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Human action recognition from a video has received growing attention in computer vision and has made significant progress in recent years. Action recognition is described as a requirement to decide which human actions appear in videos. The difficulties involved in distinguishing human actions are due to the high complexity of human behaviors as well as appearance variation, motion pattern variation, occlusions, etc. Many applications use human action recognition on captured video from cameras, resulting in video surveillance systems, health monitoring, human-computer interaction, and robotics. Action recognition based on RGB-D data has increasingly drawn more attention to it in recent years. RGB-D data contain color (Red, Green, and Blue (RGB)) and depth data that represent the distance from the sensor to every pixel in the object (object point). The main problem that this thesis deals with is how to automate the classification of specific human activities/actions through RGB-D data. The classification process of these activities utilizes a spatial and temporal structure of actions. Therefore, the goal of this work is to develop algorithms that can distinguish these activities by recognizing low-level and high-level activities of interest from one another. These algorithms are developed by introducing new features and methods using RGB-D data to enhance the detection and recognition of human activities. In this thesis, the most popular state-of-the-art techniques are reviewed, presented, and evaluated. From the literature review, these techniques are categorized into hand-crafted features and deep learning-based approaches. The proposed new action recognition framework is based on these two categories that are approved in this work by embedding novel methods for human action recognition. These methods are based on features extracted from RGB-D data that are
evaluated using machine learning techniques. The presented work of this thesis improves human action recognition in two distinct parts. The first part focuses on improving current successful hand-crafted approaches. It contributes into two significant areas of state-of-the-art: Execute the existing feature detectors, and classify the human action in the 3D spatio-temporal domains by testing a new combination of different feature representations. The contributions of this part are tested based on machine learning techniques that include unsupervised and supervised learning to evaluate this suitability for the task of human action recognition. A k-means clustering represents the unsupervised learning technique, while the supervised learning technique is represented by: Support Vector Machine, Random Forest, K-Nearest Neighbor, Naive Bayes, and Artificial Neural Networks classifiers. The second part focuses on studying the current deep-learning-based approach and how to use it with RGB-D data for the human action recognition task. As the first step of each contribution, an input video is analyzed as a sequence of frames. Then, pre-processing steps are applied to the video frames, like filtering and smoothing methods to remove the noisy data from each frame. Afterward, different motion detection and feature representation methods are used to extract features presented in each frame. The extracted features
are represented by local features, global features, and feature combination besides deep learning methods, e.g., Convolutional Neural Networks. The feature combination achieves an excellent accuracy performance that outperforms other methods on the same RGB-D datasets. All the results from the proposed methods in this thesis are evaluated based on publicly available datasets, which illustrate that using spatiotemporal features can improve the recognition accuracy. The competitive experimental results are achieved overall. In particular, the proposed methods can be better applied to the test set compared to the state-of-the-art methods using the RGB-D datasets.
Efficient Cochlear Implant (CI) surgery requires prior knowledge of the cochlea’s size and its characteristics. This information helps to select suitable implants for different patients. Registered and fused images helps doctors by providing more informative image that takes advantages of different modalities. The cochlea’s small size and complex structure, in addition to the different resolutions and head positions during imaging, reveals a big challenge for the automated registration of the different image modalities. To obtain an automatic measurement of the cochlea length and the volume size, a segmentation method of cochlea medical images is needed. The goal of this dissertation is to introduce new practical and automatic algorithms for the human cochlea multi-modal 3D image registration, fusion, segmentation and analysis. Two novel methods for automatic cochlea image registration (ACIR) and automatic cochlea analysis (ACA) are introduced. The proposed methods crop the input images to the cochlea part and then align the cropped images to obtain the optimal transformation. After that, this transformation is used to align the original images. ACIR and ACA use Mattes mutual information as similarity metric, the adaptive stochastic gradient descent (ASGD) or the stochastic limited memory Broyden–Fletcher–Goldfarb–Shanno (s-LBFGS) optimizer to estimate the parameters of 3D rigid transform. The second stage of nonrigid registration estimates B-spline coefficients that are used in an atlas-model-based segmentation to extract cochlea scalae and the relative measurements of the input image. The image which has segmentation is aligned to the input image to obtain the non-rigid transformation. After that the segmentation of the first image, in addition to point-models are transformed to the input image. The detailed transformed segmentation provides the scala volume size. Using the transformed point-models, the A-value, the central scala lengths, the lateral and the organ of corti scala tympani lengths are computed. The methods have been tested using clinical 3D images of total 67 patients: from Germany (41 patients) and Egypt (26 patients). The atients are of different ages and gender. The number of images used in the experiments is 217, which are multi-modal 3D clinical images from CT, CBCT, and MRI scanners. The proposed methods are compared to the state of the arts ptimizers related medical image registration methods e.g. fast adaptive stochastic gradient descent (FASGD) and efficient preconditioned tochastic gradient descent (EPSGD). The comparison used the root mean squared distance (RMSE) between the ground truth landmarks and the resulted landmarks. The landmarks are located manually by two experts to represent the round window and the top of the cochlea. After obtaining the transformation using ACIR, the landmarks of the moving image are transformed using the resulted transformation and RMSE of the transformed landmarks, and at the same time the fixed image landmarks are computed. I also used the active length of the cochlea implant electrodes to compute the error aroused by the image artifact, and I found out an error ranged from 0.5 mm to 1.12 mm. ACIR method’s RMSE average was 0.36 mm with a standard deviation (SD) of 0.17 mm. The total time average required for registration of an image pair using ACIR was 4.62 seconds with SD of 1.19 seconds. All experiments are repeated 3 times for justifications. Comparing the RMSE of ACIR2017 and ACIR2020 using paired T-test shows no significant difference (p-value = 0.17). The total RMSE average of ACA method was 0.61 mm with a SD of 0.22 mm. The total time average required for analysing an image was 5.21 seconds with SD of 0.93 seconds. The statistical tests show that there is no difference between the results from automatic A-value method and the manual A-value method (p-value = 0.42). There is no difference also between length’s measurements of the left and the right ear sides (p-value > 0.16). Comparing the results from German and Egypt dataset shows there is no difference when using manual or automatic A-value methods (p-value > 0.20). However, there is a significant difference when using ACA2000 method between the German and the Egyptian results (p-value < 0.001). The average time to obtain the segmentation and all measurements was 5.21 second per image. The cochlea scala tympani volume size ranged from 38.98 mm3 to 57.67 mm3 . The combined scala media and scala vestibuli volume size ranged from 34.98 mm 3 to 49.3 mm 3 . The overall volume size of the cochlea should range from 73.96 mm 3 to 106.97 mm 3 . The lateral wall length of scala tympani ranged from 42.93 mm to 47.19 mm. The organ-of-Corti length of scala tympani ranged from 31.11 mm to 34.08 mm. Using the A-value method, the lateral length of scala tympani ranged from 36.69 mm to 45.91 mm. The organ-of-Corti length of scala tympani ranged from 29.12 mm to 39.05 mm. The length from ACA2020 method can be visualised and has a well-defined endpoints. The ACA2020 method works on different modalities and different images despite the noise level or the resolution. In the other hand, the A-value method works neither on MRI nor noisy images. Hence, ACA2020 method may provide more reliable and accurate measurement than the A-value method. The source-code and the datasets are made publicly available to help reproduction and validation of my result.
Soziale Medien bieten eine leistungsstarke Möglichkeit für Menschen, Meinungen und Gefühle zu einem bestimmten Thema auszutauschen, sodass andere von diesen Gedanken und Gefühlen profitieren können. Dieses Verfahren erzeugt eine riesige Menge an unstrukturierten Daten, wie Texte, Bilder und Verweise, die durch täglich anwachsende Kommentare zu verwandten Diskussionen ständig zunimmt. Die riesige Menge an unstrukturierten Daten stellt jedoch ein Risiko für den Prozess der Informationsextraktion dar, sodass die Entscheidungsfindung zu einer großen Herausforderung wird. Dies liegt daran, dass die Datenflut zu einem Verlust von nützlichen Daten aufgrund ihrer unangemessenen Darstellung und ihrer Anhäufung führen kann. Insofern leistet diese Arbeit einen Beitrag zum Gebiet der Sentimentanalyse und des Opinion Mining, das darauf abzielt, Emotionen und Meinungen aus riesigen Text- und Bilddatensätzen zu extrahieren. Das ultimative Ziel ist es, jeden Text oder jedes Bild als Ausdruck einer positiven, negativen oder neutralen Emotion zu klassifizieren, um bei der Entscheidungsfindung zu helfen. Sentiment- und Meinungsklassifikatoren wurden für Text- und Bilddatensätze aus sozialen Medien entwickelt, z. B. für Firmen- oder Produktbewertungen, Blogbeiträge und sogar Twitter-Nachrichten. In dieser Arbeit wird zunächst eine neue Methode zur Reduktion der Dimension von Textdaten auf Basis von Data-Mining-Ansätzen vorgestellt und anschließend das Sentiment auf Basis von neuronalen und Deep Neural Network-Klassifikationsalgorithmen untersucht. Anschließend untersuchen wir im Gegensatz zur Sentiment-Analyseforschung in Textdatensätzen die Sentiment Ausdrucks- und Polaritätsklassifikation innerhalb und über Bilddatensätze hinweg, indem wir tiefe neuronale Netze auf Basis des Aufmerksamkeitsmechanismus aufbauen.
The bio-insecticide Bacillus thuringiensis israelensis (Bti) has worldwide become the most commonly used agentin mosquito control programs that pursue two main objectives: the control of vector-borne diseases and the reduction of nuisance, mainly coming frommosquitoes that emerge in large quantities from seasonal wetlands. The Upper Rhine Valley, a biodiversity hotspot in Germany, has been treated withBti for decades to reduce mosquito-borne nuisance and increase human well-being.Although Btiis presumed to be an environmentally safe agent,adverse effects on wetland ecosystems are still a matter of debate especially when it comes to long-term and indirect effects on non-target organisms. In light of the above, this thesis aims at investigating direct and indirect effects of Bti-based mosquito control on non-target organisms within wetland food chains.Effects were examinedin studies with increasingeco(toxico)logical complexity, ranging from laboratory over mesocosm to field approaches with a focus on the non-biting Chironomidae and amphibian larvae (Rana temporaria, Lissotriton sp.).In addition, public acceptance of environmentally less invasive alternative mosquito control methods was evaluated within surveys among the local population.
Chironomids were the most severely affected non-target aquatic invertebrates. Bti substantially reduced larval and adult chironomid abundances and modified their species composition. Repeated exposures to commonly used Bti formulations induced sublethal alterations of enzymatic biomarkers activityin frog tadpoles. Bti-induced reductions of chironomid prey availability indirectly decreased body size of newts at metamorphosis and increased predation on newt larvae in mesocosm experiments. Indirect effects of severe reductions in midge biomassmight equally be passed through aquatic but also terrestrial food chains influencing predators of higher trophic levels. The majority ofaffectedpeople in the Upper Rhine Valley expressed a high willingness to contributefinancially to environmentally less harmful mosquito control.Alternative approaches could still include Bti applications excepting treatment of ecologically valuable areas. Potentially rising mosquito levels could be counteracted with local acting mosquito traps in domestic and urban areas because mosquito presence was experienced as most annoying in the home environment.
As Bti-based mosquito control can adversely affect wetland ecosystems, its large-scale applications, including nature conservation areas, should be considered more carefully to avoid harmful consequences for the environmentat the Upper Rhine Valley.This thesis emphasizesthe importance to reconsiderthe current practice of mosquito control and encourage research on alternative mosquito control concepts that are endorsed by the local population. In the context ofthe ongoing amphibian and insect declinesfurther human-induced effects onwetlands should be avoided to preserve biodiversity in functioning ecosystems.
Aktuelle Schätzungen bestätigten, dass Binnengewässer eine erhebliche Menge Methan (CH4) und Kohlendioxid (CO2) sowohl auf regionaler Ebene, als auch global freisetzen. Jedoch basieren diese Schätzungen auf extrapolierten gemessenen Daten, ungenügender Auflösung der räumlich-zeitlichen Variabilität und es mangelt an Daten aus ariden und semi-ariden Gebieten, sowie den Kohlestoffquellen aus Kläranlagen.
Für die hier vorliegende Studie analysierten wir monatliche hydrologische und meteorologische Daten sowie Daten zur Wasserqualität von drei Stauseen aus dem Gebiet des unteren Jordans, die zur Trinkwassergewinnung und zur Bewässerung genutzt werden, und schätzten damit deren Emissionsrate an CO2 ab. Wir untersuchten den Effekt von Kläranlagen auf die umliegenden Gewässer im Hinblick auf CH4 und CO2-Emissionen indem wir saisonal aufgelöste Daten der Konzentration der beiden gelösten Gase in Kläranlagenauslässen und in Vorflutern von neun Kläranlagen in Deutschland analysierten. Mithilfe von Low-Cost-Methoden die die CO2-Transportrate und die Ausgasungsrate über Gasblasen messen, untersuchten wir die räumliche und zeitliche Variabilität der CH4 und CO2-Emissionen von aquatischen Süßwasser-Ökosystemen.
Unsere Schätzungen zeigen, dass Stauseen in semi-ariden Regionen CO2 übersättigt sind und somit CO2 an die Atmosphäre abgeben, also eine Netto-Quelle sind.
Die Größenordnung der beobachteten Transportraten der drei jordanischen Stauseen ist vergleichbar mit denen von tropischen Stauseen (3,3 g CO2 m-2 Tag-1). Die CO2-Emissionsrate ist abhängig von Änderungen der Wasseroberfläche, welche durch den Betrieb der Stauseen verursacht sind. Kläranlagen entlassen eine beachtlichen Menge an CH4 (30.9±40.7 kg Jahr-1) und CO2 (0.06±0.05 Gg Jahr-1) in ihre umgebenden Flüsse und Bäche. Deren Emissionsraten sind durch diese Einleitung der Kläranlagen um 1,2-fach für CH4 oder 8,6-fach für CO2 erhöht. Unsere Ergebnisse zeigen, dass sowohl die diffusive als auch die Gasblasenemissionsrate räumlich und zeitlich variabel ist, weshalb beide Emissionsraten bei zukünftigen Studien auch in der nötigen Auflösung gemessen werden sollten.
Wir schlussfolgern, dass bei zukünftigen Emissionsmessungen und –schätzungen von Binnengewässern auch die Gewässerbewirtschaftung, die Kohlenstoffquelle von Kläranlagen und die räumliche und zeitliche Variabilität der Emissionen beachtet werden sollten.
Seit Jahrzehnten wird weltweit eine zunehmende Bedrohung der biologischen Vielfalt durch anthropogene Einflüsse beobachtet. Landschaften sind durch unterschiedliche Arten von anthro-pogenen Störungen geprägt. So vereinheitlichen großflächiger Ackerbau, die Pestizidanwen¬dung und das Entfernen von Korridoren eine Landschaft, wohingegen der Straßenbau sie fragmentiert. Beides führt zu einer Einschränkung von Habitaten und reduziert sowohl den Lebensraum als auch den Genpool der Arten, verhindert den Genfluss und verändert die funktionellen Eigenschaften. Zudem können gebietsfremde Arten in der veränderten Umwelt schneller Fuß fassen. Auf der anderen Seite machen in verschiedenen zeitlichen und räumlichen Dimensionen vorkommenden Störungen eine Landschaft auch vielfältiger, da sie Nischen kreieren, in denen verschiedene Arten koexistieren können.
Diese Studie befasst sich mit der Komplexität von Störungsregimes und dessen Auswirkungen auf die Phytodiversität. Durch die Aufnahme aller erkennbaren Störungstypen unterscheidet sie sich deutlich von anderen Studien, die sich meist nur auf einzelne Störungen konzentrieren. Die Daten stammen von drei Untersuchungsgebieten im Norden Bayerns, die unterschiedlichen Landnutzungsintensitäten unterliegen: Einer intensiven Land- und Forstwirtschaft, einer kleinräumigen und weniger intensiven Land- und Forstwirtschaft und einem aktiven Truppenübungsplatzes. Der erste Teil der Arbeit befasst sich mit der Auswirkung von Störungsregimen auf die Phytodiversität, zuerst mit Fokus auf militärische Störungen, dann im Vergleich mit den Agrarlandschaften. Der zweite Teil beleuchtet den Einfluss auf Rote-Liste Arten, auf die Verbreitung von Neophyten und Generalisten sowie auf die Homogenisierung der Landschaften. Die Analysen berücksichtigen sowohl die Landschafts- als auch die lokale Ebene.
Nicht einzelne Störungstypen spielten eine entscheidende Rolle, sondern deren Vielfalt, sowohl in der Art als auch in der räumlichen und zeitlichen Vielfalt, was sich besonders auf dem Truppenübungs¬platz mit seinem multiplen aber ungerichteten Störungsregime zeigte. Die in landwirtschaftlichen Gebieten typischen homogenen Störungsregimes, wie Pflügen, Einsäen und Düngen, führten zu reduzierten Artenzahlen. Auf lokaler Ebene überlagerte die Heterogenität der abiotischen Faktoren, deren Ursprung in rezenten und historischen Störungen liegt, die positiven Effekte der Störungen, während vor allem trockene und nährstoffarme Standorte negativen Einfluss zeigten. Wälder des Truppenübungsplatzes zeigten sich durch ihre geringere Dichte und moderate Nutzung deutlich artenreicher im Vergleich zu den landwirtschaftlichen Untersuchungsgebieten.
Die Anzahl der Rote-Liste Arten war in allen drei Untersuchungsgebieten positiv mit der Gesamtzahl der Arten korreliert, jedoch zeigte der Truppenübungsplatz eine signifikant höhere Abundanz der Arten innerhalb des gesamten Gebietes im Vergleich zu den landwirtschaftlichen Gebieten, wo seltene Arten überwiegend auf Randstandorten zu finden waren. Ebenso fanden sich dort weniger Neophyten und Generalisten und somit eine geringere Homogenisierung. Somit zeigte sich der Truppenübungsplatz als Idealgebiet aus Naturschutzsicht. Die moderat bewirtschaftete Frankenalb vereint eine hohen Artenzahl und eine Produktivität, trotzdem wird diese Art von Landschaft in der heutigen industrialisierten Zeit nicht von Bestand sein, da der Ertrag zu gering ist.
In the present study the flora and vegetation of Kakamega Forest, an East African rainforest in Western Kenya, was investigated. Kakamega Forest is highly degraded and fragmented and is an ideal model to study the anthropogenic influence on the forest inventory. The main focus was to analyse the influence of human impact on the vascular plant species composition. During five field phases in the years 2001 to 2004 a total of 19 study sites scattered over the whole forest including all fragments were investigated regarding forest structure, species composition and plant communities. The different forest sites were analysed by three different methods, phytosociological relevés, line-transect and with the variable-area transect method. The forest survey revealed about 400 taxa of vascular plant species, among them 112 trees, 62 shrubs, 58 climbers and 114 herbs. Several species are restricted to this forest in Kenya, but only one endemic species, the herb Commelina albiflora, could be discovered. About 15 species were recorded as new for Kenya and probably at least one species is new to science. Kakamega Forest is a unique mixture of Guineo-Congolian and Afromontane floral elements. About one half of the vascular plant species has its origin in the lowland forests of the Congo basin and one third originates from Afromontane habitats. The present study represents the first description of plant communities of Kakamega Forest. An analysis of different forest sites and plantations resulted in 17 different vegetation units. For the mature forest sites eleven plant communities were described. The young succession stage consists of two plant communities. Since the disturbance history and the age of the different plant communities could be estimated, their chronology was also described. An exception are the study sites within the plantations and afforested sites. The four defined vegetation units were not described as plant communities, because they are highly affected by man and do not belong to the natural succession of Kakamega Forest. Nevertheless, the regeneration potential of such forests was investigated. Due to the different succession stages the changing species composition along a disturbance gradient could be analysed. Most of Kakamega Forest consists of middle-aged secondary forest often surrounded by very young secondary forest. A true primary rainforest could not be found due the massive influence by over-exploitation. In all parts of the forest the anthropogenic influence could be observed. The forest develops towards a climax stage, but a 2 Abstract comparison with former surveys shows that the regeneration is much slower than expected. Human impact has to be avoided to allow the forest to develop into a primary-like rainforest. But several climax tree species might be missing anyway, because after the broad logging activities in the past there are not enough seed trees remaining. Species richness was highest in disturbed forest sites. A mixture of pioneer, climax and bushland species could be recorded there. Therefore, a high species richness is not a suitable indicator for forest quality. The proportion of climax species typical for Kakamega Forest would be a better measure. Compared to the main forest block the forest fragments do not lack in diversity as expected due to fragmentation processes. Instead, the only near primary forest could be recorded in Kisere, a northern fragment. The high amount of climax species and the more or less undisturbed forest structure is a result of the strict protection by the Kenya Wildlife Service and due to low logging activities. Differences in species composition between the studied forest sites are either a result of the different logging history or management regime rather than due to different edaphic or climatic conditions.
Predictive Process Monitoring setzt sich als Hilfsmittel zur Unterstützung der betrieblichen Abläufe in Unternehmen immer mehr durch Die meisten heute verfüg-baren Softwareanwendungen erfordern jedoch ein umfangreiches technisches Know-how des Betreibers und sind daher für die meisten realen Szenarien nicht geeignet. Daher wird in dieser Arbeit eine prototypische Implementierung eines Predictive Process Monitoring Dashboards in Form einer Webanwendung vorgestellt. Das System basiert auf dem von Bartmann et al. (2021) vorgestellten PPM-Camunda-Plugin und ermöglicht es dem Benutzer, auf einfache Weise Metriken, Visualisierungen zur Darstellung dieser Metriken und Dashboards, in denen die Visualisierungen angeordnet werden können, zu erstellen. Ein Usability-Test mit Testnutzern mit unterschiedlichen Computerkenntnissen wird durchgeführt, um die Benutzerfreundlichkeit der Anwendung zu bestätigen.
The role of alternative resources for pollinators and aphid predators in agricultural landscapes
(2021)
Der Verlust zahlreicher Insekten wird weitgehend in Verbindung gebracht mit dem Verlust von natürlichem und halbnatürlichem Lebensraum durch intensivierte Landnutzung. Viele Insekten liefern wichtige Ökosystemleistungen an die Landwirtschaft wie z.B. Bestäubung und Schädlingsbekämpfung. Um diese Insekten effizient auf den verbleibenden halbnatürlichen Flächen zu fördern, ist genaues Wissen über ihre Ansprüche an das Umland von Agrarflächen erforderlich. Der Fokus dieser Dissertation liegt auf der Suche nach den wichtigsten halbnatürlichen Habitattypen (Waldrand, Wiesen und halb-offene Habitate) zur Förderung von Nützlingen und Bestäubern aufgrund der Bedeutung von Nahrungsressourcen, welche sie dort nutzen. Besonderes Augenmerk liegt dabei auf Blütenressourcen und wie diese räumlich und zeitlich im Kulturland verteilt sind. Darauf basierte Ressourcenkarten versprechen eine Charakterisierung der Landschaft, welche der Relevanz für Insekten näher kommt als klassische Habitatkarten. In dieser These wurde deshalb verglichen, ob sich das Vorkommen von Wildbienen, sowie Nektar und Pollen konsumierenden Nützlingen besser mit klassischen Habitatkarten, oder mit Ressourcenkarten vorhersagen lässt und identifizierte Habitate besonderer Wichtigkeit. Bei Wildbienen wurde untersucht, inwiefern sich Präferenzen verschiedener Gruppen von Wildbienen unterscheiden und ob es zeitliche und räumliche Zusammensetzungen von Blühressourcen gibt, die besonders optimal sind. Da sich Nützlinge nebst der Nutzung von Blüten vor allem räuberisch ernähren, wurde des Weiteren deren Beutespektrum untersucht. Dazu wurde der Darminhalt von Marienkäfern mit genetischen Methoden mittels High Throughput Sequencing auf konsumierte Blattläuse analysiert.
Blütenbasierte Ressourcenkarten sagten Bienen besser voraus als klassische Habitatkarten. Der Waldrand war dabei von besonderer Bedeutung. Sowohl Flächenanteil als auch Blühangebot hatten positive Einflüsse auf Abundanz und Artenreichtum von wichtigen Kulturbestäubern und seltenen Arten. Ähnliche Muster zeigten sich für Wiesendiversität. Dabei schien besonders das frühe Blühangebot einen positiven Einfluss auf Wildbienen zu haben. Kulturen und Obstbäume verursachten im April einen Blütenpuls, der das Blühangebot vom Mai und Juni um mehr als das Zehnfache überstieg. Waldränder boten besonders Anfang Mai und im Juni ein Blühangebot, das im Verhältnis zur Fläche die weitaus höchste Dichte aufwies. Das Blühangebot von Wiesen war äusserst gering, zeigte aber die höchste Diversität, welche regelmässig über die Saison verteilt war.
Obwohl die untersuchten Nützlinge Blüten fürs Überleben benötigen, waren blütenbasierte Habitatkarten weniger geeignet, um die Nützlingsabundanz zu erklären, als herkömmliche Habitatkarten. Diese zeigten, dass Waldränder von besonderer Bedeutung für Nützlinge sind. Die Anzahl der Nützlinge wiederum führte zur Unterdrückung von Blattläusen. Die Resultate der Darmuntersuchungen zeigten zum einen, dass Marienkäfer einen relativ hohen Anteil an schädlichen Blattlausarten und Brennesselblattläusen konsumieren, zum anderen zeigen sie, dass mit Klebfallen gefangene Marienkäfer einen wesentlich breiteren Einblick in das Beutespektrum erlauben, als von Hand gesammelt. Der zu diesem Zweck entwickelte Blattlausprimer wird für kommende Studien bei der Identifizierung der Blattlausbeute von Marienkäfern hilfreich sein.
Unsere Resultate zeigen, dass Blütenkarten einen wichtigen Mehrwert für die Vorhersage von Wildbienen haben, nicht aber von Nützlingen, da für diese wohl andere Habitatfaktoren zusätzlich limitierend wirken. Der positive Einfluss von Waldrändern für unterschiedliche Gruppen von Wildbienen wie auch für Nützlinge und ihre Leistung als Schädlingsbekämpfer ist besonders hervorzuheben.
Semantic descriptions of non-textual media available on the web can be used to facilitate retrieval and presentation of media assets and documents containing them. While technologies for multimedia semantic descriptions already exist, there is as yet no formal description of a high quality multimedia ontology that is compatible with existing (semantic) web technologies. We explain the complexity of the problem using an annotation scenario. We then derive a number of requirements for specifying a formal multimedia ontology, including: compatibility with MPEG-7, embedding in foundational ontologies, and modularisation including separation of document structure from domain knowledge. We then present the developed ontology and discuss it with respect to our requirements.