892 resultados para objectrecognition ECO-Feature parallelismo OpenCV python_multiprocessing
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Il contributo ripercorre la relazione uomo-castagno partendo dalle ultime glaciazioni per arrivare ai giorni nostri, con una crescente attenzione per le contrade insubriche, dove la castanicoltura raggiunse livelli straordinari di sviluppo. Dopo una sintesi critica sui primi indizi di coltivazione, si esamina la castanicoltura nel mondo greco e romano fino all’introduzione della coltivazione del castagno nell’area insubrica. Particolare attenzione è riservata al periodo aureo tardomedievale della castanicoltura nella Svizzera italiana, comprovato con dati linguistici, con l’analisi dei sistemi produttivi (composizione varietale, tecniche di essiccazione) e delle consuetudini locali. Si indagano in seguito le ragioni e le tappe storiche del declino della castanicoltura tradizionale. Si conclude discutendo la situazione attuale e le prospettive future dei castagneti a Sud delle Alpi, confrontati con alcuni problemi incalzanti come l’invecchiamento delle ceppaie nei cedui abbandonati e la comparsa di un insidioso parassita, il cinipide galligeno.
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One of the current challenges in evolutionary ecology is understanding the long-term persistence of contemporary-evolving predator–prey interactions across space and time. To address this, we developed an extension of a multi-locus, multi-trait eco-evolutionary individual-based model that incorporates several interacting species in explicit landscapes. We simulated eco-evolutionary dynamics of multiple species food webs with different degrees of connectance across soil-moisture islands. A broad set of parameter combinations led to the local extinction of species, but some species persisted, and this was associated with (1) high connectance and omnivory and (2) ongoing evolution, due to multi-trait genetic variability of the embedded species. Furthermore, persistence was highest at intermediate island distances, likely because of a balance between predation-induced extinction (strongest at short island distances) and the coupling of island diversity by top predators, which by travelling among islands exert global top-down control of biodiversity. In the simulations with high genetic variation, we also found widespread trait evolutionary changes indicative of eco-evolutionary dynamics. We discuss how the ever-increasing computing power and high-resolution data availability will soon allow researchers to start bridging the in vivo–in silico gap.
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Strassenlärm ist diejenige Verkehrslärmquelle, die am meisten Menschen belastet. Veränderungen im Handeln der Lärmverursachenden stellen eine vielversprechende Möglichkeit dar, bisherige Lärmbekämpfungsmassnahmen zu ergänzen. Die vorliegende Studie, welche vom Schweizerischen Bundesamt für Umwelt und dem Ministerium für Umwelt, Landwirtschaft, Ernährung, Weinbau und Forsten Rheinland-Pfalz gefördert wurde, widmete sich der Frage, wie die Förderung eines leisen Fahrstils zur Bekämpfung von Strassenlärm nutzbar gemacht werden kann. Hierzu erarbeiteten wir ein Interventionsprogramm zur Förderung eines leisen Fahrstils, welches in Zusammenarbeit mit Mitarbeitenden einer Stadtverwaltung umgesetzt und evaluiert wurde. Die Ergebnisse dieser Studie deuten darauf hin, dass es sich lohnt, einen leisen Fahrstil im Rahmen der Lärmbekämpfung zu fördern; während der mehrwöchigen Durchführung des Programms konnte eine Reduktion der durchschnittlichen Drehzahl, des durchschnittlichen Treibstoffverbrauchs, des gemittelten Summenpegels des Motorengeräuschs wie auch der prozentualen Fahrzeit mit Motorengeräuschen über 60dB(A) beobachtet werden. Befragungen der TeilnehmerInnen gaben zudem Auskunft über die diesen Veränderungen zu Grunde liegende Motivstruktur. Wir präsentieren in diesem Bericht sowohl eine detaillierte Darstellung des verwendeten Interventionsprogramms, des Vorgehens bei dessen Evaluation, sowie die entsprechenden Auswertungen. Wir hoffen, dass durch diese Studie zukünftige Programme zur Förderung eines leisen Fahrstils angeregt werden und von unseren Ergebnissen profitieren können.
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In this work, a method that synchronizes two video sequences is proposed. Unlike previous methods, which require the existence of correspondences between features tracked in the two sequences, and/or that the cameras are static or jointly moving, the proposed approach does not impose any of these constraints. It works when the cameras move independently, even if different features are tracked in the two sequences. The assumptions underlying the proposed strategy are that the intrinsic parameters of the cameras are known and that two rigid objects, with independent motions on the scene, are visible in both sequences. The relative motion between these objects is used as clue for the synchronization. The extrinsic parameters of the cameras are assumed to be unknown. A new synchronization algorithm for static or jointly moving cameras that see (possibly) different parts of a common rigidly moving object is also proposed. Proof-of-concept experiments that illustrate the performance of these methods are presented, as well as a comparison with a state-of-the-art approach.
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In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.
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Eco-driving has well-known positive effects on fuel economy and greenhouse-gas emissions. Moreover, eco-driving reduces road-traffic noise, which is a serious threat to the health and well-being of many people. We investigated the psychological predictors of the adoption of eco-driving from the perspective of road-traffic noise abatement. The data came from 890 car drivers who participated in a longitudinal survey over four months. Specifically, we tested the effects of the intention to prevent road-traffic noise, variables derived from the theory of planned behavior (social norm, perceived behavioral control, and attitude), and variables derived from the health action process approach (implementation intention, maintenance self-efficacy, and action control) on the intention to practice eco-driving and on eco-driving behavior. The intention to prevent road-traffic noise was not linked to the intention to practice eco-driving. The strongest predictors of the intention to practice eco-driving were attitude and perceived behavioral control. The strongest predictor of eco-driving behavior was action control. The link between behavioral intention and behavior was weak, indicating that drivers have difficulties putting their intention to practice eco-driving into action. Therefore, intervention efforts should directly address and support the transition from intention to behavior. This could be accomplished by providing reminders, which help to maintain behavioral intention, and by providing behavior feedback, which helps car drivers to monitor their behavior.
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Der diesjährige 10. Trockenrasen-Sonderteil von Tuexenia beginnt mit einem Bericht über die aktuellen Aktivitäten der European Dry Grassland Group (EDGG). Zunächst geben wir einen Überblick über die Entwicklung der Mitgliederzahl. Dann berichten wir vom letzten European Dry Grassland Meeting in Tula (Russland, 2014) und vom letzten European Dry Grassland Field Workshop in Navarra (Spanien, 2014) und informieren über künftige Veranstaltungen der EDGG. Anschließend erläutern wir die Publikationsaktivitäten der EDGG. Im zweiten Teil des Editorials geben wir eine Einführung zu den fünf Artikeln des diesjährigen Trockenrasen-Sonderteils. Zwei Artikel beschäftigen sich mit der Syntaxonomie von Trockenrasen in Ost- bzw. Südosteuropa: der eine präsentiert erstmalig eine Gesamtklassifikation der Trockenrasengesellschaften Serbiens und des Kosovo während der andere Originalaufnahmen sub-montaner Graslandgesellschaften aus den bislang kaum untersuchten ukrainischen Ostkarpaten analysiert. Zwei weitere Artikel behandeln Trockenrasen-Feuchtwiesen-Komplexe im ungarischen Tiefland: Der eine behandelt den Einfluss der Landnutzung auf die Phytodiversität von Steppen und Feuchtwiesen, der andere den Einfluss von Niederschlagsschwankungen in einem Zeitraum von drei Jahren auf die Ausbildung salzbeeinflusster Steppen-Feuchtwiesen-Komplexe. Der fünfte Artikel analysiert landnutzungsbedingte Veränderungen des Graslands des Tsentralen-Balkan-Nationalparks in Bulgarien über einen Zeitraum von 65 Jahren
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Road-traffic noise impairs the well-being and health of many people. Motivating car drivers to voluntarily adopt a low-noise driving style (i.e., eco-driving) contributes to the reduction of road-traffic noise, complementary to requirements, bans, and laws. In a field study with employees of a municipality (N = 88), we investigated the effects of an intervention on car drivers’ motivation to prevent road-traffic noise, motivation to practice eco-driving, and driving behavior. The intervention consisted of a leaflet intended to enhance participants’ motivation, a practical eco-driving course, and weekly driving-performance feedbacks. We used a switching-replications design with two intervention groups. In both groups, eco-driving behavior was significantly strengthened by the intervention. The effects on the motivational variables were significant in only one of the groups (however, it should be noted that the average motivation was already relatively high before the intervention). For one of the groups, the study design allowed testing for the effects at an additional follow-up assessment (4 months after the intervention). The results showed that the intervention effect on driving behavior held across this period. The findings of the present research suggest that it is possible to improve car driver’s behavior with regard to a low-noise driving style.
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Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.
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Differences in how organisms modify their environment can evolve rapidly and might influence adaptive population divergence [1, 2]. In a common garden experiment in aquatic mesocosms, we found that adult stickleback from a recently diverged pair of lake and stream populations had contrasting effects on ecosystem metrics. These modifications were caused by both genetic and plastic differences between populations and were sometimes comparable in magnitude to those caused by the presence/ absence of stickleback. Lake and streamfish differentially affected the biomass of zooplankton and phytoplankton, the concentration of phosphorus, and the abundance of several prey (e.g., copepods) and non-prey (e.g., cyanobacteria) species. The adult mediated effects on mesocosm ecosystems influenced the survival and growth of a subsequent generation of juvenile stickleback reared in the same mesocosms. The prior presence of adults decreased the overall growth rate of juveniles, and the prior presence of stream adults lowered overall juvenile survival. Among the survivors, lake juveniles grew faster than co-occurring stream juveniles, except in mesocosm ecosystems previously modified by adult lake fish that were reared on plankton. Overall, our results provide evidence for reciprocal interactions between ecosystem dynamics and evolutionary change (i.e., eco-evolutionary feedbacks) in the early stages of adaptive population divergence.
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We present a novel algorithm to reconstruct high-quality images from sampled pixels and gradients in gradient-domain rendering. Our approach extends screened Poisson reconstruction by adding additional regularization constraints. Our key idea is to exploit local patches in feature images, which contain per-pixels normals, textures, position, etc., to formulate these constraints. We describe a GPU implementation of our approach that runs on the order of seconds on megapixel images. We demonstrate a significant improvement in image quality over screened Poisson reconstruction under the L1 norm. Because we adapt the regularization constraints to the noise level in the input, our algorithm is consistent and converges to the ground truth.