen in der Praxis oft nicht erfüllt. Geringe Nutzungsgrade, mangelnde Einbindung in Geschäftsprozesse und unklare Wirkungszusammenhänge induzieren die Frage, ob sich eine Investition in ESN lohnt. Spitzenforschung, Thought Leader in der Unternehmenspraxis und führende Experten beschreiben wesentliche Strategien, Konzepte und Impulse für das Management der Enterprise Social Networks.
This paper provides an introduction to the topic of enterprise social networks (ESN) and illustrates possible applications, potentials, and challenges for future research. It outlines an analysis of research papers containing a literature overview in the field of ESN. Subsequently, single relevant research papers are analysed and further research potentials derived therefrom. This yields seven promising areas for further research: (1) user behaviour; (2) effects of ESN usage; (3) management, leadership, and governance; (4) value assessment and success measurement; (5) cultural effects, (6) architecture and design of ESN; and (7) theories, research designs and methods. This paper characterises these areas and articulates further research directions.
In dieser Arbeit werden verschiedene Lösungsansätze für die Konstruktion von Display-Walls in digitalen Schowrooms gesammelt und evaluiert. Besonders interessant ist dabei ein digitaler Ansatz, bei dem die Ausgabegeräte von den Zuspielern getrennt sind. Diese Lösung verspricht eine große Flexibilität und eine einfache Erweiterbarkeit im Vergleich zu herkömmlichen Ansätzen. Um diese Aussagen zu prüfen, soll ein funktionaler Prototyp auf Basis der Ergebnisse entwickelt werden.
Durch das breite Angebot an Cloud-Plattformen fällt es schwer, die passende Plattform für einen bestimmten Anwendungsfall auszuwählen. Es wird häufig die Frage gestellt, welche Unterschiede die einzelnen Cloud Plattformen aufweisen und welche Eigenschaften und Vorteile jede einzelne besitzt. In diesem Artikel werden deshalb zunächst die Prinzipien von Cloud Computing näher gebracht. Außerdem werden die Plattformen Amazon Web Services, Microsoft Azure, Pivotal Cloud Foundry und OpenStack näher beleuchtet und auf die Aspekte der Skalierung und Lastverteilung untersucht.
Nowadays there is a rich diversity of sleep monitoring systems available on the market. They promise to offer information about sleep quality of the user by recording a limited number of vital signals, mainly heart rate and body movement. Typically, fitness trackers, smart watches, smart shirts, smartphone applications or patches do not provide access to the raw sensor data. Moreover, the sleep classification algorithm and the agreement ratio with the gold standard, polysomnography (PSG) are not disclosed. Some commercial systems record and store the data on the wearable device, but the user needs to transfer and import it into specialised software applications or return it to the doctor, for clinical evaluation of the data set. Thus an immediate feedback mechanism or the possibility of remote control and supervision are lacking. Furthermore, many such systems only distinguish between sleep and wake states, or between wake, light sleep and deep sleep. It is not always clear how these stages are mapped to the four known sleep stages: REM, NREM1, NREM2, NREM3-4. [1] The goal of this research is to find a reduced complexity method to process a minimum number of bio vital signals, while providing accurate sleep classification results. The model we propose offers remote control and real time supervision capabilities, by using Internet of Things (IoT) technology. This paper focuses on the data processing method and the sleep classification logic. The body sensor network representing our data acquisition system will be described in a separate publication. Our solution showed promising results and a good potential to overcome the limitations of existing products. Further improvements will be made and subjects with different age and health conditions will be tested.
Context: The current transformation of automotive development towards innovation, permanent learning and adapting to changes are directing various foci on the integration of agile methods. Although, there have been efforts to apply agile methods in the automotive domain for many years, a wide-spread adoption has not yet taken place.
Goal: This study aims to gain a better understanding of the forces that prevent the adoption of agile methods.
Method: Survey based on 16 semi-structured interviews from the automotive domain. The results are analyzed by means of thematic coding.
Results: Forces that prevent agile adoption are mainly of organizational, technical and social nature and address inertia, anxiety and context factors. Key challenges in agile adoption are related to transforming organizational structures and culture, achieving faster software release cycles without loss of quality, the importance of software reuse in combination with agile practices, appropriate quality assurance measures, and the collaboration with suppliers and other disciplines such as mechanics.
Conclusion: Significant challenges are imposed by specific characteristics of the automotive domain such as high quality requirements and many interfaces to surrounding rigid and inflexible processes. Several means are identified that promise to overcome these challenges.
Unternehmen befassen sich in jüngster Zeit verstärkt mit der Nutzung von Social Media in der internen Kommunikation und Zusammenarbeit. So genannte Enterprise Social Networks (ESN) bieten integrierte Plattformen mit Profilen, Blogs, gemeinsamer Dokumentenverwaltung, Wikis, Chats, Gruppen- und Kommentarfunktionen für die unternehmensinterne Anwendung. Sehr häufig sind damit umfangreiche Investitionen verbunden. Die Budgets werden im Kern für die IT verwendet – „weiche Faktoren“ bleiben häufig außen vor. Dies kann zu erheblichen Problemen bei der Akzeptanz entsprechender Plattformen führen. Daher sind weitere Maßnahmen im Bereich der Steuerung der Einführung und des Betriebs von ESN erforderlich, die sich unter dem Begriff der Governance zusammenfassen lassen. Das Konstrukt Governance bezieht sich auf Art und Umfang der Rollen und Aufgaben zur Steuerung der Nutzung von ESN. Der vorliegende Beitrag beleuchtet mögliche Governancemodelle für die Einführung und Weiterentwicklung von ESN. Die Resultate der vorliegenden Forschung wurden auf der Grundlage einer fundierten Literaturanalyse sowie der explorativen Befragung verantwortlicher Executives für die Nutzung von ESN in deutschen Großunternehmen erzielt. Dabei weisen die Implikationen der qualitativen Datenanalyse auf Zusammenhänge hin, die sich als Ausgangshypothesen für weitere Forschungsarbeiten nutzen lassen.
For decades, Software Process Improvement (SPI) programs have been implemented, inter alia, to improve quality and speed of software development. To set up, guide, and carry out SPI projects, and to measure SPI state, impact, and success, a multitude of different SPI approaches and considerable experience are available. SPI addresses many aspects ranging from individual developer skills to entire organizations. It comprises for instance the optimization of specific activities in the software lifecycle as well as the creation of organization awareness and project culture. In the course of conducting a systematic mapping study on the state-of-the-art in SPI from a general perspective, we observed Global Software Engineering (GSE) becoming a topic of interest in recent years. Therefore, in this paper, we provide a detailed investigation of those papers from the overall systematic mapping study that were classified as addressing SPI in the context of GSE. From the main study’s result set, a set of 30 papers dealing with GSE was selected for an in-depth analysis using the systematic review instrument to study the contributions and to develop an initial picture of how GSE is considered from the perspective of SPI. Our findings show the analyzed papers delivering a substantial discussion of cultural models and how such models can be used to better address and align SPI programs with multi-national environments. Furthermore, experience is shared discussing how agile approaches can be implemented in companies working at the global scale. Finally, success factors and barriers are studied to help companies implementing SPI in a GSE context.
Analysis of multicellular patterns is required to understand tissue organizational processes. By using a multi-scale object oriented image processing method, the spatial information of cells can be extracted automatically. Instead of manual segmentation or indirect measurements, such as general distribution of contrast or flow, the orientation and distribution of individual cells is extracted for quantitative analysis. Relevant objects are identified by feature queries and no low-level knowledge of image processing is required.
Im Rahmen der wissenschaftlichen Vertiefung soll auf Basis einer vorhandenen Gebrauchstauglichkeitsanalyse einer mobilen Applikation das Risikomanagement geplant und durchgeführt werden. Die Applikation ist Bestandteil eines In vitro-Diagnostikums, welches transplantierten Patienten im Alltag bei der Bewertung ihrer Blutwerte und des Gesundheitszustandes, sowie bei der korrekt dosierten Einnahme der erforderlichen Medikamente unterstützen soll.
Industrie 4.0 - Ausblick
(2016)
Für Unternehmen ist es wichtig, frühzeitig die strategischen Weichen für ihre Industrie 4.0-Stoßrichtung zu stellen und Erfahrung im Umgang mit Industrie 4.0-Technologien aufzubauen. Allerdings werden einige der Industrie 4.0-relevanten Technologien voraussichtlich erst in 5 bis 10 Jahren ihr Effizienzpotential voll ausschöpfen können. Die Einführung von Industrie 4.0 betrifft nahezu alle Bereiche eines Unternehmens und ist deshalb nicht nur als digitale Transformation, sondern auch als Kulturwandel in der Organisation zu verstehen, zu planen und aktiv zu managen. Themen wie Datenschutz und IT-Sicherheit sind nicht nur wichtige Voraussetzungen für eine erfolgreiche Industrie 4.0-Einführung, sondern müssen als wesentliche Akzeptanz- und Erfolgsfaktoren konsequent und durchgängig in den digitalen Systemen verankert werden.
KMUs sehen sich häufig aus finanziellen Gründen nicht in der Lage, in grundlegende Technologien der Industrie 4.0 zu investieren. So wird als Hauptvorbehalt eine vermeintlich schlechte Kosten-Nutzen-Relation bzw. langfristige Pay-Back-Zyklen angegeben. Die aktuellen Herausforderungen liegen derzeit eher bei der immer weiter voranschreitenden Internationalisierung sowie dem ansteigenden Innovationsdruck durch den Wettbewerb. Natürlich ist bekannt, dass die zunehmende Vernetzung der Produktionsanlagen in der Industrie 4.0 zudem Risiken in der IT- und Datensicherheit mit sich bringt. Auch Datenqualitäts-, Stabilitäts-, Schnittstellenprobleme oder rechtliche Probleme sind ausschlaggebend für die Verunsicherung der Unternehmen. Durch die zukünftig immer weiter ansteigende Vernetzung zwischen Unternehmen und Stakeholdern, müssen sich insbesondere Zulieferunternehmen in der Pflicht sehen, das Thema Industrie 4.0 aufzugreifen und sich damit auseinander zu setzen. Gerade diese Unternehmen müssen sich vor Augen führen, dass sie nur durch den zukünftigen Einsatz geeigneter Informations- und Kommunikationstechnologien noch in der Lage sein werden, Teil der Wertschöpfungskette zwischen ihren Kunden und Lieferanten zu sein.
In the last decades, several driving systems were developed to improve the driving behaviour in energy efficiency or safety. However, these driving systems cover either the area of energy-efficiency or safety. Furthermore, they do not consider the stress level of the driver when showing a recommendation, although stress can lead to an unsafe or inefficient driving behaviour. In this paper, an approach is presented to consider the driver stress level in a driving system for safe and energy-efficient driving behaviour. The driving system tries to suppress a recommendation when the driver is in stress in order not to stress the driver additionally with recommendations in a stressful driving situation. This can lead to an increase in the road safety and in the user acceptance of the driving system, as the driver is not getting bothered or stressed by the driving system.
The evaluation of the approach showed, that the driving system
is able to show recommendations to the driver, while also reacting
to a high stress level by suppressing recommendations in
order not to stress the driver additionally.
Die Themen der Konferenz gehen von Präsentationen historischer Inhalte mit interaktiven Systemen (in Museen), über die Erstellung einer Risikomanagementakte im Medizinumfeld, bis zu den Interaktionsgeräten in VR-Anwendungen. In dieser Ausgabe der Informatics Inside ist der inhärent interdisziplinäre Charakter der Informatik mehr denn je spürbar. Denn die Informatik ist auch "inside" der Kunst, der Medizin, der Chemie und der Textilien.
Diese Arbeit befasst sich mit möglichen Eingabegeräten für VR-Anwendungen, die mit HMDs betrachtet werden. Es wird überprüft, ob grundlegende Interaktionsmöglichkeiten wie Navigation durch den Raum, Texteingabe und Objektauswahl mit den evaluierten Geräten umsetzbar ist. Untersucht werden der Leap Motion Controller, die Kinect 2, das Myo-Armband, der Xbox-Controller und die Razer Hydra.
On the way to achieving higher degrees of autonomy for vehicles in complicated, ever changing scenarios, the localization problem poses a very important role. Especially the Simultaneous Localization and Mapping (SLAM) problem has been studied greatly in the past. For an autonomous system in the real world, we present a very cost-efficient, robust and very precise localization approach based on GraphSLAM and graph optimization using radar sensors. We are able to prove on a dynamically changing parking lot layout that both mapping and localization accuracy are very high. To evaluate the performance of the mapping algorithm, a highly accurate ground truth map generated from a total station was used. Localization results are compared to a high precision DGPS/INS system. Utilizing these methods, we can show the strong performance of our algorithm.
Bei der Bayer AG wird als Lösung für das Enterprise Social Network IBM Connections eingesetzt. Bayer verfolgt das Ziel, die Mitarbeiter/innen weltweit zu vernetzen, die Kommunikation über Bereichsgrenzen hinweg zu unterstützen und um einen Wissens- und Expertenpool bereitzustellen. Im Rahmen eines Relaunches wurde 2012 Connections@Bayer, das vorher nur in Teilkonzernen verfügbar war, auf das gesamte Unternehmen ausgerollt. In einem weiteren Relaunch 2014 führte das Unternehmen ein Update auf die Version 4.5 und eine umfangreiche Kommunikationskampagne durch, die unter den Mitarbeiter/innen Aufmerksamkeit für die Kommunikationsplattform schuf und Neugier weckte. Darin wurde eine Analyse der Schlüsselvorteile der Nutzung von Connections durchgeführt, acht Kernnachrichten erarbeitet und diese auf diversen Kommunikationskanälen im Unternehmen verbreitet. Zudem ließen sich durch die Verwendung von Testimonials die Vorteile für alle Mitarbeitergruppen darstellen. Dieser Relaunch war erfolgreich: Die Nutzerzahlen konnten erweitert werden, die Mitarbeiterzufriedenheit stieg an. Die vorliegende Fallstudie stellt anschaulich dar, dass ein von einer effektiven Kommunikationskampagne begleiteter Relaunch eines Enterprise Social Networks einen nachhaltigen Erfolg herbeiführen kann.
The digital transformation of our society changes the way we live, work, learn, communicate, and collaborate. The digitization of software-intensive products and services is enabled basically by four megatrends: Cloud computing, big data mobile systems, and social technologies. This disruptive change interacts with all information processes and systems that are important business enablers for the current digital transformation. The internet of things, social collaboration systems for adaptive case management, mobility systems and services for big data in cloud services environments are emerging to support intelligent user-centered and social community systems. Modern enterprises see themselves confronted with an ever growing design space to engineer business models of the future as well as their IT support, respectively. The decision analytics in this field becomes increasingly complex and decision support, particularly for the development and evolution of sustainable enterprise architectures (EA), is duly needed. With the advent of intelligent user-centered and social community systems, the challenging decision processes can be supported in more flexible and intuitive ways. Tapping into these systems and techniques, the engineers and managers of the enterprise architecture become part of a viable enterprise, i.e. a resilient and continuously evolving system that develops innovative business models.
Digital companies need information systems to implement their business processes end-to-end. BPM systems are promising candidates for that, because they are highly adaptable due to their business process model-driven operation mode. End-to-end processes contain different types of sub-processes that are either procedural, data-driven or business rule-based. Modern BPM systems support modeling notations for all these types of sub-processes. Moreover, end-to-end processes contain parts of shadow processing, so consequently, they must be supported in a performant way, too. BPMN seems to be the adequate notation for modeling these parts due to its procedural nature. Further, BPMN provides several elements that enable the modeling of parallel executions which are very interesting for accelerating shadow processing parts of the process. The present paper will observe the limitations and potentials of BPM systems for a high-performance execution of BPMN models representing shadow processing parts of a business process.