@article{CamargoSchirrmannLandwehretal.2021, author = {Camargo, Tibor de and Schirrmann, Michael and Landwehr, Niels and Dammer, Karl-Heinz and Pflanz, Michael}, title = {Optimized deep learning model as a basis for fast UAV mapping of weed species in winter wheat crops}, series = {Remote sensing / Molecular Diversity Preservation International (MDPI)}, volume = {13}, journal = {Remote sensing / Molecular Diversity Preservation International (MDPI)}, number = {9}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs13091704}, pages = {19}, year = {2021}, abstract = {Weed maps should be available quickly, reliably, and with high detail to be useful for site-specific management in crop protection and to promote more sustainable agriculture by reducing pesticide use. Here, the optimization of a deep residual convolutional neural network (ResNet-18) for the classification of weed and crop plants in UAV imagery is proposed. The target was to reach sufficient performance on an embedded system by maintaining the same features of the ResNet-18 model as a basis for fast UAV mapping. This would enable online recognition and subsequent mapping of weeds during UAV flying operation. Optimization was achieved mainly by avoiding redundant computations that arise when a classification model is applied on overlapping tiles in a larger input image. The model was trained and tested with imagery obtained from a UAV flight campaign at low altitude over a winter wheat field, and classification was performed on species level with the weed species Matricaria chamomilla L., Papaver rhoeas L., Veronica hederifolia L., and Viola arvensis ssp. arvensis observed in that field. The ResNet-18 model with the optimized image-level prediction pipeline reached a performance of 2.2 frames per second with an NVIDIA Jetson AGX Xavier on the full resolution UAV image, which would amount to about 1.78 ha h(-1) area output for continuous field mapping. The overall accuracy for determining crop, soil, and weed species was 94\%. There were some limitations in the detection of species unknown to the model. When shifting from 16-bit to 32-bit model precision, no improvement in classification accuracy was observed, but a strong decline in speed performance, especially when a higher number of filters was used in the ResNet-18 model. Future work should be directed towards the integration of the mapping process on UAV platforms, guiding UAVs autonomously for mapping purpose, and ensuring the transferability of the models to other crop fields.}, language = {en} } @article{ChaabenePrieskeLesinskietal.2019, author = {Chaabene, Helmi and Prieske, Olaf and Lesinski, Melanie and Sandau, Ingo and Granacher, Urs}, title = {Short-Term Seasonal Development of Anthropometry, Body Composition, Physical Fitness, and Sport-Specific Performance in Young Olympic Weightlifters}, series = {Sports}, volume = {7}, journal = {Sports}, number = {12}, publisher = {MDPI}, address = {Basel}, issn = {2075-4663}, doi = {10.3390/sports7120242}, pages = {13}, year = {2019}, language = {en} } @article{ChenLangeAndjelkovicetal.2022, author = {Chen, Junchao and Lange, Thomas and Andjelkovic, Marko and Simevski, Aleksandar and Lu, Li and Krstić, Miloš}, title = {Solar particle event and single event upset prediction from SRAM-based monitor and supervised machine learning}, series = {IEEE transactions on emerging topics in computing / IEEE Computer Society, Institute of Electrical and Electronics Engineers}, volume = {10}, journal = {IEEE transactions on emerging topics in computing / IEEE Computer Society, Institute of Electrical and Electronics Engineers}, number = {2}, publisher = {Institute of Electrical and Electronics Engineers}, address = {[New York, NY]}, issn = {2168-6750}, doi = {10.1109/TETC.2022.3147376}, pages = {564 -- 580}, year = {2022}, abstract = {The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in space-borne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during run-time, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels.}, language = {en} } @article{CoppalleRaveBenAbderrahmanetal.2019, author = {Coppalle, Sullivan and Rave, Guillaume and Ben Abderrahman, Abderraouf and Ali, Ajmol and Salhi, Iyed and Zouita, Sghaier and Zouita, Amira and Brughelli, Matt and Granacher, Urs and Zouhal, Hassane}, title = {Relationship of Pre-season Training Load With In-Season Biochemical Markers, Injuries and Performance in Professional Soccer Players}, series = {Frontiers in Physiology}, volume = {10}, journal = {Frontiers in Physiology}, publisher = {Frontiers Research Foundation}, address = {Lausanne}, issn = {1664-042X}, doi = {10.3389/fphys.2019.00409}, pages = {11}, year = {2019}, abstract = {There is controversy in the literature in regards of the link between training load and injury rate. Thus, the aims of this non-interventional study were to evaluate relationships between pre-season training load with biochemical markers, injury incidence and performance during the first month of the competitive period in professional soccer players.}, language = {en} } @article{CoppalleRaveMoranetal.2021, author = {Coppalle, Sullivan and Rav{\´e}, Guillaume and Moran, Jason and Salhi, Iyed and Ben Abderrahman, Abderraouf and Zouita, Sghaeir and Granacher, Urs and Zouhal, Hassane}, title = {Internal and External Training Load in Under-19 versus Professional Soccer Players during the In-Season Period}, series = {International Journal of Environmental Research and Public Health}, volume = {18}, journal = {International Journal of Environmental Research and Public Health}, number = {2}, publisher = {MDPI AG}, address = {Basel}, issn = {1660-4601}, doi = {10.3390/ijerph18020558}, pages = {10}, year = {2021}, abstract = {This study aimed to compare the training load of a professional under-19 soccer team (U-19) to that of an elite adult team (EAT), from the same club, during the in-season period. Thirty-nine healthy soccer players were involved (EAT [n = 20]; U-19 [n = 19]) in the study which spanned four weeks. Training load (TL) was monitored as external TL, using a global positioning system (GPS), and internal TL, using a rating of perceived exertion (RPE). TL data were recorded after each training session. During soccer matches, players' RPEs were recorded. The internal TL was quantified daily by means of the session rating of perceived exertion (session-RPE) using Borg's 0-10 scale. For GPS data, the selected running speed intensities (over 0.5 s time intervals) were 12-15.9 km/h; 16-19.9 km/h; 20-24.9 km/h; >25 km/h (sprint). Distances covered between 16 and 19.9 km/h, > 20 km/h and >25 km/h were significantly higher in U-19 compared to EAT over the course of the study (p = 0.023, d = 0.243, small; p = 0.016, d = 0.298, small; and p = 0.001, d = 0.564, small, respectively). EAT players performed significantly fewer sprints per week compared to U-19 players (p = 0.002, d = 0.526, small). RPE was significantly higher in U-19 compared to EAT (p = 0.001, d = 0.188, trivial). The external and internal measures of TL were significantly higher in the U-19 group compared to the EAT soccer players. In conclusion, the results obtained show that the training load is greater in U19 compared to EAT.}, language = {en} } @article{EiblRosskopfSciottoetal.2022, author = {Eibl, Eva P. S. and Rosskopf, Martina and Sciotto, Mariangela and Currenti, Gilda and Di Grazia, Giuseppe and Jousset, Philippe and Kr{\"u}ger, Frank and Weber, Michael}, title = {Performance of a rotational sensor to decipher volcano seismic signals on Etna, Italy}, series = {Journal of geophysical research : Solid earth}, volume = {127}, journal = {Journal of geophysical research : Solid earth}, number = {6}, publisher = {Wiley}, address = {Hoboken, NJ}, issn = {0148-0227}, doi = {10.1029/2021JB023617}, pages = {22}, year = {2022}, abstract = {Volcano-seismic signals such as long-period events and tremor are important indicators for volcanic activity and unrest. However, their wavefield is complex and characterization and location using traditional seismological instrumentation is often difficult. In 2019 we recorded the full seismic wavefield using a newly developed 3C rotational sensor co-located with a 3C traditional seismometer on Etna, Italy. We compare the performance of the rotational sensor, the seismometer and the Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo (INGV-OE) seismic network with respect to the analysis of complex volcano-seismic signals. We create event catalogs for volcano-tectonic (VT) and long-period (LP) events combining a STA/LTA algorithm and cross-correlations. The event detection based on the rotational sensor is as reliable as the seismometer-based detection. The LP events are dominated by SH-type waves. Derived SH phase velocities range from 500 to 1,000 m/s for LP events and 300-400 m/s for volcanic tremor. SH-waves compose the tremor during weak volcanic activity and SH- and SV-waves during sustained strombolian activity. We derive back azimuths using (a) horizontal rotational components and (b) vertical rotation rate and transverse acceleration. The estimated back azimuths are consistent with the INGV-OE event location for (a) VT events with an epicentral distance larger than 3 km and some closer events, (b) LP events and tremor in the main crater area. Measuring the full wavefield we can reliably analyze the back azimuths, phase velocities and wavefield composition for VT, LP events and tremor in regions that are difficult to access such as volcanoes.}, language = {en} } @techreport{GagrčinSchaetzRakowskietal.2021, author = {Gagrčin, Emilija and Schaetz, Nadja and Rakowski, Niklas and Toth, Roland and Renz, Andr{\´e} and Vladova, Gergana and Emmer, Martin}, title = {We and AI}, publisher = {Weizenbaum Institute for the Networked Society - the German Internet}, address = {Berlin}, doi = {10.34669/wi/1}, pages = {70}, year = {2021}, language = {en} } @article{HabelUlrichEberleetal.2022, author = {Habel, Jan Christian and Ulrich, Werner and Eberle, Jonas and Schmitt, Thomas}, title = {Species community structures of Afrotropical butterflies differ depending on the monitoring method}, series = {Biodiversity and conservation}, volume = {31}, journal = {Biodiversity and conservation}, number = {1}, publisher = {Springer}, address = {Dordrecht}, issn = {0960-3115}, doi = {10.1007/s10531-021-02332-2}, pages = {245 -- 259}, year = {2022}, abstract = {Standardised biodiversity assessment is crucial to understand community structures and population dynamics of animals. There exist various methods to monitor biodiversity. Approaches differ depending on the target species group and the aim of study, and show advantages and disadvantages. The obtained data and results are influenced by local environmental conditions and seasonal variability. In a comparative approach, we studied butterfly diversity and community structure in the dryland savannah biome of south-eastern Kenya with two different methods, transect counts and bait trapping. We repeatedly collected data throughout the dry and rainy seasons, in both near natural and anthropogenically influenced landscapes. Significantly more species and individuals were recorded by transect counts than by bait trapping, though the larger and more mobile Nymphalid species (and in particular representatives of the genus Charaxes) were comparatively overrepresented in traps. The transect data revealed much more pronounced effects of land-use and seasonality than the trap data. These results show that the choice of data collection methods must depend on the general research question, habitat conditions and season. To study the relative variation of species diversity and abundance, the collection of a fraction of the total species diversity might be sufficient. However, if the focus is on a largely complete recording of species diversity, the use of various collection methods is essential. More specifically, our data clearly demonstrate that transect counts represent a reasonable method for assessing butterfly diversity for the African dryland savannah region, but fails to fully capture occurrences of all species. Bait trapping can be used only as a supplementary method for assessing some few highly mobile low-density species.}, language = {en} } @article{HeineFranckeRogassetal.2014, author = {Heine, Iris and Francke, Till and Rogass, Christian and Medeiros, Pedro Henrique Augusto and Bronstert, Axel and F{\"o}rster, Saskia}, title = {Monitoring seasonal changes in the water surface areas of reservoirs using TerraSAR-X time series data in semiarid northeastern Brazil}, series = {IEEE journal of selected topics in applied earth observations and remote sensing}, volume = {7}, journal = {IEEE journal of selected topics in applied earth observations and remote sensing}, number = {8}, publisher = {Inst. of Electr. and Electronics Engineers}, address = {Piscataway}, issn = {1939-1404}, doi = {10.1109/JSTARS.2014.2323819}, pages = {3190 -- 3199}, year = {2014}, abstract = {The 933 km(2) Bengue catchment in northeastern Brazil is characterized by distinct rainy and dry seasons. Precipitation is stored in variously sized reservoirs, which is essential for the local population. In this study, we used TerraSAR-X SM(HH) data for an one-year monitoring of seasonal changes in the reservoir areas from July 2011 to July 2012. The monitoring was based on acquisitions in the ascending pass direction, complemented by occasional descending-pass images. To detect water surface areas, a histogram analysis followed by a global threshold classification was performed, and the results were validated using in situ GPS data. Distinguishing between small reservoirs and similar looking dark areas was difficult. Therefore, we tested several approaches for identifying misclassified areas. An analysis of the surface area dynamics of the reservoirs indicated high spatial and temporal heterogeneities and a large decrease in the total water surface area of the reservoirs in the catchment by approximately 30\% within one year.}, language = {en} } @article{KuehnBeckerHarpkeetal.2022, author = {K{\"u}hn, Elisabeth and Becker, Marc and Harpke, Alexander and K{\"u}hn, Ingolf and Kuhlicke, Christian and Schmitt, Thomas and Settele, Josef and Musche, Martin}, title = {The benefits of counting butterflies: recommendations for a successful citizen science project}, series = {Ecology and Society}, volume = {27}, journal = {Ecology and Society}, number = {2}, publisher = {Resilience Alliance}, address = {Wolfville}, issn = {1708-3087}, doi = {10.5751/ES-12861-270238}, pages = {39}, year = {2022}, abstract = {Citizen science (CS) projects, being popular across many fields of science, have recently also become a popular tool to collect biodiversity data. Although the benefits of such projects for science and policy making are well understood, relatively little is known about the benefits participants get from these projects as well as their personal backgrounds and motivations. Furthermore, very little is known about their expectations. We here examine these aspects, with the citizen science project "German Butterfly Monitoring" as an example. A questionnaire was sent to all participants of the project and the responses to the questionnaire indicated the following: center dot Most transect walkers do not have a professional background in this field, though they do have a high educational level, and are close to retirement, with a high number of females; center dot An important motivation to join the project is to preserve the natural environment and to contribute to scientific knowledge; center dot Participants benefit by enhancing their knowledge about butterflies and especially their ability to identify different species (taxonomic knowledge); center dot Participants do not have specific expectations regarding the project beyond proper management and coordination, but have an intrinsic sense of working for a greater good. The willingness to join a project is higher if the project contributes to the solution of a problem discussed in the media (here, insect decline). Based on our findings from the analysis of the questionnaire we can derive a set of recommendations for establishing a successful CS project. These include the importance of good communication, e.g., by explaining what the (scientific) purpose of the project is and what problems are to be solved with the help of the data collected in the project. The motivation to join a CS project is mostly intrinsic and CS is a good tool to engage people during difficult times such as the COVID-19 pandemic, giving participants the feeling of doing something useful.}, language = {en} }