Search results for "feature"
showing 10 items of 4091 documents
Machine learning for mortality analysis in patients with COVID-19
2020
This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis where the endpoint variable is the reason for hospital discharge (home or deceased). The different methods applied show the importance of variables such as age, O2 saturation at Emergency Rooms (ER), and whether the patient comes from a nursing home. In addition, biclustering is used to globally analyze the patient-drug dataset, extracting segments of patients. We highlight the validity of the classifiers developed to predict the mortality, reaching…
Exploiting Data Analytics and Deep Learning Systems to Support Pavement Maintenance Decisions
2021
Road networks are critical infrastructures within any region and it is imperative to maintain their conditions for safe and effective movement of goods and services. Road Management, therefore, plays a key role to ensure consistent efficient operation. However, significant resources are required to perform necessary maintenance activities to achieve and maintain high levels of service. Pavement maintenance can typically be very expensive and decisions are needed concerning planning and prioritizing interventions. Data are key towards enabling adequate maintenance planning but in many instances, there is limited available information especially in small or under-resourced urban road authorit…
A Curvature Based Method for Blind Mesh Visual Quality Assessment Using a General Regression Neural Network
2016
International audience; No-reference quality assessment is a challenging issue due to the non-existence of any information related to the reference and the unknown distortion type. The main goal is to design a computational method to objectively predict the human perceived quality of a distorted mesh and deal with the practical situation when the reference is not available. In this work, we design a no reference method that relies on the general regression neural network (GRNN). Our network is trained using the mean curvature which is an important perceptual feature representing the visual aspect of a 3D mesh. Relatively to the human subjective scores, the trained network successfully asses…
Robust Selective Stereo SLAM without Loop Closure and Bundle Adjustment
2013
This paper presents a novel stereo SLAM framework, where a robust loop chain matching scheme for tracking keypoints is combined with an effective frame selection strategy. The proposed approach, referred to as selective SLAM (SSLAM), relies on the observation that the error in the pose estimation propagates from the uncertainty of the three-dimensional points. This is higher for distant points, corresponding to matches with low temporal flow disparity in the images. Comparative results based on the reference KITTI evaluation framework show that SSLAM is effective and can be implemented efficiently, as it does not require any loop closure or bundle adjustment.
Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data
2022
In preparation for new-generation imaging spectrometer missions and the accompanying unprecedented inflow of hyperspectral data, optimized models are needed to generate vegetation traits routinely. Hybrid models, combining radiative transfer models with machine learning algorithms, are preferred, however, dealing with spectral collinearity imposes an additional challenge. In this study, we analyzed two spectral dimensionality reduction methods: principal component analysis (PCA) and band ranking (BR), embedded in a hybrid workflow for the retrieval of specific leaf area (SLA), leaf area index (LAI), canopy water content (CWC), canopy chlorophyll content (CCC), the fraction of absorbed photo…
Source Mechanisms of Laboratory Earthquakes During Fault Nucleation and Formation
2021
Identifying deformation and pre-failure mechanisms preceding faulting is key for fault mechanics and for interpreting precursors to fault rupture. This study presents the results of a new and robust derivation of first motion polarity focal mechanism solutions (FMS) applied to acoustic emission (AE). FMS are solved using a least squares minimization of the fit between projected polarity measurements and the deviatoric stress field induced by dilatational (T-type), shearing (S-type), and compressional (C-type) sources. 4 × 10 cm cylindrical samples of Alzo Granite (AG, porosity <1%) and Darley Dale Sandstone (DDS, porosity ≈14%) underwent conventional triaxial tests in order to investigat…
Stilistiskie izteiksmes līdzekļi pārtikas produktu reklāmas plakātos
2021
Bakalaura darba tiek pētīti stilistiski līdzekļi ar pārtiku saistītās drukas reklāmās. Reklāma ir īpaši nozīmīga un izplatīta mūsdienu sabiedrībā, tāpat kā nepieciešamība pēc zinātniskiem pētījumiem un izpratne par tās ietekmes sfērām, kas lielā mērā nosaka reklāmas tekstu lingvistiskās un stilistiskās iezīmes. Darbā tiek pētīti stilistiski pārtikas produktu reklāmas līdzekļi, ko izmanto vadošie starptautiskie pārtikas mazumtirgotāji, kas darbojas Latvijas tirgū. Pētījuma rezultāti tika apkopoti un analizēti, izmantojot nejaušas izlases metodi materiāla atlasei un strukturālās analīzes metodi, kas ļāva šī darba autoram veikt secinājumus, kas pierādīja, ka stilistiskie līdzekļi tiek plaši iz…
Veronico beccabungae-callitrichetum stagnalis (Oberd. 1957) Müller 1962, a plant association new to Poland - Quality of habitat
2011
The paper presents a community of water plants that is new to Poland, <em>Veronico beccabungae-Callitrichetum</em> stagnalis (Oberd. 1957) Müller 1962. This community belongs to the class <em>Potametea</em>. It was discovered in the village of Odrowąż near the town of Krapkowice in Silesia (SW Poland). <em>Veronico beccabungae-Callitrichetum stagnalis</em> in Poland occurs within an irregularly shaped shallow underwater spring, located in the distal part of the Oder River’s flood terrace. This plant community covered 0.2 ha in 2008. <em>Callitriche stagnalis</em> predominated in this community. Species such as <em>Callitriche hamulata<…
Insights on Hydrothermal‐Magmatic Interactions and Eruptive Processes at Poás Volcano (Costa Rica) From High‐Frequency Gas Monitoring and Drone Measu…
2019
Texto completo del documento Identification of unambiguous signals of volcanic unrest is crucial in hazard assessment. Processes leading to phreatic and phreatomagmatic eruptions remain poorly understood, inhibiting effective eruption forecasting. Our 5‐year gas record from Poás volcano, combined with geophysical data, reveals systematic behavior associated with hydrothermal‐magmatic eruptions. Three eruptive episodes are covered, each with distinct geochemical and geophysical characteristics. Periods with larger eruptions tend to be associated with stronger excursions in monitoring data, particularly in SO2/CO2 and SO2 flux. The explosive 2017 phreatomagmatic eruption was the largest erupt…
BVLOS UAS Operations in Highly-Turbulent Volcanic Plumes.
2020
Long-range, high-altitude Unoccupied Aerial System (UAS) operations now enable in-situ measurements of volcanic gas chemistry at globally-significant active volcanoes. However, the extreme environments encountered within volcanic plumes present significant challenges for both air frame development and in-flight control. As part of a multi-disciplinary field deployment in May 2019, we flew fixed wing UAS Beyond Visual Line of Sight (BVLOS) over Manam volcano, Papua New Guinea, to measure real-time gas concentrations within the volcanic plume. By integrating aerial gas measurements with ground- and satellite-based sensors, our aim was to collect data that would constrain the emission rate of …