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The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.
This paper demonstrates an innovative and simple solution for obstacle detection and collision avoidance of unmanned aerial vehicles (UAVs) optimized for and evaluated with quadrotors. The sensors exploited in this paper are low-cost ultrasonic and infrared range finders, which are much cheaper though noisier than more expensive sensors such as laser scanners. This needs to be taken into consideration for the design, implementation, and parametrization of the signal processing and control algorithm for such a system, which is the topic of this paper. For improved data fusion, inertial and optical flow sensors are used as a distance derivative for reference. As a result, a UAV is capable of distance controlled collision avoidance, which is more complex and powerful than comparable simple solutions. At the same time, the solution remains simple with a low computational burden. Thus, memory and time-consuming simultaneous localization and mapping is not required for collision avoidance.
Recently, several backpack-mounted systems, also known as personal laser scanning systems, have been developed. They consist of laser scanners or cameras that are carried by a human operator to acquire measurements of the environment while walking. These systems were first designed to overcome the challenges of mapping indoor environments with doors and stairs. While the human operator inherently has the ability to open doors and to climb stairs, the flexible movements introduce irregularities of the trajectory to the system. To compete with other mapping systems, the accuracy of these systems has to be evaluated. In this paper, we present an extensive evaluation of our backpack mobile mapping system in indoor environments. It is shown that the system can deal with the normal human walking motion, but has problems with irregular jittering. Moreover, we demonstrate the applicability of the backpack in a suitable urban scenario.
Background
All international guidelines recommend perioperative antibiotic prophylaxis (PAB) should be routinely administered to patients undergoing cardiac surgery. However, the duration of PAB is heterogeneous and controversial.
Methods
Between 01.01.2011 and 31.12.2011, 1096 consecutive cardiac surgery patients were assigned to one of two groups receiving PAB with a second-generation cephalosporin for either 56 h (group I) or 32 h (group II). Patients’ characteristics, intraoperative data, and the in-hospital follow-up were analysed. Primary endpoint was the incidence of surgical site infection (deep and superficial sternal wound-, and vein harvesting site infection; DSWI/SSWI/VHSI). Secondary endpoints were the incidence of respiratory-, and urinary tract infection, as well as the mortality rate.
Results
615/1096 patients (56,1%) were enrolled (group I: n = 283 versus group II: n = 332). There were no significant differences with regard to patient characteristics, comorbidities, and procedure-related variables. No statistically significant differences were demonstrated concerning primary and secondary endpoints. The incidence of DSWI/SSWI/VHSI were 4/283 (1,4%), 5/283 (1,7%), and 1/283 (0,3%) in group I versus 6/332 (1,8%), 9/332 (2,7%), and 3/332 (0,9%) in group II (p = 0,76/0,59/0,63). In univariate analyses female gender, age, peripheral arterial obstructive disease, operating-time, ICU-duration, transfusion, and respiratory insufficiency were determinants for nosocomial infections (all ≤ 0,05). Subgroup analyses of these high-risk patients did not show any differences between the two regimes (all ≥ 0,05).
Conclusions
Reducing the duration of PAB from 56 h to 32 h in adult cardiac surgery patients was not associated with an increase of nosocomial infection rate, but contributes to reduce antibiotic resistance and health care costs.
Background
Information extraction techniques that get structured representations out of unstructured data make a large amount of clinically relevant information about patients accessible for semantic applications. These methods typically rely on standardized terminologies that guide this process. Many languages and clinical domains, however, lack appropriate resources and tools, as well as evaluations of their applications, especially if detailed conceptualizations of the domain are required. For instance, German transthoracic echocardiography reports have not been targeted sufficiently before, despite of their importance for clinical trials. This work therefore aimed at development and evaluation of an information extraction component with a fine-grained terminology that enables to recognize almost all relevant information stated in German transthoracic echocardiography reports at the University Hospital of Würzburg.
Methods
A domain expert validated and iteratively refined an automatically inferred base terminology. The terminology was used by an ontology-driven information extraction system that outputs attribute value pairs. The final component has been mapped to the central elements of a standardized terminology, and it has been evaluated according to documents with different layouts.
Results
The final system achieved state-of-the-art precision (micro average.996) and recall (micro average.961) on 100 test documents that represent more than 90 % of all reports. In particular, principal aspects as defined in a standardized external terminology were recognized with f 1=.989 (micro average) and f 1=.963 (macro average). As a result of keyword matching and restraint concept extraction, the system obtained high precision also on unstructured or exceptionally short documents, and documents with uncommon layout.
Conclusions
The developed terminology and the proposed information extraction system allow to extract fine-grained information from German semi-structured transthoracic echocardiography reports with very high precision and high recall on the majority of documents at the University Hospital of Würzburg. Extracted results populate a clinical data warehouse which supports clinical research.
Social interactions as introduced by Web 2.0 applications during the last decade have changed the way the Internet is used. Today, it is part of our daily lives to maintain contacts through social networks, to comment on the latest developments in microblogging services or to save and share information snippets such as photos or bookmarks online.
Social bookmarking systems are part of this development. Users can share links to interesting web pages by publishing bookmarks and providing descriptive keywords for them. The structure which evolves from the collection of annotated bookmarks is called a folksonomy. The sharing of interesting and relevant posts enables new ways of retrieving information from the Web. Users
can search or browse the folksonomy looking at resources related to specific tags or users. Ranking methods known from search engines have been adjusted to facilitate retrieval in social bookmarking systems. Hence, social bookmarking systems have become an alternative or addendum to search engines.
In order to better understand the commonalities and differences of social bookmarking systems and search engines, this thesis compares several aspects of the two systems' structure, usage behaviour and content. This includes the use of tags and query terms, the composition of the document collections and the rankings of bookmarks and search engine URLs. Searchers (recorded via session ids), their search terms and the clicked on URLs can be extracted from a search
engine query logfile. They form similar links as can be found in folksonomies where a user annotates a resource with tags. We use this analogy to build a tripartite hypergraph from query logfiles (a logsonomy), and compare structural and semantic properties of log- and folksonomies. Overall, we have found similar behavioural, structural and semantic characteristics in both systems. Driven by this insight, we investigate, if folksonomy data can be of use in web
information retrieval in a similar way to query log data: we construct training data from query logs and a folksonomy to build models for a learning-to-rank algorithm. First experiments show a positive correlation of ranking results generated from the ranking models of both systems. The research is based on various data collections from the social bookmarking systems BibSonomy and Delicious, Microsoft's search engine MSN (now Bing) and Google data.
To maintain social bookmarking systems as a good source for information retrieval, providers need to fight spam. This thesis introduces and analyses different features derived from the specific characteristics of social bookmarking systems to be used in spam detection classification algorithms. Best results can be derived from a combination of profile, activity, semantic and location-based features. Based on the experiments, a spam detection framework which identifies and eliminates spam activities for the social bookmarking system BibSonomy has been developed.
The storing and publication of user-related bookmarks and profile information raises questions about user data privacy. What kinds of personal information is collected and how do systems handle user-related items? In order to answer these questions, the thesis looks into the handling of data privacy in the social bookmarking system BibSonomy. Legal guidelines about how to deal with the private data collected and processed in social bookmarking systems are also presented. Experiments will show that the consideration of user data privacy in the process
of feature design can be a first step towards strengthening data privacy.
Within this thesis a new philosophy in monitoring spacecrafts is presented: the
unification of the various kinds of monitoring techniques used during the
different lifecylce phases of a spacecraft.
The challenging requirements being set for this monitoring framework are:
- "separation of concerns" as a design principle (dividing the steps of logging
from registered sources, sending to connected sinks and displaying of
information),
- usage during all mission phases,
- usage by all actors (EGSE engineers, groundstation operators, etc.),
- configurable at runtime, especially regarding the level of detail of logging
information, and
- very low resource consumption.
First a prototype of the monitoring framework was developed as a support library
for the real-time operating system
RODOS. This prototype was tested on dedicated hardware platforms relevant for
space, and also on a satellite demonstrator used for educational purposes.
As a second step, the results and lessons learned from the development and usage
of this prototype were transfered to a real space mission: the first satellite
of the DLR compact satellite series - a space based platform for DLR's own
research activities. Within this project, the software of the avionic subsystem
was supplemented by a powerful logging component, which enhances the traditional
housekeeping capabilities and offers extensive filtering and debugging
techniques for monitoring and FDIR needs. This logging component is the major
part of the flight version of the monitoring framework. It is completed by
counterparts running on the development computers and as well as the EGSE
hardware in the integration room, making it most valuable already in the
earliest stages of traditional spacecraft development.
Future plans in terms of adding support from the groundstation as well will lead
to a seamless integration of the monitoring framework not only into to the
spacecraft itself, but into the whole space system.
The general map-labeling problem is as follows: given a set of geometric objects to be labeled, or features, in the plane, and for each feature a set of label positions, maximize the number of placed labels such that there is at most one label per feature and no two labels overlap. There are three types of features in a map: point, line, and area features. Unfortunately, one cannot expect to find efficient algorithms that solve the labeling problem optimally.
Interactive maps are digital maps that only show a small part of the entire map whereas the user can manipulate the shown part, the view, by continuously panning, zooming, rotating, and tilting (that is, changing the perspective between a top and a bird view). An example for the application of interactive maps is in navigational devices. Interactive maps are challenging in that the labeling must be updated whenever labels leave the view and, while zooming, the label size must be constant on the screen (which either makes space for further labels or makes labels overlap when zooming in or out, respectively). These updates must be computed in real time, that is, the computation must be so fast that the user does not notice that we spend time on the computation. Additionally, labels must not jump or flicker, that is, labels must not suddenly change their positions or, while zooming out, a vanished label must not appear again.
In this thesis, we present efficient algorithms that dynamically label point and line features in interactive maps. We try to label as many features as possible while we prohibit labels that overlap, jump, and flicker. We have implemented all our approaches and tested them on real-world data. We conclude that our algorithms are indeed real-time capable.
Knowledge-based systems (KBS) face an ever-increasing interest in various disciplines and contexts. Yet, the former aim to construct the ’perfect intelligent software’ continuously shifts to user-centered, participative solutions. Such systems enable users to contribute their personal knowledge to the problem solving process for increased efficiency and an ameliorated user experience. More precisely, we define non-functional key requirements of participative KBS as: Transparency (encompassing KBS status mediation), configurability (user adaptability, degree of user control/exploration), quality of the KB and UI, and evolvability (enabling the KBS to grow mature with their users). Many of those requirements depend on the respective target users, thus calling for a more user-centered development. Often, also highly expertise domains are targeted — inducing highly complex KBs — which requires a more careful and considerate UI/interaction design. Still, current KBS engineering (KBSE) approaches mostly focus on knowledge acquisition (KA) This often leads to non-optimal, little reusable, and non/little evaluated KBS front-end solutions.
In this thesis we propose a more encompassing KBSE approach. Due to the strong mutual influences between KB and UI, we suggest a novel form of intertwined UI and KB development. We base the approach on three core components for encompassing KBSE:
(1) Extensible prototyping, a tailored form of evolutionary prototyping; this builds on mature UI prototypes and offers two extension steps for the anytime creation of core KBS prototypes (KB + core UI) and fully productive KBS (core KBS prototype + common framing functionality). (2) KBS UI patterns, that define reusable solutions for the core KBS UI/interaction; we provide a basic collection of such patterns in this work. (3) Suitable usability instruments for the assessment of the KBS artifacts. Therewith, we do not strive for ’yet another’ self-contained KBS engineering methodology. Rather, we motivate to extend existing approaches by the proposed key components. We demonstrate this based on an agile KBSE model.
For practical support, we introduce the tailored KBSE tool ProKEt. ProKEt offers a basic selection of KBS core UI patterns and corresponding configuration options out of the box; their further adaption/extension is possible on various levels of expertise. For practical usability support, ProKEt offers facilities for quantitative and qualitative data collection. ProKEt explicitly fosters the suggested, intertwined development of UI and KB. For seamlessly integrating KA activities, it provides extension points for two selected external KA tools: For KnowOF, a standard office based KA environment. And for KnowWE, a semantic wiki for collaborative KA. Therewith, ProKEt offers powerful support for encompassing, user-centered KBSE.
Finally, based on the approach and the tool, we also developed a novel KBS type: Clarification KBS as a mashup of consultation and justification KBS modules. Those denote a specifically suitable realization for participative KBS in highly expertise contexts and consequently require a specific design. In this thesis, apart from more common UI solutions, we particularly also introduce KBS UI patterns especially tailored towards Clarification KBS.
At the center of the Internet’s protocol stack stands the Internet Protocol (IP) as a common denominator that enables all communication. To make routing efficient, resilient, and scalable, several aspects must be considered. Care must be taken that traffic is well balanced to make efficient use of the existing network resources, both in failure free operation and in failure scenarios.
Finding the optimal routing in a network is an NP-complete problem. Therefore, routing optimization is usually performed using heuristics. This dissertation shows that a routing optimized with one objective function is often not good when looking at other objective functions. It can even be worse than unoptimized routing with respect to that objective function. After looking at failure-free routing and traffic distribution in different failure scenarios, the analysis is extended to include the loop-free alternate (LFA) IP fast reroute mechanism. Different application scenarios of LFAs are examined and a special focus is set on the fact that LFAs usually cannot protect all traffic in a network even against single link failures. Thus, the routing optimization for LFAs is targeted on both link utilization and failure coverage. Finally, the pre-congestion notification mechanism PCN for network admission control and overload protection is analyzed and optimized. Different design options for implementing the protocol are compared, before algorithms are developed for the calculation and optimization of protocol parameters and PCN-based routing.
The second part of the thesis tackles a routing problem that can only be resolved on a global scale. The scalability of the Internet is at risk since a major and intensifying growth of the interdomain routing tables has been observed. Several protocols and architectures are analyzed that can be used to make interdomain routing more scalable. The most promising approach is the locator/identifier (Loc/ID) split architecture which separates routing from host identification. This way, changes in connectivity, mobility of end hosts, or traffic-engineering activities are hidden from the routing in the core of the Internet and the routing tables can be kept much smaller. All of the currently proposed Loc/ID split approaches have their downsides. In particular, the fact that most architectures use the ID for routing outside the Internet’s core is a poor design, which inhibits many of the possible features of a new routing architecture. To better understand the problems and to provide a solution for a scalable routing design that implements a true Loc/ID split, the new GLI-Split protocol is developed in this thesis, which provides separation of global and local routing and uses an ID that is independent from any routing decisions.
Besides GLI-Split, several other new routing architectures implementing Loc/ID split have been proposed for the Internet. Most of them assume that a mapping system is queried for EID-to-RLOC mappings by an intermediate node at the border of an edge network. When the mapping system is queried by an intermediate node, packets are already on their way towards their destination, and therefore, the mapping system must be fast, scalable, secure, resilient, and should be able to relay packets without locators to nodes that can forward them to the correct destination. The dissertation develops a classification for all proposed mapping system architectures and shows their similarities and differences. Finally, the fast two-level mapping system FIRMS is developed. It includes security and resilience features as well as a relay service for initial packets of a flow when intermediate nodes encounter a cache miss for the EID-to-RLOC mapping.