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Institute
- Fakultät IV - Wirtschaft und Informatik (54) (remove)
Objective
The study’s objective was to assess factors contributing to the use of smart devices by general practitioners (GPs) and patients in the health domain, while specifically addressing the situation in Germany, and to determine whether, and if so, how both groups differ in their perceptions of these technologies.
Methods
GPs and patients of resident practices in the Hannover region, Germany, were surveyed between April and June 2014. A total of 412 GPs in this region were invited by email to participate via an electronic survey, with 50 GPs actually doing so (response rate 12.1%). For surveying the patients, eight regional resident practices were visited by study personnel (once each). Every second patient arriving there (inclusion criteria: of age, fluent in German) was asked to take part (paper-based questionnaire). One hundred and seventy patients participated; 15 patients who did not give consent were excluded.
Results
The majority of the participating patients (68.2%, 116/170) and GPs (76%, 38/50) owned mobile devices. Of the patients, 49.9% (57/116) already made health-related use of mobile devices; 95% (36/38) of the participating GPs used them in a professional context. For patients, age (P < 0.001) and education (P < 0.001) were significant factors, but not gender (P > 0.99). For doctors, neither age (P = 0.73), professional experience (P > 0.99) nor gender (P = 0.19) influenced usage rates. For patients, the primary use case was obtaining health (service)-related information. For GPs, interprofessional communication and retrieving information were in the foreground. There was little app-related interaction between both groups.
Conclusions
GPs and patients use smart mobile devices to serve their specific interests. However, the full potentials of mobile technologies for health purposes are not yet being taken advantage of. Doctors as well as other care providers and the patients should work together on exploring and realising the potential benefits of the technology.
Objective: The study’s objective was to assess factors contributing to the use of smart devices by general practitioners (GPs) and patients in the health domain, while specifically addressing the situation in Germany, and to determine whether, and if so, how both groups differ in their perceptions of these technologies.
Methods: GPs and patients of resident practices in the Hannover region, Germany, were surveyed between April and June 2014. A total of 412 GPs in this region were invited by email to participate via an electronic survey, with 50 GPs actually doing so (response rate 12.1%). For surveying the patients, eight regional resident practices were visited by study personnel (once each). Every second patient arriving there (inclusion criteria: of age, fluent in German) was asked to take part (paper-based questionnaire). One hundred and seventy patients participated; 15 patients who did not give consent were excluded.
Results: The majority of the participating patients (68.2%, 116/170) and GPs (76%, 38/50) owned mobile devices. Of the patients, 49.9% (57/116) already made health-related use of mobile devices; 95% (36/38) of the participating GPs used them in a professional context. For patients, age (P<0.001) and education (P<0.001) were significant factors, but not gender (P>0.99). For doctors, neither age (P¼0.73), professional experience (P>0.99) nor gender (P¼0.19) influenced usage rates. For patients, the primary use case was obtaining health (service)-related information. For GPs, interprofessional communication and retrieving information were in the foreground. There was little app-related interaction between both groups.
Conclusions: GPs and patients use smart mobile devices to serve their specific interests. However, the full potentials of mobile technologies for health purposes are not yet being taken advantage of. Doctors as well as other care providers and the patients should work together on exploring and realising the potential benefits of the technology.
In this paper, five ontologies are described, which include the event concepts. The paper provides an overview and comparison of existing event models. The main criteria for comparison are that there should be possibilities to model events with stretch in the time and location and participation of objects; however, there are other factors that should be taken into account as well. The paper also shows an example of using ontologies in complex event processing.
OSGi in Cloud Environments
(2013)
The paper provides a comprehensive overview of modeling and pricing cyber insurance and includes clear and easily understandable explanations of the underlying mathematical concepts. We distinguish three main types of cyber risks: idiosyncratic, systematic, and systemic cyber risks. While for idiosyncratic and systematic cyber risks, classical actuarial and financial mathematics appear to be well-suited, systemic cyber risks require more sophisticated approaches that capture both network and strategic interactions. In the context of pricing cyber insurance policies, issues of interdependence arise for both systematic and systemic cyber risks; classical actuarial valuation needs to be extended to include more complex methods, such as concepts of risk-neutral valuation and (set-valued) monetary risk measures.
High-performance firms typically have two features in common: (i) they produce in more than one country and (ii) they produce more than one product. In this paper, we analyze the internationalization strategies of multi-product firms. Guided by several new stylized facts, we develop a theoretical model to determine optimal modes of market access at the firm–product level. We find that the most productive firmssell core varieties via foreign direct investment and export products with intermediate productivity. Shocks to trade costs and technology affect the endogenous decision to export or produce abroad at the product-level and, in turn, the relative productivity between parents and affiliates.
Enterprise apps on mobile devices typically need to communicate with other system components by consuming web services. Since most of the current mobile device platforms (such as Android) do not provide built-in features for consuming SOAP services, extensions have to be designed. Additionally in order to accommodate the typical enhanced security requirements of enterprise apps, it is important to be able to deal with SOAP web service security extensions on client side. In this article we show that neither the built-in SOAP capabilities for Android web service clients are sufficient for enterprise apps nor are the necessary security features supported by the platform as is. After discussing different existing extensions making Android devices SOAP capable we explain why none of them is really satisfactory in an enterprise context. Then we present our own solution which accommodates not only SOAP but also the WS-Security features on top of SOAP. Our solution heavily relies on code generation in order to keep the flexibility benefits of SOAP on one hand while still keeping the development effort manageable for software development. Our approach provides a good foundation for the implementation of other SOAP extensions apart from security on the Android platform as well. In addition our solution based on the gSOAP framework may be used for other mobile platforms in a similar manner.
Music streaming platforms offer music listeners an overwhelming choice of music. Therefore, users of streaming platforms need the support of music recommendation systems to find music that suits their personal taste. Currently, a new class of recommender systems based on knowledge graph embeddings promises to improve the quality of recommendations, in particular to provide diverse and novel recommendations. This paper investigates how knowledge graph embeddings can improve music recommendations. First, it is shown how a collaborative knowledge graph can be derived from open music data sources. Based on this knowledge graph, the music recommender system EARS (knowledge graph Embedding-based Artist Recommender System) is presented in detail, with particular emphasis on recommendation diversity and explainability. Finally, a comprehensive evaluation with real-world data is conducted, comparing of different embeddings and investigating the influence of different types of knowledge.
Complex Event Processing (CEP) is a modern software technology for the dynamic analysis of continuous data streams. CEP is able of searching extremely large data streams in real time for the presence of event patterns. So far, specifying event patterns of CEP rules is still a manual task based on the expertise of domain experts. This paper presents a novel batinspired swarm algorithm for automatically mining CEP rule patterns that express the relevant causal and temporal relations hidden in data streams. The basic suitability and performance of the approach is proven by extensive evaluation with both synthetically generated data and real data from the traffic domain.
M2M (machine-to-machine) systems use various communication technologies for automatically monitoring and controlling machines. In M2M systems, each machine emits a continuous stream of data records, which must be analyzed in real-time. Intelligent M2M systems should be able to diagnose their actual states and to trigger appropriate actions as soon as critical situations occur. In this paper, we show how complex event processing (CEP) can be used as the key technology for intelligent M2M systems. We provide an event-driven architecture that is adapted to the M2M domain. In particular, we define different models for the M2M domain, M2M machine states and M2M events. Furthermore, we present a general reference architecture defining the main stages of processing machine data. To prove the usefulness of our approach, we consider two real-world examples ‘solar power plants’ and ‘printers’, which show how easily the general architecture can be extended to concrete M2M scenarios.
In this article, we present the software architecture of a new generation of advisory systems using Intelligent Agent and Semantic Web technologies. Multi-agent systems provide a well-suited paradigm to implement negotiation processes in a consultancy situation. Software agents act as clients and advisors, using their knowledge to assist human users. In the presented architecture, the domain knowledge is modeled semantically by means of XML-based ontology languages such as OWL. Using an inference engine, the agents reason, based on their knowledge to make decisions or proposals. The agent knowledge consists of different types of data: on the one hand, private data, which has to be protected against unauthorized access; and on the other hand, publicly accessible knowledge spread over different Web sites. As in a real consultancy, an agent only reveals sensitive private data, if they are indispensable for finding a solution. In addition, depending on the actual consultancy situation, each agent dynamically expands its knowledge base by accessing OWL knowledge sources from the Internet. Due to the standardization of OWL, knowledge models easily can be shared and accessed via the Internet. The usefulness of our approach is proved by the implementation of an advisory system in the Semantic E-learning Agent (SEA) project, whose objective is to develop virtual student advisers that render support to university students in order to successfully organize and perform their studies.
Mobile crowdsourcing refers to systems where the completion of tasks necessarily requires physical movement of crowdworkers in an on-demand workforce. Evidence suggests that in such systems, tasks often get assigned to crowdworkers who struggle to complete those tasks successfully, resulting in high failure rates and low service quality. A promising solution to ensure higher quality of service is to continuously adapt the assignment and respond to failure-causing events by transferring tasks to better-suited workers who use different routes or vehicles. However, implementing task transfers in mobile crowdsourcing is difficult because workers are autonomous and may reject transfer requests. Moreover, task outcomes are uncertain and need to be predicted. In this paper, we propose different mechanisms to achieve outcome prediction and task coordination in mobile crowdsourcing. First, we analyze different data stream learning approaches for the prediction of task outcomes. Second, based on the suggested prediction model, we propose and evaluate two different approaches for task coordination with different degrees of autonomy: an opportunistic approach for crowdshipping with collaborative, but non-autonomous workers, and a market-based model with autonomous workers for crowdsensing.
Dieser hier um die Einleitung ergänzte Text ist zuerst in leicht gekürzter Fassung im Ifo-Schnelldienst 17/2010 in München erschienen; ebenso unter: http://www.brainlogs.de/Geschlechtsverwirrung und unter http://www.streitbar.eu sowie unter http://www.odww.de/Hochschulpolitik. Der Autor geht der Frage nach, ob Frauenquoten ein legitimes Instrument zur Durchsetzung der Gleichberechtigung sind.
Eine Unternehmensgründung ist ein komplexes Vorhaben, dessen Risiken soweit wie möglich vermieden bzw. minimiert werden sollten. Dabei hilft eine sorgfältige Planung und Vorbereitung. Der Gründungsprozess lässt sich — von der Prüfung der Grundvoraussetzungen über den Business Plan, die Vorbereitung der Gründung sowie deren Realisierung bis zur Stabilisierung des Unternehmens — in fünf Phasen einteilen.
There are many aspects of code quality, some of which are difficult to capture or to measure. Despite the importance of software quality, there is a lack of commonly accepted measures or indicators for code quality that can be linked to quality attributes. We investigate software developers’ perceptions of source code quality and the practices they recommend to achieve these qualities. We analyze data from semi-structured interviews with 34 professional software developers, programming teachers and students from Europe and the U.S. For the interviews, participants were asked to bring code examples to exemplify what they consider good and bad code, respectively. Readability and structure were used most commonly as defining properties for quality code. Together with documentation, they were also suggested as the most common target properties for quality improvement. When discussing actual code, developers focused on structure, comprehensibility and readability as quality properties. When analyzing relationships between properties, the most commonly talked about target property was comprehensibility. Documentation, structure and readability were named most frequently as source properties to achieve good comprehensibility. Some of the most important source code properties contributing to code quality as perceived by developers lack clear definitions and are difficult to capture. More research is therefore necessary to measure the structure, comprehensibility and readability of code in ways that matter for developers and to relate these measures of code structure, comprehensibility and readability to common software quality attributes.
Metagenomic studies use high-throughput sequence data to investigate microbial communities in situ. However, considerable challenges remain in the analysis of these data, particularly with regard to speed and reliable analysis of microbial species as opposed to higher level taxa such as phyla. We here present Genometa, a computationally undemanding graphical user interface program that enables identification of bacterial species and gene content from datasets generated by inexpensive high-throughput short read sequencing technologies. Our approach was first verified on two simulated metagenomic short read datasets, detecting 100% and 94% of the bacterial species included with few false positives or false negatives. Subsequent comparative benchmarking analysis against three popular metagenomic algorithms on an Illumina human gut dataset revealed Genometa to attribute the most reads to bacteria at species level (i.e. including all strains of that species) and demonstrate similar or better accuracy than the other programs. Lastly, speed was demonstrated to be many times that of BLAST due to the use of modern short read aligners. Our method is highly accurate if bacteria in the sample are represented by genomes in the reference sequence but cannot find species absent from the reference. This method is one of the most user-friendly and resource efficient approaches and is thus feasible for rapidly analysing millions of short reads on a personal computer.
Untersuchungen zu Berufen der Wirtschaftsinformatik bleiben weiterhin
interessant, wenn sie helfen können, dem mittlerweile länger anhaltenden
IT-Fachkräftemangel entgegenzuwirken. Eine Untersuchung der Hochschule
Hannover zu Wirtschaftsinformatikern/-informatikerinnen in den ersten zehn Jahren im Beruf zeigt deren berufliche Ziele und die berufliche Zufriedenheit, die sie erlangen. Deutlich wird, dass Frauen und Männer das Arbeitsklima und die Arbeitsbedingungen sehr unterschiedlich wahrnehmen und daher auch unterschiedlich zufrieden sind. Dabei bemängeln Frauen vor allem Merkmale, die mit „fehlender Fairness“ zu beschreiben sind.
Vor der Abgabe einer Studien- oder Abschlussarbeit ist dringend eine sorgfältige Überarbeitung in Form einer Endredaktion vorzunehmen, um eine gute Bewertung der Arbeit nicht zu gefährden. Dies ist einfach; denn das Vorgehen ist schlicht und wenig aufwändig. Daher wäre es besonders ärgerlich, einfache Fehler nicht zu beheben und dafür Abzüge bei der Bewertung der Arbeit hinzunehmen. Für eine Endredaktion wird hiermit eine Anleitung vorgelegt.
With the increasing significance of information technology, there is an urgent need for adequate measures of information security. Systematic information security management is one of most important initiatives for IT management. At least since reports about privacy and security breaches, fraudulent accounting practices, and attacks on IT systems appeared in public, organizations have recognized their responsibilities to safeguard physical and information assets. Security standards can be used as guideline or framework to develop and maintain an adequate information security management system (ISMS). The standards ISO/IEC 27000, 27001 and 27002 are international standards that are receiving growing recognition and adoption. They are referred to as “common language of organizations around the world” for information security. With ISO/IEC 27001 companies can have their ISMS certified by a third-party organization and thus show their customers evidence of their security measures.