@misc{HeinrichKetterl, author = {Heinrich, Tobias and Ketterl, Hermann}, title = {AI to quantify biological diversity}, series = {LANDSUPPORT Final Conference and the Save Our Soils Workshop, 27 -28 APRIL 2022, Portici, Italy}, journal = {LANDSUPPORT Final Conference and the Save Our Soils Workshop, 27 -28 APRIL 2022, Portici, Italy}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-50080}, abstract = {The primary consumers of plant exudates - in exact fungi and bacteria, are representative for the soil succession level from bare soil, which is bacterial dominant to old growth forest constitute by fungal dominance. In a specified level of soil succession, a special kind of plant family benefits on the Fungal to Bacteria Ratio. The ability to determine this ratio in situ without complex chemical applications is part of the project Electronical Laboratory for Intelligent Soil Examination (ELISE). Several mechanical and optical tests on soil samples are covered within this Project. To analyze the fungal to bacteria ratio, samples are prepared automatically - in a defined and reproductive procedure - to generate slides for shadowing microscopy. The samples are observed by a camera, which is attached to a transmitted light microscope. The automatic analysis, done with computer vision algorithms, aims to quantify bacterial and fungal biomass in the actual sample view. Moreover, the algorithm can classify organisms according to their color and shape. To get a processable picture, several images from different focal levels must be taken through the sample thickness. Parts of each image, are in focus at the actual layer, are merged to a whole depth of field picture, by focus stacking. This produced picture is used to classify, locate and quantify - in first step filamentous organisms e.g. fungal by image sematic segmentation. The result represents an image sized mask, which indicates the class of fungi with class equivalate values at the pixel positions - covered by the organism. This information is used to calculate the fungal mass per gram soil. To quantify the bacterial biomass two approaches are implemented. For low density of bacterial existence, the individual bacteria is counted for a part of the field of view by an image detection algorithm to be extrapolate afterwards to the mass per gram soil. For high density of bacterial occurrence, specified regions of interest with only bacteria present are chosen. An image classification which has been pretrained by pictures of bacterial density patterns - previously determent by making the sample countable due to preforming sample dilutions, is done. The second option for high density bacterial count is, to automatically preform dilutions until the image detection is confidently countable. To ensure a usable confidence score a statistical approach of many fields of view is taken.}, language = {en} } @misc{KetterlHeinrich, author = {Ketterl, Hermann and Heinrich, Tobias}, title = {Vivid tool for comprehensive biological soil analysis}, series = {LANDSUPPORT Final Conference and the Save Our Soils Workshop, 27 -28 APRIL 2022, Portici, Italy}, journal = {LANDSUPPORT Final Conference and the Save Our Soils Workshop, 27 -28 APRIL 2022, Portici, Italy}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-50078}, abstract = {The sample preparation for shadowing microscopy, to examinate biological soil properties, is time consuming, manual work. The outcome depends on subjective skills of the operator, furthermore the results are mostly not quantitative. The database on biological soil properties is mostly not sufficient for an integrated modelling on an multidisciplinary scale. This project combines three progressive approaches to develop a tool that is easy to use and gives in situ results that can be used for many purposes.}, language = {en} } @inproceedings{KetterlHeinrichReitmeieretal., author = {Ketterl, Hermann and Heinrich, Tobias and Reitmeier, Torsten and Hoelscher, Clemens}, title = {Emissionsabh{\"a}ngige Leistungsregelung f{\"u}r BHKW's}, series = {Tagungsband AALE 2020: Automatisierung und Mensch-Technik-Interaktion, 17. Fachkonferenz, 4. bis 6. M{\"a}rz 2020, Leipzig}, volume = {2020}, booktitle = {Tagungsband AALE 2020: Automatisierung und Mensch-Technik-Interaktion, 17. Fachkonferenz, 4. bis 6. M{\"a}rz 2020, Leipzig}, editor = {J{\"a}kel, Jens and Thiel, Robert}, publisher = {VDE-Verlag}, isbn = {978-3-8007-5180-8}, pages = {7}, language = {de} } @inproceedings{KetterlKieseLandgrafetal., author = {Ketterl, Hermann and Kiese, Constanze and Landgraf, Hans-Peter and Danzer, Anna-Lena and Schickling, Benedikt and Nicolau-Torra, Anna and Reitmeier, Torsten and Schulte-Mattler, Wilhelm and von Schweinitz, Dietrich}, title = {Intuitive Visualization of Innervation Zones Based on Surface-EMG Signals}, series = {2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 18-21 July 2018, Honolulu, HI, USA}, booktitle = {2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 18-21 July 2018, Honolulu, HI, USA}, publisher = {IEEE}, doi = {10.1109/EMBC.2018.8513265}, pages = {3894 -- 3897}, abstract = {The purpose of this study was to develop a user-friendly presentation of surface-EMG data in near-time for intraoperative nerve-monitoring. We have built a novel surface-EMG probe as a diagnostic device to investigate innervation patterns of sphincter muscles in further clinical diagnostic studies. S-EMG data were recorded from 20 healthy volunteers from the orbicularis oris muscles. We developed an automated analysis based on correlation in order to find phase inversions and thus innervation zones automatically. We compared our automated analysis with manual, visual analysis. Both techniques were reviewed for variance and showed reproducible results. Data from automated analysis were compared to visually analyzed data showing high consistency. Based on our automated analysis, we created an intuitive visualization of all measurements per person. We displayed the quality and quantity of the phase inversions found in a subject thus allowing for simple identification of innervation zones. We conclude that our set-up showed sufficient reliability for detection of motoric endplate activity and can be used for further clinical neurophysiological studies.}, language = {en} } @inproceedings{KetterlHoelscherGotzleretal., author = {Ketterl, Hermann and Hoelscher, Clemens and Gotzler, Julian and Grill, Oliver and Heinrich, Tobias and Mayer, Anton and Reiter, Fabian and M{\"u}hlbauer, Simon and Weinzierl, Stefan}, title = {Autonomer Hackroboter}, series = {Tagungsband AALE 2020: Automatisierung und Mensch-Technik-Interaktion, 17. Fachkonferenz, 4. bis 6. M{\"a}rz 2020, Leipzig}, volume = {2020}, booktitle = {Tagungsband AALE 2020: Automatisierung und Mensch-Technik-Interaktion, 17. Fachkonferenz, 4. bis 6. M{\"a}rz 2020, Leipzig}, editor = {J{\"a}kel, Jens and Thiel, Robert}, publisher = {VDE-Verlag}, isbn = {978-3-8007-5180-8}, pages = {6}, language = {de} }