5,839 research outputs found
REMOTELY SENSED IMAGE FAST CLASSIFICATION AND SMART THEMATIC MAP PRODUCTION
Abstract. Apps available for Smartphone, as well as software for GNSS/GIS devices, permit to easily mapping the localization and shape of an area by acquiring the vertices coordinates of its contour. This option is useful for remote sensing classification, supporting the detection of representative sample sites of a known cover type to use for algorithm training or to test classification results. This article aims to analyse the possibility to produce smart maps from remotely sensed image classification in rapid way: the attention is focalized on different methods that are compared to identify fast and accurate procedure for producing up-to-date and reliable maps. Landsat 8 OLI multispectral images of northern Sicily (Italy) are submitted to various classification algorithms to distinguish water, bare soil and vegetation. The resulting map is useful for many purposes: appropriately inserted in a larger database aimed at representing the situation in a space-time evolutionary scenario, it is suitable whenever you want to capture the variation induced in a scene, e.g. burnt areas identification, vegetated areas definition for tourist-recreational purposes, etc. Particularly, pixel-based classification approaches are preferred, and experiments are carried out using unsupervised (k-means), vegetation index (NDVI, Normalized Difference Vegetation Index), supervised (minimum distance, maximum likelihood) methods. Using test sites, confusion matrix is built for each method, and quality indices are calculated to compare the results. Experiments demonstrate that NDVI submitted to k-means algorithm allows the best performance for distinguishing not only vegetation areas but also water bodies and bare soils. The resulting thematic map is converted for web publishing
Remotely sensed image fast classification and smart thematic map production
Apps available for Smartphone, as well as software for GNSS/GIS devices, permit to easily mapping the localization and shape of an area by acquiring the vertices coordinates of its contour. This option is useful for remote sensing classification, supporting the detection of representative sample sites of a known cover type to use for algorithm training or to test classification results. This article aims to analyse the possibility to produce smart maps from remotely sensed image classification in rapid way: The attention is focalized on different methods that are compared to identify fast and accurate procedure for producing up-To-date and reliable maps. Landsat 8 OLI multispectral images of northern Sicily (Italy) are submitted to various classification algorithms to distinguish water, bare soil and vegetation. The resulting map is useful for many purposes: Appropriately inserted in a larger database aimed at representing the situation in a space-Time evolutionary scenario, it is suitable whenever you want to capture the variation induced in a scene, e.g. burnt areas identification, vegetated areas definition for tourist-recreational purposes, etc. Particularly, pixel-based classification approaches are preferred, and experiments are carried out using unsupervised (k-means), vegetation index (NDVI, Normalized Difference Vegetation Index), supervised (minimum distance, maximum likelihood) methods. Using test sites, confusion matrix is built for each method, and quality indices are calculated to compare the results. Experiments demonstrate that NDVI submitted to k-means algorithm allows the best performance for distinguishing not only vegetation areas but also water bodies and bare soils. The resulting thematic map is converted for web publishing
Quality improvement activities associated with organisational capacity in general practice
Copyright © 2007 Australian College of General Practitioners Copyright to Australian Family Physician. Reproduced with permission. Permission to reproduce must be sought from the publisher, The Royal Australian College of General Practitioners.BACKGROUND Clinical audit is recognised worldwide as a useful tool for quality improvement. METHODS A feedback report profiling capacity for chronic disease care was sent to 97 general practices. These practices were invited to complete a clinical audit activity based on that feedback. Data were analysed quantitatively and case studies were developed based on the free text responses. RESULTS Eighty-two (33%) of 247 general practitioners participated in the clinical audit process, representing 57 (59%) of 97 general practices. From the data in their feedback report, 37 (65%) of the 57 practices recognised the area most in need of improvement. This was most likely where the need related to clinical practice or teamwork, and least likely where the need related to linkages with other services, and business and finance. Only 25 practices (46%) developed an action plan related to their recognised area for improvement, and 22 (39%) practices implemented their chosen activity. Participating GPs judged that change activity focused on teamwork was most successful. DISCUSSION The clinical audit process offered participating GPs and practices an opportunity to reflect on their performance across a number of key areas and to implement change to enhance the practice’s capacity for quality chronic disease care. The relationship between need and action was weak, suggesting a need for greater support to overcome barriers.Cheryl Amoroso, Judy Proudfoot, Tanya Bubner, Edward Swan, Paola Espinel, Christopher Barton, Justin Beilby and Mark Harri
Oxidative DNA damage bypass in Arabidopsis thaliana requires DNA polymerase λ and proliferating cell nuclear antigen 2
The oxidized base 7,8-oxoguanine (8-oxo-G) is the most common DNA lesion generated by reactive oxygen species. This
lesion is highly mutagenic due to the frequent misincorporation of A opposite 8-oxo-G during DNA replication. In
mammalian cells, the DNA polymerase (pol) family X enzyme DNA pol l catalyzes the correct incorporation of C opposite
8-oxo-G, together with the auxiliary factor proliferating cell nuclear antigen (PCNA). Here, we show that Arabidopsis thaliana
DNA pol l, the only member of the X family in plants, is as efficient in performing error-free translesion synthesis past
8-oxo-G as its mammalian homolog. Arabidopsis, in contrast with animal cells, possesses two genes for PCNA. Using in
vitro and in vivo approaches, we observed that PCNA2, but not PCNA1, physically interacts with DNA pol l, enhancing its
fidelity and efficiency in translesion synthesis. The levels of DNA pol l in transgenic plantlets characterized by overexpression
or silencing of Arabidopsis POLL correlate with the ability of cell extracts to perform error-free translesion synthesis. The important role of DNA pol l is corroborated by the observation that the promoter of POLL is activated by UV
and that both overexpressing and silenced plants show altered growth phenotypes
On the Comparison of Two Vehicular Safety Systems in Realistic Highway Scenarios
Abstract The application of wireless VANET technology to accident warning systems is gaining an increasing interest. These systems can significantly increase the safety of daily driving and are based on a technology that is steadily becoming mature. We present an experimental comparison between two effective approaches that cope with realistic scenarios. Both rapidly broadcast alert messages throughout platoons of vehicles, and are based on wireless vehicle-to-vehicle (V2V) communications. However, with one approach an alert message propagates through the farthest relay at each hop, whereas with the other it propagatesusing the farthest spanning relay (i.e., the relay that can retransmit farthest away an alert message). With this study we will see retransmitting through the farthest spanning relay at each hop can improve the performance by a factor of two in terms of propagation delay, in comparison to choosing the farthest relay
Psychological counseling in the Italian academic context: Expected needs, activities, and target population in a large sample of students
University psychological counseling (UPC) is receiving growing attention as a means to promote mental health and academic success among young adults and prevent irregular attendance and dropout. However, thus far, little effort has been directed towards the implementation of services attuned to students' expectations and needs. This work intends to contribute to the existing literature on this topic, by exploring the perceptions of UPC among a population of 39,277 students attending one of the largest universities in the South of Italy. Almost half of the total population correctly identified the UPC target population as university students, and about one third correctly expected personal distress to be the main need that UPC should target. However, a large percentage did not have a clear idea about UPC target needs, activities, and population. When two specific student subsamples were analyzed using a person-centered analysis, namely (i) those who expressed their intention to use the counseling service but had not yet done so and (ii) those who had already used it, the first subsample clustered into two groups, characterized by an "emotional" and a "psychopathological" focus, respectively, while the second subsample clustered into three groups with a "clinical", "socioemotional", and "learning" focus, respectively. This result shows a somewhat more "superficial" and "common" representation of UPC in the first subsample and a more "articulated" and "flexible" vision in the second subsample. Taken together, these findings suggest that UPC services could adopt "student-centered" strategies to both identify and reach wider audiences and specific student subgroups. Recommended strategies include robust communication campaigns to help students develop a differentiated perception of the available and diverse academic services, and the involvement of active students to remove the barriers of embarrassment and shame often linked to the stigma of using mental health services
A primer on machine learning techniques for genomic applications
High throughput sequencing technologies have enabled the study of complex biological aspects at single nucleotide resolution, opening the big data era. The analysis of large volumes of heterogeneous “omic” data, however, requires novel and efficient computational algorithms based on the paradigm of Artificial Intelligence. In the present review, we introduce and describe the most common machine learning methodologies, and lately deep learning, applied to a variety of genomics tasks, trying to emphasize capabilities, strengths and limitations through a simple and intuitive language. We highlight the power of the machine learning approach in handling big data by means of a real life example, and underline how described methods could be relevant in all cases in which large amounts of multimodal genomic data are available
Un enfoque novedoso en la enseñanza agropecuaria: de la Tecnicatura en Producción Vegetal Orgánica en la Licenciatura en Agroecología de la Universidad Nacional de Río Negro en El Bolsón, provincia de Río Negro, República Argentina
La Tecnicatura en Producción Vegetal Orgánica que la Facultad de Agronomía de la Universidad de Buenos Aires (FAUBA) dictó en la localidad de El Bolsón, Provincia de Río Negro, nació por una demanda local. En ese dictado estuvieron involucradas instituciones, productores y profesionales locales con la articulación de la Fundación Cooperar (COOPETEL). Se procuró que la propuesta respondiese a la problemática productiva de la Comarca Andina del Paralelo 42, en especial para la producción intensiva orgánica.
Cumplido su ciclo a término, esa carrera dejó una impronta local que fue retomada con la creación en el año 2007 de la Universidad Nacional de Río Negro (UNRN). Así, a partir de 2009 se reinició el dictado de esa carrera y el desarrollo de la misma fue evidenciando la necesidad de avanzar en estudios de grado completos en el área. Así se llegó a desarrollar la propuesta de la Licenciatura en Agroecología (primera carrera de grado en esta área en el país) que actualmente se está dictando con un enfoque diferente para las ciencias agropecuarias.The Organic Crop Production Technician in the Faculty of Agronomy of the University of Buenos Aires (FAUBA) issued in the town of El Bolson, Province of Rio Negro, born by local demand. In that dictated institutions were involved, producers and local professionals with the joint Cooperate Foundation (COOPETEL). That the proposal sought to production problems answered the Andean Region of Parallel 42, especially for organic intensive production. Its course to the end, that race left a local imprint was revived with the creation in 2007 of the National University of Rio Black (UNRN). Thus, from 2009 the issuance of the race and the development of it was evident the need to advance in studies of full degree in the area was restarted. This led to developing the proposed degree in Agroecology (first undergraduate program in this area in the country) currently is teaching a different approach to the agricultural sciences.Eje A5: Sistemas de conocimientoFacultad de Ciencias Agrarias y Forestale
Un enfoque novedoso en la enseñanza agropecuaria: de la Tecnicatura en Producción Vegetal Orgánica en la Licenciatura en Agroecología de la Universidad Nacional de Río Negro en El Bolsón, provincia de Río Negro, República Argentina
La Tecnicatura en Producción Vegetal Orgánica que la Facultad de Agronomía de la Universidad de Buenos Aires (FAUBA) dictó en la localidad de El Bolsón, Provincia de Río Negro, nació por una demanda local. En ese dictado estuvieron involucradas instituciones, productores y profesionales locales con la articulación de la Fundación Cooperar (COOPETEL). Se procuró que la propuesta respondiese a la problemática productiva de la Comarca Andina del Paralelo 42, en especial para la producción intensiva orgánica.
Cumplido su ciclo a término, esa carrera dejó una impronta local que fue retomada con la creación en el año 2007 de la Universidad Nacional de Río Negro (UNRN). Así, a partir de 2009 se reinició el dictado de esa carrera y el desarrollo de la misma fue evidenciando la necesidad de avanzar en estudios de grado completos en el área. Así se llegó a desarrollar la propuesta de la Licenciatura en Agroecología (primera carrera de grado en esta área en el país) que actualmente se está dictando con un enfoque diferente para las ciencias agropecuarias.The Organic Crop Production Technician in the Faculty of Agronomy of the University of Buenos Aires (FAUBA) issued in the town of El Bolson, Province of Rio Negro, born by local demand. In that dictated institutions were involved, producers and local professionals with the joint Cooperate Foundation (COOPETEL). That the proposal sought to production problems answered the Andean Region of Parallel 42, especially for organic intensive production. Its course to the end, that race left a local imprint was revived with the creation in 2007 of the National University of Rio Black (UNRN). Thus, from 2009 the issuance of the race and the development of it was evident the need to advance in studies of full degree in the area was restarted. This led to developing the proposed degree in Agroecology (first undergraduate program in this area in the country) currently is teaching a different approach to the agricultural sciences.Eje A5: Sistemas de conocimientoFacultad de Ciencias Agrarias y Forestale
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