1,220 research outputs found

    Joint DAMA-TCP protocol optimization through multiple cross layer interactions in DVB RCS scenario

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    Two aspects of DVB-RCS standard can worsen performance of TCP data connections: DAMA access scheme, since it introduces additional and variable delay to the already significant propagation delay and the adoption of Adaptive Coding on the return link to maximize bandwidth efficiency to face variable weather conditions, because it results in variable bandwidth allocation. Both aspects can severely impact TCP performance, especially for what concerns now adaptation to varying channel conditions and channel usage efficiency. To optimize performance, in this paper cross-layer signaling among transport, MAC and physical layers of a DVB-RCS system is addressed. In particular MAC-TCP cross-layer is analyzed through the use of NS2 network simulator, showing the possible benefit in a DVB-RCS scenario

    Assessing the capabilities of high-resolution spectral, altimetric, and textural descriptors for mapping the status of citrus parcels

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    [EN] Agricultural land abandonment is an increasing phenomenon around the world with relevant environmental and socio-economic implications. In the European Union about 11 % of agricultural land is at high risk of abandonment. The Comunitat Valenciana region (Spain) is the most important citrus producer in Europe suffering from this problem. Identifying the status of citrus crops at the parcel level is essential for policymakers in agriculture. This work assessed the use of WorldView-3 data, Very High-Resolution Airborne Images, and Structure from Motion point clouds to identify the status of citrus parcels using two machine learning algorithms: Random Forest and Support Vector Machines. Different analyses involving combinations of the three data sources were carried out to assess the impact on classification accuracy. The results showed the high potential of airborne imagery (OA ¿ 0.967) and WorldView-3 (OA ¿ 0.936) to detect parcel status using a single image. The SfM data showed a lower potential (OA ¿ 0.825). Adding SfM point cloud to the multispectral information produced small improvements (0.4¿2.0 %) in classification accuracy. The class separability analysis showed the importance of WV-3 SWIR bands to detect abandoned parcels as they produce more spectral separability over the productive parcels in the 1570 nm ¿ 2330 nm spectrum. The results also show the importance of GLCM texture features extracted from sub-metric images due to their ability to model spatial planting patterns typical of fruit cropsThis research was funded by regional government of Spain, Generalitat Valenciana, within the framework of the research project AICO/2020/246. Funding for open access charge: CRUE-Universitat Politecnica de Valencia.Morell-Monzó, S.; Estornell Cremades, J.; Sebastiá-Frasquet, M. (2023). Assessing the capabilities of high-resolution spectral, altimetric, and textural descriptors for mapping the status of citrus parcels. Computers and Electronics in Agriculture. 204:1-11. https://doi.org/10.1016/j.compag.2022.10750411120

    Comparison of Sentinel-2 and High-Resolution Imagery for Mapping Land Abandonment in Fragmented Areas

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    [EN] Agricultural land abandonment is an important environmental issue in Europe. The proper management of agricultural areas has important implications for ecosystem services (food production, biodiversity, climate regulation and the landscape). In the coming years, an increase of abandoned areas is expected due to socio-economic changes. The identification and quantification of abandoned agricultural plots is key for monitoring this process and for applying management measures. The Valencian Region (Spain) is an important fruit and vegetable producing area in Europe, and it has the most important citrus industry. However, this agricultural sector is highly threatened by diverse factors, which have accelerated land abandonment. Landsat and MODIS satellite images have been used to map land abandonment. However, these images do not give good results in areas with high spatial fragmentation and small-sized agricultural plots. Sentinel-2 and airborne imagery shows unexplored potential to overcome this thanks to higher spatial resolutions. In this work, three models were compared for mapping abandoned plots using Sentinel-2 with 10 m bands, Sentinel-2 with 10 m and 20 m bands, and airborne imagery with 1 m visible and near-infrared bands. A pixel-based classification approach was used, applying the Random Forests algorithm. The algorithm was trained with 144 plots and 100 decision trees. The results were validated using the hold-out method with 96 independent plots. The most accurate map was obtained using airborne images, the Enhanced Vegetation Index (EVI) and Thiam's Transformed Vegetation Index (TTVI), with an overall accuracy of 88.5%. The map generated from Sentinel-2 images (10 m bands and the EVI and TTVI spectral indices) had an overall accuracy of 77.1%. Adding 20 m Sentinel-2 bands and the Normalized Difference Moisture Index (NDMI) did not improve the classification accuracy. According to the most accurate map, 4310 abandoned plots were detected in our study area, representing 32.5% of its agricultural surface. The proposed methodology proved to be useful for mapping citrus in highly fragmented areas, and it can be adapted to other crops.Morell-Monzó, S.; Estornell Cremades, J.; Sebastiá-Frasquet, M. (2020). Comparison of Sentinel-2 and High-Resolution Imagery for Mapping Land Abandonment in Fragmented Areas. Remote Sensing. 12(12):1-18. https://doi.org/10.3390/rs12122062S1181212MacDonald, D., Crabtree, J. ., Wiesinger, G., Dax, T., Stamou, N., Fleury, P., … Gibon, A. (2000). Agricultural abandonment in mountain areas of Europe: Environmental consequences and policy response. Journal of Environmental Management, 59(1), 47-69. doi:10.1006/jema.1999.0335Kosmas, C., Kairis, O., Karavitis, C., Acikalin, S., Alcalá, M., Alfama, P., … Solé-Benet, A. (2015). An exploratory analysis of land abandonment drivers in areas prone to desertification. 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    Land Use Classification of VHR Images for Mapping Small-Sized Abandoned Citrus Plots by Using Spectral and Textural Information

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    [EN] Agricultural land abandonment is an increasing problem in Europe. The Comunitat Valenciana Region (Spain) is one of the most important citrus producers in Europe suffering this problem. This region characterizes by small sized citrus plots and high spatial fragmentation which makes necessary to use Very High-Resolution images to detect abandoned plots. In this paper spectral and Gray Level Co-Occurrence Matrix (GLCM)-based textural information derived from the Normalized Difference Vegetation Index (NDVI) are used to map abandoned citrus plots in Oliva municipality (eastern Spain). The proposed methodology is based on three general steps: (a) extraction of spectral and textural features from the image, (b) pixel-based classification of the image using the Random Forest algorithm, and (c) assignment of a single value per plot by majority voting. The best results were obtained when extracting the texture features with a 9 x 9 window size and the Random Forest model showed convergence around 100 decision trees. Cross-validation of the model showed an overall accuracy of the pixel-based classification of 87% and an overall accuracy of the plot-based classification of 95%. All the variables used are statistically significant for the classification, however the most important were contrast, dissimilarity, NIR band (720 nm), and blue band (620 nm). According to our results, 31% of the plots classified as citrus in Oliva by current methodology are abandoned. This is very important to avoid overestimating crop yield calculations by public administrations. The model was applied successfully outside the main study area (Oliva municipality); with a slightly lower accuracy (92%). This research provides a new approach to map small agricultural plots, especially to detect land abandonment in woody evergreen crops that have been little studied until now.This research was funded by regional government of Spain, Generalitat Valenciana, within the framework of the research project AICO/2020/246 and the APC was also funded by the research project AICO/2020/246.Morell-Monzó, S.; Sebastiá-Frasquet, M.; Estornell Cremades, J. (2021). Land Use Classification of VHR Images for Mapping Small-Sized Abandoned Citrus Plots by Using Spectral and Textural Information. Remote Sensing. 13(4):1-18. https://doi.org/10.3390/rs13040681S11813

    Assessing physical activity in people with mental illness: 23-country reliability and validity of the simple physical activity questionnaire (SIMPAQ)

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    BACKGROUND Physical inactivity is a key contributor to the global burden of disease and disproportionately impacts the wellbeing of people experiencing mental illness. Increases in physical activity are associated with improvements in symptoms of mental illness and reduction in cardiometabolic risk. Reliable and valid clinical tools that assess physical activity would improve evaluation of intervention studies that aim to increase physical activity and reduce sedentary behaviour in people living with mental illness. METHODS The five-item Simple Physical Activity Questionnaire (SIMPAQ) was developed by a multidisciplinary, international working group as a clinical tool to assess physical activity and sedentary behaviour in people living with mental illness. Patients with a DSM or ICD mental illness diagnoses were recruited and completed the SIMPAQ on two occasions, one week apart. Participants wore an Actigraph accelerometer and completed brief cognitive and clinical assessments. RESULTS Evidence of SIMPAQ validity was assessed against accelerometer-derived measures of physical activity. Data were obtained from 1010 participants. The SIMPAQ had good test-retest reliability. Correlations for moderate-vigorous physical activity was comparable to studies conducted in general population samples. Evidence of validity for the sedentary behaviour item was poor. An alternative method to calculate sedentary behaviour had stronger evidence of validity. This alternative method is recommended for use in future studies employing the SIMPAQ. CONCLUSIONS The SIMPAQ is a brief measure of physical activity and sedentary behaviour that can be reliably and validly administered by health professionals

    Silicon Encapsulated Carbon Nanotubes

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    A dual stage process of depositing bamboo-like carbon nanotubes (BCNTs) by hot filament chemical vapor deposition (HFCVD) and coating Si using Radio frequency sputtering (RFS) technique. The films were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and electron field emission studies (EFE). SEM results suggest a dense network of homogeneous silicon-coated BCNTs. From the comprehensive analysis of the results provided by these techniques emerges the picture of Si encapsulated BCNTs

    The Gas Transfer through Polar Sea Ice Experiment: Insights into the Rates and Pathways that Determine Geochemical Fluxes

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    Sea ice is a defining feature of the polar marine environment. It is a critical domain for marine biota and it regulates ocean-atmosphere exchange, including the exchange of greenhouse gases such as CO2 and CH4. In this study, we determined the rates and pathways that govern gas transport through a mixed sea ice cover. N2O, SF6, 3He, 4He, and Ne were used as gas tracers of the exchange processes that take place at the ice-water and air-water interfaces in a laboratory sea ice experiment. Observation of the changes in gas concentrations during freezing revealed that He is indeed more soluble in ice than in water; Ne is less soluble in ice, and the larger gases (N2O and SF6) are mostly excluded during the freezing process. Model estimates of gas diffusion through ice were calibrated using measurements of bulk gas content in ice cores, yielding gas transfer velocity through ice (kice) of ∼5 × 10−4 m d−1. In comparison, the effective air-sea gas transfer velocities (keff) ranged up to 0.33 m d−1 providing further evidence that very little mixed-layer ventilation takes place via gas diffusion through columnar sea ice. However, this ventilation is distinct from air-ice gas fluxes driven by sea ice biogeochemistry. The magnitude of keff showed a clear increasing trend with wind speed and current velocity beneath the ice, as well as the combination of the two. This result indicates that gas transfer cannot be uniquely predicted by wind speed alone in the presence of sea ice
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