Automated user documentation generation based on the Eclipse application model

An application's user documentation, also referred to as the user manual, is one of the core elements required in application distribution. While there exist many tools to aid an application's developer in creating and maintaining documentation on and for the code itself, there are no tools that complement code development with user documentation for modern graphical applications. Approaches like literate programming are not applicable to this scenario, as not a library, but a full application is to be documented to an end-user. Documentation generation on applications up to now was only partially feasible due to the gap between the code and its semantics. The new generation of Eclipse rich client platform developed applications is based on an application model, closing a broad semantic gap between code and visible interface. We use this application model to provide a semantic description for the contained elements. Combined with the internal relationships of the application model, these semantic descriptions are aggregated to well-structured user documentations that comply to the ISO/IEC 26514. This paper delivers a report on the Ecrit research project, where the potentials and limitations of user documentation generation based on the Eclipse application model were investigated.Comment: 9 pages, 9 figure

Mobility choices - an instrument for precise automatized travel behavior detection & analysis

Within the Mobility Choices (MC) project we have developed an app that allows users to record their travel behavior and encourages them to try out new means of transportation that may better fit their preferences. Tracks explicitly released by the users are anonymized and can be analyzed by authorized institutions. For recorded tracks, the freely available app automatically determines the segments with their transportation mode; analyzes the track according to the criteria environment, health, costs, and time; and indicates alternative connections that better fit the criteria, which can individually be configured by the user. In the second step, the users can edit their tracks and release them for further analysis by authorized institutions. The system is complemented by a Web-based analysis program that helps authorized institutions carry out specific evaluations of traffic flows based on the released tracks of the app users. The automatic transportation mode detection of the system reaches an accuracy of 97%. This requires only minimal corrections by the user, which can easily be done directly in the app before releasing a track. All this enables significantly more accurate surveys of transport behavior than the usual time-consuming manual (non-automated) approaches, based on questionnaires

Automatic measurement of departing times in smartphone alerting systems: A pilot study

Aim Smartphone alerting systems (SAS) alert volunteers in close vicinity of suspected out-of-hospital cardiac arrest. Some systems use sophisticated algorithms to select those who will probably arrive first. Precise estimation of departing times and travel times may help to further improve algorithms. We developed a global positioning system (GPS) based method for automatic measurements of departing times. The aim of this pilot study was to evaluate feasibility and precision of the method. Methods Region of Lifesavers alerting app (iOS/ Android, version 3.0, FirstAED ApS, Denmark) was used in this study. 27 experiments were performed with 9 students, who were instructed to stay in their flats during the study days. A geofence was set for each alarm in the alerting system with a radius of 10 m (8 cases), 15 m (10 cases), and 20 m (9 cases) around the GPS position at which the alarm was accepted in the app. The system logged responders as being departed when the smartphone position was registered outside the geofence. The students were instructed to manually start a stopwatch at the time of the alert and to stop the stopwatch once they had entered the street in front of their flat. Results The median difference between automatically and manually retrieved times were −16 seconds [interquartile range IQR 50 seconds] (geofence 10 m), 30 seconds [IQR 25 seconds] (15 m), and 20 seconds [IQR 13 seconds] (20 m), respectively. The 20 m geofence was associated with the smallest interquartile range. Conclusion Departing times of volunteer responders in SAS can be retrieved automatically using GPS and a geofence

Leaf Mass per Area of Wetland Vegetation under Water Stress Analyzed with Imaging Spectroscopy

Plant and community traits of wetland vegetation show a high intra-specific plasticity, originating from the high variability of environmental conditions. Remote sensing approaches promise to be able to retrieve some of these traits and their plasticity from the spectral reflectance signal of the canopy. In the present study, we evaluate a remote-sensing based approach for an analysis of spatial patterns of leaf mass per area (LMA), a key trait for ecosystem functioning and good negative correlate of potential growth rate. The test was conducted in Las Tablas de Daimiel, a National Park in Central Spain. This wetland was affected by a long-term drought, which introduced pronounced trait plasticity as part of the adaptation mechanisms of the vegetation to reduced water availability as well as a decrease in photosynthetic activity. Imaging spectroscopy (HyMap) data of the wetland were acquired in 2009 at peak drought intensity. At the same time, a field campaign was conducted. We applied an inversion of the PROSAIL model on these data to map the LMA distribution across the wetland. PROSAIL is a radiative transfer model that simulates the physical principles of light absorption and scattering in a vegetation canopy. The inversion enables the retrieval of trait information from the spectral signal. Furthermore, we assessed trends in photosynthetic activity and changing species composition across the wetland by analyzing time series of the normalized difference vegetation index (NDVI) as determined from various multispectral sensors. The mapped LMA values were analyzed within and between stands of different species and communities along a gradient of changing photosynthetic activity and species composition. LMA values retrieved for stands of species with high photosynthetic activity at peak drought intensity closely met values reported in trait data bases. The observed intra-specific LMA variability is in line with the expected plasticity of this trait along a moisture gradient that is reflected in a change in photosynthetic activity and species composition. We thus conclude that remote sensing approaches provide sufficient detail to trace the LMA-response of wetland vegetation to long-term drought stress

Remotely sensed spatial heterogeneity as an exploratory tool for taxonomic and functional diversity study

Assessing biodiversity from field-based data is difficult for a number of practical reasons: (i) establishing the total number of sampling units to be investigated and the sampling design (e.g. systematic, random, stratified) can be difficult; (ii) the choice of the sampling design can affect the results; and (iii) defining the focal population of interest can be challenging. Satellite remote sensing is one of the most cost-effective and comprehensive approaches to identify biodiversity hotspots and predict changes in species composition. This is because, in contrast to field-based methods, it allows for complete spatial coverages of the Earth's surface under study over a short period of time. Furthermore, satellite remote sensing provides repeated measures, thus making it possible to study temporal changes in biodiversity. While taxonomic diversity measures have long been established, problems arising from abundance related measures have not been yet disentangled. Moreover, little has been done to account for functional diversity besides taxonomic diversity measures. The aim of this manuscript is to propose robust measures of remotely sensed heterogeneity to perform exploratory analysis for the detection of hotspots of taxonomic and functional diversity of plant species